Multi-time-scale energy management strategy considering battery operation modes for grid-connected microgrids community

The advantages and promoting applications of the microgrids community (MGC) allows for a critical step being taken toward a smart grid. An energy management strategy (EMS) is essential to intelligently coordinate the operations of the MGC. This paper presents a multi-time-scale EMS considering battery operational modes for grid-connected MGCs. The proposed strategy consists of two modules: day-ahead integrated optimization and realtime distributed compensation. The first module aims to minimize the operational cost of the MGC considering battery free-overcharging protecting. This problem is solved by the mixed integer linear programming (MILP) simulating two charging/discharging modes: limited-current mode and constant-voltage mode. The second module is installed in local MGs to correct the optimizing deviations of the dayahead static scheduling, which are caused by predicting errors of renewable energy and loads. The main contribution of this work is integrating the advantages of global optimization of the centralized method and the fast computing speed of the distributed method. Experimental results prove the proposed EMS is feasible and effective. The computing time at each updating step is reduced by 75% on average, which has the potential to be adopted in engineering.<br/>