Metaverse-driven remote management solution for scene-based energy storage power stations

【Author】 Deng, Yimin; Weng, Zhoubo; Zhang, Tianlong

【Source】EVOLUTIONARY INTELLIGENCE

【影响因子】0.000

【Abstract】The Metaverse is a new Internet application and social form that integrates a variety of new technologies. With the "carbon peak, carbon neutrality" goal and the proposal of a new power system, the construction of a power system in the metaverse is the trend of future development. For the application of the Metaverse in the power system, the Metaverse is recognized by means of digital twin technology, Internet of Things technology and other means, and then the energy storage power station system in the Metaverse is analyzed. To this end, this paper proposes a Metaverse-driven remote management scheme for energy storage power stations, and gives a specific design scheme. With the help of large-scale computing experiments and the parallel execution of virtual and real closed loops, the remote management and virtual-real interaction of the real energy storage power station system is realized, and the energy storage power station system is promoted from the management and control that relies on simulation to the intelligent management and control driven by the metaverse. In addition, in view of the demand of energy storage power station system for high-precision power load prediction, this paper also proposes a power load prediction model based on genetic algorithm-BP neural network. Considering the data characteristics, a scene-based classification model generation method is designed. The simulation results show that, compared with the BP neural network algorithm, the performance of the prediction model proposed in this paper has been significantly improved, and it can achieve effective prediction of power load.

【Keywords】Metaverse; Load prediction; BP-Neural network; Remote management

【发表时间】

【收录时间】2022-09-22

【文献类型】实验仿真

【主题类别】

区块链应用-实体经济-电力领域