| 母线负荷预测中的自适应预测技术及其实现 |
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| 引用本文： | 赵燃,陈新宇,陈刚,程芸,杨军峰,刘梅,康重庆. 母线负荷预测中的自适应预测技术及其实现[J]. 电网技术, 2009, 0(19) |
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| 作者姓名： | 赵燃 陈新宇 陈刚 程芸 杨军峰 刘梅 康重庆 |
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| 作者单位： | 电力系统及发电设备控制和仿真国家重点实验室(清华大学电机系);国家电力调度通信中心; |
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| 基金项目： | 国家电网公司科技项目; 高等学校博士学科点专项科研基金资助课题(200800030039) |
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| 摘 要： | 负荷波动频繁、变化模式复杂是母线负荷的重要特点。如何自适应地进行预测模型的选择和模型参数的调整,从而获得更加准确的预测结果,始终是一个研究热点和难点。文章提出了一种基于虚拟预测思想的自适应母线负荷预测技术。通过分析自适应预测的基本问题,建立了母线负荷预测自适应技术的抽象统一框架,阐述了自适应预测技术的整体流程,并给出了自适应预测技术的详细数学描述与实现方法。算例分析表明,应用自适应预测技术,实际预测的效果得到显著提高。
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| 关 键 词： | 母线负荷预测 虚拟预测 自适应技术 参数估计 |
Adaptive Forecasting Approach and Its Implementation in Bus Load Forecasting |
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| ZHAO Ran,CHEN Xin-yu,CHEN Gang,CHENG Yun,YANG Jun-feng,LIU Mei,KANG Chong-qing,Haidian District,Beijing ,China,.National Power Dispatching , Communication Center,Xicheng District,Beijing ,China). Adaptive Forecasting Approach and Its Implementation in Bus Load Forecasting[J]. Power System Technology, 2009, 0(19) |
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| Authors: | ZHAO Ran CHEN Xin-yu CHEN Gang CHENG Yun YANG Jun-feng LIU Mei KANG Chong-qing Haidian District Beijing China .National Power Dispatching & Communication Center Xicheng District Beijing China) |
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| Affiliation: | ZHAO Ran1,CHEN Xin-yu1,CHEN Gang2,CHENG Yun2,YANG Jun-feng2,LIU Mei1,KANG Chong-qing1(1.State Key Lab of Control and Simulation of Power Systems and Generation Equipments(Dept.of Electrical Engineering,Tsinghua University),Haidian District,Beijing 100084,China,2.National Power Dispatching & Communication Center,Xicheng District,Beijing 100031,China) |
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| Abstract: | Due to frequent fluctuation and complex variation patterns of bus load, up to now it is a research highlight home and abroad and is regarded as a hard task to adaptively select forecasting model of bul load and adjust model parameters to obtain more accurate forecasting results.In this paper, an adaptive bus load forecasting approach based on the thinking of virtual forecasting is proposed.By means of analyzing basic issues of adaptive forecasting, a unified abstractive frame of adaptive technique for bus l... |
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| Keywords: | bus load forecasting virtual forecasting adaptive approach parameter estimation |
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