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电网技术  2011 

基于最小二乘支持向量机和负荷密度指标法的配电网空间负荷预测

, PP. 66-71

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Abstract:

传统的负荷密度指标的求取方法通常采用经验法或简单类比法,难以满足精度要求,从负荷密度与其影响因素存在着某种非线性关系的角度出发,提出了一种基于最小二乘支持向量机(leastsquaressupportvectormachine,LS-SVM)的配电网空间负荷预测方法。该方法首先引入模糊C–均值算法把各类用地性质负荷聚类为几个等级,建立比较精确的负荷密度指标体系;然后根据待预测地块的规划属性,在体系中为LS-SVM预测模型选出与预测样本特征更为相似的样本进行训练,提高LS-SVM的泛化能力和预测精度;采用遗传算法对LS-SVM预测模型的参数进行自动优化,进一步提高预测模型的适应性和预测精度,实例验证了该方法的实用性和有效性。

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