Decentralized energy trading framework for active distribution networks with multiple microgrids under uncertainty

The ever-increasing need for more reliable power supply as well as cost-effective and environmentally friendly utilization of distributed energy resources will result in the formation of Multiple Micro-Grids (MMGs) in the near future of distribution system. To reach this prospect, coordination among MMGs is necessary. Accordingly, this paper proposes a new non-hierarchical multi-level 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, the underlying risks of energy trading caused by renewable generation uncertainty are re ected in both the objective functions and the constraints of local optimization problem. The numerical results of modied IEEE 33-bus distribution test system containing two microgrids demonstrate the effectiveness and merits of the proposed model.