Power Systems Optimization under Uncertainty: A Review of Methods and Applications

Line Roald; David  Pozo; Anthony Papavasiliou; Daniel K.  Molzahn; Jalal Kazempour; Antonio J. Conejo

doi:10.1016/j.epsr.2022.108725

Power Systems Optimization under Uncertainty: A Review of Methods and Applications

Line Roald^*, David Pozo, Anthony Papavasiliou, Daniel K. Molzahn, Jalal Kazempour, Antonio J. Conejo

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

Abstract

Electric power systems and the companies and customers that interact with them are experiencing increasing levels of uncertainty due to factors such as renewable energy generation, market liberalization and climate change. This raises the important question of how to make optimal decisions under uncertainty. This paper aims to provide an overview of existing methods for modeling and optimization of problems affected by uncertainty, targeted at researchers with a familiarity with power systems and optimization. Furthermore, we provide a review of some important applications of optimization under uncertainty in power systems, as well as an outlook to future directions of research.

Original language	English
Article number	108725
Journal	Electric Power Systems Research
Volume	214
Issue number	Part A
Number of pages	32
ISSN	0378-7796
DOIs	https://doi.org/10.1016/j.epsr.2022.108725
Publication status	Published - 2023
Event	XXII Power Systems Computation Conference - University of Porto, Porto, Portugal Duration: 27 Jun 2022 → 1 Jul 2022 Conference number: 22 https://pscc2022.pt/

Conference

Conference	XXII Power Systems Computation Conference
Number	22
Location	University of Porto
Country/Territory	Portugal
City	Porto
Period	27/06/2022 → 01/07/2022
Internet address	https://pscc2022.pt/

Keywords

Stochastic optimization
Robust optimization
Chance-constrained optimization
Electric power system

UN SDGs

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

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title = "Power Systems Optimization under Uncertainty: A Review of Methods and Applications",

abstract = "Electric power systems and the companies and customers that interact with them are experiencing increasing levels of uncertainty due to factors such as renewable energy generation, market liberalization and climate change. This raises the important question of how to make optimal decisions under uncertainty. This paper aims to provide an overview of existing methods for modeling and optimization of problems affected by uncertainty, targeted at researchers with a familiarity with power systems and optimization. Furthermore, we provide a review of some important applications of optimization under uncertainty in power systems, as well as an outlook to future directions of research.",

keywords = "Stochastic optimization, Robust optimization, Chance-constrained optimization, Electric power system",

author = "Line Roald and David Pozo and Anthony Papavasiliou and Molzahn, {Daniel K.} and Jalal Kazempour and Conejo, {Antonio J.}",

year = "2023",

doi = "10.1016/j.epsr.2022.108725",

language = "English",

volume = "214",

journal = "Electric Power Systems Research",

issn = "0378-7796",

publisher = "Elsevier",

number = "Part A",

note = "XXII Power Systems Computation Conference, PSCC{\textquoteright}2022 ; Conference date: 27-06-2022 Through 01-07-2022",

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T1 - Power Systems Optimization under Uncertainty: A Review of Methods and Applications

AU - Roald, Line

AU - Pozo, David

AU - Papavasiliou, Anthony

AU - Molzahn, Daniel K.

AU - Kazempour, Jalal

AU - Conejo, Antonio J.

N1 - Conference code: 22

PY - 2023

Y1 - 2023

N2 - Electric power systems and the companies and customers that interact with them are experiencing increasing levels of uncertainty due to factors such as renewable energy generation, market liberalization and climate change. This raises the important question of how to make optimal decisions under uncertainty. This paper aims to provide an overview of existing methods for modeling and optimization of problems affected by uncertainty, targeted at researchers with a familiarity with power systems and optimization. Furthermore, we provide a review of some important applications of optimization under uncertainty in power systems, as well as an outlook to future directions of research.

AB - Electric power systems and the companies and customers that interact with them are experiencing increasing levels of uncertainty due to factors such as renewable energy generation, market liberalization and climate change. This raises the important question of how to make optimal decisions under uncertainty. This paper aims to provide an overview of existing methods for modeling and optimization of problems affected by uncertainty, targeted at researchers with a familiarity with power systems and optimization. Furthermore, we provide a review of some important applications of optimization under uncertainty in power systems, as well as an outlook to future directions of research.

KW - Stochastic optimization

KW - Robust optimization

KW - Chance-constrained optimization

KW - Electric power system

U2 - 10.1016/j.epsr.2022.108725

DO - 10.1016/j.epsr.2022.108725

M3 - Journal article

SN - 0378-7796

VL - 214

JO - Electric Power Systems Research

JF - Electric Power Systems Research

IS - Part A

M1 - 108725

T2 - XXII Power Systems Computation Conference

Y2 - 27 June 2022 through 1 July 2022

ER -

Power Systems Optimization under Uncertainty: A Review of Methods and Applications

Abstract

Conference

Keywords

UN SDGs

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