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Forecasting and uncertainty analysis of day-ahead photovoltaic power using a novel forecasting method

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  1. Liu, Benxi & Liu, Tengyuan & Liao, Shengli & Lu, Jia & Cheng, Chuntian, 2023. "Short-term coordinated hybrid hydro-wind-solar optimal scheduling model considering multistage section restrictions," Renewable Energy, Elsevier, vol. 217(C).
  2. Wang, Hu & Mao, Lei & Zhang, Heng & Wu, Qiang, 2024. "Multi-prediction of electric load and photovoltaic solar power in grid-connected photovoltaic system using state transition method," Applied Energy, Elsevier, vol. 353(PB).
  3. Liang, Xinbin & Liu, Zhuoxuan & Wang, Jie & Jin, Xinqiao & Du, Zhimin, 2023. "Uncertainty quantification-based robust deep learning for building energy systems considering distribution shift problem," Applied Energy, Elsevier, vol. 337(C).
  4. Zhi, Yuan & Yang, Xudong, 2023. "Scenario-based multi-objective optimization strategy for rural PV-battery systems," Applied Energy, Elsevier, vol. 345(C).
  5. 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).
  6. Chen, Xiang & Ding, Kun & Zhang, Jingwei & Han, Wei & Liu, Yongjie & Yang, Zenan & Weng, Shuai, 2022. "Online prediction of ultra-short-term photovoltaic power using chaotic characteristic analysis, improved PSO and KELM," Energy, Elsevier, vol. 248(C).
  7. Liu, Yang & Sun, Kangwen & Xu, Ziyuan & Lv, Mingyun, 2022. "Energy efficiency assessment of photovoltaic array on the stratospheric airship under partial shading conditions," Applied Energy, Elsevier, vol. 325(C).
  8. Zhu, Jiebei & Li, Mingrui & Luo, Lin & Zhang, Bidan & Cui, Mingjian & Yu, Lujie, 2023. "Short-term PV power forecast methodology based on multi-scale fluctuation characteristics extraction," Renewable Energy, Elsevier, vol. 208(C), pages 141-151.
  9. Yang, Mao & Zhao, Meng & Huang, Dawei & Su, Xin, 2022. "A composite framework for photovoltaic day-ahead power prediction based on dual clustering of dynamic time warping distance and deep autoencoder," Renewable Energy, Elsevier, vol. 194(C), pages 659-673.
  10. Putri Nor Liyana Mohamad Radzi & Muhammad Naveed Akhter & Saad Mekhilef & Noraisyah Mohamed Shah, 2023. "Review on the Application of Photovoltaic Forecasting Using Machine Learning for Very Short- to Long-Term Forecasting," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
  11. Kaiyan Wang & Haodong Du & Rong Jia & Hongtao Jia, 2022. "Performance Comparison of Bayesian Deep Learning Model and Traditional Bayesian Neural Network in Short-Term PV Interval Prediction," Sustainability, MDPI, vol. 14(19), pages 1-27, October.
  12. Qingyuan Yan & Xunxun Chen & Ling Xing & Xinyu Guo & Chenchen Zhu, 2024. "Multi-Timescale Voltage Regulation for Distribution Network with High Photovoltaic Penetration via Coordinated Control of Multiple Devices," Energies, MDPI, vol. 17(15), pages 1-36, August.
  13. Minli Wang & Peihong Wang & Tao Zhang, 2022. "Evidential Extreme Learning Machine Algorithm-Based Day-Ahead Photovoltaic Power Forecasting," Energies, MDPI, vol. 15(11), pages 1-25, May.
  14. 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.
  15. 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.
  16. Yu, Min & Niu, Dongxiao & Wang, Keke & Du, Ruoyun & Yu, Xiaoyu & Sun, Lijie & Wang, Feiran, 2023. "Short-term photovoltaic power point-interval forecasting based on double-layer decomposition and WOA-BiLSTM-Attention and considering weather classification," Energy, Elsevier, vol. 275(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. Yin, Linfei & Cao, Xinghui & Liu, Dongduan, 2023. "Weighted fully-connected regression networks for one-day-ahead hourly photovoltaic power forecasting," Applied Energy, Elsevier, vol. 332(C).
  19. Zhiwei Liao & Wenlong Min & Chengjin Li & Bowen Wang, 2024. "Photovoltaic Power Prediction Based on Irradiation Interval Distribution and Transformer-LSTM," Energies, MDPI, vol. 17(12), pages 1-17, June.
  20. Hui Wang & Su Yan & Danyang Ju & Nan Ma & Jun Fang & Song Wang & Haijun Li & Tianyu Zhang & Yipeng Xie & Jun Wang, 2023. "Short-Term Photovoltaic Power Forecasting Based on a Feature Rise-Dimensional Two-Layer Ensemble Learning Model," Sustainability, MDPI, vol. 15(21), pages 1-26, November.
  21. Hong Wu & Haipeng Liu & Huaiping Jin & Yanping He, 2024. "Ultra-Short-Term Photovoltaic Power Prediction by NRGA-BiLSTM Considering Seasonality and Periodicity of Data," Energies, MDPI, vol. 17(18), pages 1-19, September.
  22. liu, Qian & li, Yulin & jiang, Hang & chen, Yilin & zhang, Jiang, 2024. "Short-term photovoltaic power forecasting based on multiple mode decomposition and parallel bidirectional long short term combined with convolutional neural networks," Energy, Elsevier, vol. 286(C).
  23. Cui, Shuhui & Lyu, Shouping & Ma, Yongzhi & Wang, Kai, 2024. "Improved informer PV power short-term prediction model based on weather typing and AHA-VMD-MPE," Energy, Elsevier, vol. 307(C).
  24. Ye, Lin & Li, Yilin & Pei, Ming & Zhao, Yongning & Li, Zhuo & Lu, Peng, 2022. "A novel integrated method for short-term wind power forecasting based on fluctuation clustering and history matching," Applied Energy, Elsevier, vol. 327(C).
  25. Zhang, Xinru & Hou, Lei & Liu, Jiaquan & Yang, Kai & Chai, Chong & Li, Yanhao & He, Sichen, 2022. "Energy consumption prediction for crude oil pipelines based on integrating mechanism analysis and data mining," Energy, Elsevier, vol. 254(PB).
  26. 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.
  27. Pan, Mingzhang & Fu, Changcheng & Cao, Xinxin & Guan, Wei & Liang, Lu & Li, Ding & Gu, Jinkai & Tan, Dongli & Zhang, Zhiqing & Man, Xingjia & Ye, Nianye & Qin, Haifeng, 2024. "An energy management strategy for fuel cell hybrid electric vehicle based on HHO-BiLSTM-TCN-self attention speed prediction," Energy, Elsevier, vol. 307(C).
  28. Zhang, Chu & Ji, Chunlei & Hua, Lei & Ma, Huixin & Nazir, Muhammad Shahzad & Peng, Tian, 2022. "Evolutionary quantile regression gated recurrent unit network based on variational mode decomposition, improved whale optimization algorithm for probabilistic short-term wind speed prediction," Renewable Energy, Elsevier, vol. 197(C), pages 668-682.
  29. Mahtab Murshed & Manohar Chamana & Konrad Erich Kork Schmitt & Suhas Pol & Olatunji Adeyanju & Stephen Bayne, 2023. "Sizing PV and BESS for Grid-Connected Microgrid Resilience: A Data-Driven Hybrid Optimization Approach," Energies, MDPI, vol. 16(21), pages 1-22, October.
  30. Wang, Jianzhou & Yu, Yue & Zeng, Bo & Lu, Haiyan, 2024. "Hybrid ultra-short-term PV power forecasting system for deterministic forecasting and uncertainty analysis," Energy, Elsevier, vol. 288(C).
  31. Mayer, Martin János, 2022. "Impact of the tilt angle, inverter sizing factor and row spacing on the photovoltaic power forecast accuracy," Applied Energy, Elsevier, vol. 323(C).
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