基于相似日和最小二乘支持向量机的光伏发电短期预测OA北大核心CSCDCSTPCD
Short-term photovoltaic power forecasting based on similar days and least square support vector machine
光伏发电预测对于减小并网光伏发电系统对电力系统的影响具有重要意义.针对光伏系统的发电特性,根据影响光伏发电出力的因素,提出选取相似日的方法,通过计算分析相似度筛选出与预测日特征相似的历史数据,与天气数据一同作为预测模型的训练样本.利用最小二乘支持向量机(LS-SVM)进行光伏发电预测,并通过某微电网示范工程的光伏系统数据验证,计算分析了预测误差,结果表明该方法具有较高的预测精度,对光伏发电预测具有一定的参考价值.
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…查看全部>>
傅美平;马红伟;毛建容
许继集团有限公司,北京100085许继集团有限公司,北京100085许继集团有限公司,北京100085
信息技术与安全科学
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
least square support vector machine similar day photovoltaic generation micro-grid short-term forecasting
《电力系统保护与控制》 2012 (16)
65-69,5
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