中国电机工程学报2016，Vol.36Issue(23)：6315-6326,12.DOI:10.13334/j.0258-8013.pcsee.161167
风电集群短期及超短期功率预测精度改进方法综述
A Summary of the State of the Art for Short-term and Ultra-short-term Wind Power Prediction of Regions
摘要
Abstract
Short-term and ultra-short-term wind power prediction (WPP) in regions is an effective method to enhance the robustness of the power grid. The state of the art of short-term and ultra-short-term WPP techniques was summarized in the paper. The classification of WPP techniques was discussed, in terms of prediction method of single wind farm and regions. The overall framework of the regional WPP system was discussed in four aspects, including the forecasting flow chart, data sources, data flows and the physical levels. Generalization physical layers of wind power forecasting was presented in five levels, data layer, mapping layer, feature layer, methodology layer, and feedback layer, based on which the improvement methods for WPP were discussed. The proposed improvement methods for the five physical levels of WPP will contribute to both short-term and ultra-short-term WPP in regions.关键词
风电集群预测/短期功率预测/超短期功率/预测物理层次/预测精度Key words
regional wind power prediction/short-term wind power prediction/ultra-short-term wind power prediction/forecasting physical hierarchy/forecasting accuracy分类
信息技术与安全科学引用本文复制引用
彭小圣,熊磊,劲宇,程时杰,邓迪元,冯双磊,王勃..风电集群短期及超短期功率预测精度改进方法综述[J].中国电机工程学报,2016,36(23):6315-6326,12.基金项目
国家自然科学基金项目(51529701)；国家电网科技项目《基于集群划分的新能源功率预测技术研究和示范》资助。Project Supported by National Natural Science Foundation of China (51529701) （51529701）
Key Technological Project of State Grid Corporation of China“Research and Demonstration of New and Renewable Energy Power Prediction Based on Clustering of Power Plants” （）
