The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
A methodology to generate statistically dependent wind speed scenarios
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Citations
Cites
Introduction to Stochastic Programming
Birge, J. R., & Louveaux, F. (2011) · Springer Series in Operations Research and Financial Engineering · doi:10.1007/978-1-4614-0237-4 · Cited by 6,469
Scenario reduction in stochastic programming
Dupa?ov�, J., Gr�we-Kuska, N., & R�misch, W. (2003) · Mathematical Programming · doi:10.1007/s10107-002-0331-0 · Cited by 1,041
Multivariate distribution models with prescribed marginals and covariances
Liu, P.-L., & Kiureghian, A. D. (1986) · Probabilistic Engineering Mechanics · doi:10.1016/0266-8920(86)90033-0 · Cited by 987
Stochastic Security for Operations Planning With Significant Wind Power Generation
Bouffard, F., & Galiana, F. D. (2008) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2008.919318 · Cited by 713
Generating Scenario Trees for Multistage Decision Problems
Høyland, K., & Wallace, S. W. (2001) · Management Science · doi:10.1287/mnsc.47.2.295.9834 · Cited by 673
Economic Valuation of Reserves in Power Systems With High Penetration of Wind Power
Morales, J. M., Conejo, A. J., & Perez-Ruiz, J. (2009) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2016598 · Cited by 573
Self-citationTrading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power
Pinson, P., Chevallier, C., & Kariniotakis, G. N. (2007) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2007.901117 · Cited by 571
New Light on the Correlation Coefficient and its Transforms
Hotelling, H. (1953) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1953.tb00135.x · Cited by 544
Scenario reduction in stochastic programming: An approach using probability metrics
Dupačová, J., Gröwe‐Kuska, N., & Römisch, W. (2000) · doi:10.18452/2876 · Cited by 517
Short-Term Trading for a Wind Power Producer
Morales, J. M., Conejo, A. J., & Perez-Ruiz, J. (2010) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2036810 · Cited by 478
Self-citation
Cited by
Reserve Requirements for Wind Power Integration: A Scenario-Based Stochastic Programming Framework
Papavasiliou, A., Oren, S. S., & O'Neill, R. P. (2011) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2011.2121095 · Cited by 580
Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review
Zendehboudi, S., Rezaei, N., & Lohi, A. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.06.051 · Cited by 394
A cross-modal generative adversarial network for scenarios generation of renewable energy
Kang, M., Zhu, R., Chen, D., Li, C., Gu, W., Qian, X., & Yu, W. (2024) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2023.3277698 · Cited by 90
Metadata
- Authors
- Morales, J. M., Mínguez, R., & Conejo, A. J.
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2010-03
- Volume
- 87
- Issue
- 3
- Pages
- 843-855
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W1971474913
- Cited by
- 342
- References
- 16
- FWCI
- 7.39
- Type
- journal article
- Language
- en
- Open access
- closed
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- Morales, J. M., Mínguez, R., & Conejo, A. J. (2010). A methodology to generate statistically dependent wind speed scenarios. Applied Energy. https://doi.org/10.1016/j.apenergy.2009.09.022
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
