A Multi-objective Model Predictive Control Approach to the Energy Trading Problem in Vehicle-to-Grid System

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Karimi, Arash | 2019

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 52213 (05)
University: Sharif University of Technology
Department: Electrical Engineering
Advisor(s): Haeri, Mohammad
Abstract:
Electric vehicles (EVs) will be used rampantly in future transportation system. Although the uncontrolled charging of these EVs will be threatening for the stability and sustainability of the grid, a well-suited energy trading policy may provide a number of beneficial services to the grid as well as preserving the sustainability of the system along with heightening the performance of operation. In this paper, by taking advantage of block rate tariff, a wholesale pricing policy is introduced. A multi-objective approach is utilized to address the cost reduction and load levelling services, concurrently, in order to guarantee the profits of the both the grid and EVs. Due to the high computational complexity of a centralized problem, a game theoretic approach is exerted in order to design decentralized controllers for EVs. Moreover, an MPC approach is introduced to deal with unplanned deviation in the state of the system in future hours. Simulation results verify that the proposed method can effectively reform the performance of the system, namely, minimization of the total cost of energy trading and the variance of the load
Keywords:
Vehicle to Grid (V2G) ; Decentralized Control Strategy ; Predictive Control ; Multiobjective Optimization ; Game Theory

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