A combination method for modeling wind power plants in power systems reliability evaluation

[Display omitted] •The proposed technique is a combination of analytical and simulation methods.•We analyzed the effect of number of WTG output power levels on system reliability.•The proposed technique can incorporate mechanical behavior of system components.•The number of wind farm power states in...

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Bibliographic Details
Published in:Computers & electrical engineering 2015-01, Vol.41, p.28-39
Main Authors: Soleymani, Soodabeh, Mosayebian, Mohammad Ehsan, Mohammadi, Sirus
Format: Article
Language:English
Subjects:
Computer simulation
Electric power generation
Markov chain
Mathematical models
Monte Carlo methods
Monte Carlo simulation
Power plants
Power system reliability
System reliability
Wind power
Wind speed
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Summary:[Display omitted] •The proposed technique is a combination of analytical and simulation methods.•We analyzed the effect of number of WTG output power levels on system reliability.•The proposed technique can incorporate mechanical behavior of system components.•The number of wind farm power states increase with increasing WTGs failure rate. The production of wind energy often involves uncertainties due to the stochastic nature of wind speeds and the variation of the power curve. In this study, a method for modeling wind power plant in power systems reliability evaluation is proposed. This method is a combination of analytical and simulation methods. Initially, the mechanical behavior of each wind turbine generator (WTG) is modeled through sequential Monte Carlo method. Then, considering the wind speed of the area, the Markov model is used for modeling the power output of wind farm. The combination method is compared with the Auto Regressive Moving Average (ARMA) time series method and some other techniques such as Weibull and normal distribution methods in wind speed modeling. Also in this study, the effects of different parameters, such as failure, repair rate and number of output power levels of WTG on the system reliability are analyzed.
ISSN:0045-7906
1879-0755
DOI:10.1016/j.compeleceng.2014.12.005