Thermoelectric generation with reduced pollutants made possible by bio-inspired computing

• Autor(a) principal: Costa, Denis Carlos Lima
• Data de Publicação: 2022
• Outros Autores: Meneses, Lair Aguiar de, Lima, Mara Líbia Viana de, Costa, Heictor Alves de Oliveira, Reis, Adriane Cristina Fernandes, Pinheiro, Huan Ferreira Brasil, Costa, Erick Freitas da, Silva, André Renan dos Santos da, Reis, Ariane Cristina Fernandes, Raiol, Felippe Mathias, Santos, Roberto Carlos Pinheiro dos
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/24568
• topic: Power generation; Level of pollutants; Natural gas; Genetic Algorithm.; Generación de energía; Nivel de contaminantes; Gas natural; Algoritmo genético.; Geração de energia; Nível de poluentes; Gás natural; Algoritmo genético.

The debate to establish a balance between the generation of electricity and the preservation of the environment is, extraordinarily, important. This article proposes, as a short-term solution, the replacement of diesel oil by natural gas in thermoelectric generation. Natural gas emits 75% less pollutants to the environment than diesel and has a similar energetic efficiency. As a strategy for this replacement to occur safely, the computational modeling was developed in a Bioinspired Computing methodology, called Genetic Algorithm (GA). The GA incorporated all the variables of the electricity and natural gas networks, presented in the mathematical modeling. The result was a significant reduction in the level of pollutants emitted, with high stability in the electrical power system.