Case Study: InterGen - Hypercube | Decision Intelligence for Energy

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.

Data and AI strategy

Hypercube delivered workshops with Trading, Commercial, Risk and Finance to understand how they use data and can harness it going forward. A clear and actionable data strategy was delivered that outlined the journey from gaining buy-in across departments, identifying key priorities, building a worldclass data platform and hiring an excellent inhouse data capability.

Time series data plan for energy traders

InterGen’s trading team are experts in their field and traded power through a mix of heuristics and traditional analysis methods. With the requirement to move to real-time forecasting, Hypercube identified that the trading team required a new solution with a minimal learning curve, thus enabling them to focus their time on delivering value through optimal trading rather than extensive upskilling.

Hypercube built and deployed a new data architecture using Azure Databricks to centralise, standardise and serve data to the business more effectively. The route to maximum productivity for InterGen was lowering the technical barrier to traders and the existing IT team, so people only needed to upskill on one toolset as they moved to real-time analytics. Traders and Risk teams can now perform self-sufficient analysis and gain secure, real-time insights all within Databricks.

Data estate optimisation

InterGen had previously deployed a data platform, but the capabilities, and ultimately consumption costs, far outstretched the current needs of the business. Hypercube reviewed the data estate and switched off underutilised elements of existing technology infrastructure to optimise costs.

Building internal data capability

Hypercube managed the recruitment and hiring process of InterGen’s data engineers, as well as establishing a data graduate scheme. This provides InterGen with a stream of organic talent as the function matures and grows out its technical expertise.