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 N0.7541 per kW to N0.7628 per kW, respectively. Reverse logistics has energy costs ranging from N6 329 492.10 to N7 121 015.53. The proposed model produced average values for several WTE parametric parameters, including a 1.69 million kg hydrogen gas, a 59.16% hydrogen gas compression efficiency, and an 83.39% electricity conversion efficiency. Furthermore, the system had logistics’ minimum and maximum fractions of 0.18% and 21%, respectively.
Conclusion: Our findings demonstrated how WTE parametric parameters impact the aquaculture industry’s electrical power unit.