Feature Extraction-Based Real-Time Transient Stability Analysis

C S Saunders,Y Liu,I Pisica,M M Alamuti,G A Taylor,J Liu

doi:10.1007/s40866-019-0069-x

Abstract

With increasing amounts of asynchronous generation being deployed to meet system energy demands, many transmission corridors may become constrained by angular stability criteria rather than steady-state thermal limitations. In such a system, it is paramount to have the capability to rapidly evaluate the stability margins of the system, particularly in a threatened post-fault state. The use of single machine equivalents (SIME) has been shown to be a powerful and flexible hybrid stability analysis method which can be computed directly from measured PMU data. However, due to the nature of the system reduction employed by SIME, as well as the method of extrapolation to estimate stability margins, there are many cases where the swing of the system is not accurately modelled by the traditional methods until a significant amount of data has been collected, at which point it may be too late to respond to the threat. In this paper, we address some of the limitations imposed by the traditional methods of reduction and prediction. We propose a method where rather than identifying a single critical SIME model for stability prediction, a spectrum of SIME representations of the post-fault system is developed, yielding a more timely and accurate estimate of post-fault stability conditions, through observation and feature extraction.

Highlights

Climate change and greenhouse gas emissions have become recognized as problems of international significance in recent years
The deployment of Phasor Measurement Units (PMUs) on large scale in power systems creates the basis for near-real-time and accurate system state observations
The aim of single machine equivalents (SIME) is to generate a simplified model of a power system in the post-fault state, employing a hybrid stability analysis approach where measured or simulated data of the swing of the generators serves as a set of inputs for generating the model

Summary

Introduction

Climate change and greenhouse gas emissions have become recognized as problems of international significance in recent years. The aim of SIME is to generate a simplified model of a power system in the post-fault state, employing a hybrid stability analysis approach where measured or simulated data of the swing of the generators serves as a set of inputs for generating the model This technique creates a simplified power system model that is useful for extrapolation and prediction of system behaviour, and that can be updated with real-time data. Rather than observing the Pa – δ curve to calculate a stability margin estimate, the time-domain evolution of a SIME model’s kinetic energy trajectory forms the basis for the analysis and prediction of system stability. The approach taken in the proposed method involves the intentional simultaneous generation of a set of SIME models, Fig. 1 The concept of Multiple SIME representations

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Results

ESIME Method

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