Charting the future of Brazil’s electricity: a multicriteria analysis of northeastern power strategies amidst climate challenge
DOI:
https://doi.org/10.5327/Z2176-94782093Keywords:
technique for order of preference by similarity to ideal solution; multi-criteria decision making; energy transition; climate change; energy planning.Abstract
The article addresses the challenges faced by regions under water stress, such as conflicts over water use, environmental degradation, and water resource scarcity, intensified by climate change. In areas dependent on hydropower generation, these problems are exacerbated, highlighting the need to transition to more sustainable and resilient energy sources. The study emphasizes the importance of multifaceted criteria for an effective transition of the electricity matrix in semi-arid regions, taking into account economic, technical, environmental, and social aspects. Focusing on the São Francisco River basin in Northeastern Brazil, where the energy matrix is predominantly hydroelectric, the study uses the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to evaluate alternative scenarios, analyzing options for wind, solar, and thermoelectric energy. The methodology adopted included the close collaboration of experts in defining and weighting essential criteria, covering economic, technical, environmental, and social aspects. The results show that, within the same group, options that involve greater reductions in hydroelectric generation are more advantageous. Analyzing the ranking among all alternatives, the group that includes higher expansion of wind energy presents the most viable options, followed by the reference strategy (based on average annual generation) and the group with greater expansion of solar capacity. Increasing the share of gas-fired thermoelectric power is considered a less favorable solution according to the criteria used in the model.
Downloads
References
Abdel-Basset, M.; Gamal, A.; Chakrabortty, R.K.; Ryan, M., 2021. A new hybrid multicriteria decision-making approach for location selection of sustainable offshore wind energy stations: a case study. Journal of Cleaner Production, v. 280, 124462. https://doi.org/10.1016/j.jclepro.2020.124462.
Almeida, A.T., 2013. Processo de decisão nas organizações. Atlas, São Paulo, 256 p.
Almeida, A.T.; Morais, D.C.; Costa, A.P.C.S.; Alencar, L.H.; Daher S.F.D., 2021. Decisão em grupo e negociação. Interciência, Rio de Janeiro, 292 p.
Amer, M.; Daim, T., 2011. Selection of renewable energy technologies for a developing county: a case of Pakistan. Energy for Sustainable Development, v. 14 (4), 420-435. https://doi.org/10.1016/j.esd.2011.09.001.
Bolson, N.; Pietro, P.; Patzek, T., 2022. Capacity factors for electrical power generation from renewable and nonrenewable sources. Proceedings of the National Academy of Sciences of United States of America, v. 119 (12), e2205429119. https://doi.org/10.1073/pnas.220542911.
Brasil, 2014. Empresa de Pesquisa Energética (EPE). Plano Nacional de Energia – PNE 2030 (Accessed August 23, 2022) at:. https://www.epe.gov.br/pt/publicacoes-dados-abertos/publicacoes/Plano-Nacional-de-Energia-PNE-2030.
Brasil, 2017. Agência Nacional de Energia Elétrica (ANEEL). Prospecção tecnológica no setor elétrico brasileiro: evolução tecnológica de geração de energia elétrica e armazenamento de energia. v. 3. Centro de Gestão e Estudos Estratégicos, Brasília.
Brasil, 2020. Empresa de Pesquisa Energética (EPE). Plano Nacional de Energia – PNE 2050 (Accessed July 28, 2023) at:. https://www.epe.gov.br/pt/publicacoes-dados-abertos/publicacoes/Plano-Nacional-de-Energia-2050.
Brasil, 2022. Empresa de Pesquisa Energética (EPE). Plano Decenal de Expansão de Energia – PDE 2031 (Accessed November 18, 2023) at:. https://www.epe.gov.br/pt/publicacoes-dados-abertos/publicacoes/plano-decenal-de-expansao-de-energia-2031.
Brasil, 2023. Operador Nacional do Sistema Elétrico (ONS). Histórico de operação (Accessed April 03, 2023) at:. https://www.ons.org.br/paginas/resultados-da-operacao/historico-da-operacao/dados-gerais.
Çalık, A., 2021. A novel Pythagorean fuzzy AHP and fuzzy TOPSIS methodology for green supplier selection in the Industry 4.0 era. Soft Computing, v. 25 (3), 2253-2265. https://doi.org/10.1007/s00500-020-05294-9.
Chaube, S.; Pant, S.; Kumar, A.; Uniyal, S.; Singh, M.K.; Kotecha, K.; Kumar, A., 2024. An overview of multi-criteria decision analysis and the applications of AHP and TOPSIS methods. International Journal of Mathematical, Engineering and Management Sciences, v. 9 (3), 581-615. https://doi.org/10.33889/IJMEMS.2024.9.3.030.
Dantas, G.C.B.; Rodrigues, M.V.S.; Silva, L.M.X.; Aquino, M.D.D.; Thomaz, A.C.F., 2021. Panorama do setor eólico no estado do Rio Grande do Norte no período 2004-2017. Energia e Ambiente (Online), v. 35 (102), 79-94. https://doi.org/10.1590/s0103-4014.2021.35102.005.
Dipto, A.S.; Bari, A.; Nabil, S.T., 2020. Sustainability analysis of different types of power plants using multi-criteria decision analysis methods. Journal of Engineering Advancements, v. 1 (3), 94-100. https://doi.org/10.38032/jea.2020.03.004.
European Commission. Energy Technologies: Knowledge, Perception, Measures. Special Eurobarometer 262 / Wave 6.3 – TNS Opinion & Social (Accessed Janeiro 15, 2021) at:. https://europa.eu/eurobarometer/screen/home.
Ferreira, T.V.B., 2014. Hidrograma Ambientais para o Baixo São Francisco: avaliação de impactos sobre a geração hidrelétrica. Master's Thesis, Coppe, Universidade Federal do Rio de Janeiro, Rio de Janeiro. Retrieved 2019-06-15, from http://www.coc.ufrj.br/pt/dissertacoes-de-mestrado/380-msc-pt-2014/4473-thiago-vasconcellos-barral-ferreira.
Gates, B., 2021. How to avoid a climate disaster: the solutions we have and the breakthroughs we need. Allen Lane, New Delhi, India.
Golfam, P.; Ashofet, P.; Rajee, T.; Chu, X., 2019. Prioritization of water allocation for adaptation to climate change using Multi-Criteria Decision Making (MCDM). Water Resources Management, v. 30, 3401-3416. https://doi.org/10.1007/s11269-019-02307-7.
Hanna, R.; Heptonstall, P.; Gross, R., 2024. Job creation in a low carbon transition to renewables and energy efficiency: a review of international evidence. Sustainability Science, v. 19, 125-150. https://doi.org/10.1007/s11625-023-01440-y.
International Energy Agency (IEA), 2024. IEA Data Services. (Accessed August 20, 2024) at:. https://www.iea.org/countries/brazil/energy-mix.
Koch, H.; Silva, A.; Azevedo, R.; Souza, W.; Koppel, J.; Souza Júnior, C.B.; Hattermann, F., 2018. Integrated hydro- and wind power generation: a game changer towards environmental flow in the Sub-middle and Lower São Francisco River Basin. Regional Environmental Change, v. 18, 1927-1942. https://doi.org/10.1007/s10113-018-1301-2.
Kou, G.; Akdeniz, Ö.O.; Dinçer, H.; Yüksel, S., 2021. Fintech investments in European banks: a hybrid IT2 fuzzy multidimensional decision-making approach. Financial Innovation, v. 7, 39. https://doi.org/10.1186/s40854-021-00256-y
Koutsandreas, D.; Keppo, I., 2023. A stochastic fuzzy multicriteria methodology for energy planning decision support: case study of the electrification of the Greek road transport sector. Energy Strategy Reviews, v. 50, 101-233. https://doi.org/10.2139/ssrn.4497311
Krysanova, V.; Wechsung, F.; Arnold, J.; Srinivasan, R.; Williams, J., 2000. Soil and water integrated model: user manual. Potsdam Institute for Climate Impact Research, Potsdam. PIK Report 69.
Majid, B.; Khanmohammadi, O.S.; Morteza, Y.; Ignatius, J., 2012. A state-of the-art survey of TOPSIS applications. Expert Systems with Applications, v. 39 (17), 13051-13069. https://doi.org/10.1016/j.eswa.2012.05.056.
Medeiros, Y.; Freitas, I.; Stifelman, G.; Freire, O’Keeffe, J., 2013. Social participation in the environmental flow assessment: the São Francisco River case study. Revista Eletrônica de Gestão e Tecnologia Ambientais, v. 1 (1), 122-130. https://doi.org/10.9771/gesta.v1i1.7110
Pandey, V.; Komal; Dincer, H., 2023. A review on TOPSIS method and its extensions for different applications with recent development. Soft Computing, v. 27, 18011-18039. https://doi.org/10.1007/s00500-023-09011-0.
Rahim, R.; Siahaan, A.P.U.; Wijaya, R.F.; H, H.; Aswan, N.; Thamrin, S.; Sari, D.A.P.; Agustina, S.; Santosa, R.B.; Muttaqin, W.M.; Sujito, S.; Yulia, Y.; Fatmasari, R.; Ikhwan, A.; Sugiarto, I.; Purnomo, A.; Anam, F.; Kulsum, N.M.; Diawati, P.; Mina, R.; Sujarwo, S., 2021. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for decision support system in top management. International Journal Engineering & Technology, v. 7 (3,4), 290-293.
Romero, J.A.G.; Rangel, M.G.M.; Aguilar, J.A.H.; Valencia, A.V.; Acle, J.C.A.O.; Gutiérrez, L.J.R.; Cano, H.A.F., 2022. Relationship between the main economic, environmental and social impacts of hydroelectric dams. Brazilian Journal of Development, v.8 (10), 66322-66345. https://doi.org/10.34117/bjdv8n10-100.
Sharpton, T.; Lawrence, T.; Hall, M., 2020. Drivers and barriers to public acceptance of future energy sources and grid expansion in the United States. Renewable and Sustainable Energy Reviews, v. 126, 109826. https://doi.org/10.1016/j.rser.2020.109826.
Souza Júnior, C.B.; Koch, H.; Siegmund-Schultze, M.; Köppel, J., 2019. An exploratory scenario analysis of strategic pathways towards a sustainable electricity system of the drought-stricken São Francisco River Basin. Energy Systems, v. 12, 563-602. https://doi.org/10.1007/s12667-019-00343-1.
Souza Júnior, C.B.; Siegmund-Schultze, M.; Köppel, J.; Sobral, M.C., 2017. Sinais de um problema crônico: a governança hídrica carece promover os comitês de bacias, coordenar planos e gerir informações. Revista Ambiente & Água, v. 12 (6), 1054-1067. https://doi.org/10.4136/ambi-agua.2044.
Taherdoost, H.; Madanchian, M., 2023. Multi-Criteria Decision Making (MCDM) methods and concepts. Encyclopedia, v. 3 (1), 77-87. https://doi.org/10.3390/encyclopedia3010006.
Wang, C.N.; Kao, J.C.; Wang, Y.H.; Nguyen, V.T.; Nguyen, V.T.; Husain, S.T., 2021. A multicriteria decision-making model for the selection of suitable renewable energy sources. Mathematics, v. 9, 1318. https://doi.org/10.3390/math9121318.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Revista Brasileira de Ciências Ambientais
This work is licensed under a Creative Commons Attribution 4.0 International License.