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Short term load forecasting based on feature extraction and improved general regression neural network model

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  1. Guo‐Feng Fan & Yan‐Hui Guo & Jia‐Mei Zheng & Wei‐Chiang Hong, 2020. "A generalized regression model based on hybrid empirical mode decomposition and support vector regression with back‐propagation neural network for mid‐short‐term load forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 737-756, August.
  2. Zhang, Guoqiang & Guo, Jifeng, 2020. "A novel ensemble method for hourly residential electricity consumption forecasting by imaging time series," Energy, Elsevier, vol. 203(C).
  3. Jin, Yue & Yang, Lin & Du, Mao & Qiang, Jiaxi & Li, Jingzhong & Chen, Yuxuan & Tu, Jiayu, 2023. "Two-scale based energy management for connected plug-in hybrid electric vehicles with global optimal energy consumption and state-of-charge trajectory prediction," Energy, Elsevier, vol. 267(C).
  4. Andreea Valeria Vesa & Tudor Cioara & Ionut Anghel & Marcel Antal & Claudia Pop & Bogdan Iancu & Ioan Salomie & Vasile Teodor Dadarlat, 2020. "Energy Flexibility Prediction for Data Center Engagement in Demand Response Programs," Sustainability, MDPI, vol. 12(4), pages 1-23, February.
  5. Fan, Jingmin & Zhong, Mingwei & Guan, Yuanpeng & Yi, Siqi & Xu, Cancheng & Zhai, Yanpeng & Zhou, Yongwang, 2024. "An online long-term load forecasting method: Hierarchical highway network based on crisscross feature collaboration," Energy, Elsevier, vol. 299(C).
  6. Talaat, M. & Farahat, M.A. & Mansour, Noura & Hatata, A.Y., 2020. "Load forecasting based on grasshopper optimization and a multilayer feed-forward neural network using regressive approach," Energy, Elsevier, vol. 196(C).
  7. Amedeo Buonanno & Martina Caliano & Antonino Pontecorvo & Gianluca Sforza & Maria Valenti & Giorgio Graditi, 2022. "Global vs. Local Models for Short-Term Electricity Demand Prediction in a Residential/Lodging Scenario," Energies, MDPI, vol. 15(6), pages 1-18, March.
  8. Wei Ding & Xuguang Zhao & Weigao Meng & Haichao Wang, 2022. "Smart Evaluation of Sustainability of Photovoltaic Projects in the Context of Carbon Neutrality Target," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
  9. Hu, Yusha & Li, Jigeng & Hong, Mengna & Ren, Jingzheng & Lin, Ruojue & Liu, Yue & Liu, Mengru & Man, Yi, 2019. "Short term electric load forecasting model and its verification for process industrial enterprises based on hybrid GA-PSO-BPNN algorithm—A case study of papermaking process," Energy, Elsevier, vol. 170(C), pages 1215-1227.
  10. Zang, Haixiang & Xu, Ruiqi & Cheng, Lilin & Ding, Tao & Liu, Ling & Wei, Zhinong & Sun, Guoqiang, 2021. "Residential load forecasting based on LSTM fusing self-attention mechanism with pooling," Energy, Elsevier, vol. 229(C).
  11. Malekizadeh, M. & Karami, H. & Karimi, M. & Moshari, A. & Sanjari, M.J., 2020. "Short-term load forecast using ensemble neuro-fuzzy model," Energy, Elsevier, vol. 196(C).
  12. João Vitor Leme & Wallace Casaca & Marilaine Colnago & Maurício Araújo Dias, 2020. "Towards Assessing the Electricity Demand in Brazil: Data-Driven Analysis and Ensemble Learning Models," Energies, MDPI, vol. 13(6), pages 1-20, March.
  13. Somu, Nivethitha & M R, Gauthama Raman & Ramamritham, Krithi, 2020. "A hybrid model for building energy consumption forecasting using long short term memory networks," Applied Energy, Elsevier, vol. 261(C).
  14. Yi Liang & Haichao Wang, 2021. "Using Improved SPA and ICS-LSSVM for Sustainability Assessment of PV Industry along the Belt and Road," Energies, MDPI, vol. 14(12), pages 1-19, June.
  15. Jihoon Moon & Junhong Kim & Pilsung Kang & Eenjun Hwang, 2020. "Solving the Cold-Start Problem in Short-Term Load Forecasting Using Tree-Based Methods," Energies, MDPI, vol. 13(4), pages 1-37, February.
  16. Ivana Kiprijanovska & Simon Stankoski & Igor Ilievski & Slobodan Jovanovski & Matjaž Gams & Hristijan Gjoreski, 2020. "HousEEC: Day-Ahead Household Electrical Energy Consumption Forecasting Using Deep Learning," Energies, MDPI, vol. 13(10), pages 1-29, May.
  17. Wang, Kang & Wang, Jianzhou & Zeng, Bo & Lu, Haiyan, 2022. "An integrated power load point-interval forecasting system based on information entropy and multi-objective optimization," Applied Energy, Elsevier, vol. 314(C).
  18. 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.
  19. Zhu, Yuli & Jiang, Bo & Zhu, Jiangong & Wang, Xueyuan & Wang, Rong & Wei, Xuezhe & Dai, Haifeng, 2023. "Adaptive state of health estimation for lithium-ion batteries using impedance-based timescale information and ensemble learning," Energy, Elsevier, vol. 284(C).
  20. Kong, Xiangyu & Li, Chuang & Wang, Chengshan & Zhang, Yusen & Zhang, Jian, 2020. "Short-term electrical load forecasting based on error correction using dynamic mode decomposition," Applied Energy, Elsevier, vol. 261(C).
  21. Jian Chen & Fangyi Li & Ranran Yang & Dawei Ma, 2020. "Impacts of Increasing Private Charging Piles on Electric Vehicles’ Charging Profiles: A Case Study in Hefei City, China," Energies, MDPI, vol. 13(17), pages 1-17, August.
  22. Sungwoo Park & Jihoon Moon & Seungwon Jung & Seungmin Rho & Sung Wook Baik & Eenjun Hwang, 2020. "A Two-Stage Industrial Load Forecasting Scheme for Day-Ahead Combined Cooling, Heating and Power Scheduling," Energies, MDPI, vol. 13(2), pages 1-23, January.
  23. Bogdan Bochenek & Jakub Jurasz & Adam Jaczewski & Gabriel Stachura & Piotr Sekuła & Tomasz Strzyżewski & Marcin Wdowikowski & Mariusz Figurski, 2021. "Day-Ahead Wind Power Forecasting in Poland Based on Numerical Weather Prediction," Energies, MDPI, vol. 14(8), pages 1-18, April.
  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. Wang, Jianzhou & Gao, Jialu & Wei, Danxiang, 2022. "Electric load prediction based on a novel combined interval forecasting system," Applied Energy, Elsevier, vol. 322(C).
  26. Duan, Jikai & Chang, Mingheng & Chen, Xiangyue & Wang, Wenpeng & Zuo, Hongchao & Bai, Yulong & Chen, Bolong, 2022. "A combined short-term wind speed forecasting model based on CNN–RNN and linear regression optimization considering error," Renewable Energy, Elsevier, vol. 200(C), pages 788-808.
  27. Li, Chen, 2020. "Designing a short-term load forecasting model in the urban smart grid system," Applied Energy, Elsevier, vol. 266(C).
  28. Liu, Jinyuan & Wang, Shouxi & Wei, Nan & Qiao, Weibiao & Li, Ze & Zeng, Fanhua, 2023. "A clustering-based feature enhancement method for short-term natural gas consumption forecasting," Energy, Elsevier, vol. 278(PB).
  29. Aamer A. Shah & Almani A. Aftab & Xueshan Han & Mazhar Hussain Baloch & Mohamed Shaik Honnurvali & Sohaib Tahir Chauhdary, 2023. "Prediction Error-Based Power Forecasting of Wind Energy System Using Hybrid WT–ROPSO–NARMAX Model," Energies, MDPI, vol. 16(7), pages 1-15, April.
  30. Seyedeh Narjes Fallah & Mehdi Ganjkhani & Shahaboddin Shamshirband & Kwok-wing Chau, 2019. "Computational Intelligence on Short-Term Load Forecasting: A Methodological Overview," Energies, MDPI, vol. 12(3), pages 1-21, January.
  31. Nebojsa Bacanin & Catalin Stoean & Miodrag Zivkovic & Miomir Rakic & Roma Strulak-Wójcikiewicz & Ruxandra Stoean, 2023. "On the Benefits of Using Metaheuristics in the Hyperparameter Tuning of Deep Learning Models for Energy Load Forecasting," Energies, MDPI, vol. 16(3), pages 1-21, February.
  32. Duan, Jiandong & Wang, Peng & Ma, Wentao & Tian, Xuan & Fang, Shuai & Cheng, Yulin & Chang, Ying & Liu, Haofan, 2021. "Short-term wind power forecasting using the hybrid model of improved variational mode decomposition and Correntropy Long Short -term memory neural network," Energy, Elsevier, vol. 214(C).
  33. Mingping Liu & Xihao Sun & Qingnian Wang & Suhui Deng, 2022. "Short-Term Load Forecasting Using EMD with Feature Selection and TCN-Based Deep Learning Model," Energies, MDPI, vol. 15(19), pages 1-22, September.
  34. Luo, X.J. & Oyedele, Lukumon O. & Ajayi, Anuoluwapo O. & Akinade, Olugbenga O. & Owolabi, Hakeem A. & Ahmed, Ashraf, 2020. "Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
  35. Xian, Huafeng & Che, Jinxing, 2022. "Multi-space collaboration framework based optimal model selection for power load forecasting," Applied Energy, Elsevier, vol. 314(C).
  36. Miguel A. Jaramillo-Morán & Daniel Fernández-Martínez & Agustín García-García & Diego Carmona-Fernández, 2021. "Improving Artificial Intelligence Forecasting Models Performance with Data Preprocessing: European Union Allowance Prices Case Study," Energies, MDPI, vol. 14(23), pages 1-23, November.
  37. Li, Peng & Ji, Jie & Ji, Haoran & Song, Guanyu & Wang, Chengshan & Wu, Jianzhong, 2020. "Self-healing oriented supply restoration method based on the coordination of multiple SOPs in active distribution networks," Energy, Elsevier, vol. 195(C).
  38. Juan A. Dominguez-Jimenez & Javier E. Campillo & Oscar Danilo Montoya & Enrique Delahoz & Jesus C. Hernández, 2020. "Seasonality Effect Analysis and Recognition of Charging Behaviors of Electric Vehicles: A Data Science Approach," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
  39. Yi Liang & Yingying Fan & Yongfang Peng & Haigang An, 2022. "Smart Grid Project Benefit Evaluation Based on a Hybrid Intelligent Model," Sustainability, MDPI, vol. 14(17), pages 1-20, September.
  40. Dai, Yeming & Zhao, Pei, 2020. "A hybrid load forecasting model based on support vector machine with intelligent methods for feature selection and parameter optimization," Applied Energy, Elsevier, vol. 279(C).
  41. Kargbo, Hannah O. & Zhang, Jie & Phan, Anh N., 2021. "Optimisation of two-stage biomass gasification for hydrogen production via artificial neural network," Applied Energy, Elsevier, vol. 302(C).
  42. Dai, Yeming & Yang, Xinyu & Leng, Mingming, 2022. "Forecasting power load: A hybrid forecasting method with intelligent data processing and optimized artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
  43. Hongmei Zhao & Yang Xu & Wei-Chiang Hong & Yi Liang & Dandan Zou, 2021. "Smart Evaluation of Green Campus Sustainability Considering Energy Utilization," Sustainability, MDPI, vol. 13(14), pages 1-21, July.
  44. Yi Liang & Haichao Wang & Wei-Chiang Hong, 2021. "Sustainable Development Evaluation of Innovation and Entrepreneurship Education of Clean Energy Major in Colleges and Universities Based on SPA-VFS and GRNN Optimized by Chaos Bat Algorithm," Sustainability, MDPI, vol. 13(11), pages 1-26, May.
  45. Guangyu Qin & Qingyou Yan & Jingyao Zhu & Chuanbo Xu & Daniel M. Kammen, 2021. "Day-Ahead Wind Power Forecasting Based on Wind Load Data Using Hybrid Optimization Algorithm," Sustainability, MDPI, vol. 13(3), pages 1-17, January.
  46. Rafati, Amir & Joorabian, Mahmood & Mashhour, Elaheh, 2020. "An efficient hour-ahead electrical load forecasting method based on innovative features," Energy, Elsevier, vol. 201(C).
  47. Zhang, Yu & Peng, Zhen & Guan, Yong & Wu, Lifeng, 2021. "Prognostics of battery cycle life in the early-cycle stage based on hybrid model," Energy, Elsevier, vol. 221(C).
  48. Shi, Jian & Teh, Jiashen, 2024. "Load forecasting for regional integrated energy system based on complementary ensemble empirical mode decomposition and multi-model fusion," Applied Energy, Elsevier, vol. 353(PB).
  49. Yanhua Chang & Yi Liang, 2023. "Intelligent Risk Assessment of Ecological Agriculture Projects from a Vision of Low Carbon," Sustainability, MDPI, vol. 15(7), pages 1-21, March.
  50. Ibrahim Salem Jahan & Vaclav Snasel & Stanislav Misak, 2020. "Intelligent Systems for Power Load Forecasting: A Study Review," Energies, MDPI, vol. 13(22), pages 1-12, November.
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