Skip to main content

Machine Learning and Data Science in the Power Generation Industry

Best Practices, Tools, and Case Studies

  • 1st Edition - January 14, 2021
  • Editor: Patrick Bangert
  • Language: English
  • Paperback ISBN:
    9 7 8 - 0 - 1 2 - 8 1 9 7 4 2 - 4
  • eBook ISBN:
    9 7 8 - 0 - 1 2 - 8 2 2 6 0 0 - 1

Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational progra… Read more

Machine Learning and Data Science in the Power Generation Industry

Purchase options

Limited Offer

Save 50% on book bundles

Immediately download your ebook while waiting for your print delivery. No promo code is needed.

Book bundle cover eBook and print

Institutional subscription on ScienceDirect

Request a sales quote
Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study–driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting.