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A Review of Electricity Demand Forecasting in Low and Middle Income Countries: The Demand Determinants and Horizons

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  1. Anatolijs Borodinecs & Kristina Lebedeva & Natalja Sidenko & Aleksejs Prozuments, 2022. "Enhancement of Chiller Performance by Water Distribution on the Adiabatic Cooling Pad’s Mesh Surface," Clean Technol., MDPI, vol. 4(3), pages 1-19, July.
  2. Mehmood, Faiza & Ghani, Muhammad Usman & Ghafoor, Hina & Shahzadi, Rehab & Asim, Muhammad Nabeel & Mahmood, Waqar, 2022. "EGD-SNet: A computational search engine for predicting an end-to-end machine learning pipeline for Energy Generation & Demand Forecasting," Applied Energy, Elsevier, vol. 324(C).
  3. Ramos, Paulo Vitor B. & Villela, Saulo Moraes & Silva, Walquiria N. & Dias, Bruno H., 2023. "Residential energy consumption forecasting using deep learning models," Applied Energy, Elsevier, vol. 350(C).
  4. Gang Chen & Qingchang Hu & Jin Wang & Xu Wang & Yuyu Zhu, 2023. "Machine-Learning-Based Electric Power Forecasting," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
  5. Dana-Mihaela Petroșanu & Alexandru Pîrjan, 2020. "Electricity Consumption Forecasting Based on a Bidirectional Long-Short-Term Memory Artificial Neural Network," Sustainability, MDPI, vol. 13(1), pages 1-31, December.
  6. 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.
  7. André Luiz Marques Serrano & Patricia Helena dos Santos Martins & Guilherme Fay Vergara & Guilherme Dantas Bispo & Gabriel Arquelau Pimenta Rodrigues & Letícia Rezende Mosquéra & Matheus Noschang de O, 2025. "Forecasting Ethanol and Gasoline Consumption in Brazil: Advanced Temporal Models for Sustainable Energy Management," Energies, MDPI, vol. 18(6), pages 1-20, March.
  8. José Ignacio García-Lajara & Miguel Ángel Reyes-Belmonte, 2022. "Liquefied Natural Gas and Hydrogen Regasification Terminal Design through Neural Network Estimated Demand for the Canary Islands," Energies, MDPI, vol. 15(22), pages 1-24, November.
  9. Sen, Doruk & Tunç, K.M. Murat & Günay, M. Erdem, 2021. "Forecasting electricity consumption of OECD countries: A global machine learning modeling approach," Utilities Policy, Elsevier, vol. 70(C).
  10. Khadija Sherece Usher & Benjamin Craig McLellan, 2024. "Inherent Risk Analysis of Power Supply Management: Case of Belize’s System Operator and Third-Party Actors," Energies, MDPI, vol. 18(1), pages 1-35, December.
  11. Khondaker Golam Moazzem & Helen Mashiyat Preoty, 2021. "Proposed Power and Energy System Master Plan (PESMP): Perspective on Analytical Frame, Methodology and Influencing Factors on Demand Forecasting," CPD Working Paper 139, Centre for Policy Dialogue (CPD).
  12. Aurélie Halsband, 2022. "Sustainable AI and Intergenerational Justice," Sustainability, MDPI, vol. 14(7), pages 1-11, March.
  13. Arkadiusz Dyjakon & Łukasz Sobol & Mateusz Krotowski & Krzysztof Mudryk & Krzysztof Kawa, 2020. "The Impact of Particles Comminution on Mechanical Durability of Wheat Straw Briquettes," Energies, MDPI, vol. 13(23), pages 1-14, November.
  14. Jasiński, Tomasz, 2022. "A new approach to modeling cycles with summer and winter demand peaks as input variables for deep neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
  15. Dimitrios Kontogiannis & Dimitrios Bargiotas & Aspassia Daskalopulu & Lefteri H. Tsoukalas, 2021. "A Meta-Modeling Power Consumption Forecasting Approach Combining Client Similarity and Causality," Energies, MDPI, vol. 14(19), pages 1-19, September.
  16. Manuel Jaramillo & Diego Carrión, 2022. "An Adaptive Strategy for Medium-Term Electricity Consumption Forecasting for Highly Unpredictable Scenarios: Case Study Quito, Ecuador during the Two First Years of COVID-19," Energies, MDPI, vol. 15(22), pages 1-19, November.
  17. Niraj Buyo & Akbar Sheikh-Akbari & Farrukh Saleem, 2025. "An Ensemble Approach to Predict a Sustainable Energy Plan for London Households," Sustainability, MDPI, vol. 17(2), pages 1-30, January.
  18. Ercan Köse & Sevil Kutlu Kaynar, 2025. "Energy Demand Forecasting and Policy Development in Turkey," Energies, MDPI, vol. 18(13), pages 1-31, June.
  19. Seyed Morteza Moghimi & Thomas Aaron Gulliver & Ilamparithi Thirumarai Chelvan & Hossen Teimoorinia, 2024. "Resource Optimization for Grid-Connected Smart Green Townhouses Using Deep Hybrid Machine Learning," Energies, MDPI, vol. 17(23), pages 1-31, December.
  20. Duong Trung Kien & Phan Dieu Huong & Nguyen Dat Minh, 2023. "Application of Sarima Model in Load Forecasting in Hanoi City," International Journal of Energy Economics and Policy, Econjournals, vol. 13(3), pages 164-170, May.
  21. Kei Hirose & Keigo Wada & Maiya Hori & Rin-ichiro Taniguchi, 2020. "Event Effects Estimation on Electricity Demand Forecasting," Energies, MDPI, vol. 13(21), pages 1-20, November.
  22. Jerzy Rembeza & Grzegorz Przekota, 2022. "Influence of the Industry’s Output on Electricity Prices: Comparison of the Nord Pool and HUPX Markets," Energies, MDPI, vol. 15(16), pages 1-15, August.
  23. Bhandari, Ramchandra & Subedi, Subodh, 2023. "Evaluation of surplus hydroelectricity potential in Nepal until 2040 and its use for hydrogen production via electrolysis," Renewable Energy, Elsevier, vol. 212(C), pages 403-414.
  24. Sen, Doruk & Hamurcuoglu, K. Irem & Ersoy, Melisa Z. & Tunç, K.M. Murat & Günay, M. Erdem, 2023. "Forecasting long-term world annual natural gas production by machine learning," Resources Policy, Elsevier, vol. 80(C).
  25. Yuyang Zhang & Lei Cui & Wenqiang Yan, 2025. "Integrating Kolmogorov–Arnold Networks with Time Series Prediction Framework in Electricity Demand Forecasting," Energies, MDPI, vol. 18(6), pages 1-18, March.
  26. Irene M. Zarco-Soto & Fco. Javier Zarco-Soto & Pedro J. Zarco-Periñán, 2021. "Influence of Population Income on Energy Consumption and CO 2 Emissions in Buildings of Cities," Sustainability, MDPI, vol. 13(18), pages 1-18, September.
  27. Bibi Ibrahim & Luis Rabelo & Edgar Gutierrez-Franco & Nicolas Clavijo-Buritica, 2022. "Machine Learning for Short-Term Load Forecasting in Smart Grids," Energies, MDPI, vol. 15(21), pages 1-19, October.
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