引用本文: | 赵 强,景 罗,赵光俊,刘二涛.顾及空间异质性的多尺度空间负荷预测[J].电力自动化设备,2014,34(2): |
| ZHAO Qiang,JING Luo,ZHAO Guangjun,LIU Ertao.Multi-scale spatial load forecasting considering spatial heterogeneity[J].Electric Power Automation Equipment,2014,34(2): |
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摘要: |
提出顾及空间异质性的多尺度空间负荷预测模型。提出空间变异系数和尺度的概念,在此基础上提出按照空间变异系数对元胞空间进行不规则区域划分的方法,将得到的分区按照不同的相似度阈值进行区域聚类融合,得到不同尺度下的区域划分,然后将每一尺度下得到的结果进行叠加来预测空间负荷的分布。实例验证表明,所提模型提高了空间负荷预测的准确率。 |
关键词: 多尺度分析 空间异质性 元胞自动机 C5.0决策树 负荷预测 模型 |
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基金项目:国家自然科学基金资助项目(61273144);北京市自然科学基金资助项目(4122071) |
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Multi-scale spatial load forecasting considering spatial heterogeneity |
ZHAO Qiang1, JING Luo1, ZHAO Guangjun2, LIU Ertao1
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1.School of Control and Computer Engineering,North China Electric Power University,Beijing 102206,China;2.Richsoft Electric Power Information Technology Co.,Ltd.,Tianjin 300384,China
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Abstract: |
A multi-scale spatial load forecasting model considering spatial heterogeneity is proposed. The concept of spatial variation coefficient and scale is proposed,based on which,a method is proposed to divide the cellular space into irregular region partitions according to the spatial variation coefficient. The obtained partitions are treated by the regional clustering integration according to different similarity thresholds to get the regional divisions for different scales,which are superposed to forecast the distribution of spatial load. Practical example shows that the proposed model improves the accuracy of spatial load forecasting. |
Key words: multi-scale analysis spatial heterogeneity element cellular automata C5.0 decision tree electric load forecasting models |