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AUTHOR(S):

Dianabasi Etuk, Kingsley Udofia, Nseobong Okpura

 

TITLE

Modelling and Optimization of Cost Function for Hybrid Power Generation System using Genetic Algorithm

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ABSTRACT

Recently, there has been a growing demand for clean, reliable and cost-effective energy especially in energy-deficient areas. The high cost involved in generating power in Nigeria is very alarming. Thus, reducing this cost is very imperative and critical to the overall economic benefit of the country. This study presents mathematical models and simulation of a grid connected hybrid energy system consisting of solar-diesel based hybrid energy system for overall cost minimization. In this study, the optimal energy cost of renewable generating systems are evaluated using the genetic algorithm optimization technique. Two cost models were developed for this study. The first model considers the use of diesel generator only to produce power and the second model considers the optimized systems which include the solar power generation and the diesel power generation. The result showed that the cost of generating a kWh of energy dropped from USD 65.789 in scenario 1 to USD 0.132 in scenarios 2. From the value obtained in scenario 2, it can be inferred that the combination of solar and diesel for power generation is a more reliable, environmentally friendly and cost-effective strategy for producing energy.

KEYWORDS

Hybrid Energy System, Victor Attah International Airport, Air Field Lighting, Localizer, Genetic Algorithm, Green House Gas.

 

Cite this paper

Dianabasi Etuk, Kingsley Udofia, Nseobong Okpura. (2020) Modelling and Optimization of Cost Function for Hybrid Power Generation System using Genetic Algorithm. International Journal of Education and Learning Systems, 5, 40-48

 

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