ARTIFICIAL INTELLIGENCE DRIVEN ENERGY MANAGEMENT OF A HYBRID MINI-GRID

Bello, Ilesanmi Oluwayomi and Covenant University, Theses (2022) ARTIFICIAL INTELLIGENCE DRIVEN ENERGY MANAGEMENT OF A HYBRID MINI-GRID. Masters thesis, Covenant University Ota.

PDF Download (789kB)

Abstract

With 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.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Fuzzy Logic, Genetic Algorithm, Energy management, Supply-side management
Subjects:	T Technology > TJ Mechanical engineering and machinery
Divisions:	Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User:	nwokealisi
Date Deposited:	09 Sep 2022 13:50
Last Modified:	09 Sep 2022 13:50
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/16164

Actions (login required)

View Item