基于免疫算法的超短期负荷预测方法  

Approach for Forecasting Super-term Load Based on Immune Algorithm

作　　者：鲍光辉[1,2] 熊赟超[1] 艾芊[1] 

机构地区：[1]上海交通大学电气工程系,上海200240 [2]上海市电力公司,上海200122

出　　处：《华东电力》2010年第12期1964-1967,共4页East China Electric Power

基　　金：上海市自然科学基金项目(08ZR1409700)~~

摘　　要：运用最小二乘的方法建立差分模型并用于电力系统负荷预测,并提出了基于免疫算法的组合差分预测负荷模型,将该模型应用于超短期负荷用量预测和超短期负荷曲线预测,提高了负荷预测的精确性。在实例分析中,利用以1 h为采样时间间隔的差分模型、2 h为采样时间间隔差分模型、3 h为采样时间间隔差分模型和以这前三种模型建立的基于免疫算法的组合差分模型对某市负荷数据进行了负荷用量预测和负荷曲线预测,最终预测结果验证了论文提出的负荷预测方法的有效性。The difference model,established by the least square method,was used to forecast the load of electric power system,and the combination difference forecasting model was proposed based on immune algorithm.This model was used in super short-term load dosage forecasting and super short-term load curve forecasting,which enhanced the performance of load forecast.In example analysis,the sampling interval for difference models was selected as one hour,two hours and three hours,respectively,and combination difference model,established by these three models based on immune algorithm,were used to forecast super short-term load dosage and super short-term load curve for one city.The results showed that the proposed method was feasible.

关 键 词：超短期负荷预测 免疫算法 差分模型 负荷用量预测 负荷曲线预测 

分 类 号：TM715[电气工程—电力系统及自动化]