| 基于支持向量机的中长期电力负荷组合预测 |
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| 引用本文： | 肖先勇,葛嘉,何德胜. 基于支持向量机的中长期电力负荷组合预测[J]. 电力系统及其自动化学报, 2008, 20(1): 84-88 |
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| 作者姓名： | 肖先勇 葛嘉 何德胜 |
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| 作者单位： | 四川大学电气信息学院,成都,610065;南充电业局,南充,637000 |
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| 摘 要： | 影响中长期负荷的因素多,随机性强,单一预测方法很难满足不同情况的预测需要,组合预测能较好地解决单一模型的不足,但现有组合预测模型主要基于经验风险最小,预测精度受组合模型的限制.本文提出一种基于最小二乘支持向量机的中长期负荷组合预测模型,该模型利用结构风险最小化原则代替传统的经验风险最小化,充分挖掘原始数据和单一预测模型的信息,以单一模型的预测数据作为组合预测样本,选择多项式核函数的最小二乘支持向量机进行组合预测.实际算例表明,本文提出的组合模型预测平均误差仅为1.719%,具有良好的可行性和有效性.
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| 关 键 词： | 中长期负荷 组合预测 结构风险最小化 最小二乘支持向量机 预测风险 |
| 文章编号： | 1003-8930（2008）01-0084-05 |
| 收稿时间： | 2006-10-01 |
| 修稿时间： | 2006-11-27 |
Combination Method of Mid-Long Term Load Forecasting Based on Support Vector Machine |
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| XIAO Xian-yong,GE Jia,HE De-sheng. Combination Method of Mid-Long Term Load Forecasting Based on Support Vector Machine[J]. Proceedings of the CSU-EPSA, 2008, 20(1): 84-88 |
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| Authors: | XIAO Xian-yong GE Jia HE De-sheng |
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| Affiliation: | XIAO Xian-yong1,GE Jia1,HE De-sheng2 (1.School of Electrical Engineering , Information,Sichuan University,Chengdu 610065,China,2.Nanchong Power Supply Company,Nanchong 637000,China) |
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| Abstract: | Affected by many factors,the mid-long term load forecasting will not be satisfied if only a single method is adopted.Combination forecasting model can be used to solve the problem,but it is limited by empirical risk minimization(ERM) principle.In the paper,method based on the least square support vector machine(LS-SVM) is proposed for mid-long term load forecasting.In the model,instead of traditional ERM the principle of structure risk minimization(SRM) is used to fully mine the information of original data... |
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| Keywords: | mid-long term load combination forecasting structure risk minimization least square support vector machine forecasting risk |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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