Loading...
Search for: modal-estimation
0.019 seconds

    Estimation of Power System Electromechanical Dynamics by Processing Ambient Data Measured by PMUs

    , M.Sc. Thesis Sharif University of Technology Maddipour Farrokhifard, Mohammadreza (Author) ; Parniani, Mostafa (Supervisor)
    Abstract
    In recent years, the architecture of power systems has evolved in such a way to ease the use of Wide Area Measurement Systems (WAMS) to monitor real time situation of the grid. One of the most prevalent approaches for monitoring power systems is using data gained from Phasor Measurement Units (PMUs) and implementing advanced signal processing algorithms. By this way, tracking the electromechanical oscillatory modes of systems and stability evaluation become attainable. Unlike the model-based methods of estimating electromechanical modes, in which non-linear differential equations are linearized around the operation point, measurement-based methods lead to more accurate and continuously... 

    Novel approaches for online modal estimation of power systems using PMUs data contaminated with outliers

    , Article Electric Power Systems Research ; Volume 124 , July , 2015 , Pages 74-84 ; 03787796 (ISSN) Farrokhifard, M ; Hatami, M ; Parniani, M ; Sharif University of Technology
    Elsevier Ltd  2015
    Abstract
    One of the most important issues in modal estimation of power systems using PMUs data is the negative effect of outliers. Hence, in addition to the techniques of analyzing PMUs data, the necessity of implementing some kinds of approach to overcome these outliers is tangible. This paper aims to present different approaches to overcome outliers and also estimate the electromechanical modes of the system accurately when there is suspicion that the PMUs data may be contaminated by discordant measurements. Proposed approaches are generally categorized into two main classifications: the first category detects and modifies outliers in the pre-processing stage adaptively and then prepares the... 

    Different approaches for estimation of dampings and frequencies of electromechanical modes from PMU ambient data

    , Article 2015 IEEE 15th International Conference on Environment and Electrical Engineering, EEEIC 2015 - Conference Proceedings, 10 June 2015 through 13 June 2015 ; June , 2015 , Pages 1748-1753 ; 9781479979936 (ISBN) Farrokhifard, M ; Hatami, M ; Parniani, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2015
    Abstract
    Small signal stability of power systems is one of the most crucially important issues, since the electrical demand is increasing at a galloping rate and power systems are expanding day by day. In this regard, estimation of dampings and frequencies of electromechanical modes through the analysis of field measurements has become a heated study topic for electrical power system researchers in recent years. There have been several methods to analyze different types of Phasor Measurement Units (PMUs) signals i.e., transient, ambient, and probing. Among the proposed techniques, those which are capable of analyzing ambient data seems to be more practical, since this type of data can be achieved... 

    A non-stationary analysis of low-frequency electromechanical oscillations based on a refined margenau-hill distribution

    , Article IEEE Transactions on Power Systems ; Volume 31, Issue 2 , 2016 , Pages 1567-1578 ; 08858950 (ISSN) Hatami, M ; Farrokhifard, M ; Parniani, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc 
    Abstract
    This paper focuses on the use of quadratic time-frequency distributions (QTFDs) to characterize the temporal variation of low-frequency electromechanical oscillations (LFEOs) using ringdown data. A refined Margenau-Hill distribution (MHD) and a procedure to extract the instantaneous frequencies and damping factors as well as initial phase angles of system low-frequency modes when the analyzed signal is multi-component are proposed. The refinement process enjoys a fast-converging iterative algorithm and without loss of generality it can be applied to other QTFDs for using in other applications. A non-stationary synthetic signal as well as simulated ringdown data of a 5-area, 16-machine power... 

    Ambient data-based online electromechanical mode estimation by error-feedback lattice RLS filter

    , Article IEEE Transactions on Power Systems ; 2017 ; 08858950 (ISSN) Setareh, M ; Parniani, M ; Aminifar, F ; Sharif University of Technology
    Abstract
    This paper proposes a novel error-feedback lattice recursive least-squares (EF-LRLS) filter for online estimation of power system oscillatory modes. The EF-LRLS filter is applied to ambient data provided by phasor measurement units to identify the autoregressive (AR) model parameters. This filter has a modular structure; accordingly, if the length of the filter equals N, it identifies AR(1) to AR(N) models concurrently. In the proposed method, removing very low and high frequencies and re-sampling steps are fulfilled in an online fashion. This adaptive filter has less computational complexity than standard RLS filter, making it an appropriate choice for online system identification. The... 

    Ambient data-based online electromechanical mode estimation by error-feedback lattice RLS filter

    , Article IEEE Transactions on Power Systems ; Volume 33, Issue 4 , July , 2018 , Pages 3745-3756 ; 08858950 (ISSN) Setareh, M ; Parniani, M ; Aminifar, F ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2018
    Abstract
    This paper proposes a novel error-feedback lattice recursive least-squares (EF-LRLS) filter for online estimation of power system oscillatory modes. The EF-LRLS filter is applied to ambient data provided by phasor measurement units to identify the autoregressive (AR) model parameters. This filter has a modular structure; accordingly, if the length of the filter equals $N$, it identifies AR(1) to ${m{AR(}}N)$ models concurrently. In the proposed method, removing very low and high frequencies and resampling steps are fulfilled in an online fashion. This adaptive filter has less computational complexity than standard RLS filter, making it an appropriate choice for online system identification....