引用本文: | 黎平,宋坤,肖白,等.基于粗糙集理论的关联聚类中长期负荷预测法[J].电力系统保护与控制,2008,36(1):43-47,66.[点击复制] |
LI Ping,SONG Kun,XIAO Bai,et al.Medium and long-term load forecasting using associated clustering based on rough sets[J].Power System Protection and Control,2008,36(1):43-47,66[点击复制] |
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摘要: |
中长期电力负荷预测是电网规划的一项重要基础工作。由于中长期尺度上的电力负荷受各种相关因素的影响较大,提高负荷预测的准确性难度很大。采用粗糙集理论对影响电力负荷的诸多相关因素的影响程度进行分析,找出影响负荷变化的主要的因素;并以这些影响因素对历史数据进行了聚类,找到与预测目标年最接近的类别来进行负荷预测。文中的算例结果说明了方法的有效性。 |
关键词: 中长期负荷预测 粗糙集理论 聚类 相关因素 |
DOI:10.7667/j.issn.1674-3415.2008.01.010 |
投稿时间:2007-05-22修订日期:2007-08-08 |
基金项目:华东交通大学校立科研基金资助(07DQ05) |
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Medium and long-term load forecasting using associated clustering based on rough sets |
LI Ping,SONG Kun,XIAO Bai,ZHANG Liu |
(Magique Power System Research Group, Northeast Dianli University,Changchun 132012, China) |
Abstract: |
Medium and long term load forecast is an important base of transmission and distribution network planning. Due to the effect of some relative factors on the load, raising the precision of load forecast will be a challenging task. Based on the theory of rough sets, the relationships within the load data and relative factors are revealed, and the most sensitive factor can be found. By clustering, the model of load and most sensitive factor can be built and used to load forecast. The validity and effectiveness of the method is tested in a real power system example. |
Key words: medium and long term load forecasting rough sets clustering relative factor |