Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems
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DOI: 10.1016/j.energy.2016.11.103
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Citations
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Cited by:
- Yuan, Ran & Wang, Bo & Mao, Zhixin & Watada, Junzo, 2021. "Multi-objective wind power scenario forecasting based on PG-GAN," Energy, Elsevier, vol. 226(C).
- Rigby, Aidan & Baker, Una & Lindley, Benjamin & Wagner, Michael, 2024. "Generation and validation of comprehensive synthetic weather histories using auto-regressive moving-average models," Renewable Energy, Elsevier, vol. 224(C).
- Yuan, Xiaohui & Tan, Qingxiong & Lei, Xiaohui & Yuan, Yanbin & Wu, Xiaotao, 2017. "Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine," Energy, Elsevier, vol. 129(C), pages 122-137.
- Julio César Cuenca Tinitana & Carlos Adrian Correa-Florez & Diego Patino & José Vuelvas, 2020. "Spatio-Temporal Kriging Based Economic Dispatch Problem Including Wind Uncertainty," Energies, MDPI, vol. 13(23), pages 1-26, December.
- Diego Francisco Larios & Enrique Personal & Antonio Parejo & Sebastián García & Antonio García & Carlos Leon, 2020. "Operational Simulation Environment for SCADA Integration of Renewable Resources," Energies, MDPI, vol. 13(6), pages 1-37, March.
- Wang, Zheng-Xin & Li, Qin & Pei, Ling-Ling, 2018. "A seasonal GM(1,1) model for forecasting the electricity consumption of the primary economic sectors," Energy, Elsevier, vol. 154(C), pages 522-534.
- Jia Zhou & Hany Abdel-Khalik & Paul Talbot & Cristian Rabiti, 2021. "A Hybrid Energy System Workflow for Energy Portfolio Optimization," Energies, MDPI, vol. 14(15), pages 1-28, July.
- Karakoyun, Ece Cigdem & Avci, Harun & Kocaman, Ayse Selin & Nadar, Emre, 2023. "Deviations from commitments: Markov decision process formulations for the role of energy storage," International Journal of Production Economics, Elsevier, vol. 255(C).
- Hu, Jinxing & Li, Hongru, 2022. "A transfer learning-based scenario generation method for stochastic optimal scheduling of microgrid with newly-built wind farm," Renewable Energy, Elsevier, vol. 185(C), pages 1139-1151.
- Cartuyvels, Jacques & Papavasiliou, Anthony, 2022. "Calibration of Operating Reserve Demand Curves using Monte Carlo Simulations," LIDAM Discussion Papers CORE 2022009, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Hui Hwang Goh & Gumeng Peng & Dongdong Zhang & Wei Dai & Tonni Agustiono Kurniawan & Kai Chen Goh & Chin Leei Cham, 2022. "A New Wind Speed Scenario Generation Method Based on Principal Component and R-Vine Copula Theories," Energies, MDPI, vol. 15(7), pages 1-21, April.
- Marisol Garrouste & Michael T. Craig & Daniel Wendt & Maria Herrera Diaz & William Jenson & Qian Zhang & Brendan Kochunas, 2023. "Techno-Economic Analysis of Synthetic Fuel Production from Existing Nuclear Power Plants across the United States," Papers 2309.12085, arXiv.org.
- Baker, T.E. & Epiney, A.S. & Rabiti, C. & Shittu, E., 2018. "Optimal sizing of flexible nuclear hybrid energy system components considering wind volatility," Applied Energy, Elsevier, vol. 212(C), pages 498-508.
- Epiney, A. & Rabiti, C. & Talbot, P. & Alfonsi, A., 2020. "Economic analysis of a nuclear hybrid energy system in a stochastic environment including wind turbines in an electricity grid," Applied Energy, Elsevier, vol. 260(C).
- Caputo, Antonio C. & Federici, Alessandro & Pelagagge, Pacifico M. & Salini, Paolo, 2023. "Offshore wind power system economic evaluation framework under aleatory and epistemic uncertainty," Applied Energy, Elsevier, vol. 350(C).
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Keywords
Hybrid energy systems; Renewable energy integration; Synthetic data generation; Autoregressive moving average;All these keywords.
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