Smart meters: 40 million data sources

The smart meter rollout happened in two distinct technology generations, and the differences between them created one of the most painful interoperability failures in British energy.

SMETS1 (Smart Metering Equipment Technical Specifications, first generation) meters were installed from 2011 onwards. Each supplier chose its own communications provider and protocol. When a customer switched supplier, the new supplier could not communicate with the existing meter because it used the previous supplier's proprietary system. The meter reverted to “dumb” mode — it continued recording usage but could no longer send readings remotely. Customers had to go back to manual readings, defeating the entire purpose of a smart meter.

This interoperability failure affected millions of consumers and became a significant political embarrassment. The solution was the DCC migration programme: over 16 million SMETS1 meters have now been enrolled onto the shared DCC network, restoring smart functionality regardless of which supplier the customer uses. The migration was technically complex — each meter type required bespoke firmware updates and communication protocol changes.

SMETS2 meters were designed from the outset to avoid these problems. They communicate exclusively through the DCC using standardised protocols defined in the Smart Energy Code. The Home Area Network uses ZigBee at 2.4 GHz, connecting the electricity meter, gas meter, In-Home Display (IHD), and any Consumer Access Devices (CADs). SMETS2 supports remote prepayment switching, remote firmware updates, and supplier switching without losing smart functionality.

The numbers tell the story of progress: over 40 million smart meters are now installed, approximately 70% of all meters are smart, and 36.7 million are operating in full smart mode. Each meter produces 48 half-hourly readings per day — nearly 2 billion readings daily across the installed base.

Getting 48 readings per day from 40 million meters to the organisations that need them requires a communications network of considerable scale and complexity. The Data Communications Company (DCC) operates this network through two Wide Area Network (WAN) providers, each using different technology suited to different geography.

VMO2 (formerly Telefonica) provides cellular connectivity for south and central England. Meters communicate via 2G and 3G networks, with a migration path to 4G underway. The cellular approach works well in urban and suburban areas where mobile coverage is strong. However, approximately 7 million meters are at risk from the planned 2G and 3G network sunset — when mobile operators switch off these legacy networks, any meters still relying on them will lose connectivity unless they are migrated to 4G or an alternative technology.

Arqiva provides a dedicated radio mesh network operating at 868 MHz for north England, Scotland, and Wales. This long-range, low-power technology is better suited to rural and hard-to-reach areas where cellular coverage may be unreliable. Meters communicate via relay nodes to base stations, forming a mesh that can route around obstacles and coverage gaps.

A third option, VWAN (Virtual WAN), is launching in 2026 to address areas where neither cellular nor radio mesh provides adequate coverage. VWAN uses broadband connections — the customer's existing internet service — to reach meters in locations that are otherwise impossible to connect wirelessly. This is particularly relevant for meters in basements, deep inside buildings, or in areas with persistent wireless dead spots.

Inside the home, the Home Area Network (HAN) uses ZigBee at 2.4 GHz to connect the electricity meter, gas meter, In-Home Display, and Consumer Access Devices. The gas meter does not have its own WAN connection — it sends readings to the electricity meter via ZigBee, and the electricity meter relays them to the DCC. This extra hop adds latency and creates an additional point of failure for gas data.

To understand why smart meter data is both transformative and sensitive, consider what 48 half-hourly readings from a single day actually reveal. This is not hypothetical — it is what your meter records about you every day.

06:30 — the morning spike. Consumption jumps from near-zero to 1.5 kW. The kettle goes on, lights come on, the shower heats up. The time of this spike reveals when the occupants wake. A consistent 05:00 spike might indicate shift work. A 09:30 spike might indicate retirement or working from home.

08:00 to 17:00 — the daytime profile. If consumption drops to baseline (fridge, standby loads, around 200-400 W), the home is likely unoccupied. If it stays elevated, someone is working from home. A mid-morning spike might be a washing machine. A sustained 2-3 kW draw might be a home office with monitors and a desktop computer.

18:00 to 19:00 — the evening peak. A 3 kW spike for 30 minutes is an oven or hob. Multiple shorter spikes suggest a microwave-heavy household. The timing and size of cooking peaks correlate with household composition — families cook differently from single occupants.

22:00 to 06:00 — the overnight plateau. A sustained 7 kW draw from midnight to 06:00 is almost certainly an electric vehicle charging. A 3 kW overnight draw might be a storage heater. Complete silence (just standby at 100-200 W) for several days might indicate the occupants are on holiday — information that could be of interest to burglars.

Midday negative readings. If your meter records negative consumption around midday, you have solar panels and are exporting electricity to the grid. The magnitude and timing reveal the size and orientation of the solar installation.

The patterns extend beyond single days. Weekly patterns can reveal religion (low Friday evening consumption followed by Saturday absence might indicate observant Judaism; Sunday morning absence might indicate church attendance). Irregular patterns over weeks might indicate health issues. Sudden changes in routine might indicate relationship changes.

This is precisely why the Information Commissioner's Office classifies half-hourly smart meter data as personal data under UK GDPR. It is not merely a record of energy use — it is a detailed diary of domestic life, recorded 48 times a day, every day, from a known address that can be linked to identifiable individuals.