基于支持向量机的中长期日负荷曲线预测  

Middle and Long-Term Daily Load Curve Forecasting Based on Support Vector Machine

作　　者：蔡国伟[1] 杜毅[1] 李春山[2] 顾晓光[2] 李友[2] 

机构地区：[1]东北电力大学电气工程学院,吉林省吉林市132012 [2]东北电网有限公司,辽宁省沈阳市110006

出　　处：《电网技术》2006年第23期56-60,共5页Power System Technology

摘　　要：提出了一种预测中长期日负荷曲线的新方法,通过历史典型日负荷数据构造出典型日年度发展时间序列,运用支持向量机方法对预测日各时刻负荷值进行预测并得到了典型日负荷曲线。该方法不需要对日负荷特性、最大负荷及需电量进行预测,因此避免了可能的误差积累问题。以某电网为例对该方法进行了测试,结果表明其具有较高的预测精度。A new method to forecast middle- and long-term load curve is proposed. By means of historical typical daily load data, an annual time series of typical daily load is constituted; then adopting support vector machine（SVM） method, the values of loads at any point of time in forecasted day is forecasted and typical daily load curve is obtained. As for the proposed method, the forecasting of daily load feature, maximum load and electrical energy demand is not needed, so the possible error accumulation can be avoided. Taking a certain power network for example, the proposed method is tested. Test results show that the accuracy of daily load curve forecasted by the proposed method can be improved.

关 键 词：中长期负荷预测 日负荷曲线 支持向量机 

分 类 号：TM715[电气工程—电力系统及自动化]