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Renewable energy solutions based on artificial intelligence for farms in the state of Minas Gerais, Brazil: Analysis and proposition by Augusto Cesar Laviola de Oliveira; Natalia dos Santos Renato; Marcio Arêdes Martins; Isabela Miranda de Mendonça; Camile Arêdes Moraes; Lucas Fernandes Rocha Lago is a Engineering article available to read on EtoBox.

What is Renewable energy solutions based on artificial intelligence for farms in the state of Minas Gerais, Brazil: Analysis and proposition about?

Rural areas have great renewable energy potential. With an introduction to sustainable development goals, the smart farm concept presents a novel idea for providing energy in rural areas using artificial intelligence and renewable energy management. We proposed the following topics in this research: (i) methodologies for sizing generation systems by integer linear programming, (ii) use of analytic hierarchy process (AHP) to select the alternative source by financial, environmental, social, and physical criteria, and (iii) training of an artificial neural network (ANN) for process optimization based on the agroeconomic profile of farms. We applied the proposed generic methodology to farms in São Francisco do Glória, Brazil. The biomass, solar, and wind systems were indicated by AHP for implementation in 62.16, 15.32, and 22.52% of farms, respectively. The best configuration of ANN presented a maximum precision of 81.80 ± 3.36%. If the systems were to be implemented, 1.975 GWh yr -1 would be generated, 435.23 tonnes of CO 2 would no longer be emitted per year, and a CO 2 credit of 366.62 tonnes yr -1 would be injected into the national electric system. Public policies are necessary f

Who reads Renewable energy solutions based on artificial intelligence for farms in the state of Minas Gerais, Brazil: Analysis and proposition?

It is typically read by researchers, students, and practitioners in Engineering.

Author
Augusto Cesar Laviola de Oliveira; Natalia dos Santos Renato; Marcio Arêdes Martins; Isabela Miranda de Mendonça; Camile Arêdes Moraes; Lucas Fernandes Rocha Lago
Publisher
Elsevier BV
Published
2023
Language
EN
Field
Engineering (Physical Sciences)

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