An efficient method based on adaptive time resolution for the unit commitment problem

Semini Wijekoon, Ariel Liebman, Aldeida Aleti, Rajab Khalilpour, Simon Dunstall

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Unit Commitment (UC) is a computationally intensive problem, which has been solved sufficiently well for day ahead scheduling and single scenario simulations. However, the introduction of renewable energy sources and storage exposes new challenges in computation time due to the need for large-scale multi-scenario modeling while preserving inter-temporal constraints. To address this, we introduce a novel approach with adaptive time resolution that increases simulation speed and preserves accuracy. We reduce the size of the problem by grouping successive time intervals with similar net demand levels, forming a new longer interval. In comparison with the conventional UC solutions, the proposed approach is computationally more efficient, as it avoids repeated optimization for similar intervals. We analyze the quality of the solutions using the 6-bus, and IEEE 118-bus test systems as the two case-studies. The numerical results demonstrate that high quality solutions can be obtained with significant gains in computational speed, especially for the more difficult IEEE 118-bus case which is 115 times faster with a maximum error of less than ±1%.

Original languageEnglish
Title of host publication2018 IEEE Power & Energy Society General Meeting (PESGM)
EditorsFarnoosh Rahmatian
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages5
ISBN (Electronic)9781538677032, 9781538677025
ISBN (Print)9781538677049
DOIs
Publication statusPublished - 2018
EventIEEE Power and Energy Society General Meeting 2018
- Portland, United States
Duration: 5 Aug 201810 Aug 2018
https://www.pes-gm.org/2018/

Conference

ConferenceIEEE Power and Energy Society General Meeting 2018
Abbreviated titlePESGM 2018
CountryUnited States
CityPortland
Period5/08/1810/08/18
Internet address

Cite this

Wijekoon, S., Liebman, A., Aleti, A., Khalilpour, R., & Dunstall, S. (2018). An efficient method based on adaptive time resolution for the unit commitment problem. In F. Rahmatian (Ed.), 2018 IEEE Power & Energy Society General Meeting (PESGM) [8585851] Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/PESGM.2018.8585851
Wijekoon, Semini ; Liebman, Ariel ; Aleti, Aldeida ; Khalilpour, Rajab ; Dunstall, Simon. / An efficient method based on adaptive time resolution for the unit commitment problem. 2018 IEEE Power & Energy Society General Meeting (PESGM). editor / Farnoosh Rahmatian. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2018.
@inproceedings{4ed071bfbd934fb7a5320f6bb4cb9973,
title = "An efficient method based on adaptive time resolution for the unit commitment problem",
abstract = "Unit Commitment (UC) is a computationally intensive problem, which has been solved sufficiently well for day ahead scheduling and single scenario simulations. However, the introduction of renewable energy sources and storage exposes new challenges in computation time due to the need for large-scale multi-scenario modeling while preserving inter-temporal constraints. To address this, we introduce a novel approach with adaptive time resolution that increases simulation speed and preserves accuracy. We reduce the size of the problem by grouping successive time intervals with similar net demand levels, forming a new longer interval. In comparison with the conventional UC solutions, the proposed approach is computationally more efficient, as it avoids repeated optimization for similar intervals. We analyze the quality of the solutions using the 6-bus, and IEEE 118-bus test systems as the two case-studies. The numerical results demonstrate that high quality solutions can be obtained with significant gains in computational speed, especially for the more difficult IEEE 118-bus case which is 115 times faster with a maximum error of less than ±1{\%}.",
author = "Semini Wijekoon and Ariel Liebman and Aldeida Aleti and Rajab Khalilpour and Simon Dunstall",
year = "2018",
doi = "10.1109/PESGM.2018.8585851",
language = "English",
isbn = "9781538677049",
editor = "Farnoosh Rahmatian",
booktitle = "2018 IEEE Power & Energy Society General Meeting (PESGM)",
publisher = "IEEE, Institute of Electrical and Electronics Engineers",
address = "United States",

}

Wijekoon, S, Liebman, A, Aleti, A, Khalilpour, R & Dunstall, S 2018, An efficient method based on adaptive time resolution for the unit commitment problem. in F Rahmatian (ed.), 2018 IEEE Power & Energy Society General Meeting (PESGM)., 8585851, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, IEEE Power and Energy Society General Meeting 2018
, Portland, United States, 5/08/18. https://doi.org/10.1109/PESGM.2018.8585851

An efficient method based on adaptive time resolution for the unit commitment problem. / Wijekoon, Semini; Liebman, Ariel; Aleti, Aldeida; Khalilpour, Rajab; Dunstall, Simon.

2018 IEEE Power & Energy Society General Meeting (PESGM). ed. / Farnoosh Rahmatian. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2018. 8585851.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

TY - GEN

T1 - An efficient method based on adaptive time resolution for the unit commitment problem

AU - Wijekoon, Semini

AU - Liebman, Ariel

AU - Aleti, Aldeida

AU - Khalilpour, Rajab

AU - Dunstall, Simon

PY - 2018

Y1 - 2018

N2 - Unit Commitment (UC) is a computationally intensive problem, which has been solved sufficiently well for day ahead scheduling and single scenario simulations. However, the introduction of renewable energy sources and storage exposes new challenges in computation time due to the need for large-scale multi-scenario modeling while preserving inter-temporal constraints. To address this, we introduce a novel approach with adaptive time resolution that increases simulation speed and preserves accuracy. We reduce the size of the problem by grouping successive time intervals with similar net demand levels, forming a new longer interval. In comparison with the conventional UC solutions, the proposed approach is computationally more efficient, as it avoids repeated optimization for similar intervals. We analyze the quality of the solutions using the 6-bus, and IEEE 118-bus test systems as the two case-studies. The numerical results demonstrate that high quality solutions can be obtained with significant gains in computational speed, especially for the more difficult IEEE 118-bus case which is 115 times faster with a maximum error of less than ±1%.

AB - Unit Commitment (UC) is a computationally intensive problem, which has been solved sufficiently well for day ahead scheduling and single scenario simulations. However, the introduction of renewable energy sources and storage exposes new challenges in computation time due to the need for large-scale multi-scenario modeling while preserving inter-temporal constraints. To address this, we introduce a novel approach with adaptive time resolution that increases simulation speed and preserves accuracy. We reduce the size of the problem by grouping successive time intervals with similar net demand levels, forming a new longer interval. In comparison with the conventional UC solutions, the proposed approach is computationally more efficient, as it avoids repeated optimization for similar intervals. We analyze the quality of the solutions using the 6-bus, and IEEE 118-bus test systems as the two case-studies. The numerical results demonstrate that high quality solutions can be obtained with significant gains in computational speed, especially for the more difficult IEEE 118-bus case which is 115 times faster with a maximum error of less than ±1%.

UR - http://www.scopus.com/inward/record.url?scp=85060830193&partnerID=8YFLogxK

U2 - 10.1109/PESGM.2018.8585851

DO - 10.1109/PESGM.2018.8585851

M3 - Conference Paper

SN - 9781538677049

BT - 2018 IEEE Power & Energy Society General Meeting (PESGM)

A2 - Rahmatian, Farnoosh

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

ER -

Wijekoon S, Liebman A, Aleti A, Khalilpour R, Dunstall S. An efficient method based on adaptive time resolution for the unit commitment problem. In Rahmatian F, editor, 2018 IEEE Power & Energy Society General Meeting (PESGM). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2018. 8585851 https://doi.org/10.1109/PESGM.2018.8585851