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Effect of Meteorological Variables on Energy Demand in the Northeast and Southeast Regions of Brazil

Author

Listed:
  • Helber Barros Gomes

    (Instituto de Ciências Atmosféricas (ICAT), Universidade Federal de Alagoas (UFAL), Maceió 57072-970, AL, Brazil)

  • Dirceu Luís Herdies

    (Instituto Nacional de Pesquisas Espaciais (INPE), Cachoeira Paulista 12630-000, SP, Brazil)

  • Luiz Fernando dos Santos

    (Tempo OK Tecnologia em Meteorologia LTDA, São Paulo 05510-020, SP, Brazil)

  • João Augusto Hackerott

    (Tempo OK Tecnologia em Meteorologia LTDA, São Paulo 05510-020, SP, Brazil)

  • Bruno Ribeiro Herdies

    (Faculdade de Zootecnia e Engenharia de Alimentos (USP/FZEA), Universidade de São Paulo, Pirassununga 13635-900, SP, Brazil)

  • Fabrício Daniel dos Santos Silva

    (Instituto de Ciências Atmosféricas (ICAT), Universidade Federal de Alagoas (UFAL), Maceió 57072-970, AL, Brazil)

  • Maria Cristina Lemos da Silva

    (Instituto de Ciências Atmosféricas (ICAT), Universidade Federal de Alagoas (UFAL), Maceió 57072-970, AL, Brazil)

  • Mario Francisco Leal de Quadro

    (Instituto Federal de Santa Catarina, Florianópolis 88020-300, SC, Brazil)

  • Robinson Semolini

    (Neoenergia Elektro, Campinas 13053-024, SP, Brazil)

  • Amanda Cortez

    (Neoenergia Elektro, Campinas 13053-024, SP, Brazil)

  • Bruna Schatz

    (Neoenergia Elektro, Campinas 13053-024, SP, Brazil)

  • Bruno Dantas Cerqueira

    (Neoenergia Coelba, Salvador 41186-900, BA, Brazil)

  • Djanilton Henrique Moura Junior

    (Neoenergia COSERN, Natal 59078-270, RN, Brazil)

Abstract

Energy consumption demand has shown successive records during recent months, primarily associated with heat waves in almost all Brazilian states. The effects of climate change induced by global warming and the increasingly frequent occurrence of extreme events, mainly regarding temperature and precipitation, are associated with this increase in demand. In this sense, the impact of meteorological variables on load demand in some substations in the northeast and southeast of Brazil was analyzed, considering the historical series of energy injected into these substations. Fifteen substations were analyzed: three in the state of São Paulo, six in Bahia, three in Pernambuco, and three in Rio Grande do Norte. Initially, essential quality control was carried out on the energy injection data. The SAMeT data sets were used for the variable temperature, and Xavier was used for precipitation and relative humidity to obtain a homogeneous data series. Daily and monthly data were used for a detailed analysis of these variables in energy demand over the northeast and southeast regions of Brazil. Some regions were observed to be sensitive to the maximum temperature variable, while others were sensitive to the average temperature. On the other hand, few cases showed the highest correlation with the precipitation and relative humidity variables, with most cases being considered slight or close to zero. A more refined analysis was based on the type of consumers associated with each substation. These results showed that where consumption is more residential, the highest correlations were associated with maximum temperature in most stations in the northeast and average temperature in the southeast. In regions where consumption is primarily rural, the correlation observed with precipitation and relative humidity was the highest despite being negative. A more detailed analysis shows that rural production is associated with irrigation in these substations, which partly explains consumption, as when rainfall occurs, the demand for irrigation decreases, and thus energy consumption is reduced.

Suggested Citation

  • Helber Barros Gomes & Dirceu Luís Herdies & Luiz Fernando dos Santos & João Augusto Hackerott & Bruno Ribeiro Herdies & Fabrício Daniel dos Santos Silva & Maria Cristina Lemos da Silva & Mario Francis, 2024. "Effect of Meteorological Variables on Energy Demand in the Northeast and Southeast Regions of Brazil," Energies, MDPI, vol. 17(19), pages 1-12, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:19:p:4776-:d:1484761
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    References listed on IDEAS

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    2. OrtizBeviá, M.J. & RuizdeElvira, A. & Alvarez-García, F.J., 2014. "The influence of meteorological variability on the mid-term evolution of the electricity load," Energy, Elsevier, vol. 76(C), pages 850-856.
    3. Shaik, Saleem & Yeboah, Osei-Agyeman, 2018. "Does climate influence energy demand? A regional analysis," Applied Energy, Elsevier, vol. 212(C), pages 691-703.
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