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Design of Multi-Machine Power System Stabilizers with Forecast Uncertainties in Load/Generation.

Authors :
Krishan, Ram
Verma, Ashu
Mishra, Sukumar
Source :
IETE Journal of Research; Jan2019, Vol. 65 Issue 1, p44-57, 14p
Publication Year :
2019

Abstract

Oscillatory instability in modern power system has increased due to increasing complexity and integration of dynamic loads. Stability analysis of such interconnected power system is very prominent in the presence of uncertain load/generation. In this paper, a power system stabilizer (PSS) design approach, which aims at enhancing the oscillatory stability of the multi-machine power system over the specified uncertainty range in forecasted load/generation, is presented. With non-statistical uncertainty, problem of selecting design parameters of the PSS is formulated as an optimization problem with minimization of eigenvalues and damping ratios based multi-objective function. In order to account the non-statistical uncertainties, a boundary active power loss (BAPL) based objective function is proposed. This non-linear BAPL objective function is minimized for determining the optimal setting of the generators voltage and taps of the online tap changing transformers (OLTC) under various power system constraints. In this paper, both the objective functions are solved by a new metaheuristic technique known as gray wolf optimization (GWO). Boundary value-based approach is used to minimize the repeated load flows under uncertain load/generation scenarios. Improved small-signal stability (SSS) is achieved with optimal active power loss of uncertain power system. Eigenvalue and time domain analysis for New England system are carried out under wide range of disturbances to demonstrate the potential of the proposed approach. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03772063
Volume :
65
Issue :
1
Database :
Complementary Index
Journal :
IETE Journal of Research
Publication Type :
Academic Journal
Accession number :
134995746
Full Text :
https://doi.org/10.1080/03772063.2017.1391131