Photovoltaic probability prediction method and system based on Bayesian neural network

• Main Authors: WANG XINYING, HUANG YUEHUI, ZHAO KANGNING, PU TIANJIAO, LI YE
• Format: Patent
• Language: Chinese; English
• Published: 05.06.2020
• 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; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a photovoltaic probability prediction method and system based on a Bayesian neural network. The method comprises the steps of obtaining weather forecast data of a to-be-predicted point and historical output data of photovoltaic equipment; carrying out dimension reduction processing on the weather forecast data, and obtaining feature data based on the weather forecast data after dimension reduction processing and historical output data of photovoltaic equipment; and substituting the feature data into a pre-constructed improved Bayesian neural network model to obtain photovoltaic output distribution of the to-be-predicted point. According to the method, the photovoltaic output distribution of the to-be-predicted point is obtained, compared with a deterministic prediction mode, the photovoltaic probability prediction method provided by the invention has a smaller average interval width when the same prediction accuracy is achieved, the prediction precision is improved, and the method has