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Articles 31 - 60 of 125
Full-Text Articles in Engineering
Learning Functions Generated By Randomly Initialized Mlps And Srns, R. Cleaver, Ganesh K. Venayagamoorthy
Learning Functions Generated By Randomly Initialized Mlps And Srns, R. Cleaver, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, nonlinear functions generated by randomly initialized multilayer perceptrons (MLPs) and simultaneous recurrent neural networks (SRNs) and two benchmark functions are learned by MLPs and SRNs. Training SRNs is a challenging task and a new learning algorithm - PSO-QI is introduced. PSO-QI is a standard particle swarm optimization (PSO) algorithm with the addition of a quantum step utilizing the probability density property of a quantum particle. The results from PSO-QI are compared with the standard backpropagation (BP) and PSO algorithms. It is further verified that functions generated by SRNs are harder to learn than those generated by MLPs …
A Successful Interdisciplinary Course On Computational Intelligence, Ganesh K. Venayagamoorthy
A Successful Interdisciplinary Course On Computational Intelligence, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
This article presents experiences from the introduction of a new three hour interdisciplinary course on computational intelligence (CI) taught at the Missouri University of Science and Technology, USA at the undergraduate and graduate levels. This course is unique in the sense that it covers five main paradigms of CI and their integration to develop hybrid intelligent systems. The paradigms covered are artificial immune systems (AISs), evolutionary computing (EC), fuzzy systems (FSs), neural networks (NNs) and swarm intelligence (SI). While individual CI paradigms have been applied successfully to solve real-world problems, the current trend is to develop hybrids of these paradigms …
Coordinated Reactive Power Control Of A Large Wind Farm And A Statcom Using Heuristic Dynamic Programming, Wei Qiao, Ronald G. Harley, Ganesh K. Venayagamoorthy
Coordinated Reactive Power Control Of A Large Wind Farm And A Statcom Using Heuristic Dynamic Programming, Wei Qiao, Ronald G. Harley, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
A novel interface neurocontroller (INC) is proposed for the coordinated reactive power control between a large wind farm equipped with doubly fed induction generators (DFIGs) and a static synchronous compensator (STATCOM). The heuristic dynamic programming (HDP) technique and radial basis function neural networks (RBFNNs) are used to design this INC. It effectively reduces the level of voltage sags as well as the over-currents in the DFIG rotor circuit during grid faults, and therefore, significantly enhances the fault ride-through capability of the wind farm. The INC also acts as a coordinated external damping controller for the wind farm and the STATCOM, …
Seven-Level Shunt Active Power Filter For High-Power Drive Systems, Peng Xiao, Ganesh K. Venayagamoorthy, Keith Corzine
Seven-Level Shunt Active Power Filter For High-Power Drive Systems, Peng Xiao, Ganesh K. Venayagamoorthy, Keith Corzine
Electrical and Computer Engineering Faculty Research & Creative Works
In high-power adjustable-speed motor drives, such as those used in electric ship propulsion systems, active filters provide a viable solution to mitigating harmonic related issues caused by diode or thyristor rectifier front-ends. To handle the large compensation currents and provide better thermal management, two or more paralleled semiconductor switching devices can be used. In this paper, a novel topology is proposed where two active filter inverters are connected with tapped reactors to share the compensation currents. The proposed active filter topology can also produce seven voltage levels, which significantly reduces the switching current ripple and the size of passive components. …
Fully Evolvable Optimal Neurofuzzy Controller Using Adaptive Critic Designs, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
Fully Evolvable Optimal Neurofuzzy Controller Using Adaptive Critic Designs, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
A near-optimal neurofuzzy external controller is designed in this paper for a static compensator (STATCOM) in a multimachine power system. The controller provides an auxiliary reference signal for the STATCOM in such a way that it improves the damping of the rotor speed deviations of its neighboring generators. A zero-order Takagi-Sugeno fuzzy rule base constitutes the core of the controller. A heuristic dynamic programming (HDP) based approach is used to further train the controller and enable it to provide nonlinear near-optimal control at different operating conditions of the power system. Based on the connectionist systems theory, the parameters of the …
Power System Control With An Embedded Neural Network In Hybrid System Modeling, Seung-Mook Baek, Jung-Wook Park, Ganesh K. Venayagamoorthy
Power System Control With An Embedded Neural Network In Hybrid System Modeling, Seung-Mook Baek, Jung-Wook Park, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
Output limits of the power system stabilizer (PSS) can improve the system damping performance immediately following a large disturbance. Due to nonsmooth nonlinearities arising from the saturation limits, these values cannot be determined by the conventional tuning methods based on linear analysis. Only ad hoc tuning procedures can been used. A feedforward neural network (with a structure of multilayer perceptron neural network) is applied to identify the dynamics of an objective function formed by the states and, thereafter, to compute the gradients required in the nonlinear parameter optimization. Moreover, its derivative information is used to replace that obtained from the …
Intelligent Tool For Determining The True Harmonic Current Contribution Of A Customer In A Power Distribution Network, Joy Mazumdar, Ronald G. Harley, Frank C. Lambert, Ganesh K. Venayagamoorthy, Marty L. Page
Intelligent Tool For Determining The True Harmonic Current Contribution Of A Customer In A Power Distribution Network, Joy Mazumdar, Ronald G. Harley, Frank C. Lambert, Ganesh K. Venayagamoorthy, Marty L. Page
Electrical and Computer Engineering Faculty Research & Creative Works
Customer loads connected to power distribution network may be broadly categorized as either linear or nonlinear. Nonlinear loads inject harmonics into the power network. Harmonics in a power system are classified as either load harmonics or as supply harmonics depending on their origin. The source impedance also impacts the harmonic current flowing in the network. Hence, any change in the source impedance is reflected in the harmonic spectrum of the current. This paper proposes a novel method based on artificial neural networks to isolate and evaluate the impact of the source impedance change without disrupting the operation of any load, …
Bio-Inspired Algorithms For The Design Of Multiple Optimal Power System Stabilizers: Sppso And Bfa, Tridib Kumar Das, Ganesh K. Venayagamoorthy, Usman O. Aliyu
Bio-Inspired Algorithms For The Design Of Multiple Optimal Power System Stabilizers: Sppso And Bfa, Tridib Kumar Das, Ganesh K. Venayagamoorthy, Usman O. Aliyu
Electrical and Computer Engineering Faculty Research & Creative Works
Damping intra-area and interarea oscillations are critical to optimal power flow and stability in a power system. Power system stabilizers (PSSs) are effective damping devices, as they provide auxiliary control signals to the excitation systems of generators. The proper selection of PSS parameters to accommodate variations in the power system dynamics is important and is a challenging task particularly when several PSSs are involved. Two classical bio-inspired algorithms, which are smallpopulation- based particle swarm optimization (SPPSO) and bacterial foraging algorithm (BFA), are presented in this paper for the simultaneous design of multiple optimal PSSs in two power systems. A classical …
Comparison Of Adaptive Critic-Based And Classical Wide-Area Controllers For Power Systems, Swakshar Ray, Ganesh K. Venayagamoorthy, Balarko Chaudhuri, Rajat Majumder
Comparison Of Adaptive Critic-Based And Classical Wide-Area Controllers For Power Systems, Swakshar Ray, Ganesh K. Venayagamoorthy, Balarko Chaudhuri, Rajat Majumder
Electrical and Computer Engineering Faculty Research & Creative Works
An adaptive critic design (ACD)-based damping controller is developed for a thyristor-controlled series capacitor (TCSC) installed in a power system with multiple poorly damped interarea modes. The performance of this ACD computational intelligence-based method is compared with two classical techniques, which are observer-based state-feedback (SF) control and linear matrix inequality $hbox{LMI-H}^{infty}$ robust control. Remote measurements are used as feedback signals to the wide-area damping controller for modulating the compensation of the TCSC. The classical methods use a linearized model of the system whereas the ACD method is purely measurement-based, leading to a nonlinear controller with fixed parameters. A comparative analysis …
A Computational Approach To Optimal Damping Controller Design For A Gcsc, Swakshar Ray, Ganesh K. Venayagamoorthy, Edson H. Watanabe
A Computational Approach To Optimal Damping Controller Design For A Gcsc, Swakshar Ray, Ganesh K. Venayagamoorthy, Edson H. Watanabe
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a computational approach for an offline measurement-based design of an optimal damping controller using adaptive critics for a new type of flexible ac transmission system device-the gate-controlled series capacitor (GCSC). Remote measurements are provided to the controller to damp out system modes. The optimal controller is developed based on the heuristic dynamic programming (HDP) approach. Three multilayer-perceptron neural networks are used in the design-the identifier/model network to identify the dynamics of the power system, the critic network to evaluate the performance of the damping controller, and the controller network to provide optimal damping. This measurement-based technique provides …
Nsf Career: Scalable Learning And Adaptation With Intelligent Techniques And Neural Networks For Reconfiguration And Survivability Of Complex Systems, Ganesh K. Venayagamoorthy
Nsf Career: Scalable Learning And Adaptation With Intelligent Techniques And Neural Networks For Reconfiguration And Survivability Of Complex Systems, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
The NSF CAREER program is a premier program that emphasizes the importance the foundation places on the early development of academic careers solely dedicated to stimulating the discovery process in which the excitement of research enriched by inspired teaching and enthusiastic learning. This paper describes the research and education experiences gained by the principal investigator and his research collaborators and students as a result of a NSF CAREER proposal been awarded by the power, control and adaptive networks (PCAN) program of the electrical, communications and cyber systems division, effective June 1, 2004. In addition, suggestions on writing a winning NSF …
Multiple Reference Frame-Based Control Of Three-Phase Pwm Boost Rectifiers Under Unbalanced And Distorted Input Conditions, Peng Xiao, Keith Corzine, Ganesh K. Venayagamoorthy
Multiple Reference Frame-Based Control Of Three-Phase Pwm Boost Rectifiers Under Unbalanced And Distorted Input Conditions, Peng Xiao, Keith Corzine, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
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 Dstatcom Controller Tuned By Particle Swarm Optimization For An Electric Ship Power System, Pinaki Mitra, Ganesh K. Venayagamoorthy
A Dstatcom Controller Tuned By Particle Swarm Optimization For An Electric Ship Power System, Pinaki Mitra, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
In an all-electric ship power system, the power quality problems mainly arise due to the pulsed loads, which cause the degradation of the overall system performance. The paper proposes the application of DSTATCOM to improve these power quality problems of an electric ship. DSTATCOM is a shunt compensation device, which regulates the bus voltage by injecting reactive power during the pulsed load operations. The control strategy of DSTATCOM plays an important role to meet the objectives. The paper proposes a controller design strategy which is based on particle swarm optimization (PSO). PSO, an algorithm that falls into swarm intelligence family, …
Clustering Of High-Dimensional Gene Expression Data With Feature Filtering Methods And Diffusion Maps, Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wunsch
Clustering Of High-Dimensional Gene Expression Data With Feature Filtering Methods And Diffusion Maps, Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challenges in the computational analysis of such data is the curse of dimensionality, due to the overwhelming number of measures of gene expression levels versus the small number of samples. Here, we use a two-step method to reduce the dimension of gene expression data. At first, we extract a subset of genes based on the statistical characteristics of their corresponding gene expression measurements. For further dimensionality reduction, we then apply diffusion maps, …
Dual-Function Neuron-Based External Controller For A Static Var Compensator, Ganesh K. Venayagamoorthy, Sandhya R. Jetti
Dual-Function Neuron-Based External Controller For A Static Var Compensator, Ganesh K. Venayagamoorthy, Sandhya R. Jetti
Electrical and Computer Engineering Faculty Research & Creative Works
The use of wide-area measurements for power system stabilization has recently been given a lot of attention by researchers and the power industry to avoid cascading failures and blackouts, such as the one in North America in August 2003. This paper presents the design of a nonlinear external damping controller based on wide-area measurements as inputs to a single dual-function neuron (DFN)-based controller. This DFN controller is specifically designed to enhance the damping characteristics of a power system over a wide range of operating conditions using an existing static var compensator (SVC) installation. The major advantage of the DFN controller …
Fault-Tolerant Optimal Neurocontrol For A Static Synchronous Series Compensator Connected To A Power Network, Wei Qiao, Ronald G. Harley, Ganesh K. Venayagamoorthy
Fault-Tolerant Optimal Neurocontrol For A Static Synchronous Series Compensator Connected To A Power Network, Wei Qiao, Ronald G. Harley, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
This paper proposes a novel fault-tolerant optimal neurocontrol scheme (FTONC) for a static synchronous series compensator (SSSC) connected to a multimachine benchmark power system. The dual heuristic programming technique and radial basis function neural networks are used to design a nonlinear optimal neurocontroller (NONC) for the external control of the SSSC. Compared to the conventional external linear controller, the NONC improves the damping performance of the SSSC. The internal control of the SSSC is achieved by a conventional linear controller. A sensor evaluation and (missing sensor) restoration scheme (SERS) is designed by using the autoassociative neural networks and particle swarm …
Real-Time Implementation Of A Statcom On A Wind Farm Equipped With Doubly Fed Induction Generators, Wei Qiao, Ganesh K. Venayagamoorthy, Ronald G. Harley
Real-Time Implementation Of A Statcom On A Wind Farm Equipped With Doubly Fed Induction Generators, Wei Qiao, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
Voltage stability is a key issue to achieve the uninterrupted operation of wind farms equipped with doubly fed induction generators (DFIGs) during grid faults. This paper investigates the application of a static synchronous compensator (STATCOM) to assist with the uninterrupted operation of a wind turbine driving a DFIG, which is connected to a power network, during grid faults. The control schemes of the DFIG rotor- and grid-side converters and the STATCOM are suitably designed and coordinated. The system is implemented in real-time on a real time digital simulator. Results show that the STATCOM improves the transient voltage stability and therefore …
Intelligent Local And Hierarchical Control Of Facts Devices, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
Intelligent Local And Hierarchical Control Of Facts Devices, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents an overview of the applications of intelligent control techniques on local and hierarchical control of FACTS devices. These control techniques are superior to the conventional linear/nonlinear control schemes in the sense that they are independent of any mathematical model of the power system to be controlled. In addition, they do not depend on the operating conditions and the configuration of the system to which the FACTS device is connected. A static compensator (STATCOM) is used as the example in order to compare the performances of the proposed intelligent controllers with those of their linear counterparts. Nevertheless, the …
Identification Of Induction Machines Stator Currents With Generalized Neurons, Jing Huang, Ganesh K. Venayagamoorthy, Keith Corzine
Identification Of Induction Machines Stator Currents With Generalized Neurons, Jing Huang, Ganesh K. Venayagamoorthy, Keith Corzine
Electrical and Computer Engineering Faculty Research & Creative Works
A new approach to identify the nonlinear model of an induction machine using two generalized neurons (GNs) is presented in this paper. Compared to the multilayer perceptron feedforward neural network, a GN has simpler structure and lesser requirement in terms of memory storage which is makes it attractive for hardware implementation. This method shows that with less number of weights, GN is able to learn the dynamics of an induction machine. The proposed model is made by two coupled networks. A modified particle swarm optimization algorithm is designed to solve this distinctive GN training problem. A pseudo-random binary sequence signal …
Swarm Intelligence For Transmission System Control, Ganesh K. Venayagamoorthy, Ronald G. Harley
Swarm Intelligence For Transmission System Control, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
Many areas related to power system transmission require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality, heuristics based swarm intelligence can be an efficient alternative. This paper highlights the application of swam intelligence techniques for solving some of the transmission system control problems.
Dynamic Modeling Of Wind Farms With Fixed-Speed Wind Turbine Generators, Wei Qiao, Ronald G. Harley, Ganesh K. Venayagamoorthy
Dynamic Modeling Of Wind Farms With Fixed-Speed Wind Turbine Generators, Wei Qiao, Ronald G. Harley, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
A wind farm typically consists of a large number of individual wind turbine generators (WTGs) connected by an internal electrical network. To study the impact of wind farms on the dynamics of the power system, an important issue is to develop appropriate wind farm models to represent the dynamics of many individual WTGs. This paper presents various dynamic models, including a detailed model and three reduced-order equivalent models, of wind farms with fixed-speed WTGs. These models are developed and compared by simulation studies in the PSCAD/EMTDC environment under different wind velocity and fluctuation conditions as well as gird fault conditions. …
Neural Network Based Method For Predicting Nonlinear Load Harmonics, Joy Mazumdar, Ronald G. Harley, Frank C. Lambert, Ganesh K. Venayagamoorthy
Neural Network Based Method For Predicting Nonlinear Load Harmonics, Joy Mazumdar, Ronald G. Harley, Frank C. Lambert, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
Generation of harmonics and the existence of waveform pollution in power system networks are important problems facing the power utilities. The increased use of nonlinear devices in industry has resulted in direct increase of harmonic distortion in the industrial power system in recent years. Interaction between loads and sources in a power distribution network is a complex process and often not possible to explain analytically without making assumptions. The determination of true harmonic current distortion of a load is further complicated by the fact that the supply voltage waveform at the point of common coupling (PCC) is rarely a pure …
A Proportional-Integrator Type Adaptive Critic Design-Based Neurocontroller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Yamille Del Valle, Ronald G. Harley
A Proportional-Integrator Type Adaptive Critic Design-Based Neurocontroller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Yamille Del Valle, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
A novel nonlinear optimal controller for a static compensator (STATCOM) connected to a power system, using artificial neural networks, is presented in this paper. The action dependent heuristic dynamic programming, a member of the adaptive critic designs family is used for the design of the STATCOM neurocontroller. This neurocontroller provides optimal control based on reinforcement learning and approximate dynamic programming. Using a proportional-integrator approach, the proposed neurocontroller is capable of dealing with actual rather than deviation signals. Simulation results are provided to show that the proposed controller outperforms a conventional PI controller for a STATCOM in a small and large …
Optimal Wide Area Controller And State Predictor For A Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
Optimal Wide Area Controller And State Predictor For A Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
An optimal wide area controller is designed in this paper for a 12-bus power system together with a Static Compensator (STATCOM). The controller provides auxiliary reference signals for the automatic voltage regulators (AVR) of the generators as well as the line voltage controller of the STATCOM in such a way that it improves the damping of the rotor speed deviations of the synchronous machines. Adaptive critic designs theory is used to implement the controller and enable it to provide nonlinear optimal control over the infinite horizon time of the problem and at different operating conditions of the power system. Simulation …
Comparison Of Nonuniform Optimal Quantizer Designs For Speech Coding With Adaptive Critics And Particle Swarm, Ganesh K. Venayagamoorthy, Wenwei Zha
Comparison Of Nonuniform Optimal Quantizer Designs For Speech Coding With Adaptive Critics And Particle Swarm, Ganesh K. Venayagamoorthy, Wenwei Zha
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents the design of a companding nonuniform optimal scalar quantizer for speech coding. The quantizer is designed using two neural networks to perform the nonlinear transformation. These neural networks are used in the front and back ends of a uniform quantizer. Two approaches are presented in this paper namely adaptive critic designs and particle swarm optimization, aiming to maximize the signal-to-noise ratio. The comparison of these optimal quantizer designs over a bit-rate range of 3-6 is presented. The perceptual quality of the coding is evaluated by the International Telecommunication Union's Perceptual Evaluation of Speech Quality standard
Optimal Neuro-Fuzzy External Controller For A Statcom In The 12-Bus Benchmark Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
Optimal Neuro-Fuzzy External Controller For A Statcom In The 12-Bus Benchmark Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
An optimal neuro-fuzzy external controller is designed in this paper for a static compensator (STATCOM) in the 12-bus benchmark power system. The controller provides an auxiliary reference signal for the STATCOM in such a way that it improves the damping of the rotor speed deviations of its neighboring generators. A Mamdani fuzzy rule base constitutes the core of the controller. A heuristic dynamic programming-based approach is used to further train the controller and enable it to provide nonlinear optimal control at different operating conditions of the power system. Simulation results are provided that indicate the proposed neuro-fuzzy external controller is …
Optimal Statcom Sizing And Placement Using Particle Swarm Optimization, J. C. Hernandez, Ganesh K. Venayagamoorthy, Yamille Del Valle, Ronald G. Harley
Optimal Statcom Sizing And Placement Using Particle Swarm Optimization, J. C. Hernandez, Ganesh K. Venayagamoorthy, Yamille Del Valle, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
Heuristic approaches are traditionally applied to find the size and location of Flexible AC Transmission Systems (FACTS) devices in a small power system. Nevertheless, more sophisticated methods are required for placing them in a large power network. Recently, the Particle Swarm Optimization (PSO) technique has been applied to solve power engineering optimization problems giving better results than classical methods. This paper shows the application of PSO for optimal sizing and allocation of a Static Compensator (STATCOM) in a power system. A 45 bus system (part of the Brazilian power network) is used as an example to illustrate the technique. Results …
Optimal Allocation Of A Statcom In A 45 Bus Section Of The Brazilian Power System Using Particle Swarm Optimization, J. C. Hernandez, Ganesh K. Venayagamoorthy, Yamille Del Valle, Ronald G. Harley
Optimal Allocation Of A Statcom In A 45 Bus Section Of The Brazilian Power System Using Particle Swarm Optimization, J. C. Hernandez, Ganesh K. Venayagamoorthy, Yamille Del Valle, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
This paper introduces the application of Particle Swarm Optimization (PSO) to solve the optimal allocation of a STATCOM in a 45 bus system which is part of the Brazilian power network. The criterion used in finding the optimal location is based on the voltage profile of the system, i.e. the voltage deviation at each bus, with respect to its optimum value, is minimized. In order to test the performance of the PSO algorithm in this particular application, different approaches for inertia weight are investigated; also different values of acceleration constants, number of iterations and maximum velocity are considered. A sensitivity …
Time-Delay Neural Network Based Predictions Of Elephant Distribution In A South African Game Reserve, Parviz Palangpour, Ganesh K. Venayagamoorthy, Kevin Duffy
Time-Delay Neural Network Based Predictions Of Elephant Distribution In A South African Game Reserve, Parviz Palangpour, Ganesh K. Venayagamoorthy, Kevin Duffy
Electrical and Computer Engineering Faculty Research & Creative Works
A large portion of South Africa's elephant population can be found on small wildlife reserves. When confined to enclosed reserves the elephant densities are much higher than observed in the wild. The large nutritional demands and destructive foraging behavior of elephants threaten rare species of vegetation. If conservation management is to protect threatened species of vegetation, knowing how long elephants will stay in one area of the reserve as well as which area they will move to next is essential. The goal of this study is to train an artificial neural network to predict an elephant herd's next position in …
Multiple Statcom Allocation And Sizing Using Particle Swarm Optimization, Ganesh K. Venayagamoorthy, J. C. Hernandez, Yamille Del Valle, Ronald G. Harley
Multiple Statcom Allocation And Sizing Using Particle Swarm Optimization, Ganesh K. Venayagamoorthy, J. C. Hernandez, Yamille Del Valle, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
No abstract provided.