Business balanced distribution method based on artificial intelligence and remote service facility

The invention provides a business balanced distribution method based on artificial intelligence and a remote service facility, and relates to the field of power systems, and the business balanced distribution method based on artificial intelligence comprises the steps: obtaining historical energy st...

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Hauptverfasser:	ZHU BIN, YU PEIZHOU, ZHAO NINGYUAN, ZHANG XUANWEN, PAN YAN, JIANG JUN, SHEN HUAZHOU, GU HAODA, SHI QIAOSHI, ZHANG MENGNI, ZHAO WANFANG, LU JIE, LI JUNMOU, LEI QIAN, GE KAILIANG, WANG YINGBU, WANG YAN, ZHANG LIXING, SHI ZHIQIANG
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	CALCULATING CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER 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
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Beschreibung
Zusammenfassung:	The invention provides a business balanced distribution method based on artificial intelligence and a remote service facility, and relates to the field of power systems, and the business balanced distribution method based on artificial intelligence comprises the steps: obtaining historical energy storage data and historical position information of a battery; establishing a historical electricity utilization inertia model according to the historical energy storage data and the historical position information; an energy storage service prediction model is established according to the historical electricity utilization inertia model, and the historical electricity utilization inertia model is used for describing the charging and discharging frequency of the battery and the circulation activity of the battery; and obtaining the load size of future business according to the energy storage business prediction model, and obtaining a battery distribution strategy according to the communication rule type multi-agent m