Measurement based algorithms for estimating low-frequency electromechanical modes serve as useful practical methods to monitor the modal properties of power system oscillations in real-time. This paper proposes a recursive adaptive stochastic subspace identification (RASSI) algorithm for online monitoring of power system modes using wide-area synchrophasor data. The proposed method gives an online estimation of mode frequency and damping ratio as well as mode shapes using multi-channel measurement data. It exploits both the accuracy of subspace identification and fast computational capability of recursive methods. An adaptive method is proposed to enable fast tracking of modal evolution under poorly damped conditions together with low estimation variance under quasi-steady-state conditions. The algorithms are tested using simulated data from Kundur two-area test power system as well as measured data from real systems.

Electromechanical Mode Estimation Using Recursive Adaptive Stochastic Subspace Identification

Measurement based algorithms for estimating low-frequency electromechanical modes serve as useful practical methods to monitor the modal properties of power system oscillations in real-time. This paper proposes a Recursive Adaptive Stochastic Subspace Identification (RASSI) algorithm for online monitoring of power system modes using wide-area synchrophasor data. The proposed method gives an online estimation of mode frequency and damping ratio as well as mode shapes using multi-channel measurement data. It exploits both the accuracy of subspace identification and fast computational capability of recursive methods. An adaptive method is proposed to enable fast tracking of modal evolution under poorly damped conditions together with low estimation variance under quasi-steady-state conditions. The algorithms are tested using simulated data from Kundur two-area test power system as well as measured data from real systems.

Electromechanical mode estimation using recursive adaptive stochastic subspace identification

Fast computational methods are developed for finding the equivalent continuous-time state equations from discrete-time state equations. The computational methods utilize the direct truncation method, the matrix continued fraction method, and the geometric-series method in conjunction with the principal q th root of the discrete-time system matrix for quick determination of the approximants of a matrix logarithm function. It is shown that the use of the principal q th root of a matrix enables us to enlarge the convergence region of the expansion of a matrix logarithm function and to improve the accuracy of the approximants of the matrix logarithm function.

Determining continuous-time state equations from discrete-time state equations via the principal q th root method

A novel approach for estimating the inertia of an interconnected power system is presented using the identification of interarea oscillation modes (frequency, damping and mode shape) extracted from ambient data The proposed method concentrates on estimating the values of the effective inertia of each area rather than the equivalent inertia of the entire system Based on an equivalent two-machine system (ETmS) obtained by combining small signal stability analysis (SSSA) with the structure of the power grid, we derive a mathematical relationship between the effective inertia of each area and the interarea oscillation modes Furthermore, the interarea oscillation modes can be extracted from ambient data, and the developed scheme enables an online estimation of the inertia only by using the outputs measured by PMUs The performance of the proposed methodology is tested via numerical simulation cases and real data

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Ambient-Data-Driven Modal-Identification-Based Approach to Estimate the Inertia of an Interconnected Power System

This paper presents a geometric-series method for finding two-dimensional (2D) discrete-time (continuous-time) state-space models from 2D continuous-time (discretetime) systems. This method allows the use of well-developed theorems and algorithms in the 2D discrete-time (continuous-time) domain to indirectly carry out analysis and design of hybrid 2D composite systems.

H. Wang

Papers

Discrete-continuous model conversion