Solving Unit Commitment Problems with Demand Responsive Loads: Preprint

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

Solving Unit Commitment Problems with Demand Responsive Loads: Preprint

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

Research output: Contribution to conference › Paper

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 RTS-GMLC test system that the time series of demand responsive load decisions obtained through our approach are near optimal and provide details regarding how large scale parallel implementations of our approach can be highly computationally efficient.

Original language	American English
Number of pages	8
State	Published - 2022
Event	2022 IEEE Power & Energy Society General Meeting - Denver, Colorado Duration: 17 Jul 2022 → 21 Jul 2022

Conference

Conference	2022 IEEE Power & Energy Society General Meeting
City	Denver, Colorado
Period	17/07/22 → 21/07/22

Bibliographical note

See NREL/CP-2C00-84982 for paper as published in proceedings

NREL Publication Number

NREL/CP-2C00-81362

Keywords

demand response
Frank-Wolfe Algorithm
unit commitment

Access to Document

https://www.nrel.gov/docs/fy22osti/81362.pdf

Cite this

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

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 RTS-GMLC test system that the time series of demand responsive load decisions obtained through our approach are near optimal and provide details regarding 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-2C00-84982 for paper as published in proceedings; 2022 IEEE Power & Energy Society General Meeting ; Conference date: 17-07-2022 Through 21-07-2022",

year = "2022",

language = "American English",

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TY - CONF

T1 - Solving Unit Commitment Problems with Demand Responsive Loads: Preprint

AU - Sigler, Devon

AU - Ugirumurera, Juliette

AU - Lara, Jose Daniel

AU - Dalvi, Sourabh

AU - Barrows, Clayton

N1 - See NREL/CP-2C00-84982 for paper as published in proceedings

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 RTS-GMLC test system that the time series of demand responsive load decisions obtained through our approach are near optimal and provide details regarding 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 RTS-GMLC test system that the time series of demand responsive load decisions obtained through our approach are near optimal and provide details regarding how large scale parallel implementations of our approach can be highly computationally efficient.

KW - demand response

KW - Frank-Wolfe Algorithm

KW - unit commitment

M3 - Paper

T2 - 2022 IEEE Power & Energy Society General Meeting

Y2 - 17 July 2022 through 21 July 2022

ER -

Solving Unit Commitment Problems with Demand Responsive Loads: Preprint

Abstract

Conference

Bibliographical note

NREL Publication Number

Keywords

Access to Document

Fingerprint

Cite this