IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v96y2012icp12-20.html
   My bibliography  Save this item

Evaluating the quality of scenarios of short-term wind power generation

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Yuan, Ran & Wang, Bo & Mao, Zhixin & Watada, Junzo, 2021. "Multi-objective wind power scenario forecasting based on PG-GAN," Energy, Elsevier, vol. 226(C).
  2. Zhang, Yao & Wang, Jianxue & Wang, Xifan, 2014. "Review on probabilistic forecasting of wind power generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 255-270.
  3. Mike Ludkovski & Glen Swindle & Eric Grannan, 2022. "Large Scale Probabilistic Simulation of Renewables Production," Papers 2205.04736, arXiv.org.
  4. Poncela, Marta & Poncela, Pilar & Perán, José Ramón, 2013. "Automatic tuning of Kalman filters by maximum likelihood methods for wind energy forecasting," Applied Energy, Elsevier, vol. 108(C), pages 349-362.
  5. Peru Muniain & Florian Ziel, 2018. "Probabilistic Forecasting in Day-Ahead Electricity Markets: Simulating Peak and Off-Peak Prices," Papers 1810.08418, arXiv.org, revised Dec 2019.
  6. Zhang, Menglin & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Zuo, Wenping & Chen, Zhe & Wen, Jinyu, 2018. "A systematic approach for the joint dispatch of energy and reserve incorporating demand response," Applied Energy, Elsevier, vol. 230(C), pages 1279-1291.
  7. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
  8. Rachunok, Benjamin & Staid, Andrea & Watson, Jean-Paul & Woodruff, David L., 2020. "Assessment of wind power scenario creation methods for stochastic power systems operations," Applied Energy, Elsevier, vol. 268(C).
  9. Arrieta-Prieto, Mario & Schell, Kristen R., 2022. "Spatio-temporal probabilistic forecasting of wind power for multiple farms: A copula-based hybrid model," International Journal of Forecasting, Elsevier, vol. 38(1), pages 300-320.
  10. Oliver Grothe & Fabian Kachele & Fabian Kruger, 2022. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Papers 2204.10154, arXiv.org.
  11. Gensler, André & Sick, Bernhard & Vogt, Stephan, 2018. "A review of uncertainty representations and metaverification of uncertainty assessment techniques for renewable energies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 352-379.
  12. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2020. "Spatial and temporal correlation analysis of wind power between different provinces in China," Energy, Elsevier, vol. 191(C).
  13. Yongjie Luo & Qinghao Meng & Yuan Chi & Qianggang Wang & Yongshou Zeng & Zaoming Deng & Yao Zou, 2024. "A Low-Carbon Optimal Operation Method for an Industrial Park Multi-Energy Coupling System Utilizing By-Product Hydrogen," Sustainability, MDPI, vol. 16(6), pages 1-24, March.
  14. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Pan, Bo & Qi, Shiqiang, 2020. "Two-stage stochastic optimal operation of integrated electricity and heat system considering reserve of flexible devices and spatial-temporal correlation of wind power," Applied Energy, Elsevier, vol. 275(C).
  15. Hilger, Hannes & Witthaut, Dirk & Dahmen, Manuel & Rydin Gorjão, Leonardo & Trebbien, Julius & Cramer, Eike, 2024. "Multivariate scenario generation of day-ahead electricity prices using normalizing flows," Applied Energy, Elsevier, vol. 367(C).
  16. Li, Jinghua & Zhou, Jiasheng & Chen, Bo, 2020. "Review of wind power scenario generation methods for optimal operation of renewable energy systems," Applied Energy, Elsevier, vol. 280(C).
  17. Nuño Martinez, Edgar & Cutululis, Nicolaos & Sørensen, Poul, 2018. "High dimensional dependence in power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 197-213.
  18. Rahimiyan, Morteza, 2014. "A statistical cognitive model to assess impact of spatially correlated wind production on market behaviors," Applied Energy, Elsevier, vol. 122(C), pages 62-72.
  19. Xiao, Yunpeng & Wang, Xifan & Wang, Xiuli & Dang, Can & Lu, Ming, 2016. "Behavior analysis of wind power producer in electricity market," Applied Energy, Elsevier, vol. 171(C), pages 325-335.
  20. C. Alexander & M. Coulon & Y. Han & X. Meng, 2024. "Evaluating the discrimination ability of proper multi-variate scoring rules," Annals of Operations Research, Springer, vol. 334(1), pages 857-883, March.
  21. Yannik Pflugfelder & Aiko Schinke-Nendza & Jonathan Dumas & Christoph Weber, 2024. "Deriving multivariate probabilistic solar generation forecasts based on hourly imbalanced data," EWL Working Papers 2407, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Nov 2024.
  22. Ricardo J. Bessa & Corinna Möhrlen & Vanessa Fundel & Malte Siefert & Jethro Browell & Sebastian Haglund El Gaidi & Bri-Mathias Hodge & Umit Cali & George Kariniotakis, 2017. "Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry," Energies, MDPI, vol. 10(9), pages 1-48, September.
  23. Xu, Jian & Wang, Jing & Liao, Siyang & Sun, Yuanzhang & Ke, Deping & Li, Xiong & Liu, Ji & Jiang, Yibo & Wei, Congying & Tang, Bowen, 2018. "Stochastic multi-objective optimization of photovoltaics integrated three-phase distribution network based on dynamic scenarios," Applied Energy, Elsevier, vol. 231(C), pages 985-996.
  24. Gilbert, Ciaran & Browell, Jethro & McMillan, David, 2021. "Probabilistic access forecasting for improved offshore operations," International Journal of Forecasting, Elsevier, vol. 37(1), pages 134-150.
  25. Muniain, Peru & Ziel, Florian, 2020. "Probabilistic forecasting in day-ahead electricity markets: Simulating peak and off-peak prices," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1193-1210.
  26. Grothe, Oliver & Kächele, Fabian & Krüger, Fabian, 2023. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Energy Economics, Elsevier, vol. 120(C).
  27. Ilias G. Marneris & Pandelis N. Biskas & Anastasios G. Bakirtzis, 2017. "Stochastic and Deterministic Unit Commitment Considering Uncertainty and Variability Reserves for High Renewable Integration," Energies, MDPI, vol. 10(1), pages 1-25, January.
  28. Iversen, Emil B. & Morales, Juan M. & Møller, Jan K. & Madsen, Henrik, 2016. "Short-term probabilistic forecasting of wind speed using stochastic differential equations," International Journal of Forecasting, Elsevier, vol. 32(3), pages 981-990.
  29. Zheng, Kedi & Chen, Huiyao & Wang, Yi & Chen, Qixin, 2022. "Data-driven financial transmission right scenario generation and speculation," Energy, Elsevier, vol. 238(PC).
  30. Chen, Xianqing & Dong, Wei & Yang, Qiang, 2022. "Robust optimal capacity planning of grid-connected microgrid considering energy management under multi-dimensional uncertainties," Applied Energy, Elsevier, vol. 323(C).
  31. Ma, Chao & Xu, Ximeng & Pang, Xiulan & Li, Xiaofeng & Zhang, Pengfei & Liu, Lu, 2024. "Scenario-based ultra-short-term rolling optimal operation of a photovoltaic-energy storage system under forecast uncertainty," Applied Energy, Elsevier, vol. 356(C).
  32. Tang, Chenghui & Wang, Yishen & Xu, Jian & Sun, Yuanzhang & Zhang, Baosen, 2018. "Efficient scenario generation of multiple renewable power plants considering spatial and temporal correlations," Applied Energy, Elsevier, vol. 221(C), pages 348-357.
  33. 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.
  34. Chapaloglou, Spyridon & Varagnolo, Damiano & Marra, Francesco & Tedeschi, Elisabetta, 2022. "Data-driven energy management of isolated power systems under rapidly varying operating conditions," Applied Energy, Elsevier, vol. 314(C).
  35. Jon Olauson & Johan Bladh & Joakim Lönnberg & Mikael Bergkvist, 2016. "A New Approach to Obtain Synthetic Wind Power Forecasts for Integration Studies," Energies, MDPI, vol. 9(10), pages 1-16, October.
  36. Golestaneh, Faranak & Gooi, Hoay Beng & Pinson, Pierre, 2016. "Generation and evaluation of space–time trajectories of photovoltaic power," Applied Energy, Elsevier, vol. 176(C), pages 80-91.
  37. Müller, Alfred & Reuber, Matthias, 2023. "A copula-based time series model for global horizontal irradiation," International Journal of Forecasting, Elsevier, vol. 39(2), pages 869-883.
  38. Cramer, Eike & Witthaut, Dirk & Mitsos, Alexander & Dahmen, Manuel, 2023. "Multivariate probabilistic forecasting of intraday electricity prices using normalizing flows," Applied Energy, Elsevier, vol. 346(C).
  39. Chen, Jun & Rabiti, Cristian, 2017. "Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems," Energy, Elsevier, vol. 120(C), pages 507-517.
  40. Pinto, Mauro S.S. & Miranda, Vladimiro & Saavedra, Osvaldo R., 2016. "Risk and unit commitment decisions in scenarios of wind power uncertainty," Renewable Energy, Elsevier, vol. 97(C), pages 550-558.
  41. Florian Ziel & Kevin Berk, 2019. "Multivariate Forecasting Evaluation: On Sensitive and Strictly Proper Scoring Rules," Papers 1910.07325, arXiv.org.
  42. Xu, Bin & Zhu, Feilin & Zhong, Ping-an & Chen, Juan & Liu, Weifeng & Ma, Yufei & Guo, Le & Deng, Xiaoliang, 2019. "Identifying long-term effects of using hydropower to complement wind power uncertainty through stochastic programming," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
  43. Roy, Sanjoy, 2014. "Performance prediction of active pitch-regulated wind turbine with short duration variations in source wind," Applied Energy, Elsevier, vol. 114(C), pages 700-708.
  44. Mousavizadeh, Saeed & Haghifam, Mahmoud-Reza & Shariatkhah, Mohammad-Hossein, 2018. "A linear two-stage method for resiliency analysis in distribution systems considering renewable energy and demand response resources," Applied Energy, Elsevier, vol. 211(C), pages 443-460.
  45. Elberg, Christina & Hagspiel, Simeon, 2015. "Spatial dependencies of wind power and interrelations with spot price dynamics," European Journal of Operational Research, Elsevier, vol. 241(1), pages 260-272.
  46. Camal, S. & Teng, F. & Michiorri, A. & Kariniotakis, G. & Badesa, L., 2019. "Scenario generation of aggregated Wind, Photovoltaics and small Hydro production for power systems applications," Applied Energy, Elsevier, vol. 242(C), pages 1396-1406.
  47. Busiswe Skosana & Mukwanga W. Siti & Nsilulu T. Mbungu & Sonu Kumar & Willy Mulumba, 2023. "An Evaluation of Potential Strategies in Renewable Energy Systems and Their Importance for South Africa—A Review," Energies, MDPI, vol. 16(22), pages 1-27, November.
  48. Didem Sarı Ay & Sarah M. Ryan, 2019. "Observational data-based quality assessment of scenario generation for stochastic programs," Computational Management Science, Springer, vol. 16(3), pages 521-540, July.
  49. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).
  50. Zendehboudi, Sohrab & Rezaei, Nima & Lohi, Ali, 2018. "Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review," Applied Energy, Elsevier, vol. 228(C), pages 2539-2566.
  51. Gao, Cuixia & Sun, Mei & Geng, Yong & Wu, Rui & Chen, Wei, 2016. "A bibliometric analysis based review on wind power price," Applied Energy, Elsevier, vol. 182(C), pages 602-612.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.