Using data to power-fuel the transition to a carbon-neutral world

Overview

Helen, Helsinki's energy utility, built a centralized data and AI platform on Databricks to power forecasting and optimization models for its district heating system serving about 90% of Helsinki's population, processing real-time streaming sensor and IoT data to optimize distributed energy resources and EV charging placement as part of a plan to cut carbon emissions over 80% by decommissioning coal plants.

The challenge

As Helen moves toward renewable energy, its energy system has become far more complex, relying on distributed energy resources like heat pumps, waste energy recovery, electric boilers and industrial by-products, requiring Helen to turn to AI and data-driven solutions to manage this complexity.

The solution

Helen developed a centralized data and AI platform using Databricks that powers forecasting and optimization models processing streaming data from hundreds of sensors and IoT devices to make real-time adjustments, enabling improvements ranging from predicting optimal EV charging station placement to optimizing energy system flexibility with virtual and physical energy storage.

Reported business value

Decommissioning coal plants for this AI-driven system will reduce Helen's carbon footprint by over 80%, and even small efficiency improvements from the platform translate into substantial cost savings and reduced carbon emissions.