DocumentCode :
14522
Title :
Quasi-Monte Carlo Based Probabilistic Small Signal Stability Analysis for Power Systems With Plug-In Electric Vehicle and Wind Power Integration
Author :
Huazhang Huang ; Chung, C.Y. ; Chan, Ka Wing ; Haoyong Chen
Author_Institution :
Dept. of Electr. Eng., Hong Kong Polytech. Univ., Hong Kong, China
Volume :
28
Issue :
3
fYear :
2013
fDate :
Aug. 2013
Firstpage :
3335
Lastpage :
3343
Abstract :
This paper presents a new quasi-Monte Carlo (QMC) based probabilistic small signal stability analysis (PSSSA) method to assess the dynamic effects of plug-in electric vehicles (PEVs) and wind energy conversion systems (WECSs) in power systems. The detailed dynamic model of PEVs is first proposed for stability study. To account for the stochastic behavior of PEVs and WECSs in load flow studies, the randomized model and probability density function (PDF) representing their nodal power injections are first developed, and then their stochastic injections are sampled by Sobol sequences. Finally, the distribution of system eigenvalues can be obtained by the PSSSA. The proposed QMC-based PSSSA is tested on the modified 2-area 4-machine system and New England 10-generator 39-bus system. Results showed the necessity of modeling of PEVs and WECSs, and validated the efficiency of the proposed QMC.
Keywords :
Monte Carlo methods; battery chargers; eigenvalues and eigenfunctions; electric vehicles; power system stability; probability; wind power; 2-area 4-machine system; New England 10-generator 39-bus system; PDF; PEV; PSSSA method; Sobol sequences; WECS; plug-in electric vehicles; power systems; probabilistic small signal stability analysis; probability density function; quasiMonte Carlo method; wind energy conversion systems; wind power integration; Monte Carlo simulation; Sobol sequence; plug-in electric vehicle; probabilistic small signal stability analysis; quasi-Monte Carlo; wind energy conversion system;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2013.2254505
Filename :
6496179
Link To Document :
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