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contributor authorZhihao Li
contributor authorYong Jiang
contributor authorXu Zhang
contributor authorWei Tian
date accessioned2017-05-08T22:33:05Z
date available2017-05-08T22:33:05Z
date copyrightSeptember 2016
date issued2016
identifier other49292537.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/82462
description abstractThis 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.
publisherAmerican Society of Civil Engineers
titleMarket-Based Optimal Control of Plug-In Hybrid Electric Vehicle Fleets and Economic Analysis
typeJournal Paper
journal volume142
journal issue3
journal titleJournal of Energy Engineering
identifier doi10.1061/(ASCE)EY.1943-7897.0000287
treeJournal of Energy Engineering:;2016:;Volume ( 142 ):;issue: 003
contenttypeFulltext


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