In this chapter a MINLP model has been presented for evaluating a SOFC based micro-CHP design in a dwelling. The model identi es the optimal values for the max- imum capacity and output of plant considering simultaneously a variety of electricity and heat sources included in the proposed design.
It has been established that a micro-CHP system when optimised on its environ-
mental bene ts can provide signi cant reduction in the dwelling's CO2 emissions.
This reduction can reach up to 20% depending on the design and operation. The fuel cell maximum electrical capacity ranges from 1.9-2.5 kW for all cases which is close to most existing micro-CHP products that are sized around that value. This
provides some indirect validation of the results from the industry, as the fuel cell based micro-CHP products are at the 1-3 kW capacity.
A TST can increase the energy availability of the system and reduce peaks of heat demand in winter. Including a TST in the design, allows for reduced sizing of plant as it was the case with the gas boiler in the winter day case studies. The boiler's capacity dropped from 11 kW to 8.5 kW while at the same time the hours of operation also dropped. The fuel cell system achieved longer operation and higher reductions
in CO2 emissions when storage was available. The TST allows the fuel cell micro-
CHP to cover the majority of the electricity demand and to minimise electricity import from the electricity grid even when there is no heat demand by storing the
recovered heat in the thermal storage tank. The eect of the TST on CO2 emissions
reduction is greater in winter than in summer. The 48 hour analysis that includes a more complete data set with winter and summer days, showed that a thermal storage tank is essential for the system to provide emissions reduction. The sizing of the boiler to cover the winter load and its operational turn down constraints cause
the system to produce some additional CO2 emissions.
The results showed that the fuel cell in some cases starts and stops twice during the examined periods (case 4, case 5, case 6). SOFCs operate at high temperatures so when an SOFC cools down to the environmental temperature it stresses the stack materials and results in degradation of the components [107]. Also, it would take
some time for it to warm up again to 700 oC-100 oC [108] and restart producing
electricity. The operation of SOFCs micro-CHPs fuelled by natural gas is depend- ent on the su ciency of heat provided by the fuel cell to the reformer to maintain the steam reforming reaction. On start up however, when heat from the fuel cell is not available, the reformer is designed to operate on partial oxidation which is an exothermic reaction. Partial oxidation and steam reforming occur combined at the reformer from low output to full output operation [108]. Recent research is focused on lowering SOFC operating temperatures in order to reduce thermal stress and in- crease start-up times. Alvarez et al. studied the optimisation of a hybrid start-up process of an intermediate temperature SOFC, showing that a start-up time of 286 s can be achieved [105]. In terms of thermal management an option is to seal with insulating materials the SOFC stack and keep it within the operating temperature of the stack. Apfel et al. showed that using Microtherm, a low-conductivity ma- terial, the cool down period can be extended to days [11]. Providing an eective thermal management strategy for SOFC based micro-CHPs becomes essential to re- duce thermal cycles as the number of total start-up cycles of SOFC systems should be below 100 [11]. Therefore, the results that allow the fuel cell to turn on and o
twice during a 24-hour period are still achievable as long as the stack temperature does not drop below the operating points. In terms of the system design the manu- facturers would be forced to seal the stack with an advanced insulating material to allow for this type of thermal management to occur and prevent stack degradation. Fuel cell micro-CHPs perform better in dwellings with lower heat than electricity demands due to their low heat-to-power ratio. This was demonstrated in this study as higher reductions occur at the summer case studies that heat and electricity demand are in the same order. This can be seen in table 6.9.
The methodology used in the presented work although subject to limitations (see 6.8) is a new approach in modelling micro-CHP fuel cell systems in dwellings. It considers the variability of the energy patterns of the dwelling which are produced in BIM software and the interaction with the fuel cell and its operation. It is not a technique that only maximises the fuel cell's e ciency which might not be the op-
timum choice for the overall CO2emissions of the system but considers the variation
of the dwelling's energy demand.
The results obtained by using the 48 hour data set give an approximation of how the system would perform on a yearly basis, however a bigger data set would give more representative results. This is the approach followed in the analysis presented in chapter 7.
Allowing any data set (real or from building simulation) to be used in the model as input the exibility of the process increases. This methodology is also very adapt- able to adding other technologies as the models for all plant are based on e ciency equations.