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
•Journal Article
Real-Time Dual Heuristic Programming-Based Neurocontroller for a Turbogenerator in a Multimachine Power System
TL;DR: Simulation and real-time hardware implementation demonstrate that the DHP neurocontroller is much more effective than conventional PID controllers, the automatic voltage regulator, power system stabilizer and the governor, for improving dynamic performance and stability under small and large disturbances.
Multiple Reference Frame-Based Control of Three-Phase PWM Boost Rectifiers under Unbalanced and Distorted Input Conditions
Abstract: Many control algorithms and circuits for three-phase pulse width modulation active rectifiers have been proposed in the past decades. In most of the research, it is often assumed that the input voltages are balanced or contain only fundamental frequency components. In this paper, a selective harmonic compensation method is proposed based on an improved multiple reference frame algorithm, which decouples signals of different frequencies before reference frame transformation. This technique eliminates interactions between the fundamental-frequency positive-sequence components and harmonic and/or negative-sequence components in the input currents, so that fast and accurate regulation of harmonic and unbalanced currents can be achieved. A decoupled phase-locked loop algorithm is used for proper synchronization with the utility voltage, which also benefits from the multiple reference frame technique. The proposed control method leads to considerable reduction in low-order harmonic contents in the rectifier input current and achieves almost zero steady-state error through feedback loops. Extensive experimental tests based on a fixed-point digital signal processor controlled 2 kW prototype are used to verify the effectiveness of the proposed ideas.
Cyber security in smart DC microgrid operations
Xingsi Zhong,Lu Yu,Richard R. Brooks,Ganesh K. Venayagamoorthy +3 more
- 07 Jun 2015
TL;DR: In this article, the authors discuss security vulnerabilities and some solutions for DC microgrids, which are low voltage electric distribution grids with modular distributed energy sources and controllable loads.
Distributed Volt-Var Curve Optimization Using a Cellular Computational Network Representation of an Electric Power Distribution System
TL;DR: In this paper , the authors presented a simple, scalable, and robust distributed optimization framework (DOF) for optimizing voltage control in modern electric power distribution systems, which allows data-driven distributed voltage optimization in a power distribution system.
Neural networks letter: Effects of spectral radius and settling time in the performance of echo state networks
TL;DR: The effects of varying two important ESN parameters, the spectral radius (alpha) and settling time (ST) are studied in this letter.