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Electrical and Computer Engineering Faculty Research & Creative Works

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Full-Text Articles in Engineering

Zero-Sum Two-Player Game Theoretic Formulation Of Affine Nonlinear Discrete-Time Systems Using Neural Networks, S. Mehraeen, T. Dierks, S. Jagannathan, M. L. Crow Jan 2010

Zero-Sum Two-Player Game Theoretic Formulation Of Affine Nonlinear Discrete-Time Systems Using Neural Networks, S. Mehraeen, T. Dierks, S. Jagannathan, M. L. Crow

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the nearly optimal solution for discrete-time (DT) affine nonlinear control systems in the presence of partially unknown internal system dynamics and disturbances is considered. the approach is based on successive approximate solution of the Hamilton-Jacobi-Isaacs (HJI) equation, which appears in optimal control. Successive approximation approach for updating control input and disturbance for DT nonlinear affine systems are proposed. Moreover, sufficient conditions for the convergence of the approximate HJI solution to the saddle-point are derived, and an iterative approach to approximate the HJI equation using a neural network (NN) is presented. Then, the requirement of full knowledge of …

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Time-Domain Field Responses Of The Thin, High-Contrast, Finely Layered Structure In Ic Packagings, Adrianus T. De Hoop, Lijun Jiang Jan 2010

Time-Domain Field Responses Of The Thin, High-Contrast, Finely Layered Structure In Ic Packagings, Adrianus T. De Hoop, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

The thin, high-contrast, fine layers with dielectric and conductive properties, such as ground planes, are feature structures in IC packagings. Their responses to the pulsed electromagnetic field is important both theoretically and practically. In this paper, a new semi-analytical method is proposed to model the interaction of the layer with an incident electromagnetic field via a boundary condition that expresses the in-plane conduction and contrast electric polarization currents in terms of the exciting incident field by relating the jump in the tangential component of the magnetic field strength across the layer in terms of the (continuous) tangential component of the …

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A Novel Emulator For Discrete-Time Mimo Triply Selective Fading Channels, Fei Ren, Yahong Rosa Zheng Jan 2010

A Novel Emulator For Discrete-Time Mimo Triply Selective Fading Channels, Fei Ren, Yahong Rosa Zheng

Electrical and Computer Engineering Faculty Research & Creative Works

Hardware implementation of discrete-time triply selective Rayleigh fading channel emulators is proposed for multiple-input multiple-output (MIMO) communications. the proposed work differs from existing ones in that it incorporates temporal correlation, intertap correlation, and spatial correlation matrices into multiple uncorrelated frequency-flat fading waveforms to obtain a triply selective fading channel. the flat fading waveforms with temporal correlation or Doppler spectrum are generated using a sum-of-sinusoid method. the intertap correlation matrix associated with multipath delay spread is computed according to the channel power delay profile and transmit/receive filters. the spatial correlation matrices are predefined inputs associated with transmit and receive antenna arrangements. …

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A Variable Step-Size Normalized Sign Algorithm For Acoustic Echo Cancelation, Tiange Shao, Yahong Rosa Zheng, Jacob Benesty Jan 2010

A Variable Step-Size Normalized Sign Algorithm For Acoustic Echo Cancelation, Tiange Shao, Yahong Rosa Zheng, Jacob Benesty

Electrical and Computer Engineering Faculty Research & Creative Works

A variable step size normalized sign algorithm (VSS-NSA) is proposed, for acoustic echo cancelation, which adjusts its step size automatically by matching the L1 norm of the a posteriori error to that of the background noise plus near-end signal. Simulation results show that the new algorithm combined with double-talk detection outperforms the dual sign algorithm (DSA) and the normalized triple-state sign algorithm (NTSSA) in terms of convergence rate and stability. ©2010 IEEE.

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Mahalanobis Taguchi System (Mts) As A Prognostics Tool For Rolling Element Bearing Failures, Ahmet Soylemezoglu, Sarangapani Jagannathan, Can Saygin Jan 2010

Mahalanobis Taguchi System (Mts) As A Prognostics Tool For Rolling Element Bearing Failures, Ahmet Soylemezoglu, Sarangapani Jagannathan, Can Saygin

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel Mahalanobis-Taguchi system (MTS)-Based fault detection, isolation, and prognostics scheme is presented. the proposed data-driven scheme utilizes the Mahalanobis distance (MD)-Based fault clustering and the progression of MD values over time. MD thresholds derived from the clustering analysis are used for fault detection and isolation. When a fault is detected, the prognostics scheme, which monitors the progression of the MD values, is initiated. Then, using a linear approximation, time to failure is estimated. the performance of the scheme has been validated via experiments performed on rolling element bearings inside the spindle headstock of a microcomputer numerical …

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Optimal Control Of Affine Nonlinear Continuous-Time Systems Using An Online Hamilton-Jacobi-Isaacs Formulation, T. Dierks, Sarangapani Jagannathan Jan 2010

Optimal Control Of Affine Nonlinear Continuous-Time Systems Using An Online Hamilton-Jacobi-Isaacs Formulation, T. Dierks, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Solving the Hamilton-Jacobi-Isaacs (HJI) equation, commonly used in ℋ∞ optimal control, is often referred to as a two-player differential game where one player tries to minimize the cost function while the other tries to maximize it. in this paper, the HJI equation is formulated online and forward-in-time using a novel single online approximator (SOLA)-Based scheme to achieve optimal regulation and tracking control of affine nonlinear continuous-time systems. the SOLA-Based adaptive approach is designed to learn the infinite horizon HJI equation, the corresponding optimal control input, and the worst-case disturbance. a novel parameter tuning algorithm is derived which not only achieves …

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Hardware Implementation Of Triply Selective Rayleigh Fading Channel Simulators, Fei Ren, Yahong Rosa Zheng Jan 2010

Hardware Implementation Of Triply Selective Rayleigh Fading Channel Simulators, Fei Ren, Yahong Rosa Zheng

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we implement a real-time hardware triply selective Rayleigh fading simulator. This simulator incorporates the inter-tap and spatial correlation matrices into multiple uncorrelated frequency-flat Rayleigh fading waveforms (including temporal correlation) to simulate a multiple-input multiple-output (MIMO) triply selective Rayleigh fading channel. in the correlation incorporation procedure, this simulator uses a Kronecker product method to save a large amount of hardware memories. Occupying 34% hardware resources of one Stratix III FPGA chip, this simulator can simulate 4 x 4 MIMO fading channels with 10 correlated delay-taps per subchannel in real-time for a symbol rate of 3.69 μs. Accuracy of …

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Decentralized Nearly Optimal Control Of A Class Of Interconnected Nonlinear Discrete-Time Systems By Using Online Hamilton-Bellman-Jacobi Formulation, S. Mehraeen, Sarangapani Jagannathan Jan 2010

Decentralized Nearly Optimal Control Of A Class Of Interconnected Nonlinear Discrete-Time Systems By Using Online Hamilton-Bellman-Jacobi Formulation, S. Mehraeen, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the direct neural dynamic programming technique is utilized to solve the Hamilton Jacobi-Bellman (HJB) equation online and forward-in-time for the decentralized nearly optimal control of nonlinear interconnected discrete-time systems in affine form with unknown internal subsystem and interconnection dynamics. Only the state vector of the local subsystem is considered measurable. the decentralized optimal controller design for each subsystem consists of an action neural network (NN) that is aimed to provide a nearly optimal control signal, and a critic NN which approximates the cost function. the NN weights are tuned online for both the NNs. It is shown …

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Output Feedback Control Of A Quadrotor Uav Using Neural Networks, Travis Dierks, Sarangapani Jagannathan Jan 2010

Output Feedback Control Of A Quadrotor Uav Using Neural Networks, Travis Dierks, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. the assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control …

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Optimal Control Of Affine Nonlinear Continuous-Time Systems, T. Dierks, Sarangapani Jagannathan Jan 2010

Optimal Control Of Affine Nonlinear Continuous-Time Systems, T. Dierks, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the optimal regulation and tracking control of affine nonlinear continuous-time systems with known dynamics is undertaken using a novel single online approximator (SOL)-Based scheme. the SOLA-Based adaptive approach is designed to learn the infinite horizon continuous time Hamilton-Jacobi-Bellman (HJB) equation and its corresponding optimal control input. a novel parameter tuning algorithm is derived which not only ensures the optimal cost (HJB) function and control input are achieved, but also ensures the system states remain bounded during the online learning process. Lyapunov techniques show that all signals are uniformly ultimately bounded (UUB) and the approximated control signal approaches …

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An Adaptive Control Strategy For Dstatcom Applications In An Electric Ship Power System, Pinaki Mitra, Ganesh K. Venayagamoorthy Jan 2010

An Adaptive Control Strategy For Dstatcom Applications In An Electric Ship Power System, Pinaki Mitra, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

Distribution static compensator (DSTATCOM) is a shunt compensation device that is generally used to solve power quality problems in distribution systems. In an all-electric ship power system, power quality issues arise due to high-energy demand loads such as pulse loads. This paper presents the application of a DSTATCOM to improve the power quality in a ship power system during and after pulse loads. The control strategy of the DSTATCOM plays an important role in maintaining the voltage at the point of common coupling. A novel adaptive control strategy for the DSTATCOM based on artificial immune system (AIS) is presented in …

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Novel Dynamic Representation And Control Of Power Systems With Facts Devices, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow Jan 2010

Novel Dynamic Representation And Control Of Power Systems With Facts Devices, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow

Electrical and Computer Engineering Faculty Research & Creative Works

FACTS devices have been shown to be useful in damping power system oscillations. However, in large power systems, the FACTS control design is complex due to the combination of differential and algebraic equations required to model the power system. In this paper, a new method to generate a nonlinear dynamic representation of the power network is introduced to enable more sophisticated control design. Once the new representation is obtained, a back stepping methodology for the UPFC is utilized to mitigate the generator oscillations. Finally, the neural network approximation property is utilized to relax the need for knowledge of the power …

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Dynamic System Eigenvalue Extraction Using A Linear Echo State Network For Small-Signal Stability Analysis - A Novel Application, Jiaqi Liang, Jing Dai, Ganesh K. Venayagamoorthy, Ronald G. Harley Jan 2010

Dynamic System Eigenvalue Extraction Using A Linear Echo State Network For Small-Signal Stability Analysis - A Novel Application, Jiaqi Liang, Jing Dai, Ganesh K. Venayagamoorthy, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

A large nonlinear dynamic system usually has complex dynamic modes corresponding to the system's eigenvalues. These eigenvalues govern the system's local behavior and thus are critical information for designing system operation and control strategies. Without the availability of the system's analytical model, which is often the case for large nonlinear systems, the system's eigenvalues need to be estimated. a linear echo state network (ESN) based method for extracting observable eigenvalues of a dynamic system together with the participation factors of these eigenvalues in the accessible system states is presented in this paper. a linear ESN is first trained to track …

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On The Power Allocation For Relay Networks With Finite-Alphabet Constraints, Weiliang Zeng, Mingxi Wang, Chengshan Xiao, Jianhua Lu Jan 2010

On The Power Allocation For Relay Networks With Finite-Alphabet Constraints, Weiliang Zeng, Mingxi Wang, Chengshan Xiao, Jianhua Lu

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we investigate the optimal power allocation scheme for relay networks with finite-alphabet constraints. It has been shown that the previous work utilizing various design criteria with the Gaussian inputs assumption may lead to significant loss for a practical system with finite constellation set constraint, especially when signal-to-noise ratio (SNR) is in medium-to-high regions, or when the channel coding rate is medium to high. an optimal power allocation scheme is proposed to maximize the mutual information for the relay networks under discrete-constellation input constraint. Numerical examples show that significant gain can be obtained compared to the conventional counterpart …

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A Higher-Order Spectro-Temporal Integration Model For Predicting Signal Audibility, Qing Yang, John G. Harris Jan 2010

A Higher-Order Spectro-Temporal Integration Model For Predicting Signal Audibility, Qing Yang, John G. Harris

Electrical and Computer Engineering Faculty Research & Creative Works

A higher-order model to determine audibility of audio signals is presented. Previous models have been energy based (second order) and adequate only for stationary, narrow-band signals. Music, speech and other audio signals are nonstationary and wideband so traditional energy models poorly predict the audibility of these sounds. The predictions from the higher-order model are compared to actual subjective listening tests to show that the higher order, wide-band technique outperforms previous models. ©2010 IEEE.

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Design And Characterization Of An Integrate-And-Fire Neural Recording System, Sheng Feng Yen, John G. Harris Jan 2010

Design And Characterization Of An Integrate-And-Fire Neural Recording System, Sheng Feng Yen, John G. Harris

Electrical and Computer Engineering Faculty Research & Creative Works

A neuronal recording system for brain-machine interfaces (BMI) based on asynchronous biphasic pulse coding is described. A recording experiment comparing, in parallel, a commercial recording system (Tucker-Davis Technology) and the UF's custom solution (FWIRE) is set up to compare performance. The novel aspect of the UF system is that the analog signal is represented by an asynchronous pulse train, which provides a low-power, low-bandwidth, noise-resistant means for coding and transmission. Based on different front-end hardware settings, recording bandwidth and corresponding reconstruction accuracy can be varied. Taking advantage of neural firing features, the pulse-based approach requires less than 3K pulses/second to …

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Structural Identification Using A Low-Cost Search Method, James W. Fonda, Steve Eugene Watkins Dec 2009

Structural Identification Using A Low-Cost Search Method, James W. Fonda, Steve Eugene Watkins

Electrical and Computer Engineering Faculty Research & Creative Works

An easily implementable and trainable damage detection method is proposed and implemented for a simple truss structure. The approach uses the iterative search identification method and is compatible with low-cost and low-power microcontroller hardware. This method employs pattern matching for a data set from a strain sensor array and predicts location (truss member) and severity (member cross sectional area) of damage. As a health monitoring approach, the method is not as robust or rigorous as more complex methods. However, it has modest processing requirements and can handle noisy signals. The work presents an algorithm applied to a truss structure, the …

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One Million Plug-In Electric Vehicles On The Road By 2015, Ahmed Yousuf Saber, Ganesh K. Venayagamoorthy Dec 2009

One Million Plug-In Electric Vehicles On The Road By 2015, Ahmed Yousuf Saber, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

It is mentioned that one million plug-in hybrid and electric vehicles will be on the road by 2015 in United States to reduce emission. If one million electric vehicles (EVs) are connected to the existing electric grid randomly, peak load will be very high. Electrified transportation based on a traditional thermal power system will be costly economically and environmentally though it has a great value for electric power and transportation sectors. EVs cannot alone solve the emission problem completely since they need electric power, which is one of the main sources of emission. Therefore, significant emission reduction greatly depends on …

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Real-Time Modeling Of Distributed Plug-In Vehicles For V2g Transactions, Ganesh K. Venayagamoorthy, Pinaki Mitra, Keith Corzine, Chris Huston Dec 2009

Real-Time Modeling Of Distributed Plug-In Vehicles For V2g Transactions, Ganesh K. Venayagamoorthy, Pinaki Mitra, Keith Corzine, Chris Huston

Electrical and Computer Engineering Faculty Research & Creative Works

A real-time model of a fleet of plug-in vehicles performing vehicle-to-grid (V2G) power transactions is presented in this paper. Two sets of four vehicles are connected to both the grid and to each other through a short transmission line. the real-time modeling is carried out on a Real-Time Digital Simulator (RTDS). This setup allows for two different case studies with either two distributed sets of four individual vehicles or two smart parking lots with several vehicles. Output power levels and charge/discharge times are scheduled intelligently in order to maximize profits from grid transactions based on one-day ahead electricity pricing. the …

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Ieee Conference On Intelligent Transportation Systems, Proceedings, Itsc: Welcome Message From Conference General Chair, Steve Eugene Watkins Dec 2009

Ieee Conference On Intelligent Transportation Systems, Proceedings, Itsc: Welcome Message From Conference General Chair, Steve Eugene Watkins

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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Potentials And Promises Of Computational Intelligence For Smart Grids, Ganesh K. Venayagamoorthy Dec 2009

Potentials And Promises Of Computational Intelligence For Smart Grids, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

The electric power grid is a complex adaptive system under semi-autonomous distributed control. It is spatially and temporally complex, non-convex, nonlinear and non-stationary with a lot of uncertainties. the integration of renewable energy such as wind farms, and plug-in hybrid and electric vehicles further adds complexity and challenges to the various controllers at all levels of the power grid. a lot of efforts have gone into the development of a smart grid to align the interests of the electric utilities, consumers and environmentalists. Advanced computational methods are required for planning and optimization, fast control of power system elements, processing of …

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Missing-Sensor-Fault-Tolerant Control For Sssc Facts Device With Real-Time Implementation, Wei Qiao, Ganesh K. Venayagamoorthy, Ronald Harley Dec 2009

Missing-Sensor-Fault-Tolerant Control For Sssc Facts Device With Real-Time Implementation, Wei Qiao, Ganesh K. Venayagamoorthy, Ronald Harley

Electrical and Computer Engineering Faculty Research & Creative Works

Control of power systems relies on the availability and quality of sensor measurements. However, measurements are inevitably subjected to faults caused by sensor failure, broken or bad connections, bad communication, or malfunction of some hardware or software. These faults in turn may cause the failure of power system controllers and consequently severe contingencies in the power system. to avoid such contingencies, this paper presents a sensor evaluation and (missing sensor) restoration scheme (SERS) by using auto-associative neural networks (auto-encoders) and particle swarm optimization (PSO). based on the SERS, a missing-sensor-fault-tolerant control (MSFTC) is developed for controlling a static synchronous series …

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Channeling University-Based Sponsored Research Into Classroom Education, Badrul H. Chowdhury Dec 2009

Channeling University-Based Sponsored Research Into Classroom Education, Badrul H. Chowdhury

Electrical and Computer Engineering Faculty Research & Creative Works

An important mission of university-Based research that often gets overlooked is the education component. based on the 2005-2006 Electric Power Engineering Education Resources report produced by PES, tens of millions of dollars' worth of research is being conducted annually by university faculty throughout North America. While such sponsored research almost always produces master's and Ph.D. dissertations, how much of that is channeled into creating a broader impact of educating undergraduate and graduate students is of concern to many sponsoring agencies. This paper presents a summary of panel presentations that describe and discuss examples of how some faculty members have brought …

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Labrat™: Miniature Robot For Students, Researchers, And Hobbyists, Paul Robinette, Ryan Meuth, Ryanne Dolan, Donald C. Wunsch Dec 2009

Labrat™: Miniature Robot For Students, Researchers, And Hobbyists, Paul Robinette, Ryan Meuth, Ryanne Dolan, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

LabRat™ is an autonomous, self-contained mobile robot kit with batteries, motors, two bumper whisker sensors, and three infrared proximity sensors that double as channels for "Rat-to-Rat" communication. the vehicle determines its position with an optical sensor that detects movement in both lateral directions. the LabRat™ design is completely open source, including software examples and libraries. LabRat™ is designed to fit inside the body of a computer mouse and has applications in the classroom, the lab and the home. the device has been successfully used in an undergraduate robotics class. © 2009 IEEE.

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Comparative Study Of Population Based Techniques For Power System Stabilizer Design, Pinaki Mitra, Chuan Yan, Lisa Grant, Ganesh K. Venayagamoorthy, Komla Folly Dec 2009

Comparative Study Of Population Based Techniques For Power System Stabilizer Design, Pinaki Mitra, Chuan Yan, Lisa Grant, Ganesh K. Venayagamoorthy, Komla Folly

Electrical and Computer Engineering Faculty Research & Creative Works

Power System Stabilizers (PSSs) are used in interconnected power systems in order to mitigate low frequency oscillations. the comparison of the performances of four advanced population-based techniques in tuning the parameters of PSS in a three-machine-nine-bus test system is presented in this paper. the algorithms considered in this paper are A) Differential Evolution based Particle Swarm Optimization (DEPSO), b) Modified Clonal Selection Algorithm (MCSA), c) Small Population based Particle Swarm Optimization (SPPSO) and d) Population based Incremental Learning (PBIL). the comparative study is focused on the frequency domain performances. It is observed that MCSA is performing better than the other …

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Short To Medium Range Time Series Prediction Of Solar Irradiance Using An Echo State Network, Stephen M. Ruffing, Ganesh K. Venayagamoorthy Dec 2009

Short To Medium Range Time Series Prediction Of Solar Irradiance Using An Echo State Network, Stephen M. Ruffing, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

An Echo State Network (ESN) can make multi-step predictions since it can process temporal information without the training difficulties encountered by conventional recurrent neural networks. an ESN is applied in this paper to make multistep predictions of solar irradiance, 30 minutes to 270 minutes into the future. the ESN is trained and tested using two performance metrics (correlation coefficient and mean squared error) on meteorological and solar data recorded at the National Renewable Energy Laboratory Solar Radiation Research Laboratory in Golden, Colorado. When feedback of target outputs is utilized, an improvement is seen for the first performance metric, while no …

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Comparison Of Enhanced-Pso And Classical Optimization Methods: A Case Study For Statcom Placement, Yamille Del Valle, Ronald G. Harley, Ganesh K. Venayagamoorthy Dec 2009

Comparison Of Enhanced-Pso And Classical Optimization Methods: A Case Study For Statcom Placement, Yamille Del Valle, Ronald G. Harley, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

This paper validates the effectiveness of an enhanced particle swarm optimizer (Enhanced-PSO) method in solving the problem of optimal allocation of FACTS devices in a power system. the performance of the Enhanced-PSO method is compared with classical optimization approaches using a simple but realistic case study of optimal allocation of STATCOM devices, considering steady state and economic criteria. This paper also discusses the concepts and details about the optimization process that tend to be overlooked in the literature since the selection of an optimization algorithm highly depends on them. © 2009 IEEE.

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Heuristic Algorithms For Solving Convex And Nonconvex Economic Dispatch, Yusuf Yare, Ganesh K. Venayagamoorthy, Ahmed Yousuf Saber Dec 2009

Heuristic Algorithms For Solving Convex And Nonconvex Economic Dispatch, Yusuf Yare, Ganesh K. Venayagamoorthy, Ahmed Yousuf Saber

Electrical and Computer Engineering Faculty Research & Creative Works

Economic dispatch (ED) is a power system optimization problem, and its objective is to reduce the total generation cost of units while satisfying constraints. the presence of nonlinearities in practical generator operation makes solving the ED problem more challenging. These generator nonlinearities are modeled as constraints to be met in the form of ramp-rate limits and prohibited operating zones. This paper proposes three heuristic algorithms, namely, the genetic algorithm (GA), differential evolution (DE) and modified particle swarm optimization (MPSO) to solve this ED problem for two test systems. Simulation, numerical results and convergence performances of these three algorithms are presented …

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Cellular Multilayer Perceptron For Prediction Of Voltages In A Power System, Lisa L. Grant, Ganesh K. Venayagamoorthy Dec 2009

Cellular Multilayer Perceptron For Prediction Of Voltages In A Power System, Lisa L. Grant, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

With the increase in renewable energy sources connected to the power grid, better identification tools are needed for power system voltage profile prediction. Current deregulation trends have led to voltages operating close to stability limits which increases the need for quick estimation tools for system security and contingency analysis. This paper presents a Cellular Multilayer Perceptron (CMLP) architecture for fast identification and prediction of bus voltages. the CMLP method is compared with a standard MLP neural network for bus voltage prediction on the 12-bus three-area test power system. CMLPs can represent a direct mapping of any power system simplifying the …

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An Introduction To The Echo State Network And Its Applications In Power System, Jing Dai, Ganesh K. Venayagamoorthy, Ronald G. Harley Dec 2009

An Introduction To The Echo State Network And Its Applications In Power System, Jing Dai, Ganesh K. Venayagamoorthy, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

Echo State Network (ESN) is a new type of Recurrent Neural Network (RNN) proposed in recent years. the training process of ESN is easier and requires less computational effort than regular RNN which has the same size. Due to its high modeling capability of complex dynamic system, ESN has been used in various power system applications such as power system nonlinear load modeling and true harmonic current detection, wide area monitoring, intelligent control of an Active Power Filter (APF), overhead conductor thermal dynamics identification, wind speed or water inflow forecasting, etc. This paper introduces the basic concept and the offline …

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