Dec 10, 2007 - taking branch lines can be implemented in a compressed pipe net work. However further work has to be carried out to estimate the energy ...
i
INVESTIGATION ON ENERGY CONSUMPTION AND CO2 EMISSION REDUCTION IN INDUSTRY
A THESIS
Submitted by
THIRUGNANASAMBANDAM M In partial fulfillment for the award of the degree of
DOCTOR OF PHILOSOPHY
DEPARTMENT OF MECHANICAL ENGINEERING KALASALINGAM UNIVERSITY (Kalasalingam Academy of Research and Education) ANAND NAGAR: KRISHNANAKOIL - 626 126 JANUARY 2013
ii
iii
DEDICATED TO MY LOVING PARENT, MY WIFE AND CHILDREN
iv
ABSTRACT Industrialization and globalization have increased the tapping and consumption of primary energy sources in developing countries and these have contributed to global warming along with the simultaneous increase in energy related Greenhouse Gas (GHG) emission. Earlier studies on emission estimations have found a wide variation in the projected GHG emissions. According to a new Earth study report released on July 29, 2012, in Berkeley (US) the average temperature of the Earth's atmosphere has risen by 1.5°C over the past 250 years. The good match between the new temperature records and historical carbon dioxide data records suggests that the most straight forward explanation for this warming is the increase in greenhouse gas emission. Some of the scientists on the Berkeley Earth team admit surprise over what the new analysis has shown is the clear agreement between global land-‐temperature rise and human-‐caused greenhouse gases. "I was not expecting this," says Richard Muller, "but as a scientist, I feel it is my duty to let the evidence change my mind." The report also emphasizes that the carbon dioxide (CO2) in the atmosphere is more responsible for this temperature rise. The carbon dioxide released into the atmosphere mostly comes from the burning of carbon fuels particularly for the generation of electricity and the decentralized use of these fuels in the industrial process. Therefore a concerted effort becomes indispensable to curtail the exhaustive and inefficient use of carbon fuels. In addition to this, the electricity generated by the burning of carbon fuels like coal, diesel and gas should certainly be used efficiently to optimize the use of such fuels. Thus the need arises to conserve carbon fuels not only to save our environment but also to extend the availability of these energy reserves. The present situation has given an opportunity to find a scientific way of assessing the energy saving potential in
v the form of electricity and fuel particularly in industrial activities. The enactment of the Energy Conservation Act 2001 by the Indian Government and making it mandatory to reduce energy intensities in industries have made end users focus on optimizing their energy consumption by minimizing wastages and adopting energy efficient technologies. In this research work energy audit is applied as a scientific tool. Energy Efficiency Index is used as a guiding factor to predict the future energy saving potential in an industry and numerical analysis is used to critically analyze energy systems to quantify energy saving and related CO2 emission potential. A detailed energy audit has been carried out in a paper based industry through the “Bottom Up” approach. The specific energy consumption of the plant was estimated for Electrical at 91.85 kWh/tonn (304 MJ/t) and for thermal (Biomass) at 0.13 tonn/tonn (5.2MJ/t). Further analysis showed that the chosen industry had electricity saving potential of 49.128 MWh per annum. The energy saved worked out to be 5.9% of total electricity used in the industry (831.223 MWh). The major saving from arresting compressed air leakages accounted for 50% (25.602 MWh) of the total electricity savings identified.
The lighting system has given a saving
opportunity of 25.526 MWh/annum. This could be achieved by installing energy efficient lighting by reducing the standard supply voltage for lighting. In boiler, energy saving was identified through the de-rating of the capacity since the boiler at present was underutilized. The estimated fuel saving (biomass) was 34.23tonn/annum. The CO2 corresponding to the energy saved was estimated by multiplying it by the emission factor given by the Central Electricity Authority, Govt. of India. The cumulative CO2 emission reduction was estimated at 102.47 tonn per annum with an emission factor of 1.08 tCO2/MWh as suggested by the CEA and 1443.67 kg of CO2/tonn for
vi biomass as suggested by the Green House Gas Guidelines-2009, North Carolina Division of Air Quality.
The Energy Efficiency Index is the indicator of the energy performance of industry as a whole and is a guiding factor to predict the future available scope for energy saving measures relative to similar industry under study. A cement industry was analysed using this concept. The Energy Efficiency Index for electrical energy was estimated to be 117.15 for the year 2007-08 and it was found from the implemented energy saving measures that the plant achieved a saving potential of 1.42%. The absolute quantum of saving identified was 4833 MWh with and without investment. The further available scope is 15.73% which comes to 51,676.83 MWh/annum from the annual consumption of 328,524 MWh as estimated after implementing the suggested measures. The corresponding estimated emission saving was 5637.21 tCO2 per annum. A critical analysis was made on T-junction and Elbow of the compressed air pipe lines by the application of the Computational Fluid Dynamics (CFD), a powerful tool to dig out the hidden energy saving potential. Simulations were made for conventional T and Elbow and a new geometry was created for both T and elbow. The new designs were simulated for pressure drop across the junctions for three inlet pressures and varying flow in branch pipe. The simulation results showed that for taking branch at an angle of 46o with 150 mm fillet radius (refer. Fig 6.1) and for conventional elbow, a fillet radius of 150 mm was found to be the best design to get minimum pressure drop across joint. Thus for 5000 new redesigned T joints with 30% flow in the branch and 4 bar inlet pressure the estimated power saving was 6.90 MWh per annum. In the case of elbow for the same inlet pressure with 100% flow across junction the estimated energy saving was
vii 54.26 MWh/Annum. The corresponding CO2 saving was estimated at 7.24 and 58.60 tonn per annum. In any typical energy intensive industry like cement, petrochemical and fertilizer industries there are thousands of junctions installed in the compressed air piping network and the new design can be implemented in such industries to mitigate CO2 emission through energy conservation route. Detailed discussions are presented on the above finding in this thesis.
viii
ACKNOWLEDGEMENT The complete research work that has gone into this thesis has crossed many memorable events both at home and at the work place. My first discussion with my supervisor Dr. S Rajakarunakaran, Sr. Professor, Mechanical Engineering Department, Kalasalingam Academy of Research and Education, gave me the complete confidence that I will complete this research successfully. I sincerely thank him encouragement and for extending all kinds of support during the period of my research. I thank Dr. D. Devaraj, Sr. Professor, Electrical and Electronics Engineering Department, Kalasalingam Academy of Research and Education, my Joint Supervisor who practically pulled me into the paradigm of research through his critical observations and comments on my work and particularly while scripting the manuscript for publication. I place my sincere gratitude on record for his accepting my request to be my Joint Supervisor and for all the support he extended during the period of research. Dr. R. Saidur, Professor, Mechanical Engineering Department, University of Malaya, was my mentor and well wisher who introduced me to the art of writing research manuscripts for publications. He taught me how to convert practical experience into history! Thank you, sir, for all your support extended during the course my research. I sincerely thank Dr. C.E Sooriyamoorthy, former Professor and Head, School of Energy and Environmental Studies, Kamaraj University, Madurai for extending timely assistance, suggestions and comments in finalizing this thesis.
ix I sincerely thank Dr. J. Ramamohana Rao, Vice Chancellor, R.K University, Rajkot, Gujarat for suggesting appropriate corrections in the final version of my thesis.
In addition to the moral and professional support extended by my supervisors and mentor, I thank my friends really stood by me when I get fatigued. Their wishes, comments and the humor that they shared with me really made my journey for the past four years more enjoyable one. My heartfelt thank to all my friends, colleagues and well wishers.
THIRUGNANASAMBANDAM
x
CONTENTS CHAPTER NO.
1.0
2.0
3.0
TITLE
PAGE NO.
ABSTRACT
iv
ACKNOWLEDGEMENT
viii
LIST OF TABLES
xiv
LIST OF FIGURES
xvi
LIST OF SYMBOLS AND ABBREVIATIONS
xviii
INTRODUCTION
1
1.1
INTRODUCTION TO THE PROPOSED RESEARCH
1
1.2
ENERGY INTENSIVE INDUSTRIES
2
1.3
RESEARCH FRAME WORK
3
1.4
ORGANIZATION OF THESIS
7
LITERATURE REVIEW
8
2.1
INTRODUCTION
8
2.2
LITERATURE SURVEY
8
2.3
RESEARCH GAP
17
2.4
MOTIVATION FOR THIS WORK
18
2.5
SCOPE OF PRESENT RESEARCH
19
2.6
SUMMARY
19
RESEARCH METHODOLOGY
20
3.1
INTRODUCTION
20
3.2
ENERGY AUDIT
20
3.3
TYPES OF ENERGY AUDIT
21
xi CHAPTER NO.
3.4
TITLE
PAGE NO.
3.3.1 Preliminary Energy Audit
21
3.3.2 Targeted Energy Audit
21
3.3.3 Detailed Energy Audit
22
3.3.3.1 Pre-audit phase
22
3.3.3.2 Audit phase
23
3.3.3.3 Post-audit phase
25
EMISSION ANALYSIS
25
3.4.1 Grid Emission Factor
25
3.4.2 Description of the “Tool to Calculate the Emissions for an Electricity System” and Application of the “Tool” to India 3.4.3 Data and calculation Approach
3.5
4.0
26 27
3.4.3.1 Base data
27
3.4.3.2 Annual data
27
3.4.4 Calculation of CO2 Emission
28
SUMMARY
30
ENERGY AND EMISSION ANALYSIS IN INDUSTRIES-PAPER BASED
31
4.1
INTRODUCTION
31
4.2
METHODOLOGY
31
4.3
MANUFACTURING PROCESS OF PAPER CARTON BOX
32
4.4
PROCEDURAL STEPS FOR ENERGY ANALYSIS 34
4.5
DATA COLLECTION
35
4.6
DEVELOPMENT OF MATHEMATICAL MODEL
36
4.7
DATA ANALYSIS
39
xii CHAPTER NO.
4.8
4.9
5.0
6.0
TITLE
PAGE NO.
ENERGY SAVING OPPORTUNITIES
43
4.8.1 Analysis on Lighting
43
4.8.1.1 Reducing standard supply voltage
44
4.8.1.2 Installation of energy efficient lamps
45
4.8.2 Analysis on Air Compressor
46
4.8.3 Analysis on Motor
48
4.8.4 Analysis on Boiler
50
SUMMARY
55
ENERGY AND EMISSION ANALYSIS IN CEMENT INDUSTRY
56
5.1
INTRODUCTION
56
5.2
ENERGY PROFILE
56
5.3
ENERGY CONSERVATION STATUS
57
5.4
MATHEMATICAL FORMULATION
62
5.5
RESULT AND DISCUSSION
62
5.6
SUMMARY
64
CFD ANALYSIS ON COMPRESSED AIR PIPE LINE WITH REFERENCE TO T-JUNCTION AND ELBOW
65
6.1
INTRODUCTION
65
6.2
CFD ANALYSIS
65
6.3
TURBULENCE MODELS
66
6.4
PROBLEM IDENTIFICATION
68
6.5
MATHEMATICAL EQUATIONS TO ESTIMATE ENERGY AND EMISSION SAVING
69
xiii CHAPTER NO.
6.6
6.7
TITLE
PAGE NO.
SIMULATION OF COMPRESSED AIR PIPE JUNCTIONS
70
6.6.1 T- Junction
70
6.6.2 Elbow
75
6.6.3 Branching with Fillet and θ =46o
77
ESTIMATION OF ENERGY AND CO2 EMISSION SAVING
80
6.8
RESULT AND DISCUSSION
82
6.9
SUMMARY
85
7.0
SUMMARY OF RESEARCH FINDINGS
86
8.0
FUTURE SCOPE
91
REFERENCES
92
LIST OF PUBLICATIONS
96
CURRICULUM VITAE
99
xiv
LIST OF TABLES Table No.
Title
1.1
Potential saving available in few selected industries
3.1
Weighted average specific emissions for fossil fuel fired stations in FY 2010-11, in t CO2/MWh
4.1
Page No. 3
29
List of instruments and their specifications for conducting energy audit
35
4.2
Sources of energy and their contributions
39
4.3
Annual energy consumption in the plant
39
4.4
Energy consumption details for the year 2009
41
4.6
Operating parameters for lighting
44
4.7
Comparison of lighting performance parameters for different types of lightings(ES, 2010)
45
4.8
Load survey on electrical motors
49
4.9
Operation and fuel consumption of a boiler
51
4.10
Estimated energy and CO2 reduction potential
53
5.1
Summary of energy consumption, specific energy consumption and energy cost (M/s. JayPee Cements)
5.2
57
Comparison of electrical and thermal SEC for few selected countries around the world for the year 2004
58
5.3
Energy savings measures without investment
59
5.4
Energy savings measures with investment
61
5.5
Energy Efficiency Index and relative energy saving potential (m/s. Jaypee cement)
6.1
Simulation result of pressure drop through T junction for various pressure
6.2
63
71
Pressure and flow pattern at 4 bar for different values of angle (θ) 73
xv Table No. 6.3
Title
Change in percentage pressure drop without fillet and with 150 mm radius fillet
6.4
83
Energy and emission saving due to redesigning of ‘L’ joints (r=150 mm)
7.1
80
Energy and emission saving in the new geometry of T joints with θ=46o and r=150 mm
6.6
75
Estimated pressure loss % with 46o branch with fillet and 90o branch without fillet
6.5
Page No.
84
Summary of cumulative energy and emission saving potential identified
90
xvi LIST OF FIGURES Figure No.
Title
Page No.
1.1
Methodological Frameworks
5
1.2
Procedural steps involved in the proposed research
6
2.1
Estimated World GHG Emissions
17
3.1
Principle of Calculating Emission Reductions
26
4.1
Methodology of energy analysis
32
4.2
Process flow of paper carton manufacturing
33
4.3
Share of energy carrier in the facility
40
4.4
Trend of specific energy consumption and production
42
4.5
Share of self generated and grid power consumed during 2009
6.1
43
The geometry of existing (straight line) and the geometry investigated (dotted line) for T and Elbow ( r=fillet radius)
67
6.2
Existing joints in pipes transporting compressed air
68
6.3
Pressure contour across joint at pressure 4 bar
71
6.4
Pressure contour across joint at pressure 6 bar
72
6.5
Pressure contour across joint at pressure 8 bar
72
6.6
Pressure drop observed at 46o with inlet pressure 4 bar
74
6.7
Pressure gradient at different air pressure (4,6 &8 bar) with θ=90 & 46
74
6.8
Pressure gradient without fillet at 4 bar
76
6.9
Pressure gradients for elbow with 150 mm fillet at 4 bar inlet pressure
76
6.10
Fillet radius Vs Pressure drop for elbow
77
6.11
Redesigned geometry of branching in place of 90o T joint
77
xvii Figure No. 6.12
Title
Simulated pressure contour for inlet pressure 4 bar and 10% of flow in branch pipe with θ=46o and fillet radius (r) = 150 mm
6.13
78
Simulated pressure contour for inlet pressure 6 bar and 10% of flow in branch pipe with θ=46o and fillet radius (r) = 150 mm
6.14
Page No.
79
Simulated pressure contour for inlet pressure 8 bar and 10% of flow in branch pipe with θ=46o and fileet radius (r) = 150 mm 79
6.15
Energy recovered in redesigned geometry for branch at test pressures
84
xviii
LIST OF SYMBOLS AND ABBREVIATIONS ACC
Air compressor capacity (cfm)
ACS
Annual cost saving in (INR)
AECc
Annual energy consumption by air compressor (KWh)
AEUe
Annual electrical energy used in (kWh)
BAU
Business As Usual
BEE
Bureau of Energy Efficiency
BPST
Back pressure steam turbine
CAl
Compressed air leakage in %
cfm
Cubic feet per minute
Cε1,C ε2
Standard k- ε model constants
DG
Diesel Generator
Dy
No of days for the year y
Dy
Number of days operated in the year “y”
e
Electrical
ELal
Energy loss due to air leakage (kWh)
Er
Energy recovered (MWh)
F
Fuel
Fm
Fuel consumed for the given month ‘m’ in kg
Fij
Fuel consumed for the given equipment ‘i’ for the given fule ‘j’
FW
Fire Wood
GCV
Gross Calorific value (kJ/kg)
GT
Gas Turbine
H
Operating hour
HPMVL
High Pressure Mercury Vapor Lamp
HPSVL
High Pressure Sodium Vapor Lamp
I
Investment (INR)
xix INR
Indian Rupees
k
Turbulent kinetic energy (m2/s2)
La
Air leakage actual in (cfm)
Lua
Air leakage un-avoidable (cfm)
LVSD
Percentage of load associated with the use of VSD
mf
Mass of fuel (Kg)
n
Number of equipments using electricity
Na
Adiabatic power required (MWh)
Nθ
Adiabatic power at angle θ and is replaced with fillet radius (r) in case of elbows
P
Power consumed at full load (kW)
P1 & P2
Initial and final pressure in bar (a)
Pi
Actual electrical energy consumed by the ith equipment (kW)
Pm
Energy consumed for the given month ‘m’ in kWh
Pr
Rated power (kW)
PuL
Power consumed during unloading time in minuits
PVSD
Power required (kW) when VSD is installed
Q
Flow rate (M3/h)
Qf
Heat in feed water (KJ)
Qm
Production in month m
Qs
Heat in steam (kJ)
ROI
Return on Investment
SEC
Specific energy consumption (MJ/ton)
SPB
Simple payback period in years
SV
Salvage Value of old motor in (INR)
t
Thermal
T
Total time of operation in hour
Tf
Air receiver filling time in minuets
xx Ti
Time of operation of ith equipment (hr/day)
TL
Air compressor loading time in minuets
TuL
Compress or unloading time in minuets
Vr
Compressed air receiver volume in m3
γ
Compression index, 1.4
ε
η ρ
σk
Turbulent dissipation per unit mass Thermal efficiency of boiler Mass density (kg/m3) Turbulent Prandtl number for k
σε
Turbulent Prandtl number for ε
µ
Dynamic viscosity (Kg/ms)
µt
Turbulent viscosity (Kg/ms)
1
CHAPTER 1 INTRODUCTION
1.1
INTRODUCTION TO THE PROPOSED RESEARCH Energy requirement keeps increasing exponentially in the context of
increased industrial activities in the aftermath of globalization and liberalization particularly in developing economies. This makes the developing economies in the planet to exploit the natural sources of energy like coal, oil and gas in an uncontrolled fashion. Since the start of the 19th century this planet has started experiencing the heat of extensive use of carbon fuels in the form of climate change and global warming. The major contributor to this phenomenon is the increased release of the Carbon dioxide (CO2) into the atmosphere which is responsible for the Green House Gas Effect. A major portion of this gas comes from the combustion of carbon fuels in the process of generating electricity. However, for this reason the generation of electricity cannot be avoided, instead it becomes more inevitable to generate electricity to sustain the process of industrialization.
This additional requirement of
electricity has caused an increase in the release of CO2 into the atmosphere and at the same time triggered the fast depletion of carbon resources. On the one hand the electricity needs are increasing and on the other hand we have practical limitations in improving the efficiency of power generation. It means the inefficiency remains the same as dictated by the laws of thermodynamics. This conflicting engineering phenomenon further intensifies the issue of green house gas effect and the global warming.
2 Today this planet needs a quick remedy from getting warmer and warmer and thus forcing all the beneficiaries of the natural carbon resources to adopt methods to use these resources efficiently with two major objectives: (i) to conserve energy for future and (ii) to reduce the release of CO2 into the atmosphere. The users of carbon fuels considered in this research are the industrial end users of electricity. The status of the present energy conservation/management practices in the identified sector is discussed in this chapter.
1.2
ENERGY INTENSIVE INDUSTRIES Globally, Industrial energy use accounts for 40% of electricity use,
77% of coal and coal products use, and 37% of natural gas use and is a major contributor to CO2 emissions. (American National Standards Institute, 2005, MSE 2000:2005 A Management System for Energy, Washington, DC, USA) The list of energy intensive industries and other establishments specified as designated consumers by the Indian Govt. under the Energy Conservation Act2001 covers the following specific industries: •
Aluminum
•
Fertilizers
•
Iron and Steel
•
Cement
•
Pulp and paper
Naphtha Crackers and Petroleum
•
Chlor Akali
Refineries
•
Sugar
•
Textile
power stations, electricity
•
Chemicals
transmission companies and
•
Railways
distribution companies
•
Port Trust
•
Transport Sector (industries and services)
•
•
Petrochemicals, Gas Crackers,
Thermal Power Stations, hydel
3
The above industries have to establish an energy management cell within the industry to measure and monitor the energy flow within the industry and submit a report on the energy performance to the Indian Govt. The potential energy saving available in a few selected industries is listed in Table 1.1. Table 1.1 Potential saving available in few selected industries Industry
Energy share in Manufacturing cost range %
Energy saving potential %
Aluminium 60—70 15 Automobile 9—11 10 Cement 35—45 15 Chemical 10—15 15 Glass & Ceramics 22—25 15 Dairy 4—6 20 Engineering 8—10 10 Foundry 15—20 20 Paints 17—19 20 Paper 22—25 20 Petrochemicals 2—3 15 Steel 12—15 15 Sugar 2—3 15 Textiles 12—15 20 Tyre 14—16 15 (Source: Bureau of Energy Efficiency, Govt. of India)
1.3
RESEARCH FRAME WORK The research frame work covers the following: •
Identification of two industrial sectors where the energy carriers such as coal and its by-products along with coal based electricity are extensively utilized
•
Segregation and grouping of equipment and processes based on energy use
4 •
Performing energy and emission analysis on individual equipment to ascertain the existing level of energy consumption
•
Development of mathematical models for energy and emission analysis
•
Identification of scope for reducing energy consumption and reduction of CO2 emission
•
Optimization studies for resource conservation using numerical analysis
The methodological frame work for the proposed research is shown in Figure 1.1 and the procedural steps involved to carry out the work are given in Figure 1.2. In the research frame work energy consumption in the form of electricity and fuel which leads to CO2 emission is presented. Electricity is generated by burning coal in a thermal power plant and fuel is used in the industry to meet the local heating needs and for self power generation. If the end user does not use the energy resource efficiently the industry may require more electricity and coal and thus become responsible for higher CO2 emission. Therefore, the end users need guidance on the need for the efficient use of energy and this could be achieved through “bottom-up” approach. Employing an energy efficient technology and retrofitting the existing systems with cost effective energy saving measures is one of the options to reduce energy consumption.
5
Top-Down
Reduced Indirect Emission
Reduced Direct Emission CO2
CO2
Policy measures to Encourage Industries to Invest in EE Technologies and Energy Conservation
Electricity
Coal Power Plant
Reduced Coal consumption
Industry & Buildings
Coal, Gas, Oil
Reduced Power consumption
Reduced Coal, Oil and Gas Consumption
EE Technologies and Optimization, Control and Monitoring Mechanism for improving End use Energy Efficiency
Bottom -Up
Figure 1.1 Methodological frameworks
In the “bottom-up” approach a complete diagnosis of energy use within the plant is carried out to ascertain the energy efficiency of the individual energy system. The steps involved are: • Conducting a detailed energy audit/analysis • Estimation of annual energy consumption of each energy system in terms of kWh/unit of product • Identification of opportunities for energy saving by the application of the basic engineering skill • Performing critical analysis using numerical methods to identify hidden energy saving potential • Estimation of equivalent emission reduction
6 • Making an economic analysis to prioritize the energy saving measures for implementation
CO2 emission Estimation
Identification of Energy Saving Opportunities
CFD- Analysis
Data Analysis
Data measurement
Motors
Air Compressor
Boiler
Lighting
Process Industry
Energy carriers
Figure 1.2 Procedural steps involved in the proposed research
By following these procedural steps a sustainable development of industrial and commercial activities can be ensured with reduced damage to the environment.
7 1.4
ORGANIZATION OF THESIS The research output is elaborated in this thesis and structured as
follows. Chapter-2: In this chapter the research gap is identified and then objectives and the motivation for the research are discussed. A detailed literature survey is presented to support the research gap identified. The major research gap identified is the need of the application of numerical tools for the critical analysis of energy systems to quantify the saving potentials in terms of energy and CO2 emission. Chapter-3: The research tool applied is discussed with the applicable theory. The research tools applied are Energy Audit and numerical analysis Chapter-4: A case of paper based industry is discussed for energy performance by conducting a detailed energy audit. The methodology, procedural steps, energy and emission saving potential identified applying the Energy Audit tool with the Bottom-Up approach are presented in this chapter. Chapter-5: In this chapter the case of the cement industry is discussed. The energy efficiency Index is used as an indicator of the energy performance in the cement sector and a case of the cement industry is discussed in estimating the energy saving potential relative to the sector’s best performance. Chapter-6: The Numerical method-Computational Fluid Dynamics applied to pressure drop analysis in compressed air pipe junctions T and L is presented in this chapter. A new geometry for taking branch line is simulated and results are also discussed. Chapter-7:
The result and discussion of the research findings are
summarized in this chapter. Chapter-8: The future scope of this research is spelt out in this chapter. The methodology explained in this research can be applied to similar energy intensive industries as well as other sectors of economy like building and domestic sectors.
8
CHAPTER 2 LITERATURE REVIEW
2.1
INTRODUCTION The impact of industrialization on this planet is clearly visible in the
form of climate change. The root cause of this burning issue is the release of carbon dioxide (CO2) into the atmosphere by the extensive burning of carbon fuels. Therefore it becomes imperative to look for opportunities to reduce CO2 emission keeping the tempo of development on a sustainable note. Further, the maximum amount of CO2 is released from electricity generation. From this fact it is evident that minimizing coal based electrical energy use in industries will ultimately lead to reduced CO2 emission. The problems of energy and related emission are dynamic and keep changing with the current need of human convenience and comfort. Keeping this logical cycle in mind the literature survey is made and presented in this chapter.
2.2
LITERATURE SURVEY The literature survey was made to understand the impact of
electricity use and related emission in industries by focusing on: •
Energy usage and related CO2 emission in industries
•
CO2 emission from industries
•
Energy audit in industries
•
Green House Gas (GHG) emission from industries
•
Energy and emission study in energy systems
9 Mongia et al (1994) studied the implication of energy use in the energy intensive industries in the abetment of CO2 emission. They proposed various strategies to reduce the energy use and the predominant one suggested was the fuel mix in the energy requirement. For this purpose, we quantify levels of CO2 emissions associated with different industrial strategies CO2 and process choices for given levels of projected demand for end-use service and for industrial products. Sathaye (2006) observed that worldwide concern with global climate change has highlighted the challenges faced by industrialized and developing countries in maintaining a sustained process of development. He studied the implication of introducing combined cycle power generation in developing countries in place of conventional coal power plants. He observed that the new technology will improve the energy efficiency and thus reduce the fuel consumption and the related CO2 emission into the atmosphere. Mongia et al (2001) in their study observed that the non-availability of energy was a serious obstacle to economic growth, and industrial energy demand was growing at 5% per year. They also studied the implications of the policy reforms on the productivity in the energy intensive industries. They focused their study on cement, fertilizer, Aluminium, paper and Iron and steel. Mathur et al (2003) pointed out that the growth of an economy was closely related to the growth in its energy consumption. During the past decade, electricity demand in India has increased many folds at an average rate of 6.13% per year. They also studied the emission abetment measures in Indian power plants and suggested that hydro electric and wind power generation would be a better option; however the low cost of coal makes India rely on thermal power generation. They pointed out that to make coal based power plants more economical many countries had introduced carbon tax. They used MARKAL model to find the rate of carbon tax that could be suitable for India in four categories namely low, moderate, reference and high tax. They also recommend fluidized bed combustion technology to improve the efficiency of
10 coal based power generation. Gielen et al (2009) said that as per the report of International Energy Agency, energy consumption in the Indian industry is projected to be more than double by 2030. In India, they observed that the cement industries are relatively efficient compared to other industries such as pulp and paper. They suggest a strong focus on industrial efficiency that can minimize the growth of energy demand but at the same time the CO2 emission is bound to increase substantially due to increased industrial activity. They also point out that to curtail the emission of CO2 it is necessary to combine energy efficiency with measures that reduce the carbon intensity in industries. Avami et al (2007) conducted energy audits in 30 cement industries in Iran between 2004 and 2006. They say energy audit is the most comprehensive approach to improve the energy efficiency of existing energy systems and to lower the carbon dioxide emission. They observe that 15% of the total energy is consumed by the cement industries. The major energy carrier used in cement production in Iran is hydrocarbons (72%) and electricity (28%). The energy intensity of cement production lies nearer to 120 kWh/ton of cement and they proposed a 10% reduction in the energy intensity by improving the energy efficiency. They have proposed various measures to reduce energy consumption and the estimated electricity saving is 42.075 MWh per annum. Madlool et al (2011) conducted a detailed review on energy use in Malaysian cement industries. The study revealed that 12–15% of the total industrial energy was consumed by the cement sector. In their article they studied the energy use in various sections of the cement industry, specific energy consumption, types of energy use and energy saving measures adopted in cement industries. Pyro-processing is the highest energy intensive process in the cement manufacturing consuming 93-99% of the total energy consumed. They had presented an exhaustive review of various energy saving measures in their article.
11 Saidur et al (2010) had presented a detailed review of energy use by industrial motors. They reviewed the different losses that occur
in a
motor and measures to reduce these losses are presented in his article. In addition to technologies they also proposed policy measures like intensive based energy saving programs. They use computer tools to perform cost benefit analysis to reduce energy consumption. He suggested measures like shaft alignment and coupling, constant speed motor, lubrication and installation of capacitors. Zeng and Yan (2005) say that in China 68% of the primary energy is met from coal and its average energy intensity is 7.5 times higher than the EU and 4.3 times higher than US. The energy efficiency in China is generally low and carbon intensity is high. They concluded that the Chinese government needs to promote awareness, streamline administrative systems, and be more active in building a competitive edge in the world carbon market. Wang et al (2007) had investigated optimum solutions for European steel plants to meet their emission standards at low cost. They developed an optimization model based on Swedish steel plant and presented three scenarios: (1) internal changes within the industry, (2) EU-Emission Trading Scheme and (3) the Kyoto Protocol’s clean development mechanism. They observed that the CDM projects and internal changes will make the plant reduce CO2 emissions at lower cost. Jing Liu (2011) discussed measures to sustain the development of China’s pulp and paper industries through emission trading.
He recommended the active participation of industries in CDM
(Clean Development Mechanism) projects. The possible areas that these industries can target are the energy efficiency improvement in boilers, electrical systems, and fuel substitutions, reduction of electricity consumption by recovering soda from paper manufacturing process, optimization of steam consumption and the use of renewable energy sources. Axelsson (2011) estimated the CO2 saving potential through energy saving in Swedish paper and pulp mills alone at 0.4–3.1 Mton/yr. He showed that the export of
12 electricity was the most cost effective method to reduce CO2 emission and concludes that savings in electricity was the best option to reduce CO2 emission compared to exporting carbon fuels to the end users.
Roosa (2007)
conducted an eloborate study on urban sustainability by considering 25 Sunbelt cities defined as cities which have high growth of population and economy. He studied the implementation of major urban policies related to energy and environment and concluded that the policies related to energy was critical in their urban agenda for sustainability. Palanichamy and Sundar Babu (2005) conducted an energy audit in a textile industry and the policy implications. This article highlights the energy saving opportunities and the practically implementable and environmental friendly measures that were implemented. The energy saving opportunities identified includes building insulation, enhanced natural lighting, installing flat belts in place of V- belts, synthetic sandwich tapes for spinning frames and introduction of renewable energy sources. On policy side they advocate the introduction of stringent policy for co-generation, setting standard for specific energy consumption, electrical demand approval policy and rationing of fossil fuels. Klugman et al (2007) conducted energy audit in a Swedish wood-pulp industry. They conducted energy performance study on the process equipments namely digesters, bleaching, drying, boilers and evaporators. The chosen industry was thermally intensive and it was observed that the evaporator section consume the maximum energy in the form of heat. They also studied the generic process equipments like air compressors, lighting, pumps, air conditioning and fans. Li et al (2010) performed a similar study in a glass manufacturing industry. Through their study they could reduce the energy cost from 51.19% in 2007 to 46.48% in 2008. His study was focused on reducing non production related energy consumption, management of air conditioning energy consumption, management of water consumption and motor vehicle management. He also suggested reward and punishment schemes to improve
13 the energy efficiency of the plant. Saidur and Mekhilef (2010) published the outcome of the energy performance study conducted in a rubber industry. They observed that 75% of the cost was spent for energy. In the total energy consumed, motors consumed 48%, process heat 20% and air compressors 9%. He recommended energy efficient and variable speed drives for motors. This article suggests energy saving measures in air conditioners, chillers, air compressors and boilers. Mathematical formulations are presented for the estimation of energy saving, payback period for investment and emission reduction.
Akbaba (1999) observed that the electric motors and motor driven systems use a major share of energy in an industry and the cost of energy to operate motors and motor driven systems have become a real concern for industries. According to him, in Bahrain electric motors consume three quarters of total electricity generated. He compared the energy efficiency of energy efficient motors with standard motors ranging from 3 to 300 HP. A detailed cost analysis was presented for a case of 200 HP standard motor with energy efficient motors with reference to a petrochemical industry. Hasanuzzaman et al (2011) said in their article that electrical motors consume 30-80% of the total
industrial energy around the world. They
presented the economic viability of replacing rewound and standard motors with energy efficient motors. They suggest that it is economical to rewind larger motors than small motors as each time a motor is rewound its efficiency gets detoriarated and the cost of rewinding a large motor is comparatively high. The energy efficient motors save energy at an average rate of 5.5% compared to standard motors. The payback period for the energy efficient motors is attarctive if these motors are operated at 50% load. They demonstarated that the rewinding of large motors and introduction of high efficiency motors are economical and also reduce largely the emission of CO2
14 into the atmosphere.
They also advocate that an energy audit helps an
organization to understand and analyze its energy utilization and to identify areas where energy use can be reduced and to decide on how to budget energy use,plan and practice feasible energy conservation mearures that will enhance their energy efficiency, curtail energy wastage and substantially reduce energy costs. Nadel et al (2002) published a comprehensive study on electric motor’s energy savings, policy, and technology by Energy use, savings and energy efficiencies of machines used in industrial sectors. Ozturk (2005) has studied the case of four textile industries in Turkey. He compared various indicators like energy consumption per kg of production, energy cost per kg of production, energy cost per unit of consumption and energy consumption. He showed that all the above values have a liner relationship with production. Christoffersen et al (2006) presented an empirical analysis for energy management to find out to what extent the Danish manufacturing industries practice energy management. The study covered 305 manufacturing industries and the study was conducted through telephonic interview. They found that between 3% and 14% industries practice energy management. The highest motivating factor for this is the utility supplier and the realization of the reduction in energy cost.
Subrahmanya (2006) presented the impact of
labour efficiency in promoting energy efficiency in small scale brick manufacturing enterprises cluster in India; surprisingly he observed that the labour efficiency has negative influence on energy cost. His study showed that those enterprises that exhibited higher labour productivities had lower average energy intensity and higher returns to scale as compared to those that had lower labour productivities. Considering this, he argued in his article that the improvement of labour efficiency can be an alternative approach for energy efficiency improvement in energy intensive small scale industries in developing countries like India. Almeida et al (2003) in his article says that the energy can be saved using energy efficient motors and variable speed
15 drives in both industry and services sectors in European Union. They noticed that a major chunk of electricity is consumed by motors (36%), pumps (21%) followed by air compressors (18%) in the industrial sector. In the case of service sector he observed that the refrigeration and air conditioning consumed 42% of electricity followed by fans (24%) and pumps (16%). The other major observation was that in industrial sector low range motors (10-100 HP) operate for more hours consuming less power whereas high range motors (100-500 HP) operates for lesser hours but consume more electricity.
In
service sector the maximum number of motors installed falls in the range of 0.75 to 30 HP and these motors consume significant portion of electricity. Garcia et al (2007) discussed the introduction of Minimum Energy Performance Standards (MEPS) introduced in Brazil through “Energy Efficiency Act”. His article presents the consequences of this new act and he observed that motors substitution from standard to energy efficient motors is advantageous from an economic point of view. A total of nine thousand motors were studied and he predicted a possible reduction in generation capacity of 350 MW of hydroelectric power through energy saving for Brazil. Ryszard Dindorf (2012) discussed energy saving potential in compressed air system. He has mentioned that for every 0.5 bar pressure reduction the energy saving would be 3% of electricity consumed by the compressor. He estimated energy loss due to pressure reduction assuming adiabatic compression.
Numerical applications in engineering assist to perform critical analysis on flow processes.
Compressed air is widely used in various
pneumatic applications in industries. The earliest publication on the fundamental theory on flow through short pipes in a compressible viscous stream was made by Seddon (1957) in a report (CP No. 355) of the Aeronautical Research Council, London. Though the report focused on the applications related to aeronautical engineering the fundamental theory is
16 applied in similar flow process in industrial activities. In his report he derived a relationship for a given free stream Mach number at which the flow just becomes supersonic in terms of Reynolds number and pipe dimensions like diameter and length to radius ratio. He conducted an experimental test with Mach numbers between 1.34 and 2.41 and compared with theoretical results. His study is focused to know the pressure distribution on the wings of an aircraft due to the external shock developed with the nature of flow: subsonic or supersonic. Nikola Tanasic (2011) has applied CFD analysis to predict energy efficiency and CO2 emission in a card board mill hall by simulating the air flow and temperature. He studied the optimum location to extract waste heat from ventilation systems. He estimated that by utilizing the waste heat from the proposed optimal locations, fuel savings of 5% and reduction of 1140 t/year in CO2 emissions could be achieved. He applied the CFD simulation to study the air flow pattern inside the mill assuming laminar flow. He commented that the simulation results served well for qualitative analysis and gave better insight in the general air movements inside the hall and indicated the exact air intake locations. Ruth Mossad (2009) investigated the turbulent air flow across a 90o elbow using CFD simulation. He applied three turbulence models: k-ε realizable, k-ε RNG and Reynolds Stress using FLUENT software with 3D assuming steady, turbulent and incompressible flow conditions. The study compared velocity profiles across the elbow for various mesh patterns: course, medium and fine. Fine mesh was observed to give better results in predicting velocity profiles. His study concluded that among the entire three turbulence models k-ε realizable model gave better results matching with experimental results. Mohammed Abdulwahhab (2012) investigated the flow of water through T-junction assuming isothermal conditions. He applied the standard k-ε turbulent model with standard constants and said that this model was widely applied for modeling turbulent flows. The commercial software ANSIS CFX 13 Solver is used in the analysis with tetrahedral mesh. He used
17 the same diameter for main pipe and branch pipe maintaining the area ratio of one. His study showed that the flow rate has significant effect on pressure loss across junction.
2.3
MOTIVATION FOR THIS WORK It is clearly spelt out in the Planning Commission Report on
Integrated Energy policy-2006, “relentlessly pursue energy efficiency and energy conservation...”
“Areas of action by India (on climate change)
include initiatives in clean energy including renewable energy and action to increase energy efficiency. In this context, one of the monitorable objectives of the Eleventh Plan is to reduce the energy intensity per unit of GDP by 20 per cent over the Plan period,” says the 11th Plan (2007-2012) paper of the Planning Commission. (Source: www.indianexpress.com, posted on Dec 10 2007). Studies conducted at various regional economies show that the majority of CO2 emissions will be concentrated in developing countries as per the projected data shown in Figure 2.1.
This is mainly because of fast
industrialization and therefore the energy systems used in the industries must be kept at the highest efficiency level to mitigate the release of CO2 emission into the atmosphere.
Figure 2.1 Estimated world GHG emissions (Source: SGM Energy Modeling Forum EMF-21 Projections, Energy Journal Special Issue, in press, reference case CO2 projections-EPA (US))
18 Therefore it is evident that the end use efficiency is a critical factor in the estimation of GHG emissions. In India the maximum GHG emission in the form of CO2 comes from the energy transforming industries (Thermal power plant) and the combustion of fossil fuels in industries. Therefore the industrial energy users are to be encouraged to adopt energy conservation measures to reduce their energy intensity per unit of industrial product vis-àvis GHG emission for sustainable growth. The scope for reduction in the energy consumption is high at the rate of 20% in energy intensive industries as per the Planning Commission of India report. The recent enactment of the Energy Conservation Act-2001 in India has already created a momentum in this sector. India has introduced various schemes and awards for encouraging energy users to adopt energy efficient technologies and practices. This could be achieved by developing sector specific energy and environment indicators for GHG emission particularly CO2 emission. All the above facts motivated us to take up this research which has a strong social relevance. It aims to contribute to ensuring a sustainable development, as defined by Our Common Future, also known as the Brundtland Report (1987) "Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs”.
2.4
RESEARCH GAP The exhaustive review of literature has shown the following
research gaps: • There is a sustained need for the quantification of possible energy saving both thermal and electrical, and corresponding CO2 emission at the end user, particularly Industry
19 • Lack of system specific mathematical equations in energy and emission analysis for generalization • There is need to make a critical analysis of energy systems using numerical methods for energy and emission estimation
2.5
SCOPE OF PRESENT RESEARCH The current research is directed on the following aspects: • Quantification of possible energy saving and related CO2 emission in selected industries by the application of the energy Audit tool • Development of system specific mathematical equations for the estimation of energy saving and related CO2 emission reduction • To apply the numerical method for the critical analysis of an energy system to quantify the energy saving and related CO2 emission reduction
2.6
SUMMARY It is inferred from the literature review that there is need for a
concerted effort to quantify the emission reduction potential through the conservation of energy carriers. The major source of CO2 emission comes from thermal power plants. Though improving the operating efficiency at the generation point itself reduces emission, it is equally important to ensure that the generated electricity is used efficiently by the end user so that it also contributes to the process of emission reduction.
20
CHAPTER 3 RESEARCH METHODOLOGY
3.1
INTRODUCTION The research methodology followed in this work is based on energy
conservation and related emissions. Energy conservation and emission reduction measures are employed in industries mostly by experience and with working knowledge in energy systems. The requirements for conducting energy audit are the basic engineering skills and arithmetic operations. The application of a systematic procedure in energy and emission study is seldom followed in most of the industries except in large scale energy intensive industries like cement, petroleum and fertilizer. Therefore awareness in using scientific tools for energy analysis is the need of the hour for all categories of energy users. This chapter spells out the methodology employed for energy and energy related emission analysis.
3.2
ENERGY AUDIT Energy Audit is the key to a systematic approach for decision-
making in the area of energy management. It attempts to balance the total energy inputs with its use, and serves to identify all the energy streams in a facility. It quantifies energy usage according to its discrete functions. Industrial energy audit is an effective tool in defining and pursuing a comprehensive energy management program.
As per the Energy Conservation Act, 2001, Energy Audit is defined as "the verification, monitoring and analysis of use of energy including
21 submission of technical report containing recommendations for improving energy efficiency with cost benefit analysis and an action plan to reduce energy consumption".
3.3
TYPES OF ENERGY AUDIT Types of energy audit depend on the type of industry, the depth to
which the final report is needed, potential and magnitude of cost reduction is desired. Thus the energy audit can be classified into the following types
3.3.1
Preliminary Energy Audit Preliminary energy audit which is also known as walk through
energy audit (or) diagnostic audit is a relatively quick exercise and uses existing (or) easily obtained data. The scope of preliminary energy audit is to • Establish energy consumption in the organization • Obtain related data such as production for relating energy consumption • Estimate the scope for energy savings • Identify the most likely and easiest areas for attention • Identify immediate especially no/low improvements for energy savings • Set up a baseline (or) reference point for energy consumption • Identify areas for more detailed energy study or measurements Preliminary energy audit can be completed in a day or two depending on the size and activities of the industry. This audit does not require sophisticated measuring instruments or software tools.
3.3.2
Targeted Energy Audit: Targeted energy audit is conducted on the particular energy system
or process within an industry to minimize the energy intensity in a particular operational area. This often results from preliminary energy audit. Necessary
22 data is provided by the industry by collecting data from calibrated online instruments (or) measured by the auditor wherever possible. This type of audit normally targets energy intensive equipment like air compressors, refrigeration and air conditioning, boilers, heat exchangers, pumps and fans and lighting systems. Therefore targeted energy audit involves detailed survey of the target subjects and analysis of the energy flows and cost associated with the targets. The final outcome is the recommendation regarding action plan to be taken to improve the energy performance of the energy system.
3.3.3
Detailed Energy Audit Detailed energy audit is a comprehensive audit and results in a
detailed energy project implementation plan for an industry, since it accounts for the energy use of all major equipments. It considers the interactive effects of various projects and offers the most accurate estimate of energy saving and cost. It includes detailed energy cost saving calculations and project implementation cost.
One of the key elements in the detailed energy audit is the energy balance in the industries. This is based on the inventory of the energy using system, assumptions of current operating conditions, measurements and calculation of energy use. The detailed energy audit is carried out in three steps. • Pre audit phase • Audit phase • Post audit phase 3.3.3.1
Pre audit phase In this phase an initial study of the industry is carried out for proper
planning of pre request to conduct the audit effectively. A one or two day visit to the site is required to meet the personnel concerned to familiarize with the
23 manufacturing activities and to access the procedures necessary to carry out the energy audit. During this visit the following activities are carried out in general. • Detailed discussion with the senior management personnel to understand the need, aims and objectives to conduct the energy audit. • To explain the kind of information that is required during the actual audit period. • To get guidelines for economic analysis particularly budget provisions details of earlier audit conducted and the status of implementation of energy conservation already recommended by any previous audit team. • Analyze the major energy consumption data and discuss elaborately with the relevant personnel.
The outcome of the visit needs to finalize an energy audit team and expertise required, actual expectation of the management, identification of potential areas for energy saving, identification of the type of instruments and the level of accuracy required and the schedule to carry out the detailed energy audit.
3.3.3.2
Audit phase Depending on the nature and complexity of the manufacturing
activity, this can take a minimum of 3 days to several weeks or months to complete the audit. It involves the investigation and establishment of material and energy balances for specific energy system and process equipments. This is a well planned operation or check over extended periods of time to ensure that it is over looped. The information to be collected during the energy audit includes • Sources of energy supplies • Energy cost and tariffs
24 • Generation and distribution of utilities like compressed air, steam, chilled water • Process and material for diagrams • Internal electrical distribution diagrams (single line diagram) • Energy consumption details, equipments, running hours, failure rates, production details • Potential for fuel substitution, process modification and the use of cogeneration systems • Review of ongoing energy management procedures and energy awareness training programs
Apart from the above information the baseline data of the following are also to be collected. • Quantity and type of raw materials • Technology, process used and equipment used • Capacity, utilization efficiencies and yield • Percentage rejection in reprocessing • Quantity of type of waste • Consumption of fuel, water, steam, electricity, compressed air, chilled water
However the type and natural data solely depends on the nature of the manufacturing process and the type of industry. As part of the audit, interview with supervisors and equipment operators must be conducted as they have information related to the actual operating condition of the equipment. The maintenance manager is often the primary person to talk about equipment conditions and the efficiency level and associated operational problems.
25 3.3.3.3
Post audit phase After the completion of the detailed energy audit the energy action
plan is prepared. These plans list-out all the energy conservation measures which are to be implemented first and suggest an overall implementation schedule. Detailed energy audit is incomplete without monitoring and associated feedback. Monitoring consists of collecting and interpreting data towards the goals set out in the energy action plan. Electrical and fuel power consumption must be evaluated and monitored on a regular basis to ensure the predicted energy savings. If the gap between planned objective and actual achievement is large reasons should be analyzed and corrective actions should be initiated to achieve the goals.
In this way the complete energy audit cycle is completed in an industry.
3.4
EMISSION ANALYSIS
3.4.1
Grid Emission Factor (GEF) The emission analysis is done to estimate the CO2 emission due to
electricity generation. This is arrived at by knowing the Grid Emission Factor (GEF). Having the data (fuel consumption and generated electricity) of each power plant serving the grid, GEF can be calculated according to the “Tool” provided by the Executive Board (EB) of the United Nations Frame work Convention on Climate Change (UNFCCC). The GEF is expressed as tons CO2 emitted per produced MWh [tonsCO2/MWh]. There is huge country specific differences in the value of the GEF dependent on the electricity generation mix. Thermal electricity generation with coal or diesel results in a higher GEF, natural gas in a lower GEF and more electricity is generated by renewable power sources (like in Brazil) the lower the GEF would be. The calculation of the amount of the Baseline Emissions (BE) generated per year is done by multiplication of the GEF [tonsCO2/MWh] with the additional
26 electricity produced [MWh], through efficiency improvement, which can be claimed as generated electricity. (Electricity saved=electricity generated) (CEA-Govt. of India, “CO2 Baseline Database for the Indian Power Sector” Version 6.00, 2011) Figure 3.1 shows the principle adopted in the calculation of Emission Reductions. tCO2 Saved Base line tCO2
tCO2 after efficiency improvement
Figure 3.1 Principle of calculating emission reductions Emission reduction (ER) = Baseline Emission (BE) – Emission after Efficiency Improvement (EAEI)
3.4.2
Description of the “Tool to Calculate the Emissions for an Electricity System” and Application of the “Tool” to India Since the emergence of the Kyoto Protocol and its Clean
Development Mechanism (CDM) energy projects lowering carbon intensity of the electricity grid through Demand Side management or by improving energy efficiency at end users have gained momentum to generate additional revenue through carbon trade. However, in order to facilitate adoption of authentic baseline emission data and also to ensure uniformity in the calculation of CO2 emission reductions, Central Electricity Authority (CEA), the custodian of all grid connected power stations, Govt. of India has compiled a database containing the necessary data on CO2 emission for all grid connected power stations in India.
The base line emission factor is estimated as per the
guidelines approved by the United Nations Frame work Convention on Climate Change (UNFCCC).
27 3.4.3
Data and Calculation Approach This section gives an overview on the base data, annual data as well
as the approaches used to calculate station –level and unit-level CO2 emissions. 3.4.3.1
Base data The base data contains the following parameters collected for all the
stations listed in the CO2 data base. • Sl. No of the station for unambiguous identification of stations • Name of the Station • Unit Number • Date of Commissioning • Capacity • Grid Zone. Indian grid is divided into two namely: NEWNE Grid represents Northern, Eastern, Western and North-Eastern region and SR represents Southern Grid. • Name of the State • Sector, this represents whether the station is operated by Central sector or State authorities or by the private sector • System, it represents the abbreviations and full names used in the data base • Type, this represents the type of station whether thermal, nuclear, hydro, DG • Fuel used, like coal, oil, Gas. Coal is indicated as Fuel 1 and oil as Fuel 2.
3.4.3.2
Annual data The following information is provided in the annual data column for
each station for five fiscal years 2006-7 to 2010.
28 • Net Generation in GWh • Absolute CO2 emissions in metric tones • Specific CO2 emission in t CO2/MWh CEA has compiled the CO2 Data base based upon generation, fuel consumption and fuel gross calorific value (GCV) data furnished by each power station. In cases where the station could not provide reliable data for all the relevant parameters, suitable assumptions were made which are elaborated in the User Guide Version 7.0 2012, Annexure-I ( User Guide Verson-7, 2012, CEA)
3.4.4
Calculation of CO2 Emissions Calculation Approach-Station Level
CO2 emissions of thermal stations are calculated using the formula below: ∑ , , (3.1) where,
Absolute CO2 emission of the station in the given fiscal year ‘y’
,
Amount of fuel of type i consumed in the fiscal year ‘y’
,
Gross calorific value of the fuel i in the fiscal year ‘y’
CO2 emission factor of the fuel i based on GCV
Oxidation factor of the fuel i
The oxidation factors used in the data base are given in the reference “User Guide Version -7, 2012.
29 The specific CO2 emission of stations was computed by dividing the absolute emissions estimated above by the station’s net generation as below:
మ
(3.2)
where,
Specific CO2 emission for station ‘y’ in t CO2/MWh
Net Generation in MWh
The result of the weighted average specific emissions for fossil fuel fired power stations in the two national grids are summarized below in Table: 3.1.
Table 3.1 Weighted average specific emissions for fossil fuel fired stations in FY 2010-11, in t CO2/MWh Sector
Coal
Diesel
Gas
Lignite
Naphtha
Oil
NEWNE
1.06
0.93
0.44
1.46
0.39
0.64
SR
1.00
0.54
0.43
1.43
0.61
0.65
India
1.08
0.55
0.44
1.44
0.39
0.64
Inter-grid variations arise chiefly from differences in station age and installed capacity and conversion technology.
Based on the database on CO2 emission the level of emission reduction through energy conservation at user end through demand side management is estimated using the eq. 3.3 Total Emission= [Total energy consumed in the process] x [Emission factor for the source of energy] x [1+ Energy equivalent to T&D loss for the energy consumed] Ej,y = ∑ ECpjy X EFj,y X (1+TDLj,y)
(3.3)
30 where, E j,y
=
Total Emission due to consumption of electricity from the source j for the year, y in tCO2
ECpjy =
Electricity Consumed in the process p from the source j, for the year y in MWh
EFj,y =
Emission factor for the electricity source j for the year y in tCO2/MWh
TDLj,y = Transmission and distribution loss for the electricity source j for the year y in MWh
Transmission and distribution losses are already included while calculating the emission factor. Apart from the above approach, CO2 emission is also calculated based on an average emission factor of 0.85 tCO2/MWh as suggested by Singhi & Bhargava (2010) and 316 tCO2/TJ as suggested by Reddy and Ray (2010).
3.5
SUMMARY Energy Audit is a practically acceptable methodology that gives
immediate benefit to the energy users in the form of energy and cost saving. The basic methodology of conducting energy audit is well defined and in India, the Bureau of Energy Efficiency (BEE) provides the complete guidelines of conducting energy audit and therefore employed primarily in this research work. Emission factor will be taken from the CO2 baseline data base published by CEA, Govt. of India for emission estimation.
31
CHAPTER 4 ENERGY AND EMISSION ANALYSIS IN A PAPER BASED INDUSTRY
4.1
INTRODUCTION A detailed energy audit was conducted in a paper carton
manufacturing unit, an energy intensive industry in India (M/S. Star Boxes Ltd, Chennai) to quantify the energy saving and emission reduction potential. The details of the energy profile, the methodology of conducting the detailed energy audit, the development of mathematical model and the outcome of the energy audit are discussed in this chapter.
4.2
METHODOLOGY The methodology of conducting a detailed energy analysis is
presented in Figure. 4.1. The process started with the identification of an industry on a convenient sampling method and as a first step the nature and type of energy carriers used were quantified by collecting data from electricity bills and fuel stock registers. The focus was mainly on utilities, the supporting system for the manufacturing process like motors, air compressors, boilers and lighting. Then actual measurements were taken using portable energy flow measuring instruments. The collected primary data were then analyzed for estimating the energy and the emission reduction potential. However a brief note on the manufacturing process is also presented here. The economic viability of implementing energy saving measures is then presented to make them acceptable to the industry.
32
Figure 4.1 Methodology of energy analysis
4.3
MANUFACTURING PROCESS OF PAPER CARTON BOX The manufacturing of corrugated paperboard is one of the largest
tonnage items of the paper packing industry. Apart from the fact that it is inexpensive to produce, corrugated paperboard is resistant to water, vapor, gases, oil, grease, mold, insects, rodents, corrosion and impact. Furthermore, because paper is an excellent medium for the printed word, such as advertising, corrugated paper boards and boxes have become the most popular type of packing and shipping cartons for radios, television sets, rugs, refrigerators, mattresses, furniture, and a number of other products including heavy machinery and equipment.
Corrugated paperboard consists of two structure elements. The facing, which is made from Kraft paper linerboard, can be easily purchased around the world. The process flow is shown in figure 4.2. The raw materials
33 needed for the fluting must be converted into corrugated paperboard by the corrugators. Next the corrugated board is slit and cut into the desired size. A flexography-printing machine is used to print the facing with whatever information that is desired. At this point the paperboard is prepared for assembly in one or more of the following ways. Die-Cutting dies are used to cut or punch out the size and shape of the corrugated paper desired. Stitching is used to connect the lap and the end of the sheet of a corrugated container. Gluing is similar to stitching but resin adhesive is used instead of metal wire. The paperboard is then folded or assembled into boxes. After being properly packed, the boxes are ready for shipping. Linear
Corrugated
Corrugating
Starch (Adhesive)
Slitting, Cutting Printing
Slotting,Scoring
Stitching
Ink
Die cutting,
Gluing Metal Wire
Assembling Adhesive
Packing
Product
Figure 4.2 Process flowchart of paper carton manufacturing
34 4.4
PROCEDURAL STEPS FOR ENERGY ANALYSIS Before conducting a detailed energy audit in the selected industrial
facility the following preparations were made. A meeting was held with the appropriate plant personnel familiar with the physical conditions and day-today operation of the manufacturing facility. The purpose of the meeting was to identify areas where the auditors’ attention should be focused during the detailed audit. Since the audit was carried out a second time in the facility, the focused area was limited to lightings, air compressors, electric motors, boilers, and co-generation. No specific questionnaires were prepared as the audit team was familiar with the facility. The audit team consisting of a qualified and an experienced electrical and mechanical engineer was formed.
The identified industry M/s. Star Boxes (I) Ltd is located in Chennai, Tamilnadu state, India.
The industry is a paper-based industry
established in the year 2006, a bulk manufacturer of paper carton boxes of various sizes from paper. The unit consumes electrical energy supplied by the Tamilnadu Electricity Board (TNEB) through grid. The thermal energy requirement for the unit is met by steam, generated using a biomass fuelbriquettes fired boiler. In case of power failure, a DG set of 500 kVA is used to meet the power requirement. The average annual production is 757 tons of finished products.
The audit work was started with a kick-off meeting as detailed below. (a)
An energy audit meeting was held with the facility manager/maintenance engineer to introduce an energy audit target and the members of the audit group. The facility manager then explained their manufacturing process and
energy-consuming
machinery
and
provided
maintenance records for review by the auditors.
operation
and
35 (b)
Following the meeting, visual observation of the various facilities, location and the accessibility of the measuring points was made.
(c)
A review of the operating manual vis-à-vis the operating parameters and the equipment specifications for every energy consuming equipment was made.
(d)
In addition to the facility inspection, the auditors discussed with the facility staff to review the implementation of suggestions made during the previous energy audit.
(e)
The instruments were verified for the calibration status by the facility manager, and counter checked with the online instruments installed in the facility to ensure measurement accuracy. The list of instruments used in this audit is shown in Table 4.1.
(f)
In the first stage, the electrical and fuel bill for the year 2009 was thoroughly analyzed, and the existing levels of the SEC were estimated. These are discussed in detail in Section 4.5.
Table 4.1 List of instruments and their specifications for conducting energy audit Sr. No.
Name of instrument and accessories
1
MECO make clip on power meter with CT 200 Amps & 1000 Amps
2
Anemometer (Lutron)
air flow- m/s
0.4 to 20 m/s
3
Infrared thermometer
Temperature in deg C
-32 to 550 deg C
4
Pressure meter (gauges)
Air pressure
0 to 25 bar
5
Tachometer (contact)
Rpm
100 to 29999
4.5
Measuring parameters volts, amps, kW, pF, kWh, Hz
specifications range up to 5A, 200A & 1000A
Accuracy V & I- 1%, kW & KWh 2% +/-(0.2 m/s + 2% of measured value) +/- 0.5 deg C +/- 0.03 kPa (0 to 30 kPa) +/- 3 rpm
DATA COLLECTION During the period of energy audit in the facility, all the equipments
on the production floor were counted and notes were taken on the rated power
36 from the technical specifications of the equipment and the operating hours per working day. The total working days in a year was also noted down.
The
data collected during the audit included: power rating and
operation time of energy consuming equipment/machinery; fossil fuel and other sources of energy use; production figure; peak and off-peak tariff usage behavior; and power factor. Then the actual operating data on power consumption, power factor, pressure, and temperature and air flow were measured using the portable instruments listed in Table 4.1. Data were collected for a period of one year, and instant power consumption was measured using portable instruments. Using these data, an analysis was carried out to investigate the end-use equipment/machinery energy use, equipment loadings, power factor trend and specific electricity consumption.
It may be mentioned that data collection by hand held meters (such as power meter, electric pliers) would be the best method to collect instant values. Data were measured on “Business As Usual” without making any changes in the operating conditions to help auditors make practically implementable and economically viable recommendations to reduce energy consumption. Any data which were assumed in the calculation of energy flow, and cost was a good estimate and based on what was actually happening in the field. To get a realistic value, the values were rounded off to the nearest whole number wherever possible. It will be more appropriate to use the best available data to take corrective actions immediately rather than waiting for more accurate data, which may delay the activity and result in wastage of energy and money .
4.6
DEVELOPMENT OF THE MATHEMATICAL MODEL All physical phenomena applied in analyzing energy consumption,
specific energy consumption, savings potential, compressed air leakage and
37 boiler efficiency are expressed below in the form of mathematical equations. Most of the equations have been taken from other sources and cited properly. Equations without references have been developed for this work. These mathematical equations are employed in all the analysis: Electrical and thermal specific energy consumption (SEC) can be estimated using Equations (4.1) & (4.2) as follows (Jayamaha, 2007): 12 P SEC e = ∑ m m =1 Qm
SECt = ∑
Fm × GCV Qm m=1
(4.1)
12
(4.2)
Electric energy used by industrial equipment can be estimated using Equation (4.3)
AEU e = ∑ n × Pi × Ti × Dy n
(4.3)
i =1
Thermal energy used by industrial equipment can be estimated using Equation (4.4)
AEU t = ∑ n × Fij × GCV j × T i × D y n
i =1
(4.4)
Simple payback period for different energy saving measures can be calculated using Equation (4.5) without considering the salvage value. Equation (4.6) is used to calculate the payback considering the salvage value (Saidur et al 2011) SPB =
IINR ACS INR
(4.5)
SPB =
IINR - SV INR ACSI NR
(4.6)
38 The estimation of compressor energy consumption, generation capacity and compressed air leakage can be estimated using Equations (4.7)(4.10) (EEE, 2006):
AECc = ∑ [(Pl × TL + Pul × TU ) × D y ]
∆P × Vr ACC = Patm × T
T l × 100 CA l (%) = T l + Tu
(4.7) (4.8)
(4.9)
P EL al = CFMa × ( La − Lua ) × × T × Dy (4.10) CFM
Boiler efficiency can be estimated using Equation (4.11) (Jayamaha, 2007):
η=
Qs − Q f m f × GCV
(4.11)
The corresponding CO2 emission is estimated using the eqn. (4.12) n
CO2Emission = ∑ESi*EF
(4.12)
i =1
where ESi energy source i electricity or fuel wood/Briquette and EF is Emission Factor for the fuel type. EFe = 1.08 tCO2/ MWh and EFw = 1443.67 kg/ton. EFe is the emission factor for electricity use and EFw is the emission factor for biomass fuel (wood /Briquette). (Source: Central Electricity Authority, Govt. of India).
39
4.7
DATA ANALYSIS The annual energy consumption of the unit is shown in Table 4.2.
Table 4.2 Sources of energy and their contributions Sources of Energy
Value
Electrical energy including grid and self generated (MWh)/
831
Biomass fuel-wood/briquettes (Ton)
1141
Diesel (kilo liter)
125
The average energy cost is found to be INR4.70 per kWh for purchased power and INR 18.40 for power generated by a DG set (Cost of diesel is taken as INR 50 per lit). During peak hours, the grid supplier imposes power cut or restrictions on the use of electricity. The plant operates DG sets during peak hours only. However, due to increase in fuel price, the unit changed its working hours to off-peak hours. The plant has started its production only in 2006, and the benchmarking of its energy consumption has to be made based on the annual average specific energy consumption. In this study, various options for reducing energy consumption and thereby specific energy consumption are discussed as well. The facility consumes both electrical and thermal energy as shown in Table 4.3.
Table 4.3 Annual energy consumption in the plant Energy carrier
Annual consumption
Electrical Biomass fuel (wood/briquettes)
490 1141
Diesel (Sp. Gravity. 0.85)**
125
Units MWh Ton Kilo liter
**GCV in kJ/kg *(kJ/kWh) 3600 12,550
1766 14,329
39,750
4241
Total
20,336
Total (MJ)
* For electrical units consumed ** BEE Guide book for energy auditor and manager, Govt. of India
40 Different types of energy used to operate the plant for the year 2009 are shown in Table 4.4. The share of each fuel source in a common energy unit is shown in Figure 4.3.
Figure 4.3 Share of energy carrier in the facility
Biomass fuel contributes 68.65% of the energy requirement of the facility followed by diesel (22.89%) and electricity (8.46%). Electrical bills for the period Jan-2009 to Dec-2009 are analyzed and it was observed that the plant’s contracted demand was 500 kVA for grid supply and the restricted quota was 265 kVA per month. The unit maintained its demand within the restricted quota to avoid penalty. The plant has maintained the power factor at an average value of 0.99 and received financial incentives every month from the grid supplier. The average cost of power, including all taxes and charges, was found to be INR4.70 for grid supply. The plant should consider reducing the peak hour energy consumption and increasing night hour (i.e. off peak usage hours) energy consumption to reduce the financial implications of the total energy cost. The specific energy consumption of the plant is estimated as follows: Electricity
:
91.85 kWh/ton (304 MJ/t)
Biomass
:
0.13 ton/ton (5.2MJ/t)
Table 4.3 shows an overview of the energy use, the types of energy, production figure and specific energy consumption of the pant for the year 2009.
41
Table 4.4 Energy consumption details for the year 2009 Month (2009)
FW Consumption (t/m)
EB (kWh)
TNEB cost (INR)
CGP/ kWh (INR)
DG ( kWh )
Diesel/m (l)
DG power (l/ kWh)
Jan
98.3
26,424
194,102
7.35
13,160
4130
0.31
Cost of DG power (INR) 15.691
Feb
96.7
25,620
180,742
7.05
26,280
9420
0.36
Mar
89.1
27,240
346,151
12.71
25,820
9110
Apr
96.2
21,078
161,692
7.67
41,460
May
72.1
28,458
206,968
7.27
Jun
83.1
51,378
282,959
Jul
79.5
54,090
Aug
71.2
Sep
Total energy ( kWh )
Total P rod
SECe (kWh / ton)
SECe (MJ/ton)
SECt (MJ/Ton)
39,584
539
73.44
264.38
2290.26
17.922
51,900
574
90.42
325.50
2115.61
0.35
17.641
53,060
581
91.33
328.77
1925.85
14,300
0.34
17.246
62,538
708
88.33
317.99
1706.33
34,060
12,600
0.37
18.497
62,518
606
103.17
371.39
1494.11
5.51
20,980
8060
0.38
19.209
72,358
636
113.77
409.57
1640.83
N/A
0.00
18,720
7562
0.40
20.198
72,810
835
87.20
313.91
1195.64
44,130
267,525
6.06
29,700
11,670
0.39
19.646
73,830
776
95.14
342.51
1152.23
87.3
47,868
278,606
5.82
30,420
13,420
0.44
22.058
78,288
906
86.41
311.07
1210.06
Oct
137.7
53,034
298,170
5.62
32,380
11,700
0.36
18.067
85,414
1009
84.65
304.74
1713.81
Nov
140.16
61,626
N/A
0.00
38,649
12,600
0.33
16.301
100,275
1123
89.29
321.45
1567.35
Dec
89.7
49,548
284,621
5.74
29,100
10,890
0.37
18.711
78,648
794
99.05
356.59
1418.71
Total
1141.06
490,494
2,307,434
-
340,729
125,462
-
-
831,223
9087.00
-
-
-
41
42 The trend of specific energy consumption for the thermal and electrical in a common unit (MJ/ton) along with monthly production figures for the year 2009 is presented in Figure 4.4.
Figure 4.4 Trend of specific energy consumption and production
The maximum value of 113 kWh/ton was reached when the production was 636 tons in the month of June 2009. The minimum value of 84.65 kWh/ton 65 kWh/ton was reached in October-2009 when the production was at 1009 tons. The electrical SEC is showing a stabilized trend, and the thermal SEC is showing wide variations. It implies that the unit is unable to optimize the demand and supply for the process steam.
The plant has rescheduled its operation time to reduce diesel consumption for power generation. The diesel consumption for power generated is estimated at an average value of 0.37 l/kWh. The share of selfgenerated power in the total electrical energy consumed is estimated to be 40%. Shares of DG and grid power are presented in Figure 4.5. The power cut was heavy during the month of April, and the share of the DG power went to upto 66% and remained at 50% in February and March 2009. The average cost
43 of the DG power is estimated to be INR 18.43, and it certainly imposed a heavy financial burden on the plant during grid failure.
Figure 4.5 Share of self generated and grid power consumed during 2009
4.8
ENERGY SAVING OPPORTUNITIES This section explains how energy saving potential is quantified in
various energy consuming equipment. In the present analysis lighting, air compressor, electric motors and boiler were considered. The details of the analysis are presented in the following sections.
4.8.1
Analysis on Lighting The plant has installed mercury lamps in the factory shed. Different
operating parameters for lighting are measured and presented in Table 4.6.
44
Table 4.6 Operating parameters for lighting Sl.No 1 2 3 4 5 6
Measured parameters Total load Demand Voltage Current Daily usage time Annual operation
Unit KW KVA V A hr Days
Value 47.34 56.9 233 74.27 5 300
Based on the operating parameters observed, the following two categories of energy saving options can be implemented economically:
4.8.1.1
Reducing supply voltage The supply voltage can be reduced to 210 V, which is sufficient for
lighting. This can be done by installing a servo stabilizer of capacity 60 kVA. This measure will reduce the energy consumption by 10%. The reduction in illumination level will be negligible. Using Equations (4.3) and (4.5) the energy consumption, savings and payback period for implementing this measure are estimated as follows. Present power requirement
=
47.34 kW
Anticipated power reduction@10%=
4.734 kW
Annual energy saving
=
4.734 × 5 hour × 300 = 7101kWh
Equivalent cost savings/annum
=
7101 kWh × 4.70 = INR 333,745
Investment for a 3-phase voltage stabilizer with ratings of 60 kVA and 100 Amp is considered to be approximately INR 200,000 Payback for the investment
=
200,000/333,745
=
0.6 years
45
4.8.1.2
Installation of energy efficient lamps All existing high pressure mercury vapor lamps with a capacity of
400W each can be replaced with low pressure sodium vapor lamps with a capacity of 250W each. Since the plant does not need a high color rendering index, the existing HPMVL can be replaced with 250W HPSVL. It has to be noted that the plant has a printing section which needs the white light. There are 25 lights installed in the printing area and therefore, the actual number of HPMVLs to be replaced is only 73. A comparative efficiency analysis of different lighting sources is presented in Table 4.7.
Table 4.7 Comparison of lighting performance parameters for different types of lightings (ES, 2010)
Lighting Type
Efficacy (lumens/watt)
Standard "A" bulb Tungsten halogen
10–17
Straight tube
30–110
Compact fluorescent lamp (CFL) Circline
50–70
Mercury vapor
25–60
Metal halide
70–115
High-pressure sodium Low-Pressure Sodium
50–140
12–22
40–50
60–150
Color Rendition Index (CRI) Incandescent 750– 98–100 2500 (excellent) 2000– 98–100 4000 (excellent) Fluorescent 7000– 50–90 (fair 24,000 to good) 10,000 65–88 (good)
Lifetime (hours)
12,000
Color Temperature (K)
Indoors/ Outdoors
2700–2800 (warm) 2900–3200 (warm to neutral)
Indoors/outdoors
2700–6500 (warm to cold) 2700–6500 (warm to cold)
Indoors/outdoors
65–88 2700–6500 (good) (warm to cold) High-Intensity Discharge 16,000– 50 (poor to 3200–7000 24,000 fair) (warm to cold) 5000– 70 (fair) 3700 (cold) 20,000 16,000– 25 (poor) 2100 (warm) 24,000 12,000– -44 (very 2100 (warm) 18,000 poor)
Indoors/outdoors
Indoors/outdoors
Indoors
Outdoors Indoors/outdoors Outdoors Outdoors
46 Using Equations (4.3) & (4.5) energy saving and payback are estimated below: No of HPMVLs installed
73
Rating of a lamp
400 W
Rating of a HPSVL
250 W
Annual power saved by replacing 73 HPMVLs for 5 hours operation per day = (400-250) ×73×5×300 = 16,425 kWh Cost savings @INR 4.70/kWh per annum
= 16,425×4.70 = INR 77,197
Investment required for replacing 73 lamps @ INR 2500/lamp = INR 182,500 Simple payback period
= (182500/77197) = 2.36 years
4.8.2
Analysis on Air Compressor The plant uses compressed air for various pneumatic operations in
the facility. Compressed air is generated through a screw compressor with a capacity of 135 cfm. The rated capacity of the motor is 22 kW. The plant is operated for two shifts in a day (16 hours/day). Estimation of compressor power consumption, generation capacity and compressed air leakage were done using Equations (4.7), (4.8) & (4.9). It has to be noted that air in the receiver is at room temperature. Estimations are shown as below: Maximum pressure
=
7 bar
Atmospheric pressure
=
1 bar
Power consumed during loading
=
22×0.97 = 21.34 kW
Power consumption during unloading
=
2.5 kW
Compressor on load time (%)
=
35%
Compressor on no load time (%)
=
65%
47 Annual energy consumption
= (21.34×0.35+2.5×0.65) ×16×300 = 43,651.2 kWh
Time of filling (1 m3 receiver at 7 bar)
= 97.11 s
Actual cfm generated by a compressor
= [(7-1)/1] × [1/97.11] ×3600×0.59#
(# Conversion factor from m3/hr to cfm) = 131.23 cfm Compressor on load time
= 31 seconds
Compressor on no load time
= 57 seconds
Compressed air leakage (%)
= 31×100/ (31+57) = 35%
The compressor is set to operate in the pressure band of 6.5 and 7.0 bar. The capacity test was conducted, and it was observed that the compressor generates 131.23 cfm (Equation 4.1) which is 97.20% of the rated capacity. The air leakage test was conducted, and it was observed that the plant air leakage is at 35% (45.9 cfm). The unavoidable loss in an industry should not be more than 10% (13.1 cfm). Therefore, the loss should be reduced by 25%. The leakage points can be identified by visual observation or by conducting the soap tests (a general maintenance practice to identify leakage points in the air lines). The leaking points can be rectified by replacing the damaged parts with new ones like air nozzles, tightening the loose connections, etc.
Energy loss due to air leakage can be calculated using the Equation (4.10). Energy loss due to air leakage per annum = (21.34/131.23) × (45.9-13.1) ×16×300 =
25,602 kWh
48 Cost saving/annum
Investment
=
25,602×4.7
=
INR 120,330
=
Nominal (labor & minor replacements only)
Hence investment cost is considered to be nil. Therefore the payback period is immediate.
Leaks can be a significant source of wasted energy in an industrial compressed-air system, sometimes wasting 20–50% of a compressor’s output. An unmaintained plant will likely have a leak-rate equal to 20% of the total compressed-air production capacity. Other than a source of wasted energy, a leak contributes to other operating losses; it causes a drop in system pressure, making air tools function less efficiently, affecting production. In addition to increased energy consumption, leaks can make air tools less efficient and adversely affect production, shorten the life of equipment, lead to additional maintenance requirements and increase unscheduled downtime. Leaks cause an increase in compressor energy and maintenance costs.
4.8.3
Analysis on Motor Industrial motors use about 30-70% of the total industrial energy
consumption in most of the industrial and developing countries. Therefore, there is tremendous energy saving potential for electrical motors by applying energy saving strategies such as the use of VSD in places where load variations are considerable. A sample load survey was conducted on selected motors, which are listed in Table 4.8.
49
Table 4.8 Load survey on electrical motors S. No.
Location
Rated capacity (kW) 29.84
Pf
kVA
0.86
27.6
Actual Capacity (kW) 24.5
Load (%)
Running hr/day
MWh/yr
Remark
82.1
16
117,600
Good
1
Boiler ID fan
2
Feed water pump
5.6
0.98
3.9
5.02
89.72
10
15,060
Good
3
FD fan
5.6
0.96
3.94
2.75
49.15
10
8250
Under loaded
22.38
0.75
19
14.76
65.95
14
61,992
Low Pf
-
0.94
22.43
20.27
80
10
60,810
AC total load
22.38
0.85
18.7
16.6
74.17
15
74,700
Satisfactory
22.38
0.8
16
12.8
57.19
15
57,600
Under loaded
18.65
0.72
12.99
9.1
48.79
15
40,950
4 5 6
7
Printing disposal paper motor A/C load DB B-Flute suction motor C-Flute suction motor Corrugated
8
dispose paper suction motor
Total energy consumed
Under loaded and low pf
436,962
49
50 It was observed that many of the motors were working at satisfactory conditions. However the motors attached to the FD fan and the corrugated paper suction were found to be under loaded. The printing paper disposal suction motor had poor pf of 0.76. The ID fan was poorly loaded because the boiler was not in operation at the time of load measurement. The performance of the printing paper disposal suction motor should be studied in detail by measuring the pressure developed and the required pressure for drawing the papers. A 10 kVAr small capacitor may be connected to the motor to improve pf.
4.8.4
Analysis on Boiler Most of the heating systems, although not all, employ boilers to
produce hot water or steam. Since industrial systems are very diverse, but often have major steam systems in common, it makes a useful target for energy efficiency measures. The plant had installed a 4 ton wood fired packaged boiler with 3 passes. The present operating parameters of the boiler are: Fuel consumption
:
2.5 to 3.0tone/shift
Rated steam pressure.
:
12 bar
Pressure (actual)
:
8 bar (saturated steam)
Steam generation
:
1.5 ton/hour
Draft
:
Balanced draft
Combustion air
:
Preheated through WHRS
Flue gas temperature
:
2000C after WHRS
Flue gas temperature
:
2700C (at boiler exit)
Feed water temperature
:
800C
Operational and fuel consumption data of the boiler is presented in Table 4.9.
51
Table 4.9 Operation and fuel consumption data of boiler Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
FW FW/ton Boiler running time consumption of ( hr) ( ton) steam 98 200 182 97 224 168 89 210 153 96 279 136 72 205 119 83 249 131 80 275 95 71 247 92 87 288 96 138 309 136 140 381 125 90 278 113 t t 1141 3145 128* t *Average values; Total values
SECt (MJ/Ton) 2290 2116 1926 1706 1494 1641 1196 1152 1210 1714 1567 1419 1619*
The analysis showed that boilers are underutilized as load is about 37.5%. It is known that part load efficiency of a boiler is quite low. Reduced load will have the following effects on thermal efficiency:
• The mass flow rate of flue gas through tubes gets reduced when the load falls. This will result in a slight reduction in the flue gas exit temperature. As a result sensible heat loss will be slightly reduced.
• If the load is reduced below the 50% of the rated value, more excess air will be needed to burn a fuel completely. This will lead to an increase in the sensible heat loss.
In general, the efficiency is reduced significantly if the loading goes below 25%, and the optimum efficiency occurs at 65-85% of loading. In this study, the thermal efficiency of the boilers was estimated using Equation (4.11) and it was found to be 87%. Since the boiler was operated at the
52 reduced pressure of 8 bar compared to the rated pressure at 12 bar, loss due to reduced load will be lower. The specific thermal energy consumption was estimated and found to be 1619 MJ/ton of product.
The plant had installed a water softening unit and condensate return and flash steam recovery systems. The TDS of the boiler water was maintained within the recommended value of 3000 ppm. Blow down was done two times in a shift for one minute per blow down. The underutilization of the boiler (load is about 37.5%) resulted in higher fuel consumption. Therefore to minimize the fuel consumption the boiler should be de-rated by blocking 20% of the fire tubes or by reducing the grate area by 10% in consultation with the manufacturer to improve loading and hence the overall efficiency. The corresponding fuel saving is estimated at 3%, which comes to 34 ton/annum as per discussion held with one of the manufacturers of industrial boilers M/s Ansaldo Caldaie Boilers India Pvt. Ltd. The estimated energy and emission reduction are summarized in Table 4.10.
53
Table 4.10 Estimated energy and CO2 reduction potential Energy System Air compressor Motors
Unit
Quantity
Cost INR/Yr
MWh
25.60
120330
Investment INR -
Payback (m) Immediate
tCO2 Saving 27.65
No significant Saving potential Identified Lighting
(1)
Energy Eff. Lighting
MWh
16.43
77197
182500
28
17.74
(2)
Reducing Voltage
MWh
7.10
33375
200000
72
7.67
Ton
49.13 34.23
230901 85575
382500 500000
20 70
53.06 49.41
34.23
85575
500000
70
49.41
Total (E)* Total (T) Briquette
Total (T)** * E- Electrical ** T- Thermal
54 The plant can reduce its electrical energy intensity from 91.85 to 86 units/ton on “BAU” by implementing the energy saving measures identified in this study. The reduction in the energy intensity will be 6.36%. The unit is facing difficulties in matching the steam supply as well as the demand. The boiler is underutilized. It requires a detailed study to match demand and supply. The plant has installed a good condensate recovery system. Waste heat from flue gas is recovered to heat the combustion air, and thus it has adopted significant energy saving measures in the boiler section.
The unit has a total of 49.128 MWh of electrical energy saving potential, which comes to 5.9 % of the total (831.223 MWh) electrical energy consumption. The un-arrested compressed air leakage is a continuous threat for the environment although it may seem minor. In this case, the air leakage accounts for 25.602 MWh of electricity per annum which alone accounts for 3% of the total electrical energy consumed, which is almost equal to 50% of the total energy saving identified.
The plant has stabilized Specific Energy Consumption (Electrical) at an average value of 91.85kWh/ton (330.66MJ/ton). However the steam consumption is yet to be optimized. At present, the value fluctuates from as high as 182 kg of briquette/ton to 91.75 kg of briquette /ton. The average value of the SEC (T) is estimated to be 129 kg of wood/briquettes per ton of product (1619 MJ/ton of product). The estimated power saving in lighting is 23.526 MWh per annum and the investment required is INR 382,500. The payback for the investment is 3.5 years. Installation of energy efficient HPSVL provides lucrative saving opportunity in terms of energy (16.425MWh/annum) and cost (INR 77197). The payback for the investment is found to be only 2.3 years.
55 4.9
SUMMARY The analysis showed that the major share of the plant energy
requirement is met by thermal energy (68%) followed by electrical energy (32%). Therefore, it can be concluded that the industry is thermal energy intensive. The study revealed that compressed air leakage is the source of major energy loss. The study can be extended to other energy intensive industries using a compressed air system to reduce energy loss through reducing air leakages in addition to other options identified.
56
CHAPTER 5 ENERGY AND EMISSION ANALYSIS IN CEMENT INDUSTRY
5.1
INTRODUCTION A cement industry was identified from the data bank of annual
energy conservation award winners from the web site www.energymanager training.com. The annual award is given by the Govt. of India through the Bureau of Energy Efficiency (BEE), Ministry of Power and how the energy efficiency index helps an industry to forecast the saving potential is demonstrated in this chapter. The results of the analysis are presented in terms of energy and energy related CO2 emission.
5.2
ENERGY PROFILE The identified cement industry M/s Jaypee Cement factory is
located in J.P. Nagar, 14 km from Rewa city of Madhya Pradesh in India. The first line (Unit-I) of production was commissioned in 1986 with an annual production capacity of 1 million tons. The second line of production (U-II) with a capacity of 1.5 MTPA was commissioned in the year 1991. Unit one (U-I) was upgraded to improve the energy efficiency and re-commissioned in 2004 with an enhanced capacity of 1.5 million tons per annum. It was then the largest cement manufacturing facility in the country. Continuous in-house improvements and further modernization have helped the plant to raise its annual capacity to 3.5 million tons. The plant has set up a captive power plant (CPP) with a capacity of 25MW in 2003 and another with a capacity of 38.5 MW in 2006. The plant has its own two captive limestone mines situated
57 at a distance of 4 to 5 km apart from each other. The plant manufactures cement using a fully automated dry process. The plant is the most modern with the state-of-art technology in the country. It is assumed that the plant produces only Portland cement with standard specification as per the Bureau of Indian Standard. The plant has established an energy management cell to reduce its overall energy intensity.
5.3
ENERGY CONSERVATION STATUS The plant has its own energy cell to take care of the energy
conservation efforts within the industry. The achievements in energy saving are tabulated in Table 5.1.
Table 5.1 Summary of energy consumption, specific energy consumption, and energy cost (M/s. JayPee Cements) Specific power consumption details Annual cement production Total electrical energy consumption per annum
Units
2005-06 2006-07 2007-08
ton
2,819,000 3,207,000 3,253,000
MWh
311,912 339,372 338,190
kWh/MT cement Specific thermal energy consumption GJ/ton Specific energy consumption
92.9
89.9
88.1
3.24
2.85
2.81
It is observed from the data presented in Table 5.2 that the plant reduced its electrical energy consumption from 92.9 to 88.1 kWh/ton in a period of three years and bringing it close to the national average value (i.e. 88 kWh/MT) as shown in Table 5.2.
58 Table 5.2 Comparison of electrical and thermal SEC for a few selected countries around the world for the year 2004 [9] Country
Electrical SEC (kWh/t)
India
88
Spain
92
Germany
100
Japan
100
Korea
102
Brazil
110
Italy
112
China
118
Mexico
118
Canada
140
US
141
It was also observed that the plant has reduced its SEC in 2008 by 5.4% compared to 2005. It seems that the cell’s activities are effective in reducing the plant’s overall electrical energy consumption. The plant has identified energy saving measures in two major categories namely (i) without investment and (ii) with investment. The identified areas are listed in Tables 5.3 and 5.4
59 Table 5.3 Energy saving measures without investment
S. No.
Details of energy savings activities
Energy savings (MWh/yr)
Bill savings (INR)
Optimizing the main transformer load by switching off 1
1 transformer. This resulted in savings of 25kWh per
219
714,000
268
875,000
134
438,000
94
308,000
48
158,000
10
33,000
71
230,000
146
477,000
688
2,224,000
72
235,000
712
2,322,000
69
224,000
hour 2
Reducing operating voltage from 433 V to 422 V of a distributed transformer at a crusher Reducing operating pressure of a plant packaging
3
compressor from 5.86 bar to 5.38 bar for loading and 6.9 bar to 5.86 bar for unloading conditions
4
5
6
Increasing pressure drop up to optimum level for bag filters Avoiding idle operation of a flash conveying compressor Improving the power factor from 0.53 to 0.90 by installing a capacitor bank of 2 × 60 kVAr Optimization of operation of FAD ESP heaters by
7
installing a new thermostat for an in-house insulator heater
8 9
10
11
Minimizing air infiltration in a coal mill circuit Avoiding damper loss by improving maintenance of 2 fans Reducing speed of a silo aeration blower in an old packing plant DBC drag chain de-dusting pipe line connected to cooler ESP and it’s bag filter & fan was stopped Clinker yard tunnel pan conveyor de-dusting BF Fan
12
(511 FN2) pulley replaced to reduce BF fan speed, to avoid damper losses
60
S. No. 13
14
15
Details of energy savings activities CM-4 hopper top BF Fan (511 FN8) pulley replaced to reduce BF fan speed, to avoid damper losses CM-3 Reject BF Fan (553 FN7) pulley replaced to reduce BF fan speed to avoid damper losses CM-4 Spool BF Fan (554FN6) pulley was replaced to reduce BF fan speed, to avoid damper losses
Energy savings (MWh/yr)
Bill savings (INR)
49
159,000
80
261,000
64
209,000
56
184,000
120
391,000
208
678,000
4
12,000
1223
3,990,000
4335
14,122,000
Cement Silo-1 top BF (591BF-1) fan pulley was 16
replaced to reduce BF fan speed, to avoid damper losses
17
18
CM-4 WF BF (534BF1) fan pulley was replaced to reduce BF fan speed, to avoid damper losses CM-4 WF BF (534BF1) fan pulley was replaced to reduce BF fan speed, to avoid damper losses GCT bottom screw conveyor (No- 46) was replaced
19
with old Enmass conveyor (spared from U-1 cooler ESP bottom)
20 21
A DC drive was installed in CID Fan in-place of GRR & AC motor Total
(Energy conservation award winners presentation, BEE, Govt. of India, 2009)
61 Table 5.4 Energy saving measures with investment S Details of energy savings No activities
Energy savings (MWh/yr)
Bill savings (INR)
Investment (INR)
Payback period (yr)
A new water spray system with variable frequency drive installed for 1 20 66,000 731,000 11 controlling mill outlet temperature at cement mill # 4 for Unit 2. A fly ash dryer ESP was modified to a precipitator 2 58 188,000 2,207,000 12 type filter (i.e. ESP + bag filter). A coal mill classifier was replaced with new classifier. A hot air 3 cyclone dip tube was 123 401,000 4,000,000 10 replaced. Mill ‘sold duct was replaced to a cyclone duct A demand side controller installed for CPT – 4 compressor and old 116 379,000 640,000 2 compressor for cement mills A V/F drive was installed 59 193,000 1,473,000 8 in 3 cooler fans for Unit 1 A new single DC drive for Kiln was installed in6 122 399,000 3,100,000 8 place of a twin DC drive for Unit 2. Total 498 1,626,000 12,151,000 (Values are rounded off to whole numbers) (Energy conservation award winners presentation, BEE, Govt. of India, 2009)
62 The total estimated energy savings without investment was 4335 MWh/annum which has resulted in a direct cost saving of INR14.12 billion/annum. It will reduce about 4681 ton of CO2 emissions for the above savings. This was calculated based on an average emission factor of 1.08 tCO2/MWh recommended by the Central Electricity Authority of India. The quantum of electricity saving with investment was estimated at 498 MWh per annum with an investment of INR 12.151 billion and the corresponding saving in CO2 would be 537.84 ton/annum. Payback periods are found to be within 2 to 11 years for identified energy saving measures. It has been found that a demand side controller installed for the compressor plant (CPT) is economically very viable as the payback period is very short. Energy saving options 5 and 6 in Table 5.4 are also found to be economically viable.
5.4
MATHAMATICAL FORMULATION The Energy Efficiency Index can be estimated using Equation (5.1).
SECp EEI = 100 SECref
(5.1)
In which SECp is the specific energy consumption for sector p and SECref is the reference specific energy consumption for the sector p. Since the best value pertains to a single industry it may not be possible for every industry to achieve the same. Therefore, the authors prefer to consider the average value of SEC by taking into account the top 25 industries at the national level (Source: Bureau of Energy Efficiency, Govt. of India).
5.5
RESULT AND DISCUSSION The energy efficiency index of the plant is compared with the
national average for the year 2005-2008. By using equation (5.1), the energy
63 efficiency index for electrical energy was estimated to be 117.15 for the year 2007-08 and is presented in Table 5.5. It was found that the plant has achieved a saving potential of 1.42%. The absolute quantum of saving identified is 4833 MWh which includes measures with investment and without investment. The further available scope is 15.73%, which comes to 49,278.6 MWh/annum. Since the data on energy savings identified for the year 2005-06 and 2006-07 are not available, the actual savings achieved in the respective years could not be estimated to compare the energy saving achieved with respect to the previous year. Table 5.5 Energy Efficiency Index (EEI) and relative energy saving potential (Jaypee cement)
Year
National Best (SEC)*
Actual for Jaypee (SEC)*
Energy Efficiency Index
Available Scope for energy saving (%)
% Reduction in Energy consumption
2005-06
77.5
92.9
119.87
19.87
-
2006-07
76.4
89.9
117.67
17.67
-
2007-08
75.2
88.1 117.15 17.15 * Specific Energy Consumption
1.42
The plant’s specific energy consumption (SEC) was estimated to be 88.1 kWh/ton of cement and the national average best value was found to be 75.2 kWh/ton of cement. Based on this information, the relative Energy Efficiency Index for the selected industry was found to be 117.15 indicating an energy saving potential of 17.15%. It may be stated that the plant could reduce its energy consumption by 4833MWh (i.e. 1.42%) per annum. However, the plant still can reduce its annual energy consumption by 52,676 MWh to reach the national average value as estimated using the concept of EEI.
64 5.6
SUMMARY The methodology of identifying the relative position and saving
potential using the Energy Efficiency Index for cement manufacturing has been demonstrated. The methodology discussed can be adopted in other energy intensive industrial sectors too.
65
CHAPTER 6 CFD ANALYSIS ON COMPRESSED AIR PIPE LINE WITH REFERENCE TO T- JUNCTION AND ELBOW
6.1
INTRODUCTION In recent times the energy analysis has become a mandatory activity
in industries to conserve carbon based conventional energy sources. Many countries have made it mandatory for energy intensive industries by introducing policies, rules and regulations. This has become imperative in the context of the fast depletion of these energy reserves and the threatening menace of climate change and global warming. In this work an attempt is made to demonstrate how the numerical method helps to make a critical analysis. It is otherwise not possible to dig out and quantify the hidden energy saving potential.
6.2
CFD- ANALYSIS The pressure pattern across a junction and bend in a compressed air
pipe is studied using computational fluid dynamics (CFD). The simulation of pressure gradient is made and the corresponding energy and emission savings are estimated. A complete CFD analysis involves the following three stages: Pre-processing
Solving
Post- Processing
The pre-processing stage consists of determining the governing equations to be solved, specifying the boundary conditions and generating a computational mesh. The pre- processing depends on the desired output of the simulation and the capability of the solver. The solving stage involves the
66 identification of a suitable computational tool considering the nature of the flow, turbulent or laminar and the complexity of flow pattern. In most of the cases for turbulent flow modelling the standard two equation model is used [20].
Post-processing involves the analysis of pressure change and the flow pattern is visualized to arrive at an efficient design of pipe network which gives the minimum pressure loss and saves energy and reduces the CO2 emission.
In this work input study and modelling of geometry was done using CATIA V5 R20, pre-processing and meshing was done using ANSYS WORKBENCH V12 and simulation was carried out with CFX V12 solver.
6.3
TURBULENCE MODELS The following two equations turbulence models are available in
ANSYS CFX: • Standard k-ε model • RNG k-ε model • The k-ω model • The Wilcox k-ω model • The Baseline k-ω model A detailed discussion on each of the above models is out of the scope of this research; however among all the above models the most commonly used model to describe the turbulent behavior of fluid flow is the kepsilon, first proposed by A.N. Kolmogrov (1942), then further refined by Harlow and Nakayama, who finally proposed the model for the fully turbulent
67 flow and is widely accepted for modeling turbulent flow.
The
model
includes two transport equations (6.1 & 6.2). The transport equation for (k)
(6.1)
The transport equation for (ε)
(6.2)
where C ,C , σ , σ are constants. P and P represent the influency of
buoyancy forces which is neglected in the present analysis.
The default values for the model constant which are arrived at by the best data fitting method for various range of turbulent flow are, . , . , . , .
The first transported variable is turbulent kinetic energy (k); the second transported variable is turbulent dissipation (ε). These variables determine the scale of the turbulence and the energy in the turbulence. Free length of 1000 mm downstream of the pipe after the junction is considered for ensuring the fully developed flow. The analysis is made for various pressures and the chosen cases for the simulation are shown in figures. 6.1 (a & b)
(a) T – Junction
(b) L- junction
Figure 6.1 Existing junctions in pipes transporting compressed air
68 6.4
PROBLEM DEFINITION The identified T and elbow are shown in Figure 6.2. The straight
line shows the existing geometry of the junction. The flow for T junction is split flow and for the elbow it is straight flow. The variables studied are the angle θ for T junction and fillet radius r for the elbow. The objective of the study is to find the best angle (θ) and the best fillet radius (r) which gives the minimum pressure drop across the junctions. In both cases the main pipe diameter is assumed to be 50 mm (ID) and for branch in T junction is assumed to be 25 mm (ID), with an area ratio of 4. Compressed air velocity is assumed to be 10 m/s and the flow rate in the main pipe is 100% and for the branch it is 10%. Hence the exit flow in main pipe would be 90% of the inlet flow for T junction. The calculated flow rate in the main pipe is 0.0197m3/s and in the branch 0.002m3/s. The calculated Mach number is 0.03 which is less than 0.2 and hence the fluid can be considered incompressible. The calculated Reynolds number is 31219 which is greater than 4000 showing that the flow is turbulent. The simulation is carried out for three values of inlet pressures 4, 6 and 8 bar. Flow θ
r
r
Existing Suggested
Figure 6.2
The existing and the suggested geometry for T and elbow
69 6.5
MATHEMATICAL EQUATIONS TO ESTIMATE ENERGY AND EMISSION SAVING The energy saving potential is estimated as follows if the above
research findings are implemented in the compressed air pipe network. The energy required for compressing air adiabatically from and above atmospheric pressure using a screw compressor is estimated using the eq. (6.4)
!"
#$
(6.4)
where Q1 if flow rate in m3/h Energy recovered due to change in angle θ for branching and fillet
radius (r) for elbow is estimated using eq. (6.2). % ∑'() ! & & " # $*
(6.5)
where ‘j’ is junction, elbow Er is energy recovered in MWh due to change in the design of junctions, & = Adiabatic power equivalent to the exit pressure
of junction when θ1, & = Adiabatic power equivalent to the exit pressure of
junction when θ1 , n= no of junctions, H= Hours of operation, Dy = No of days of the year y. The corresponding CO2 emission is estimated using the eqn. (6.6) n
CO2 Emission= ∑ESi*EF
(6.6)
i =1
where ESi is energy source i is electricity or fuel wood/Briquette and EF is Emission Factor for the fuel type i. EFe = 1.08 tCO2/ MWh and EFw = 1443.67 kg/ton. EFe is emission factor for electricity use and EFw is the emission factor for biomass fuel (wood /Briquette). (Source: Central Electricity Authority, Govt. of India)
70 6.6
SIMULATION OF COMPRESSED AIR PIPE JUNCTIONS Two types of common junctions were analyzed namely T and
Elbow and a redesigned geometry for branching. For both cases the geometry was generated in CATIA V5 R20. The pre-processing of meshing was done with ANSYS WORKBENCH and simulation was carried out with a CFX solver. A tetrahedron mesh pattern was selected with nodes and elements as 116796 and 604094 respectively for T and elbow respectively. The solver used is CFX with 500 iterations. The simulation results are presented in the subsequent sections.
6.6.1
T- Junction Initially simulation was carried out for ‘T’ junction with θ=90o.
Then simulation was repeated for various angles (θ) to get the best flow pattern at the junction with minimum pressure drop.
The junction was
simulated for inlet pressures of 4, 6 and 8 bar. The simulation results with the estimated pressure drop values after the junction and the percentage reduction over inlet pressure are given in Table.6.1 In this table the observation on the flow pattern is also spelt out for quick understanding. The simulation of the pressure gradient is shown in figures 6.3, 6.4 & 6.5. To find the best angle (θ) with horizontal to take a branch line from main pipe to minimize the pressure drop across the junction further simulations were carried out between θ =26o
and θ = 66o. A close interval of θ = 2o was maintained between θ =42o and 50o.
The simulations were performed with 4 bar inlet pressure for all the cases. The observed results are tabulated in Table 6.2.
71 Table 6.1 Simulation result of pressure drop through T junction for various pressures Inlet Air Pr. in bar
Observed Air Pr. in Downstream in bar
% Loss in Pressure
4
3.99917
0.021
6
5.99916
0.014
8
7.99916
0.011
Observation on flow pattern Flow separation at junction is observed Large flow separation compared to the case at 4 bar. Still more large flow separation compared to the case at 6 bar.
Figure 6.3 Pressure contour across junction at pressure 4 bar
72
Figure.6.4. Pressure contour across junction at pressure 6 bar
Figure.6.5 Pressure contour across junction at pressure 8 bar From the tabulated simulated results it is concluded that at θ = 46o the flow profile is more uniform and almost fully developed with minimum pressure drop. At an angle of 48o though there is no change in pressure loss and the flow showed separation. The loss percentage in pressure drop at θ=46o
73 was observed to be very low at 0.0005% compared to 0.021% at θ=90o which shows a 97.57% reduction in pressure drop. Hence it is concluded that the pressure loss is maximum at θ=900 compared to θ=460 as shown in figure.6.6 and it follows a polynomial relationship with R2=1 showing a perfect fit as shown in Figure. 6.7. Table.6.2 Pressure and flow pattern at 4 bar for different values of θ
26
Observed Air pressure at Downstream in bar 3.99861
36 42 44
3.99969 3.99981 3.99983
0.007 0.00475 0.00425
45
3.99970
0.00750
46
3.99998
0.0005
48
3.99998
0.0005
50
3.99987
0.00325
56
3.99966
0.0085
66
3.99961
0.00975
90
3.99827
0.02075
ranch Angle (θ)
% Loss in Pressure 0.139
Observation on flow pattern
Flow separation and vortices observed Flow separation observed Flow separation observed Flow pattern is close to the case of 460 Fully developed flow obtained. Flow profile more uniform in comparison to case of θ = 440 to θ =460. Pressure drop marginally higher in comparison to case of θ = 440 to θ =460. No flow separation is observed and pressure loss across the junction low No flow separation is observed. The pressure drop low. However the flow pattern is not as good as in the case of θ =460. Flow disrupted and further separation occurs. Pressure drop higher than previous case. (θ = 480), No separation observed and pressure drop more than that of θ =460 Flow separation as well as more pressure drop observed. Flow separation and high pressure drop observed.
74
Figure.6.6 Pressure drop observed at θ =46o with inlet pressure 4 bar
0.0035
Pressure loss in %
0.003 0.0025
y = 6E-05x2 - 0.001x + 0.006 R² = 1
0.002 0.0015 0.001 0.0005 0
3
4
5
6
7
8
9
Air pressure in bar
% Pr.Loss θ=90
% Pr.Loss θ=46
Figure 6.7 Pressure gradient at different air pressure (4, 6 &8 bar) with θ=90o & 46o
75 6.6.2
Elbow Simulation of elbow is conducted for different fillet radius (r). In
the present case the fillet radius was very small and it is almost to 90o bend. First the elbow was simulated with 90o at three different pressure values of 4, 6 & 8 bar. It is observed from the simulation results that the 150 mm fillet radius resulted in minimum pressure drop and best flow pattern compared to the sharp bend (θ=90o). It is seen from the values that the percentage of pressure drop is minimum at fillet radius 150 mm compared to sharp bend in all the three given inlet pressure. The reduction in pressure drop was observed as 82.9%, 79.39% and 77.24% for 4, 6 and 8 bar respectively.
The
comparative pressure drop reduction without fillet and with 150 mm fillet is presented in Table 6. The simulated pressure gradient is shown in Figure 6.8 and 6.9. Table 6.3 Change in percentage pressure drop without fillet and with 150 mm radius fillet Pressure (bar)
Without fillet
With fillet r=150 mm
% Change in pressure drop
Rounded value
4
0.0425
0.0073
82.82
83
6
0.0283
0.0058
79.50
80
8
0.0165
0.0038
76.96
77
76
Figure 6.8 Pressure gradients without fillet at 4 bar
Figure 6.9 Pressure gradients for elbow with 150 mm fillet at 4 bar inlet pressure The relationship between the fillet radius and the pressure drop is observed to be polynomial with R2=0.9929 showing a perfect fit as shown in Figure 6. 10.
77 0.045 0.04
y = -2E-09x3 + 2E-06x2 - 0.000x + 0.042 R² = 0.992
0.035 0.03
0.025 0.02
0.015 0.01
0.005 0
0
100
200
Pr. Drop(%)
300
400
500
Poly. (Pr. Drop(%))
Figure 6.10 Fillet radius Vs Pressure drop for elbow
6.6.3
Branching with Fillet and θ =46O A new geometry was developed combining the above results by
introducing fillet radius with θ =46o branch angle instead of 90o T junction as shown in Figure. 6.11.
Figure 6.11 Redesigned geometry of branching in place of 90o T junction
78 The number of nodes and elements in the mesh was 28293 and 133401and fine mesh was selected at corners for better result. The simulated pressure contour for 4 bar inlet pressure is shown in figure 6.12. The observed pressure after the junction from the simulation result in the branch pipe was 3.99962 bar which is comparatively less than in the straight branch at 46o (ref. fig.6.6). The simulation was done for 6 and 8 bar as inlet pressure and the simulated pressure contour is shown in figure 6.13 and 6.14. The calculated pressure loss % compared to 90o T junction is presented in Table 6.4. It is observed from the simulation that the new design gives minimum pressure drop across the junction than the conventional T junction.
Figure 6.12 Simulated pressure contour for inlet pressure 4 bar and 10% of flow in branch pipe with θ=46o and fillet radius (r) = 150 mm
79
Figure 6.13 Simulated pressure contour for inlet pressure 6 bar and 10% of flow in branch pipe with θ=46o and fillet radius (r)=150 mm
Figure 6.14 Simulated pressure contour for inlet pressure 8 bar and 10% of flow in branch pipe with θ=46o and fillet radius (r) =150 mm
80 Table 6.4 Estimated pressure loss % with 46o branch with fillet and 90o branch without fillet
Inlet Air Pr (bar)
Pr after junction in 90o branch (T)
Pr after junction in 46o and 150 mm fillet branch
% Pr loss in T junction (90o)
% Pr Loss ( New design)
4
3.99917
3.99987
0.02
0.003
6
5.99916
5.99988
0.014
0.002
8
7.99916
7.99988
0.01
0.002
6.7
ESTIMATION OF ENERGY AND CO2 EMISSION SAVING The power requirement for compressing air through a screw
compressor is determined with the following assumptions. • The compressed air is at room temperature • Gauge pressure is used for calculation • Adiabatic compression with compression index of 1.4 • Single stage compression • Atmospheric pressure is 1.013 bar The power consumption for the T junction is estimated for three cases of compressed air generated at pressures 4, 6 and 8 bar.
The adiabatic compressor power required to generate 10% of the total flow is estimated using eqn. 6.4. As follows: .
N+
..-
.
1.013 10
72.96 0.10
. .
#$
!
= 0.34526 kW
The exit pressure (at θ=90o) after the junction is reduced to 3.99917
bar and the equivalent power is estimated using eq. (1)
81 .- .-
1.4 N+ 1.013 10. 72.96 0.10 1.4 1 = 0.34519 kW
3.99917 . 1.013
1/
3600 1000
Similarly the exit pressure (at θ=46o and r = 150) mm is reduced to 3.99987 and the equivalent compressor power is estimated as follows: .- .-
1.4 N+ 1.013 10. 72.96 0.10 1.4 1
3.99987 . 1.013
1/
3600 1000
= 0.34525
Energy recovered as per eq. (6.5)
= 0.34525- 0.34519 = 0.00005 kW
The percentage reduction in power required
= 0.00006*/3.45257 = 0.02%
For a 5000 T junctions and considering screw compressor running for 24 hrs and 350 days in a year the annual energy recovery would be = 0.00005 * 24*350*5000 = 2.10 MWh/annum Estimation of CO2 emission reduction Corresponding CO2 reduction per annum per junction using eq. (4) = 2.10*1.08 = 2.27 tCO2 per annum Similarly the calculated values of power reduction and CO2 saved for 5000 number of junction of new geometry over conventional T (θ=90o), and for elbow with 150 mm fillet radius over 90o elbow at 4, 6 and 8 bar inlet pressure are listed in Table. 6.5 and 6.6.
82 6.8
RESULT AND DISCUSSION The energy and CFD analysis has proved to be an effective tool to
estimate energy and emission saving potential at end user. The simulations conducted in the compressed air pipe line junctions have proved that a redesign of T and elbow will result in significant energy and CO2 emission reduction as summarised in Tables 6.5 and 6.6. The best angle for branching is found to be 46o instead 90o. In the case of elbow the best fillet radius which gives the minimum pressure drop is found to be 150 mm. The estimated annual energy and CO2 emission reduction with the new design of T and elbow are summarized in Table 5 and Table 6 considering 5000 junctions and 24 hr and 350 days of operation. In the case of the new design the energy recovery increases as flow increases. The estimated values of energy recovered for 10%, 30%, 605 and 90% flow in branch pipe are also presented in Table 6.5. The energy recovery shows a linear relationship with the flow rate and the pressure with R2 value of 0.99 shows a perfect fit for the case of pressure 8 bar and is similar to other pressures also. In case of the elbow the energy recovery gets decreased as pressure increased as noted in Table 6.6. The energy recovered gets decreased as pressure increases for the given flow rate, however for the same pressure the energy recovered increased with increase in the flow rate as seen from the graph in Figure 6.15.
83
Table 6.5 Energy and emission saving in the new geometry of T junctions with θ=46o and r=150 mm Percentage Flow in branch pipe Initial generated air pressure (bar) Adiabatic power required for initial pressure generation for various flow percentage (kW) Adiabatic power equivalent to exit pressure with θ= 90o (kW) Adiabatic power equivalent to exit pressure with θ= 46o and fillet radius r= 150 mm (kW) Energy recovered over 90o branch (kW) % Energy recovered Energy saving for 5000 junctions for 24 hr operation and 350 working days (MWh) CO2 saving per annum (tCO2/Annum)
10%
30%
60%
90%
4
6
8
4
6
8
4
6
8
4
6
8
0.34526
0.47591
0.57823
1.035772
1.427735
1.7346979
2.071543043
2.85547
3.469396
3.107315
4.283204
5.204094
0.34519
0.47586
0.57819
1.03558
1.42759
1.73458
2.07116
2.85518
3.46916
3.10675
4.28277
5.20374
0.34525
0.47590
0.57823
1.03574
1.42771
1.73468
2.071483776
2.855429
3.469362
3.107226
4.283143
5.204044
0.00005
0.00004
0.00003
0.00016
0.00012
0.00010
0.00032
0.00025
0.00020
0.00048
0.00037
0.00030
0.02
0.01
0.01
0.02
0.01
0.01
0.02
0.01
0.01
0.02
0.01
0.01
2.10
1.68
1.26
6.70
5.16
4.20
13.40
10.32
8.40
20.11
15.48
12.60
2.27
1.81
1.36
7.24
5.57
4.54
14.48
11.15
9.08
21.72
16.72
13.61
83
84 Table 6.6 Energy and emission saving due to redesigning of elbow (r=150 mm) Initial generated air pressure (bar)
4 3.99830
6 5.99830
8 7.99868
3.99971
5.9997
7.9997
3.45257
4.75912
5.78233
Adiabatic power equivalent without fillet (kW)
3.45128
4.75815
5.78171
Adiabatic power equivalent with fillet (kW)
3.45235
4.75892
5.78219
Energy recovered (kW)
0.00129
0.00097
0.00061
% Energy recovered
0.04
0.02
0.01
Energy saving for 5000 junctions for 24hr operational and 350 working days (MWh)
54.26
34.81
22.01
CO2 saving per annum (tCO2/Annum)
58.60
37.60
23.77
Available pressure after the junction without fillet (bar) Available pressure after the junction with fillet (bar) Adiabatic power required for initial pressure generation (kW)
25
y = 6.073x - 4.605 R² = 0.992
MWh
20 15 10 5 0
10%
30% 4
6
60% 8
90%
Linear (4)Flow rate
Figure 6.15 Energy recovered in redesigned geometry for branch at test pressures The simulation results show that in a typical cement industry if the new design proposed for branching and elbows is implemented in compressed air pipes carrying compressed air at 4, 6 and 8 bar for every 5000 junctions a cumulative energy saving (assuming 30% flow in branch pipe) of 127.14 MWh per annum can be achieved. This will lead to the emission reduction of 137.31 tCO2 per annum.
85 6.9
SUMMARY The present work demonstrates that the CFD analysis provides an
insight into energy systems to make a critical analysis to find opportunities for energy and related emission reductions. The new geometry proposed for taking branch lines can be implemented in a compressed pipe net work. However further work has to be carried out to estimate the energy saving potential for various
pipe diameter, inlet pressure and flow velocity. It is
therefore concluded that numerical methods can be effectively applied to quantify energy and emission saving potential in energy systems.
86
CHAPTER 7 SUMMARY OF RESEARCH FINDINGS
A summary of the outcome of this research is discussed in this chapter. This research has demonstrated that the emission of CO2 into the atmosphere could be mitigated through energy conservation measures and also the energy audit is a powerful tool in providing practically implementable solutions to the objective of this research. This approach encourages the end users of electricity particularly industrial users to use electricity efficiently and to reduce the wasteful usage of electricity. The major motivating factor in adopting energy audit is the immediate realization of monetary benefits by the end users.
In the case of a paper based industry a detailed energy flow analysis was conducted in a paper carton manufacturing unit in India to quantify the energy saving potential. The study revealed that the compressed air leakage is responsible for about 50% of the total energy loss. The specific electrical and thermal energy consumptions are estimated and found to be 91.85kWh/ton and 1619MJ/ton of biomass, respectively. The annual energy savings potential is found to be 5.9% of the total annual energy consumption. The cost of the DG power is estimated at 389% higher than the grid power. The share of the selfgenerated DG power contributed to 41% of the total power consumed.
It is predicted from the analysis that the electrical energy intensity of the plant could be reduced by 6.36% by implementing the energy conservation measures proposed in this study. It has been found that major share of the plant energy requirement is met by thermal energy (68%)
87 followed by electrical energy (32%). Therefore, it can be concluded that the industry is thermal energy intensive. The plant has stabilized specific energy consumption (electrical), SEC (E) at an average value of 91.85kWh/ton (330.66MJ/ton). However, the plant is yet to optimize the Specific Energy Consumption (Thermal), SEC (T). At present, the value fluctuates between 182 kg/ton and 91.75 kg/ton. The average value of the SEC (T) is estimated at 129 kg of wood or briquettes per ton of product (1619 MJ/ton of product)
Analysis carried out on the individual energy system showed that lighting has energy saving potential of 23.526 MWh per annum and to achieve this saving an estimated investment of INR 382,500 is required. The Return on Investment (ROI) for the investment is 3.5 years. The installation of energy efficient HPSVL (High Pressure Sodium Vapor Lamp) provides the lucrative saving opportunity in terms of energy (16.425MWh/annum) and cost (INR 77197). The ROI for the investment is found to be only 2.3 years.
The performance study conducted in the air compressor showed that the operating load is 97.5% and it generated 131.23 cfm of compressed air at a pressure of 8 bar. The compressed air leakage was found to be 35%. By arresting this leakage, the plant can save up to 25.60MWh/annum. The investment required is very nominal to meet labor and minor replacement cost at the leakage points.
The share of self-generated power in the total electrical energy consumption is estimated at 41%, and it goes to above 65% during summer, which imposes a heavy financial burden due to the high cost of self-generated power (INR 18.32) which is 389% higher than the cost of grid power (INR 4.70).
88 The plant can reduce its electrical energy intensity from 91.85 to 86 units/ton on “BAU” (Business As Usual) by implementing the energy saving measures identified in this study. The reduction in the energy intensity would be 6.36%.
The unit is facing difficulties in matching the steam supply and the demand. The boiler is underutilized. It requires a detailed study to match demand and supply. The plant has installed a good condensate recovery system. The waste heat from flue gas is recovered to heat the combustion air, and thus it has adopted significant energy saving measures in the boiler section. The unit has a total of 49.128 MWh of electrical energy saving potential, which comes to 5.9 % of the total (831.223 MWh) electrical energy consumption.
The compressed air leakage is a continuous threat for environment although it may appear a minor problem. In this case, the air leakage accounts for 25.602 MWh of electricity per annum which alone accounts for 3% of the total electrical energy consumed, which is almost equal to 50% of the total energy saving identified. Energy audit emerges as a powerful tool in mitigating energy related CO2 emission in industry on a sustainable basis. An analysis to predict the energy saving potential in a cement industry using the concept of Energy Efficiency Index was performed. It was found from the analysis that the chosen cement industry has achieved only 1.42% of total energy consumption and still has energy saving potential of 15.73% to be on par with the national best energy performing industry in the cement sector. The result showed that the achieved total electricity energy saving was 4833 MWh per annum which leads to emission reduction of 5219.64 tCO2 per annum. Further predicted scope for energy saving is
89 49,278.6 MWh/annum which may result in an emission saving of 53,220 tCO2 per annum. The concept of Energy Efficiency Index has thus proved to be a guiding factor to predict energy and emission saving potential in industries.
CFD analysis made on a compressed air pipe junction showed that with a redesign of the conventional T and elbow, a significant quantum of energy needed for air compression can be reduced. The simulation of pressure drop across the junctions showed that the minimum pressure drop occurred when a branch line is taken at an angle of 46o with a 150 mm fillet radius instead of 90o (T) branch.
In case of elbow, 150 mm fillet radius gives
minimum pressure drop instead of conventional elbow. The CFD analysis carried out on the T junction and Elbow of compressed air pipe network with various inlet air pressures showed that for a 5000 numbers of such junctions a replacement of T junction and 90o elbow can reduce cumulative energy consumption to a tune of 127.14 MWh and emission reduction of 137.31 tCO2 per annum. The summary of result findings is shown in Table 7.1
90 Table 7.1 Summary of cumulative energy and emission saving potential identified (for 5000 junctions) Industry
Energy System
Unit
Quantity
Cost INR/Yr
Paper based Industry
Air compressor
MWh
25.60
120330
Motors
Cement Industry
Compressed air pipe junction
Lighting Energy Eff. (1) MWh 16.43 Lighting Reducing (2) MWh 7.10 Voltage Total (E)* 49.13 Total (T) Briquette Ton 34.23 Total (T)** 34.23 Predicted through Energy efficiency MWh 51,676.83 Index Predicted through CFD Analysis Redesigned T MWh junction with 30% (4/6/8 6.90/5.16/4.20 flow in branch line bar) MWh Redesigned Elbow (4/6/8 54.26/34.81/22.01 bar)
Investment INR -
Payback (m) Immediate
tCO2 Saving 27.65
No significant Saving potential Identified
77197
182500
28
17.74
33375
200000
72
7.67
230901 85575 85575
382500 500000 500000
20 70 70
53.06 49.41 49.41
*
*
*
**
**
**
**
**
**
5637.21
7.24/5.57/4.54
58.60/37.60/23.77
* Economic analysis is not performed since the analysis made for the whole industry and not for individual system. ** Economic analysis is not made since the simulation results are to be further analyzed with experimental result which is not in the scope of present research
90
91
CHAPTER 8 FUTURE SCOPE
•
The research suggests that the energy audit is a tool to a wide range of industries to quantify the possible energy and emission reduction potential. Therefore the methodology proposed in this research can be extended to a wider section of industries and appliances
•
CFD analysis can be applied to energy systems involving water and cold, hot air circulations.
92
REFERENCES
[1]
Akbaba M, Energy conservation by using energy efficient electric motors. Applied Energy. Vol.64, No.(1-4), pp. 149-158, 1999.
[2]
Almeida AT, Fonseca P and Bertoldi P, Energy-efficient motor systems in the industrial and in the services sectors in the European Union: characterization, potentials, barriers and policies. Energy. Vol. 28, No.7, pp. 673-690, 2003.
[3]
Avami A and Sattari S, Energy conservation opportunities: cement industry in Iran. International Journal of Energy. Vol.1, No.3, pp. 65-71, 2007.
[4]
Axelsson E and Berntsson, Profitability and off-site CO2-emission reduction from energy savings in the pulp and paper industry in different future energy markets. International Journal of Energy Research. Vol.36, No. 9, pp. 975–986, 2012.
[5]
Christoffersen LB, Larsen A and Togeby M, Empirical analysis of energy management in Danish industry. Journal of Cleaner Production. Vol.14, No.5, pp. 516-526, 2006.
[6]
EEE , Electrical Energy Equipment: Compressors and Compressed Air Systems, Energy Efficiency Guide for Industry in Asia, 2006 www.energyefficiencyasia.org.
[7]
ES 2010 Energy savers, US department of energy, http://www.energysavers.gov/your_home/lighting_daylighting/index.cf m/mytopic=12030 ( visited on :12/10/2010).
[8]
Garcia AGP, Szklo AS, Schaeffer R and McNeil MA, Energyefficiency standards for electric motors in Brazilian industry. Energy Policy. Vol.35, No.6, pp. 3424-3439, 2007.
[9]
Gielen D and Taylor P, Indicators for industrial energy efficiency in India. Energy. Vol.34, No.8, pp. 962-969, 2009.
93 [10]
Green House Gas Guidelines, North Carolina Air Qualitywww.ncair.org – visited on 06.10.12.
[11]
Hasanuzzaman M, Rahim NA, Saidur R, Kazi SN, Energy savings and emissions reductions for rewinding and replacement of industrial motor. Energy Vol. 36, No.1, pp. 233-240, 2011.
[12]
http://www.sciencedaily.com/releases/2012/07/120730142509.htm visited on 10.12.12.
[13]
Jayamaha L Energy Effficiency Building Systems: Green Strategies for Operation and Maintenance, 7th Ed. McGraw-Hill, 2007.
[14]
Klugman, S., Karlsson, M. and Moshfegh, B. A Scandinavian chemical wood pulp mill. Part 1. Energy audit aiming at efficiency measures. Applied Energy. Vol.84, No.3, pp. 326-339, 2007.
[15]
Kumar Mandal, S. and Madheswaran, S. Environmental efficiency of the Indian cement industry: An interstate analysis. Energy Policy. Vol.38, No. 2, pp. 1108-1118, 2010.
[16]
Li Y, Li J, Qiu Q, Xu Y Energy auditing and energy conservation potential for glass works. Appl Energy. Vol.87, No.8, pp. 2438–2446, 2010.
[17]
Liu. J, Nagata K and Onoda H Carbon emission trading and China’s pulp and paper making. IJ of Civil and Environmental Enginering. Vol.11, No.5, pp. 129-133, 2011.
[18]
Madlool NA, Saidur R, Hossain MS, and Rahim NA, A critical review on energy use and savings in the cement industries. Renewable and Sustainable Energy Reviews. Vol.15, No.4, pp.2042-2060, 2011.
[19]
Mathur J, Bansal NK and Wagner HJ, Investigation of greenhouse gas reduction potential and change in technological selection in Indian power sector. Energy Policy. Vol.31, No.21, pp. 1235-1244, 2003.
[20]
Mohammed Abdulwahhab et.al, CFD Simulations and flow analysis through a T-junction pipe. International Journal of Science and Technology. Vol.4, No.07, pp. 3392-3407, 2012.
94 [21]
Mongia N, Sathaye J and Mongia P, Energy use and carbon implications in India Focus on industry. Energy Policy. Vol.22, No.11, pp.894-906, 1994.
[22]
Mongia P, Schumacher K and Sathaye J, Policy reforms and productivity growth in India's energy intensive industries. Energy Policy. Vol.29, No.9, pp.715-724, 2001.
[23]
Nadel S, Elliott RN, Shepard M, Greenberg S, Katz G and Almeida AT, Energy-Efficient Motor Systems: A Handbook on Technology, Program, and Policy Opportunities. Second Edition. Washington, D.C.: American Council for an Energy-Efficient Economy. 2002.
[24]
Nikola T, Goran J and Hakon S, Cfd analysis and air flow measurements to approach large industrial halls energy efficiency: A case study of a cardboard mill hall. IJ Energy and Building, Vol. 43, No.6, pp. 1200-1206, 2011.
[25]
Ozturk HK Energy usage and cost in textile industry: a case study for Turkey. Energy. Vol.30, No.13, pp. 2424–2446, 2005.
[26]
Palanichamy, C. and Sundar Babu, N. Second stage energy conservation experience with a textile industry. Energy Policy. Vol.33, No.5, pp. 603-609, 2005.
[27]
Roosa, S. A. Energy Policy and Sustainability in Sunbelt Cities in the United States. International Journal of Green Energy. Vol.4, No.2, pp.173-196, 2007.
[28]
Ruth Mossad, William Yang, Philip Schwarz. M, Numerical Prediction of air flow in a sharp 90o elbow. Seventh International Conference on CFD in the Mineral and Process Industries CSIRO, Melbourne, Australia, 9-11 December 2009.
[29]
Ryszard Dindorf. Estimating potential energy saving in compressed air system. Procedia Engineering, Vol. 39, pp. 204-211, 2012.
[30]
Saidur R, A review on electrical motors energy use and energy savings. Renew Sustain Energy Rev. Vol.14, No.3, pp.877–898, 2010.
95 [31]
Saidur R, Hasanuzzaman M, Mahlia T M I, Rahim N A and Mohammed H A Chillers energy consumption, energy savings and emission analysis in an institutional buildings Energy, Vol. 36, pp. 5233-8, 2011.
[32]
Saidur R and Mekhilef S, Energy use, energy savings and emission analysis in the Malaysian rubber producing industries. Applied Energy Vol. 87, No. 8, pp. 2746-2758, 2010.
[33]
Sathaye J and Phadke A, Cost of electric power sector carbon mitigation in India: international implications. Energy Policy. Vol.34, No.13,pp.1619-1629, 2006.
[34]
Seddon. J, The flow through short straight pipes in a compressible viscous stream, A report by Ministry of Supply, Aeronautical Research Council, London, 1957.
[35]
Subrahmanya M H B, Labor productivity, energy intensity and economic performance in small enterprises: a study of brick enterprises cluster in India. Energy Conversion and Management, Vol. 47, No.6, pp. 763–777, 2006.
[36]
Wang, C., Larsson, M., Yan, J. and Dahl, J. CO2 Emission Reduction in the Steel Industry by Using Emission Trading Programs. International Journal of Green Energy. Vol.4, No.5, pp.505-518, 2007.
[37]
Zeng, L. and Yan, J. Policy, Institutional and Market Barriers to the Implementation of Clean Development Mechanisms (CDM) in China. International Journal of Green Energy. Vol.2, No.3, pp. 259-271, 2005.
96
LIST OF PUBLICATION
1.
R. Saidur, M.T. Sambandam, M. Hasanuzzaman, D. Devaraj, S. Rajakarunakaran. An analysis of actual energy savings in an Indian cement Industry through energy efficiency index. International Journal of Green Energy. Vol.9 No.8. 2012. Accepted author version posted online: 30 Apr 2012. (IF: 1.188, 2011) (http://www.tandfonline.com/doi/full/10.1080/15435075.2011.647166)
2.
M.Thirugnanasambandam, M. Hasanuzzaman, R. Saidur M.B Ali D. Devaraj, S.Rajakarunakaran N.A Rahim. Analysis of electrical motors load factors and energy saving in an Indian cement industry. International Journal of Energy Volume 36 (2011) pp. 4307-4314 (IF- 3.487, 2011)
3.
R. Saidur, M.T. Sambandam, M. Hasanuzzaman, D. Devaraj, S. Rajakarunakaran, D.Islam. An energy flow analysis in a paper based industry, IJ Clean Technology and Environment Policy, October 2012, Volume 14, Issue 5, pp 905-916. (IF-1.753, 2011). (http://rd.springer.com/article/10.1007/s10098-012-0462-9)
4.
M.Thirugnanasambandam, D. Devaraj, S. Rajakarunakaran. Development of Energy and Carbon management System (ECMS) for building stock owned by banking sector. International Journal of Energy Policy, (Article under review)
5.
M.Thirugnanasambandam, D. Devaraj, S. Rajakarunakaran. CFD analysis to investigate energy saving potential in compressed air pipe lines with reference to T- junction and Elbow. International Journal of Energy, (Under Submission)
97 International conferences 1.
M.T. Sambandam, D. Devaraj, S. Rajakarunakaran Energy Audit- a tool to mitigate energy related CO2 emission in process industries. International conference on “Climate Change and CO2 Management: Mitigation, Separation and Utilization, 2-3 February 2012 CES Anna University, Chennai, India.
2.
M. Thirugnanasambandam D.Devaraj S Rajakarunakaran Exergy analysis and assessment of energy saving potential in industrial compressed air treatment systems. 5th International conference on Intelligent
Systems,
Sustainable,
New
and
Renewable
Energy
Technology and Nanotechnology (IISN-2011), February 18-20, 2011, organised by Institute of Science and Technology, Klawad, Haryana, India. 3.
M. Thirugnanasambandam, Dr. S Rajakarunakaran Estimation of CO2 emission through energy audit in process industry. 1st International Conference on Advances in Energy Conversion Technologies (ICAECT 2010), Jan07 -10, 2010, MIT, Manipal.
4.
M.Thirugnanasambandam S. Rajakarunakaran. A Study on Energy Intensity Vis-à-vis GHG Emission in Industries. International Conference on Advanced Manufacturing and Automation (INCAMA) 26-28 March 2009, Kalasalingam University, Krishnankoil, India.
98 Technical Magazine 1.
M. Thirugnanasambandam, S Rajakarunakaran
D. Devaraj On site air
Compressor capacity test saves energy and money Cooling India, a monthly Technical Magazine, Vol. 7, No.9, pp. 66-69, Dec-2011. 2.
M. Thirugnanasambandam, S Rajakarunakaran D. Devaraj. Compressed Air Treatment System- Scope for Energy Saving. Cooling India, a monthly Technical Magazine, Vol. 7, No.6, pp.30-37, Sep-2011.
3.
M. Thirugnanasambandam, S Rajakarunakaran Energy Audit in a Commercial Establishment a case study. Energy manager, a quarterly Technical magazine, Vol.3, No.1, pp.48-52, Jan-March 2010.
99
CURRICULUM VITAE
THIRUGNANASAMBANDAM.M was born on 19.05.1965 in a small village named UNNIYUR, on the banks of river Cauvery in Trichirappalli district Tamilnadu, India. His father was a primary school teacher and his mother was a home maker. He completed his schooling at Panchayath Union Middle School, Unniyur and Zamindar’s higher Secondary School, Kattuputhur, which is 5 KM away from his village. He completed his whole school education in his mother tongue Tamil. In the year 1986 he completed his Bachelors’ degree in Mechanical Engineering from Thiagarajar College of Engineering, Madurai. He then, underwent one year apprenticeship training with the Agricultural Engineering Department, Govt. of Tamilnadu. In 1987 he joined as lecturer in the erstwhile Arulmigu Kalasalingam College of Engineering as lecturer. Then he left the institute and joined with School of Energy, Bharathidasan University Trichy to pursue his Masters degree in Energy Conservation and Management and passed out in the year 1991. He returned to the teaching profession and served at North Eastern Regional Institute of Science and Technology, Arunachal Pradesh, India and then worked with the National Small Industries Corporation, Govt. of India from 1995 to 2008. He left the job and joined with the Kalasalingam Academy of Research and Education as a faculty member in the Mechanical Engineering Department and perused his research work as a part time research scholar.
