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.