Open AccessThermoelectric generation with reduced pollutants made possible by bio-inspired computing
Author(s) -
Dênis Carlos Lima Costa,
Lair Aguiar de Meneses,
Mara Líbia Viana de Lima,
Heictor Alves de Oliveira Costa,
Adriane Cristina Fernandes Reis,
Huan Ferreira Brasil Pinheiro,
Erick Freitas da Costa,
André Renan dos Santos da Silva,
Ariane Cristina Fernandes Reis,
Felippe Mathias Raiol,
Roberto Carlos Pinheiro dos Santos
Publication year - 2022
Publication title -
research, society and development
Language(s) - English
Resource type - Journals
ISSN - 2525-3409
DOI - 10.33448/rsd-v11i1.24568
Subject(s) - pollutant , electricity , natural gas , electricity generation , diesel fuel , environmental science , genetic algorithm , process engineering , computer science , waste management , biochemical engineering , power (physics) , engineering , electrical engineering , chemistry , physics , organic chemistry , quantum mechanics , machine learning
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.