华南理工大学学报(自然科学版) ›› 2017, Vol. 45 ›› Issue (4): 30-36,43.doi: 10.3969/j.issn.1000-565X.2017.04.005

• 动力与电气工程 • 上一篇    下一篇

配电网分布式风电与电池储能的协调优化配置

欧阳森 陈欣晖 杨家豪   

  1. 华南理工大学 电力学院//广东省绿色能源技术重点实验室,广东 广州 510640
  • 收稿日期:2016-06-01 修回日期:2016-10-31 出版日期:2017-04-25 发布日期:2017-03-01
  • 通信作者: 欧阳森( 1974-) ,男,博士,副研究员,主要从事电能质量、节能技术与智能电器研究. E-mail:ouyangs@scut.edu.cn
  • 作者简介:欧阳森( 1974-) ,男,博士,副研究员,主要从事电能质量、节能技术与智能电器研究.
  • 基金资助:

    广东省自然科学基金资助项目( 2016A030313476)

Coordinated Optimal Allocation of Distributed Wind Generator and Battery Energy Storage in Distribution Network

OUYANG Sen CHEN Xin-hui YANG Jia-hao   

  1. School of Electric Power//Key Laboratory of Clean Energy Technology of Guangdong Province,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2016-06-01 Revised:2016-10-31 Online:2017-04-25 Published:2017-03-01
  • Contact: 欧阳森( 1974-) ,男,博士,副研究员,主要从事电能质量、节能技术与智能电器研究. E-mail:ouyangs@scut.edu.cn
  • About author:欧阳森( 1974-) ,男,博士,副研究员,主要从事电能质量、节能技术与智能电器研究.
  • Supported by:
    Supported by the Natural Science Foundation of Guangdong Province( 2016A030313476)

摘要: 分布式风电( DWG) 与电池储能( BES) 在配电网中的位置与容量均会影响配电网的运行状态,为提高风电消纳能力,削弱风电出力不确定性对配电网运行的影响,在规划阶段应对二者进行选址定容协调优化配置. 文中以计及风- 储系统的随机潮流全面反映含DWG 及BES 的配电网运行状态及不确定性,以等年值综合收益最大化作为目标函数建立机会约束规划模型; 提出改进多种群遗传算法,引入有效的寻优机制以增强算法性能. IEEE 33 节点配电网算例的仿真分析验证了优化模型的合理性及算法的有效性.

关键词: 配电网, 分布式风电, 电池储能, 选址定容, 协调优化, 随机潮流

Abstract:

The location and capacity of distributed wind generator ( DWG) and the battery energy storage ( BES) both affect the operating state of the distribution system.In order to improve the wind power accommodation capacity of the distribution system and weaken the effect of wind power output uncertainty,a coordinated optimal allocation for the locating and sizing of DWG and BES is performed in the planning stage.Then,a chance-constrained programming model,of which the objective function is to maximize the annual comprehensive income,is established by taking into consideration the stochastic power flow of the wind-storage system to reflect the operating state and the uncertainty of the distribution system containing DWG and BES.Moreover,an improved multi-population genetic algorithm is proposed,and an effective searching optimal mechanism is introduced to enhance the performance of the algorithm.Simulated results on the IEEE 33-bus distribution system show that the proposed optimization model is rational and that the proposed algorithm is effective.

Key words: distribution network, distributed wind generator, battery energy storage, locating and sizing, coordinated optimization, stochastic power flow

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