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.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/622668 |
| Date | 11 1900 |
| Creators | Dashti, Hossein, Conejo, Antonio J., Jiang, Ruiwei, Wang, Jianhui |
| Contributors | Department of Systems and Industrial Engineering, University of Arizona, Tucson |
| Publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Article |
| Rights | U.S. Government work not protected by U.S. copyright. |
| Relation | http://ieeexplore.ieee.org/document/7377128/ |
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