On-Line Electrical Supply Generation Fuel Mix Data Analysis using Python and TensorFlow

Ian Grout, Willian Assis Pedrobon De Ferreira, Alexandre Cesar Rodrigues Da Silva

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, the Python scripting language and TensorFlow open source platform for machine learning is used to create a software script that can automatically extract electricity supply generation data from an on-line resource and use machine learning techniques to analyze the available data for the creation of end-user information. An on-line resource was chosen where the data could be readily extracted and stored in multi-dimensional TensorFlow arrays for analysis. The usefulness of such generated end-user information is however based on the accuracy of the information and any biases introduced in the data collation, data presentation, data analysis and results presentation, along with the perceptions of the enduser. With these considerations in mind, this paper focuses on the aspects relating to the creation, operation and use of the Python and TensorFlow script.

Original languageEnglish
Title of host publicationProceedings of the 2019 International Conference on Power, Energy and Innovations, ICPEI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages20-23
Number of pages4
ISBN (Electronic)9781728152660
DOIs
Publication statusPublished - Oct 2019
Event2019 International Conference on Power, Energy and Innovations, ICPEI 2019 - Pattaya, Chonburi, Thailand
Duration: 16 Oct 201918 Oct 2019

Publication series

NameProceedings of the 2019 International Conference on Power, Energy and Innovations, ICPEI 2019

Conference

Conference2019 International Conference on Power, Energy and Innovations, ICPEI 2019
Country/TerritoryThailand
CityPattaya, Chonburi
Period16/10/1918/10/19

Keywords

  • analysis
  • electricity supply generation
  • monitoring
  • on-line
  • Python
  • TensorFlow

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