源荷不确定性下基于自适应分布鲁棒优化的微电网日前调度OA

A day-ahead dispatch model for microgrids under source-load uncertainty conditions is established to enhance their economical effectiveness.In view of the source-load uncertainty composed of photovoltaic power and demand,a novel adaptive optimization decision-based distributionally robust optimization is proposed to overcome the conservativeness of traditional robust optimization.Firstly,a conser-vativeness-adjustable ambiguous set of source-load uncertainty is constructed,which can flexibly adjust the conservatism through distribu-tion constraints.Meanwhile,auxiliary uncertainty variables are introduced to transform the ambiguous set into a manageable form.Second-ly,leveraging the duality principle of infinite programming and fixing the dual variables,the distribution uncertainty is reduced to scenario uncertainty.Finally,employing an extreme dual variable generation method,the proposed model is converted into a deterministic program-ming in a two-stage solving framework.Numerical simulations verify the superiority of the proposed model in balancing the economical ef-fectiveness and robustness of microgrid operations.