• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology

Article

Indian Journal of Science and Technology

Year: 2015, Volume: 8, Issue: Supplementary 3, Pages: 1-12

Original Article

Real-Time Energy Imbalance Management Scheme for Electric Vehicles in the Smart Grid

Abstract

Electric Vehicles (EVs) as the alternative of the current fossil fuels vehicles represent the most promising green approach to the electrification of a significant portion of the transportation sector. Taking the randomness of EV’s charging/ discharging characteristics into consideration, a significant uncertainty will be added to the grid by the large penetration of EVs. Consequently, charging/ discharging management of EVs in presence of large scale intermittent Renewable Energy Resources (RERs) are considered as the most significant challenge for the future smart grid. In this context, a novel marketoriented energy imbalance management scheme is proposed for the seamless integration of EVs to the grid. The proposed scheme which, unlike previous works, utilizes the grid’s operating characteristics model within the signaling game-theoretic approach for the successful operation of electicity market. Optimal decision strategies for both EV owners and utility are devised by capturing the conflicting economic interests of players together under load/generation uncertainities. The maximization of the profit expectation of each market player in the presence of independent multi-generation resources is considered. This facilitates both the customer and utility to derive their robust bidding strategies. The efficacy of the proposed approach in reducing peak loads while satisfying customers needs are demonstrated by simulating the various scenarios of different penetration levels of EVs to the grid. Results show that the proposed methodology can successfully alleviate the peaks caused by the mass adoption of EVs with the better utilization of RER.
Keywords: Electrical Vehicles, Management Scheme, Renewable Resources, Real-Time, Smart Grid

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