Optimal Trading Strategies for Multi-Energy Microgrid Cluster Considering Demand Response Under Different Trading Modes: A Comparison Study

Abstract

The linkage of neighborhood multi-energy microgrids (MEMGs) may overcome the disadvantage of one single microgrid (MG) since surplus/deficient energy can meet balance internally and realize self-satisfaction. In order to realize successful cooperation of such a complicated energy system, optimal trading strategy and reasonable trading price among all entities are important. In this study, a bi-level optimization model combined of two trading modes is proposed under different scenarios: intermediary agent (IA)-based trading mode where IA acts as an intermediate operator, as well as direct trading mode without IA. Stackelberg game theory (SGT) method and supply/demand (S/D) ratio method are used for price determination, respectively. Again, integrated demand response (IDR) is also considered in this study. As an illustrative example, a comparative study is implemented in a neighboring energy cluster combing three park-level MEMGs. The results show that, compared with the situation that each MEMG acts alone, a cluster obviously increase total benefit which may contribute to the development of tailored policy instruments. In addition, although direct trading among MEMGs enjoys higher benefit, self-sufficient ability is lower than the situation considering IA, which may help policy makers to more accurately predict merits and demerits associated with different energy trading modes among MEMGs.