Borusan EnBW reduced balancing costs with Kavaken

Learn how Borusan EnBW reduced balancing costs with Kavaken's solutions.

Bora Tokyay
Bora Tokyay
Co-Founder / CEO
“We have been working with multiple providers for more than 5 years. Thanks to Kavaken’s solutions we have achieved the highest accuracy in our production forecasts in all of our plants.“
Tuna Guven, Assistant General Manager, Operations at Borusan EnBW
“Kavaken’s product enabled us to reduce balancing costs and save on operational expenses.“
Emre Okuyan, Assistant General Manager, Business Development, Sales & Trading at Borusan EnBW

Challenge

Borusan EnBW is one of the leading renewable energy providers in Turkey with an installed capacity of 505MW.

  • Given their large capacity Borusan EnBW were looking to improve their day ahead predictions to reduce balancing costs and increase operational efficiency
  • In addition to accuracy improvement Borusan EnBW are expanding their asset portfolio and need a solution that can scale with growing needs
  • On a user level, one of the biggest challenges was the lack of a user interface to monitor predictions with historical data and insights

Solution

Kavaken addressed Borusan EnBW’s concerns with a holistic solution powered by its proprietary machine learning platform. First, forecast accuracy was improved via leveraging more data resulting in higher financial returns. Second productivity challenges were addressed with a simple and intuitive customer interface where users can digest key metrics and make informed decisions. Kavaken’s close collaboration with Borusan EnBW yielded the best accuracy seen in the last 5 years. Improvements in accuracy were validated across 8 wind farms.

Results

  • 5–10% Improvement in forecast accuracy
  • Kavaken predicted highest accuracy across all 8 power plants for a whole year
  • Solution is easily being scaled to Borusan EnBW’s new fields
  • Received the Best Corporate Startup Collaboration Award

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