Optimal Coordination of Charging and Frequency Regulation for an Electric Vehicle Aggregator Using Least Square Monte-Carlo (LSMC) with Modeling of Electricity Price Uncertainty
- Authors
- Lee, Jong-Uk; Wi, Young-Min; Kim, Youngwook; Joo, Sung-Kwan
- Issue Date
- 11월-2013
- Publisher
- SPRINGER SINGAPORE PTE LTD
- Keywords
- Electric Vehicle; Frequency Regulation; Least Squares Monte-Carlo
- Citation
- JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, v.8, no.6, pp.1269 - 1275
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
- Volume
- 8
- Number
- 6
- Start Page
- 1269
- End Page
- 1275
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/101677
- DOI
- 10.5370/JEET.2013.8.6.1269
- ISSN
- 1975-0102
- Abstract
- 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.
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Collections - College of Engineering > School of Electrical Engineering > 1. Journal Articles
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