Windpower Engineering & Development

  • Home
  • Articles
    • Most recent posts
    • News
    • Featured
  • Resources
    • Digital issues
    • Podcasts
    • Suppliers
    • Webinars
    • Events
  • Videos
  • 2025 Leadership
    • 2024 Winners
    • 2023 Winners
    • 2022 Winners
  • Magazine
  • Advertise
  • Subscribe

Sempra selects Ensemble Energy’s predictive analytics platform to increase wind production & lower costs

By Michelle Froese | April 2, 2018

Ensemble Energy announced that they have been selected by Sempra Renewables to extend a pilot project using Ensemble Energy’s predictive analytics platform to reduce cost and increase energy production in Sempra’s wind-turbine fleet.

Ensemble Energy predictive maintenance program

Ensemble Energy’s predictive analytics platform lets wind operators predict turbine failures days or weeks before they occur, reducing costs and lost production.

Sempra began working on a pilot with Ensemble Energy in 2017. The pilot focused on two specific component reliability issues that were driving unplanned maintenance costs at one of Sempra’s projects.

Ensemble Energy wind-turbine engineers and data scientists worked closely with the Sempra team to build predictive models of the selected components using advanced machine learning and artificial intelligence techniques. The predictive models developed by Ensemble Energy use existing sources of data, with no additional hardware required.

Upon receiving indications of anomalies from the Ensemble Energy predictive analytics platform, Sempra performed inspections of the turbine components, and confirmed the accuracy of Ensemble Energy’s notifications.

In one case, the Ensemble Energy anomaly notification allowed Sempra to perform a maintenance action that prevented a significant failure, resulting in a very large cost savings.

“Detecting operational and maintenance issues on our system in a timely manner is very important to Sempra Renewables and our stakeholders,” said Darren Weim, director of operations at Sempra Renewables. “Ensemble Energy’s advanced analytics capability coupled with their wind-turbine engineering expertise, are helping us identify and address potential issues well in advance, thereby supporting our maintenance and reliability goals.”

Dr. Sandeep Gupta, CEO of Ensemble Energy added: “Combining machine learning with domain expertise is the key to making the best decisions for predictive maintenance.”

Dr. Gupta also commented on the working relationship between Sempra Renewables and Ensemble Energy, noting that “Sempra Renewables has been an incredible partner for Ensemble. They are committed to using the very best tools and practices maximize production and minimize costs, and we could not be prouder to be helping them to do just that.”


Filed Under: News, O&M
Tagged With: ensembleenergy
 

About The Author

Michelle Froese

Related Articles Read More >

Richardson Electronics to deliver pitch energy modules to TransAlta wind fleets
Equinor halts work on Empire Wind offshore project after federal government order
ARESCA wants input on offshore wind standards
US wind market has worst install year since 2013

Podcasts

Wind Spotlight: Looking back at a year of Thrive with ZF Wind Power
See More >

Windpower Engineering & Development Digital Edition

Digital Edition

Browse the most current issue of Windpower Engineering & Development and back issues in an easy to use high quality format. Clip, share and download with the leading wind power engineering magazine today.

Windpower Engineering & Development
  • Wind Articles
  • Solar Power World
  • Subscribe to Windpower Engineering
  • About Us/Contact Us

Copyright © 2025 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy | Advertising

Search Windpower Engineering & Development

  • Home
  • Articles
    • Most recent posts
    • News
    • Featured
  • Resources
    • Digital issues
    • Podcasts
    • Suppliers
    • Webinars
    • Events
  • Videos
  • 2025 Leadership
    • 2024 Winners
    • 2023 Winners
    • 2022 Winners
  • Magazine
  • Advertise
  • Subscribe