A Stochastic Model for the Optimal Operation of a Wind-Thermal Power System

This paper presents a stochastic cost model and a solution technique for optimal scheduling of the generators in a wind integrated power system considering the demand and wind generation uncertainties. The proposed robust unit commitment solution methodology will help the power system operators in o...

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Bibliographic Details
Published in:IEEE transactions on power systems 2009-05, Vol.24 (2), p.940-950
Main Authors: Pappala, V.S., Erlich, I., Rohrig, K., Dobschinski, J.
Format: Article
Language:English
Subjects:
Artificial neural network
Cost function
Optimal scheduling
Particle swarm optimization
Power generation
Power system modeling
Power system planning
scenario tree
stochastic programming
Stochastic systems
Uncertainty
unit commitment
Wind energy generation
Wind power generation
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Summary:This paper presents a stochastic cost model and a solution technique for optimal scheduling of the generators in a wind integrated power system considering the demand and wind generation uncertainties. The proposed robust unit commitment solution methodology will help the power system operators in optimal day-ahead planning even with indeterminate information about the wind generation. A particle swarm optimization based scenario generation and reduction algorithm is used for modeling the uncertainties. The stochastic unit commitment problem is solved using a new parameter free self adaptive particle swarm optimization algorithm. The numerical results indicate the low risk involved in day-ahead power system planning when the stochastic model is used instead of the deterministic model.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2009.2016504