Solving Unit Commitment Problems with Demand Responsive Loads

Devon Sigler; Juliette Ugirumurera; Jose Daniel Lara; Sourabh Dalvi; Clayton Barrows

doi:10.1109/PESGM48719.2022.9916703

Solving Unit Commitment Problems with Demand Responsive Loads

Devon Sigler, Juliette Ugirumurera, Jose Daniel Lara, Sourabh Dalvi, Clayton Barrows

Research output: Contribution to conference › Paper › peer-review

1 Scopus Citations

Abstract

This paper focuses on using variations of the Frank-Wolfe algorithm for solving unit commitment problems with high volumes of demand responsive loads on the power grid. We present a formulation of the unit commitment problem with demand responsive loads. We then show through reformulation and relaxations of the problem that variations of the Frank-Wolfe algorithm can be used to determine the time series decisions for the demand responsive loads. We show through computational experiments on the IEEE Reliability Test System that the time series of demand responsive load decisions obtained through our approach are near optimal and describe how large-scale parallel implementations of our approach can be highly computationally efficient.

Original language	American English
Number of pages	5
DOIs	https://doi.org/10.1109/PESGM48719.2022.9916703 https://doi.org/10.1109/PESGM48719.2022.9916703
State	Published - 2022
Event	2022 IEEE Power and Energy Society General Meeting, PESGM 2022 - Denver, United States Duration: 17 Jul 2022 → 21 Jul 2022

Conference

Conference	2022 IEEE Power and Energy Society General Meeting, PESGM 2022
Country/Territory	United States
City	Denver
Period	17/07/22 → 21/07/22

Bibliographical note

See NREL/CP-2C00-81362 for preprint

NREL Publication Number

NREL/CP-2C00-84982

Keywords

Demand Response
Frank-Wolfe Algorithm
Unit Commitment

UN SDGs

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

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Cite this

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title = "Solving Unit Commitment Problems with Demand Responsive Loads",

abstract = "This paper focuses on using variations of the Frank-Wolfe algorithm for solving unit commitment problems with high volumes of demand responsive loads on the power grid. We present a formulation of the unit commitment problem with demand responsive loads. We then show through reformulation and relaxations of the problem that variations of the Frank-Wolfe algorithm can be used to determine the time series decisions for the demand responsive loads. We show through computational experiments on the IEEE Reliability Test System that the time series of demand responsive load decisions obtained through our approach are near optimal and describe how large-scale parallel implementations of our approach can be highly computationally efficient.",

keywords = "Demand Response, Frank-Wolfe Algorithm, Unit Commitment",

author = "Devon Sigler and Juliette Ugirumurera and Lara, {Jose Daniel} and Sourabh Dalvi and Clayton Barrows",

note = "See NREL/CP-2C00-81362 for preprint; 2022 IEEE Power and Energy Society General Meeting, PESGM 2022 ; Conference date: 17-07-2022 Through 21-07-2022",

year = "2022",

doi = "10.1109/PESGM48719.2022.9916703",

language = "American English",

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T1 - Solving Unit Commitment Problems with Demand Responsive Loads

AU - Sigler, Devon

AU - Ugirumurera, Juliette

AU - Lara, Jose Daniel

AU - Dalvi, Sourabh

AU - Barrows, Clayton

N1 - See NREL/CP-2C00-81362 for preprint

PY - 2022

Y1 - 2022

N2 - This paper focuses on using variations of the Frank-Wolfe algorithm for solving unit commitment problems with high volumes of demand responsive loads on the power grid. We present a formulation of the unit commitment problem with demand responsive loads. We then show through reformulation and relaxations of the problem that variations of the Frank-Wolfe algorithm can be used to determine the time series decisions for the demand responsive loads. We show through computational experiments on the IEEE Reliability Test System that the time series of demand responsive load decisions obtained through our approach are near optimal and describe how large-scale parallel implementations of our approach can be highly computationally efficient.

AB - This paper focuses on using variations of the Frank-Wolfe algorithm for solving unit commitment problems with high volumes of demand responsive loads on the power grid. We present a formulation of the unit commitment problem with demand responsive loads. We then show through reformulation and relaxations of the problem that variations of the Frank-Wolfe algorithm can be used to determine the time series decisions for the demand responsive loads. We show through computational experiments on the IEEE Reliability Test System that the time series of demand responsive load decisions obtained through our approach are near optimal and describe how large-scale parallel implementations of our approach can be highly computationally efficient.

KW - Demand Response

KW - Frank-Wolfe Algorithm

KW - Unit Commitment

UR - http://www.scopus.com/inward/record.url?scp=85141546363&partnerID=8YFLogxK

U2 - 10.1109/PESGM48719.2022.9916703

DO - 10.1109/PESGM48719.2022.9916703

M3 - Paper

AN - SCOPUS:85141546363

T2 - 2022 IEEE Power and Energy Society General Meeting, PESGM 2022

Y2 - 17 July 2022 through 21 July 2022

ER -

Solving Unit Commitment Problems with Demand Responsive Loads

Abstract

Conference

Bibliographical note

NREL Publication Number

Keywords

UN SDGs

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