In the Renewable Heat Incentive (RHI) consultation published by the last administration, the incentive will be paid to households against a "deemed" amount of heat, rather than the heat actually used. Put simply, deeming is a method used to estimate how much heat is required to provide comfortable conditions in a particular house. It is preferable to making a payment per unit, as explained previously.

So how is the amount of heat to be estimated

Simples!  It will use BREDEM.

BREDEM is the Building Research Establishment Domestic Energy Model.  Not many people have heard of it, which isn’t surprising, as it’s quite a technical concept.  

For the past 20 years it has underpinned much of the work done to set standards for energy efficient housing, and to support the installation of measures to improve energy efficiency. Perhaps it should be better known. It’s a model, so by its nature it’s an approximation compared to reality, and the reason it’s used so often is that it has the following features:

1. It’s not time consuming to calculate.  All models of building energy use require data to be entered

into a computer program. Unlike the more complex models that are used to design highly complex buildings, which can take several days to input all the data required, BREDEM uses fewer data items. This means that it balances the data required with the level of accuracy that’s needed, and with the possibility that more data  = more mistakes in entering that data.  Less time spent collecting and inputting data means less cost, so the overall cost of the RHI is reduced.

2. It’s got a long pedigree. Created in Milton Keynes in the early 1980s, and based on monitoring the energy used in real homes, the model has undergone much refinement since then, and the assumptions it makes about human behaviour have been updated. For example, the amount of energy used in lighting our homes has vastly increased in the last 30 years, as we now demand more variety of lighting and higher lighting levels - and the model has been updated to reflect this.

3. It ignores how the occupier uses their home heating. It calculates how much energy is needed to heat the home to a specific heating pattern, known as Standard Occupancy.  It assumes that the occupier heats the home for 2 hours in the morning and 7 hours at night on weekdays, and for 13 hours a day at weekends, to set temperatures of 21^o in the living room and 18^o elsewhere.  People may choose to heat their homes for longer or shorter periods, or to higher or lower temperatures, and ignoring these occupier preferences allows homes to be compared on a like for like basis.

4. It makes simplified assumptions about fuel use for lighting and hot water. Ignoring how many people currently live there, it assumes that the larger the home, the more people will live in it, so there will be more energy used for lighting and hot water; these two uses are therefore estimated based on the floor area.  

5. It can produce an energy rating that is independent of the size of the home.  If you were to look at the annual fuel bills for two homes, and one cost much more to heat than the other, you might think that was because it was less energy efficient. However, the two homes might be equally energy efficient in themselves, and the difference in bills – even ignoring the influence of the occupier, described above – might just be that one was twice the size of the other.  So the BREDEM model calculates the total energy use for the complete home taking into account its size, then expresses this as a rating by dividing it by the floor area, to give a figure per square metre.  

6. All the above means that BREDEM provides a fair comparison that ignores the preferences of the current occupier.  You can immediately see that the model isn’t going to correctly predict the heat needed for a specific occupier every time, since everyone is different, with some being heavy users and some being more careful.  The important point for the RHI is that everyone is treated equally, and the wasteful users don’t get more from the RHI than those who don’t waste energy.

This system is already used in the Energy Performance Certificate (EPC).  There is more than one version of BREDEM, and the one that’s used to produce EPCs is called BREDEM9.  This is a slightly simplified version of the full model, BREDEM12, which is used in the NHER rating system. However, if needed, the EPC could be uprated, with the addition of a few extra items of data, to allow for a BREDEM12 calculation to be made.  

For the technically inclined, the main differences between the two versions are:

BREDEM9 does not consider where in the country the home is located, so a home in the warmer South is assumed to have the same heat requirement as one in the colder North.  Using BREDEM9, people in the South will benefit more, compare to those in the North. 

It doesn’t include energy used for cooking, or used in appliances such as white and brown goods, which isn’t really an issue for the renewable heat incentive.

It doesn’t reflect the heat flows, between the better heated living area and those areas that are heated to a lower temperature, quite as accurately as does BREDEM12.  The Standard Occupancy assumption of 18^o in the rest of the home isn’t always achieved in real life, as some homes don’t have good enough heating controls.  Poor controls allow the rest of the home to overheat compared to the desired temperature. Overheating causes higher than necessary energy use, and this effect is better modelled in BREDEM12 than in BREDEM9.  This affects the calculation of the heat requirement, but so long as good controls are a requirement of the renewable heat installation (as they should be), it shouldn’t be an issue.

So there you have it – a suitable method for deeming the heat use in homes is already available for use in the renewable heat incentive.  So there’s no excuse - the politicians should agree that the RHI is needed, it can be made to work, and to give us confirmation that it’s going ahead. 

Illustration Energy flows: taken from BRECSU Information leaflet 6, dated Oct 1988

About the author: @linniR is a consultant, a freelance writer and a Domestic Energy Assessor accredited with the NHER scheme, and she enjoys all three.  She tweets regularly on issues relating to energy efficiency and renewables and provides consultancy, especially in relation to training needs.

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