Artificial Ecosystem-Based Optimization for Solving the Multi-Objective Economic Emission Load Dispatch Problem with Wind-Solar-Thermal Integration and Uncertainty Handling

Thermal generating units have incorporated renewable energy sources, such solar and wind, to lower pollutant gas emissions and overall fuel costs. As a result, the incorporation of renewable sources such as wind energy makes the multi-objective EELD issue more complicated and non-linear. An Artificial Ecosystem-Based Optimization (AEO) method has been presented to address this issue by optimizing the wind-solar-thermal model's cost and emissions while accounting for uncertainty in the outputs of solar and wind power. Key components of the AEO algorithm, which draw inspiration from ecosystem dynamics, enable search agents to more quickly converge to global optima and successfully escape local optima. Two systems—one with 40 heat producing units and the other with 13—have been used to test the suggested method.