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Development of a Genetic Algorithm Optimization Model for Biogas Power Electrical Generation

Author

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  • Timothy Oluwaseun Araoye

    (Department of Electrical and Electronics Engineering, Enugu State University of science and Technology, Enugu, Nigeria)

  • C. A. Mgbachi

    (Department of Electrical and Electronics Engineering, Enugu State University of Science and Technology, Enugu, Nigeria)

  • Olushola Adebiyi Omosebi

    (Department of Works and Services, Federal College of Education, Oyo, Nigeria.)

  • Oluwaseun Damilola Ajayi

    (Department of Electrical and Electronics Engineering, University of Ibadan, Ibadan, Nigeria)

  • Adeleye Qasim Olaniyan

    (Department of Electrical and Electronics Engineering, University of Ibadan, Ibadan, Nigeria)

Abstract

Biogas power generation is renewable energy made from biological materials. Biogas power production is technology which helps in development of sustainable energy supply systems. This paper develops Genetic Algorithm optimization model for Biogas electrical power generation of Ilora in Oyo, Oyo state. The production is done using co-digestion system of pig dung and Poultry dung under the process of anaerobic digestion. The pig dung and poultry dung were mixed 50:50%. MATLAB and VISUAL BASIC Software was used to carry out simulations to develop optimized Genetic Algorithm model for Biogas power production with aims to improving electricity accessibility and durability of the community. The results of the research reveal the Empirical Biogas power production without and with Genetic Algorithm optimization. The Result showed that biogas electrical power generated without and with Genetic Algorithm Optimization were 5KW and 11.18KW respectively. The biogas power generation was increased by 6.18KW, which is 38.2% increase after Genetic Algorithm optimization. The results show the application of the Genetic Algorithm optimization model which can be used to improving Biogas power generation when amount of methane gas produced from the animal dung varies with speed of thermal rotating shaft.

Suggested Citation

  • Timothy Oluwaseun Araoye & C. A. Mgbachi & Olushola Adebiyi Omosebi & Oluwaseun Damilola Ajayi & Adeleye Qasim Olaniyan, 2019. "Development of a Genetic Algorithm Optimization Model for Biogas Power Electrical Generation," European Journal of Engineering and Technology Research, European Open Science, vol. 4(2), pages 7-11, February.
    • Handle: RePEc:epw:ejeng0:v:4:y:2019:i:2:id:61111
    DOI: 10.24018/ejeng.2019.4.2.1111
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