DocumentCode
134910
Title
A stochastic model for power system transient stability with wind power
Author
Wei Wu ; Keyou Wang ; Guojie Li ; Yue Hu
Author_Institution
Dept. of Electr. Eng., Shanghai Jiao Tong Univ., Shanghai, China
fYear
2014
fDate
27-31 July 2014
Firstpage
1
Lastpage
5
Abstract
There has been continuous development of methods for evaluating transient stability of power system incorporating wind farms. A stochastic model of power systems with wind farms is proposed in this paper. The model takes into account both of the random initial values and stochastic noise of wind speed, with which power system transient stability analysis is modeled as a stochastic initial value problem (SIVP). Monte Carlo trials transform the model into stochastic differential algebraic equations (SDAEs). An implicit numerical method for SDAEs is discussed, which is similar to implicit trapezoidal integration for deterministic differential algebraic equations (DAEs). Case studies illustrating the proposed model are tested on the IEEE 39-bus 10-machine system. The simulation results demonstrate that the proposed model can provide comprehensive description of stochastic excitation of wind farms.
Keywords
IEEE standards; Monte Carlo methods; differential algebraic equations; initial value problems; power system transient stability; stochastic processes; wind power plants; IEEE 39-bus 10-machine system; Monte Carlo trials; SDAE; SIVP; implicit numerical method; implicit trapezoidal integration; power system transient stability; random initial values; stochastic differential algebraic equations; stochastic initial value problem; stochastic model; stochastic noise; wind farms; wind power; wind speed; Mathematical model; Noise; Power system stability; Power system transients; Stability analysis; Stochastic processes; Wind speed; Implicit Trapezoidal Integration; Monte Carlo Simulation; Stochastic Differential Algebraic Equations; Stochastic Initial Value Problem;
fLanguage
English
Publisher
ieee
Conference_Titel
PES General Meeting | Conference & Exposition, 2014 IEEE
Conference_Location
National Harbor, MD
Type
conf
DOI
10.1109/PESGM.2014.6939022
Filename
6939022
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