Case study

How sepaş enerji saved 8% on electricity costs with enverus fused demand forecasts

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Executive summary

Sepaş Enerji is a leading electricity provider in Turkey, delivering reliable power through designated suppliers. The group is the assigned retail supply company for the Turkish cities of Sakarya, Kocaeli, Bolu, and Düzce, and supplies electricity to more than 1.8 million subscribers and 4 million people across the country. The group formed in 2013 via a joint venture between AKKOK Holding and ČEZ Group, two leading international firms that are well-known in the European region.

In 2020, Sepaş Enerji ranked 85th in Turkey’s Fortune 500 list in terms of net sales, and supplied 9.8 TWh of electricity. This year, the group was ranked 4th Best Employer in Turkey by the Great Place to Work Institute among companies with 100-249 employees.

To effectively balance its electricity load, Sepaş Enerji’s experienced team of demand forecast engineers works to innovate and improve its internal models and analytics. The team is constantly seeking to improve the accuracy of its forecasts, and sought out a solution that would enhance the distribution unit responsible for delivering energy, aiming to improve the quality of supply and new distribution. This group oversees the building of new distribution facilities while increasing capacity and investing in future growth. It was vital for the team to develop a strategy that not only supported continued market share growth, but also minimized the risk of energy supply losses in the region.

Quick facts about Sepaş enerji:

4th in great place to work turkey ranking
85th in turkey’s fortune 500
4th in great place to work turkey ranking
Delivered 9.8 twh of electricity in 2020
Saved 8% in electricity budget with enverus

How sepaş enerji adopted support for innovation, accuracy and cost savings:

Before Sepaş Enerji adopted Enverus Fused Demand Forecasts, the group depended on a local provider that distributed forecasts via email. The team received six different forecasts localized to Sepaş Enerji’s distribution regions, of which distribution managers and analysts would choose the most accurate option.

While this process supported the team’s trading and risk strategy, the forecast engineers knew that improvements could be made in intraday market interpretations. Without functionality for updating metrological or weather conditions, the team could not simulate forecast scenarios based on upcoming changes that could impact load or supply.

The solution

Sepaş Enerji switched over to Enverus Fused Demand Forecasts for a more responsive and interactive solution to support the team’s distribution forecasting analytics. Enverus’ platform is an interactive, web-based platform that allows Sepaş Enerji analysts to simulate supply and demand scenarios and adjust forecasts based on multiple weather changes.

“With the Fused Demand Forecasts system, our colleagues can easily see the results, accurately and fast, to make quick responses from the system,” said Remezan Arslan, Energy Supply and Regulation Director.

Improvements made with Fused Demand Forecasts:

  • Accuracy rate increased 0.2% from 2.5% to 2.3%
  • Total electricity cost savings: 8%

“With the Fused Demand Forecasts system, our colleagues can easily see the results, accurately and fast, to make quick responses from the system.” 

- Remezan Arslan

Energy Supply and Regulation Director


Enverus’ machine learning-based technology continues to improve as it collects more and more data about Sepaş Enerji’s load patterns. From 2020 onward, demand patterns could pivot at the drop of a hat as unexpected COVID-19 related government shutdowns curb electricity consumption.

As we continue to work with customers like Sepaş Enerji, Enverus is proud to keep teaching our deep learning and neural networks how to adapt to completely unpredictable load shifts.

No matter where your electricity distribution is located in the world, Enverus has the capability to learn the region’s demand habits and help your company save money on power purchases.

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