湖南大学学报（自然科学版）2024，Vol.51Issue(2)：68-80,13.DOI:10.16339/j.cnki.hdxbzkb.2024227
基于新型相似日选取和VMD-NGO-BiGRU的短期光伏功率预测
Short Term Photovoltaic Power Prediction Based on New Similar Day Selection and VMD-NGO-BiGRU
摘要
Abstract
Photovoltaic power prediction plays an important role in the scheduling and operation of modern power systems.Aiming at the variability and complexity of photovoltaic power generation,a short-term PV power prediction method based on new similar day selection and northern Goshawk optimization(NGO)to optimize bidirec-tional gated recurrent unit(BiGRU)is proposed.The main meteorological factors are selected with the Spearman cor-relation coefficient,and the original PV power and maximum meteorological factor are decomposed into a series of sub-signals by variational mode decomposition(VMD).Then,according to the construction of new evaluation indi-cators,the data set of similar days is screened out,a group of BiGRU is used to establish a deep learning model with similar day signals as network input,and NGO is used to effectively optimize the hyperparameters of each BiGRU network.Finally,the predicted value of PV power is obtained by synthesizing the predicted results of each sub-signal.Simulation results show that the proposed hybrid deep learning method is superior to other methods in terms of prediction accuracy and computational efficiency.关键词
光伏功率预测/变分模态分解/双向门控循环单元/北方苍鹰算法Key words
photovoltaic power prediction/variational mode decomposition/bidirectional gated cycle unit/northern Goshawk algorithm分类
动力与电气工程引用本文复制引用
王瑞,张璐婷,逯静..基于新型相似日选取和VMD-NGO-BiGRU的短期光伏功率预测[J].湖南大学学报（自然科学版）,2024,51(2):68-80,13.基金项目
国家自然科学基金资助项目(62273133),National Natural Science Foundation of China(62273133) （62273133）
河南省科技攻关项目(222102210120),Scientific and Technological Breakthrough Foundation of Henan province(222102210120) （222102210120）
