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Effective Power Restoration in the National Grid, Using Interconnected System (Neural Network Intelligence): A Review of the Nigerian Grid System

Power demand is increasing with recent developments in technology to improve and facilitate the smooth running of daily lives around the country. In other to realize the purpose of basic and daily use of energy and safer environment; researchers and fields of specialists have actualized methods of maximizing the advantages provided through artificial Neural community Intelligence techniques. This article affords an outline of this network and its application in the strength sector, basically the Nigerian national Grid, studies progress of energy recuperation, such as power failure and load recovery. There may be a great job to obtain automatic restoration in huge effective electricity restoration. The studies makes a specialty of healing of electricity failure in Nigeria with the aid of the usage of artificial neural network. There are many reasons of energy failures in Nigeria power community. Nigerian 330kV network was modeled. The network was modeled in PSAT and the south eastern part was mapped out and modeled with electricity library in SIMULINK. The contemporary side of the network without fault prevalence was provided. The contemporary side for each region after switching of each of the place’s circuit breaker was received and applied in producing the ANN model. ANN model version was applied to the power device version in SIMULINK and used to predict the effect switching places or location of the circuit. A great result was achieved thereafter.

Power Failure, Power Restoration, National Grid System, Artificial Neural Network, Artificial Intelligence

Uchegbu Chinenye Eberechi, Inyama Kelechi, Kalu Peace Onyekachi. (2023). Effective Power Restoration in the National Grid, Using Interconnected System (Neural Network Intelligence): A Review of the Nigerian Grid System. American Journal of Electrical Power and Energy Systems, 12(3), 40-50.

Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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