Papers by G. Venayagamoorthy
31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005., 2005
IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)
This paper presents the design of a Continually Online Trained (COP Artificial Neural Network (AN... more This paper presents the design of a Continually Online Trained (COP Artificial Neural Network (ANN) controller for a laboratory turbogenerator system connected to the infhite bus through a transmission line in real time. Two COT AMVs are used for the implementation; one ANN to identifv the complex nonlinear +zamics of the power system and the other AhPJ to control the turbogenerator. Practical results are presented to show that COT AhPJ controllers can control turbogenerators under steady state as well as transient conditions in the laboratory environment.
Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems
The increasing complexity of the modern power grid highlights the need for advanced modeling and ... more The increasing complexity of the modern power grid highlights the need for advanced modeling and control techniques for effective control of excitation, turbine and Flexible AC Transmission Systems (FACTS). The crucial factors affecting the modern power systems today is voltage and load flow control. Simulation studies in the PSCAD/EMTDC environment and realtime laboratory experimental studies carried out are described and the results show the successful control of the power system elements and the entire power system with adaptive and optimal neurocontrol schemes. Performances of the neurocontrollers are compared with the conventional PI controllers for damping under different operating conditions for small and large disturbances.
2007 IEEE Power Engineering Society General Meeting, 2007
2006 IEEE Power Engineering Society General Meeting, 2006
2012 IEEE Power and Energy Society General Meeting, 2012
ABSTRACT High penetration of intermittent renewable energy demands major upgrades to the existing... more ABSTRACT High penetration of intermittent renewable energy demands major upgrades to the existing power grid transmission infrastructure. Increasing transmission capacities and interconnections creates larger balancing areas. With a larger balancing area, more grid-connected energy systems can be coordinated to achieve one or multiple control objectives (for example, balancing intermittent renewable energy), but how to achieve such an optimal coordination has not yet been fully answered. The existing power system operation method is based on steady-state optimization that may break down when fast variation is present in the system. To provide a coordinating control solution to multiple grid-connected energy systems, an intelligent real-time power flow control method, namely the dynamic stochastic optimal power flow (DSOPF) control, is presented in this paper. The DSOPF control algorithm is based on the Adaptive Critic Designs (ACDs), which provide methods to design optimal neurocontrollers without the need of system analytical models. Studies on a 12-bus and a 70-bus test power system are presented to demonstrate the DSOPF controller.
2012 IEEE Power and Energy Society General Meeting, 2012
This paper introduces a new concept called a Virtual Generator (VG). VGs are simplified represent... more This paper introduces a new concept called a Virtual Generator (VG). VGs are simplified representations of groups of coherent synchronous generators in a power system. They resemble commonly used power system dynamic equivalents obtained via generator aggregation techniques. Traditionally power system dynamic equivalents are developed offline, fixed, and used to replace large portions of the system that are considered external to the portion of the system being analyzed in detail. In contrast, VGs are calculated online, are not limited to representing external areas of the system being analyzed/controlled, and do not replace any portion of the power system. Instead, they allow wide-area damping controllers (WADCs) to exploit the realization that a group of coherent synchronous generators in a power system can be controlled as a single generating unit for achieving wide-area damping control objectives. The implementation of VGs is made possible by the availability of Wide-Area Measurements (WAMs) from Phasor Measurement Units (PMUs). To the authors' knowledge, this is the first time that the use of power system equivalencing techniques has been extended to real-time WADC. Simulation studies carried out on the 68-bus New England/New York power system demonstrate that intelligent controllers developed using VGs can significantly improve the stability of a power system by effectively damping low-frequency interarea oscillations.
2006 37th IEEE Power Electronics Specialists Conference
The increased use of nonlinear devices in industry has resulted in direct increase of harmonic di... more The increased use of nonlinear devices in industry has resulted in direct increase of harmonic distortion in the industrial power system. Variable speed drives are an example. With the widespread proliferation of nonlinear loads in a power distribution network, the voltage at the point of common coupling is rarely a pure sinusoid. It has become necessary to identify accurately which load(s) is injecting the excessively high harmonic currents. Simply measuring the harmonic currents at each individual load is not sufficiently accurate since these harmonic currents may be caused by not only the nonlinear load, but also by a non-sinusoidal PCC voltage. This paper proposes a neural network solution methodology for the problem of measuring the actual amount of harmonic current injected into a power network by a three phase variable speed drive, and this technique can be extended to any nonlinear load in general. The proposed method has been experimentally verified by applying the scheme to a commercially available variable speed drive. The scheme has been applied to each phase individually as well as to all three phases together. The goal of this paper is to quantify the difference in current distortion of a load when supplied from a distorted source as compared to a clean sine wave. A Multilayer Perceptron Neural Network is used to estimate the true harmonic current distortion of a load. Theory and practical results are presented. This technology could be integrated into any commercially available power quality instrument or be fabricated as a standalone instrument.
2006 IEEE PES Power Systems Conference and Exposition, 2006
2008 IEEE Swarm Intelligence Symposium, 2008
2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309)
IEEE Power Engineering Society General Meeting, 2004.
2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491)
In this paper, the application of a novel and computationally enhanced genetic algorithm (CA) for... more In this paper, the application of a novel and computationally enhanced genetic algorithm (CA) for solving the reactive power dispatch problem is presented. In order to attain a significant reduction in the computational time of GA, a systematic procedure of reactive power control device preselection mechanism is herein proposed to choose a-priori subsets of the available control devices, which maximally influence buses experiencing voltage limit violations. The GA reactive power dispatch module then accesses such judiciously pre-selected control device candidates to determine their optimal settings. A pragmatic scheme aimed at further curtailing the number of the final control actions entertained is also set forth. The farreaching simulation results obtained for two case study scenarios using the proposed algorithmic procedures on a German utility network of Duisburg, replicated on an operator-training simulator, are presented and fully discussed in depth.
2007 International Conference on Intelligent Systems Applications to Power Systems, 2007
This paper presents the comparative application of two metaheuristic approaches: Differential Evo... more This paper presents the comparative application of two metaheuristic approaches: Differential Evolution (DE) and Particle Swarm Optimization (PSO) to the solution of the reactive power and voltage control problem. Efficient distribution of reactive power in an electric network leads to minimization of the system losses and improvement of the system voltage profile. It can be achieved by varying the excitation of generators or the on-load tap changer positions of transformers as well as by switching of discrete portions of inductors or capacitors etc. This constitutes a typical mixed integer non-linear optimization problem for the solution of which metaheuristic techniques have proven well suited in principle. The feasibility, effectiveness and generic nature of both DE and PSO approaches investigated are exemplarily demonstrated on the Nigerian grid system and the New England power system. Comparisons were made between the two approaches in terms of the solution quality and convergence characteristics. The simulation results revealed that both approaches were able to remove the voltage limit violations, but PSO procured in some instances slightly higher power loss reduction as compared with DE; on the other hand DE required a lower number of function evaluations as compared with PSO. Consideration of computational effort is relevant for potential real time on line application.
2007 IEEE Power Engineering Society General Meeting, 2007
IEEE Power Engineering Society General Meeting, 2005
IEEE Power Engineering Society General Meeting, 2005
2009 15th International Conference on Intelligent System Applications to Power Systems, 2009
An optimal transient controller for a synchronous generator in a multi-machine power system is de... more An optimal transient controller for a synchronous generator in a multi-machine power system is designed using the concept of flatness-based feedback linearization in this paper. The computation of the flat output and corresponding controller for reduced order model of the synchronous generator is presented. The required feedback gains used to close the linearization loop is optimized using particle swarm optimization for maximum damping. Typical results obtained for transient disturbances on a two-area, four-generator power system equipped with the proposed controller on one generator and conventional power system stabilizers on the remaining generators are presented. The effectiveness of the flatness-based controller for multi-machine power systems is discussed.
2007 IEEE Power Engineering Society General Meeting, 2007
IET Generation, Transmission & Distribution, 2008
A modified discrete particle swarm optimisation (MDPSO) algorithm to generate optimal preventive ... more A modified discrete particle swarm optimisation (MDPSO) algorithm to generate optimal preventive maintenance schedule of generating units for economical and reliable operation of a power system, while satisfying system load demand and crew constraints, is presented. Discrete particle swarm optimisation (DPSO) is known to effectively solve large-scale multi-objective optimisation problems and has been widely applied in power system. The MDPSO proposed for the generator maintenance scheduling optimisation problem generates optimal and feasible solutions and overcomes the limitations of the conventional methods, such as extensive computational effort, which increases exponentially as the size of the problem increases. The efficacy of the proposed algorithm is illustrated and compared with the genetic algorithm (GA) and DPSO in two case studies-a 21-unit test system and a 49-unit system feeding the Nigerian national grid. The MDPSO algorithm is found to generate schedules with comparatively higher system reliability indices than those obtained with GA and DPSO. Nomenclature AM t available manpower at period t X id ith particle position in dimension d 834
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Papers by G. Venayagamoorthy