| 引用本文: | 李彦伦,窦晓波,卜强生,等.基于改进FCM和最小互信息算法的户变关系辨识方法[J].电力系统保护与控制,2024,52(11):102-111.[点击复制] |
| LI Yanlun,DOU Xiaobo,BU Qiangsheng,et al.Identification method of transformer-customer relationship based on an improved FCM algorithm and minimum mutual information[J].Power System Protection and Control,2024,52(11):102-111[点击复制] |
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| 摘要: |
| 随着低压分布式光伏的高比例接入，传统的户变关系辨识方法利用电压与功率特征进行判断，受光伏出力影响较大。针对分布式光伏大规模接入下低压配电网的电气特征，提出了一种基于数据驱动的低压配电网户变关系辨识方法。首先，基于改进模糊C均值(fuzzy C-means, FCM)聚类算法，利用电压相关性对用户进行初步聚类划分。其次，在初步聚类的基础上，利用最小互信息算法排除光伏出力的影响，建立配变与用户的连接关系识别模型并用回归分析的思想求解，实现对户变关系的精确辨识。最后，通过对某地实际数据进行算例分析，验证了基于改进FCM和最小互信息算法的户变关系辨识方法在大规模光伏接入场景下的有效性。实验表明，该方法相比传统的电压和功率特征判别方法具有更高的准确率。 |
| 关键词: 低压配电网 户变关系辨识 拓扑识别 电压相关性 互信息 |
| DOI：10.19783/j.cnki.pspc.231575 |
| 投稿时间：2023-12-12修订日期：2024-02-28 |
| 基金项目:国网有限公司总部科技项目资助(5108- 202218280A-2-367–XG)；国家自然科学基金项目资助(52077036) |
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| Identification method of transformer-customer relationship based on an improved FCM algorithm and minimum mutual information |
| LI Yanlun1,DOU Xiaobo1,BU Qiangsheng2,XU Xiaochun3,LÜ Pengpeng2 |
| (1. College of Electrical Engineering, Southeast University, Nanjing 210096, China; 2. Electric Power Research Institute
of State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211103, China; 3. Huai’an Power Supply
Company, State Grid Jiangsu Electric Power Co., Ltd., Huaian 223002, China) |
| Abstract: |
| With the high proportion of low-voltage distributed PV access, traditional transformer-customer relationship identification methods based on voltage and power characteristics are largely affected by photovoltaic input. Given the electrical characteristics of the low-voltage distribution network when there is large-scale distributed PV access, a data-driven identification method for transformer-customer relationship in the low-voltage distribution network is proposed. First, using voltage correlation, customers are preliminarily divided based on an improved fuzzy C-means (FCM) clustering algorithm. Then, based on the initial clustering, a minimum mutual information algorithm is used to eliminate the influence of photovoltaic output, and an identification model of the connection relationship between distribution transformers and customers is established. Regression analysis is used to solve the problem, so as to realize accurate identification. Finally, the effectiveness of the identification method of transformer-customer relationship based on improved FCM algorithm and minimum mutual information is verified by analyzing the actual data of a certain place. Experiments show that this method has higher accuracy than the traditional discrimination method using voltage and power characteristics. |
| Key words: low-voltage distribution network transformer-customer relationship identification topology identification voltage correlation mutual information |
