NDLI: A Chance-Constrained Two-Stage Stochastic Program for Unit Commitment With Uncertain Wind Power Output

Content Provider	IEEE Xplore Digital Library
Author	Qianfan Wang Yongpei Guan Jianhui Wang
Copyright Year	1969
Abstract	In this paper, we present a unit commitment problem with uncertain wind power output. The problem is formulated as a chance-constrained two-stage (CCTS) stochastic program. Our model ensures that, with high probability, a large portion of the wind power output at each operating hour will be utilized. The proposed model includes both the two-stage stochastic program and the chance-constrained stochastic program features. These types of problems are challenging and have never been studied together before, even though the algorithms for the two-stage stochastic program and the chance-constrained stochastic program have been recently developed separately. In this paper, a combined sample average approximation (SAA) algorithm is developed to solve the model effectively. The convergence property and the solution validation process of our proposed combined SAA algorithm is discussed and presented in the paper. Finally, computational results indicate that increasing the utilization of wind power output might increase the total power generation cost, and our experiments also verify that the proposed algorithm can solve large-scale power grid optimization problems.
Sponsorship	IEEE Power Engineering Society
Starting Page	206
Ending Page	215
Page Count	10
File Size	464139
File Format	PDF
ISSN	08858950
Volume Number	27
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-02-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wind power generation Stochastic processes Generators Approximation algorithms Uncertainty Upper bound Optimization wind power Chance-constrained optimization sample average approximation unit commitment
Content Type	Text
Resource Type	Article
Subject	Energy Engineering and Power Technology Electrical and Electronic Engineering

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