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(searched for: Development of a Genetic Algorithm Optimization Model for Biogas Power Electrical Generation)
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Timothy Oluwaseun Araoye, C. A. Mgbachi, Olushola Adebiyi Omosebi, Oluwaseun Damilola Ajayi, Adeleye Qasim Olaniyan
European Journal of Engineering and Technology Research, Volume 4, pp 7-11; doi:10.24018/ejers.2019.4.2.1111

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.
Stephen Oodo,
European Journal of Engineering and Technology Research, Volume 4, pp 64-68; doi:10.24018/ejers.2019.4.1.1063

Abstract:
The purpose of a power grid is to transfer electrical energy from the production to the consumption, while maintaining an acceptable reliability and voltage quality for all customers. This research paper present the integration of generation based on Biogas power renewable energy source to the Distribution network and how it stabilizes the network by normalizing the fluctuating voltage at the distribution end of power system. A Genetic Algorithm model was performed and evaluation of the impact of the DG by stimulating the developed model in the system. A mathematical formulation and optimization algorithm was performed using the MATLAB/Simulink program. The results obtained were correction of the faulty buses voltages and stable power supply which is 25% better than the conventional one. It was concluded that the implementation of the optimisation technique has improved the energy efficiency of the distribution network.
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