Distributed Optimal Energy Management of a Microgrid Community

This paper studies optimal scheduling of multiple microgrids using distributed coordination algorithms. Each microgrid is controlled by an individual agent using mixed-integer linear programming (MILP). The algorithm is designed towards a two-level microgrid community (MGC) structure, where the exchange power is adjusted several times through information communication between the upper-level agent and lower-level agents to minimize the operation cost. In the paper, an overview of the system model is first given, followed by a description of the distributed coordination algorithm in detail incorporating the mathematical modeling of the problem. A simulation study of the algorithm is performed based on a real MGC system. We found that the distributed coordination algorithm with multiple iterations can make the operation cost of the MGC system closer to the centralized result if appropriate parameter values are selected. Compared with other hierarchical energy management methods, our approach can achieve a lower cost.