| 关于短期及超短期风电功率预测的评述 |
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| 引用本文： | 薛禹胜,郁琛,赵俊华,Kang LI,Xueqin LIU,Qiuwei WU,Guangya YANG.关于短期及超短期风电功率预测的评述[J].电力系统自动化,2015,39(6):141-151. |
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| 作者姓名： | 薛禹胜 郁琛 赵俊华 Kang LI Xueqin LIU Qiuwei WU Guangya YANG |
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| 作者单位： | 南瑞集团公司(国网电力科学研究院), 江苏省南京市 211106;南京理工大学自动化学院, 江苏省南京市 210094,南京理工大学自动化学院, 江苏省南京市 210094;南瑞集团公司(国网电力科学研究院), 江苏省南京市 211106,浙江大学电气工程学院, 浙江省杭州市 310027,Queen's University Belfast, BT9 5AH, Northern Ireland, UK,Queen's University Belfast, BT9 5AH, Northern Ireland, UK,Technical University of Denmark, Lyngby 2800, Denmark,Technical University of Denmark, Lyngby 2800, Denmark |
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| 基金项目： | 国家重点基础研究发展计划(973计划)资助项目(2013CB228204);澳大利亚ARC资助项目(DP120101345);中英合作研究项目(NSFC-513111025-2013,EPSRC-EP/L001063/1);国家电网公司科技项目。 |
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| 摘 要： | 讨论风电功率预测及其误差对电力系统的影响,从信息流观点解读风电功率预测过程,归纳影响风电功率预测精度的因素,并对风电功率预测的研究现状加以归类与梳理。在此基础上,讨论对风电功率预测结果评价指标的要求,提出误差评估指标应该反映整个时间窗口内的预报质量,并展望风电功率预测可能的突破。
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| 关 键 词： | 风电预测 信息流向 组合预测 评估指标 概率预测 |
| 收稿时间： | 2014/12/18 0:00:00 |
| 修稿时间： | 2/3/2015 12:00:00 AM |
A Review on Short-term and Ultra-short-term Wind Power Prediction |
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| XUE Yusheng,YU Chen,ZHAO Junhu,Kang LI,Xueqin LIU,Qiuwei WU and Guangya YANG.A Review on Short-term and Ultra-short-term Wind Power Prediction[J].Automation of Electric Power Systems,2015,39(6):141-151. |
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| Authors: | XUE Yusheng YU Chen ZHAO Junhu Kang LI Xueqin LIU Qiuwei WU and Guangya YANG |
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| Affiliation: | NARI Group Corporation (State Grid Electric Power Research Institute), Nanjing 211106, China;School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China,School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China;NARI Group Corporation (State Grid Electric Power Research Institute), Nanjing 211106, China,College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China,Queen's University Belfast, BT9 5AH, Northern Ireland, UK,Queen's University Belfast, BT9 5AH, Northern Ireland, UK,Technical University of Denmark, Lyngby 2800, Denmark and Technical University of Denmark, Lyngby 2800, Denmark |
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| Abstract: | The impact of wind power prediction (WPP) on power systems is discussed and the factors affecting the accuracy of WPP are summarized. Then the paper unscrambles the WPP process from the viewpoint of information flow, classifies its research status and discusses the requirements of evaluation index for WPP results. It is proposed that the error evaluation index should reflect the WPP quality of the whole time window, and possible breakthroughs of WPP are also predicted. This work is jointly supported by National Basic Research Program of China (973 Program) (No. 2013CB228204), Australian Research Council Project (No. DP120101345), NSFC-EPSRC Collaborative Project (No. NSFC-513111025-2013, No. EPSRC-EP/L001063/1), and State Grid Corporation of China. |
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| Keywords: | wind power prediction information flow combinational prediction evaluation index probabilistic forecasting |
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