Stochastic Optimization for Unit Commitment-A Review

Optimization models have been widely used in the power industry to aid the decision-making process of scheduling and dispatching electric power generation resources, a process known as unit commitment (UC). Since UC's birth, there have been two major waves of revolution on UC research and real...

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Bibliographic Details
Published in:IEEE transactions on power systems 2015-07, Vol.30 (4), p.1913-1924
Main Authors: Zheng, Qipeng P., Jianhui Wang, Liu, Andrew L.
Format: Article
Language:English
Subjects:
Computational modeling
distributed generator (DG)
distribution network
Electricity market operations
Load modeling
microgrid (MG)
mixed integer program (MIP)
mixed integer programming
Optimization
POWER TRANSMISSION AND DISTRIBUTION
pricing
Probabilistic logic
risk constraints
robust optimization
Robustness
Stochastic processes
stochastic programming
Uncertainty
unit commitment
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Summary:Optimization models have been widely used in the power industry to aid the decision-making process of scheduling and dispatching electric power generation resources, a process known as unit commitment (UC). Since UC's birth, there have been two major waves of revolution on UC research and real life practice. The first wave has made mixed integer programming stand out from the early solution and modeling approaches for deterministic UC, such as priority list, dynamic programming, and Lagrangian relaxation. With the high penetration of renewable energy, increasing deregulation of the electricity industry, and growing demands on system reliability, the next wave is focused on transitioning from traditional deterministic approaches to stochastic optimization for unit commitment. Since the literature has grown rapidly in the past several years, this paper is to review the works that have contributed to the modeling and computational aspects of stochastic optimization (SO) based UC. Relevant lines of future research are also discussed to help transform research advances into real-world applications.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2014.2355204