Transfer Learning for Event-Type Differentiation on Power Systems

Haoran Li, Zhihao Ma, Yang Weng, Evangelos Farantatos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Machine Learning (ML) models are continuously introduced to power systems in domains like state estimation and event identification. However, training an ML model usually requires a lot of data. For data-limited grids, we propose a transfer learning framework to transfer knowledge from a source grid with rich Phasor Measurement Unit (PMU) data for the event-type differentiation problem. The goal is challenging due to (1) different dimensionalities of the source and the target measurement spaces, (2) dissimilar data distributions, and (3) redundant PMU's information. Thus, we project the source and the target measurement space into a latent feature space, which reduces and aligns the dimensionality of input measurements, maintains close data distributions in the latent space, and enables the transferability from the source domain to the target domain. Then, we introduce transfer learning in supervised learning by vectorizing each PMU's measurement window as one training sample, forming the latent space. We theoretically show that our approach minimizes the upper bound of misclassification rate and experimentally demonstrates the high performance on various synthetic datasets.

Original languageEnglish (US)
Title of host publication2022 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2022 - Proceedings
EditorsLars Nordstrom, Ninoslav Holjevac, Igor Kuzle, Igor Ivankovic, Mladen Kezunovic, Mario Paulone, Hamed Mohsenian-Rad, Carlo Muscas, Tomislav Basakarad
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9789531842822
DOIs
StatePublished - 2022
Event2022 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2022 - Split, Croatia
Duration: May 24 2022May 26 2022

Publication series

Name2022 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2022 - Proceedings

Conference

Conference2022 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2022
Country/TerritoryCroatia
CitySplit
Period5/24/225/26/22

Keywords

  • Event-type differentiation
  • dimensionality reduction
  • latent feature space
  • power systems
  • transfer learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Control and Optimization
  • Instrumentation

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