Citation: Santos, E.S.d.; Nunes, M.V.A.; Nascimento, M.H.R.; Leite, J.C. Rational Application of Electric Power Production Optimization through Metaheuristics Algorithm. Energies 2022, 15, 3253. https:// doi.org/10.3390/en15093253 Academic Editor: Marcin Kaminski Received: 15 March 2022 Accepted: 26 April 2022 Published: 29 April 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). energies Article Rational Application of Electric Power Production Optimization through Metaheuristics Algorithm Eliton Smith dos Santos 1, * , Marcus Vinícius Alves Nunes 1 , Manoel Henrique Reis Nascimento 2 and Jandecy Cabral Leite 2,† 1 Post-Graduate Program in Electrical Engineering, Federal University of Para—UFPA, Belem 66075-110, PA, Brazil; mvanprof@gmail.com 2 Research Department, Institute of Technology and Education Galileo of the Amazon—ITEGAM, Manaus 69020-030, AM, Brazil; hreys@itegam.org.br (M.H.R.N.); jandecy.cabral@itegam.org.br (J.C.L.) * Correspondence: eliton.santos@docente.unip.br † Jandecy Cabral Leite is a member of IEEE. Abstract: The aim of this manuscript is to introduce solutions to optimize economic dispatch of loads and combined emissions (CEED) in thermal generators. We use metaheuristics, such as particle swarm optimization (PSO), ant lion optimization (ALO), dragonfly algorithm (DA), and differential evolution (DE), which are normally used for comparative simulations, and evaluation of CEED optimization, generated in MATLAB. For this study, we used a hybrid model composed of six (06) thermal units and thirteen (13) photovoltaic solar plants (PSP), considering emissions of contaminants into the air and the reduction in the total cost of combustibles. The implementation of a new method that identifies and turns off the least efficient thermal generators allows metaheuristic techniques to determine the value of the optimal power of the other generators, thereby reducing the level of pollutants in the atmosphere. The results are presented in comparative charts of the methods, where the power, emissions, and costs of the thermal plants are analyzed. Finally, the comparative results of the methods were analyzed to characterize the efficiency of the proposed algorithm. Keywords: economic dispatch and combined emissions; thermal unit; photovoltaic solar generation; metaheuristics; optimization 1. Introduction The energy crises that occur worldwide can be managed through the connection of sustainable and renewable energy systems, which are needed as we attempt to reduce the use of fossil fuels as populations increase. Interconnected grids can be divided into a power system structure based on the joint operations to generate and transmit power to the load demand as operational and technical controls [1–3]. The standard economic load dispatch (ELD) solution seeks to assign the total power demand among all generators used to achieve the minimum fuel cost [4]. Deterministic methods applied in the ELD solution are difficult to apply because of the non-continuous, non-convex, and nonlinear nature of the problem [5,6]. However, new rules have forced Thermoelectric Power Plant (TPP) to reduce the amount of polluting emissions into the atmosphere, expanding the ELD issue to the economic combined emissions dispatch (CEED) created to minimize fuel costs and pollutant emissions such as NO x , SO x , and CO x elements from the TPP. Although the ELD and CEED problems are nonlinear optimization problems, many heuristic methods have been implemented to solve them, CEED is a multi- objective optimization [7,8]. The concept of the price penalty factor was proposed by some researchers to transform the CEED multi-objective issue into a single-objective issue by unifying the emission cost equations with the fuel cost equations [9,10]. Many techniques have been proposed to solve the ELD problem in power systems [11–13], and a nonconvex ELD difficulty has been addressed by several hybrid optimization tech- Energies 2022, 15, 3253. https://doi.org/10.3390/en15093253 https://www.mdpi.com/journal/energies