Solving Dynamic Combined Economic Environemental Dispatch Problem with Renewable Energies and Constraints Using Gorilla Troops Optimizer

Abstract

The primary goal is to optimize the hourly allocation of power generation outputs by minimizing operational costs, pollutant emissions, and transmission losses, and ensuring compliance with a range of equality and inequality constraints. To tackle this challenge, a novel metaheuristic algorithm inspired by gorilla’s behavior is proposed. Gorilla Troops Optimizer (GTO) was applied to 5- and 10-generator unit systems, integrating variable wind and solar energies over a day with varying load demands. To demonstrate the effectiveness of the GTO algorithm in handling the hybrid dynamic combined economic and environmental dispatch problem, including equality constraints, transmission losses, valve-point effects, prohibited operating zones, ramp rates, and power limits, its performance was compared with other optimization techniques. The findings indicate that GTO provides the optimal scheduling of power generators, leading to significant reductions in daily operational costs and emissions with high percentages. Moreover, the integration of renewable energy significantly reduces pollutant gas emissions, fuel costs, and transmission losses, while meeting all imposed constraints. This research positively contributes to enhancing the reliability of power supply systems, while simultaneously reducing environmental pollution, transmission losses, and fuel costs.