Measurement and Simulation of Standalone Solar PV ...

EFEEA’10 International Symposium on Environment Friendly Energies in Electrical Applications

2-4 November 2010, Ghardaïa, Algeria

Measurement and Simulation of Standalone Solar PV System for Residential Lighting in Malaysia Dimas Firmanda Al Riza, Syed Ihtsham Ul Haq Gilani, Mohd. Shiraz Bin Aris Mechanical Engineering Department, Universiti Teknologi PETRONAS Bandar Sri Iskandar, Perak, MALAYSIA E-mail: [email protected]

This paper presents work carried out on the modeling and simulation of a standalone PV system for residential house lighting using TRNSYS 16 software. The actual measurement from a 400 Wp PV systems was used to compare and validate simulation results. System monitoring and data logging of the actual system was conducted in Bandar Sri Iskandar, Malaysia.

Abstract – A system modeling and simulation is necessary to investigate the dynamic behavior of a Solar PV system. There are some softwares that can be used to model, simulate and estimate photovoltaics system performance. In this research a system model was built using TR SYS 16 software. TR SYS 16 is a complete and extensible simulation environment for the transient simulation of PV systems. This software can be used to validate new energy concepts and simulate energy systems. This paper presents results of a simulation work carried out on a stand alone photovoltaic system for residential house lighting. Model validation was carried out by an established and monitored standalone PV system and then a comparison of the simulation results were made against measurement results. The measurement of an actual PV system was conducted in Bandar Sri Iskandar, Malaysia. It was found that the TR SYS model gave comparable results to the actual measurement but some adjustment need to be made to the simulation model to attain better simulation results.

II. TRNSYS MODEL OF THE SYSTEMS A TRNSYS software library contains many components to be used for the simulation of various energy systems. To simulate a standalone PV system for residential house lighting, the following components are needed: a. Solar radiation model b. PV Panel c. Controller d. Battery e. Load Fig. 1 shows a typical diagram of the components involved in a standalone PV system. An inverter need to be added if an AC load is utilized. This paper however presents TRNSYS simulation results of a standalone PV system with DC load.

Index Terms— Solar Energy, Photovoltaic, Simulation, TR SYS

I.

INTRODUCTION

As the Solar PV system technology grows rapidly and become more popular all over the world, engineers and scientists have carried out many researches, taken measurements and modeled for PV systems for various applications [1]. There are two types of photovoltaic systems, an On-grid and a standalone (Off-grid) system. Standalone PV systems are commonly used in rural areas, where there is no connection to the national electricity grid [2]. Standalone PV systems are independent to grid electricity because they have their own energy storage system. They can also be used as a hybrid system with other energy conversion systems such as wind turbines and micro-hydro or even with a connection to grid electricity. Since PV technology is continuous growing and will one day be competitive to conventional systems, standalone PV systems become more interesting to investigate. To ensure the improved reliability and economic viability of a PV system, the design and simulation of a PV system has to be developed by engineers. Modeling and the simulation of PV systems are necessary to understand the dynamic behavior of the system. There are some softwares that have been used to model and simulate PV systems. TRNSYS is one of the softwares that have the capability for this purpose. The modular structures of TRNSYS give the software tremendous flexibility and facilitate addition of new models into the program [3].

PV Array

Controller

Load

Battery

Figure 1. Standalone PV system components

A. TRSYS components Solar radiation model

For the solar radiation model, type 109 (Combined data reader and solar radiation processor) was selected. This component serves to read weather data at regular time intervals from a data file, converting them into a desired system of units which generates direct and diffuse radiation outputs, for an arbitrary number of surfaces, with arbitrary orientation and inclination. [4]

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detailed mathematical description, refer to TRNSYS 16 Users manual.

Nomenclature: G Gb Gbn Gd Tamb RH I IL ID IO Rs Rsh V Pp Ir Vr Isc Voc PSH RMSE MBE n Yc Yo

Total global horizontal irradiance Direct beam irradiance Direct normal beam irradiance Diffuse irradiance Ambient temperature Relative humidity Current Module photo current Diode current Diode reverse saturated current Module series resistance Module shunt resistance Voltage Peak power Rated current Rated voltage Short circuit current Open circuit voltage Peak Sun Hour Root Mean Square Error Mean bias Error Measurement number Comparator value (measured results) Observed Value (simulated results)

Figure 2. One diode 4-parameter model

Controller

In photovoltaic power systems, two power conditioning devices are needed. The first of these is a regulator, which distributes DC power from the solar cell array to and from a battery (in systems with energy storage) and to the second component, the inverter. Since this research only use DC loads, so the inverter is not simulated in this study. In type 48 models, both the regulator and inverter can operate in one of four modes. Modes 0 and 3 are based upon the "no battery/feedback system" and "direct charge system," respectively. Modes 1 and 2 are modifications of the "parallel maximum power tracker system" in the same reference. Since the investigated PV system does not contain an AC load, inverter is not needed. Type 48b is used as the controller.

The solar radiation model needs at least two components of solar radiation in-order to calculate the radiation on a tilted surface. It can use different combinations of: − Gb and Gd − G and Gd − G and Gbn − G, Tamb and RH. The diffuse radiation is estimated using Reindl's full correlation − G, The diffuse radiation is estimated using Reindl's reduced correlation Commonly, most of weather stations provide I, Tamb and RH data, while only few weather stations can provide Ib and Id data.

Battery

Type 47b (Shepherd and Hyman battery model) was used as battery model. This model of a lead-acid storage battery operates in conjunction with solar cell array and power conditioning components. It specifies how the battery state of charge varies over time, given the rate of charge or discharge. Load

Type 9 (Generic data files) was used to input the load profile data. The calculation for PV size, battery size and typical load profile for a typical terraced house in Malaysia was conducted in a previous paper [5].

PV Panel

Several different PV generator types have been planted into TRNSYS 16: type 94 series, type 180 series and type 194 series. All of them are based on the one diode equivalent circuit model in Fig.2 and the equation below: = − − = −


B. Components connection Modeling and simulation was conducted using TRNSYS 16. Fig. 3 shows the component and connections between the components modeled in TRNSYS 16.

+ + − 1 −

The four parameters model is the simplified version of 5 parameters model. The four parameter model assumes that the slope of the IV curve is zero at the short-circuit condition. This is a reasonable approximation for crystalline modules. The “four parameters” in the model are IL,ref, Io,ref, γ, and Rs. Type 94 calculates these values from the manufactures data. Type 94a is appropriate for multi-crystalline PV panel. This type employs four-parameter model and it is more adequate for crystalline cells which have the slope of I-V curve at the short-circuit condition equal to zero. For

Figure 3. Solar Power System modeling in TRNSYS 16

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The TRNSYS model was tested using the Ipoh city weather data from which input file was created. Most weather stations provide hourly data as the smallest time series. So in the TRNSYS simulation, the simulation time step is set to hourly simulation. In this research sub-hourly data were converted to hourly average data to reduce data quantity. Monitoring and measurement results of total global horizontal solar radiation on an experimental set up site was used as input data for the type 109 solar radiation models. Parameter from the solar panel, controller and battery data sheet was also embedded into the TRNSYS model. The Load profile data was entered into a .txt file and implemented as an input for a type 9 data reader component.

Since a PV system is established in a small scale system (less than 1 kilo-Watt peak), a PWM type controller was used as the charge controller. In a small system PWM type controller is expected to give better results than the MPPT controller which is suitable for large scale systems. Table 2 shows the controller specifications.

III. EXPERIMENTAL SETUP

Lead acid type solar deep-cycle batteries were used as the storage system. There are four 100Ah batteries, each with 12V rated voltage and all battery connected in parallel connection. For the DC load, DC lamps were used and power resistors added to establish equivalent load.

TABLE 2 CONTROLLER SPECIFICATION [7]

Description Controller Type Maximum current ominal System Voltage Indicator

A. PV System configuration Fig. 4 shows the PV system configuration. The system consists of four PV Panel with a total power of 400Wp, a combiner box for parallel connection of the panels, battery charge controller, battery and DC load.

Characteristic Value Morning-Star, ProStar-30 PWM type 30 A 12/24 Volt LED

B. Measurement system The measurement system consisted of a data logger and sensors as described in Table 3. TABLE 3 MEASUREMENT SYSTEM COMPONENT LIST

Table 1 presents the specification of the solar panel used in the system.

General Specification

1

2

PicoLog 1216 Data logger PC

3

Pyranometer

4

Current Sensor

5 6 7

Temperature Sensor Humidity sensor Radiation shield

Single ended input, 12 Channel, 0-2.5V Desktop PC, Pentium 4, Windows XP Kipp & Zonen Pyranometer, SPLite HTFS 200-P/SP-2 LEM (Hall Effect) LM35 HIH-5030 Honeywell Handmade multi-plates radiation shield

Pyranometer

PC Picolog Recorder Software

TABLE 1 PV PANEL SPECIFICATION [6]

PV Module Type ominal Peak Power (Pp) Rated Voltage (Vr) Rated Current (Ir) Open Circuit Voltage (Voc) Short Circuit Current (Isc) Temperature Coefficient Company/Country of origin

Equipment

There are seven sensors connected to a 16 channel Picolog 1216 data logger. The data logger can record sensor output based on voltage, and stored data is sent to the connected PC. Fig. 5 shows schematic diagram of measurement connections.

Figure 4. Standalone solar power system with a DC load scheme

Description

o.

Air Temperature Sensor RH Sensor

Characteristic Value Picolog 1216 input module

Multi-Crystalline Silicon 100 Watt 17.2 Volt 5.81 Ampere 21.6 Volt 6.46 Ampere -0.074 V/oC; +2.80 mA/oC Photon Solar - India

IN/OUT Current from/to Battery

Panel Voltage

Battery Voltage

Figure 5. Measurement system connections

For Irradiance measurement a Kipp&Zonen pyranometer SPLite series was used. The Pyranometer was used to

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measure global horizontal solar irradiance in Watt/m2. For the RH measurement sensor, a HIH 5030 series was used. The HIH-5030 Series Low Voltage Humidity Sensors operate from 2.7 to 5.5V. LM35 IC sensors were used to measure air and the panels rear side surface temperature. The RH, HIH 5030 and LM35 sensors was supplied with external power source. A radiation shield is required to minimize the radiation effect on air temperature and relative humidity measurement. Without a radiation shield the temperature sensor will give relatively high measurement error during the day due to huge amount of irradiance presence. Due to costly commercial radiation shields a low-cost radiation shield was fabricated and used in the experiment.


in different time steps. These discrepancies however were not further investigated in this paper. B. Energy Input and Output of Solar power System Fig. 8 shows the monitored results of the power-in and out of the battery storage system and Fig. 9 shows hourly data. Power-in from the PV panels is indicated in positive values and the power out due to the loading indicated by negative values. The load was about 120 Watt in the 10 hour duration during the night. Therefore the total lighting equivalent load for each day was approximately 1200 Wh per day.

IV. RESULTS AND DISCUSSIONS A. Converting Solar Irradiance sub-hourly data to hourly data All parameters in the measurement system were recorded in 5 minutes time intervals. Most of the weather stations provide hourly data, so in this research the data were converted to hourly data by taking hourly averages. Fig. 6 shows Solar Irradiance measurement results during the 1-5 July 2010 period in 5 minutes time intervals and Fig. 7 is the equivalent hourly converted versions. Figure 8. Power input and output to/from battery (5 minutes time step)

Figure 6. Measured Solar Irradiance 1-5 July 2010 (5 min time step) Figure 9. Power input and output to/from battery (hourly average)

It can be observed from the data presented in Fig. 9 that the designed system works well and was not interrupted during the observation period. Power input and output is separated into two hourly data, called solar panel output and load data as input for TRNSYS simulation. The negative load value is converted to positive value because in TRNSYS simulation, load data is considered as positive value. C. Battery Voltage during charge and discharge The state of charge of the batteries can be observed by monitoring their voltage. The level change of the battery voltage during charging and discharging can be observed in more detail in Fig. 12. The controller maintained the battery voltage to not exceed 14.5 Volts to avoid overcharging. During discharging, the battery level drops linearly due to the constant loading. In the afternoon, after charging process, the battery level drops to about 13.2 Volts.

Figure 7. Measured Solar Irradiance 1-5 July 2010 (hourly average)

The measurement indicated that during 1-5 July 2010 period the maximum irradiance on site was about 850 Watt/m2. After averaging the data, the curve become smoother with maximum irradiance at about 610 Watt/m2. This results show that there is discrepancies between the data

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Figure 12. Comparison between measured and simulated panel output

Figure 10. Battery Voltage 1-5 July (hourly average)

D. Comparison between Measurement and Simulation Results

E. Solar PV system performance during low irradiance day

Before using experimental data in TRNSYS, the 5 minutes interval data was converted to hourly data by taking the average for every hour, then a comparison between simulated and measured results were carried out. Residual error was calculated using RMSE (Root Mean Square Error) and MBE (Mean Bias Error) equations as follows:

Fig. 13 shows measured and simulated battery voltage from 24 June to 4 July 2010 monitoring period. Low irradiation day was occurred in 25 June 2010 with PSH value only about 1.6 hours. During monitoring period the low irradiation day only occurred on 25 June and occurred again after seven days on 3 July 2010 with PSH value 2.6.

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Fig. 11 shows the solar panel energy output comparison between the measured and simulated results. Calculation results shows, for Solar Panel output RMSE is about 33.52 Watt and MBE is about 10.77 Watt, while simulation results in Fig.13 shows better and closer results to experimental value. The results show that the simulation error is bigger in low irradiance days and on the contrary the simulation error in higher irradiance days is smaller.

Figure 13. Measured and simulated battery voltage 24 June-4 July 2010

Fig. 14 shows measured and simulated panel output from 24 June to 4 July 2010 monitoring period. In low irradiation day, after loading time at the night, the battery voltage drop to 11.8Volts. The next five days, the after loading battery voltage increasing and almost reach initial voltage before low irradiation day, but the battery voltage dropped again on the sixth day due to low irradiation. However, the PV systems still work well continuously during monitoring period.

Figure 11. Comparison between measured and simulated battery voltage

Fig. 12 shows battery voltage changing during the charging and discharging period, comparing between the measured and simulated results. It can be seen from the simulation results that similar results were obtained. The energy output of the panels in simulation results show lower values compared to the measured results. MBE for battery voltage is about -0.08 Volts and RSME is about 0.42 Volts. This value is relatively high errors. The model should be further analyzed to minimize error.

Figure 14. Measured and simulated panel output 24 June-4 July 2010

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V. CONCLUSIONS Simulation and experimental work have been carried out for a standalone PV system. As the lighting loads occur during the night, the experiment equivalent lighting load was implemented for about ten hours during the night. Measurement result shows that the system works well with the designed load of about 1200Wh during the night. TRNSYS simulation result shows that the TRNSYS model can be used for a standalone PV system simulation but some components like the PV panel and the battery storage system need to be improved to get better results. The trend between the measured and simulated results is similar but there are some differences in value, this difference might have come from the measurement error or from errors within the TRNSYS component. ACKNOWLEDGMENT The authors would like to thank Universiti Teknologi PETRONAS for providing facilities and grant under STIRF schemes for the research. REFERENCES [1] [2] [3]

[4] [5]

[6] [7]

Zekai Sen, “Solar Energy Fundamentals and Modeling Techniques”, Springer, 2008 T. Markvart, and Luis Castener, “Practical Handbook of Photovoltaics Fundamentals and Applications”, Elsevier ltd. 2003 Feng Shao, “Measurement and Simulation of Stand Alone Photovoltaic Systems”, Master Thesis, European Solar Engineering School, Högskolan Dalarna, Sweden, 2007 TRNSYS 16 User manual Dimas Firmanda Al Riza et. al., “Preliminary Investigation into the use of Solar PV System for Residential House Lighting in Bandar Sri Iskandar, Malaysia”, ESTCON, 2nd ICPER proceeding, Kuala Lumpur, 2010 Solar Panel Data Sheet, Photon Solar India Solar Charge Controller Data sheet, PS-30, Morning Star

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