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Climate change and electricity demand in Brazil: A stochastic approach

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  1. Huntington, Hillard G. & Barrios, James J. & Arora, Vipin, 2019. "Review of key international demand elasticities for major industrializing economies," Energy Policy, Elsevier, vol. 133(C).
  2. Yang, Shubo & Jahanger, Atif & Awan, Ashar, 2024. "Temperature variation and urban electricity consumption in China: Implications for demand management and planning," Utilities Policy, Elsevier, vol. 90(C).
  3. Atalla, Tarek & Gualdi, Silvio & Lanza, Alessandro, 2018. "A global degree days database for energy-related applications," Energy, Elsevier, vol. 143(C), pages 1048-1055.
  4. Tian, Chuyin & Huang, Guohe & Piwowar, Joseph M. & Yeh, Shin-Cheng & Lu, Chen & Duan, Ruixin & Ren, Jiayan, 2022. "Stochastic RCM-driven cooling and heating energy demand analysis for residential building," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
  5. Ang, B.W. & Wang, H. & Ma, Xiaojing, 2017. "Climatic influence on electricity consumption: The case of Singapore and Hong Kong," Energy, Elsevier, vol. 127(C), pages 534-543.
  6. Tian, Chuyin & Huang, Guohe & Lu, Chen & Zhou, Xiong & Duan, Ruixin, 2021. "Development of enthalpy-based climate indicators for characterizing building cooling and heating energy demand under climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
  7. Atif Maqbool Khan & Magdalena Osińska, 2021. "How to Predict Energy Consumption in BRICS Countries?," Energies, MDPI, vol. 14(10), pages 1-21, May.
  8. Baxter L. M. Williams & R. J. Hooper & Daniel Gnoth & J. G. Chase, 2025. "Residential Electricity Demand Modelling: Validation of a Behavioural Agent-Based Approach," Energies, MDPI, vol. 18(6), pages 1-22, March.
  9. Zhanyang Xu & Jian Xu & Chengxi Xu & Hong Zhao & Hongyan Shi & Zhe Wang, 2024. "Analysis of the Impact of Policies and Meteorological Factors on Industrial Electricity Demand in Jiangsu Province," Sustainability, MDPI, vol. 16(22), pages 1-23, November.
  10. Ian M. Trotter & Lu'is A. C. Schmidt & Bruno C. M. Pinto & Andrezza L. Batista & J'essica Pellenz & Maritza Isidro & Aline Rodrigues & Attawan G. S. Suela & Loredany Rodrigues, 2020. "COVID-19 and Global Economic Growth: Policy Simulations with a Pandemic-Enabled Neoclassical Growth Model," Papers 2005.13722, arXiv.org, revised Jun 2020.
  11. Thangjam Aditya & Sanjita Jaipuria & Pradeep Kumar Dadabada, 2025. "A Review of Methods for Long‐Term Electric Load Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(4), pages 1403-1423, July.
  12. Kamal Chapagain & Somsak Kittipiyakul, 2018. "Performance Analysis of Short-Term Electricity Demand with Atmospheric Variables," Energies, MDPI, vol. 11(4), pages 1-34, April.
  13. Mauree, Dasaraden & Naboni, Emanuele & Coccolo, Silvia & Perera, A.T.D. & Nik, Vahid M. & Scartezzini, Jean-Louis, 2019. "A review of assessment methods for the urban environment and its energy sustainability to guarantee climate adaptation of future cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 733-746.
  14. Alejandra Martínez-Martínez & Rafael Llorca-Vivero, 2025. "The Taxonomy of Climate Change: How Rising Temperatures Unequally Impact Nations’ Discomfort," Working Papers 2507, Department of Applied Economics II, Universidad de Valencia.
  15. Zheng, Shuguang & Huang, Guohe & Zhou, Xiong & Zhu, Xiaohang, 2020. "Climate-change impacts on electricity demands at a metropolitan scale: A case study of Guangzhou, China," Applied Energy, Elsevier, vol. 261(C).
  16. João Vitor Leme & Wallace Casaca & Marilaine Colnago & Maurício Araújo Dias, 2020. "Towards Assessing the Electricity Demand in Brazil: Data-Driven Analysis and Ensemble Learning Models," Energies, MDPI, vol. 13(6), pages 1-20, March.
  17. Yi Liang & Dongxiao Niu & Ye Cao & Wei-Chiang Hong, 2016. "Analysis and Modeling for China’s Electricity Demand Forecasting Using a Hybrid Method Based on Multiple Regression and Extreme Learning Machine: A View from Carbon Emission," Energies, MDPI, vol. 9(11), pages 1-22, November.
  18. Atul Anand & L Suganthi, 2018. "Hybrid GA-PSO Optimization of Artificial Neural Network for Forecasting Electricity Demand," Energies, MDPI, vol. 11(4), pages 1-15, March.
  19. Ahmed, T. & Vu, D.H. & Muttaqi, K.M. & Agalgaonkar, A.P., 2018. "Load forecasting under changing climatic conditions for the city of Sydney, Australia," Energy, Elsevier, vol. 142(C), pages 911-919.
  20. Chabouni, Naima & Belarbi, Yacine & Benhassine, Wassim, 2020. "Electricity load dynamics, temperature and seasonality Nexus in Algeria," Energy, Elsevier, vol. 200(C).
  21. Ian M. Trotter & Torjus F. Bolkesj{o} & Eirik O. J{aa}stad & Jon Gustav Kirkerud, 2021. "Increased Electrification of Heating and Weather Risk in the Nordic Power System," Papers 2112.02893, arXiv.org.
  22. Kang, Jieyi & Reiner, David M., 2022. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Energy Economics, Elsevier, vol. 111(C).
  23. Fan, Jing-Li & Hu, Jia-Wei & Zhang, Xian, 2019. "Impacts of climate change on electricity demand in China: An empirical estimation based on panel data," Energy, Elsevier, vol. 170(C), pages 880-888.
  24. Hsiao, Cody Yu-Ling & Chen, Hsing Hung, 2018. "The contagious effects on economic development after resuming construction policy for nuclear power plants in Coastal China," Energy, Elsevier, vol. 152(C), pages 291-302.
  25. Fernando Alves Silveira & Silvio Parodi de Oliveira Camilo, 2024. "A blockchain-based platform for trading weather derivatives," Digital Finance, Springer, vol. 6(1), pages 3-22, March.
  26. Jose M. Garrido-Perez & David Barriopedro & Ricardo García-Herrera & Carlos Ordóñez, 2021. "Impact of climate change on Spanish electricity demand," Climatic Change, Springer, vol. 165(3), pages 1-18, April.
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