Abstract
A modified fruit fly optimization algorithm (MFOA) combined with a probabilistic approach are proposed in this paper to coordinate and optimize the parameters of power system stabilizers (PSSs) and static VAR compensator (SVC) damping controller for improving the probabilistic small-signal stability of power systems with large-scale wind generation, taking into consideration the stochastic uncertainty of system operating conditions. It is generally accepted that there is a threat to the stability of power system with penetration of wind farm. In addition, the stochastic fluctuations of wind generation make PSSs tuning more difficult. In this paper, PSSs and SVC damping controller are employed for suppressing local and inter-area low frequency oscillation. In order to eliminate the adverse effect between PSSs and SVC damping controller, the MFOA based on the probabilistic eigenvalue is applied to coordinate and optimize their parameters. The effectiveness of the proposed approach is verified on two test systems.
| Original language | English |
|---|---|
| Pages (from-to) | 2371-2382 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Power Systems |
| Volume | 31 |
| Issue number | 3 |
| Early online date | 7 Aug 2015 |
| DOIs | |
| Publication status | Published - 1 May 2016 |
Keywords
- modified fruit fly optimization algorithm (MFOA)
- power system stabilizer (PSS)
- probabilistic small-signal stability
- static VAR compensator (SVC)
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