(Universidade Federal do Pará, 2023) Santos, Eliton Smith dos; NUNES, Marcus Vinicius Alves
Economic Load Dispatch (ELD) aims at planning and operating Thermoelectric Power Plants (TPP) to meet energy demand at the lowest cost. However, traditional ELD does not consider environmental costs, which are crucial under current sustainability concerns. Thus, this thesis proposes the use of metaheuristic techniques — Ant Lion Optimizer (ALO), Dragonfly Algorithm (DA), and Differential Evolution (DE) — to optimize the Environmental Economic Dispatch (EED), integrating photovoltaic solar generation. The proposal includes an intelligent algorithm that adjusts TPP motor power based on demand, allowing the shutdown of less efficient motors and reducing emissions. Simulations performed in the MATLAB environment, with a hybrid model of six Generating Units (GU) and thirteen Solar Photovoltaic Plants (SPP), demonstrated that the DE technique yielded the best results, reducing fossil fuel consumption by 3.02% and atmospheric emissions by 1.42%.
