电力系统保护与控制2012，Vol.40Issue(16)：65-69,5.
基于相似日和最小二乘支持向量机的光伏发电短期预测
Short-term photovoltaic power forecasting based on similar days and least square support vector machine
摘要
Abstract
Photovoltaic power forecast is significant to reducing the impact of PV generation integration on the power grid. According to the characteristics of power generation of photovoltaic and the factors impacting PV power output, a method of selecting similar days is proposed. By calculating and analyzing similarity degree, the historical data similar to the features of forecasted day are selected and considered as the training samples together with weather data. The least square support vector machine (LS-SVM) is used to calculate PV power output. The method is validated by photovoltaic system data of a micro-grid demonstration project and the forecast error is calculated and analyzed. The results show the method has high accuracy, which provides reference to forecast generation power of PV system.关键词
最小二乘支持向量机(LS-SVM)/相似日/光伏发电/微电网/短期预测Key words
least square support vector machine/ similar day/ photovoltaic generation/ micro-grid/ short-term forecasting分类
信息技术与安全科学引用本文复制引用
傅美平,马红伟,毛建容..基于相似日和最小二乘支持向量机的光伏发电短期预测[J].电力系统保护与控制,2012,40(16):65-69,5.
