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An Estimation Of Distribution Improved Particle Swarm Optimization Algorithm, Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy
An Estimation Of Distribution Improved Particle Swarm Optimization Algorithm, Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
PSO is a powerful evolutionary algorithm used for finding global solution to a multidimensional problem. Particles in PSO tend to re-explore already visited bad solution regions of search space because they do not learn as a whole. This is avoided by restricting particles into promising regions through probabilistic modeling of the archive of best solutions. This paper presents hybrids of estimation of distribution algorithm and two PSO variants. These algorithms are tested on benchmark functions having high dimensionalities. Results indicate that the methods strengthen the global optimization abilities of PSO and therefore, serve as attractive choices to determine solutions to …
Dhp-Based Wide-Area Coordinating Control Of A Power System With A Large Wind Farm And Multiple Facts Devices, Wei Qiao, Ganesh K. Venayagamoorthy, Ronald G. Harley
Dhp-Based Wide-Area Coordinating Control Of A Power System With A Large Wind Farm And Multiple Facts Devices, Wei Qiao, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
Wide-area coordinating control is becoming an important issue and a challenging problem in the power industry. This paper proposes a novel optimal wide-area monitor and wide-area coordinating neurocontroller (WACNC), based on wide-area measurements, for a power system with power system stabilizers, a large wind farm, and multiple flexible ac transmission system (FACTS) devices. The wide-area monitor is a radial basis function neural network (RBFNN) that identifies the input-output dynamics of the nonlinear power system. Its parameters are optimized through a particle swarm optimization (PSO) based method. The WACNC is designed by using the dual heuristic programming (DHP) method and RBFNNs. …
Optimal Scheduling Of Generator Maintenance Using Modified Discrete Particle Swarm Optimization, Yusuf Yare, Ganesh K. Venayagamoorthy
Optimal Scheduling Of Generator Maintenance Using Modified Discrete Particle Swarm Optimization, Yusuf Yare, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a modified discrete particle swarm optimization (PSO) based technique for generating optimal preventive maintenance schedule of generating units for economical and reliable operation of a power system while satisfying system load demand and crew constraints. While GA and other analytical methods might suffer from premature convergence and the curse of dimensionality, heuristics based swarm intelligence can be an efficient alternative. PSO is known to effectively solve large scale multi-objective optimization problems. Here, a modified discrete PSO approach is proposed for the GMS optimization problem in order to overcome the limitations of the conventional methods and come up …
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 …
Combined Training Of Recurrent Neural Networks With Particle Swarm Optimization And Backpropagation Algorithms For Impedance Identification, Peng Xiao, Ganesh K. Venayagamoorthy, Keith Corzine
Combined Training Of Recurrent Neural Networks With Particle Swarm Optimization And Backpropagation Algorithms For Impedance Identification, Peng Xiao, Ganesh K. Venayagamoorthy, Keith Corzine
Electrical and Computer Engineering Faculty Research & Creative Works
A recurrent neural network (RNN) trained with a combination of particle swarm optimization (PSO) and backpropagation (BP) algorithms is proposed in this paper. The network is used as a dynamic system modeling tool to identify the frequency-dependent impedances of power electronic systems such as rectifiers, inverters, and DC-DC converters. As a category of supervised learning methods, the various backpropagation training algorithms developed for recurrent neural networks use gradient descent information to guide their search for optimal weights solutions that minimize the output errors. While they prove to be very robust and effective in training many types of network structures, they …
A Fuzzy-Pso Based Controller For A Grid Independent Photovoltaic System, Richard L. Welch, Ganesh K. Venayagamoorthy
A Fuzzy-Pso Based Controller For A Grid Independent Photovoltaic System, Richard L. Welch, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a particle swarm optimization (PSO) method for optimizing a fuzzy logic controller (FLC) for a photovoltaic (PV) grid independent system consisting of a PV collector array, a storage battery, and loads (critical and non-critical loads). PSO is used to optimize both the membership functions and the rule set in the design of the FLC. Optimizing the PV system controller yields improved performance, allowing the system to meet more of the loads and keep a higher average state of battery charge. Potential benefits of an optimized controller include lower costs through smaller system sizing and a longer battery …