IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v312y2022ics0306261922001830.html

Hour-ahead photovoltaic generation forecasting method based on machine learning and multi objective optimization algorithm

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Tian, Zhirui & Gai, Mei, 2023. "A novel hybrid wind speed prediction framework based on multi-strategy improved optimizer and new data pre-processing system with feedback mechanism," Energy, Elsevier, vol. 281(C).
  2. Chang, Chen & Ma, Guangxing & Zhang, Jiehao & Tao, Jinlei, 2025. "Investigation on the CNN-LSTM-MHA-based model for the heating energy consumption prediction of residential buildings considering active and passive factors," Energy, Elsevier, vol. 333(C).
  3. Zhang, Linyue & Wang, Jianzhou & Qian, Yuansheng & Li, Zhiwu, 2025. "Photovoltaic power uncertainty quantification system based on comprehensive model screening and multi-stage optimization tasks," Applied Energy, Elsevier, vol. 381(C).
  4. Jiahui Wang & Mingsheng Jia & Shishi Li & Kang Chen & Cheng Zhang & Xiuyu Song & Qianxi Zhang, 2024. "Short-Term Power-Generation Prediction of High Humidity Island Photovoltaic Power Station Based on a Deep Hybrid Model," Sustainability, MDPI, vol. 16(7), pages 1-24, March.
  5. Li, Jieyi & Qian, Shuangyue & Li, Ling & Guo, Yuanxuan & Wu, Jun & Tang, Ling, 2024. "A novel secondary decomposition method for forecasting crude oil price with twitter sentiment," Energy, Elsevier, vol. 290(C).
  6. Tian, Ai-Qing & Wang, Xiao-Yang & Xu, Heying & Pan, Jeng-Shyang & Snášel, Václav & Lv, Hong-Xia, 2024. "Multi-objective optimization model for railway heavy-haul traffic: Addressing carbon emissions reduction and transport efficiency improvement," Energy, Elsevier, vol. 294(C).
  7. Bingchun Liu & Xia Zhang & Yasen Zhou & Tiezhu Yuan, 2025. "Conversion Potential of Renewable Energy Surplus to Methane in China Based on Power Generation Forecasting," Sustainability, MDPI, vol. 17(7), pages 1-20, March.
  8. Yuan, Yi & Ding, Tao & Chang, Xinyue & Jia, Wenhao & Xue, Yixun, 2024. "A distributed multi-objective optimization method for scheduling of integrated electricity and hydrogen systems," Applied Energy, Elsevier, vol. 355(C).
  9. Zhi, Yuan & Yang, Xudong, 2023. "Scenario-based multi-objective optimization strategy for rural PV-battery systems," Applied Energy, Elsevier, vol. 345(C).
  10. Sabadus, Andreea & Blaga, Robert & Hategan, Sergiu-Mihai & Calinoiu, Delia & Paulescu, Eugenia & Mares, Oana & Boata, Remus & Stefu, Nicoleta & Paulescu, Marius & Badescu, Viorel, 2024. "A cross-sectional survey of deterministic PV power forecasting: Progress and limitations in current approaches," Renewable Energy, Elsevier, vol. 226(C).
  11. Sergio Cantillo-Luna & Ricardo Moreno-Chuquen & Jesus Lopez-Sotelo & David Celeita, 2023. "An Intra-Day Electricity Price Forecasting Based on a Probabilistic Transformer Neural Network Architecture," Energies, MDPI, vol. 16(19), pages 1-24, September.
  12. Li, Yanmei & Zhang, Yi & Yin, Minghao, 2026. "Physics-informed Mamba network for ultra-short-term photovoltaic power forecasting: integrating WGAN-GP augmentation and CEEMDAN-SST decomposition," Renewable Energy, Elsevier, vol. 257(C).
  13. Wang, Jianzhou & An, Yining & Li, Zhiwu & Lu, Haiyan, 2022. "A novel combined forecasting model based on neural networks, deep learning approaches, and multi-objective optimization for short-term wind speed forecasting," Energy, Elsevier, vol. 251(C).
  14. Ridha, Hussein Mohammed & Ahmadipour, Masoud & Alghrairi, Mokhalad & Hizam, Hashim & Mirjalili, Seyedali & Zubaidi, Salah L. & Mohammed S, Marwa Y., 2026. "A novel hybrid photovoltaic current prediction model utilizing singular spectrum analysis, adaptive beluga whale optimization, and improved extreme learning machine," Renewable Energy, Elsevier, vol. 256(PA).
  15. Max Olinto Moreira & Betania Mafra Kaizer & Takaaki Ohishi & Benedito Donizeti Bonatto & Antonio Carlos Zambroni de Souza & Pedro Paulo Balestrassi, 2022. "Multivariate Strategy Using Artificial Neural Networks for Seasonal Photovoltaic Generation Forecasting," Energies, MDPI, vol. 16(1), pages 1-30, December.
  16. Huang, Congzhi & Yang, Mengyuan, 2023. "Memory long and short term time series network for ultra-short-term photovoltaic power forecasting," Energy, Elsevier, vol. 279(C).
  17. Niu, Yunbo & Wang, Jianzhou & Zhang, Ziyuan & Luo, Tianrui & Liu, Jingjiang, 2024. "De-Trend First, Attend Next: A Mid-Term PV forecasting system with attention mechanism and encoder–decoder structure," Applied Energy, Elsevier, vol. 353(PB).
  18. Liu, Lin & Zhang, Jianqiu & Xue, Shibei, 2025. "Photovoltaic power forecasting: Using wavelet threshold denoising combined with VMD," Renewable Energy, Elsevier, vol. 249(C).
  19. Liu, Bingchun & Huo, Xiankai, 2024. "Prediction of Photovoltaic power generation and analyzing of carbon emission reduction capacity in China," Renewable Energy, Elsevier, vol. 222(C).
  20. Deng, Ruizhe & Wang, Yiming & Xu, Po & Luo, Futao & Chen, Qi & Zhang, Haoran & Chen, Yuntian & Zhang, Dongxiao, 2025. "A high-precision photovoltaic power forecasting model leveraging low-fidelity data through decoupled informer with multi-moment guidance," Renewable Energy, Elsevier, vol. 250(C).
  21. Seman, Laio Oriel & Stefenon, Stefano Frizzo & Yow, Kin-Choong & Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2026. "Multi-step short-term solar energy forecasting using Fourier-enhanced BiLSTM and neural additive models," Renewable Energy, Elsevier, vol. 257(C).
  22. Yang, Shaomei & Luo, Yuman, 2025. "Short-term photovoltaic power prediction based on RF-SGMD-GWO-BiLSTM hybrid models," Energy, Elsevier, vol. 316(C).
  23. 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.
  24. Meng, Anbo & Zhu, Zibin & Deng, Weisi & Ou, Zuhong & Lin, Shan & Wang, Chenen & Xu, Xuancong & Wang, Xiaolin & Yin, Hao & Luo, Jianqiang, 2022. "A novel wind power prediction approach using multivariate variational mode decomposition and multi-objective crisscross optimization based deep extreme learning machine," Energy, Elsevier, vol. 260(C).
  25. Yin, Linfei & Ye, Yongzi, 2025. "Distributed multi-objective African vulture accelerated optimization intelligent algorithm for multi-objective economic dispatch of power systems," Applied Energy, Elsevier, vol. 398(C).
  26. Wang, Jianzhou & Niu, Xinsong & Zhang, Lifang & Liu, Zhenkun & Wei, Danxiang, 2022. "The influence of international oil prices on the exchange rates of oil exporting countries: Based on the hybrid copula function," Resources Policy, Elsevier, vol. 77(C).
  27. Yang, Yi & Xing, Qianyi & Wang, Kang & Li, Caihong & Wang, Jianzhou & Huang, Xiaojia, 2024. "A novel combined probabilistic load forecasting system integrating hybrid quantile regression and knee improved multi-objective optimization strategy," Applied Energy, Elsevier, vol. 356(C).
  28. Li, Yifan & Liu, Gang & Cao, Yisheng & Chen, Jiawei & Gang, Xiao & Tang, Jianchao, 2025. "WNPS-LSTM-Informer: A Hybrid Stacking model for medium-term photovoltaic power forecasting with ranked feature selection," Renewable Energy, Elsevier, vol. 244(C).
  29. Hu, Zehuan & Gao, Yuan & Ji, Siyu & Mae, Masayuki & Imaizumi, Taiji, 2024. "Improved multistep ahead photovoltaic power prediction model based on LSTM and self-attention with weather forecast data," Applied Energy, Elsevier, vol. 359(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.