Case Study: Slovenske Elektrarne (SE) cuts forecasting time to 15 minutes and saves €100,000 with Microsoft Power BI

Slovenské elektrárne supercharges weather predictions with Azure and Power BI analytics

Slovenske Elektrarne (SE), Slovakia’s largest electricity provider, faced slow, manual weather‑based forecasting that took analysts nearly two hours per run and limited their ability to react in electricity trading. To build a faster, cost‑effective system, SE turned to Microsoft Power BI alongside Azure services including Azure Synapse Analytics, Azure Databricks, Azure Data Factory and Azure Data Lake to create an AI‑driven forecasting platform.

The solution—ingesting meteorological data, training models in Azure Databricks/Synapse, and delivering forecasts via Microsoft Power BI—automated the pipeline and cut forecast time from about two hours to 15 minutes, eliminated manual intervention, and gave SE earlier market insights than external providers. The new system improved operational efficiency and is estimated to save around €100,000 a year while enabling quicker trading decisions.

Slovenske Elektrarne (SE)

Matúš Medžo

Sales Strategy Manager