Threshold-bad-scenario-set Robust Energy Trading Decisions for Interconnected Microgrids under Uncertain Electricity Price

Microgrids can be cost-effective by reducing transmission and distribution losses, and enabling energy trading between microgrids can further optimize economic benefits. This paper discusses the energy trading decision problem of interconnected microgrids under uncertain electricity price between any microgrid and the main grid. The uncertain energy trading price is described by discrete scenarios. The interests of individual microgrids and the share benefits generated from the cooperation among microgrids are considered. Based on the threshold-bad-scenario (TBS) set concept proposed by our previous work, we propose a robust energy trading model. The TBS-set robust energy trading problem actually consists of a family of robust energy trading problems. Each robust energy trading problem is decomposed into two subproblems of social robust cost minimization and trading payment. The alternating direction method of multipliers (ADMM) is applied to develop a distributed algorithm to solve the problem. The computational results show that the robust energy trading strategy could reduce the total cost of the society by 8.89% and the robust cost of individual microgrid can be reduced by 12.34% at most. The proposed robust energy trading model could obtain various robust solutions with different degrees of tradeoff between robustness and optimality. The robustness prices of robust solutions obtained are discussed to indicate that the impact of the values of threshold on the robustness prices.