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基于粗糙集理论和最小二乘支持向量机的中长期负荷预测

Medium and long-term load forecasting based on rough sets and least square support vector machines

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【作者】 刘耀年庞松岭李鉴

【Author】 LIU Yao-nian,PANG Song-ling,LI Jian(School of Electrical Engineering,Northeast Dianli University,Jilin 132012,China)

【机构】 东北电力大学电气工程学院东北电力大学电气工程学院 吉林132012吉林132012

【摘要】 根据电力系统中长期负荷预测的特点,提出了粗糙集理论与最小二乘支持向量机相结合的预测方法。应用粗糙集理论对影响负荷的众多因素进行约简,得到与负荷关系最为密切的核心因素,将其作为最小二乘支持向量机的输入矢量进行预测。实际算例分析表明,该预测模型符合中长期负荷预测的特点并具有较高的精度,方法是可行和有效的。

【Abstract】 According to the load characteristics of power system,a integrated method of rough sets and least square vector machines was proposed.Rough sets theory was used to reduce attributes that influence loads,thus the kernel factors were determined and using them as the input vector of least square support vector machines.Forecasting results of calculation examples show that the proposed forecasting method possesses satisfactory accuracy.The feasibility and validity of the method is proved by practical examples.

  • 【文献出处】 中国电力 ,Electric Power , 编辑部邮箱 ,2007年10期
  • 【分类号】TM715
  • 【被引频次】19
  • 【下载频次】383
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