Photovoltaic power generation prediction method based on clustering algorithm fusion

• Main Authors: CHENG JINRUI, HUANG SHUAI, WANG XINGHU
• Format: Patent
• Language: Chinese; English
• Published: 01.03.2024
• 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; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; ELECTRICITY; GENERATION; PHYSICS; SYSTEMS FOR STORING ELECTRIC ENERGY; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a clustering algorithm fusion-based photovoltaic power generation prediction method. The method comprises the steps of obtaining meteorological data of a photovoltaic power station; classifying the meteorological data through a clustering algorithm, and inputting the classified meteorological data into the BP photovoltaic prediction model to output a photovoltaic prediction result; the BP photovoltaic prediction model comprises a plurality of photovoltaic meteorological networks, and the training process of the BP photovoltaic prediction model comprises the following steps: S1, constructing a training set; s2, classifying historical data sets in the training set through a K-means clustering algorithm to obtain meteorological data sets of different meteorological types; s3, adopting a Pearson similarity analysis method to select historical data from the meteorological data set of the meteorological type # imgabs0 # as an input vector of the photovoltaic meteorological network correspond