Open Access
Issue |
Renew. Energy Environ. Sustain.
Volume 8, 2023
|
|
---|---|---|
Article Number | 18 | |
Number of page(s) | 12 | |
DOI | https://doi.org/10.1051/rees/2023018 | |
Published online | 22 September 2023 |
- S. Sobria, S. Koohi-Kamalia, N.A. Rahima, Solar photovoltaic generation forecasting methods: a review, Energy Convers. Manag. 156, 459 (2018) [CrossRef] [Google Scholar]
- D. Yang et al., A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: towards carbon neutrality, Renew. Energy Environ. Sustain. 161, 112348 (2022) [CrossRef] [Google Scholar]
- B.J. Martins et al., Systematic review of nowcasting approaches for solar energy production based upon ground-based cloud imaging, Sol. Energy Adv. 2, 100019 (2022) [CrossRef] [Google Scholar]
- B. Nouri et al., Probabilistic solar nowcasting based on all-sky imagers, Sol. Energy 253, 285 (2023) [CrossRef] [Google Scholar]
- A.T. Lorenzo, W.F. Holmgren, A.D. Cronin, Irradiance forecasts based on an irradiance monitoring network, cloud motion, and spatial averaging, Sol. Energy 122, 1158 (2015) [CrossRef] [Google Scholar]
- X. Chen et al., Sensor network based PV power nowcasting with spatio-temporal preselection for grid-friendly control, Appl. Energy 255, 113760 (2019) [CrossRef] [Google Scholar]
- T. Schmidt et al., Short-term solar forecasting based on sky images to enable higher PV generation in remote electricity networks, Renew. Energy Environ. Sustain. 2, 23 (2017) [CrossRef] [EDP Sciences] [Google Scholar]
- Z. Peng et al., 3D cloud detection and tracking system for solar forecast using multiple sky imagers, Sol. Energy 118, 496 (2015) [CrossRef] [Google Scholar]
- Z. Peng et al., A hybrid approach to estimate the complex motions of clouds in sky images, Sol. Energy 138, 10 (2016) [CrossRef] [Google Scholar]
- B. Nouri et al., Cloud height and tracking accuracy of three all sky imager systems for individual clouds, Sol. Energy 177, 213 (2019) [CrossRef] [Google Scholar]
- F.J. Rodríguez-Benítez et al., Assessment of new solar radiation nowcasting methods based on sky-camera and satellite imagery, Appl. Energy 292, 116838 (2021) [CrossRef] [Google Scholar]
- A.H. Eslik et al., Short-term solar radiation forecasting with a novel image processing-based deep learning approach, Renew. Energy 200, 1490 (2022) [CrossRef] [Google Scholar]
- T. Bando et al., Statistical analysis of cloud layers and derivation of motion directions of two layer clouds, IEEJ Trans. Power Energy 142, 490 (2022) [Google Scholar]
- J. Kleissl, Solar energy forecasting and resource assessment (Elsevier, 2013) [Google Scholar]
- R. Blaga, M. Paulescu, Quantifiers for the solar irradiance variability: a new perspective, Sol. Energy 174, 606 (2018) [CrossRef] [Google Scholar]
- R. Tapakis, A.G. Charalambides, Equipment and methodologies for cloud detection and classification: a review, Sol. Energy 95, 392 (2013) [CrossRef] [Google Scholar]
- P.D. Clift, R. Alan Plumb, The Asian monsoon causes, history and effects (Cambridge University Press, 2008) [CrossRef] [Google Scholar]
- K.-J. Ha et al., Variability in the East Asian monsoon: a review, Meteorol. Appl. 19, 200 (2012) [CrossRef] [Google Scholar]
- K.-J. Ha et al., Linkages between the South and East Asian summer monsoons: a review and revisit, Clim Dyn. 51 4207 (2018) [CrossRef] [Google Scholar]
- K. Venkata Subrahmanyam, K. Kishore Kumar, CloudSat observations of multi layered clouds across the globe, Clim Dyn. 49, 327 (2017) [CrossRef] [Google Scholar]
- J.M. Haynes et al., Low cloud detection in multilayer scenes using satellite imagery with machine learning methods, J. Atmos. Ocean. Technol. 39, 319 (2022) [CrossRef] [Google Scholar]
- A.A. Piedehierro et al., Evaluation of enhancement events of total solar irradiance during cloudy conditions at Granada (Southeastern Spain), Atmos. Res. 135–136, 1 (2014) [Google Scholar]
- R. Tapakis, A.G. Charalambides, Enhanced values of global irradiance due to the presence of clouds in Eastern Mediterranean, Renew. Energy 62, 459 (2014) [CrossRef] [Google Scholar]
- R.C. de Andrade, C. Tiba, Extreme global solar irradiance due to cloud enhancement in northeastern Brazil, Renew. Energy 86, 1433 (2016) [CrossRef] [Google Scholar]
- R.H. Inman, Y. Chu, C.F.M. Coimbra, Cloud enhancement of global horizontal irradiance in California and Hawaii, Sol. Energy 130, 128 (2016) [CrossRef] [Google Scholar]
- A. Castillejo-Cubero, R. Escobar, Detection and characterization of cloud enhancement events for solar irradiance using a model-independent, statistically-driven approach, Sol. Energy 209, 547 (2020) [CrossRef] [Google Scholar]
- A.K. Yadav, S.S. Chandel, Tilt angle optimization to maximize incident solar radiation: a review, Renew. Energy Environ. Sustain. 23, 503 (2013) [CrossRef] [Google Scholar]
- V. Badescu, Modeling solar radiation at the earth's surface (Springer, 2008) [Google Scholar]
- G. Notton et al., Calculation of solar irradiance profiles from hourly data to simulate energy systems behaviour, Renew. Energy 27, 123 (2002) [CrossRef] [Google Scholar]
- A.M. Whitman, A simple expression for the equation of time, J. North Am. Sundial Soc. 14, 29 (2003) [Google Scholar]
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