基于盲信号分离原理的台区光伏实时出力感知算法  

Real⁃time Power Sensing Algorithm of Station Photovoltaic Based on Blind Signal Separation Principle

作　　者：徐晓春 李佑伟 李彦伦 戴欣 窦晓波[2] 卜强生 张岩 XU Xiaochun;LI Youwei;LI Yanun;DAI Xin;DOU Xiaobo;BU Qiangsheng;ZHANG Yan(Jiangsu Electric Power Company Huai’an Power Supply Company,Jiangsu Huaian 223002,China;Electrical Engineering College of Southeast University,Nanjing 210096,China;Electric Power Research Institute of State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing 211103,China)

机构地区：[1]国网江苏省电力有限公司淮安供电分公司,江苏淮安223002 [2]东南大学电气工程学院,南京210096 [3]国网江苏省电力有限公司电力科学研究院,南京211103

出　　处：《电力电容器与无功补偿》2024年第4期133-140,148,共9页Power Capacitor & Reactive Power Compensation

基　　金：国网江苏省电力有限公司科技项目(J2021036)。

摘　　要：随着整县分布式光伏项目的推进,分布式光伏的装机规模和范围逐渐扩大,台区内出现潮流反向现象,而现有的光伏电表无法完成发电数据的实时采集,这将导致调度侧负荷数据的失真和分布式新能源管理的缺失等问题。考虑到台区现有的一次设备量测与通信状况,提出了一种基于盲信号分离理论的台区内光伏实时出力估计方法。该方法基于变压器总表的电能数据与台区内光伏出力的轮廓数据,以最小互信息为标准进行光伏出力分解,并对结果进行卡尔曼滤波去噪。进一步基于分解得到的带标签的数据建立数据库,采用卷积神经网络进行训练,以得到优化的光伏出力估计结果。最后以扬中地区一含光伏台区实际数据进行验证,评估了算法的误差。With the promotion of the distributed photovoltaic project across the country,the installed scale and scope of the distributed photo-voltaic are gradually expanding,and the reverse trend of power flow occurs in the station area.However,the existing photo-voltaic meters have no way to complete the real-time collection of power generation data,which will lead to such problems as distortion of load data at the dispatching side and the lack of distributed new energy management.Considering the measurement and communication status of primary equipment in the station area,a kind of real-time photovoltaic output estimation method based on signal decomposition theory is proposed in this paper.Based on the electric energy data of the transformer meter and the contour data of photovoltaic output in the station area,the photovoltaic output is decomposed in accordance with the minimum mutual information,and the separation results are denoised by Kalman filter.Furthermore,the database is set up based on the labeled data obtained by decomposition,and the convolutional neural network is used for training to obtain the optimized photovoltaic output estima-tion results.Finally,the actual data of a photovoltaic neighborhood area in Yangzhong area is verified,and the error of the algorithm is assessed.

关 键 词：配电网 盲信号 光伏感知 互信息 

分 类 号：TM615[电气工程—电力系统及自动化]