Optimal power flow with random wind resources

Yuquan Shan, George Kesidis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We consider optimal power-flow calculations based on statistics (means and variances) of wind-power that are assumed known hour ahead. In real-time, adjustments of these calculations to the true wind power amounts have been proposed using affine control and chance constraints on generation and transmission [1]. We study how correlated wind power sources affect the optimized power plan and cost. We also explore how the errors in wind forecasting statistics, due to real-time control actions to limit wind oscillations (ramping) or just simple misinformation, affect costs. There are direct extensions to the case where random/flexible demands/loads are correlated and similarly predictable.

Original languageEnglish (US)
Title of host publicationProceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016
EditorsRalph H. Sprague, Tung X. Bui
PublisherIEEE Computer Society
Pages2426-2434
Number of pages9
ISBN (Electronic)9780769556703
DOIs
StatePublished - Mar 7 2016
Event49th Annual Hawaii International Conference on System Sciences, HICSS 2016 - Koloa, United States
Duration: Jan 5 2016Jan 8 2016

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2016-March
ISSN (Print)1530-1605

Other

Other49th Annual Hawaii International Conference on System Sciences, HICSS 2016
CountryUnited States
CityKoloa
Period1/5/161/8/16

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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  • Cite this

    Shan, Y., & Kesidis, G. (2016). Optimal power flow with random wind resources. In R. H. Sprague, & T. X. Bui (Eds.), Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016 (pp. 2426-2434). [7427486] (Proceedings of the Annual Hawaii International Conference on System Sciences; Vol. 2016-March). IEEE Computer Society. https://doi.org/10.1109/HICSS.2016.303