Optimization of Biogas Plant Operational Efficiencies Using Evolutionary Algorithms

The growing needs for clean energy will continue to attract global attention, especially as it has been recognized as a means of managing solid wastes - especially from households and industrial sector. We now have different waste-to-energy technologies for small and medium-scale plants. But sparse information exists on how to optimize these plants operational efficiencies, especially boilers and reformers. Hence, this article considers the optimization of these efficiencies to optimal electricity generation. This objective is achieved using a nonlinear programming approach. The proposed model utility was tested using a case study of six locations in Southwest Nigeria. A comparison of Genetic algorithm (GA) and Differential Evolution (DE) algorithm are presented as solution methods for the model. In terms of the total electricity generated, there is no significant difference between these algorithms results. The total electricity generated is 10MW, while the average boilers and reformers efficiencies are 0.9 and 0.8, respectively. To be strategic with a waste-to-energy operation, this article recommends that optimal parametric settings for a plant’s operational efficiencies should be combined with experts’ opinions.