Hyperfine optimal dispatch for integrated energy microgrid considering uncertainty

•A hyperfine dispatch model for IEM is proposed. This model presents fine-grained mechanism and constructs the complement model for purification subsystem model to achieve more accurate optimal dispatch.•An optimal dispatch strategy is derived based on DRO considering the uncertain PV prediction error. DRO combines the advantages of robust optimization (RO) and stochastic optimization (SO) to overcome the limitations of the above two methods.•A piecewise McCormick algorithm with parallel computation is designed as the solving strategy, which can significantly reduce the optimization time and guarantee solution performance for optimal dispatch. Different from the traditional microgrid, the optimal dispatch of integrated energy microgrid (IEM) may face the problems of infeasibility, non-convexity and quantification of uncertainties. To fill this gap, this paper presents the hyperfine optimal dispatch methodology for IEM considering uncertainties. The proposed method not only reveals the impact of time resolution for integrated energy optimal dispatch, but also solves the uncertainty of photovoltaic (PV) power prediction error based on distributionally robust optimization (DRO). To cape with the complexity and non-convexity of the proposed model, a piecewise McCormick algorithm with parallel computation is constructed. The case studies are performed to demonstrate the benefits of the proposed optimal dispatch in terms of operation economics, model feasibility, optimization computation time and robustness.