南方电网技术2025，Vol.19Issue(8)：31-43,71,14.DOI:10.13648/j.cnki.issn1674-0629.2025.08.004
基于Critic权重法与反熵权法组合的风电功率概率预报
Probability Prediction of Wind Power Based on the Combination of Critic Weight Method and Anti-Entropy Weight Method
摘要
Abstract
In order to improve the performance of wind power probability interval prediction,a wind power interval probability predic-tion method is proposed which is the combination of variable bandwidth hybrid sliding Gaussian kernel density estimation(VHSKDE(Gaussian))and normal sliding exponential iteration(NSEI)based on critical weight method and anti-entropy weight method.The combination method is called VHSKDE(Gaussian)-NSEI for short.Firstly,the error is obtained by point prediction based on variational mode decomposition and long short-term memory neural network(VMD-LSTM).Then,VHSKDE(Gaussian)and NSEI are used to estimate the probability distribution of the prediction errors,and forecast interval is obtained under corresponding confidence probability.Finally,four objective weight assignment methods are used to weight the VHSKDE(Gaussian)link and the VHSKDE(Gaussian)-NSEI combination link twice to generate the final wind power prediction interval.The research results show that the excellent performances of PICP and PIAW can be compatible by using the proposed VHSKDE(Gaussian)-NSEI prediction model under different levels of confidence.The VHSKDE(Gaussian)-NSEI prediction model has higher reliability and accuracy than NSEI and VHSKDE(Gaussian),and provides an important reference for wind power probability prediction.关键词
风电功率/概率预报/Critic/反熵权法/均方积分偏差/核密度估计Key words
wind power/probability prediction/Critic/anti-entropy method/mean integrated square error/kernel density estimation分类
信息技术与安全科学引用本文复制引用
屈伯阳,李宏伟,付立思..基于Critic权重法与反熵权法组合的风电功率概率预报[J].南方电网技术,2025,19(8):31-43,71,14.基金项目
国家自然科学基金资助项目(52007124) （52007124）
辽宁省兴辽英才计划项目(XLYC2008005).Supported by the National Natural Science Foundation of China(52007124) （XLYC2008005）
the Xing Liao Ying Cai Project of Liaoning Province(XLYC2008005). （XLYC2008005）
