This paper is a tutorial on linear, state space, model-based methods for certain nonlinear estimation problems commonly encountered in signal and data analysis. A prototypical problem that is studied is that of estimating the frequencies of multiple, superimposed sinusoids from a short record of noise-corrupted data. The approach expounded however, is applicable to a vast range of nonlinear signal analysis problems and applications in direction finding and damped sinusoid retrieval are dealt with in some detail. The benefits that result from using a state space description of the signal are highlighted in this paper. It is shown that state space models provide an elegant tool for exposing the structure present in the problem. The approach also allows for robust parameterization of the model with respect to finite precision errors. The robustness of the parameter set is complemented by the availability of numerically robust tools to estimate the parameters. The resulting algorithms are compatible with multiprocessor implementations. >

Model based processing of signals : a state space approach. Prolog

This paper presents a brief review of techniques available for reducing large systems to smaller equivalents This paper is divided into high frequency equivalents, low frequency equivalents, and wideband equivalents Numerical examples are presented to demonstrate selected methods of high frequency equivalencing

Dynamic System Equivalents: A Survey of Available Techniques

A wide-area control system (WACS) uses wide-area measurement signals to provide auxiliary stabilising controls to power system devices. An adaptive WACS has been designed to provide damping control signals to the excitations of generators. The delays in signal transmission and the reliability of the communication network is a major concern with wide-area measurement- based control. The adaptive WACS is designed to compensate for a wide range of communication delays and provide robust damping to mitigate system oscillations. A single simultaneous recurrent neural network is used in the realisation of the adaptive WACS for both identification and control of the power system. The WACS has been implemented on a digital signal processor and its performance is evaluated on a power system implemented on a real-time platform - the real-time digital simulator. The additional damping provided by the WACS is enumerated using Prony analysis.

Real-time implementation of a measurement-based adaptive wide-area control system considering communication delays

High voltage direct current (HVDC) links are interties, characterized by good controllability, large adjustable capacity and fast responses, and have inherent advantage in damping interarea oscillations over power system stabilizers (PSS) and flexible alternating current transmission systems (FACTS). In this paper, a systematic and practical means to design the multiple HVDC damping control system, which aims to enhance the damping of certain interarea modes and minimize the interactions between different control loops, is provided. In the proposed procedure, the wide-area feedback signals that have the good observability of target modes are preselected by an index based on residue analysis firstly. Then the interactions between the candidate control loops, in which the setting power reference of the HVDC as the input and the preselected wide-area signals as the output, are investigated by relative gain array (RGA) analysis. According to the RGA results, a suitable input-output pairing for multiple HVDC damping controller is determined. The transfer function residues used in the feedback signal preselection and the RGA calculation are identified by Prony analysis in the transient stability program and electromagnetic transient program respectively. Finally, the damping controller parameters are optimized by time-domain simulations. The application in China Southern Power Grid (CSG) is illustrated as the case study.

Design of WAMS-Based Multiple HVDC Damping Control System

The design and implementation of an optimal neurocontroller for a flexible ac transmission device - the unified power-flow controller (UPFC) - is presented in this paper. Wide area signals in a power system are used to provide auxiliary control to a UPFC in order to achieve enhanced damping of system oscillations. The neurocontroller provides auxiliary signals to the real and reactive power references of a UPFC series inverter. The design of the optimal neurocontroller is based on an adaptive critic design approach - the heuristic dynamic programming. A system identifier, referred to as the wide-area monitor), and a critic network (performance evaluator) are designed for optimizing the neurocontroller. Real-time implementation of the optimal UPFC neurocontroller for a multimachine power system is carried out successfully on a digital signal processor. The power system is simulated on a real-time digital simulator. The performance of this neurocontroller is compared with a conventional linear damping controller. Results show enhanced damping of both inter-area and intra-area modes in the power system under different operating conditions and disturbances with the neurocontroller. The improvement in the damping is also quantified using the Prony method.

Wide-Area Signal-Based OptimalNeurocontroller for a UPFC

This paper presents a method of obtaining transmission network equivalents from the network's response to a pulse excitation signal. The proposed method is based on modal decomposition representation for the large-scale interconnected system. In this framework we use Prony analysis to identify the network function of the system and to decompose the large system into a parallel combination of simple first-order systems. As a result the network function of the transmission network can be identified easily, and a Thevenin-type of discrete-time filter model can be generated. It can reproduce the driving-point impedance characteristic of the network. Furthermore, the proposed model can be implemented into the EMTP in a direct manner. The simulation results with the full system representation and the developed equivalent system showed a good agreement.

A time-domain approach to transmission network equivalents via Prony analysis for electromagnetic transients analysis

Abstrud: This paper presents a method of obtaining transmission network equivalents from the network's response to a pulse excitation signal. The proposed method is based on modal decomposition representation for a large-scale interconnected system. I n this framework we use Prony analysis to identify the network function of the system and to decompose the large system into a parallel combination of simple firstorder systems. As a result, the network function of the transmission network can be identified easily, and a Nortontype discrete-time filter model can be generated. I t can reproduce the driving-point admittance characteristic of the network. The proposed model can be implemented into the time-domnin simulator like EMTP in a direct manner. The simulation results with the full system representation and the developed equivalent system showed a good agreement.

http://ieeexplore.ieee.org/iel3/3558/10652/00492979.pdf

Transmission network equivalents in time-domain for electromagnetic transients analysis

High Precision Distance Relaying Algorithm for Transmission Line Protection by Optimal Integral Approximation Technique

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Jun-Hee Hong

Author Tools

Chat about Author

Papers

A time-domain approach to transmission network equivalents via Prony analysis for electromagnetic transients analysis

Transmission network equivalents in time-domain for electromagnetic transients analysis

High Precision Distance Relaying Algorithm for Transmission Line Protection by Optimal Integral Approximation Technique