Ultra-short-term photovoltaic power generation power prediction method and device and storage medium

• Main Authors: XIE JIAJIA, CHEN WENJIN, CHEN JINGWEI, FANG WENWEN, WANG SHU, JIN CONGYOU, GUAN QIANQIAN, XU DANLU, WANG ZIHENG, ZHANG XIAOBO, QIN JIANSONG, JIANG WEI, LIU ZHOUBIN
• Format: Patent
• Language: Chinese; English
• Published: 21.07.2023
• Subjects: CALCULATING; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER; COUNTING; ELECTRICITY; GENERATION; PHYSICS; SYSTEMS FOR STORING ELECTRIC ENERGY

The invention discloses an ultra-short-term photovoltaic power generation power prediction method and device and a storage medium, and the method comprises the steps: obtaining data related to a centralized photovoltaic power station, including basic data, historical operation data, historical meteorological data and meteorological forecast data of the centralized photovoltaic power station, and generating a plurality of original data sequences; determining a preset wavelet decomposition layer number, and performing wavelet decomposition processing on the original data sequence to generate a sample data set; training and optimizing a preset original prediction model according to the sample data set to obtain a target prediction model; wherein the target prediction model is of a CNN-LSTM network structure, and the target prediction model is used for predicting the photovoltaic power generation power of the centralized photovoltaic power station in a future preset duration. By adopting the method, the accuracy