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A coordinated approach to energy exchange between electric vehicle load aggregators and wind generation companies under uncertainty

Citation

Tavakoli, A and Negnevitsky, M and Muttaqi, KM, A coordinated approach to energy exchange between electric vehicle load aggregators and wind generation companies under uncertainty, Proceedings of the 2015 IEEE Power and Energy Society General Meeting, 26-30 July, Denver, CO, USA, pp. 1-5. ISBN 978-1-4673-8040-9 (2015) [Refereed Conference Paper]


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Copyright Statement

Copyright 2015 IEEE

Official URL: http://www.pes-gm.org/2015/

DOI: doi:10.1109/PESGM.2015.7285807

Abstract

The use of wind energy sources for supplying electric vehicle (EV) loads is a challenge for electricity market operators due to their inherent uncertainty in the current market architecture. Coordinated energy exchange between EV load aggregators and wind generating companies (WGenCOs) can potentially increase the competitiveness of WGenCOs and EV-load customers in the energy market. This paper proposes a bilateral contract between WGenCO and EV load aggregators with coordinated scheduling in the day-ahead, balancing, and ancillary markets. A stochastic optimal bidding/offering strategy model is developed to mitigate wind energy and EV imbalance threats, and optimize EV charging profiles. Stochastic intra-hour optimization is solved by mixed-integer linear programming (MIP). Case studies are considered for investigation of the payoff analysis, and generation and demand dispatch.

Item Details

Item Type:Refereed Conference Paper
Keywords:ancillary market, balancing market, day-ahead market, electric vehicles, wind power generation, stochastic optimization
Research Division:Engineering
Research Group:Electrical and Electronic Engineering
Research Field:Power and Energy Systems Engineering (excl. Renewable Power)
Objective Division:Energy
Objective Group:Energy Storage, Distribution and Supply
Objective Field:Energy Services and Utilities
Author:Tavakoli, A (Mr Ahmad Tavakoli)
Author:Negnevitsky, M (Professor Michael Negnevitsky)
ID Code:105789
Year Published:2015
Deposited By:Engineering
Deposited On:2016-01-14
Last Modified:2017-08-07
Downloads:0

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