Abstract

The number of CHP units installed in domestic buildings is increasing rapidly in recent years, due to the fact that CHP has the potential to increase energy efficiency, to improve energy controllability and to reduce energy costs and carbon emissions. However, installing CHP with inappropriate capacity may increase energy costs and reduce energy efficiency. This paper first uses electricity and heat loads as sizing criteria to find the best capacities of gas engine and fuel cell CHP with the help of the maximum rectangle method (MR). Subsequently, the genetic algorithm optimisation technique (GA) will be used to optimise the daily energy costs of the different cases. Then, heat and electricity loads are jointly considered for sizing different types of CHP and for optimizing the daily energy costs through the GA method. Finally, the optimization results show that the GA sizing method gives a higher average daily energy cost saving, which is 13% reduction.

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