Integration of embedded systems and artificial intelligence in electrical automation for smart grid management
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Bo Fu
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BinHua Yuan
Abstract
With the continuous progress of social civilization, electricity plays an indispensable role in human life. China is a vast country with wide grid coverage and frequent natural disasters, which cause certain losses to the national economy. Therefore, this paper fully considers the role of meteorological information in the emergency decision-making of smart grid disaster prevention, uses the Dijkstra algorithm to clarify the best path, and integrates many factors such as traffic coefficient, road level, road congestion and road quality to establish the optimal path model, which can effectively improve the management level, reduce the smart grid loss by more than 48 %, protect the residents and industrial electricity consumption, and provide safe operation of the smart grid. Powerful guarantee.
Funding source: Research on Point Position Balance Control Strategy of Three Level Inverter
Award Identifier / Grant number: HXZK2487
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Research ethics: The local Institutional Review Board deemed the study exempt from review.
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Informed consent: Informed consent was obtained from all individuals included in this study.
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Author contributions: BoFu and BinHuaYuan, contributed to the design and methodology of this study, the assessment of the outcomes, and the writing of the manuscript.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: There is no potential conflict of interest in our paper, and all authors have seen the manuscript and approved to submit to your journal. We confirm that the content of the manuscript has not been published or submitted for publication elsewhere.
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Research funding: Research on Point Position Balance Control Strategy of Three Level Inverter (HXZK2487).
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Data availability: Not applicable.
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