Applied Energy, Vol.184, 375-395, 2016
Modeling a novel CCHP system including solar and wind renewable energy resources and sizing by a CC-MOPSO algorithm
Due to problems, such as, heat losses of equipment, low energy efficiency, increasing pollution and the fossil fuels consumption, combined cooling, heating, and power (CCHP) systems have attracted lots of attention during the last decade. In this paper, for minimizing fossil fuel consumption and pollution, a novel CCHP system including photovoltaic (PV) modules, wind turbines, and solid oxide fuel cells (SOFC) as the prime movers is considered. Moreover, in order to minimize the excess electrical and heat energy production of the CCHP system and so reducing the need for the local power grid and any auxiliary heat production system, following electrical load (FEL) and following thermal load (FTL) operation strategies are considered, simultaneously. In order to determine the optimal number of each system component and also set the penalty factors in the used penalty function, a co-constrained multi objective particle swarm optimization (CC-MOPSO) algorithm is applied. Utilization of the renewable energy resources, the annual total cost (ATC) and the CCHP system area are considered as the objective functions. It also includes constraints such as, loss of power supply probability (LPSP), loss of heat supply probability (LHSP), state of battery charge (SOC), and the number of each CCHP component. A hypothetical hotel in Kermanshah, Iran is conducted to verify the feasibility of the proposed system. 10 wind turbines, 430 PV modules, 11 SOFCs, 106 batteries and 2 heat storage tanks (HST) are numerical results for the spring as the best season in terms of decreasing cost and fuel consumption. Comparing the results of the system with a common separated production (SP) system shows that the fossil fuels consumption and the pollution can be reduced up to 263 and 353 times, respectively. (C) 2016 Elsevier Ltd. All rights reserved.