The Energy Consumption Twin

Challenge Description

Energy suppliers and BRPs (Balance Responsible Party) manage thousands to millions of connection points, yet they lack a true behavioral understanding of how customers consume energy. CRM systems capture contracts, billing, and contact data, but they do not explain load behavior, predictability, flexibility potential, or imbalance risk. The challenge is to design and prototype a Consumption Twin: a digital behavioral model of individual connection points, capable of learning, forecasting, scoring flexibility, and detecting anomalies, even when smart meter data is low frequency or delayed.

Business Context / Why This Matters?

The energy sector is entering a phase where customer consumption behavior is more important than customer identity. Traditional tools such as CRM systems and billing platforms provide valuable administrative and commercial information, but they do not explain how customers actually behave on the energy grid. For suppliers, BRPs and energy service providers, the true challenge lies in predicting and steering consumption patterns so they can manage portfolio risk, reduce imbalance exposure and offer smarter services to their customers.

Specific Requirements

• Read-only integration with existing customer database via API or database view
• Strictly no data mutations

Data provided

A copy of the DVEP CRM and metering database is available.

Solution (Expected Outcome)

• A working proof of concept that demonstrates how consumption behavior can be modeled and interpreted for multiple EANs (European Article Number - in this context, Energy Identification Number)
• A live demo on laptop or tablet showing meaningful insights derived from real or simulated data
• A concise architectural overview describing how the concept could scale beyond the PoC