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Статті в журналах з теми "SOLAR POWER FORECASTING"
El hendouzi, Abdelhakim, and Abdennaser Bourouhou. "Solar Photovoltaic Power Forecasting." Journal of Electrical and Computer Engineering 2020 (December 31, 2020): 1–21. http://dx.doi.org/10.1155/2020/8819925.
Повний текст джерелаK., D., and Isha I. "Solar Power Forecasting: A Review." International Journal of Computer Applications 145, no. 6 (July 15, 2016): 28–50. http://dx.doi.org/10.5120/ijca2016910728.
Повний текст джерелаIheanetu, Kelachukwu J. "Solar Photovoltaic Power Forecasting: A Review." Sustainability 14, no. 24 (December 19, 2022): 17005. http://dx.doi.org/10.3390/su142417005.
Повний текст джерелаKim, Kihan, and Jin Hur. "Weighting Factor Selection of the Ensemble Model for Improving Forecast Accuracy of Photovoltaic Generating Resources." Energies 12, no. 17 (August 28, 2019): 3315. http://dx.doi.org/10.3390/en12173315.
Повний текст джерелаDivya, R., and S. Umamaheswari. "Solar Power Forecasting Methods – A Review." International Journal of Advanced Science and Engineering 9, no. 1 (August 1, 2022): 2591–98. http://dx.doi.org/10.29294/ijase.9.1.2022.2591-2598.
Повний текст джерелаOkhorzina, Alena, Alexey Yurchenko, and Artem Kozloff. "Autonomous Solar-Wind Power Forecasting Systems." Advanced Materials Research 1097 (April 2015): 59–62. http://dx.doi.org/10.4028/www.scientific.net/amr.1097.59.
Повний текст джерелаBacher, Peder, Henrik Madsen, and Henrik Aalborg Nielsen. "Online short-term solar power forecasting." Solar Energy 83, no. 10 (October 2009): 1772–83. http://dx.doi.org/10.1016/j.solener.2009.05.016.
Повний текст джерелаKumar, R. Dhilip, Prakash K, P. Abirama Sundari, and Sathya S. "A Hybrid Machine Learning Model for Solar Power Forecasting." E3S Web of Conferences 387 (2023): 04003. http://dx.doi.org/10.1051/e3sconf/202338704003.
Повний текст джерелаNath, N. C., W. Sae-Tang, and C. Pirak. "Machine Learning-Based Solar Power Energy Forecasting." Journal of the Society of Automotive Engineers Malaysia 4, no. 3 (September 1, 2020): 307–22. http://dx.doi.org/10.56381/jsaem.v4i3.25.
Повний текст джерелаArias, Mariz B., and Sungwoo Bae. "Design Models for Power Flow Management of a Grid-Connected Solar Photovoltaic System with Energy Storage System." Energies 13, no. 9 (April 29, 2020): 2137. http://dx.doi.org/10.3390/en13092137.
Повний текст джерелаДисертації з теми "SOLAR POWER FORECASTING"
Wang, Zheng. "Solar Power Forecasting." Thesis, The University of Sydney, 2019. https://hdl.handle.net/2123/21248.
Повний текст джерелаIsaksson, Emil, and Conde Mikael Karpe. "Solar Power Forecasting with Machine Learning Techniques." Thesis, KTH, Matematisk statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229065.
Повний текст джерелаSänkta produktionskostnader och ökad effektivitet har de senaste åren gjort solceller till ett attraktivt alternativ som energikälla. Detta har lett till en stor ökning av dess användning runt om i världen. Parallellt med denna utveckling har större tillgänglighet av data samt datorers förbättrade beräkningskapacitet möjliggjort förbättrade prediktionsresultat för maskininlärningsmetoder. Det finns för många aktörer anledning att intressera sig för prediktion av solcellers energiproduktion och från denna utgångspunkt kan maskininlärningsmetoder samt tidsserieanalys användas. I denna studie jämför vi hur metoder från de båda fälten presterar på fem olika geografiska områden i Sverige. Vi finner att tidsseriemodeller är komplicerade att implementera på grund av solcellernas icke-stationära tidsserier. I kontrast till detta visar sig maskininlärningstekniker enklare att implementera. Specifikt finner vi att artificiella neurala nätverk och så kallade Gradient Boosting Regression Trees presterar bäst i genomsnitt över de olika geografiska områdena.
Almquist, Isabelle, Ellen Lindblom, and Alfred Birging. "Workplace Electric Vehicle Solar Smart Charging based on Solar Irradiance Forecasting." Thesis, Uppsala universitet, Institutionen för teknikvetenskaper, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-323319.
Повний текст джерелаKim, Byungyu. "Solar Energy Generation Forecasting and Power Output Optimization of Utility Scale Solar Field." DigitalCommons@CalPoly, 2020. https://digitalcommons.calpoly.edu/theses/2149.
Повний текст джерелаD, Pepe. "New techniques for solar power forecasting and building energy management." Doctoral thesis, Università di Siena, 2019. http://hdl.handle.net/11365/1072873.
Повний текст джерелаRudd, Timothy Robert. "BENEFITS OF NEAR-TERM CLOUD LOCATION FORECASTING FOR LARGE SOLAR PV." DigitalCommons@CalPoly, 2011. https://digitalcommons.calpoly.edu/theses/597.
Повний текст джерелаvan, der Meer Dennis. "Spatio-temporal probabilistic forecasting of solar power, electricity consumption and net load." Licentiate thesis, Uppsala universitet, Fasta tillståndets fysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-363448.
Повний текст джерелаBarbieri, Florian Benjamin Eric. "Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking." Thesis, Curtin University, 2019. http://hdl.handle.net/20.500.11937/77126.
Повний текст джерелаUppling, Hugo, and Adam Eriksson. "Single and multiple step forecasting of solar power production: applying and evaluating potential models." Thesis, Uppsala universitet, Institutionen för teknikvetenskaper, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-384340.
Повний текст джерелаLorenzo, Antonio Tomas, and Antonio Tomas Lorenzo. "Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation." Diss., The University of Arizona, 2017. http://hdl.handle.net/10150/624494.
Повний текст джерелаКниги з теми "SOLAR POWER FORECASTING"
United States. Bureau of Labor Statistics, ed. Careers in solar power. Washington, D.C.]: U.S. Bureau of Labor Statistics, 2011.
Знайти повний текст джерелаRay, George, Bush Brian, National Renewable Energy Laboratory (U.S.), and Colorado Renewable Energy Conference (2009), eds. Estimating solar PV output using modern space/time geostatistics. Golden, Colo.]: National Renewable Energy Laboratory, 2009.
Знайти повний текст джерелаNational Renewable Energy Laboratory (U.S.) and IEEE Photovoltaic Specialists Conference (37th : 2011 : Seattle, Wash.), eds. An economic analysis of photovoltaics versus traditional energy sources: Where are we now and where might we be in the near future? : preprint. Golden, Colo.]: National Renewable Energy Laboratory, 2011.
Знайти повний текст джерелаSolar Energy Technologies Program (U.S.), National Renewable Energy Laboratory (U.S.), and IEEE Photovoltaic Specialists Conference (37th : 2011 : Seattle, Wash.), eds. An economic analysis of photovoltaics versus traditional energy sources: Where are we now and where might we be in the near future? [Golden, Colo.]: National Renewable Energy Laboratory, U.S. Dept. of Energy, Office of Energy Efficienty and Renewable Energy, 2011.
Знайти повний текст джерелаPaulescu, Marius. Weather Modeling and Forecasting of PV Systems Operation. London: Springer London, 2013.
Знайти повний текст джерелаLipták, Béla G. Post-oil energy technology: The world's first solar-hydrogen demonstration power plant. Boca Raton: CRC Press, 2009.
Знайти повний текст джерелаEuropean Commission. Directorate-General for Energy and European Photovoltaic Industry Association, eds. Photovoltaics in 2010. Luxembourg: Office for Official Publications of the European Communities, 1996.
Знайти повний текст джерелаNelson, Brent P. Potential of Photovoltaics. Washington, D.C: National Renewable Energy Laboratory, 2008.
Знайти повний текст джерелаLiptak, Bela G. Post-oil energy technology: After the age of fossil fuels. Boca Raton, Fl: Taylor & Francis, 2008.
Знайти повний текст джерелаWiley, John. Photovoltaic Materials: An Analysis of Emerging Technology and Markets (Technical Insights, R-259). John Wiley & Sons Inc, 1999.
Знайти повний текст джерелаЧастини книг з теми "SOLAR POWER FORECASTING"
Khurana, Agrim, Ankit Dabas, Vaibhav Dhand, Rahul Kumar, Bhavnesh Kumar, and Arjun Tyagi. "Solar Power Forecasting." In Artificial Intelligence for Solar Photovoltaic Systems, 23–41. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003222286-2.
Повний текст джерелаZack, John W. "Wind and Solar Forecasting." In Power Electronics and Power Systems, 135–65. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55581-2_4.
Повний текст джерелаWang, Zheng, Irena Koprinska, and Mashud Rana. "Solar Power Forecasting Using Pattern Sequences." In Artificial Neural Networks and Machine Learning – ICANN 2017, 486–94. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68612-7_55.
Повний текст джерелаSyu, Jia-Hao, Chi-Fang Chao, and Mu-En Wu. "Forecasting System for Solar-Power Generation." In Recent Challenges in Intelligent Information and Database Systems, 65–72. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1685-3_6.
Повний текст джерелаPiazza, Antonino, and Giuseppe Faso. "Concentrated Solar Power: Ontologies for Solar Radiation Modeling and Forecasting." In Advances in Intelligent Systems and Computing, 325–37. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03992-3_23.
Повний текст джерелаShareef Syed, Mahaboob, Ch V. Suresh, B. Sreenivasa Raju, M. Ravindra Babu, and Y. S. Kishore Babu. "Forecasting of Wind Power Using Hybrid Machine Learning Approach." In Wind and Solar Energy Applications, 27–34. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003321897-3.
Повний текст джерелаLin, Yang, Irena Koprinska, Mashud Rana, and Alicia Troncoso. "Pattern Sequence Neural Network for Solar Power Forecasting." In Communications in Computer and Information Science, 727–37. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36802-9_77.
Повний текст джерелаDahl, Astrid, and Edwin Bonilla. "Scalable Gaussian Process Models for Solar Power Forecasting." In Data Analytics for Renewable Energy Integration: Informing the Generation and Distribution of Renewable Energy, 94–106. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71643-5_9.
Повний текст джерелаSampathraja, N., L. Ashok Kumar, R. Saravana Kumar, and I. Made Wartana. "Solar Power Forecasting Using Adaptive Curve-Fitting Algorithm." In Proceedings of International Conference on Artificial Intelligence, Smart Grid and Smart City Applications, 227–36. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-24051-6_22.
Повний текст джерелаMohammed, Azhar Ahmed, Waheeb Yaqub, and Zeyar Aung. "Probabilistic Forecasting of Solar Power: An Ensemble Learning Approach." In Intelligent Decision Technologies, 449–58. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19857-6_38.
Повний текст джерелаТези доповідей конференцій з теми "SOLAR POWER FORECASTING"
Bacher, Peder, Henrik Madsen, and Bengt Perers. "Short-Term Solar Collector Power Forecasting." In ISES Solar World Congress 2011. Freiburg, Germany: International Solar Energy Society, 2011. http://dx.doi.org/10.18086/swc.2011.28.03.
Повний текст джерелаJascourt, Stephen D., Daniel Kirk-Davidhoff, and Christopher Cassidy. "Forecasting Solar Power and Irradiance – Lessons from Real-World Experiences." In American Solar Energy Society National Solar Conference 2016. Freiburg, Germany: International Solar Energy Society, 2016. http://dx.doi.org/10.18086/solar.2016.01.15.
Повний текст джерелаLee, Jeong-In, Young-Mee Shin, Il-Woo Lee Energy, and Sang-Ha Kim. "Solar Power Generation Forecasting Service." In 2019 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2019. http://dx.doi.org/10.1109/ictc46691.2019.8939757.
Повний текст джерелаPanamtash, Hossein, and Qun Zhou. "Coherent Probabilistic Solar Power Forecasting." In 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE, 2018. http://dx.doi.org/10.1109/pmaps.2018.8440483.
Повний текст джерелаWanady, Irene, Aparna Viswanath, and Kaushik Mahata. "Solar Forecasting for Power System Operator." In 2018 IEEE Electrical Power and Energy Conference (EPEC). IEEE, 2018. http://dx.doi.org/10.1109/epec.2018.8598379.
Повний текст джерелаChen, Zezhou, and Irena Koprinska. "Ensemble Methods for Solar Power Forecasting." In 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020. http://dx.doi.org/10.1109/ijcnn48605.2020.9206713.
Повний текст джерелаAbuella, Mohamed, and Badrul Chowdhury. "Hourly probabilistic forecasting of solar power." In 2017 North American Power Symposium (NAPS). IEEE, 2017. http://dx.doi.org/10.1109/naps.2017.8107270.
Повний текст джерелаShedbalkar, Kaustubha H., and D. S. More. "Bayesian Regression for Solar Power Forecasting." In 2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP). IEEE, 2022. http://dx.doi.org/10.1109/aisp53593.2022.9760559.
Повний текст джерелаShedbalkar, Kaustubha H., and D. S. More. "Bayesian Regression for Solar Power Forecasting." In 2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP). IEEE, 2022. http://dx.doi.org/10.1109/aisp53593.2022.9760559.
Повний текст джерелаAmreen, T. Sana, Radharani Panigrahi, and N. R. Patne. "Solar Power Forecasting Using Hybrid Model." In 2023 5th International Conference on Energy, Power and Environment: Towards Flexible Green Energy Technologies (ICEPE). IEEE, 2023. http://dx.doi.org/10.1109/icepe57949.2023.10201483.
Повний текст джерелаЗвіти організацій з теми "SOLAR POWER FORECASTING"
Haupt, Sue Ellen. A Public-Private-Acadmic Partnership to Advance Solar Power Forecasting. Office of Scientific and Technical Information (OSTI), April 2016. http://dx.doi.org/10.2172/1408392.
Повний текст джерелаMarquis, Melinda, Stan Benjamin, Eric James, kathy Lantz, and Christine Molling. A Public-Private-Academic Partnership to Advance Solar Power Forecasting. Office of Scientific and Technical Information (OSTI), April 2015. http://dx.doi.org/10.2172/1422824.
Повний текст джерела