Fully Parallel Stochastic Security-Constrained Unit Commitment

The increasing size and complexity of modern power systems and the integration of volatile renewable energy bring great challenges to the existing security-constrained unit commitment (SCUC) solution engines. This paper presents a fully parallel stochastic SCUC approach to obtain an efficient and fa...

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Veröffentlicht in:IEEE transactions on power systems Jg. 31; H. 5; S. 3561 - 3571
Hauptverfasser: Wang, Chunheng, Fu, Yong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.09.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Bridges
Construction
Couplings
Large-scale power system optimization
Linear programming
Mathematical models
Modules
Optimization
parallel algorithm
Power systems
Stochastic processes
stochastic programming
Stochasticity
Uncertainty
Unit commitment
Wind energy
ISSN:0885-8950, 1558-0679
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Zusammenfassung:The increasing size and complexity of modern power systems and the integration of volatile renewable energy bring great challenges to the existing security-constrained unit commitment (SCUC) solution engines. This paper presents a fully parallel stochastic SCUC approach to obtain an efficient and fast solution for a large-scale power system with wind energy uncertainty. Variables duplication and auxiliary problem principle (APP) techniques are adopted to fully decompose the original stochastic optimization problem into three major solution modules: the unit commitment (UC) module solves multiple single UC problems; the optimal power flow (OPF) module handles multiple hourly DC-OPF problems; and the bridge module builds a connection between the UC and OPF modules. These three modules are conducted for both base case and scenarios, and can be totally solved in a parallel manner. Numerical case studies on a modified IEEE 118-bus system and a practical 1168-bus system demonstrate the effectiveness and efficiency of the proposed approach which will offer the power system a secure and economic operation under various uncertainties.
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ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2015.2494590