光伏出力随机性分量的提取和统计特性分析  

Analysis on Random Component Extraction and Statistical Characteristics of Photovoltaic Power

作　　者：赵亮[1] 黎嘉明[1] 艾小猛[1] 文劲宇[1] 谢海莲 岳程燕 

机构地区：[1]强电磁工程与新技术国家重点实验室华中科技大学,湖北省武汉市430074 [2]ABB(中国)有限公司ABB中国研究院,北京市100016

出　　处：《电力系统自动化》2017年第1期48-56,共9页Automation of Electric Power Systems

基　　金：国家重点研发计划智能电网技术与装备专项项目(2016YFB0900400,2016YFB0900403)~~

摘　　要：准确刻画光伏出力的随机特性对分析光伏电站并网的影响具有重要的作用。然而受日地运动和大尺度天气过程影响,光伏出力整体上却表现出日周期性和年周期性而并非一个单纯的随机序列,因此从光伏出力序列中区分规律性与随机性特征并正确提取出其随机性分量显得尤为重要。根据不同物理因素的影响,基于太阳辐射模型和最小二乘原理,提出了一种光伏出力随机性分量的提取方法。基于该提取方法,利用甘肃及德国的光伏实测数据对所提随机性分量进行了详细的统计特性分析。A good understanding of the stochastic characteristics of photovoltaic （PV） power is essential to analysis of the influence of PV power integration. However, solar radiation intensity is influenced by the solar-earth revolution and the longterm weather processes. As a result, PV power series as a whole exhibits a mixture of stochastic process with annually and diurnally periodical components rather than a purely stochastic series. So how to distinguish between the random and periodical patterns of the PV power and extract the random component from the time series is particularly important. A method is proposed to extract the random component from the PV power series based on the global solar radiation model and the least square method. Multiple dominant factors influencing the PV output are considered. Moreover, the statistical characteristics of the random component are analyzed at length using the real-world measurement of the PV power from Gansu and Germany. This work is supported by National Key Research and Development Program of China No. 2016YFB0900400, No. 2016YFB0900403）.

关 键 词：光伏出力 随机性 太阳辐射 最小二乘法 统计特性 

分 类 号：TM615[电气工程—电力系统及自动化]