Robust Coordinated Optimization With Adaptive Uncertainty Set for a Multi-Energy Microgrid

Abstract

With the increasing integration of the multi-energy microgrid (MEM) with the distribution network (DN), the distributed coordination between MEM and DN becomes critical. This paper proposes a distributed scheduling method for the coupled MEM-DN under operational uncertainties. First, a worst-expectation min-max-max-min robust optimization model is formulated for MEM considering the uncertainties of renewable distributed generation (wind and photovoltaic) as well as its class probability. Second, the column and constraint generation algorithm with an alternating iteration strategy (C&CG-AIS) is proposed to accelerate the solution by decoupling the subproblems. Third, the multi-interval convex hull uncertainty set (MCHUS) is proposed to reduce the conservatism of robust optimization by decreasing the low-probability scenarios. Furthermore, the Bregman alternating direction method with multipliers (BADMM) is combined with the alternating optimization procedure (AOP) to overcome the convergence difficulty in the nonconvex distributed MEM-DN model. Finally, the effectiveness of the proposed model and method is verified by simulation tests based on IEEE-33 node DN and a park-level MEM.