Weekly Two-Stage Robust Generation Scheduling for Hydrothermal Power Systems

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

Research output: Contribution to journalArticle

20 Citations (Scopus)

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.

Original languageEnglish (US)
JournalIEEE Transactions on Power Systems
DOIs
StateAccepted/In press - Jan 8 2016

Fingerprint

Scheduling
Water
Electricity
Decomposition
Uncertainty

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology

Cite this

Weekly Two-Stage Robust Generation Scheduling for Hydrothermal Power Systems. / Dashti, Hossein; Conejo, Antonio J.; Jiang, Ruiwei; Wang, Jianhui.

In: IEEE Transactions on Power Systems, 08.01.2016.

Research output: Contribution to journalArticle

@article{54f46d92808f4592ae1a59fe4ff535d0,
title = "Weekly Two-Stage Robust Generation Scheduling for Hydrothermal Power Systems",
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.",
author = "Hossein Dashti and Conejo, {Antonio J.} and Ruiwei Jiang and Jianhui Wang",
year = "2016",
month = "1",
day = "8",
doi = "10.1109/TPWRS.2015.2510628",
language = "English (US)",
journal = "IEEE Transactions on Power Systems",
issn = "0885-8950",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Weekly Two-Stage Robust Generation Scheduling for Hydrothermal Power Systems

AU - Dashti, Hossein

AU - Conejo, Antonio J.

AU - Jiang, Ruiwei

AU - Wang, Jianhui

PY - 2016/1/8

Y1 - 2016/1/8

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84954056589&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84954056589&partnerID=8YFLogxK

U2 - 10.1109/TPWRS.2015.2510628

DO - 10.1109/TPWRS.2015.2510628

M3 - Article

JO - IEEE Transactions on Power Systems

JF - IEEE Transactions on Power Systems

SN - 0885-8950

ER -