Thermal demand profiles?



Hi all,

as you know the number of modelling frameworks that are capable of handling multiple energy sectors at once with a high temporal detail is increasing (calliope, oemof,…), which is great. However, it is still quite rare - at least as far as I’m concerned - to have hourly demand profiles for non-electric energy sectors (I’m referring in particular to thermal demand), which would be needed as an input to perform such an integrated modelling. From the Wiki I can only find yearly data, in fact, whereas hourly profiles are available for electricity from TSOs data and other sources. Anyone has ever faced/solved this issue?

Now, I’m putting this topic in the “Modelling” section, even if it is bordeline with the “Open Data” section, because I see that potentially the oemof-demandlib could provide hourly heat demand profiles, but I’m not 100% sure about how it works (the documentation is, unfortunately, still work-in-progress) nor about how much is it extendable to contexts other than Germany (since I understood that it builds profiles based on data provided by the German system operator).

If others (as I hope) are interested in this topic, and unless there’s a quick solution that I was not able to find myself, we might alsodiscuss it at the next OpenMod meeting.



Thermal demand data and models
Hourly resolved data of heat demand in private households (for Germany)

The heat part of the demandlib is based on the BDEW approach and as I know this approach is documented in German only :frowning:

Heat demand in Europe will become more important so I endorse the idea of a breakout group at the meeting. Unfortunately I will not be at the meeting but if anybody wants to add new approaches I can give admin privileges to the demandlib if wanted. At the moment the demandlib is not actively maintained but the general structure, documentation etc. already exist, so it might be a good start.


Thanks Uwe for the reply, I agree that it would be a good idea to start from what we have (demandlib) and see how we can expand it, even though I don’t know how to overcome the issue about the documentation (I was planning to learn German but it may take quite a while :smiley: ).

By the way, just for the sake of precision (I forgot to specify this): I am aware that there are a number of tools in the literature to model multi-energy load profiles with a bottom-up approach for the residential sector (e.g. DHW and space heating based on building info), but when modelling anything from town-scale to larger scales it is very unlikely in Europe to have only residential demands, so they won’t help.


We have to translate the most important parts (or explain the essential parts in our own words). The problem is that I have no time to do that until summer/autumn. I could try to find the essential parts and you could start with a online translator and some help on the OpenMod meeting.


I could try to find the essential parts and you could start with a online translator and some help on the OpenMod meeting

That would be great, if the whole document it’s not too long I think I can even manage to find by myself the most relevant parts, so that you don’t have to spend time on that. In the while I’m also searching throughout the literature for anything else that may help in this matter, so that eventually we can arrive at the Workshop with some ideas and discuss together with all those who are interested


You will find the description mainly in chapter 4. If you use a translator tool you can mark the most confusing parts and we may help to clean the translation.

I will not be at the meeting but I am interested in the outcome.


Thanks, sure I’ll post here any update, and I invite everyone who has an interest or advices on the topic to do the same, so that we can keep sharing thoughts regardless of the presence to the next meeting.



Hi Francesco,

the subject you are addressing is highly relevant. Obtaining consistent, temporally resolved data with good spatial coverage is one of the main challenges in building good models. As I am working on questions regarding the heating sector, I was happy to read your thread!

I hope that our discussion can lead to a better overview over the issue of creating heat load profiles, so I will begin by posting two approaches that we have crossed recently:

  • The first one is the mentioned approach of the german BDEW, implemented in the demandlib. I read through the corresponding guideline of BDEW and the PhD thesis and added some lines to the documentation. Have a look!

  • A second approach that I saw recently is the one used for the data released by DIW recently (documented here on page 56: Modeling approach and in this paper, page 6)

I am sure that there are other approaches, so I would be happy to discuss this issue with anyone interested on the upcoming meeting in Zurich!


Hi Jann,

thanks a lot for adding to the demandlib documentation, that will help a lot! It looks like the approach includes not only residential users but also commercial/services user classes, which would be already something more than what I found up to know (i.e. profiles for purely residential users only). Industry, instead, is not comprised, isn’t it (of course the approach cannot be the same)?




Hi Francesco,
for Germany there is some data available here which is documented in English here. Contact me if you need any further infos.


Hi Jens, this is great!
From a rapid look this seems to be the first approach that actually goes beyond considering only residential/commercial activities by including also industrial demand. It seems that it is considered as a “residual” demand when subracting the estimated residential and commercial demand from the national total. In this way I guess it can be added to an hourly profile as a “constant” surplus demand.
This is what I was thinking myself as the best option in the absence of more precise data.
I’m just wondering if the error of considering the Industrial profile as flat is large or not, but I think that we can hardly do better than this.

One question, is this approach the one formalised into the demandlib?




Hi Francesco,
I have not worked with oemof yet so I don’t know what methodology demandlib is using.
Best, Jens


Hi Francesco,

You’ve got a very interesting question here - and in a way I’m glad you’ve confirmed my thoughts that there is very little data available at the moment - as that makes this a good topic to work on.

The DESSTINEE model produces constructs artificial hourly demand profiles for electricity in each country of Europe and North Africa. This includes the influences of electrified heat and transport. It would be fairly easy to remove all other forms of electricity demand and focus on these, giving hourly profiles for heat and transport alone.

Kind regards,


Hi Iain,

thank you for sharing the DESSTINEE model, the idea of coupling a bottom-up approach with some macro-economic considerations sounds really interesting. Nevertheless, if I have more or less understood how the model is conceived, even removing other electricity uses from the DESSTINEE load profiles we would only get that portion of thermal demand that is supplied through electric appliances, which in many countries is currently a very small one. But in general, the idea of replicating/expanding something like this for the thermal side could be very interesting. I think that it might be useful also to compare the indications that can be provided by bottom-up models with those achievable from top-down models.

Since I see that many are responding to this topic with interest, I will propose shortly a working group for the next openMod, so that we can at least share views about the different existing approaches and get to know who’s doing what.



Reviewing approaches for Thermal Loads modelling

Hi Francesco and others,

I faced your question during my master thesis and created a dataset with thermal load profiles for 16 European countries. I combined the BDEW methodology (updated in 2015), which I documented in English and which I applied to other countries including some validation. For now, my thesis (section 3, from p. 23) and the dataset are available here. However, I am thinking about properly publishing an open dataset and a seperate documentation, so I am happy about your feedback, advice and discussion.



Hi Oliver,

this looks like a great and very welcome addition to what we have collected so far! I’ll definitely give a deeper look at the material you shared and provide some feedback. By the way, are you still working on that after the master thesis? Are you still in the research field?