Threshold-Bad-Scenario-Set Robust Energy Trading Decisions for Interconnected Microgrids Under Uncertain Electricity Price

Abstract

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 an 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 shared benefits generated from cooperation among microgrids are considered. Based on the threshold-bad-scenario (TBS) set concept proposed in 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: social robust cost minimization and trading payment. The alternating direction method of multipliers is applied to develop a distributed algorithm to solve the problem. The computational results show that the robust energy trading strategy can reduce the total cost of society by 8.89% and the cost of individual microgrids can be reduced by up to 12.34%. The proposed robust energy trading model can obtain various robust solutions with different degrees of tradeoff between robustness and optimality. The robustness prices of the robust solutions obtained are discussed to indicate the impact of the threshold values on the robustness prices.