A Three-Level Framework for Determining the Optimal Strategy of Microgrids to Participate in the Day-Ahead Competitive Market by Considering Electric Vehicles and Demand Response Programs
Subject Areas : Renewable energyAbolfazl Bayatian 1 , Amir Ahmarinejad 2
1 - Department of Electrical Engineering- Yadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran
2 - Department of Electrical Engineering- Central Tehran Branch, Islamic Azad University, Tehran, Iran
Keywords: Demand Response Programs, optimal bidding strategy, renewable energy resources, electric vehicles, Microgrids Scheduling, Cooperative Game Theory Approach,
Abstract :
In this paper, a three-level scenario-based framework for determining the optimal strategy and planning of microgrids located in a 118-bus distribution system is presented. This paper considers the uncertainties of renewable energy resources, load demand, and the charge / discharge schedule of electric vehicles. In order to increase planning flexibility, the operator will be able to change the flow through the distribution feeder reconfiguration. Also in the proposed model, customers will be able to reduce their costs by participating in a demand response program. In the first level of the proposed model, the bidding strategy of microgrids is determined. In the second level, the market clearing price is determined by the independent system operator and according to the submitted bids. Finally, in the third stage, the problem of final microgrid programming is solved by a participatory game theory method. The proposed model is solved by the CPLEX solver in GAMS software and the results show that the dynamic topology improves the planning flexibility and thus reduces the total operating cost by about 10%. The results also show that the coordination of electric vehicles with scheduling, the presence of storage systems and the implementation of the demand response program leads to a significant reduction in the level of market-clearing price and thus reduce operating costs.
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