Synthesize Phasor Measurement Unit Data Using Large-Scale Electric Network Models

TL;DR

This paper presents a method to generate synthetic phasor measurement unit (PMU) data using large-scale electric network models, enabling data sharing and analysis without compromising actual grid confidentiality.

Contribution

It introduces a novel approach to synthesize PMU data by combining public utility data and detailed load dynamics modeling, facilitating research and education.

Findings

Synthetic PMU data closely mimics real data

Method enhances data accessibility for research

Supports improved grid operation analysis

Abstract

Big data analytic applications using phasor measurements help improve the situation awareness of grid operators to better operate and control the system. Phasor measurement unit (PMU) data from actual grids is viewed as highly confidential and is not publicly available to researchers and educators. This paper develops a methodology to synthesize PMU data that can be accessed and shared freely, with a focus on input data preparation. Time series of demand- and generation-side input data are generated using public data from different utilities and statistical analysis methods. Detailed load dynamics modeling is also performed in this paper to extend the synthetic electric network models.