DocumentCode :
28078
Title :
Real-Time Load Elasticity Tracking and Pricing for Electric Vehicle Charging
Author :
Soltani, Nasim Yahya ; Seung-Jun Kim ; Giannakis, Georgios B.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Minnesota, Minneapolis, MN, USA
Volume :
6
Issue :
3
fYear :
2015
fDate :
May-15
Firstpage :
1303
Lastpage :
1313
Abstract :
While electric vehicles (EVs) are expected to provide environmental and economical benefit, judicious coordination of EV charging is necessary to prevent overloading of the distribution grid. Leveraging the smart grid infrastructure, the utility company can adjust the electricity price intelligently for individual customers to elicit desirable load curves. In this context, this paper addresses the problem of predicting the EV charging behavior of the consumers at different prices, which is a prerequisite for optimal price adjustment. The dependencies on price responsiveness among consumers are captured by a conditional random field (CRF) model. To account for temporal dynamics potentially in a strategic setting, the framework of online convex optimization is adopted to develop an efficient online algorithm for tracking the CRF parameters. The proposed model is then used as an input to a stochastic profit maximization module for real-time price setting. Numerical tests using simulated and semi-real data verify the effectiveness of the proposed approach.
Keywords :
electric vehicles; power distribution; pricing; secondary cells; smart power grids; stochastic processes; conditional random field model; distribution grid; electric vehicle charging; online convex optimization; pricing; real-time load elasticity tracking; smart grid infrastructure; stochastic profit maximization; Elasticity; Electricity; Heuristic algorithms; Load modeling; Pricing; Real-time systems; Stochastic processes; Conditional random field (CRF); online convex optimization; real-time pricing; smart grid;
fLanguage :
English
Journal_Title :
Smart Grid, IEEE Transactions on
Publisher :
ieee
ISSN :
1949-3053
Type :
jour
DOI :
10.1109/TSG.2014.2363837
Filename :
6948246
Link To Document :
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