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Optimal Coordination of Charging and Frequency Regulation for an Electric Vehicle Aggregator Using Least Square Monte-Carlo (LSMC) with Modeling of Electricity Price Uncertainty
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 Title & Authors
Optimal Coordination of Charging and Frequency Regulation for an Electric Vehicle Aggregator Using Least Square Monte-Carlo (LSMC) with Modeling of Electricity Price Uncertainty
Lee, Jong-Uk; Wi, Young-Min; Kim, Youngwook; Joo, Sung-Kwan;
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Recently, many studies have suggested that an electric vehicle (EV) is one of the means for increasing the reliability of power systems in new energy environments. EVs can make a contribution to improving reliability by providing frequency regulation in power systems in which the Vehicle-to-Grid (V2G) technology has been implemented and, if economically viable, can be helpful in increasing power system reliability. This paper presents a stochastic method for optimal coordination of charging and frequency regulation decisions for an EV aggregator using the Least Square Monte-Carlo (LSMC) with modeling of electricity price uncertainty. The LSMC can be used to assess the value of options based on electricity price uncertainty in order to simultaneously optimize the scheduling of EV charging and regulation service for the EV aggregator. The results of a numerical example show that the proposed method can significantly improve the expected profits of an EV aggregator.
Electric Vehicle;Frequency Regulation;Least Squares Monte-Carlo;
 Cited by
Decentralized Vehicle-to-Grid Design for Frequency Regulation within Price-based Operation,;;;;

Journal of Electrical Engineering and Technology, 2015. vol.10. 3, pp.1335-1341 crossref(new window)
Stochastic Charging Coordination Method for Electric Vehicle (EV) Aggregator Considering Uncertainty in EV Departures, Journal of Electrical Engineering and Technology, 2016, 11, 5, 1049  crossref(new windwow)
An optimal dispatching strategy for V2G aggregator participating in supplementary frequency regulation considering EV driving demand and aggregator’s benefits, Applied Energy, 2017, 190, 591  crossref(new windwow)
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