A robust optimization approach for risk-averse energy transactions in networked microgrids

Abstract

Abstract In order to alleviate the risk of energy transactions in networked microgrids (MGs) under uncertainties, such as renewable energy and transaction prices, a risk-averse energy transaction approach is proposed based on robust optimization. A systematic combinatorial optimization is applied to model energy exchanges among MGs, and then a two-stage robust optimization model for energy transactions is formulated to optimize the joint operation of networked MGs. Furthermore, the proposed model can be effectively solved by column-and-constraint generation (C&CG) algorithm. Under different budgets of price uncertainty, the results show the proposed approach can not only achieve the optimal operational cost of networked MGs, but also ensure the robustness of energy transactions among MGs.