Intelligent energy storage system grid-connected real-time control method based on artificial fish swarm algorithm

An intelligent energy storage system grid-connected real-time control method based on an artificial fish swarm algorithm adopts an Elman neural network to predict intraday power load real time data on the base of power load historical data, then utilizes the artificial fish swarm algorithm to plan t...

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Bibliographische Detailangaben
Hauptverfasser:	HU ZHANGSHENG, YU YONGYI, GUO MING, BAO YIXIA, ZHANG MENG, XIA BIN, SHI DONG, WANG HONG, CHEN FENG, ZHANG QIANG, CHEN PING, LIU HONG, BI GUOLONG, GU QIANFAN, XU YIN
Format:	Patent
Sprache:	eng
Schlagworte:	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 ELECTRICITY GENERATION PHYSICS SYSTEMS FOR STORING ELECTRIC ENERGY
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Beschreibung
Zusammenfassung:	An intelligent energy storage system grid-connected real-time control method based on an artificial fish swarm algorithm adopts an Elman neural network to predict intraday power load real time data on the base of power load historical data, then utilizes the artificial fish swarm algorithm to plan the optimal charge-discharge time and the optimal power of intraday power load prediction data, and performs comparison with the electric power real time data through an intelligent electric meter, so as to determine the optimal charge-discharge time node. The invention achieves automatic grid-connected discharge in the peak of power utilization and achieves charge in the low ebb of power utilization, achieves peak load shifting on the user side, and improves the utilization efficiency of electric power resources.