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.
| Original language | English |
|---|---|
| Article number | 6496179 |
| Pages (from-to) | 3335-3343 |
| Number of pages | 9 |
| Journal | IEEE Transactions on Power Systems |
| Volume | 28 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 15 Apr 2013 |
Keywords
- Monte Carlo simulation
- plug-in electric vehicle
- probabilistic small signal stability analysis
- quasi-Monte Carlo
- Sobol sequence
- wind energy conversion system
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering