Drax Power

Drax Power required a data science solution to generate accurate predictions of fluctuations in the Balancing Service Use of System (BSUoS) charge.

All energy suppliers must pay the BSUoS to the National Grid to cover the cost of ensuring the supply of energy meets demand. The charge is highly volatile and can change as frequently as every 30 minutes. This leaves operators like Drax Power vulnerable to increased costs, and can impact severely on profitability. Accurate predictions of fluctuations would enable Drax Power to optimise its production.

Elastacloud deployed a version of our data analytics platform to ingest the relevant data and develop a working model that could predict future movements of the BSUoS to a high level of accuracy.

Our experts created a database to which predictions could be delivered, and built an API that could be used by Drax Power’s energy trading team. In time, our predictions were integrated into their own trading platform dashboards.  

When it became clear that the model delivered valuable data to Drax Power, it invited us to build a service that could make predictions on a daily basis.


Elastacloud enabled Drax Power to transform its business with the help of artificial intelligence and our data analytics platform.  

Over the three years during which we operated our solution on behalf of the client, it saved Drax Power several million pounds.


“The machine learning model and forecasting platform has meant we can now reduce costs by minimising generation in the high BSUoS Charge price periods.”

Alex Nancolas
IT programme manager

'Energy predictions as a service' saves a client millions

Case Study Information

Client Drax Power
About the client

Drax Power is a UK-based renewable energy company. It operates across four sites in England and Scotland and is the largest supplier of renewable electricity to businesses in the UK.

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