Modelling and evaluation of building integrated SOFC systems

i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 6 ( 2 0 1 1 ) 1 3 2 4 1 e1 3 2 4 9 Available at www.sciencedirect.com journal homepage: www.elsevier.com/locate/he Modelling and evaluation of building integrated SOFC systems Pejman Kazempoor*, Viktor Dorer, Andreas Weber Empa, Swiss Federal Laboratories for Materials Science and Technology, Building Science and Technology Laboratory, CH-8600 Dübendorf, Switzerland article info abstract Article history: This study presents the final results of a series of modelling steps which are undertaken for Received 3 March 2010 the performance assessment of the building cogeneration and polygeneration systems Received in revised form using solid oxide fuel cell (SOFC). Based on earlier work, generic SOFC cell stack and system 15 September 2010 models were developed and employed to analyze different SOFC systems configurations Accepted 1 November 2010 for optimal efficiencies, this SOFC system model is used to derive performance input data Available online 4 December 2010 for transient whole-building and energy system simulation tools which contain simpler SOFC system models. These steps are shortly summarized here. Then the final step, the Keywords: evaluation of building integrated co- and polygeneration SOFC systems in terms of primary Solid oxide fuel cell energy demand and CO2 emissions, employing such tools, is presented here for a poly- System model generation system with typical heating and cooling loads, and electricity demand profiles, Cogeneration for different SOFC systems, including a comparison to current standard technologies. Polygeneration Copyright ª 2010, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights Residential application 1. Introduction High efficiency building cogeneration (also termed combined heat and power -CHP) and polygeneration (including thermally driven cooling -TDC) systems using solid oxide fuel cell (SOFC) are expected to be one of the key technology options for improving building energy efficiency and reduce emissions. However, it is not a mature technology yet. There are a lot of uncertainties about the SOFC technology itself, and its integration into a building in terms of feasibility, performance, economics and controllability which must be investigated. If ongoing development programs succeed, SOFC’s high generation efficiencies, low emissions, quiet operation, high exhaust gas temperature, and wide range of capacity covering reserved. all types of buildings from single family homes to large scale commercial buildings will make it attractive for a range of distributed generation (DG) and CHP applications, providing stiff competition for the currently preferred DG technology [1]. However, not many SOFC systems are developed for the DG application yet, and even lesser experimental investigations are followed. There are a number of analytical and numerical methods which focus on optimising the SOFC cells and system parameters. However, only a few of them, e.g. by Braun [2], Lee [3] and Farhad [4], are suited for the analysis of building integrated applications. In the case of polygeneration, the presented works are more limited. Only very few studies were presented until now [5e7] and a complete model which can consider a general SOFC system as well as complete Abbreviations: CC, combined cycle; CGD, Cogeneration device; COP, coefficient of performance; DG, distributed generation; DHW, domestic hot water; GB, gas boiler; HHV, higher heating value; ICE, internal combustion engine; LHV, lower heating value; MC, mechanical chiller; MFH, multifamily house; NRPE, non-renewable primary energy; PEN, positive electrode-electrolyte-negative electrode; SC, space cooling; SH, space heating; SOFC, solid oxide fuel cell; TDC, thermally driven chiller; UCTE, Union for the Co-ordination of Transmission of Electricity, now part of the European network of transmission system operators for electricity (ENTSO-E). * Corresponding author. Tel.: þ41 44 823 55 11; fax: þ41 44 823 40 09. E-mail addresses: pejman.kazempoor@empa.ch, pejman.kazempoor@gmail.com (P. Kazempoor). 0360-3199/$ e see front matter Copyright ª 2010, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.ijhydene.2010.11.003 13242 i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 6 ( 2 0 1 1 ) 1 3 2 4 1 e1 3 2 4 9 building cooling and heating system, cannot be found in the open literature. For the performance assessment of building integrated SOFC systems, the interaction between the cogeneration system and transient building loads is considered using dynamic building simulation tools. Cogeneration models presently used are formulated on system level, based on quasi-steady state performance characteristics and with simple approximations for the transient behaviour. A typical model of this type is the fuel cell cogeneration system model developed within Annex 42 of the International Energy Agency’s Energy Conservation in Buildings and Community Systems Programme (IEA/ECBCS) [8], which uses a pragmatic “grey box” approach, where the model structure partially reflects underlying physical processes and partially relies on empirical relations. Subsystems are handled as control volumes for which one or more conservation equations are formulated. The whole fuel cell power module is considered as one control volume. In this paper, we refer to this model as the IEA Annex 42 fuel cell model. For a specific device, the cogeneration system model has to be calibrated using performance data gained from laboratory tests. Such calibration process using empirical data was demonstrated e.g. for a 2.8 kWAC SOFC device [9]. However, the experimental methods are restricted to the system characteristics such as size and configuration and it is not a general approach. Alternatively, the model parameters could also be derived using a detailed fuel cell system model including a detailed cell and stack fuel cell model. This approach is a relatively easy and straightforward way to derive the system parameters and evaluate variations of system size and configuration, but of course may lack of experimental verification. This last approach is followed in the present work. In the frame of the European PolySMART project [10], the performances of natural gas driven polygeneration SOFC systems were assessed by simulation in terms of primary energy demand and CO2 emissions, using SOFC system performance data derived from a detailed model. This work comprised the following modelling steps: A detailed SOFC cell model was developed. This cell model was extended to a generic SOFC stack model. The stack model was complemented to a system model comprising balance of plant components. This system model was employed to analyze SOFC systems fuelled by hydrogen and methane respectively. Different system configurations were studied and evaluated for optimal efficiencies. This SOFC plant model was used to derive performance input data for the transient whole-building and energy system simulation tool, which contains a simpler SOFC plant model. With this tool building integrated co- and polygeneration SOFC systems were evaluated in terms of primary energy demand and CO2 emissions, for a number of different cases in regard to polygeneration system configurations, building types, heating and cooling loads, and electricity demand profiles. In this paper the modelling steps for the cell, stack and system are only briefly described, as they are discussed in more detail in earlier publications [11,12]. The main purpose of this paper is to describe the methods applied for the integration of the SOFC model into a whole-building simulation tool and for the performance assessment of systems, and to demonstrate them in a building integrated polygeneration system example case, including the comparisons with current standard technologies. 2. SOFC cell and stack model description Only a brief description of the cell and stack models applied is given here (for details see [11]). In regards to their easier manufacturing, potential to provide higher power densities, and lower cost, the SOFC system considered in this research was constructed based on the planar SOFC cells in both anode-supported (or intermediate temperature) and electrolyte-supported (or high temperature) designs. A generic and detailed quasi 2D model including the mass, momentum, thermal and complete electrochemical analysis as well as the kinetic model of hydrocarbon reactions was developed for the considered geometry. The planar SOFC cell is divided into series of piped-type volumes (unit elements) and the finite volume method is used to discretize the governing equations on each unit element. The electrochemical analysis comprises the complete evaluation of the cell ohmic, activation and concentration polarisations. These polarisations are subtracted from the Nernst potential to calculate the unit element operational voltage [13]. The continuity equations comprise the anode and cathode molar flow rate variations due to the electrochemical, internal reforming of methane, and water-gas-shift reactions. To improve the accuracy of the thermal model, five layers of temperatures were considered in energy balance equations. Therefore, for each unit element the energy balance equations are written for the fuel and air side interconnectors, PEN (positive electrode-electrolyte-negative electrode), air and fuel streams. Radiation between solid parts is also considered in the thermal model. The SOFC cell model was validated with available numerical and experimental data for intermediate [14] and high temperature [15] SOFCs with internal reforming, showing the capacity to accurately predict their operating conditions. For the extension of the cell model to the entire stack, the following steps were considered [12]: 1) Several experimental results show that for an SOFC stack considering constant operational voltage is acceptable except for a few cells which are located on the top and end of the stack [16,17]. Therefore, it is assumed that the stack cells are equipotential. 2) Internal manifolding allows a great deal of flexibility in the stack design. Therefore, the stack pressure losses are calculated based on this type of flow distribution which is discussed in more detail in [12]. 3) Two radiative air pre-heaters (RAP) are attached to the stack to control the cell temperatures and manage the system waste heat. The heat exchange between RAPs and stack is considered in the extension of the cell model to the stack model. The RAP model and its integration to the stack are discussed in [12]. 3. Balance of plant component model definitions and assumptions The developed SOFC model was integrated into the system model, which considers all the necessary balance of plant (BoP) i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 6 ( 2 0 1 1 ) 1 3 2 4 1 e1 3 2 4 9 components, namely [12]: Fuel compressor, air blower, water pump, air and fuel ejector, external fuel pre-reformer, gas to gas heat exchanger, gas to water heat exchanger, DC to AC inverter, desulphuriser, radiation air pre-heater and air filter. Each component was individually modelled in the present work. A brief introduction to these system component models is given below; more detailed descriptions are presented in [12]: (1) Compressors, pumps and air blower are modelled in a similar way, based on efficiency expressions in function of the gas flow rate to the system. As the reactant flow rates to the system depend on the system size, different sources for efficiency data are used. For the systems considered here these values are taken from [18]. (2) A simple model is considered here for the desulphuriser. In this model only the pressure loss in the desulphuriser is accounted for. Two optional methods are applied to calculate it, based on constant or flow rate dependant pressure drop respectively. (3) The Effectiveness -NTU method is used for the modelling of the air and the fuel heat exchanger. (4) Mass, momentum and energy balance equations are used to model the air and fuel ejector, considering steady state conditions, constant cross-section mixing, and isentropic expansion of the actuating fluid. (5) Considering a steady state and adiabatic operation, mass and energy balance equations are used to calculate the reformer parameters. (6) A 1D finite volume model, considering the mass, energy and momentum conservation laws, was developed to calculate the heat transfer and flow quantities for the radiation air pre-heater (RAP). Two raps are considered for each stack. Incorporating the RAPs into the system depends on the considered BoP components and the procedure which is used to control the heat management. (7) Ideal combustion is considered for the burner. This means that all of the methane, hydrogen and carbon monoxide will be converted to carbon dioxide and steam. (8) The power conditioning unit (PCU) has been modelled considering a constant efficiency. 4. SOFC system model performance parameters The following performance parameters for cell and system evaluations were used: SOFC cell fuel utilization, air excess ratio, cell stack efficiency, electric efficiency, CHP efficiency and thermal-to-electric ratio (TER) respectively. They are defined as: UF ¼ n_ H2;consumed ð4n_ CH4 þ n_ CO þ n_ H2 ÞAn;In lCell ¼ hCell ðn_ O2 ÞCa;in ½2n_ CH4 þ 0:5ðn_ CO þ n_ H2 ފAn;In Stack hSy;E ¼ ¼ PDC ðn_ F LHVF ÞAn;In PAC;Net ðn_ F LHVF ÞSy;In (1) (2) (3) (4) 13243 hCHP ¼ PAC;Net þ Q_ CHP ðn_ F LHVF ÞSy;In (5) TER ¼ Q_ CHP PAC;Net (6) 5. System model descriptions and defining optimised cases All the components models described in the previous sections were integrated to build the system model. Incorporating internal reforming (IR), anode gas recycling (AGR) line, cathode gas recycling (CGR) line, and radiation air pre-heater (RAP); different system configurations fuelled by methane and hydrogen were studied and evaluated for optimal efficiencies [12]. The results showed that the incorporation of CGR to the SOFC system can effectively improve the electric and CHP efficiencies. It is also observed that the system performance can fairly increase with only partial internal fuel flow reformation in the SOFC anode surfaces, due to the lower auxiliary power consumption. The incorporation of RAPs to the system proofed to be an effective way to decrease the air excess ratio and thus allow for smaller heat exchanger size and lower cost, as well as for lower auxiliary power consumption. Since the RAP was designed based on the design-point characteristic, it has been observed that there are some uncertainties about how to dimension and operate the RAP when the cell parameters deviate much from the design-point values, especially because high pressure losses may arise in the RAP. The results also clearly indicated that the hydrogen-fuelled systems do not offer any electric efficiency advantages over methane-fuelled systems. Lower electric efficiency, higher TER and higher cell stack efficiency were observed for all of the hydrogen-fuelled cases in comparison to the methanefuelled cases. The results of system configuration evaluation and parametric studies of cell parameters, i.e. fuel utilization, cell voltage and inlet fuel flow, were used to determine optimised system design and part-load operation points. For the present study, two optimised system are considered. It should be mentioned that these two new systems are not identical to the ones presented in [12]. These systems are selected in regards to their fairly high electric efficiency in comparison to previously investigated systems and, as the dominant criterion, their high CHP efficiency. This selection is based on the experience gained in earlier studies of building integrated cogeneration systems [19]. The systems process flow diagrams for both considered cases are shown in Fig. 1 (Case (M1)) and Fig. 2 (Case (M2)). As can be seen, AGR, CGR, and IR concepts are implemented in these systems to achieve high CHP efficiencies. The basic system configuration is identical for both cases. However, a lower fuel utilization and higher anode and cathode gas recycling ratio are considered for Case (M2) in order to improve the CHP efficiency over the whole range of part-load operation. The input parameters for the two systems are shown in Table 1. The system capacities considered base on the total heat demand for space heating, domestic hot water and for the thermally driven chiller (Fig. 2). 13244 i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 6 ( 2 0 1 1 ) 1 3 2 4 1 e1 3 2 4 9 Fig. 1 e Process flow-sheet diagram of an optimised methane-fuelled SOFC system (Case (M1)), with data for typical operation point. 6. Performance characteristic curves The performance characteristics of the two optimised system mentioned above are employed here to derive SOFC system performance curves for energy and environmental impact studies of building integrated SOFC co- and polygeneration systems, using transient whole-building and plant simulation tools. In the IEA Annex 42 fuel cell model [8] (the model used in the present investigation), the whole fuel cell power module is considered as one control volume and the characteristics of this module have to be determined using either empirical data or data derived from a more detailed cell and stack fuel cell model. For an individual system, characteristics curves are used as input parameters to the IEA Annex 42 fuel cell model, namely power module electric efficiency and air flow rate versus power module net system AC power output. These curves are approximated by second (or higher) order Table 1 e Parameters for Case (M1) and Case (M2). Parameters SOFC stack input parameters Anode thickness (m) Cathode thickness (m) Electrolyte thickness (m) Interconnector thickness (m) Cell active area (width  height) (mm2) Channel height, fuel and air sides (m) Channel width, fuel and air sides (m) Fuel utilization (%) System input parameters-standard values Anode recycling ratio (%) Extent of methane reforming (percent of external reforming) Compressor efficiency (%) Blower efficiency (%) DC/AC convertor efficiency (%) Air feed Fuel feed to the systems Value Parameters Value 500  10 6 50  10 6 Average current density(A m 2) Air excess ratio 20  10 6 0.5  10 3 100  120 1  10 3 3  10 3 Case (M1): 80 Case (M2): 55 Max. PEN allowable temperature increase (K) Stack configuration Air and Fuel inlet temperatures to cells (K) Number of channels, fuel and air sides Number of cells Cell electrochemical and thermal properties 5000 Case (M1): 7.84 Case (M2): 7.06 <100 Co-flow 1023 25 250 Ref. [10] Case (M1): 60 Case (M2): 70 30% Fuel and air input temperature to system ( C) 15 Cathode recycling ratio (%) Case (M1): 60 Case (M2): 60 >2 50 900 W 101325 68 Ref. [14] 92 21%O2,79%N2 100% CH4 Steam to carbon ratio to cells and reformer Whole system exhaust gas temperature ( C) System heat losses (W) Inlet pressure (Pa) i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 6 ( 2 0 1 1 ) 1 3 2 4 1 e1 3 2 4 9 13245 Fig. 2 e Process flow-sheet diagram of an optimised methane-fuelled SOFC system (Case (M2)), with data for typical operation point. In the final step of the present investigation, the performances of natural gas driven polygeneration systems were assessed, using the transient whole-building and energy system simulation tool TRNSYS [20], with the Annex 42 SOFC plant model and the respective calibration input data incorporated. The performance evaluations are based on the methodology developed in the frame of IEA/ECBCS Annex 42 [21]. The system performances were determined in terms of nonrenewable primary energy (NRPE) demand and carbon dioxide equivalent (CO2-eq) emissions, and compared to a system with internal combustion engine (ICE) and the reference system. The reference system for all cases comprises a gas boiler (GB) and a mechanical chiller and grid electricity supply according to the selected generation mix. Two different grid electricity generation mixes were considered, using NRPE and CO2-eq emission factors from the ecoinvent, 2006 database [22]: (i) European mix according to UCTE and (ii) combined cycle (CC) power plant. Fig. 3 e Example of system performance curves for the methane-fuelled SOFC system configuration (Case (M1)), to be used as input to the IEA ECBCS Annex 42 fuel cell model. Fig. 4 e Example of system performance curves for the methane-fuelled SOFC system configuration (Case (M2)), to be used as input to the IEA ECBCS Annex 42 fuel cell model. polynomials. The procedure which should be applied to derive these curves was explained in [11]. Examples of the system performance curves for both Case (M1) and Case (M2) are shown in Figs. 3 and 4. Respective resulting performance curves derived from the IEA Annex 42 model are shown in Fig. 5. This model then is employed in the evaluation of building integrated co- and polygeneration SOFC systems, as outlined in the next section below. 7. Evaluation of building integrated co- and polygeneration SOFC systems 13246 i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 6 ( 2 0 1 1 ) 1 3 2 4 1 e1 3 2 4 9 Fig. 5 e Performance data curve of the calibrated Annex 42 model for Case (M1) and Case (M2). The ICE CGD is a commercially available device, operated in on-off mode at 5.5 kWe constant electric power, and 12.5 kW nominal thermal output at 60  C return flow water temperature; and with 27% electrical and 61% thermal efficiency (LHV). For the ICE CGD the IEA Annex 42 ICE model calibrated with data of an available unit measured within IEA Annex 42 [23] has been used. The two SOFC systems considered have a nominal power output of in the range of 10.7 kWe electric and 16.4 kW thermal at 40  C return flow water temperature. Both SOFC systems can be modulated down to 4.4 kWe electric and 2.7 kW thermal output. The TDC device is a 10 kW H2O/LiBr single effect absorption chiller with a COP of 0.76 at driving hot water inlet temperature of 75  C, cooling water inlet temperature of 27  C and chilled water inlet and outlet temperatures of 18  C and 15  C respectively. The TDC device is modelled using the characteristic temperature difference method. Models for the TDC and the cooling tower for the heat rejection are described in more detail in [24]. 7.2. 7.1. Building and loads Systems analyzed Fig. 6 shows the configuration of the considered polygeneration system, basically comprising a cogeneration plant device (CGD) and a thermally driven chiller (TDC). The system is supplemented with an auxiliary gas boiler and a mechanical chiller. A combined storage for heat and domestic hot water, a cold storage, pumps, valves and energy management and control devices complete the system. The electricity generated by the CGD is used at site or is supplied to the grid (and possibly later re-used, considering a grid loss factor of 10%). Two different CGDs were considered: (a) an internal combustion engine (ICE) and (b) the SOFC system. For the modelling of the building loads, a multifamily house (MFH) was assumed. Space heating and cooling loads were determined using the dynamic multi-zone building model of TRNSYS. Two different thermal zones, an attic and an intermediate zone, each representing a flat with 140 m2 reference floor area were modelled. The thermal properties concerning windows, walls, and roof in the attic dwelling are given in Table 2. The two zones are thermally not coupled. Adiabatic conditions are assumed in the next upper or lower zone. The size of the building was adjusted to the cooling capacity of the TDC system by using an integer multiplication factor to the thermal outputs of the intermediate zone. Here, a 3 storey Fig. 6 e Configuration of the assessed building integrated polygeneration system. i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 6 ( 2 0 1 1 ) 1 3 2 4 1 e1 3 2 4 9 13247 Table 2 e Multifamily house characteristics. Parameter Floor area per dwelling U-values of ground floor U-values of external walls U-values of roof U-values of window g-value of window Window area per dwelling Domestic hot water average consumption dwelling Domestic hot water temperature value Unit 2 140 0.56 0.49 0.38 2.8 0.76 20 200 m W/(m2 K) W/(m2 K) W/(m2 K) W/(m2 K) e m2 Liters/day 45  C MFH building consisting of 4 intermediate and 2 attic dwellings was assumed. The internal gains from inhabitants were considered according to a fixed daily occupancy profile with 3.3 people present at maximum per dwelling. For the gains from electricity use for appliances and lighting it is assumed that 58% of the electric energy remain inside the building as thermal energy. The external shading control was assumed as a function of the incident solar radiation, the room and ambient temperatures. During the heating season a natural air change rate of 0.4 was assumed due to leakages. During summer, natural ventilation including a night ventilation mode were assumed in order to reduce the cooling load. In the considered climate of Madrid the simulation resulted in a space heating demand per m2 energy reference floor area of 135 MJ/m2/a and a cooling demand of 45.7 MJ/m2/a. Heat and cold supplied by the system were emitted to the room spaces by a fan coil system. The set points for the room air temperature control were 20  C during the heating period and between 24 and 27  C during the cooling period, depending on the outside temperature. Room temperature control was with thermostatic valves with a 1 K proportional band. The reaction of the demand on a possible shortage in heat or cold delivery was taken into account within the following time steps. Such, the correct supply and return flow temperatures resulted and their influence on the thermal efficiencies of the devices could be taken into account. Also possible additional cooling loads due to condensation in the fan coil were taken into account. For the domestic hot water an average consumption of 200 litres per day and dwelling was assumed, with a stochastic load profile produced with the tool described in [25]. A medium electricity consumption of 3028 kWh/a per dwelling was assumed according to a measured load profile as provided by Annex 42 [26]. The MFH was modelled with two thermal zones i.e. one zone per dwelling, using the dynamic multi-zone building model of TRNSYS. In the considered climate of Madrid the simulation resulted in a heat demand per m2 energy reference floor area of 135 MJ/m2/a and a cooling demand of 45.7 MJ/m2/a. 7.3. Results Fig. 7 shows values per m2 energy reference floor area for the different energies and for the CO2 eq emissions, resulting for the four methane-fuelled cases, namely the SOFC M1 and M2 Fig. 7 e Energy demand and CO2-eq emission values per m2 energy reference floor area resulting for the four methane-fuelled cases (SOFC M1, SOFC M2, ICE, and GB reference case). cases, the ICE case, and the GB reference case. The SOFC systems produce slightly more heat than the ICE system as their heating capacity is also higher. The cold produced by the TDC is quite similar in all polygeneration cases, although more heat at higher temperature is available from the SOFC. Cold generated by the TDC covers more or less the demand for space cooling. Thus, the auxiliary mechanical chiller could be omitted without significantly affecting thermal comfort, which in fact would be done in reality in this case. However here it was added to the system in order to have fully comparable thermal comfort situations. Due to the higher electric efficiency and the modulating capability, the electricity generated by the SOFC systems is significantly higher than by the ICE CGD. The difference between case (M1) and (M2) is small. The potential of the SOFC systems for savings in both NRPE demand as well as CO2 emissions is clearly demonstrated. In the case of UCTE grid mix 66% reduction in NRPE demand and 35% in CO2 emissions resulted, compared to the reference case (14% NRPE and 14% CO2 emissions reduction for the CC plant case). At first glance the SOFC systems seem to be oversized as they run for a long time in part-load and the portion of the heat demand covered by the auxiliary gas boiler is quite small. But a special feature of SOFC based cogeneration devices is their characteristic of increasing electrical efficiency towards lower part loads, and thus of better performance in terms of NRPE demand and CO2-eq emission. The limiting factor for sizing is the assumed requirement that the system may not be shut off, as this may induce stack degradation problems. Therefore the system capacity is determined by the condition not to produce surplus heat during the season with the lowest heat demand at the smallest possible modulation rate. Not only the electric and overall efficiencies of the CGD but also the assumed grid electricity mix play a key role. The dominant role of the assumed electricity grid is confirmed, as already demonstrated in earlier performance assessments of residential cogeneration systems [19] and also shown in preliminary assessments of polygeneration systems [27]. 13248 8. i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 6 ( 2 0 1 1 ) 1 3 2 4 1 e1 3 2 4 9 Conclusions The performance of building integrated SOFC polygeneration systems is dependant (i) on the performance of the SOFC device, (ii) the polygeneration systems configuration with heat (and cold) storages, TDC device and control, and (iii) the respective building with its heating and cooling loads and electric demand. For the assessment of (annual) energy and emission, building simulation tools are employed, incorporating simplified models of SOFC and similar cogeneration devices. Normally, input data for such models must be determined empirically. In this paper, series of modelling steps are presented where these input data were generated by a SOFC system model, specifically developed for this task, were SOFC cell and stack module and BoP components are modelled in detail and different cell and system configurations can be optimised. Thus, the methodology and models presented allow directly on the one hand studying the effects of changes in SOFC cell and system configurations and in BoP components on the SOFC system performance, and on other hand assessing the influence of different SOFC system performance characteristics on the polygeneration system performance in its building integrated context. This is demonstrated for two SOFC systems integrated in a multifamily house. Compared to internal combustion based cogeneration and to traditional gas burner/mechanical chiller/grid electricity supply technology, significant savings in both energy and CO2 emissions resulted, especially when an UCTE electricity grid mix was assumed. Acknowledgements A part of this work was supported by the European Commission; project PolySMART (Contract No TREN/46/FP6EN/S07.64055/ 019988). Only the author’s view is reflected, and the European Community is not liable for any use that may be made of the information contained therein. references [1] Zogg R, Sriramulu S, Carlson E, Roth K, Brodrick J. Using solid-oxide fuel cells for distributed generation. ASHRAE Journal 2006;48:116e8. [2] Braun RJ, Klein SA, Reindl DT. Evaluation of system configurations for solid oxide fuel cell-based microcombined heat and power generators in residential applications. Journal of Power Sources 2006;158:1290e305. [3] Lee KH, Strand RK. SOFC cogeneration system for building applications, part 2: system configuration and operating condition design. Renewable Energy 2009;34:2839e46. [4] Farhad S, Hamdullahpur F, Yoo Y. Performance evaluation of different configurations of biogas-fuelled SOFC micro-CHP systems for residential applications. 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Nomenclature Latin letters HHV: Higher heating value, J mol 1 LHV: Lower heating value, J mol 1 _ Molar flow rate, mol s 1 n: n_ H2; consumed : Hydrogen consumed in each channel, mol s PAC,Net: Net system AC power output, W PDC: power output, W Q_ CHP : System output heat, J s 1 UF: Fuel utilization Greek letters h: Efficiency (%) lCell : Air excess ratio Sub scripts An: Anode Ca: Cathode CHP: Combined Heat and Power E: Electric F: Fuel In: Inlet Stack: SOFC stack Sy: System 13249 1