The cost associated with generating electrical energy varies among power plants, influenced by the energy source and the emissions produced. Due to these operational cost differences, economic dispatch techniques that consider emissions are commonly employed to optimize power systems, aiming to minimize both operational costs and pollutant emissions. The continual increase in electric power generation, driven by global economic development, has led to a significant rise in greenhouse gas emissions. This surge in electrical generation, primarily fueled by coal (accounting for 42% of global electricity generation), contributes to environmental issues such as global warming, ozone layer depletion, and air pollution. The heavy reliance on fuel for electricity generation results in elevated costs, attributed to expenses incurred by generation companies for emissions fees and fuel procurement. This study addresses these challenges by implementing an advanced approach, utilizing the developed Moth Flame Optimization and Bat hybrid algorithm.