Table 1
SMETER technology options.
| SMETER TECHNOLOGY OPTION | DESCRIPTION |
|---|---|
| 1) ‘Remote’ SMETER methods | Do not require internal temperature measurements. These can be applied at scale using smart metering and weather data, as within a recent pilot (Hollick et al. 2025). |
| 2) Methods using a single temperature sensor located within an existing device | Utilising for example a smart thermostat or a temperature measurement-enabled smart meter in-home display located in a central point in the home. |
| 3) Methods using one or more standalone temperature sensors | Sensors typically installed in homes as part of deployment. |
| 4) Methods using additional measurement data9 | Uses, for example, data from heat metering or other types of measurement that is more complicated to install than temperature sensors. These will tend to be more costly than 1–3 due to being more complicated to deploy. |
Table 2
In-use performance measurement relevance, implications and benefits by opportunity area.
| OPPORTUNITY AREA | AREAS OF RELEVANCE AND KEY INFORMATION SYSTEM CONSTRAINTS | IN-USE MEASUREMENT AND KEY DATA SYSTEM IMPLICATIONS FOR HIGHLIGHTED AREAS | BENEFITS – KEY POLICY AND MARKET OUTCOMES |
|---|---|---|---|
| Policy coordination | Home energy performance interactions with housing market, health, fuel poverty and electricity networks and flexibility: Constraints relate to lack of granular spatial data on the performance gap and thermal inertia of the housing stock. | To include granular data on heat loss rates and thermal inertia in data systems, in order to enable coordination with public/regulated bodies such as DNOs. Supporting technology may be a mix of remote SMETER methods & internal temperature data. |
|
| Performance management | Building and minimum efficiency standards, heating system governance, supplier obligations and publicly funded retrofit programmes: Constraints relate to performance gap-related weaknesses in predicting and reporting outcomes within model-based information systems. | To integrate the capability to measure heat loss rates into information systems, supported by validation and QA arrangements. Maximum value would accrue from the capability to measure and access HTC information for both individual and groups of homes. |
|
| Fiscal management | ‘User pays’ via regulation (ECO), public grants, tax incentives and carbon pricing/financing arrangements: Constraints relate to reliance on EPC-based information which does not accurately represent outcomes. | Case for a centralised data system to provide controlled/aggregated access to energy consumption and HTC data. |
|
| Market transformation | Property market, energy products and services and energy efficiency retrofit and low carbon heating. Constraints relate to reliance on modelling of thermal performance, leading to inability to accurately predict e.g. heating demand. | Need for robust QA, integration of measurement into existing standards & tools. Facilitating ease of access to measurement for innovators, supply chain actors and householders. |
|
| Behavioural and organisational change | Engagement in owning, prioritising and legitimising net-zero actions by communities, businesses and householders. Constraints relate to the perceived low relevance to individuals of current information on energy performance and costs. | Need for robust QA and verification of individual performance measurements. Ability of the system to support personalised measurements (thermal performance reflecting occupant behaviour). Ease of availability of measurement tools, including to disengaged. |
|