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A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea

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Cited by:

  1. Ivan Trifonov & Dmitry Trukhan & Yury Koshlich & Valeriy Prasolov & Beata Ślusarczyk, 2021. "Influence of the Share of Renewable Energy Sources on the Level of Energy Security in EECCA Countries," Energies, MDPI, vol. 14(4), pages 1-15, February.
  2. He, Xinbo & Wang, Yong & Zhang, Yuyang & Ma, Xin & Wu, Wenqing & Zhang, Lei, 2022. "A novel structure adaptive new information priority discrete grey prediction model and its application in renewable energy generation forecasting," Applied Energy, Elsevier, vol. 325(C).
  3. Ryoo, Seung Gul & Jung, Han Sol & Kim, MinJae & Kang, Yong Tae, 2021. "Bridge to zero-emission: Life cycle assessment of CO2–methanol conversion process and energy optimization," Energy, Elsevier, vol. 229(C).
  4. Ifaei, Pouya & Tayerani Charmchi, Amir Saman & Loy-Benitez, Jorge & Yang, Rebecca Jing & Yoo, ChangKyoo, 2022. "A data-driven analytical roadmap to a sustainable 2030 in South Korea based on optimal renewable microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  5. Li, Jingmiao & Wang, Jun, 2020. "Forcasting of energy futures market and synchronization based on stochastic gated recurrent unit model," Energy, Elsevier, vol. 213(C).
  6. Shangli Zhou & Hengjing He & Leping Zhang & Wei Zhao & Fei Wang, 2023. "A Data-Driven Method to Monitor Carbon Dioxide Emissions of Coal-Fired Power Plants," Energies, MDPI, vol. 16(4), pages 1-27, February.
  7. Chengcheng Gu & Hua Li, 2022. "Review on Deep Learning Research and Applications in Wind and Wave Energy," Energies, MDPI, vol. 15(4), pages 1-19, February.
  8. 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.
  9. Nam, KiJeon & Heo, SungKu & Li, Qian & Loy-Benitez, Jorge & Kim, MinJeong & Park, DuckShin & Yoo, ChangKyoo, 2020. "A proactive energy-efficient optimal ventilation system using artificial intelligent techniques under outdoor air quality conditions," Applied Energy, Elsevier, vol. 266(C).
  10. Lim, Juin Yau & Safder, Usman & How, Bing Shen & Ifaei, Pouya & Yoo, Chang Kyoo, 2021. "Nationwide sustainable renewable energy and Power-to-X deployment planning in South Korea assisted with forecasting model," Applied Energy, Elsevier, vol. 283(C).
  11. Bortoluzzi, Mirian & Correia de Souza, Celso & Furlan, Marcelo, 2021. "Bibliometric analysis of renewable energy types using key performance indicators and multicriteria decision models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
  12. Gennadiy Stroykov & Alexey Y. Cherepovitsyn & Elizaveta A. Iamshchikova, 2020. "Powering Multiple Gas Condensate Wells in Russia’s Arctic: Power Supply Systems Based on Renewable Energy Sources," Resources, MDPI, vol. 9(11), pages 1-15, November.
  13. 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).
  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. Khan, Zulfiqar Ahmad & Hussain, Tanveer & Baik, Sung Wook, 2023. "Dual stream network with attention mechanism for photovoltaic power forecasting," Applied Energy, Elsevier, vol. 338(C).
  16. Hwangbo, Soonho & Heo, SungKu & Yoo, ChangKyoo, 2022. "Development of deterministic-stochastic model to integrate variable renewable energy-driven electricity and large-scale utility networks: Towards decarbonization petrochemical industry," Energy, Elsevier, vol. 238(PC).
  17. 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.
  18. Juan Manuel González Sopeña & Vikram Pakrashi & Bidisha Ghosh, 2022. "A Spiking Neural Network Based Wind Power Forecasting Model for Neuromorphic Devices," Energies, MDPI, vol. 15(19), pages 1-24, October.
  19. Kim, SangYoun & Heo, SungKu & Nam, KiJeon & Woo, TaeYong & Yoo, ChangKyoo, 2023. "Flexible renewable energy planning based on multi-step forecasting of interregional electricity supply and demand: Graph-enhanced AI approach," Energy, Elsevier, vol. 282(C).
  20. Zixia Yuan & Guojiang Xiong & Xiaofan Fu, 2022. "Artificial Neural Network for Fault Diagnosis of Solar Photovoltaic Systems: A Survey," Energies, MDPI, vol. 15(22), pages 1-18, November.
  21. Qin, Yuxiao & Liu, Pei & Li, Zheng, 2024. "Enhancing accuracy of flexibility characterization in integrated energy system design: A variable temporal resolution optimization method," Energy, Elsevier, vol. 288(C).
  22. Yugang He, 2024. "Evaluating Environmental Sustainability: The Role of Agriculture and Renewable Energy in South Korea," Agriculture, MDPI, vol. 14(9), pages 1-18, September.
  23. Zhengwei Huang & Jin Huang & Jintao Min, 2022. "SSA-LSTM: Short-Term Photovoltaic Power Prediction Based on Feature Matching," Energies, MDPI, vol. 15(20), pages 1-16, October.
  24. 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.
  25. Norouzi, Mohammadali & Aghaei, Jamshid & Niknam, Taher & Alipour, Mohammadali & Pirouzi, Sasan & Lehtonen, Matti, 2023. "Risk-averse and flexi-intelligent scheduling of microgrids based on hybrid Boltzmann machines and cascade neural network forecasting," Applied Energy, Elsevier, vol. 348(C).
  26. Joseph Akpan & Oludolapo Olanrewaju, 2023. "Towards a Common Methodology and Modelling Tool for 100% Renewable Energy Analysis: A Review," Energies, MDPI, vol. 16(18), pages 1-42, September.
  27. Aisha Blfgeh & Hanadi Alkhudhayr, 2024. "A Machine Learning-Based Sustainable Energy Management of Wind Farms Using Bayesian Recurrent Neural Network," Sustainability, MDPI, vol. 16(19), pages 1-21, September.
  28. Yuan-Kang Wu & Cheng-Liang Huang & Quoc-Thang Phan & Yuan-Yao Li, 2022. "Completed Review of Various Solar Power Forecasting Techniques Considering Different Viewpoints," Energies, MDPI, vol. 15(9), pages 1-22, May.
  29. Wang, Gaosheng & Song, Xianzhi & Yu, Chao & Shi, Yu & Song, Guofeng & Xu, Fuqiang & Ji, Jiayan & Song, Zihao, 2022. "Heat extraction study of a novel hydrothermal open-loop geothermal system in a multi-lateral horizontal well," Energy, Elsevier, vol. 242(C).
  30. Qin, Yuxiao & Liu, Pei & Li, Zheng, 2022. "Multi-timescale hierarchical scheduling of an integrated energy system considering system inertia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
  31. Khan, Zulfiqar Ahmad & Khan, Shabbir Ahmad & Hussain, Tanveer & Baik, Sung Wook, 2024. "DSPM: Dual sequence prediction model for efficient energy management in micro-grid," Applied Energy, Elsevier, vol. 356(C).
  32. Yao Li & Yugang He, 2024. "Unraveling Korea’s Energy Challenge: The Consequences of Carbon Dioxide Emissions and Energy Use on Economic Sustainability," Sustainability, MDPI, vol. 16(5), pages 1-29, March.
  33. Ahmad, Tanveer & Zhang, Hongcai, 2020. "Novel deep supervised ML models with feature selection approach for large-scale utilities and buildings short and medium-term load requirement forecasts," Energy, Elsevier, vol. 209(C).
  34. Noman Khan & Fath U Min Ullah & Ijaz Ul Haq & Samee Ullah Khan & Mi Young Lee & Sung Wook Baik, 2021. "AB-Net: A Novel Deep Learning Assisted Framework for Renewable Energy Generation Forecasting," Mathematics, MDPI, vol. 9(19), pages 1-18, October.
  35. Bossink, Bart, 2020. "Learning strategies in sustainable energy demonstration projects: What organizations learn from sustainable energy demonstrations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
  36. Rita Teixeira & Adelaide Cerveira & Eduardo J. Solteiro Pires & José Baptista, 2024. "Advancing Renewable Energy Forecasting: A Comprehensive Review of Renewable Energy Forecasting Methods," Energies, MDPI, vol. 17(14), pages 1-30, July.
  37. Xiaoyan Peng & Xin Guan & Yanzhao Zeng & Jiali Zhang, 2024. "Artificial Intelligence-Driven Multi-Energy Optimization: Promoting Green Transition of Rural Energy Planning and Sustainable Energy Economy," Sustainability, MDPI, vol. 16(10), pages 1-20, May.
  38. Lee, Seonho & Kim, Jiwon & Byun, Jaewon & Joo, Junghee & Lee, Yoonjae & Kim, Taehyun & Hwangbo, Soonho & Han, Jeehoon & Kim, Sung-Kon & Lee, Jechan, 2023. "Environmentally-viable utilization of chicken litter as energy recovery and electrode production: A machine learning approach," Applied Energy, Elsevier, vol. 350(C).
  39. Gustavo G. Koch & Caio R. D. Osório & Ricardo C. L. F. Oliveira & Vinícius F. Montagner, 2023. "Robust Control Based on Observed States Designed by Means of Linear Matrix Inequalities for Grid-Connected Converters," Energies, MDPI, vol. 16(4), pages 1-24, February.
  40. Ding, Song & Li, Ruojin & Wu, Shu & Zhou, Weijie, 2021. "Application of a novel structure-adaptative grey model with adjustable time power item for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 298(C).
  41. Zhang, Nan & Hwang, Bon-Gang & Lu, Yujie & Ngo, Jasmine, 2022. "A Behavior theory integrated ANN analytical approach for understanding households adoption decisions of residential photovoltaic (RPV) system," Technology in Society, Elsevier, vol. 70(C).
  42. Lee, Yoonjae & Ha, Byeongmin & Hwangbo, Soonho, 2022. "Generative model-based hybrid forecasting model for renewable electricity supply using long short-term memory networks: A case study of South Korea's energy transition policy," Renewable Energy, Elsevier, vol. 200(C), pages 69-87.
  43. Wang, Qiang & Li, Shuyu & Zhang, Min & Li, Rongrong, 2022. "Impact of COVID-19 pandemic on oil consumption in the United States: A new estimation approach," Energy, Elsevier, vol. 239(PC).
  44. Ifaei, Pouya & Nazari-Heris, Morteza & Tayerani Charmchi, Amir Saman & Asadi, Somayeh & Yoo, ChangKyoo, 2023. "Sustainable energies and machine learning: An organized review of recent applications and challenges," Energy, Elsevier, vol. 266(C).
  45. 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.
  46. Gema Hernández-Moral & Sofía Mulero-Palencia & Víctor Iván Serna-González & Carla Rodríguez-Alonso & Roberto Sanz-Jimeno & Vangelis Marinakis & Nikos Dimitropoulos & Zoi Mylona & Daniele Antonucci & H, 2021. "Big Data Value Chain: Multiple Perspectives for the Built Environment," Energies, MDPI, vol. 14(15), pages 1-21, July.
  47. Yugang He, 2022. "Investigating the Routes toward Environmental Sustainability: Fresh Insights from Korea," Sustainability, MDPI, vol. 15(1), pages 1-17, December.
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