Abstract
With the increased number of PMUs in the power grid, effective high speed, realtime methods to ascertain relevant data for situational awareness are needed. Several techniques have used data from PMUs in conjunction with state estimation to assess system stability and event detection. However, these techniques require system topology and a large computational time. This paper presents a novel approach that uses real-time PMU data streams without the need of system connectivity or additional state estimation. The new development is based on the approximation of the eigenvalues related to the decoupled discreet-time power flow Jacobian matrix using direct openPDC data in real-time. Results are compared with other methods, such as Prony’s method, which can be too slow to handle big data. The newly developed Discreet-Time Jacobian Eigenvalue Approximation (DDJEA) method not only proves its accuracy, but also shows its effectiveness with minimal computational time: an essential element when considering situational awareness.
Highlights
The traditional power flow Jacobian matrix, utilized in Newton-Raphson method, cannot be calculated given these constraints
This paper presented an approximate method to be used for the purpose of situational awareness and assessing weak areas of the system without using system topology
The proposed developed Discreet-Time Jacobian Eigenvalue Approximation (DDJEA) method used synchrophasor data to approximate the change in the system by observing the change in the diagonal terms of the DDJEA matrix, the approximation of the eigenvalues for the Jacobian matrix used in the Newton-Raphson power flow method
Summary
The traditional power flow Jacobian matrix, utilized in Newton-Raphson method, cannot be calculated given these constraints. If an eigenvalue of the Jacobian matrix, decoupled or full, approaches a singularity, meaning zero or infinity, that mathematically means that any change to voltage or bus angle will yield no change or an infinite change. Prony analysis has been used alongside Frequency Domain Decomposition and oscillatory monitoring system approaches as in [6] [7] This analytical method has been used to determine unstable conditions in slow tie-line power flows [6] and inter-area oscillations [8]. This paper proposes a novel method, DDJEA that attempts to approximate the eigenvalues of the decoupled Jacobian matrix at each bus by measuring the difference between two neighboring measurements of real and reactive power with bus angle and voltage respectively. By comparing the event detection and instability indicators of both methods, strengths of the proposed method standalone are discussed, as well as a combined methodology to enhance situational awareness and stability monitoring
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