A Decentralized Energy Trading Framework for Active Distribution Networks with Multiple-Microgrids under Uncertainty

Abstract

The ever-increasing need for more reliable power supply, cost-effective and environmental-friendly utilization of distributed energy resources will result in formation of multiple microgrids (MMGs) in the near future of distribution system. To achieve this prospective, a coordination among MMGs is necessary. Accordingly, this paper proposes a new non-hierarchical multilevel architecture for the optimal scheduling of active distribution network (ADN) with MMGs. The proposed model is a decentralized decision making algorithm to optimally coordinate the mutual interaction between local optimization problems of ADN and MMGs. A non-hierarchical analytical target cascading (ATC) method is presented to solve the local optimization problems in parallel. Also, underlying risks of the energy trading caused by renewable generation uncertainty are reflected in both the objective functions and the constraints of local optimization problem. The numerical results on modified IEEE 33-bus distribution test system containing two microgrids demonstrate the effectiveness and merits of proposed model.