Interval optimization combined with point estimate method for stochastic security-constrained unit commitment

•IO-PEM is proposed to solve stochastic SCUC problem.•Interval optimization is used to cope with operational security constraints.•PEM is introduced to evaluate the expected corrective dispatching cost.•The comparative studies show the IO-2M+1PEM is outstanding over IO-2MPEM.•The proposed approach i...

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Veröffentlicht in:International journal of electrical power & energy systems Jg. 63; S. 276 - 284
Hauptverfasser: Zhou, Ming, Xia, Shu, Li, Gengyin, Han, Xiao
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Elsevier Ltd 01.12.2014
Elsevier
Schlagworte:
Applied sciences
Direct energy conversion and energy accumulation
Electrical engineering. Electrical power engineering
Electrical power engineering
Energy
Exact sciences and technology
Interval optimization
Miscellaneous
Natural energy
Operation. Load control. Reliability
Point estimate
Power networks and lines
Stochastic SCUC
Volatility
Wind energy
Wind power
Interval optimization
Wind power
Stochastic SCUC
Volatility
Point estimate
Dispatching problem
Monte Carlo method
Costs
Worst case method
Power system planning
Optimization method
Power distribution planning
Scheduling
Forecasting management
Optimization
Bus system
Reduction method
Wind energy
Electrical network
Numerical simulation
System simulation
IEEE standards
Safety
Comparative study
ISSN:0142-0615, 1879-3517
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Zusammenfassung:•IO-PEM is proposed to solve stochastic SCUC problem.•Interval optimization is used to cope with operational security constraints.•PEM is introduced to evaluate the expected corrective dispatching cost.•The comparative studies show the IO-2M+1PEM is outstanding over IO-2MPEM.•The proposed approach is compared with three conventional methods. To the stochastic nature of unit commitment problem induced by wind power fluctuation, an interval optimization combined with point estimation method (IO-PEM) is proposed to model and solve stochastic security constrained unit commitment (SCUC) problem. Considering reasonable fluctuation range of wind power, an interval optimization model is established which takes two worst-case scenarios to replace all scenarios in the interval. This model accelerates the solution speed on the premise that the scheduling result meets security constraints. At the same time, in order to accurately evaluate corrective dispatching cost caused by wind power fluctuations and make the scheduling scheme more economic, two kinds of point estimation method: 2M and 2M+1 schemes, are introduced to improve the accuracy of the interval optimization approach. Comparison studies are done with the proposed method over three conventional methods: Monte Carlo method, the scenario reduction method and the interval optimization method, on the six-bus system and the modified IEEE 118-bus system, the simulation results show that the proposed method has the merits in computation speed and accuracy, in the meanwhile keeping security and economy of the dispatching scheme.
ISSN:0142-0615
1879-3517
DOI:10.1016/j.ijepes.2014.06.012