Photovoltaic subsidy automatic settlement method and system based on RPA + AI

Photovoltaic subsidy automatic settlement method and system based on RPA + AI

The invention provides a photovoltaic subsidy automatic settlement method and system based on RPA + AI, and belongs to the technical field of new energy, and the method specifically comprises the steps: obtaining the daily photovoltaic power generation amount of a settlement main body to be subjecte...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: ZHAO XINLIANG, ZHANG HUIFANG, DONG YIKE, ZHANG YUAN, YANG SHUZI, HUANG YANRU
Format: Patent
Sprache:chi ; eng
Schlagworte:
CALCULATING
COMPUTING
CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRICITY
GENERATION
GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRA-REDRADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, E.G. USINGPHOTOVOLTAIC [PV] MODULES
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:The invention provides a photovoltaic subsidy automatic settlement method and system based on RPA + AI, and belongs to the technical field of new energy, and the method specifically comprises the steps: obtaining the daily photovoltaic power generation amount of a settlement main body to be subjected to settlement, when the daily photovoltaic generating capacity is not missing and the date when the absolute value of the difference value between the photovoltaic generating capacity of the current day and the photovoltaic generating capacity of the previous day is greater than a first threshold value does not exist, taking the date when the absolute value of the difference value between the photovoltaic generating capacity of the current day and the photovoltaic generating capacity of the previous day is greater than a second threshold value as a potential abnormal date; the prediction model based on the AI algorithm is adopted to correct the photovoltaic generating capacity of the potential abnormal day to obt