Regarding HP heat demand-Electrical power; Self-consumption; Location

[sidsanghani]

Hello Sir,

I am currently working on my Master's thesis on "Demand Side Flexibility". In order to analyze household load consumption and PV generation data, I am interested in utilizing "alpg". I have a few questions regarding the Heat Pump's Heat Demand Output, the results of Self-Consumption, and the location in Germany.

1: Result folder:

• I have a dataset called "Heatdemand_Profile" which contains information on the heat demand (in Watts) for DH Water. In addition, I also have a "Heat gain profile" which includes the combined heat gain from both people and devices. My question is whether the values in these datasets are already in electrical power (Watts) or if I need to convert them using the COP?
• Additionally, I would like to inquire about how the HP or CHP heat demand is factored into the results. I have also observed alterations in the profiles of "Heat gain" and "Heat gain persons" based on the thermostat's response to achieving the set point temperature. Could you clarify if the data for "Heat gain persons" (measured in Watts) is equivalent to the heat pump's heat demand, or do I need to do something else for the calculation? I would appreciate your guidance on this matter.

2: example.py:
-In the "example.py" file, I came across a line that reads, "This emulates the Dutch 'nul-op-the-meter regime (net zero annual electricity usage)." From this, it appears that the output is generated using either a self-consumption or a net-metering mechanism to achieve net-zero annual electricity usage. Can you provide more clarity on the meaning of this line?

• I need to update the location from the Netherlands to Germany in this file. I switched from the "Europe/Amsterdam" timezone to "Europe/Berlin" in order to collect German household data, and I also updated the latitude and longitude accordingly. I'm curious to know if the changes I made are enough to display the relevant data or if I need to modify anything else in the config or input folder.

Thank you in advance!

[ghoogsteen]

Dear sidsanghani,

Thanks for using the ALPG. Regarding your questions:

Question 1: All values for heating are provided in Watts of thermal energy, This way, they can be used for any type of heating device (to support also multiple energy vectors). But important here is that we do not provide direct heating demand! The output files are only the data streams required to eventually be able to calculate the heat demand based on also the insulation, position of windows, solar irradiance etc. Due to all nonlinearities, a static load profile would not be accurate. Instead, we follow the needs as discussed by R.P. van Leeuwen in his thesis: https://research.utwente.nl/en/publications/towards-100-renewable-energy-supply-for-urban-areas-and-the-role-

The easiest way is to combine the ALPG with our open source DEMKit simulator, which reads these files and can generate heat demands based on thermal models and different operations of a heat pump (or other heat source). More details are in my phD thesis, the software can be found here: https://github.com/utwente-energy/demkit

For your second question: You should also update the weather data to reflect the solar irradiance on your location. The rest should be fine indeed.

Regarding the comment "This emulates the Dutch 'nul-op-the-meter regime (net zero annual electricity usage).": We generate the number of solar panels such that the annual production would (nearly) match the annual consumption. This is optimal (economic wise) in the Netherlands at this moment, and therefore reflects a realistic scenario. But you can always scale the resutling profile (or use a different PV input) to your own liking

Good luck and let me know if you have further questions.

Best,
Gerwin

[sidsanghani]

Dear Gerwin,

Thank you for your help. It will be helpful for my thesis.

Best regards,
Siddharthkumar Sanghani.

[sidsanghani]

Hello Mr. Gerwin,

I have an additional concern regarding the text profiles for the washing machine and dishwasher. It's challenging to articulate my question, but here it is:

In the profile text file, there are consistent readings of active and reactive power for specific appliances, such as the washing machine (72 times) and dishwasher (81 times). I have noticed that these readings remain unchanged throughout the year or week.

In the "Readme" file, there is a line that states, "Specifies the consumption profile for Timeshiftable devices (washing machines, dishwashers, etc) for each interval of 60 seconds." Based on my understanding, this profile generates data on the active and reactive power for 72 minutes for washing machines and 81 minutes for dishwashers.

Let's say the washing machine runs for 269 minutes. To calculate the intervals, we can divide 269 by 72, which equals 3.74. So, the machine operates for 72 intervals three times and then runs until the 53rd minute (72+72+72+53=269). This is how I plan to use the active and reactive power data for the entire 269 minutes. Can you please clarify if I am on the right track, or explain in more detail how I can determine the active and reactive power profiles based on the start and end time text profiles if I am incorrect?

I appreciate your assistance and the time you have dedicated to helping me.

Best regards,
Siddharthkumar Sanghani (Sid).

WashingMachine_Profile.txt
Dishwasher_Profile.txt

[ghoogsteen]

Dear Sid,

You can't say that the washing machine runs for 269 minutes. The profile provided is a measured profile of an actual washing machine that runs for 72 minutes before it is done with washing the clothes. Hence, every time it starts, the same power profile is loaded from the start time and then it runs for the 72 minutes, after which its consumption is 0 again, until the next start.

The start and end-times indicate the so-called "availability" of the device. That is, the time the laundry is put into the washing machine (start-time) and the time the laundry needs to be finished latest as set by the user (end-time). This means that the latest start time is endtime - 72 minutes. This is what we call flexibility, and therefore indicates how an Energy Management System can shift the actal start time, the moment the device is activated, to better match e.g. renewables. In mathematical optimization, these can be seen as constraints.

If you want to have another profile of a washing machine, you can override the given profile of course.

Best,
Gerwin

[sidsanghani]

Dear Gerwin,

I got my answer. I appreciate your assistance and the time you have dedicated to helping me.

Best regards,
Sid

[sidsanghani]

Hello Mr. Gerwin,

I want to know the House index (IDposition)'s in the CSV and text files. I've included a PNG file with this issue for you to understand it better. Is that in the same order that the user wrote it in the "example.py" file, or is there another order?

I appreciate your assistance and the time you have dedicated to helping me.

Best regards,
Sid.