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In rural areas, grid expansions and diesel generators are commonly used to provide electricity, but their high maintenance costs and CO2 emissions make renewable energy sources (RES) a more practical alternative. Traditional methods such as analytical, statistical, and numerical-based techniques are inadequate for designing an energy-efficient RES. Therefore, this study utilized the bat algorithm (BA) to optimize the use of hybrid RES for rural electrification. A feasibility study was conducted in the village of Kalema to assess energy consumption, and a diesel-only system was modeled to serve the entire community. The BA was used to determine the optimal size and cost-effectiveness of the hybrid RES, with MATLAB R (2021a) utilized for simulation. The BA's performance was compared with diesel only and GA using cost of energy (COE) and CO2 emissions as metrics. Diesel generators only produced a COE of 6, 562, 000 and 1679. 6 lb/hr of CO2 emissions. COE with BA was 356, 9781. 37 (a 45. 6% reduction) and CO2 emissions were 635. 29 lb/hr (a 62. 2% drop). Genetic algorithm (GA) resulted in 364, 3122. 46 COE and 652. 69 lb/hr CO2 emissions, indicating 61. 1% and 44. 5% decreases, respectively. BA significantly reduced COE and CO2 emissions over GA, according to the analysis.
Adebayo et al. (Thu,) studied this question.