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A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids

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  1. Sajjad Khan & Shahzad Aslam & Iqra Mustafa & Sheraz Aslam, 2021. "Short-Term Electricity Price Forecasting by Employing Ensemble Empirical Mode Decomposition and Extreme Learning Machine," Forecasting, MDPI, vol. 3(3), pages 1-18, June.
  2. Zi-Xuan Yu & Meng-Shi Li & Yi-Peng Xu & Sheraz Aslam & Yuan-Kang Li, 2021. "Techno-Economic Planning and Operation of the Microgrid Considering Real-Time Pricing Demand Response Program," Energies, MDPI, vol. 14(15), pages 1-28, July.
  3. 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.
  4. Bo Hu & Jian Xu & Zuoxia Xing & Pengfei Zhang & Jia Cui & Jinglu Liu, 2022. "Short-Term Combined Forecasting Method of Park Load Based on CEEMD-MLR-LSSVR-SBO," Energies, MDPI, vol. 15(8), pages 1-14, April.
  5. Kaleem Ullah & Abdul Basit & Zahid Ullah & Rafiq Asghar & Sheraz Aslam & Ayman Yafoz, 2022. "Line Overload Alleviations in Wind Energy Integrated Power Systems Using Automatic Generation Control," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
  6. Li, Tianyu & Gao, Ciwei & Chen, Tao & Jiang, Yu & Feng, Yingchun, 2022. "Medium and long-term electricity market trading strategy considering renewable portfolio standard in the transitional period of electricity market reform in Jiangsu, China," Energy Economics, Elsevier, vol. 107(C).
  7. Qin, Meng & Hu, Wei & Qi, Xinzhou & Chang, Tsangyao, 2024. "Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy," Energy Economics, Elsevier, vol. 131(C).
  8. Sana Qaiyum & Martin Margala & Pravin R. Kshirsagar & Prasun Chakrabarti & Kashif Irshad, 2023. "Energy Performance Analysis of Photovoltaic Integrated with Microgrid Data Analysis Using Deep Learning Feature Selection and Classification Techniques," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
  9. Arafat, M.Y. & Hossain, M.J. & Alam, Md Morshed, 2024. "Machine learning scopes on microgrid predictive maintenance: Potential frameworks, challenges, and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
  10. Herodotos Herodotou & Sheraz Aslam, 2022. "Data-Intensive Computing in Smart Microgrids: Volume II," Energies, MDPI, vol. 15(16), pages 1-2, August.
  11. Hernández, José L. & de Miguel, Ignacio & Vélez, Fredy & Vasallo, Ali, 2024. "Challenges and opportunities in European smart buildings energy management: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
  12. 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.
  13. Paulescu, Marius & Stefu, Nicoleta & Dughir, Ciprian & Sabadus, Andreea & Calinoiu, Delia & Badescu, Viorel, 2022. "A simple but accurate two-state model for nowcasting PV power," Renewable Energy, Elsevier, vol. 195(C), pages 322-330.
  14. Xie, Haonan & Ahmad, Tanveer & Zhang, Dongdong & Goh, Hui Hwang & Wu, Thomas, 2024. "Community-based virtual power plants’ technology and circular economy models in the energy sector: A Techno-economy study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
  15. Xu, Gaoyuan & Shi, Jian & Wu, Jiaman & Lu, Chenbei & Wu, Chenye & Wang, Dan & Han, Zhu, 2024. "An optimal solutions-guided deep reinforcement learning approach for online energy storage control," Applied Energy, Elsevier, vol. 361(C).
  16. Fahad R. Albogamy & Ghulam Hafeez & Imran Khan & Sheraz Khan & Hend I. Alkhammash & Faheem Ali & Gul Rukh, 2021. "Efficient Energy Optimization Day-Ahead Energy Forecasting in Smart Grid Considering Demand Response and Microgrids," Sustainability, MDPI, vol. 13(20), pages 1-29, October.
  17. Kalim Ullah & Quanyuan Jiang & Guangchao Geng & Sahar Rahim & Rehan Ali Khan, 2022. "Optimal Power Sharing in Microgrids Using the Artificial Bee Colony Algorithm," Energies, MDPI, vol. 15(3), pages 1-22, January.
  18. Sheeraz Ahmed & Zahoor Ali Khan & Syed Muhammad Mohsin & Shahid Latif & Sheraz Aslam & Hana Mujlid & Muhammad Adil & Zeeshan Najam, 2023. "Effective and Efficient DDoS Attack Detection Using Deep Learning Algorithm, Multi-Layer Perceptron," Future Internet, MDPI, vol. 15(2), pages 1-24, February.
  19. Seyfi, Mohammad & Mehdinejad, Mehdi & Mohammadi-Ivatloo, Behnam & Shayanfar, Heidarali, 2022. "Deep learning-based scheduling of virtual energy hubs with plug-in hybrid compressed natural gas-electric vehicles," Applied Energy, Elsevier, vol. 321(C).
  20. Adam Krechowicz & Maria Krechowicz & Katarzyna Poczeta, 2022. "Machine Learning Approaches to Predict Electricity Production from Renewable Energy Sources," Energies, MDPI, vol. 15(23), pages 1-41, December.
  21. Fachrizal Aksan & Vishnu Suresh & Przemysław Janik & Tomasz Sikorski, 2023. "Load Forecasting for the Laser Metal Processing Industry Using VMD and Hybrid Deep Learning Models," Energies, MDPI, vol. 16(14), pages 1-24, July.
  22. van Zyl, Corne & Ye, Xianming & Naidoo, Raj, 2024. "Harnessing eXplainable artificial intelligence for feature selection in time series energy forecasting: A comparative analysis of Grad-CAM and SHAP," Applied Energy, Elsevier, vol. 353(PA).
  23. Shahzad Aslam & Nasir Ayub & Umer Farooq & Muhammad Junaid Alvi & Fahad R. Albogamy & Gul Rukh & Syed Irtaza Haider & Ahmad Taher Azar & Rasool Bukhsh, 2021. "Towards Electric Price and Load Forecasting Using CNN-Based Ensembler in Smart Grid," Sustainability, MDPI, vol. 13(22), pages 1-28, November.
  24. Zhu, Junpeng & Huang, Yong & Lu, Shuai & Shen, Mengya & Yuan, Yue, 2024. "Incorporating local uncertainty management into distribution system planning: An adaptive robust optimization approach," Applied Energy, Elsevier, vol. 363(C).
  25. 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.
  26. Thamer Alquthami & Ahmad H. Milyani & Muhammad Awais & Muhammad B. Rasheed, 2021. "An Incentive Based Dynamic Pricing in Smart Grid: A Customer’s Perspective," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
  27. Igogo, Tsisilile & Awuah-Offei, Kwame & Newman, Alexandra & Lowder, Travis & Engel-Cox, Jill, 2021. "Integrating renewable energy into mining operations: Opportunities, challenges, and enabling approaches," Applied Energy, Elsevier, vol. 300(C).
  28. Lin, Qingcheng & Cai, Huiling & Liu, Hanwei & Li, Xuefeng & Xiao, Hui, 2024. "A novel ultra-short-term wind power prediction model jointly driven by multiple algorithm optimization and adaptive selection," Energy, Elsevier, vol. 288(C).
  29. Gomez, William & Wang, Fu-Kwun & Lo, Shih-Che, 2024. "A hybrid approach based machine learning models in electricity markets," Energy, Elsevier, vol. 289(C).
  30. 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.
  31. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
  32. Muhammad Asgher Nadeem & Scott Uk-Jin Lee & Muhammad Usman Younus, 2022. "A Comparison of Recent Requirements Gathering and Management Tools in Requirements Engineering for IoT-Enabled Sustainable Cities," Sustainability, MDPI, vol. 14(4), pages 1-18, February.
  33. Serrano-Arévalo, Tania Itzel & López-Flores, Francisco Javier & Raya-Tapia, Alma Yunuen & Ramírez-Márquez, César & Ponce-Ortega, José María, 2023. "Optimal expansion for a clean power sector transition in Mexico based on predicted electricity demand using deep learning scheme," Applied Energy, Elsevier, vol. 348(C).
  34. Syed Muhammad Mohsin & Tahir Maqsood & Sajjad Ahmed Madani, 2022. "Solar and Wind Energy Forecasting for Green and Intelligent Migration of Traditional Energy Sources," Sustainability, MDPI, vol. 14(23), pages 1-20, December.
  35. Suqi Zhang & Ningjing Zhang & Ziqi Zhang & Ying Chen, 2022. "Electric Power Load Forecasting Method Based on a Support Vector Machine Optimized by the Improved Seagull Optimization Algorithm," Energies, MDPI, vol. 15(23), pages 1-17, December.
  36. Sandelic, Monika & Peyghami, Saeed & Sangwongwanich, Ariya & Blaabjerg, Frede, 2022. "Reliability aspects in microgrid design and planning: Status and power electronics-induced challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
  37. Khan, Waqas & Liao, Juo Yu & Walker, Shalika & Zeiler, Wim, 2022. "Impact assessment of varied data granularities from commercial buildings on exploration and learning mechanism," Applied Energy, Elsevier, vol. 319(C).
  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. Zheng, Jianqin & Du, Jian & Wang, Bohong & Klemeš, Jiří Jaromír & Liao, Qi & Liang, Yongtu, 2023. "A hybrid framework for forecasting power generation of multiple renewable energy sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 172(C).
  40. Bo Gu & Xi Li & Fengliang Xu & Xiaopeng Yang & Fayi Wang & Pengzhan Wang, 2023. "Forecasting and Uncertainty Analysis of Day-Ahead Photovoltaic Power Based on WT-CNN-BiLSTM-AM-GMM," Sustainability, MDPI, vol. 15(8), pages 1-27, April.
  41. 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.
  42. Nasir Ayub & Usman Ali & Kainat Mustafa & Syed Muhammad Mohsin & Sheraz Aslam, 2022. "Predictive Data Analytics for Electricity Fraud Detection Using Tuned CNN Ensembler in Smart Grid," Forecasting, MDPI, vol. 4(4), pages 1-13, November.
  43. Nan Shao & Yu Chen, 2022. "Abnormal Data Detection and Identification Method of Distribution Internet of Things Monitoring Terminal Based on Spatiotemporal Correlation," Energies, MDPI, vol. 15(6), pages 1-19, March.
  44. 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.
  45. Ullah, Asad & Zhang, Qingyu & Raza, Syed Ali & Ali, Sajid, 2021. "Renewable energy: Is it a global challenge or opportunity? Focusing on different income level countries through Panel Smooth Transition Regression Model," Renewable Energy, Elsevier, vol. 177(C), pages 689-699.
  46. Tingting Hou & Rengcun Fang & Jinrui Tang & Ganheng Ge & Dongjun Yang & Jianchao Liu & Wei Zhang, 2021. "A Novel Short-Term Residential Electric Load Forecasting Method Based on Adaptive Load Aggregation and Deep Learning Algorithms," Energies, MDPI, vol. 14(22), pages 1-21, November.
  47. Dongwei Yao & Xinwei Lu & Xiangyun Chao & Yongguang Zhang & Junhao Shen & Fanlong Zeng & Ziyan Zhang & Feng Wu, 2023. "Adaptive Equivalent Fuel Consumption Minimization Based Energy Management Strategy for Extended-Range Electric Vehicle," Sustainability, MDPI, vol. 15(5), pages 1-18, March.
  48. 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).
  49. Hamdi Abdi, 2022. "A Brief Review of Microgrid Surveys, by Focusing on Energy Management System," Sustainability, MDPI, vol. 15(1), pages 1-20, December.
  50. Karol Bot & Samira Santos & Inoussa Laouali & Antonio Ruano & Maria da Graça Ruano, 2021. "Design of Ensemble Forecasting Models for Home Energy Management Systems," Energies, MDPI, vol. 14(22), pages 1-37, November.
  51. Sarmas, Elissaios & Spiliotis, Evangelos & Stamatopoulos, Efstathios & Marinakis, Vangelis & Doukas, Haris, 2023. "Short-term photovoltaic power forecasting using meta-learning and numerical weather prediction independent Long Short-Term Memory models," Renewable Energy, Elsevier, vol. 216(C).
  52. Wu, Han & Liang, Yan & Heng, Jiani, 2023. "Pulse-diagnosis-inspired multi-feature extraction deep network for short-term electricity load forecasting," Applied Energy, Elsevier, vol. 339(C).
  53. 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.
  54. Sajawal ur Rehman Khan & Israa Adil Hayder & Muhammad Asif Habib & Mudassar Ahmad & Syed Muhammad Mohsin & Farrukh Aslam Khan & Kainat Mustafa, 2022. "Enhanced Machine-Learning Techniques for Medium-Term and Short-Term Electric-Load Forecasting in Smart Grids," Energies, MDPI, vol. 16(1), pages 1-16, December.
  55. Liang, Xinbin & Chen, Siliang & Zhu, Xu & Jin, Xinqiao & Du, Zhimin, 2023. "Domain knowledge decomposition of building energy consumption and a hybrid data-driven model for 24-h ahead predictions," Applied Energy, Elsevier, vol. 344(C).
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