Weekly Two-Stage Robust Generation Scheduling for Hydrothermal Power Systems

Dashti, Hossein; Conejo, Antonio J.; Jiang, Ruiwei; Wang, Jianhui

dc.contributor.author	Dashti, Hossein
dc.contributor.author	Conejo, Antonio J.
dc.contributor.author	Jiang, Ruiwei
dc.contributor.author	Wang, Jianhui
dc.date.accessioned	2017-03-01T00:22:02Z
dc.date.available	2017-03-01T00:22:02Z
dc.date.issued	2016-11
dc.identifier.citation	Weekly Two-Stage Robust Generation Scheduling for Hydrothermal Power Systems 2016, 31 (6):4554 IEEE Transactions on Power Systems	en
dc.identifier.issn	0885-8950
dc.identifier.issn	1558-0679
dc.identifier.doi	10.1109/TPWRS.2015.2510628
dc.identifier.uri	http://hdl.handle.net/10150/622668
dc.description.abstract	As compared to short-term forecasting (e.g., 1 day), it is often challenging to accurately forecast the volume of precipitation in a medium-term horizon (e.g., 1 week). As a result, fluctuations in water inflow can trigger generation shortage and electricity price spikes in a power system with major or predominant hydro resources. In this paper, we study a two-stage robust scheduling approach for a hydrothermal power system. We consider water inflow uncertainty and employ a vector autoregressive (VAR) model to represent its seasonality and accordingly construct an uncertainty set in the robust optimization approach. We design a Benders' decomposition algorithm to solve this problem. Results are presented for the proposed approach on a real-world case study.
dc.description.sponsorship	University of Arizona Renewable Energy Network; National Science Foundation (NSF) [60050502]; NSF [CMMI-1555983]; U.S. Department of Energy Office of Electricity Delivery and Energy Reliability	en
dc.language.iso	en	en
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
dc.relation.url	http://ieeexplore.ieee.org/document/7377128/	en
dc.rights	U.S. Government work not protected by U.S. copyright.	en
dc.rights.uri	https://creativecommons.org/publicdomain/mark/1.0/
dc.subject	Hydrothermal coordination	en
dc.subject	robust optimization	en
dc.subject	unit commitment	en
dc.subject	vector autoregressive model	en
dc.title	Weekly Two-Stage Robust Generation Scheduling for Hydrothermal Power Systems	en
dc.type	Article	en
dc.contributor.department	Department of Systems and Industrial Engineering, University of Arizona, Tucson	en
dc.identifier.journal	IEEE Transactions on Power Systems	en
dc.description.collectioninformation	This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.	en
dc.eprint.version	Final published version	en
refterms.dateFOA	2018-09-11T17:45:39Z
html.description.abstract	As compared to short-term forecasting (e.g., 1 day), it is often challenging to accurately forecast the volume of precipitation in a medium-term horizon (e.g., 1 week). As a result, fluctuations in water inflow can trigger generation shortage and electricity price spikes in a power system with major or predominant hydro resources. In this paper, we study a two-stage robust scheduling approach for a hydrothermal power system. We consider water inflow uncertainty and employ a vector autoregressive (VAR) model to represent its seasonality and accordingly construct an uncertainty set in the robust optimization approach. We design a Benders' decomposition algorithm to solve this problem. Results are presented for the proposed approach on a real-world case study.