Multi-target photovoltaic-electric vehicle scheduling method for improving photovoltaic consumption level

• Main Authors: ZHAN YUEMEI, QI ZELONG, WANG CHENFEI, LYU ZHENGRUI, XU JIAYU, LIANG MAN, JI XINZHE, LIU YANG, WANG XIAOYU, WANG FANG, HUANG ZIJIAN, ZHANG JUNWEI, QIU YUTAO, FAN ZHENG, WANG QIN, ZHU HAO, ZHANG MOHAN, ZHANG HOUJIE, LI YUANYUAN, HAN DANHUI
• Format: Patent
• Language: Chinese; English
• Published: 31.01.2023
• 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; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; 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 relates to a multi-target photovoltaic-electric vehicle scheduling method for improving a photovoltaic consumption level, and the method comprises the steps: training a long-short-term memory neural network through an extreme learning machine based on photovoltaic output and power consumption load power historical data, and predicting short-term photovoltaic power and short-term power consumption load power; generating a short-time photovoltaic output curve and a short-time load power curve according to a prediction result, and predicting photovoltaic power needing to be consumed by the electric vehicle in a short time in combination with a conventional unit output curve; establishing a short-time photovoltaic-electric vehicle multi-target scheduling model by taking the minimum difference value between the predicted photovoltaic electric quantity needing to be consumed and the electric vehicle charging quantity as a target function; establishing an electric vehicle charging price strategy model