Sharif University of Technology Scientia Iranica 1026-3098 26 Special Issue on machine learning, data analytics, and advanced optimization techniques... 2019 12 01 Decentralized energy trading framework for active distribution networks with multiple microgrids under uncertainty 3606 3621 21558 10.24200/sci.2019.53962.3557 EN M. Doostizadeh Faculty of Engineering, Lorestan University, 5 km Tehran Road, Khorramabad, P.O. Box 68151-44316, Lorestan, Iran. M.R. Shakarami Faculty of Engineering, Lorestan University, 5 km Tehran Road, Khorramabad, P.O. Box 68151-44316, Lorestan, Iran. H. Bastami Faculty of Engineering, Lorestan University, 5 km Tehran Road, Khorramabad, P.O. Box 68151-44316, Lorestan, Iran. Journal Article 2019 07 17 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. https://scientiairanica.sharif.edu/article_21558_aa0395a7bbcb02611a479934297da60a.pdf