InterGen Builds Times-Series Forecasting and Advanced Energy Trading

About InterGen

InterGen is a world-class owner, developer and operator of power generation, with a 28-year history of financing and operating gas power stations. It’s one of the UK’s largest independent power producers and has an expert power trading team for the UK electricity market.

Its portfolio includes the Spalding battery energy storage system development, co-located with the Spalding power plant.

1.07 Million Homes Powered a Year
2,800+ Megawatt Generating Capacity
190 Employees Across the UK

The Challenge

Euan Chisholm, the Trading and Commercial Director at InterGen, initiated efforts to modernise data practices and leverage data science and AI for strategic decision-making within the business. However, initial attempts to transform the data culture faced challenges that are common across many energy organisations:

  • Overstretched internal IT capacity with cloud solutions skills gap.
  • Data team siloed from other departments.
  • Lack of optimised data science tooling.
  • Unable to drive real value from the existing platform investment.

InterGen required expertise to deliver a clear data and AI roadmap.

"Working with a partner like Hypercube, which has experience working with other companies in the energy industry and can draw on the experience, allows us to take the time to grow our data team organically.” 

Christopher Wallace
Head of Data and Analytics at InterGen

Approach

Hypercube partnered with InterGen to design, develop, and build its next-generation data and AI capability. Its approach was two fold – deeply understanding the business context, domain, and stakeholder requirements to design a data and AI strategy for InterGen to adopt and drive positive change over the coming years. Hypercube designed and delivered a data platform to prove the first advanced analytics use cases and integrated the new technology with InterGen’s ways of working.

InterGen has gained:

  • Improved decision making for the energy trading team.
  • Data estate optimisation with cost saving of £3,000 per month.
  • Time-series forecasting capability essential for energy trading.
  • A highly skilled in-house data capability.

"We’ve built a forecasting model that looks at the different trading routes to market, the different trading platforms and how we can best optimise trading between the two. We were able to show in quite simple charts and outputs, how the model helps decision-making and how it adds value to our business.”

Euan Chisholm
Trading and Commercial Director at InterGen

Read the full case study to discover how Hypercube helped InterGen's energy trading team make better decisions, save £3,000 per month in consumption costs and more