JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Optimal Coordination of Charging and Frequency Regulation for an Electric Vehicle Aggregator Using Least Square Monte-Carlo (LSMC) with Modeling of Electricity Price Uncertainty
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 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;
  PDF(new window)
 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.
 Keywords
Electric Vehicle;Frequency Regulation;Least Squares Monte-Carlo;
 Language
English
 Cited by
1.
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)
 References
1.
Willett Kempton and Jasna Tomic, "Vehicle-to-Grid Power Implementation: From Stabilizing the Grid to Supporting Large-Scale Renewable Energy," J. Power Sources, Vol. 144, No. 1, pp. 280-294, Jun. 2005. crossref(new window)

2.
Henrik Lund and Willett Kempton, "Integration of Renewable Energy into the Transport and Electricity Sectors Through V2G," Energy Policy, Vol. 36, No. 9, pp. 3578-3587, Sep. 2008. crossref(new window)

3.
Sekyung Han, Soohee Han, and Sezaki. K., "Estimation of Achievable Power Capacity From Plug-in Electric Vehicles for V2G Frequency Regulation: Case Studies for Market Participation," IEEE Trans. Smart Grid, Vol. 2, No. 4, Dec. 2011.

4.
Willett Kempton, et al., "A Test of Vehicle-to-Grid (V2G) for Energy Storage and Frequency Regulation in the PJM System," Nov. 2008.

5.
A. Y. Saber and G. K. Venayagamoorthy, "Intelligent Unit Commitment with Vehicle-to-Grid - a Cost-Emission Optimization," J. Power Sources, Vol. 195, No. 3, pp. 898-911, 2010. crossref(new window)

6.
F. A. Longstaff and E. S. Schwarts, "Valuing American Options by Simulation: A Simple Least-Squares Approach," Review of Financial Studies, 04, No. 1, pp. 113-147, 2001.

7.
Keith Cuthbertson and Dirk Nitzsche, "Financial engineering, derivatives and risk management", John Wiley & Sons Ltd, 2011.

8.
Hull, John, "Options, Futures, and other Derivatives," Pearson Education, Inc., pp. 263-280, 2009.

9.
A. Rodrigues and M. Armada, "The valuation of real options with the least squares monte carlo simulation method", SSRN, Feb. 2006.

10.
PJM Interconnection, http://www.pjm.com/