contributor author | Zhihao Li | |
contributor author | Yong Jiang | |
contributor author | Xu Zhang | |
contributor author | Wei Tian | |
date accessioned | 2017-05-08T22:33:05Z | |
date available | 2017-05-08T22:33:05Z | |
date copyright | September 2016 | |
date issued | 2016 | |
identifier other | 49292537.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/82462 | |
description abstract | This paper proposes an optimization algorithm for coordinating charging/discharging activities of plug-in hybrid electric vehicles (PHEVs) within the electricity market environment. PHEV Fleets are considered as a promising solution to provide vehicle-to-grid (V2G) services. The interactions between PHEVs and the power grid will bring many challenges to the current power market. In this paper, V2G is taken into account in the ancillary service market for providing frequency regulation service. Large-scale PHEV fleet integration will cause load volatility and destabilize the grid if it is implemented without proper control. This paper proposes an optimal strategy to maximize the V2G profits while minimizing the charging costs. The optimal strategy is based on the price forecast for both residential electricity and market regulation. Because of the stochastic nature of electricity price, the proposed optimal problem is solved using stochastic dynamic programming to obtain an optimal solution with the price uncertainties taken into account. Constraints related to vehicle use as well as technical limitations are also considered. Numerical results show the effectiveness of the proposed optimal control strategy and the additional costs arising from discharging batteries for ancillary service can be partially or completely compensated by V2G profits. | |
publisher | American Society of Civil Engineers | |
title | Market-Based Optimal Control of Plug-In Hybrid Electric Vehicle Fleets and Economic Analysis | |
type | Journal Paper | |
journal volume | 142 | |
journal issue | 3 | |
journal title | Journal of Energy Engineering | |
identifier doi | 10.1061/(ASCE)EY.1943-7897.0000287 | |
tree | Journal of Energy Engineering:;2016:;Volume ( 142 ):;issue: 003 | |
contenttype | Fulltext | |