Yang, Jiajia, Zhao, Junhua, Wen, Fushuan, Xue, Yusheng, Li, Liang, and Lv, Haohua (2014) Development of Bidding Strategies for Virtual Power Plants Considering Uncertain Outputs from Plug-in Electric Vehicles and Wind Generators. Dianli Xitong Zidonghua/Automation of Electric Power Systems, 38 (13). pp. 92-102.

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Abstract

The output of a virtual power plant (VPP) with wind power and dispatchable plug-in electric vehicles (EVs) included fluctuates as the result of the intermittence of wind power and uncertain number of EVs. Thus, in participating the competition in an electricity market, a VPP must address its output uncertainty. Given this background, the problems of developing a joint optimal bidding strategy for a VPP in the day-ahead spot market and regulation market are examined, with a special focus on the impacts of uncertain factors. Some assumptions are made: (1) the up and low limits of the wind power output are modelled as stochastic variables; (2) the electricity market prices in the day-ahead spot market and regulation market are modeled as stochastic variables with given intervals; (3) the number of EVs is huge, and could mitigate the output intermittence of wind power and at the same time participate the regulation market. Under these assumptions, a joint bidding strategy model for a VPP participating in the day-ahead spot and regulation markets is presented based on the robust optimization theory, with the battery discharging cost and the expected percentage of the bidded reserve capacity dispatched in each bidding period taken into account. Then, the commercial solver CPLEX 12.2 is next used to solve the developed robust optimization model. Finally, a sample example is employed to demonstrate the feasibility and efficiency of the developed model and algorithm.

Item ID:	82459
Item Type:	Article (Research - C1)
ISSN:	1000-1026
Date Deposited:	19 Dec 2024 06:57
FoR Codes:	40 ENGINEERING > 4008 Electrical engineering > 400805 Electrical energy transmission, networks and systems @ 100%
SEO Codes:	17 ENERGY > 1703 Energy storage, distribution and supply > 170309 Smart grids @ 100%
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