Weekly Two-Stage Robust Generation Scheduling for Hydrothermal Power Systems

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

Research output: Contribution to journalArticlepeer-review

42 Scopus citations


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.

Original languageEnglish (US)
Article number7377128
Pages (from-to)4554-4564
Number of pages11
JournalIEEE Transactions on Power Systems
Issue number6
StatePublished - Nov 2016


  • Hydrothermal coordination
  • robust optimization
  • unit commitment
  • vector autoregressive model

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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