The National Household Model (NHM) is a domestic energy-policy modelling and analytical tool covering the whole of Great Britain. It was built by CSE and commissioned by central Government. CSE supported updates and maintenance of the Model until 2021, training Government analysts to operate and manage it going forward.

Using information from national housing surveys (the English Housing Survey and Scottish House Condition Survey), the NHM presents a detailed representation of the physical characteristics of Great Britain’s housing stock and the types of occupants who live in these homes. As a micro-simulation model, the NHM allows analysts to create policy scenarios and explore the potential impacts on domestic energy demand over time.

Modelling energy demand

A key component of the NHM is the ‘energy calculator’. This estimates the level of fuel consumption needed to maintain a specified heating regime. By default, this is calibrated to apply the Government’s standard assumptions for heating regimes (21° in living areas, 18° elsewhere). But the user can adjust these and apply their own settings.

The energy calculator estimates household energy demand by taking information on the physical characteristics of a property. This includes things like building fabric, insulation level and heating system from the housing stock dataset. It combines these characteristics with energy prices (again, defined within the model but adjustable by the user) and calculates energy demand to generate an annual fuel bill for the household. This forms the basis for calculating the SAP rating – an estimate of the energy efficiency of the building, based on the building’s performance on energy costs per square meter.

Scenarios and reporting

All modelling and analysis of the housing stock data is constructed through ‘scenarios’ written by the user on a web-based user interface that permits a very high degree of flexibility. A single scenario may encompass a huge range of functions – from modelling the impact of very complex, multi-layered policies on specified households to a simple report showing housing stock characteristics such as energy demand or SAP rating.

The housing stock data underpinning the NHM encompasses a wide range of variables, including physical factors (e.g. dwelling type, age of property), geographical factors (e.g. region, rurality) and socio-demographic factors (e.g. tenure, income, number of occupants). All of which may be used within a scenario for policy modelling and reporting purposes.

The NHM also generates reports in the form of user-defined tables that explore features of the housing stock and the impact of a policy over time, at the aggregate or individual household level. As well as reporting on different socio-demographic variables, the user can also generate reports to quantify the total cost of measures deployed, loan repayments, household energy consumption, carbon emissions, fuel bills and energy efficiency measures.

In addition to modelling the effect of policies on the housing stock, the NHM incorporates external factors that may change over time and have implications for household energy demand. These include weather conditions, fuel prices, rates of taxation, capital costs of technologies, and behavioural characteristics (like the way people use their heating).