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

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

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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 2018)
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages5
ISBN (Electronic)9781538677032, 9781538677025
ISBN (Print)9781538677049
Publication statusPublished - 2018
EventIEEE Power and Energy Society General Meeting 2018
- Portland, United States of America
Duration: 5 Aug 201810 Aug 2018 (Proceedings)

Publication series

NameIEEE Power and Energy Society General Meeting
PublisherIEEE, Institute of Electrical and Electronics Engineers
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933


ConferenceIEEE Power and Energy Society General Meeting 2018
Abbreviated titlePES-GM 2018
Country/TerritoryUnited States of America
Internet address

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