文章基本信息

标题：Thermoelectric generation with reduced pollutants made possible by bio-inspired computing
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作者：Denis Carlos Lima Costa ; Lair Aguiar de Meneses ; Mara Líbia Viana de Lima 等
期刊名称：Research, Society and Development
电子版ISSN：2525-3409
出版年度：2022
卷号：11
期号：1
页码：1-13
DOI：10.33448/rsd-v11i1.24568
语种：English
出版社：Grupo de Pesquisa Metodologias em Ensino e Aprendizagem em Ciências
摘要：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.
关键词：Power generation;Level of pollutants;Natural gas;Genetic Algorithm.