电动汽车集群并网的分布式鲁棒优化调度模型

doi:10.19595/j.cnki.1000-6753.tces.200531

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Abstract The coordinated regulation of electric vehicle (EV) cluster and distributed energy is a powerful means to ensure the optimal economic operation of the power grid. Considering the different preferences of EV users in actual scenarios, an EV control model with demand preferences is established. Then, the polyhedral uncertainty sets are constructed to represent the intermittent characteristics of wind and photovoltaic and the demand volatility of EV cluster in three dimensions: time, space and power interval. A deterministic optimization model is established with minimum cost of system operation, and based on the uncertainty set of polyhedrons, deterministic optimization is transformed into robust optimization through robust peer-to-peer transformation. The alternating direction method of multipliers(ADMM) algorithm is used to decouple the robust optimization model ,which achieves collaborative distributed iterative solution for EV clusters and other distributed energy sources. The example analysis demonstrates that the proposed robust optimization model minimizes the system operating cost while taking into account the preferences of EV users.

Key words： Electric vehicle demand difference robustness distributed optimization alternating direction method of multipliers (ADMM)

Received: 23 May 2020

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TM769

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	Xu Gang
	Zhang Bingxu
	Zhang Guangchao

Cite this article:

Xu Gang,Zhang Bingxu,Zhang Guangchao. Distributed and Robust Optimal Scheduling Model for Large-Scale Electric Vehicles Connected to Grid[J]. Transactions of China Electrotechnical Society, 2021, 36(3): 565-578.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.200531 OR https://dgjsxb.ces-transaction.com/EN/Y2021/V36/I3/565

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