Situational awareness indices of solar PV power generation under temporal weather conditions for near real-time planning and operation
Author
Abstract
Suggested Citation
DOI: 10.1016/j.apenergy.2025.126855
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.References listed on IDEAS
- Hasala Dharmawardena & Ganesh Kumar Venayagamoorthy, 2022. "Distributed Volt-Var Curve Optimization Using a Cellular Computational Network Representation of an Electric Power Distribution System," Energies, MDPI, vol. 15(12), pages 1-18, June.
- Kumari, Pratima & Toshniwal, Durga, 2021. "Long short term memory–convolutional neural network based deep hybrid approach for solar irradiance forecasting," Applied Energy, Elsevier, vol. 295(C).
- Khezri, Rahmat & Mahmoudi, Amin & Aki, Hirohisa, 2022. "Optimal planning of solar photovoltaic and battery storage systems for grid-connected residential sector: Review, challenges and new perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
- Mellit, Adel & Kalogirou, Soteris, 2021. "Artificial intelligence and internet of things to improve efficacy of diagnosis and remote sensing of solar photovoltaic systems: Challenges, recommendations and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
- Markos A. Kousounadis-Knousen & Ioannis K. Bazionis & Athina P. Georgilaki & Francky Catthoor & Pavlos S. Georgilakis, 2023. "A Review of Solar Power Scenario Generation Methods with Focus on Weather Classifications, Temporal Horizons, and Deep Generative Models," Energies, MDPI, vol. 16(15), pages 1-29, July.
- Nespoli, Alfredo & Niccolai, Alessandro & Ogliari, Emanuele & Perego, Giovanni & Collino, Elena & Ronzio, Dario, 2022. "Machine Learning techniques for solar irradiation nowcasting: Cloud type classification forecast through satellite data and imagery," Applied Energy, Elsevier, vol. 305(C).
- Shah, Rakibuzzaman & Mithulananthan, N. & Bansal, R.C. & Ramachandaramurthy, V.K., 2015. "A review of key power system stability challenges for large-scale PV integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1423-1436.
- Youssef, Ayman & El-Telbany, Mohammed & Zekry, Abdelhalim, 2017. "The role of artificial intelligence in photo-voltaic systems design and control: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 72-79.
- Nie, Yuhao & Paletta, Quentin & Scott, Andea & Pomares, Luis Martin & Arbod, Guillaume & Sgouridis, Sgouris & Lasenby, Joan & Brandt, Adam, 2024. "Sky image-based solar forecasting using deep learning with heterogeneous multi-location data: Dataset fusion versus transfer learning," Applied Energy, Elsevier, vol. 369(C).
- Wang, Xiaoyang & Sun, Yunlin & Luo, Duo & Peng, Jinqing, 2022. "Comparative study of machine learning approaches for predicting short-term photovoltaic power output based on weather type classification," Energy, Elsevier, vol. 240(C).
- Gao, Mingming & Li, Jianjing & Hong, Feng & Long, Dongteng, 2019. "Day-ahead power forecasting in a large-scale photovoltaic plant based on weather classification using LSTM," Energy, Elsevier, vol. 187(C).
- Zheng, Lingwei & Su, Ran & Sun, Xinyu & Guo, Siqi, 2023. "Historical PV-output characteristic extraction based weather-type classification strategy and its forecasting method for the day-ahead prediction of PV output," Energy, Elsevier, vol. 271(C).
- Liu, Jingxuan & Zang, Haixiang & Cheng, Lilin & Ding, Tao & Wei, Zhinong & Sun, Guoqiang, 2023. "A Transformer-based multimodal-learning framework using sky images for ultra-short-term solar irradiance forecasting," Applied Energy, Elsevier, vol. 342(C).
- Markovics, Dávid & Mayer, Martin János, 2022. "Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
- Dou, Weijing & Wang, Kai & Shan, Shuo & Li, Chenxi & Wang, Yiye & Zhang, Kanjian & Wei, Haikun & Sreeram, Victor, 2024. "Day-ahead Numerical Weather Prediction solar irradiance correction using a clustering method based on weather conditions," Applied Energy, Elsevier, vol. 365(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Mousavi, Rashin & Mousavi, Arash & Mousavi, Yashar & Tavasoli, Mahsa & Arab, Aliasghar & Kucukdemiral, Ibrahim Beklan & Alfi, Alireza & Fekih, Afef, 2025. "Revolutionizing solar energy resources: The central role of generative AI in elevating system sustainability and efficiency," Applied Energy, Elsevier, vol. 382(C).
- Verdone, Alessio & Panella, Massimo & De Santis, Enrico & Rizzi, Antonello, 2025. "A review of solar and wind energy forecasting: From single-site to multi-site paradigm," Applied Energy, Elsevier, vol. 392(C).
- Chen, Yunxiao & Bai, Mingliang & Zhang, Yilan & Liu, Jinfu & Yu, Daren, 2023. "Proactively selection of input variables based on information gain factors for deep learning models in short-term solar irradiance forecasting," Energy, Elsevier, vol. 284(C).
- 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).
- Zheng, Lingwei & Su, Ran & Sun, Xinyu & Guo, Siqi, 2023. "Historical PV-output characteristic extraction based weather-type classification strategy and its forecasting method for the day-ahead prediction of PV output," Energy, Elsevier, vol. 271(C).
- Temitayo O. Olowu & Aditya Sundararajan & Masood Moghaddami & Arif I. Sarwat, 2018. "Future Challenges and Mitigation Methods for High Photovoltaic Penetration: A Survey," Energies, MDPI, vol. 11(7), pages 1-32, July.
- Yap, Kah Yung & Chin, Hon Huin & Klemeš, Jiří Jaromír, 2022. "Solar Energy-Powered Battery Electric Vehicle charging stations: Current development and future prospect review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
- Liu, Tianhao & Shan, Linke & Jiang, Meihui & Li, Fangning & Kong, Fannie & Du, Pengcheng & Zhu, Hongyu & Goh, Hui Hwang & Kurniawan, Tonni Agustiono & Huang, Chao & Zhang, Dongdong, 2025. "Multi-dimensional data processing and intelligent forecasting technologies for renewable energy generation," Applied Energy, Elsevier, vol. 398(C).
- Zang, Haixiang & Chen, Dianhao & Liu, Jingxuan & Cheng, Lilin & Sun, Guoqiang & Wei, Zhinong, 2024. "Improving ultra-short-term photovoltaic power forecasting using a novel sky-image-based framework considering spatial-temporal feature interaction," Energy, Elsevier, vol. 293(C).
- Xie, Yang & Zheng, Jianyong & Mei, Fei & Taylor, Gareth & Gao, Ang, 2025. "An efficient approach for regional photovoltaic power forecasting optimization based on texture features from satellite images and transfer learning," Applied Energy, Elsevier, vol. 385(C).
- 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).
- Sun, Fengpeng & Li, Longhao & Bian, Dunxin & Bian, Wenlin & Wang, Qinghong & Wang, Shuang, 2025. "Photovoltaic power prediction based on multi-scale photovoltaic power fluctuation characteristics and multi-channel LSTM prediction models," Renewable Energy, Elsevier, vol. 246(C).
- Shi, Chaojun & Zhang, Xiaoyun & Zhang, Ke & Xie, Xiongbin & Lu, Qiaochu & Zhang, Ningxuan & Su, Zibo, 2025. "Ultra-short-term photovoltaic power prediction based on ground-based cloud images: A review," Applied Energy, Elsevier, vol. 402(PA).
- Hanif, M.F. & Mi, J., 2024. "Harnessing AI for solar energy: Emergence of transformer models," Applied Energy, Elsevier, vol. 369(C).
- Xie, Qiyue & Ma, Lin & Liu, Yao & Fu, Qiang & Shen, Zhongli & Wang, Xiaoli, 2023. "An improved SSA-BiLSTM-based short-term irradiance prediction model via sky images feature extraction," Renewable Energy, Elsevier, vol. 219(P2).
- 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.
- Chen, Xin & Li, Baojie & Braid, Jennifer L. & Byford, Brandon & Colvin, Dylan J. & Glaws, Andrew & Jost, Norman & Pierce, Benjamin & Rabade, Salil & Springer, Martin & Jain, Anubhav, 2025. "Open data sets for assessing photovoltaic system reliability," Applied Energy, Elsevier, vol. 395(C).
- Perera, Maneesha & De Hoog, Julian & Bandara, Kasun & Senanayake, Damith & Halgamuge, Saman, 2024. "Day-ahead regional solar power forecasting with hierarchical temporal convolutional neural networks using historical power generation and weather data," Applied Energy, Elsevier, vol. 361(C).
- Dou, Weijing & Wang, Kai & Shan, Shuo & Chen, Mingyu & Zhang, Kanjian & Wei, Haikun & Sreeram, Victor, 2025. "A multi-modal deep clustering method for day-ahead solar irradiance forecasting using ground-based cloud imagery and time series data," Energy, Elsevier, vol. 321(C).
- 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).
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:402:y:2025:i:pa:s0306261925015855. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/eee/appene/v402y2025ipas0306261925015855.html