Solar photovoltaic power generation prediction method and device, electronic equipment and storage medium

• Main Author: SHEN HENGLE
• Format: Patent
• Language: Chinese; English
• Published: 24.12.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention relates to a solar photovoltaic power generation prediction method and device, electronic equipment and a storage medium, and belongs to the field of solar photovoltaic power generation. The method comprises the steps that: environmental data and PV power are collected to form a data set, wherein the environmental data and the PV power have time sequence characteristics; data preprocessing is performed on the data set; and the preprocessed data are input into a pre-trained mixed deep learning model, and a prediction result is obtained, wherein the mixed deep learning model comprises a variational mode decomposition model, a nested long and short term memory artificial neural network and a full connection layer. According to the embodiment of the invention, a plurality of models are integrated, the complexity between the photovoltaic data and the environmental data can be well processed, and the advantages of the time sequence characteristic and the hybrid deep learning model are combined, so tha