| 基于改进NSGA-II算法的含分布式电源配电网无功优化 |
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| 引用本文： | 张晓英,张艺,王琨,张蜡宝,陈伟,王晓兰.基于改进NSGA-II算法的含分布式电源配电网无功优化[J].电力系统保护与控制,2020,48(1):55-64. |
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| 作者姓名： | 张晓英 张艺 王琨 张蜡宝 陈伟 王晓兰 |
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| 作者单位： | 兰州理工大学 电气工程与信息工程学院,甘肃 兰州 730050;国网甘肃省电力公司电力科学研究院, 甘肃兰州 730050;南京大学 电子科学与工程学院,江苏 南京 210093 |
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| 基金项目： | 国家自然科学基金项目资助(51867015，51767017);甘肃省基础研究创新群体项目资助(18JR3RA133);甘肃省高校协同创新团队项目资助(2018C-09) |
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| 摘 要： | 针对含分布式电源(DG)的配电网无功优化的问题,为更准确地描述DG出力的不确定性,基于加权高斯混合分布(WGMD)和Beta分布分别构建风电DG和光伏DG的出力模型。采用结合切片采样算法的马尔科夫链蒙特卡洛模拟法进行潮流计算。建立以系统有功网损最小、节点电压总偏差最小为目标函数的多目标无功优化模型,并采用改进的非支配排序遗传算法(NSGA-Ⅱ)对该优化模型进行求解。通过改进的IEEE 33节点系统的仿真验证了所提方法的可行性和有效性。
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| 关 键 词： | 分布式电源 配电网无功优化 加权高斯混合分布 切片采样算法 改进的NSGA-Ⅱ算法 |
| 收稿时间： | 2019/1/20 0:00:00 |
| 修稿时间： | 2019/5/29 0:00:00 |
Reactive power optimization of distribution network with distributed generations based on improved NSGA-II algorithm |
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| ZHANG Xiaoying,ZHANG Yi,WANG Kun,ZHANG Labao,CHEN Wei and WANG Xiaolan.Reactive power optimization of distribution network with distributed generations based on improved NSGA-II algorithm[J].Power System Protection and Control,2020,48(1):55-64. |
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| Authors: | ZHANG Xiaoying ZHANG Yi WANG Kun ZHANG Labao CHEN Wei and WANG Xiaolan |
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| Affiliation: | College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China,College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China,State Grid Gansu Electric Power Company Electric Power Research Institute, Lanzhou 730050, China,School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China,College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China and College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China |
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| Abstract: | To more accurately describe the uncertainty of the DG power, this paper respectively establishes the output models of wind power DG and photovoltaic DG based on the Weighted Gauss Mixed Distribution (WGMD) and Beta distribution to solve the problem of reactive power optimization in the distribution network with Distributed Generations (DG). In the meantime, the Markov Chain Monte Carlo method combined with slice sampling algorithm is used for power flow calculation. The multi-objective reactive power optimization model which takes the minimum loss of the active power and minimum total voltage deviation of bus as objective function is established. And the improved Non- Dominated Sorting Genetic Algorithm (NSGA-II) is used to solve the optimization model. The feasibility and effectiveness of the proposed method is verified by the simulation of an improved IEEE33 node system. This work is supported by National Natural Science Foundation of China (No. 51867015 and No. 51767017). |
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| Keywords: | distributed generation reactive power optimization of distribution network weighted Gauss mixture distribution slice sampling algorithm improved NSGA-II algorithm |
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