Build Without This and Your Home Fails

Okay.

So

I think there's two ways to think about this to start with.

Number one is you can't build 10 versions of the same building, live in them for 10 years, work out which one is best and say that's the one I want to go with.

Okay.

Well, that's the end of the podcast.

Thanks, Cam.

So modelling is a waste of time.

And so given that you can't build those 10 buildings, live in them and work out which one was the best, you've got to have another way of doing it.

And that's what modelling is.

And I think the way I always try to bang on about modelling is it's a what if.

What if I do this? What if I do that? And it tries to provide a...

balanced quantitative, so numerical basis to establish the difference between option A, option B, option C through to Z.

And when you

say option A, it could be like double glazing or triple glazing or is that what you mean by option A, option B? And I

think it would be cheaper to model things 10 times and actually build the house 10 times.

Of course.

And it's almost impossible with a real built building to actually evaluate the how much energy and, you know, we should say at the outset, the particular sort of modelling we're talking about here is thermal modelling a building.

How energy efficient is it? How comfortable ultimately does it become? You've got, it's a very challenging thing to build a building and measure how much energy it consumes.

That's not as trivial as it may at first.

Have you ever done that? Like, so you've obviously run that many PHPPs.

Have you ever got like lives of data, put it back in and compared it to the model or what?

Yeah, so I've tried to do that with my place.

So just to jump into that for a second, obviously you're trying to benchmark the heating and cooling energy required that was modelled with the heating and cooling energy of the real observed building.

Now, problem number one is the climate file you've used in the thermal model doesn't necessarily accord with the last 12 months.