中国电机工程学报2015，Vol.35Issue(11)：2645-2653,后插2,10.DOI:10.13334/j.0258-8013.pcsee.2015.11.002
基于数据驱动的短期风电出力预估-校正预测模型
Predictor-Corrector Model of Wind Power Forecast Based on Data-driven
摘要
Abstract
Improving the prediction accuracy of wind power is of great value in reducing the complexity and conservative of dispatch, optimization and control of power system with high percentage penetration of wind power. Motivated by the idea of data-driven, a short-time predictor-corrector model with an additional learning architecture was proposed based on the analysis of the coupled relationship between wind power historical data and meteorological factors. Wavelet neural network was taken to perform as a predictor while additional learning structure with adaptive dynamic programming that makes use of the wind power data to update the state parameters of predictor was also introduced to form the corrector. Consequently, this model could adapt to a great variety of the operating points of wind system. The test results indicate that this method could both adapt to the frequent change of environment and get better forecast accuracy than BP and GABP methods.关键词
风电出力预测/数据驱动/预估-校正/自适应动态规划/小波神经网络Key words
wind power forecast/data-driven/predictor- corrector/direct heuristic dynamic programming (HDP)/wavelet neural network分类
信息技术与安全科学引用本文复制引用
高亚静,刘栋,程华新,李天,李鹏..基于数据驱动的短期风电出力预估-校正预测模型[J].中国电机工程学报,2015,35(11):2645-2653,后插2,10.基金项目
国家863高技术基金项目(2015AA050104) （2015AA050104）
清华大学电力系统国家重点实验室资助项目(SKLD14KM02). The National High Technology Research and Development of China 863 Program (2015AA050104) （SKLD14KM02）
Project Supported by State Key Laboratory of Tsinghua university power system (SKLD14KM02). （SKLD14KM02）
