Stochastic optimization formulations for reliability unit commitment runs

Kai Pan; Yang Lu; Yongpei Guan; Jean Paul Watson

doi:10.1109/PESGM.2014.6939833

Stochastic optimization formulations for reliability unit commitment runs

Kai Pan, Yang Lu, Yongpei Guan, Jean Paul Watson

Research output: Journal article publication › Conference article › Academic research › peer-review

1 Citation (Scopus)

Abstract

To address the uncertainties caused by the penetration of intermittent renewable energy, most ISOs/RTOs perform day-ahead and look-ahead reliability unit commitment (RUC) runs, ensuring sufficient generation capacity available in real time to accommodate the uncertainties. Two-stage stochastic optimization models have been studied extensively to strengthen the RUC runs, while multi-stage stochastic optimization models were barely studied. In this paper, we investigate the unit commitment and economic dispatch decision differences generated by these two approaches considering the load uncertainties in the system. The stochasticity is represented by a set of scenarios for the two-stage model and a scenario tree for the multi-stage case.

Original language	English
Article number	6939833
Journal	IEEE Power and Energy Society General Meeting
Volume	2014-October
Issue number	October
DOIs	https://doi.org/10.1109/PESGM.2014.6939833
Publication status	Published - 1 Jan 2014
Externally published	Yes
Event	2014 IEEE Power and Energy Society General Meeting - National Harbor, United States Duration: 27 Jul 2014 → 31 Jul 2014

Keywords

mixed-integer linear programming
multi-stage stochastic optimization
two-stage stochastic optimization
Unit commitment

ASJC Scopus subject areas

Energy Engineering and Power Technology
Nuclear Energy and Engineering
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/PESGM.2014.6939833

Cite this

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title = "Stochastic optimization formulations for reliability unit commitment runs",

abstract = "To address the uncertainties caused by the penetration of intermittent renewable energy, most ISOs/RTOs perform day-ahead and look-ahead reliability unit commitment (RUC) runs, ensuring sufficient generation capacity available in real time to accommodate the uncertainties. Two-stage stochastic optimization models have been studied extensively to strengthen the RUC runs, while multi-stage stochastic optimization models were barely studied. In this paper, we investigate the unit commitment and economic dispatch decision differences generated by these two approaches considering the load uncertainties in the system. The stochasticity is represented by a set of scenarios for the two-stage model and a scenario tree for the multi-stage case.",

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T1 - Stochastic optimization formulations for reliability unit commitment runs

AU - Pan, Kai

AU - Lu, Yang

AU - Guan, Yongpei

AU - Watson, Jean Paul

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N2 - To address the uncertainties caused by the penetration of intermittent renewable energy, most ISOs/RTOs perform day-ahead and look-ahead reliability unit commitment (RUC) runs, ensuring sufficient generation capacity available in real time to accommodate the uncertainties. Two-stage stochastic optimization models have been studied extensively to strengthen the RUC runs, while multi-stage stochastic optimization models were barely studied. In this paper, we investigate the unit commitment and economic dispatch decision differences generated by these two approaches considering the load uncertainties in the system. The stochasticity is represented by a set of scenarios for the two-stage model and a scenario tree for the multi-stage case.

AB - To address the uncertainties caused by the penetration of intermittent renewable energy, most ISOs/RTOs perform day-ahead and look-ahead reliability unit commitment (RUC) runs, ensuring sufficient generation capacity available in real time to accommodate the uncertainties. Two-stage stochastic optimization models have been studied extensively to strengthen the RUC runs, while multi-stage stochastic optimization models were barely studied. In this paper, we investigate the unit commitment and economic dispatch decision differences generated by these two approaches considering the load uncertainties in the system. The stochasticity is represented by a set of scenarios for the two-stage model and a scenario tree for the multi-stage case.

KW - mixed-integer linear programming

KW - multi-stage stochastic optimization

KW - two-stage stochastic optimization

KW - Unit commitment

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DO - 10.1109/PESGM.2014.6939833

M3 - Conference article

SN - 1944-9925

VL - 2014-October

JO - IEEE Power and Energy Society General Meeting

JF - IEEE Power and Energy Society General Meeting

IS - October

M1 - 6939833

T2 - 2014 IEEE Power and Energy Society General Meeting

Y2 - 27 July 2014 through 31 July 2014

ER -

Stochastic optimization formulations for reliability unit commitment runs

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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