Two‐stage robust optimal scheduling of cooperative microgrids based on expected scenarios

Abstract

Cooperative microgrids (CMGs) can effectively solve the energy interaction between microgrids (MGs) while increasing the penetration rate of renewable energy systems (RESs) and reducing the interaction frequency with the grid. However, the uncertainty of RESs will bring new challenges to the energy management and economic dispatch of CMGs, especially in increasing the number of MGs connected to the grid. Taking into account this uncertainty, it is extremely unlikely that the forecast uncertainty information will be at the worst values in every period, and this forecast uncertainty information is near the expected values in most cases. Therefore, a two-stage robust optimal model under expected scenarios for CMGs is proposed in this study to improve the conservatism of traditional models and minimise the daily cost. In this model, the first-stage decision results (FDRs) are determined by minimising the daily cost of CMGs under the expected scenarios. The proposed model is transformed based on two-stage zero-sum game theory and dual theory, a column and constraint generation algorithm is first used to test the robust feasibility of the FDR, and the second-stage decision results can be obtained without changing the FDR. Case studies verify that the proposed model can effectively solve energy transactions between MGs while mitigating the uncertainty disturbances in the operation of CMGs.