电气工程学报 ›› 2017, Vol. 12 ›› Issue (8): 42-49.doi: 10.11985/2017.08.007

• 工程技术 • 上一篇    下一篇

考虑DG、DS和EV协同运行的配电网无功优化方法

陈嘉威1,吴杰康2,郭清元1,赵守安2,徐宏海1   

  1. 1. 广东电网有限责任公司东莞供电局 东莞 523008
    2. 广东工业大学自动化学院 广州 510006
  • 收稿日期:2016-12-18 出版日期:2017-08-25 发布日期:2019-12-11
  • 作者简介:陈嘉威 男 1988年生,工程师,从事电网调度运行方面的工作。|吴杰康 男 1965年生,博士,教授,研究方向为电力系统运行与控制。
  • 基金资助:
    国家自然科学基金项目(50767001);广东省公益研究与能力建设专项资金项目(2014A010106026);中国南方电网有限责任公司科技项目(031900KK52150047)

Reactive Power Optimization Method for Distribution Network Considering DG, DS and EV Cooperative Operation

Chen Jiawei1,Wu Jiekang2,Guo Qingyuan1,Zhao Shouan2,Xu Honghai1   

  1. 1. Dongguan Power Supply Bureau Guangdong Power Grid Corporation Dongguan 523008 China
    2. School of Automation Guangdong University of Technology Guangzhou 510006 China
  • Received:2016-12-18 Online:2017-08-25 Published:2019-12-11

摘要:

综合考虑分布式电源、电动汽车充放电和分布式储能运行的协调配合,并与不同类型无功补偿装置输出无功功率的协同控制,以配电网有功网损及电压波动量最小化为目标函数,建立配电网无功优化的多目标优化模型。考虑风速的概率特性、日照强度的不确定性、荷电状态和充放电特性以及运行效率,构建分布式风电机组出力、光伏发电系统出力、电动汽车充放电功率以及储能装置充放电功率的随机模型。选择DG、DS和EV等无功功率作为控制变量,采用遗传算法对优化问题进行求解。仿真计算表明了本文构建的无功优化模型的适应性和所提算法的可行性和有效性。

关键词: 新能源配电网, 无功优化, DG、DS和EV协同运行, 无功补偿装置

Abstract:

A reactive power optimization model is presented considering operation coordination of distributed generation, electric vehicle charging and distributed storage systems, and coordinative control of DG, DS, EV and other different types of reactive power compensation devices in power distribution network. In the proposed model, power loss and voltage fluctuation minimization is taken as the objective function. Considering the probabilistic characteristics of wind speed, the uncertainty of sunshine intensity, charge state and charge discharge characteristics,and the operation efficiency, a stochastic probabilistic model is constructed for power output of distributed wind turbine power output of PV system, charging and discharging power of electric vehicle, and charging and discharging power of energy storage device. The reactive power of DG, DS and EV is chosen as control variable, and genetic algorithm is used to solve the optimization problem. The simulation results show the adaptability of the proposed reactive power optimization model, and the feasibility and effectiveness of the proposed algorithm.

Key words: Distribution grids with renewable energy, reactive power optimization, coordinative operation of DG、DS and EV, reactive power compensation devices

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