1. Modeling Parametric Forecasts of Solar Energy over Time in the Mid-North Area of Mozambique. (2025). Magaia, Loureno Lzaro ; Santos, Carlos Augusto ; Mucomole, Fernando Venncio.
   In: Energies.
   RePEc:gam:jeners:v:18:y:2025:i:6:p:1469-:d:1614023.

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2. Experimental Parametric Forecast of Solar Energy over Time: Sample Data Descriptor. (2025). Santos, Carlos Augusto ; Mucomole, Fernando Venncio ; Magaia, Loureno Lzaro.
   In: Data.
   RePEc:gam:jdataj:v:10:y:2025:i:3:p:37-:d:1613980.

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3. A multiscale network with mixed features and extended regional weather forecasts for predicting short-term photovoltaic power. (2025). Zhang, Ruoyang ; Wu, YU ; Xu, Chongbin ; Wang, Zeyu ; Sun, Xiaomin ; Zuo, Xin ; Chen, Qian.
   In: Energy.
   RePEc:eee:energy:v:318:y:2025:i:c:s0360544225004347.

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4. Short-Term Photovoltaic Power Prediction Using Nonlinear Spiking Neural P Systems. (2024). Gao, Yunzhu ; Guo, Lin ; Wang, Jun ; Peng, Hong.
   In: Sustainability.
   RePEc:gam:jsusta:v:16:y:2024:i:4:p:1709-:d:1341730.

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5. Hybrid Photovoltaic Output Forecasting Model with Temporal Convolutional Network Using Maximal Information Coefficient and White Shark Optimizer. (2024). Yan, Zixuan ; Niu, Yisen ; Lin, Xilong ; Tang, Ping ; Zou, Lianglin ; Song, Jifeng.
   In: Sustainability.
   RePEc:gam:jsusta:v:16:y:2024:i:14:p:6102-:d:1436965.

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6. Short-Term Irradiance Prediction Based on Transformer with Inverted Functional Area Structure. (2024). Yu, Cilong ; Wang, Huaizhi ; Zhuang, Zhenyuan.
   In: Mathematics.
   RePEc:gam:jmathe:v:12:y:2024:i:20:p:3213-:d:1498340.

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7. Improving Solar Radiation Forecasting in Cloudy Conditions by Integrating Satellite Observations. (2024). Luo, Fei ; Zhuang, Shuyi ; Bu, Qiangsheng ; Ye, Zhigang ; Yuan, Yubo ; Ma, Tianrui ; Da, Tao.
   In: Energies.
   RePEc:gam:jeners:v:17:y:2024:i:24:p:6222-:d:1540673.

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8. Spatial solar forecast verification with the neighborhood method and automatic threshold segmentation. (2024). Xia, Xiangao ; Li, Mengying ; Wang, Jingnan ; Zhang, Hao ; Yang, Dazhi ; Liu, Bai ; Chu, Yinghao.
   In: Renewable and Sustainable Energy Reviews.
   RePEc:eee:rensus:v:202:y:2024:i:c:s1364032124003812.

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9. A review of distributed solar forecasting with remote sensing and deep learning. (2024). Chu, Yinghao ; Wang, Yiling ; Chen, Shanlin ; Li, Mengying ; Yang, Dazhi.
   In: Renewable and Sustainable Energy Reviews.
   RePEc:eee:rensus:v:198:y:2024:i:c:s136403212400114x.

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10. A novel solar irradiance forecasting method based on multi-physical process of atmosphere optics and LSTM-BP model. (2024). Wu, Ji ; Wang, Zhenyu ; Zhang, Yunpeng ; Zhou, Hai ; Li, Guorong.
    In: Renewable Energy.
    RePEc:eee:renene:v:226:y:2024:i:c:s0960148124004324.

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11. Solar power forecasting using domain knowledge. (2024). Kr, Surajit ; Mondal, Rakesh ; Giri, Chandan.
    In: Energy.
    RePEc:eee:energy:v:302:y:2024:i:c:s0360544224014828.

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12. Medium-term forecasting of global horizontal solar radiation in Brazil using machine learning-based methods. (2024). da Silva, Diogo Nunes ; Moreira, Davidson Martins ; Lago, Yasmin Kaore ; Cotta, Arthur Lucide ; Jacondino, William Duarte ; Dos, Thalyta Soares ; Araujo, Allan Cavalcante ; Pedruzzi, Rizzieri ; Bandeira, Alex Alisson ; Saraiva, Mirella Lima ; de Carvalho, Marcio ; Melgao, Luana Kruger ; de Melo, Jose Bione ; Lopes, Francisco Jose.
    In: Energy.
    RePEc:eee:energy:v:300:y:2024:i:c:s0360544224013227.

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13. Day-ahead regional solar power forecasting with hierarchical temporal convolutional neural networks using historical power generation and weather data. (2024). Halgamuge, Saman ; Perera, Maneesha ; Bandara, Kasun ; de Hoog, Julian ; Senanayake, Damith.
    In: Applied Energy.
    RePEc:eee:appene:v:361:y:2024:i:c:s0306261924003544.

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14. Review on the Application of Photovoltaic Forecasting Using Machine Learning for Very Short- to Long-Term Forecasting. (2023). Mekhilef, Saad ; Liyana, Putri Nor ; Shah, Noraisyah Mohamed ; Akhter, Muhammad Naveed.
    In: Sustainability.
    RePEc:gam:jsusta:v:15:y:2023:i:4:p:2942-:d:1059527.

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15. Six Days Ahead Forecasting of Energy Production of Small Behind-the-Meter Solar Sites. (2023). Menezes, Hugo Bezerra ; Zareipour, Hamidreza.
    In: Energies.
    RePEc:gam:jeners:v:16:y:2023:i:3:p:1533-:d:1057124.

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16. Poultry litter valorization: Development and optimization of an electro-chemical and thermal tri-generation process using an extreme gradient boosting algorithm. (2023). Ayub, Yousaf ; Shen, Weifeng ; Shi, Tao ; Ren, Jingzheng.
    In: Energy.
    RePEc:eee:energy:v:263:y:2023:i:pc:s0360544222027256.

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17. Stacking Model for Photovoltaic-Power-Generation Prediction. (2022). Zhu, Tengteng ; Zhang, Hongchao.
    In: Sustainability.
    RePEc:gam:jsusta:v:14:y:2022:i:9:p:5669-:d:810783.

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18. An Integrated Framework Based on an Improved Gaussian Process Regression and Decomposition Technique for Hourly Solar Radiation Forecasting. (2022). Hao, Xiangmiao ; Jiang, Wei ; Peng, Tian ; Zhang, Shuai ; Sun, NA.
    In: Sustainability.
    RePEc:gam:jsusta:v:14:y:2022:i:22:p:15298-:d:976158.

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19. Evaluation of Various Tree-Based Ensemble Models for Estimating Solar Energy Resource Potential in Different Climatic Zones of China. (2022). Zhou, Zhigao ; Wang, Lunche ; He, Lijie ; Lin, Aiwen.
    In: Energies.
    RePEc:gam:jeners:v:15:y:2022:i:9:p:3463-:d:811731.

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20. BiLSTM Network-Based Approach for Solar Irradiance Forecasting in Continental Climate Zones. (2022). Sulaiman, Shaharin Anwar ; Naz, Muhammad Yasin ; Bou-Rabee, Mohammed A ; Ed, Imad.
    In: Energies.
    RePEc:gam:jeners:v:15:y:2022:i:6:p:2226-:d:774209.

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21. Short-Term Solar Power Predicting Model Based on Multi-Step CNN Stacked LSTM Technique. (2022). Hasan, Shazia ; Michael, Neethu Elizabeth ; Mishra, Manohar ; Al-Durra, Ahmed.
    In: Energies.
    RePEc:gam:jeners:v:15:y:2022:i:6:p:2150-:d:771767.

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22. A Review on a Data-Driven Microgrid Management System Integrating an Active Distribution Network: Challenges, Issues, and New Trends. (2022). Tightiz, Lilia ; Yoo, Joon.
    In: Energies.
    RePEc:gam:jeners:v:15:y:2022:i:22:p:8739-:d:978985.

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23. SENERGY: A Novel Deep Learning-Based Auto-Selective Approach and Tool for Solar Energy Forecasting. (2022). Hasan, Syed Hamid ; Mehmood, Rashid ; Alkhayat, Ghadah.
    In: Energies.
    RePEc:gam:jeners:v:15:y:2022:i:18:p:6659-:d:912883.

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24. Deep-Learning-Based Adaptive Model for Solar Forecasting Using Clustering. (2022). Roy, Sugata Sen ; Malakar, Sourav ; Goswami, Saptarsi ; Boopathi, K ; Ganguli, Bhaswati ; Chakrabarti, Amlan ; Rangaraj, A G.
    In: Energies.
    RePEc:gam:jeners:v:15:y:2022:i:10:p:3568-:d:814752.

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25. Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction. (2022). Mayer, Martin Janos ; Markovics, David.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:161:y:2022:i:c:s136403212200274x.

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26. Ensemble solar forecasting and post-processing using dropout neural network and information from neighboring satellite pixels. (2022). Yagli, Gokhan Mert ; Srinivasan, Dipti ; Yang, Dazhi.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:155:y:2022:i:c:s1364032121011734.

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27. Solar forecasting with hourly updated numerical weather prediction. (2022). Galanis, George ; Zhang, Gang ; Androulakis, Emmanouil ; Yang, Dazhi.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:154:y:2022:i:c:s1364032121010364.

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28. Deep learning and statistical methods for short- and long-term solar irradiance forecasting for Islamabad. (2022). Ayaz, Yasar ; Haider, Syed Altan ; Sajid, Muhammad ; Uddin, Emad.
    In: Renewable Energy.
    RePEc:eee:renene:v:198:y:2022:i:c:p:51-60.

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29. EGD-SNet: A computational search engine for predicting an end-to-end machine learning pipeline for Energy Generation & Demand Forecasting. (2022). Mahmood, Waqar ; Shahzadi, Rehab ; Ghani, Muhammad Usman ; Asim, Muhammad Nabeel ; Ghafoor, Hina ; Mehmood, Faiza.
    In: Applied Energy.
    RePEc:eee:appene:v:324:y:2022:i:c:s0306261922010388.

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30. Quad-kernel deep convolutional neural network for intra-hour photovoltaic power forecasting. (2022). Liu, Yongqian ; Ren, Xiaoying ; Zhu, Honglu ; Zhang, Fei.
    In: Applied Energy.
    RePEc:eee:appene:v:323:y:2022:i:c:s0306261922009801.

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31. Ridge regression ensemble of machine learning models applied to solar and wind forecasting in Brazil and Spain. (2022). Carneiro, Tatiane C ; Fernandez-Ramirez, Luis M.
    In: Applied Energy.
    RePEc:eee:appene:v:314:y:2022:i:c:s0306261922003555.

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32. Hour-ahead photovoltaic generation forecasting method based on machine learning and multi objective optimization algorithm. (2022). Li, Zhiwu ; Zhou, Yilin ; Wang, Jianzhou.
    In: Applied Energy.
    RePEc:eee:appene:v:312:y:2022:i:c:s0306261922001830.

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33. Prediction of Solar Power Using Near-Real Time Satellite Data. (2021). Kay, Merlinde ; Prasad, Abhnil Amtesh.
    In: Energies.
    RePEc:gam:jeners:v:14:y:2021:i:18:p:5865-:d:636858.

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34. MPF-Net: A computational multi-regional solar power forecasting framework. (2021). Mahmood, Waqar ; Shahzadi, Rehab ; Ghani, Muhammad Usman ; Asim, Muhammad Nabeel ; Mehmood, Faiza.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:151:y:2021:i:c:s1364032121008376.

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35. Post-processing in solar forecasting: Ten overarching thinking tools. (2021). van der Meer, Dennis ; Yang, Dazhi.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:140:y:2021:i:c:s1364032121000307.

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36. Hybrid deep neural model for hourly solar irradiance forecasting. (2021). Huang, Xiaoqiao ; Liu, Wuming ; Zhang, Jun ; Shi, Junsheng ; Gao, Bixuan ; Chen, Zaiqing ; Tai, Yonghang.
    In: Renewable Energy.
    RePEc:eee:renene:v:171:y:2021:i:c:p:1041-1060.

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37. Photovoltaic power forecasting based on GA improved Bi-LSTM in microgrid without meteorological information. (2021). Ji, Zhengsen ; Shi, Yucheng ; Xu, Xiaomin ; Wang, Keke ; Zhen, Hao ; Niu, Dongxiao.
    In: Energy.
    RePEc:eee:energy:v:231:y:2021:i:c:s0360544221011567.

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38. Prediction of solar energy guided by pearson correlation using machine learning. (2021). Kabbaj, Mohammed Issam ; Jebli, Imane ; Belouadha, Fatima-Zahra ; Tilioua, Amine.
    In: Energy.
    RePEc:eee:energy:v:224:y:2021:i:c:s0360544221003583.

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39. Assessing new intra-daily temperature-based machine learning models to outperform solar radiation predictions in different conditions. (2021). Bellido-Jimenez, Juan Antonio ; Gualda, Javier Estevez ; Garcia-Marin, Amanda Penelope.
    In: Applied Energy.
    RePEc:eee:appene:v:298:y:2021:i:c:s0306261921006358.

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40. Short-term solar power forecasting: Investigating the ability of deep learning models to capture low-level utility-scale Photovoltaic system behaviour. (2021). Strauss, J M ; Rix, A J ; du Plessis, A A.
    In: Applied Energy.
    RePEc:eee:appene:v:285:y:2021:i:c:s0306261920317657.

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41. Comparison of Implicit vs. Explicit Regime Identification in Machine Learning Methods for Solar Irradiance Prediction. (2020). McCandless, Tyler ; Dettling, Susan ; Haupt, Sue Ellen.
    In: Energies.
    RePEc:gam:jeners:v:13:y:2020:i:3:p:689-:d:316869.

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42. Intra-day solar irradiation forecast using RLS filters and satellite images. (2020). Alonso-Suarez, Rodrigo ; Marchesoni-Acland, Franco.
    In: Renewable Energy.
    RePEc:eee:renene:v:161:y:2020:i:c:p:1140-1154.

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43. Short-term global horizontal irradiance forecasting based on a hybrid CNN-LSTM model with spatiotemporal correlations. (2020). Wei, Zhinong ; Sun, LI ; Liu, Ling ; Cheng, Lilin ; Zang, Haixiang.
    In: Renewable Energy.
    RePEc:eee:renene:v:160:y:2020:i:c:p:26-41.

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44. A novel electrical net-load forecasting model based on deep neural networks and wavelet transform integration. (2020). Niknam, Taher ; Hashemi, Sattar ; Norouzi, Mohammadali ; Alipour, Mohammadali ; Lehtonen, Matti ; Aghaei, Jamshid.
    In: Energy.
    RePEc:eee:energy:v:205:y:2020:i:c:s0360544220312135.

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45. Forecasting the industrial solar energy consumption using a novel seasonal GM(1,1) model with dynamic seasonal adjustment factors. (2020). Wang, Zhi-Wei ; Li, Qin.
    In: Energy.
    RePEc:eee:energy:v:200:y:2020:i:c:s0360544220305673.

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46. Can we justify producing univariate machine-learning forecasts with satellite-derived solar irradiance?. (2020). Gandhi, Oktoviano ; Yagli, Gokhan Mert ; Srinivasan, Dipti ; Yang, Dazhi.
    In: Applied Energy.
    RePEc:eee:appene:v:259:y:2020:i:c:s0306261919318094.

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47. Time series prediction for output of multi-region solar power plants. (2020). Zheng, Taicheng ; Liao, QI ; Zhang, Haoran ; Wang, Bohong ; Dai, Yuanhao ; Liang, Yongtu ; Song, Xuan.
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    RePEc:eee:appene:v:257:y:2020:i:c:s0306261919316885.

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48. Photovoltaic power forecasting based LSTM-Convolutional Network. (2019). Qi, Xiaoxia ; Wang, Kejun ; Liu, Hongda.
    In: Energy.
    RePEc:eee:energy:v:189:y:2019:i:c:s0360544219319206.

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49. A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network. (2019). Qi, Xiaoxia ; Wang, Kejun ; Liu, Hongda.
    In: Applied Energy.
    RePEc:eee:appene:v:251:y:2019:i:c:30.

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