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State of the Art of Machine Learning Models in Energy Systems, a Systematic Review

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  1. Pirhooshyaran, Mohammad & Scheinberg, Katya & Snyder, Lawrence V., 2020. "Feature engineering and forecasting via derivative-free optimization and ensemble of sequence-to-sequence networks with applications in renewable energy," Energy, Elsevier, vol. 196(C).
  2. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
  3. Thrampoulidis, Emmanouil & Mavromatidis, Georgios & Lucchi, Aurelien & Orehounig, Kristina, 2021. "A machine learning-based surrogate model to approximate optimal building retrofit solutions," Applied Energy, Elsevier, vol. 281(C).
  4. Rabia Tehseen & Muhammad Shoaib Farooq & Adnan Abid, 2020. "Earthquake Prediction Using Expert Systems: A Systematic Mapping Study," Sustainability, MDPI, vol. 12(6), pages 1-32, March.
  5. Shahaboddin Shamshirband & Masoud Hadipoor & Alireza Baghban & Amir Mosavi & Jozsef Bukor & Annamária R. Várkonyi-Kóczy, 2019. "Developing an ANFIS-PSO Model to Predict Mercury Emissions in Combustion Flue Gases," Mathematics, MDPI, vol. 7(10), pages 1-16, October.
  6. Alessandro Bosisio & Matteo Moncecchi & Andrea Morotti & Marco Merlo, 2021. "Machine Learning and GIS Approach for Electrical Load Assessment to Increase Distribution Networks Resilience," Energies, MDPI, vol. 14(14), pages 1-23, July.
  7. Sabarathinam Srinivasan & Suresh Kumarasamy & Zacharias E. Andreadakis & Pedro G. Lind, 2023. "Artificial Intelligence and Mathematical Models of Power Grids Driven by Renewable Energy Sources: A Survey," Energies, MDPI, vol. 16(14), pages 1-56, July.
  8. Sina Ardabili & Amir Mosavi & Asghar Mahmoudi & Tarahom Mesri Gundoshmian & Saeed Nosratabadi & Annamaria R. Varkonyi-Koczy, 2020. "Modelling Temperature Variation of Mushroom Growing Hall Using Artificial Neural Networks," Papers 2010.02673, arXiv.org.
  9. Isaac Kofi Nti & Adebayo Felix Adekoya & Benjamin Asubam Weyori & Owusu Nyarko-Boateng, 2022. "Applications of artificial intelligence in engineering and manufacturing: a systematic review," Journal of Intelligent Manufacturing, Springer, vol. 33(6), pages 1581-1601, August.
  10. Yukta Mehta & Rui Xu & Benjamin Lim & Jane Wu & Jerry Gao, 2023. "A Review for Green Energy Machine Learning and AI Services," Energies, MDPI, vol. 16(15), pages 1-30, July.
  11. Dania Ortiz & Vera Migueis & Vitor Leal & Janelle Knox-Hayes & Jungwoo Chun, 2022. "Analysis of Renewable Energy Policies through Decision Trees," Sustainability, MDPI, vol. 14(13), pages 1-31, June.
  12. Susie Ruqun WU & Gabriela Shirkey & Ilke Celik & Changliang Shao & Jiquan Chen, 2022. "A Review on the Adoption of AI, BC, and IoT in Sustainability Research," Sustainability, MDPI, vol. 14(13), pages 1-25, June.
  13. Kusumoto, Yoshiki & Delage, Rémi & Nakata, Toshihiko, 2024. "Machine learning application for estimating electricity demand by municipality," Energy, Elsevier, vol. 296(C).
  14. Simon Wenninger & Christian Wiethe, 2021. "Benchmarking Energy Quantification Methods to Predict Heating Energy Performance of Residential Buildings in Germany," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(3), pages 223-242, June.
  15. González Grandón, T. & Schwenzer, J. & Steens, T. & Breuing, J., 2024. "Electricity demand forecasting with hybrid classical statistical and machine learning algorithms: Case study of Ukraine," Applied Energy, Elsevier, vol. 355(C).
  16. Guijo-Rubio, D. & Durán-Rosal, A.M. & Gutiérrez, P.A. & Gómez-Orellana, A.M. & Casanova-Mateo, C. & Sanz-Justo, J. & Salcedo-Sanz, S. & Hervás-Martínez, C., 2020. "Evolutionary artificial neural networks for accurate solar radiation prediction," Energy, Elsevier, vol. 210(C).
  17. Hubert Szczepaniuk & Edyta Karolina Szczepaniuk, 2022. "Applications of Artificial Intelligence Algorithms in the Energy Sector," Energies, MDPI, vol. 16(1), pages 1-24, December.
  18. Md Mijanur Rahman & Mohammad Shakeri & Sieh Kiong Tiong & Fatema Khatun & Nowshad Amin & Jagadeesh Pasupuleti & Mohammad Kamrul Hasan, 2021. "Prospective Methodologies in Hybrid Renewable Energy Systems for Energy Prediction Using Artificial Neural Networks," Sustainability, MDPI, vol. 13(4), pages 1-28, February.
  19. Li, Chen & Kies, Alexander & Zhou, Kai & Schlott, Markus & Sayed, Omar El & Bilousova, Mariia & Stöcker, Horst, 2024. "Optimal Power Flow in a highly renewable power system based on attention neural networks," Applied Energy, Elsevier, vol. 359(C).
  20. Takuji Matsumoto & Yuji Yamada, 2021. "Comprehensive and Comparative Analysis of GAM-Based PV Power Forecasting Models Using Multidimensional Tensor Product Splines against Machine Learning Techniques," Energies, MDPI, vol. 14(21), pages 1-22, November.
  21. Hao Wang & Chen Peng & Bolin Liao & Xinwei Cao & Shuai Li, 2023. "Wind Power Forecasting Based on WaveNet and Multitask Learning," Sustainability, MDPI, vol. 15(14), pages 1-22, July.
  22. Saima Akhtar & Sulman Shahzad & Asad Zaheer & Hafiz Sami Ullah & Heybet Kilic & Radomir Gono & Michał Jasiński & Zbigniew Leonowicz, 2023. "Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead," Energies, MDPI, vol. 16(10), pages 1-29, May.
  23. Oliveira Santos, Victor & Costa Rocha, Paulo Alexandre & Scott, John & Van Griensven Thé, Jesse & Gharabaghi, Bahram, 2023. "Spatiotemporal analysis of bidimensional wind speed forecasting: Development and thorough assessment of LSTM and ensemble graph neural networks on the Dutch database," Energy, Elsevier, vol. 278(PA).
  24. Zahra Jahangiri & Mackenzie Judson & Kwang Moo Yi & Madeleine McPherson, 2023. "A Deep Learning Approach for Exploring the Design Space for the Decarbonization of the Canadian Electricity System," Energies, MDPI, vol. 16(3), pages 1-21, January.
  25. Rémi Delage & Toshihiko Nakata, 2022. "Multivariate Empirical Mode Decomposition and Recurrence Quantification for the Multiscale, Spatiotemporal Analysis of Electricity Demand—A Case Study of Japan," Energies, MDPI, vol. 15(17), pages 1-17, August.
  26. Brahmana, Rayenda Khresna, 2022. "Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?," MPRA Paper 119598, University Library of Munich, Germany.
  27. Pierdicca, Roberto & Balestra, Mattia & Micheletti, Giulia & Felicetti, Andrea & Toscano, Giuseppe, 2022. "Semi-automatic detection and segmentation of wooden pellet size exploiting a deep learning approach," Renewable Energy, Elsevier, vol. 197(C), pages 406-416.
  28. Lily Popova Zhuhadar & Miltiadis D. Lytras, 2023. "The Application of AutoML Techniques in Diabetes Diagnosis: Current Approaches, Performance, and Future Directions," Sustainability, MDPI, vol. 15(18), pages 1-24, September.
  29. Tayeb Brahimi, 2019. "Using Artificial Intelligence to Predict Wind Speed for Energy Application in Saudi Arabia," Energies, MDPI, vol. 12(24), pages 1-16, December.
  30. Duberney Murillo-Yarce & José Alarcón-Alarcón & Marco Rivera & Carlos Restrepo & Javier Muñoz & Carlos Baier & Patrick Wheeler, 2020. "A Review of Control Techniques in Photovoltaic Systems," Sustainability, MDPI, vol. 12(24), pages 1-21, December.
  31. Aya Amer & Khaled Shaban & Ahmed Massoud, 2022. "Demand Response in HEMSs Using DRL and the Impact of Its Various Configurations and Environmental Changes," Energies, MDPI, vol. 15(21), pages 1-20, November.
  32. Vasallo, Manuel Jesús & Cojocaru, Emilian Gelu & Gegúndez, Manuel Emilio & Marín, Diego, 2021. "Application of data-based solar field models to optimal generation scheduling in concentrating solar power plants," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 1130-1149.
  33. Alvaro Furlani Bastos & Surya Santoso, 2021. "Optimization Techniques for Mining Power Quality Data and Processing Unbalanced Datasets in Machine Learning Applications," Energies, MDPI, vol. 14(2), pages 1-21, January.
  34. Carlos Ruiz & Carlos M. Alaíz & José R. Dorronsoro, 2020. "Multitask Support Vector Regression for Solar and Wind Energy Prediction," Energies, MDPI, vol. 13(23), pages 1-21, November.
  35. Aslam, Sheraz & Herodotou, Herodotos & Mohsin, Syed Muhammad & Javaid, Nadeem & Ashraf, Nouman & Aslam, Shahzad, 2021. "A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
  36. Ascher, Simon & Watson, Ian & You, Siming, 2022. "Machine learning methods for modelling the gasification and pyrolysis of biomass and waste," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
  37. Tseng, Fang-Mei & Palma Gil, Eunice Ina N. & Lu, Louis Y.Y., 2021. "Developmental trajectories of blockchain research and its major subfields," Technology in Society, Elsevier, vol. 66(C).
  38. Nailya Maitanova & Jan-Simon Telle & Benedikt Hanke & Matthias Grottke & Thomas Schmidt & Karsten von Maydell & Carsten Agert, 2020. "A Machine Learning Approach to Low-Cost Photovoltaic Power Prediction Based on Publicly Available Weather Reports," Energies, MDPI, vol. 13(3), pages 1-23, February.
  39. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
  40. Saeed Nosratabadi & Amir Mosavi & Ramin Keivani & Sina Ardabili & Farshid Aram, 2020. "State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability," Papers 2010.02670, arXiv.org.
  41. Dimitrios K. Panagiotou & Anastasios I. Dounis, 2022. "Comparison of Hospital Building’s Energy Consumption Prediction Using Artificial Neural Networks, ANFIS, and LSTM Network," Energies, MDPI, vol. 15(17), pages 1-25, September.
  42. Wenninger, Simon & Kaymakci, Can & Wiethe, Christian, 2022. "Explainable long-term building energy consumption prediction using QLattice," Applied Energy, Elsevier, vol. 308(C).
  43. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
  44. Yannik Hahn & Tristan Langer & Richard Meyes & Tobias Meisen, 2023. "Time Series Dataset Survey for Forecasting with Deep Learning," Forecasting, MDPI, vol. 5(1), pages 1-21, March.
  45. Claudia Condemi & Loretta Mastroeni & Pierluigi Vellucci, 2021. "The impact of Clean Spark Spread expectations on storage hydropower generation," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1111-1146, December.
  46. Zini, Marco & Carcasci, Carlo, 2023. "Machine learning-based monitoring method for the electricity consumption of a healthcare facility in Italy," Energy, Elsevier, vol. 262(PB).
  47. Maciej Klimas & Dariusz Grabowski & Dawid Buła, 2021. "Application of Decision Trees for Optimal Allocation of Harmonic Filters in Medium-Voltage Networks," Energies, MDPI, vol. 14(4), pages 1-24, February.
  48. Robert Basmadjian & Amirhossein Shaafieyoun, 2023. "Assessing ARIMA-Based Forecasts for the Percentage of Renewables in Germany: Insights and Lessons for the Future," Energies, MDPI, vol. 16(16), pages 1-19, August.
  49. Lilia Tightiz & Joon Yoo, 2022. "A Review on a Data-Driven Microgrid Management System Integrating an Active Distribution Network: Challenges, Issues, and New Trends," Energies, MDPI, vol. 15(22), pages 1-24, November.
  50. Izanloo, Milad & Aslani, Alireza & Zahedi, Rahim, 2022. "Development of a Machine learning assessment method for renewable energy investment decision making," Applied Energy, Elsevier, vol. 327(C).
  51. Leonardo Brain García Fernández & Anna Diva Plasencia Lotufo & Carlos Roberto Minussi, 2023. "Development of a Short-Term Electrical Load Forecasting in Disaggregated Levels Using a Hybrid Modified Fuzzy-ARTMAP Strategy," Energies, MDPI, vol. 16(10), pages 1-30, May.
  52. Balderrama, Sergio & Lombardi, Francesco & Stevanato, Nicolo & Peña, Gabriela & Colombo, Emanuela & Quoilin, Sylvain, 2021. "Surrogate models for rural energy planning: Application to Bolivian lowlands isolated communities," Energy, Elsevier, vol. 232(C).
  53. Wolfram Rozas & Rafael Pastor-Vargas & Angel Miguel García-Vico & José Carpio, 2023. "Consumption–Production Profile Categorization in Energy Communities," Energies, MDPI, vol. 16(19), pages 1-27, October.
  54. Nebiyu Kedir & Phuong H. D. Nguyen & Citlaly Pérez & Pedro Ponce & Aminah Robinson Fayek, 2023. "Systematic Literature Review on Fuzzy Hybrid Methods in Photovoltaic Solar Energy: Opportunities, Challenges, and Guidance for Implementation," Energies, MDPI, vol. 16(9), pages 1-38, April.
  55. Dimitrios Vamvakas & Panagiotis Michailidis & Christos Korkas & Elias Kosmatopoulos, 2023. "Review and Evaluation of Reinforcement Learning Frameworks on Smart Grid Applications," Energies, MDPI, vol. 16(14), pages 1-38, July.
  56. Julián Ascencio-Vásquez & Jakob Bevc & Kristjan Reba & Kristijan Brecl & Marko Jankovec & Marko Topič, 2020. "Advanced PV Performance Modelling Based on Different Levels of Irradiance Data Accuracy," Energies, MDPI, vol. 13(9), pages 1-12, May.
  57. Justyna Światowiec-Szczepańska & Beata Stępień, 2022. "Drivers of Digitalization in the Energy Sector—The Managerial Perspective from the Catching Up Economy," Energies, MDPI, vol. 15(4), pages 1-25, February.
  58. 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.
  59. López, Germánico & Arboleya, Pablo, 2022. "Short-term wind speed forecasting over complex terrain using linear regression models and multivariable LSTM and NARX networks in the Andes Mountains, Ecuador," Renewable Energy, Elsevier, vol. 183(C), pages 351-368.
  60. Jose Cruz & Christian Romero & Oscar Vera & Saul Huaquipaco & Norman Beltran & Wilson Mamani, 2023. "Multiparameter Regression of a Photovoltaic System by Applying Hybrid Methods with Variable Selection and Stacking Ensembles under Extreme Conditions of Altitudes Higher than 3800 Meters above Sea Lev," Energies, MDPI, vol. 16(12), pages 1-21, June.
  61. Naveed, Muhammad Hamza & Khan, Muhammad Nouman Aslam & Mukarram, Muhammad & Naqvi, Salman Raza & Abdullah, Abdullah & Haq, Zeeshan Ul & Ullah, Hafeez & Mohamadi, Hamad Al, 2024. "Cellulosic biomass fermentation for biofuel production: Review of artificial intelligence approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
  62. Ajith Gopi & Prabhakar Sharma & Kumarasamy Sudhakar & Wai Keng Ngui & Irina Kirpichnikova & Erdem Cuce, 2022. "Weather Impact on Solar Farm Performance: A Comparative Analysis of Machine Learning Techniques," Sustainability, MDPI, vol. 15(1), pages 1-28, December.
  63. Merel Noorman & Brenda Espinosa Apráez & Saskia Lavrijssen, 2023. "AI and Energy Justice," Energies, MDPI, vol. 16(5), pages 1-16, February.
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