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Full-Text Articles in Engineering
Novel Dynamic Representation And Control Of Power Networks Embedded With Facts Devices, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow
Novel Dynamic Representation And Control Of Power Networks Embedded With Facts Devices, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow
Electrical and Computer Engineering Faculty Research & Creative Works
FACTS devices have been shown to be powerful in damping power system oscillations caused by faults; however, in the multi machine control using FACTS, the control problem involves solving differential-algebraic equations of a power network which renders the available control schemes ineffective due to heuristic design and lack of know how to incorporate FACTS into the network. A method to generate nonlinear dynamic representation of a power system consisting of differential equations alone with universal power flow controller (UPFC) is introduced since differential equations are typically preferred for controller development. Subsequently, backstepping methodology is utilized to reduce the generator oscillations …
Swarm Intelligence And Evolutionary Approaches For Reactive Power And Voltage Control, Ganesh K. Venayagamoorthy, G. Krost, G. A. Bakare, Lisa L. Grant
Swarm Intelligence And Evolutionary Approaches For Reactive Power And Voltage Control, Ganesh K. Venayagamoorthy, G. Krost, G. A. Bakare, Lisa L. Grant
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a comparison of swarm intelligence and evolutionary techniques based approaches for minimization of system losses and improvement of voltage profiles in a power network. Efficient distribution of reactive power in an electric network can be achieved by adjusting the excitation on generators, the on-load tap changer positions of transformers, and proper switching of discrete portions of inductors or capacitors. This is a mixed integer non-linear optimization problem where metaheuristics techniques have proven suitable for providing optimal solutions. Four algorithms explored in this paper include differential evolution (DE), particle swarm optimization (PSO), a hybrid combination of DE and …
Implementation Of Neuroidentifiers Trained By Pso On A Plc Platform For A Multimachine Power System, Curtis Alan Parrott, Ganesh K. Venayagamoorthy
Implementation Of Neuroidentifiers Trained By Pso On A Plc Platform For A Multimachine Power System, Curtis Alan Parrott, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
Power systems are nonlinear with fast changing dynamics. In order to design a nonlinear adaptive controller for damping power system oscillations, it becomes necessary to identify the dynamics of the system. This paper demonstrates the implementation of a neural network based system identifier, referred to as a neuroidentifier, on a programmable logic controller (PLC) platform. Two separate neuroidentifiers are trained using the particle swarm optimization (PSO) algorithm to identify the dynamics in a two-area four machine power system, one neuroidentifier for Area 1 and the other for Area 2. The power system is simulated in real time on the Real …
Dsp-Based Pso Implementation For Online Optimization Of Power System Stabilizers, Parviz Palangpour, Pinaki Mitra, Swakshar Ray, Ganesh K. Venayagamoorthy
Dsp-Based Pso Implementation For Online Optimization Of Power System Stabilizers, Parviz Palangpour, Pinaki Mitra, Swakshar Ray, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
Real-time implementations of controllers require optimization algorithms which can be performed quickly. In this paper, a digital signal processor (DSP) implementation of particle swarm optimization (PSO) is presented. PSO is used to optimize the parameters of two stabilizers used in a power system. The controllers and PSO are both implemented on a single DSP in a hardware-in-loop configuration. Results showing the performance and feasibility for real-time implementations of PSO are presented.