Desmond Eseoghene Ighravwe - Corresponding author: Department of Mechanical Engineering, Bells University of Technology, Ota, Nigeria
Akpevweoghene Solomon Abijah - University of Limerick, Castletroy, Limerick, V۹۴ T۹PX, Ireland
Daniel Osezua Aikhuele - Department of Mechanical Engineering, University of Port-Harcourt, Nigeria
Sunday Thomas Ajayi - Department of Mechanical Engineering, Bells University of Technology, Ota, Nigeria
Johnson Adeleke Adeyiga - Department of Computer Science and Information Technology, Bells University of Technology, Ota, Nigeria

Background: Several aquaculture industries in underdeveloped nations use fossil fuel-powered generators to produce electricity. This pattern has raised greenhouse gas emissions as well as the price of aquaculture products. Methods: To address this issue, this study contains a bi-objective model that optimizes the parametric settings of waste-to-energy (WTE) plants for aquaculture firms: Levelized cost of energy and power expenses for reverse logistics. The best values for these objectives were created using a genetic algorithm and goal programming. Results: Four planning periods were taken into account during implementation, and actual data were gathered from a Nigerian aquaculture company. The electricity costs from biodiesel ranged from N۰.۷۵۴۱ per kW to N۰.۷۶۲۸ per kW, respectively. Reverse logistics has energy costs ranging from N۶ ۳۲۹ ۴۹۲.۱۰ to N۷ ۱۲۱ ۰۱۵.۵۳. The proposed model produced average values for several WTE parametric parameters, including a ۱.۶۹ million kg hydrogen gas, a ۵۹.۱۶% hydrogen gas compression efficiency, and an ۸۳.۳۹% electricity conversion efficiency. Furthermore, the system had logistics’ minimum and maximum fractions of ۰.۱۸% and ۲۱%, respectively. Conclusion: Our findings demonstrated how WTE parametric parameters impact the aquaculture industry’s electrical power unit.

Algorithm, Aquaculture, Electricity, Hydrogen, Nigeria