ARTIFICIAL INTELLIGENCE DRIVEN ENERGY MANAGEMENT OF A HYBRID MINI-GRID

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dc.contributor.authorBELLO, ILESANMI OLUWAYOMI
dc.date.accessioned2022-12-19T17:03:32Z
dc.date.available2022-12-19T17:03:32Z
dc.date.issued2022
dc.description.abstractWith the driving theme of sustainability in our world today, it is imperative to consider approaches to reduce the carbon footprint on a global scale. One critical area is in the generation and distribution of energy supply. In the management of energy, various methodologies have been implemented especially in the area of Demand Side Management where a lot of research work has been done. However, while it is very important for the consumer to be very efficient in their consumption of energy, it is also quite critical that energy supply is properly managed such that even though the demand is optimized, the supply also needs to be properly optimized to avoid energy wastage. This work has contributed to the ongoing research for Supply Side Management by adopting two heuristic artificial intelligence models – Fuzzy logic for intelligent decisions and Genetic Algorithm (GA) for optimizing the energy supplied to consumers. The fuzzy logic helps in predicting the demand and optimizing it for the required supply while the GA helps to clean up the minimization function for the optimization of the supply of energy. This model is applicable to any energy system – on-grid and off-grid application.
dc.identifier.urihttps://nerd.ethesis.ng/handle/123456789/630
dc.titleARTIFICIAL INTELLIGENCE DRIVEN ENERGY MANAGEMENT OF A HYBRID MINI-GRID
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