Ganesh K. Venayagamoorthy
Clemson University
449 Papers
4.3K Citations
Ganesh K. Venayagamoorthy is an academic researcher from Clemson University. The author has contributed to research in topics: Electric power system & Particle swarm optimization. The author has an hindex of 56, co-authored 435 publications. Previous affiliations of Ganesh K. Venayagamoorthy include University of KwaZulu-Natal & ML Sultan Technikon.
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Papers
Stochastic Subspace Identification Validation of PV Inverter Operation Improvement with Optimally–Tuned Controllers
Ali Arzani,Paranietharan Arunagirinathan,Ganesh K. Venayagamoorthy +2 more
- 01 Sep 2018
TL;DR: Stochastic Subspace Identification method (SSI) results in frequency domain are compared with time-domain to conclude the effectuality of the SSI empirical approach in validating improvement in PV inverter operation with heuristic-tuned PV-VSI controllers’ parameters in time- domain.
Implementation of neuroidentifiers trained by PSO on a PLC platform for a multimachine power system
C. Parrott,Ganesh K. Venayagamoorthy +1 more
- 07 Nov 2008
TL;DR: In this paper, two separate neuro-identifiers are trained using the particle swarm optimization (PSO) algorithm to identify the dynamics in a two-area four machine power system, one neuroidentifier for Area 1 and the other for Area 2.
An Adaptive Control Strategy for DSTATCOM Applications in an Electric Ship Power System
TL;DR: In this article, an adaptive control strategy for distribution static compensator (DSTATCOM) based on artificial immune system (AIS) is presented, which provides a sort of innate immunity (robustness) to common system disturbances.
Frequency stability and control of a power system with large PV plants using PMU information
Abdlmnam Abdlrahem,Ganesh K. Venayagamoorthy,Keith Corzine +2 more
- 25 Nov 2013
TL;DR: In this paper, the impact of a large PV plant on the frequency stability of a power system under small and large disturbances is investigated. But the effects of increased PV penetration in a given power system area are examined.
Adaptive neural network based power system stabilizer design
Wenxin Liu,Ganesh K. Venayagamoorthy,Donald C. Wunsch +2 more
- 20 Jul 2003
TL;DR: In this article, an indirect adaptive neural network based power system stabilizer (IDNC) design is proposed, which consists of a neuro-controller, which is used to generate a supplementary control signal to the excitation system, and a neuroidentifier, which was used to model the dynamics of the power system and to adapt the neurocontroller parameters.