电工技术学报  2020, Vol. 35 Issue (23): 4940-4948    DOI: 10.19595/j.cnki.1000-6753.tces.191618
电力系统 |
基于聚类抽样的随机潮流计算
谢桦1, 任超宇1, 郭志星1, 张沛1, 郭宝甫2
1. 北京交通大学电气工程学院 北京 100044;
2. 许继电气股份有限公司研发中心 许昌 461000
Stochastic Load Flow Calculation Method Based on Clustering and Sampling
Xie Hua1, Ren Chaoyu1, Guo Zhixing1, Zhang Pei1, Guo Baofu2
1. School of Electrical Engineering Beijing Jiaotong University Beijing 100044 China;
2. Research and Development Center of Xuji Electric Co. Ltd Xuchang 461000 China
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摘要 随机潮流针对电网不确定因素建模,快速准确的计算结果对于系统运行控制非常重要。该文提出了基于聚类抽样的随机潮流计算方法。首先,基于历史数据,采用蒙特卡洛算法产生大量随机变量样本;其次,采用误差二次方和与平均轮廓系数确定样本聚类簇数,并采用K-means算法进行样本聚类;然后,依据聚类中心和簇内样本的平均概率密度,将簇内样本均值带入潮流方程中进行确定性潮流计算;最后,对潮流计算结果和对应的平均概率密度信息进行数据统计,得到状态变量的概率密度函数。以修改后IEEE 39系统和某实际区域电网为算例,进行计算精度和计算效率分析。结果表明,所提方法兼顾了计算速度和计算精度,在大系统中更具优势,可为电网调度计划的制定和运行分析提供决策依据。
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谢桦
任超宇
郭志星
张沛
郭宝甫
关键词 随机潮流不确定性聚类抽样    
Abstract:Stochastic load flow is designed for power systems with uncertainties, whose fast and accurate calculation results are very important for grid operational control. In this paper, a stochastic load flow calculation method was proposed on basis of clustering and sampling. Firstly, according to history data, Monte Carlo simulation method was used to generate a large number of random variable samples. Secondly, the optimal cluster number was determined for samples by the average silhouette coefficient and sum of squared error, and the samples were clustered by using K-means. Thirdly, according to the clustering center and the average probability density of the sample in the cluster, load flow was calculated with the mean values of each cluster. Finally, the power flow calculation results and the corresponding average probability density were statistically analyzed, and the probability density function of the state variables was obtained. The modified IEEE39 system and a real regional power grid were taken as examples to analyze the calculation accuracy and calculation efficiency. The results show that the method proposed in this paper can balance calculation accuracy and calculation speed, and there are more advantageous in large systems. It provides decision basis for grid dispatching plan and operation analysis.
Key wordsStochastic load flow    uncertainty    clustering    sampling   
收稿日期: 2019-11-26     
PACS: TM711  
基金资助:国家电网有限公司总部科技项目“新一代能源发展战略评估推演关键技术及应用研究”资助(SGXJJY00GHJS1900031)
作者简介: 谢 桦 女,1970年生,博士,副教授,研究方向为储能规划与控制、综合能源系统优化运行。E-mail:hxie@bjtu.edu.cn;任超宇 男,1994年生,硕士研究生,研究方向为电力系统分析。E-mail:494192416@qq.com
引用本文:   
谢桦, 任超宇, 郭志星, 张沛, 郭宝甫. 基于聚类抽样的随机潮流计算[J]. 电工技术学报, 2020, 35(23): 4940-4948. Xie Hua, Ren Chaoyu, Guo Zhixing, Zhang Pei, Guo Baofu. Stochastic Load Flow Calculation Method Based on Clustering and Sampling. Transactions of China Electrotechnical Society, 2020, 35(23): 4940-4948.
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