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Electric load forecasting based on deep learning and optimized by heuristic algorithm in smart grid

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  1. Odin Foldvik Eikeland & Filippo Maria Bianchi & Harry Apostoleris & Morten Hansen & Yu-Cheng Chiou & Matteo Chiesa, 2021. "Predicting Energy Demand in Semi-Remote Arctic Locations," Energies, MDPI, vol. 14(4), pages 1-17, February.
  2. Sun, Fangyuan & Kong, Xiangyu & Wu, Jianzhong & Gao, Bixuan & Chen, Ke & Lu, Ning, 2022. "DSM pricing method based on A3C and LSTM under cloud-edge environment," Applied Energy, Elsevier, vol. 315(C).
  3. Seyed Mahdi Miraftabzadeh & Michela Longo & Federica Foiadelli & Marco Pasetti & Raul Igual, 2021. "Advances in the Application of Machine Learning Techniques for Power System Analytics: A Survey," Energies, MDPI, vol. 14(16), pages 1-24, August.
  4. Taimoor Ahmad Khan & Amjad Ullah & Ghulam Hafeez & Imran Khan & Sadia Murawwat & Faheem Ali & Sajjad Ali & Sheraz Khan & Khalid Rehman, 2022. "A Fractional Order Super Twisting Sliding Mode Controller for Energy Management in Smart Microgrid Using Dynamic Pricing Approach," Energies, MDPI, vol. 15(23), pages 1-14, November.
  5. Zhao, Zhenyu & Zhang, Yao & Yang, Yujia & Yuan, Shuguang, 2022. "Load forecasting via Grey Model-Least Squares Support Vector Machine model and spatial-temporal distribution of electric consumption intensity," Energy, Elsevier, vol. 255(C).
  6. Qingyuan Yan & Yang Gao & Ling Xing & Binrui Xu & Yanxue Li & Weili Chen, 2024. "Optimal Scheduling for Increased Satisfaction of Both Electric Vehicle Users and Grid Fast-Charging Stations by SOR&KANO and MVO in PV-Connected Distribution Network," Energies, MDPI, vol. 17(14), pages 1-36, July.
  7. Hu, Yusha & Man, Yi, 2023. "Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
  8. Hafeez, Ghulam & Khan, Imran & Jan, Sadaqat & Shah, Ibrar Ali & Khan, Farrukh Aslam & Derhab, Abdelouahid, 2021. "A novel hybrid load forecasting framework with intelligent feature engineering and optimization algorithm in smart grid," Applied Energy, Elsevier, vol. 299(C).
  9. 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.
  10. Di, Kaisheng & Chen, Weidong & Shi, Qiumei & Cai, Quanling & Liu, Sichen, 2024. "Analysing the impact of coupled domestic demand dynamics of green and low-carbon consumption in the market based on SEM-ANN," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
  11. Li, Peiran & Zhang, Haoran & Wang, Xin & Song, Xuan & Shibasaki, Ryosuke, 2020. "A spatial finer electric load estimation method based on night-light satellite image," Energy, Elsevier, vol. 209(C).
  12. Li, Yiyan & Zhang, Si & Hu, Rongxing & Lu, Ning, 2021. "A meta-learning based distribution system load forecasting model selection framework," Applied Energy, Elsevier, vol. 294(C).
  13. Chuanhui Zuo & Jialong Wang & Mingping Liu & Suhui Deng & Qingnian Wang, 2023. "An Ensemble Framework for Short-Term Load Forecasting Based on TimesNet and TCN," Energies, MDPI, vol. 16(14), pages 1-17, July.
  14. Ghulam Hafeez & Khurram Saleem Alimgeer & Zahid Wadud & Zeeshan Shafiq & Mohammad Usman Ali Khan & Imran Khan & Farrukh Aslam Khan & Abdelouahid Derhab, 2020. "A Novel Accurate and Fast Converging Deep Learning-Based Model for Electrical Energy Consumption Forecasting in a Smart Grid," Energies, MDPI, vol. 13(9), pages 1-25, May.
  15. Fanidhar Dewangan & Almoataz Y. Abdelaziz & Monalisa Biswal, 2023. "Load Forecasting Models in Smart Grid Using Smart Meter Information: A Review," Energies, MDPI, vol. 16(3), pages 1-55, January.
  16. Cui, Jindong & Ran, Zihan & Shen, Wei & Xin, Yechun, 2024. "Study on multi-type flexible load control method of active distribution network based on dynamic time-sharing electricity price," Applied Energy, Elsevier, vol. 357(C).
  17. Hisham Alghamdi & Ghulam Hafeez & Sajjad Ali & Safeer Ullah & Muhammad Iftikhar Khan & Sadia Murawwat & Lyu-Guang Hua, 2023. "An Integrated Model of Deep Learning and Heuristic Algorithm for Load Forecasting in Smart Grid," Mathematics, MDPI, vol. 11(21), pages 1-22, November.
  18. Shi, Jiaqi & Liu, Nian & Huang, Yujing & Ma, Liya, 2022. "An Edge Computing-oriented Net Power Forecasting for PV-assisted Charging Station: Model Complexity and Forecasting Accuracy Trade-off," Applied Energy, Elsevier, vol. 310(C).
  19. 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.
  20. Ullah, Kalim & Hafeez, Ghulam & Khan, Imran & Jan, Sadaqat & Javaid, Nadeem, 2021. "A multi-objective energy optimization in smart grid with high penetration of renewable energy sources," Applied Energy, Elsevier, vol. 299(C).
  21. Filipe Rodrigues & Carlos Cardeira & João M. F. Calado & Rui Melicio, 2023. "Short-Term Load Forecasting of Electricity Demand for the Residential Sector Based on Modelling Techniques: A Systematic Review," Energies, MDPI, vol. 16(10), pages 1-26, May.
  22. Abdelwahed Motwakel & Eatedal Alabdulkreem & Abdulbaset Gaddah & Radwa Marzouk & Nermin M. Salem & Abu Sarwar Zamani & Amgad Atta Abdelmageed & Mohamed I. Eldesouki, 2023. "Wild Horse Optimization with Deep Learning-Driven Short-Term Load Forecasting Scheme for Smart Grids," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
  23. Guo, Yi & Ming, Bo & Huang, Qiang & Wang, Yimin & Zheng, Xudong & Zhang, Wei, 2022. "Risk-averse day-ahead generation scheduling of hydro–wind–photovoltaic complementary systems considering the steady requirement of power delivery," Applied Energy, Elsevier, vol. 309(C).
  24. Houjian Li & Xinya Huang & Deheng Zhou & Andi Cao & Mengying Su & Yufeng Wang & Lili Guo, 2022. "Forecasting Carbon Price in China: A Multimodel Comparison," IJERPH, MDPI, vol. 19(10), pages 1-16, May.
  25. Prasertsak Charoen & Nathavuth Kitbutrawat & Jasada Kudtongngam, 2022. "A Demand Response Implementation with Building Energy Management System," Energies, MDPI, vol. 15(3), pages 1-21, February.
  26. Rosato, Antonello & Panella, Massimo & Andreotti, Amedeo & Mohammed, Osama A. & Araneo, Rodolfo, 2021. "Two-stage dynamic management in energy communities using a decision system based on elastic net regularization," Applied Energy, Elsevier, vol. 291(C).
  27. Guo, Yi & Ming, Bo & Huang, Qiang & Liu, Pan & Wang, Yimin & Fang, Wei & Zhang, Wei, 2022. "Evaluating effects of battery storage on day-ahead generation scheduling of large hydro–wind–photovoltaic complementary systems," Applied Energy, Elsevier, vol. 324(C).
  28. Hu, Yi & Qu, Boyang & Wang, Jie & Liang, Jing & Wang, Yanli & Yu, Kunjie & Li, Yaxin & Qiao, Kangjia, 2021. "Short-term load forecasting using multimodal evolutionary algorithm and random vector functional link network based ensemble learning," Applied Energy, Elsevier, vol. 285(C).
  29. Yin, Linfei & Xie, Jiaxing, 2021. "Multi-temporal-spatial-scale temporal convolution network for short-term load forecasting of power systems," Applied Energy, Elsevier, vol. 283(C).
  30. Eren, Yavuz & Küçükdemiral, İbrahim, 2024. "A comprehensive review on deep learning approaches for short-term load forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
  31. Hany Habbak & Mohamed Mahmoud & Khaled Metwally & Mostafa M. Fouda & Mohamed I. Ibrahem, 2023. "Load Forecasting Techniques and Their Applications in Smart Grids," Energies, MDPI, vol. 16(3), pages 1-33, February.
  32. Xudong Pang & Xiangchen Lu & Hao Ding & Josep M. Guerrero, 2022. "Construction of Smart Grid Load Forecast Model by Edge Computing," Energies, MDPI, vol. 15(9), pages 1-16, April.
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