An exergy based method for the optimal integration of

PROCEEDINGS OF ECOS 2012 - THE 25TH INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS JUNE 26-29, 2012, PERUGIA, ITALY

An exergy based method for the optimal integration of a building and its heating plant. Part 1: comparison of domestic heating systems based on renewable sources Marta Cianfrinia, Enrico Sciubbab, Claudia Torob a

Dept. of Mechanical and Aerospace Engineering, U. of Roma –Sapienza, [email protected] b Dept. of Electrical Engineering, U. of Roma – Sapienza,

Abstract: In all developed Countries, the residential space conditioning sector is one of the highest exergy consumers and least efficient from the point of view of primary-to-end-use matching. Such an unsatisfactory situation can be cured by a systematic analysis of the conditioning system of a building that takes into correct account the thermodynamics of primary-to-final energy conversion chain. The present study analytically and critically compares different domestic heating systems based on renewable energy resources. Specifically, solar and hybrid photovoltaic-thermal (PV/T) panels coupled with radiative heating panels and ground-source (closed and open loop) heat pumps coupled with fan coils and radiative heating panels are analyzed in detail from an exergy point of view. The main objective of the study is the development and implementation of a general systemic procedure for the optimal integration of the building and its heating plant (heating element + primary energy supply system): the “optimality” -intended here as the most convenient choice among a finite set of alternative processes- is reached by identifying the thermodynamically most convenient heating configuration for the building under examination. The method combines a CFD modeling of the thermal building dissipation, a simulation of the system that makes up for the thermal consumption and finally a calculation of the global (well-to-final use) exergy efficiency.

Keywords: space conditioning, green buildings, exergy efficiency, renewable resources, source/end-use matching.

1. Introduction The sustainable energy conversion in building heating/cooling systems has become an urgent issue on the energy agendas of most developed countries. Worldwide energy use by HVAC equipment in buildings accounts for 16–50% of the total final energy use, depending on the countries and their sectorial energy use patterns; and, more than half of this energy is typically used for heating [5]. Therefore, a reduction in the energy demand for building conditioning is very important for the large-scale improvement of the energy resources management. While a wide literature exists on the exergy analysis of power plants, the application of the exergy approach to the built environment may be still considered at an earlier stage. Most of the energy use in a building is related to near-environmental temperature thermal uses for space heating/cooling and for domestic hot water production. These low exergy demands are mainly satisfied with high exergy sources (e.g. fossil fuels), and thus a wide margin for exergy saving exists. Renewable energy sources may give an essential contribution to the CO2 emissions reduction. Although some of them may be considered purely renewable (e.g. solar energy), others are not endlessly available (e.g. biomass), since their availability depends on the ratio between their consumption and regeneration timescales. 81-1


Therefore, it is proper to apply exergy analysis to renewable energy-based systems to identify the most efficient use of the available renewable sources in space conditioning: in fact, some recent studies [14] stress the need for providing such an assessment. Balta et al. [1]evaluated a low exergy heating system from the primary exergy source through the ground-source heat pump to the building envelope and showed that the largest exergy destruction rate of the system occurred in the primary energy conversion. Shukuya and Hammache [12] compared three numerical examples of exergy consumption for space heating from the external source, through the boiler to the building envelope in steady state conditions. More than 20 case studies of “low exergy” buildings from 11 countries were presented in the Lowex guidebook [8]. Shukuya [11] described an exergetic approach to the assessment of future buildings equipped with low-exergy heating and cooling systems. Sakulpipatsin et al. [9] presented an extended method for the exergy analysis of buildings and HVAC systems by using a commercial building simulation tool, TRNSYS, for a reference building and its HVAC systems. Balta et al. [1] conducted an energy and exergy analyses of four building heating options driven by renewable and fossil-fuel sources and compared their energy and exergy efficiencies. Scope of present study is to develop and test a general systemic procedure [3] for the optimal integration of buildings and their conditioning plants. First, a thermal building dissipation modelling is applied to compute the actual thermal demand of a living space, and a process simulator is then used to identify the most exergetically suitable energy plant. The “optimal” configuration depends on the thermal characteristics of the building, the type of internal heating element (fan coil, ceiling or floor radiant panel in this study, since the example of application is limited to the winter mode of operation) and the type of primary energy conversion system (solar collector, PVT and ground source, closed-loop, heat pump). In detail, the proposed procedure, that we plan to completely incorporate within an automatic computational procedure in the second part of this project, consists of an initial thermofluiddynamic phase, in which the detailed temperature maps within the building are obtained by means of a CFD simulation, followed by a calculation, for each type of heating element, of the actual thermal power required to meet the environmental comfort standards. This second step is performed by means of a process simulator that uses as input the data extracted from the CFD results. In this step, all the feasible different combinations of internal and external systems providing the prescribed thermal power are simulated by means of the process simulator CAMELPro™ and the flow sheet of the primary-to-final use energy conversion chain is completely quantified. Finally, the individual systems are evaluated on the basis of the global exergy efficiency of the conversion chain to identify the most convenient pairings, i.e., those that consume the least primary resources for the same comfort level of the inside space.

2. 2. The numerical tools In the selection of the “optimal” integration of the building and its energy plant, it is necessary to examine three main aspects: the heat demand of the building, the type of heating element and the type of the primary energy conversion system. In this work, the first point consists of a detailed analysis of the thermal characteristics of the building and its temperature map, to obtain a more accurate calculation of the convective and radiative heat transfer on the inner surfaces and therefore to a better prediction of the thermal load. Notice that such thermal maps depend substantially on the type of the installed heating/cooling device: therefore, the calculations must be repeated for each one of the possible/feasible 81-2


configurations. All thermo-fluid dynamic simulations presented in this work have been performed via a commercial CFD code (Fluent® [4]). The pre-processing software Gambit, embedded in Fluent, has been used to create the geometry and generate the grid. The procedure, consisting of geometry modelling, creation of the mesh and its automatic acquisition by Fluent, can be easily translated into a systematic methodology for all type of heating elements. Since the internal flows are likely to be turbulent, the Navier-Stokes equations have been solved here by a modified version of the Hanjalic/Launder/Spalding ke-ε model [6]. This well established model is based on transport equations for the turbulence kinetic energy (ke) and its dissipation rate (ε): the equation for ke is derived by modelling its exact counterpart, while the equation for ε is obtained by using flow similarity and energy balance considerations, and bears little resemblance to its exact counterpart. In the derivation of the ke-ε model, the assumption is that the flow is fully turbulent, and the effects of molecular viscosity are negligible. The model is therefore valid only for fully turbulent flows. The pressure-velocity coupling is handled through the SIMPLE-C algorithm described by Van Doormaal and Raithby [15]. The advection fluxes are evaluated by the QUICK discretization scheme proposed by Leonard [7]. The computational spatial domain is filled with a non-uniform grid, with a higher concentration of grid lines near the boundary walls and other high-gradient areas, and a coarser uniform spacing throughout the remainder of the domain. After convergence of the velocity and temperature fields, the amount of thermal power transferred to the enclosure is calculated. As stated above, the results of the CFD simulations provide the thermal maps of the interior, that are then used to: a) verify that the comfort zone fits well with the usual occupancy areas; b) calculate the actual thermal load of the building. The next step is the process simulation of each type of building conditioning system, to calculate the power consumption and exergy efficiency of each configuration. To this purpose, models [3] of external and internal sub-units have been implemented and integrated in an existing process simulator, CAMEL-Pro™[17]. In CAMEL the system is represented as a network of components connected by material and energy streams; each component is characterized by its own set of equations describing the thermodynamic changes imposed on the streams. The solver algorithm is based on the “equation system” concept; each component of the plant has its own transfer function, based on a “local” equation system and a similarly “local” array of variables. When the simulation is launched, the first step CAMEL performs is to assemble the overall (typically non-linear) system: it does so by collecting together all the components equations and renumbering/reshuffling the unknowns, to form a single, global, equations system that describes the whole plant behaviour. An optimized iterative Newton-Raphson algorithm is used to solve the global equation system. The main feature of CAMEL-Pro™ is in fact its modularity that enables users to expand the code by adding new components or by modifying the model of the existing ones: we exploited these capabilities to introduce the proper process equations for heating (internal and external) and cooling component models as described with more details in [3] and [2]. Clearly, the proposed procedure is to a large extent independent of the process simulator employed: any commercial code may be used, provided it contains the proper functions and utilities required by the computation of the local and global parameters of the energy conversion chain.

3. 3. The concept of exergy The introduction of exergy as a thermodynamic analysis tool can help achieve the objective of reducing the degree of unsustainability of modern buildings. 81-3


The exergy of a system in a given environment is defined as the maximum work obtainable by the system when it is brought to a state of stable (possibly dynamic) equilibrium with the reference environment by means of ideally reversible transformations in which it exchanges heat only with the environment at a fixed reference temperature T0 [13]. Exergy analysis has been applied to energy conversion systems since the early 1970s with the aim of encouraging the rational use of energy, which means in essence to strive for a better matching of the quality levels of the energy supply and demand. For each component of a plant, the outlet exergy is always less than the inlet exergy because of irreversible entropy generation. When calculating the exergy of a process component, the difference between the exergy losses and exergy destruction are recorded. Exergy losses include the exergy flowing to the surroundings, whereas exergy destruction indicates the exergy destruction within the system boundary due to irreversibility. The exergy of a stream of matter can be divided into different “component exergies”. In the absence of nuclear, magnetic, electrical and surface tension effects, exergy is calculated as the sum of : Ex  ExK  ExP  ExPh  ExCh (1) where ExK, ExP , ExPh and ExCh are the kinetic, potential, physical and chemical exergy respectively: in the present study, the changes in kinetic and gravitational potential energies are neglected. Physical exergy has been defined above, whereas chemical exergy is defined as the maximum amount of work which can be obtained when a stream of matter is brought from the environment state to the total dead (unrestricted) state as a result of heat transfer and exchange of substances only with the environment. ExPh   h  h0   T0   s  s0 

(2)

ExCh  R·T0 · xi  ln xi   xi exch ,i

0

(3)

where xi is the mole fraction of the species i in the flow and exch,i0 is the molar chemical exergy of the ith species. To perform an exergy analysis of the heating plants studied in this work, we need to calculate first the mass- and energy flows of each process. The process simulator (CAMEL-Pro™) calculates the exergy of each (material and immaterial) stream and displays the values of the exergy destruction, Ex and of the exergy efficiency, ηex, of each component. Te; Solar heat, kW

T room N person Plight

T, hot w.; P

exergy source

Ventilation

internal plant

external plant

Heat Losses to the surroundings

ex

ex

ex

T, cold w

Figure 1 Exergy flows within the “building” system

3.1 - Internal system exergy analysis The distribution of warm and cold air by ventilation, heat transfer through the walls and fixtures, and solar heat gain within the building envelope are calculated by a CFD simulation, which results in a more accurate determination of the actual thermal demand for space conditioning. 81-4


This newly calculated thermal load is then used to design the heating/cooling surface of the internal plant, which leads in turn to the calculation of the hot/cold water flow rate and its inlet temperature and pressure. These parameters, together with the hardware characteristics of the space conditioning devices, allow to calculate the exergetic destruction and exergy efficiency of the internal system. The exergy exchanged between a heating surface and the room is calculated as 



E Q  Q ( 1 

T0 ) Tav

(4)



where Q is the heat transfer rate of the device, T0 is the environment temperature taken as 273 K, Tav is the average temperature of the exchange, calculated here as the room temperature plus the log mean temperature difference of the exchange, TLMTD. (5) Tav  T0  TLMTD The LMTD is given by: (Tin  T0 )  (Tout  T0 ) TLMTD  ln (Tin  T0 ) /(Tout  T0 )

(6)

The exergy destruction rate general formulation for the internal plant is then calculated as: 





Ex   Pel  m ( exin  exout )  E Q

(7)

where the first term on the right represents the electrical input to the internal system (only in case of 

a fan coil ), the second term is the exergy ”input” provided by the hot water, m being the water mass flowrate and exin and exout the water specific exergy in the respective states. The exergy efficiency of the internal plant is finally calculated by: 

ex 

EQ

(8)



m ( exin  exout )  Pel

3.2 - Intermediate system exergy analysis The storage subsystem is represented by a water tank and piping system. The former is assumed to operate at steady state and is affected by a pre-assigned thermal loss (2% in the present analysis). The piping system leads to both thermal and pressure losses, allocated here to the water tank. The circulation pumps (and, where present, the air circulation fans) consume additional electrical power, the value of which is added to the exergy consumption of the system. In this case we assume that every unit of electrical energy is fully converted to exergy, therefore for electrical devices the electricity/exergy conversion coefficient is equal to 1 (but each device is assigned its own mechanical efficiency). The exergy destruction within the auxiliary devices is: 





Ex   Ex in  Ex out 

Ex in ,out  m  ( exhot  excold ) 

Ex in  Pel (9)

81-5

PROCEEDINGS OF ECOS 2012 - THE 25TH INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS JUNE 26-29, 2012, PERUGIA, ITALY 



where Ex in and Ex out are the exergy content of the working fluid at the inlet and outlet of the  stands for the mass flow rate, exhot and excold are the specific exergies of the fluid device, m calculated at the highest and lowest temperature within the subsystem respectively, Pel is the electric power absorbed by pumps and fans. .

3.3 - External generation system exergy analysis The external plant satisfies the global demand of all “downstream” subsystems. It may do so by using electrical energy, natural gas or other fuels, and/or solar irradiation or ground heat to heat the working fluid. The exergy destruction for the external plant is calculated by the same formulae as for the intermediate subsystems. In the present study, the exergy factor for solar radiation is calculated with Petela’s formula [9] and posited constant and equal to 0.95. For all electrically powered devices the national average conversion efficiency factor equal to 0.45 is applied, which represents the efficiency of the primary resources conversion into electrical power for the italian mix in year 2009 [16]: lacking a sufficiently detailed database, this was taken also equal to the average exergy resource-to-electricity conversion factor, though it is likely that substantial adjustments may be necessary in this case [13]. The results of the calculations are reported in Section 6.

4. 4. Description of the case studies 4.1 Layout To show the potential of the proposed methodology, four case studies will be presented here. All deal solely with the “winter mode” operation, in which the building is heated against a pre-specified lower ambient temperature. Several different domestic heating systems based on renewable energy resources have been simulated here. Specifically, solar and hybrid PV/T panels coupled with radiative heating panel and ground-source (closed and open loop) heat pumps coupled with fan coils and radiative heating panels are analyzed in detail from an exergy point of view. The analyzed cases are: CASE A: floor heating panel coupled with a solar collector; CASE B: radiant ceiling panels coupled with a solar collector; CASE C: floor heating panel coupled with PVT collector; CASE D: radiant ceiling panels coupled with PVT collector; CASE E: floor heating panel coupled with ground-source heat pump; CASE F: radiant ceiling panel coupled with ground-source heat pump; CASE G: fan coil coupled with ground-source heat pump. Inlet and outlet stream for each case are reported in Table 1 Table 1. Input and output streams of simulated cases CASE Description Inputs Floor heating panel + A solar collector Water pumps electrical 81-6

Outputs Heating load of the building


power Solar irradiance

B

Radiant ceiling panels + solar collector

Water pumps electrical power Solar irradiance

C

Floor heating panel + PVT collector


Heating load of the building PVT Electrical Power

D

Radiant ceiling panels + PVT collector


Heating load of the building PVT Electrical Power

E

Floor heating panel + ground-source heat pump

F

G

Heating load of the building

Water pumps electrical power Ground heat


Water pumps electrical Radiant ceiling panel + power ground-source heat Heat to ground heat pump exchanger


Fan coil + groundsource heat pump

Water pumps electrical power Fan coil electrical power Heat to ground heat exchanger


5. 5. Input data 5.1 CFD simulations The object of the simulations is a simple two-levels house. The ground floor consists of a single room, while the first floor consists of two rooms, so that the building consists of three enclosed spaces which have a strong thermal interaction, Fig.2 and Table 2. The wall separating the two floors is thermal insulating and is characterized by a thermal conductivity of 0.03 W/mK. The wall separating the two rooms on first floor is an ordinary partition characterized by a thermal conductivity value of 0.3 W/mK. All remaining horizontal and vertical walls have a thermal conductivity value of 0.6 W/mK. The heating devices examined in this work are floor and radiant panels and fan coil units. In each simulation, the building is heated by a single type of device. The heated floor or ceiling is considered isothermal, at a temperature of 300K and 303K, respectively. The mass flow rate through the fan coil units, two at the ceiling of the main floor and one at the bottom, is 0.16kg/s each and the outlet air temperature is 302K (this value is necessary to compensate heat losses). The outdoor temperature is 0°C and the solar radiation is 500W/m2, Table 3. The buoyancy-induced air flow inside the enclosures is assumed to be steady and incompressible.

81-7


The grid generator Gambit is used to create a mesh in the fluid domain. An unstructured mesh is used in entire domain except around the walls, where a boundary layer mesh is used. A proper mesh sensitivity analysis has been performed. The accuracy of the mesh results could be increased by refining the mesh, but the additional refinement is expensive in both computation cost and solution time. As a result, the number of nodal points used for computations for the three heating configurations is shown in Table 4. The optimal grid-size values, those used for computations, are such that further refinements do not produce noticeable modifications in the heat transfer rates. Table 2. Building geometry Building Ground floor-Room 0 First floor-Room 1 First floor-Room 2 Floor radiant panel (ground floor) Floor radiant panel (first floor-Room 1) Floor radiant panel (first floor-Room 2) Ceiling radiant panel (ground floor) Ceiling radiant panel (first floor-Room 1) Ceiling radiant panel (first floor-Room 2) Window (ground floor) Window (first floor)

Figure 2 Building geometry

Table 3. CFD simulations data input Mass flow Temperature(K) rate (kg/s) Floor radiant 300 panel Ceiling radiant 303 panel Fan Coil Unit 0.16 302

Dimension (m) 10(w)x4(d)x6(h) 10(w)x4(d)x3(h) 5(w)x4(d)x3(h) 5(w)x4(d)x3(h) 10(w)x4(d) 5(w)x4(d) 5(w)x4(d) 10(w)x4(d) 5(w)x4(d) 5(w)x4(d) 0.9(w)x2.2(h) 0.9(w)x1.5(h)

Internal emissivity (at ~ 300K) 0.96

Outdoor temperature (K) 273

Solar radiation (W/m2) 500

0.96

273

500

-

273

500

Table 4. Mesh sensitivity analysis

Number of nodal points per meter 70 80 90 100

Floor radiant panel Heat transfer rate (W/m2) 57.9 60.5 65.4 67.6

Ceiling radiant panel Heat transfer rate (W/m2) 85.3 91.8 96.4 100.1 81-8

Fan Coil Unit Heating capacity (W) 1463 1516 1599 1649


120

67.9

100.5

1663

5.2 Building energy systems simulations The main parameters assigned in CAMEL-ProTM process simulations are reported in Table 5 Table 5 Process simulation input parameters Parameter

Description [3]

Value

Units

η0

SCconstant

0.819

-

k1

SCconstant

3.125

W/m2K

k2

SCconstant

0.022

W/m2K2

ηP

Pumps hydraulic efficiency Pumps mechanic efficiency RHpressure losses

0.9

-

0.98

-

2

%

0.00872

kW/m2K

0.00174

kW/m2K

0.001395

kW/m2K

0.006978

kW/m2K

0.0015

W/mK

0.8

-

0.98

-

15

°C

ηP.m ΔpRH kA (Floor Panels) kA (Ceiling Panels) kB (Floor Panels) kB (Ceiling Panels) λ ηComp,HP ηmecc,HP Tsoil

RH upward thermal transmittance RH upward thermal transmittance RH downward thermal transmittance RH downward thermal transmittance thermal conductivity Heat Pump compressor efficiency Heat Pump mechanical efficiency Ground temperature

ηComp,HP

Ground heat exchanger efficiency

90

%

ΔpFCU

FCU pressure losses (water side)

5

kPa

81-9


ΔTw,FCU

FCU Water temperature difference

10

K

For each configuration simulations have been performed the heat demand value calculated from the CFD simulations,depending on the type of heating device selected (Table 6) . Table6. Process simulation main data inputs: heat demands and characteristic temperatures for each case. Parameter Heat Demand RH Inlet water T RH Outlet water T HP Inlet ground water T HP Outlet ground water T FCU inlet water FCU air outlet T

Units

A

B

C

D

E

F

G

W

4350

6500

4350

6500

4350

650 0

6600

K

318

313

318

313

318

313

-

K

310

310

310

310

310

310

-

K

-

-

-

-

285

285

285

K

-

281

281

281

K

-

-

-

307

K

-

-

-

303

-

6. 6. Results 6.1 Results of the CFD simulations The results of the CFD simulations are shown in Figures 3 to 5 were the flow and temperature patterns for all configurations are shown in terms of isotherm contours and stream function, plotted on the central section of the building. The streamlines are coloured by their respective mass flow rates, which are proportional in each point to the local velocity vector. The heat transfer rate required to meet the environmental comfort standards for floor and ceiling radiant panel configuration is 67.6W/m2 and 100.1 W/m2, respectively. The actual thermal power required to meet the environmental comfort standards for each fan coil heating is 1649W. The ideal standard for thermal comfort can be defined by the operating temperature, which is the average of the air dry-bulb temperature and of the mean radiant temperature at a given place in a room. The operating temperature intervals vary depending on the type of indoor location. They also vary by the time of year. ASHRAE [20] has lists of suggested temperatures, in different types of buildings and different environmental conditions. For a single room in a building, with an occupancy ration per square meter of 0.1, the recommended winter operating temperature is between 21 °C and 24°C. From this point of view, the best heating device, which also provides an homogeneous temperature distribution, is the floor radiant panel. In addition, this configuration 81-10


provides a greater improvement because it generates circulation cells so that stagnation zones, which are the cause of mold and moisture in buildings, are avoided.

Figure 3 Isotherms (K) and stream function (kg/s) for floor radiant panel configuration

Figure 4 Isotherms (K) and stream function(kg/s) for ceiling radiant panel configuration

Figure 5 Isotherms (K) and stream function(kg/s) for Fan Coil Units configuration

6.2 Exergy analysis The main results of the exergy calculations are reported in Figure 6. The exergy input represents the total “exergy load” in our simplified building model. It is the total “external” power required by the 81-11


heating system to obtain the desirable user’s comfort. The exergy output is for all practical purposes the exergy of the heat load calculated at some proper average temperature (we used the LMTD of the heating device). The exergy efficiency is the ratio of the latter to the former (in exergy terms, of the “product” to the “fuel”). The system that presents the best exergetic performance is Case C (floor heating panel coupled with PVT) with an overall exergy efficiency of 12,11%. The results show (see Figs 7 and 8) that -under the conditions assumed in these experiments- the best external system performer is the GSHP that uses less exergy than the solar thermal panel to deliver the same heat load. It is not surprising that solar thermal collectors have a lower efficiency as hot water generators: they have an intrinsically low exergy efficiency (on the average, their exergy destruction amounts to 65-80%). With the new generation of hybrid solar collectors – PVT ( Cases C and D), which, besides the heated water, co-generate electrical power, the values of exergy efficiency are 12,11% for Case C and 11,52% for Case D, 2% higher than that of the solar collector. Therefore, applying solar collectors for a space heating purposes (hot water generation) remains the worst scenario. The internal heating elements have also different exergetic performances: the floor panel is more efficient because the natural air circulation it generates improves the heat convection in the room and reduces the overall thermal load (more uniform inside temperature), the worst is the fan coil that uses direct external electrical power.

Figure 6 Exergy analysis results: Exergy Inlet, Outlet and Exergy Efficiency for each case.

Figure 7 Exergy destruction within external components components 81-12

Figure 8 Exergy destruction within internal


Conclusions Scope of this study was to test a novel systemic approach to the joint design-and-analysis of space conditioning. In order to identify more thermodynamically efficient configurations, and using only commercially available devices, the proposed procedure is developed along the following steps: first, a refined estimate for the thermal power requirements for a given heating system inserted into a prescribed residential space is obtained by CFD simulations. Then, the data thus obtained are elaborated by a process simulator in order to calculate the total exergy demand for the (steady) operation of the space heating system. Finally, the exergy efficiency of each configuration is calculated and the tested configurations are ranked accordingly. Seven study cases are presented and discussed. The results show that the heating plant consisting of floor heating panel coupled with PVT is the most efficient solution, since it covers the same thermal load with the best overall exergy efficiency. The present paper demonstrates the feasibility of the proposed approach. More complex building envelopes and different combinations of internal/external heating devices can be tested. Cooling loads can be taken into account as well, and so on. The final goal is to develop an application to the entire (seasonal) operational curve of the “building+plant” system, including inertia effects. A systematic application of the procedure outlined in this study will help design less exergydestroying buildings, and reduce the exergy intensity of the Domestic and Tertiary sectors.

Nomenclature ex Ex 

specific exergy , kJ/kg Exergy flow, kJ/s

Ex

destroyed exergy , kW

ε η I h k ke m

turbulence dissipation rate, m2/s3 exergy efficiency Solar Irradiance , W/m2 specific enthalpy, J/kg thermal transmittance, W/m2K turbulence kinetic energy, m2/s2 mass flow rate, kg/s

P Q

Electric power, kW

R s T ηex

universal gas constant, J/(mol K) specific entropy, J/(kg K) temperature, K exergy efficiency, %

thermal power, kW

81-13


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