| 引用本文: | 杨茂,刘红柳,季本明.基于混沌理论的风电功率超短期多步预测的误差分析[J].电力系统保护与控制,2017,45(4):50-55.[点击复制] |
| YANG Mao,LIU Hongliu,JI Benming.Analysis of ultra-short-term prediction error of wind power based on chaos theory[J].Power System Protection and Control,2017,45(4):50-55[点击复制] |
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| 摘要: |
| 风电功率对电力系统的安全运行、合理调度等方面有不可忽视的影响。掌握风电功率预测误差的分布特性，对风资源的大规模开发利用具有重要意义。利用两种混沌预测方法进行风电功率超短期的预测。并且以东北某风电场的实测风电功率数据为例，分析了超短期风电功率预测误差的概率分布、预测误差与超前预测步数之间的关系、预测误差与风电场出力情况之间的关系以及预测误差与装机容量之间的关系。该研究为揭示风电功率超短期多步预测的误差构成及修正奠定了理论基础。 |
| 关键词: 风电功率 预测 误差 概率分布 混沌理论 |
| DOI：10.7667/PSPC160395 |
| 投稿时间：2016-03-22修订日期：2016-07-20 |
| 基金项目:国家重点基础研究发展计划项目(973计划) (2013CB228201);国家自然科学基金(51307017);吉林省科技发展计划(20140520129JH);吉林省产业技术研究与开发专项项目(2014Y124) |
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| Analysis of ultra-short-term prediction error of wind power based on chaos theory |
| YANG Mao,LIU Hongliu,JI Benming |
| (School of Electrical Engineering, Northeast Dianli University, Jilin 132012, China) |
| Abstract: |
| Wind power has a big influence on the safe operation and rational management of electric power system. It is useful to grasp the distribution characteristics of wind power prediction error for the large-scale development and utilization of wind energy. Two chaos ultra-short-term forecasting methods are used to predict wind power. The wind power data of a northeast wind farm is taken as an example to analyze the probability distribution of single-step prediction error of wind power, the relationship between the wind power prediction error and the prediction step number, the relationship between the wind power prediction error and the wind farm output power, and the relationship between the wind power prediction error and the installed capacity. It lays the theoretical foundation for the analysis of the composition and correction of the wind power prediction error. This work is supported by National Key Basic Research Program of China (973 Program) (No. 2013CB228201), National Natural Science Foundation of China (No. 51307017), Science and Technology Development Program of Jilin Province (No. 20140520129JH), and Special Program of Industrial Technology Research and Development of Jilin Province (No. 2014Y124). |
| Key words: wind power prediction error probability distribution chaos theory |
