Review of Machine Learning in Power System

Zhibo Ma, Chi Zhang, Chen Qian

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

Abstract

The trend of decentralisation and decarbonisation have been developed over the years. This has brought certain challenges to the prediction and control of the energy system using conventional method. There are some recent technology breakthrough in Machine Learning which has made some of the objectives achievable in many different aspects especially for the non-linear tasks. This paper has focused on reviewing the available machine learning technologies applied on the fault forecasting and load forecasting in power system.

Original languageEnglish
Title of host publication2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019
PublisherIEEE
Pages3401-3406
Number of pages6
ISBN (Electronic)9781728135205
DOIs
Publication statusPublished - 24 Oct 2019
Event2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019 - Chengdu, China
Duration: 21 May 201924 May 2019

Publication series

Name2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019
ISSN (Print)2378-8534
ISSN (Electronic)2378-8542

Conference

Conference2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019
CountryChina
CityChengdu
Period21/05/1924/05/19

Keywords

  • Deep learning
  • Demand Forecasting
  • Fault Forecasting
  • Machine learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization

Cite this

Ma, Z., Zhang, C., & Qian, C. (2019). Review of Machine Learning in Power System. In 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019 (pp. 3401-3406). [8881330] (2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019). IEEE. https://doi.org/10.1109/ISGT-Asia.2019.8881330