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iLAD and DIME Show and Tell webinar

10 June 2026 — 10:00 - 11:30

10 June 2026 — 10:00 - 11:30
Status: Spaces Available

Join us for our Show and Tell on the Innovating Losses Analysis and Detection (I-LAD) and DIME (Demand Insights for Metered Enterprises) projects.


I-LAD is an innovation project focused on improving how non-technical losses (NTLs), such as energy theft, are identified and reduced. By combining data from electricity networks, energy suppliers and third-party sources, I-LAD is transforming detection through smart, data-led tools that deliver greater accuracy, efficiency and coordination across the sector.

 

In the Show and Tell session, we will share: 


  • Key progress from the Alpha phase, including how the project has demonstrated early feasibility, detecting and identifying cases of energy theft
  • Outline our approach to trusted governance, highlighting transparent data sharing within a robust, GDPR-compliant framework to ensure fair, secure and accurate insight generation
  • How I-LAD supports lower costs, fairer outcomes for consumers, reduced emissions, and future scaling into the Beta phase
  • Interactive wireframes and a demo tool of I-LAD to support decision-making
  • Outputs tested with stakeholders to ensure practical and ensure real-world usability 

DIME is a Discovery-phase project looking at how we can better understand electricity demand from non-domestic customers who are not half-hourly metered. These customers are less visible on the network, which makes planning and forecasting more challenging.


In the session, we will:

  • Introduce the problem DIME is aiming to address
  • Share key learning from the Discovery phase so far
  • Outline the potential benefits of improving demand insights in this area

We’ll also touch on what this could mean for future network planning and whether the approach is worth taking forward into further development.

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Event Details

When:

10 June 2026 — 10:00 - 11:30

Status:

Spaces Available

Location:

Online

Contact Name:

Simon O'Loughlin

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