The value of multi-stage stochastic programming in risk-averse unit commitment under uncertainty

Date
2019
Advisor
Instructor
Source Title
IEEE Transactions on Power Systems
Print ISSN
0885-8950
Electronic ISSN
1558-0679
Publisher
IEEE
Volume
34
Issue
5
Pages
3667 - 3676
Language
English
Type
Article
Journal Title
Journal ISSN
Volume Title
Abstract

Day-ahead scheduling of electricity generation or unit commitment is an important and challenging optimization problem in power systems. Variability in net load arising from the increasing penetration of renewable technologies has motivated study of various classes of stochastic unit commitment models. In two-stage models, the generation schedule for the entire day is fixed while the dispatch is adapted to the uncertainty, whereas in multi-stage models the generation schedule is also allowed to dynamically adapt to the uncertainty realization. Multi-stage models provide more flexibility in the generation schedule; however, they require significantly higher computational effort than two-stage models. To justify this additional computational effort, we provide theoretical and empirical analyses of the value of multi-stage solution for risk-averse multi-stage stochastic unit commitment models. The value of multi-stage solution measures the relative advantage of multi-stage solutions over their two-stage counterparts. Our results indicate that, for unit commitment models, the value of multi-stage solution increases with the level of uncertainty and number of periods, and decreases with the degree of risk aversion of the decision maker.

Course
Other identifiers
Book Title
Keywords
Unit commitment, Risk-averse optimization, Stochastic programming
Citation
Published Version (Please cite this version)