In this paper, a geothermal heating system coupled with energy storage for office building heating has been studied. Optimization was carried out based on time-of-use electricity prices. The aim of this study is to lower the system’s operation cost and to have better techno- economic performance. By choosing the minimum levelized energy cost (LEC) as an objective function, the optimal values of 4 decision variables have been determined by using the Genetic Algorithm. 12 scenarios have been investigated. Comparison shows that the optimal energy storage ratio of the coupled heating system is between 23% and 25% in most scenarios. It has been found out that the energy-storage tank price, heat pump price, peak-valley electricity price difference and lower limit temperature of the energy- storage tank have obvious influence on the optimal energy storage ratio. Water pump price and heat exchanger price have little influence on the optimal energy storage ratio. The results obtained in this study are considered to be useful for the application of using geothermal energy for building heating.
Keywords geothermal heating system, energy storage, optimization, time-of-use electricity prices, Genetic Algorithm, decision variables, levelized energy cost