计及电动汽车无功支撑能力的分布式电源与智能停车场联合规划方法

doi:10.19595/j.cnki.1000-6753.tces.L70751

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Abstract With the growing penetration of distributed generations (DG) and electric vehicles (EV), the coordinated planning of the above two is necessary to ensure efficient, clean, economical and safe operation of distribution grids. Thus, this paper proposes a joint planning method for DG and intelligent parking lots which takes account of the reactive power capacity of EVs. Firstly, based on the fundamental structure of active distribution network, the adjustable range of reactive power of EV power battery is derived. Then, to represent the temporal and spatial uncertainties that associated with stochastic generation, traditional demand and EV charging loads, a series of generation-demand scenarios are built. On this basis, a two-stage planning model for optimal siting and sizing DG and intelligent parking lots (IPL) is developed, which takes the minimization of system construction and operation cost as the goal. According to the feature of the model, genetic algorithm is used to solve the problem. Effectiveness of the proposed model is tested on the 33-node distribution system, and the results show that considering reactive supporting capability of EV in distribution system planning can improve power quality and promote the efficiency for renewable energy utilization, thus bringing better economic benefits.

Key words： Distributed generation electric vehicle reactive support active distribution network dual-stage optimization

Received: 22 August 2016 Published: 22 December 2017

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TM715

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	Zeng Bo
	Li Yingzi
	Feng Jiahuan
	Zhang Jianhua
	Liu Zongqi

Cite this article:

Zeng Bo,Li Yingzi,Feng Jiahuan等. A Combinatorial Planning Method for Distributed Generation and Intelligent Parking Lots Considering Reactive Supporting Capability of Electric Vehicles[J]. Transactions of China Electrotechnical Society, 2017, 32(23): 185-197.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.L70751 OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I23/185

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