Open Access
Issue |
E3S Web Conf.
Volume 261, 2021
2021 7th International Conference on Energy Materials and Environment Engineering (ICEMEE 2021)
|
|
---|---|---|
Article Number | 02017 | |
Number of page(s) | 5 | |
Section | Energy Chemistry Performance and Material Structure Analysis | |
DOI | https://doi.org/10.1051/e3sconf/202126102017 | |
Published online | 21 May 2021 |
- A. Venzke, L. Halilbasic, U. Markovic, G. Hug, and S. Chatzivasileiadis, “Convex relaxations of chance constrained AC optimal power flow,” IEEE Transactions on Power Systems, vol. 33, no. 3, pp. 2829–2841, (2017). [Google Scholar]
- M. Vrakopoulou, K. Margellos, J. Lygeros, and G. Andersson, “A Probabilistic Framework for Reserve Scheduling and N-1 Security Assessment of Systems With High Wind Power Penetration,” IEEE Transactions on Power Systems, vol. 28, no. 4, pp. 3885–3896, (2013). [CrossRef] [Google Scholar]
- T. Summers, J. Warrington, M. Morari, and J. Lygeros, “Stochastic optimal power flow based on conditional value at risk and distributional robustness,” International Journal of Electrical Power & Energy Systems, vol. 72, pp. 116–125, (2015). [Google Scholar]
- W. Xie and S. Ahmed, “Distributionally robust chance constrained optimal power flow with renewables: A conic reformulation,” IEEE Transactions on Power Systems, vol. 33, no. 2, pp. 1860–1867, (2017). [Google Scholar]
- R. A. Jabr, S. Karaki, and J. A. Korbane, “Robust multi-period OPF with storage and renewables,” IEEE Transactions on Power Systems, vol. 30, no. 5, pp. 2790–2799, (2014). [Google Scholar]
- Y. Liu, N. Zhang, Y. Wang, J. Yang, and C. Kang, “Data-driven power flow linearization: A regression approach,” IEEE Transactions on Smart Grid, vol. 10, no. 3, pp. 2569–2580, (2018). [Google Scholar]
- R. T. Rockafellar, S. Uryasev, and others, “Optimization of conditional value-at-risk,” Journal of risk, vol. 2, pp. 21–42, (2000). [Google Scholar]
- P. M. Esfahani and D. Kuhn, “Data-driven distributionally robust optimization using the Wasserstein metric: Performance guarantees and tractable reformulations,” Mathematical Programming, vol. 171, no. 1–2, pp. 115–166, (2018). [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.