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.

The classic Economic Dispatch (ED) problem considers only the cost of power generation by thermal generators, often disregarding the safety parameters of the electrical network, environmental costs and especially the importance of predictive maintenance of the generators, when considering environmental costs in the optimization of ED this becomes a multi-objective problem Environmental Economic Dispatch (EED). Considering the global pressure to reduce emissions of pollutants in the atmosphere and environmental sustainability, incorporating the generation of Renewable Energies (RE) or Green Energy in the electricity grid is indispensable. Solar energy is becoming an important part of the power generation portfolio in many regions due to the fast decline in its costs and political incentives that favor the generation of clean energy sources. This article uses the Ant Lion Optimizer (ALO) method to solve the problem and EED restricted to the grid in a hybrid system (thermoelectric and photovoltaic). The results of the optimization problem were simulated in MATLAB. This research included 01 thermoelectric with 06 generators and 13 solar plants.

The present study has as main objective to verify the reduction of electric energy consumption, allied to the possible economic-financial and environmental benefits that are associated with the use of LED lamps in a commercial building, where it develops office activities covering only part of the building. , which served as the experimental basis for the application of the case study, initiated after a survey of the electrical and constructive characteristics of the luminaires installed on site. In research conducted in the local market specialized in the subject, we selected lamps that are more easily found, analogous to those already installed, manufactured by traditional companies in the field. The monitoring of lighting loads was made by measuring by specific equipment and simulation of energy billing according to the rules of calculations established in rules governed by government agencies and tariff framework in which the building is in both scenarios, before and after lamp replacement. Providing financial technical evaluation through the use of indicators that show the viability of this substitution.