Modeling different dispatch algorithms with pySAM

I am trying to model a system using PV-Battery Residential. I want to be able to size a system with fixed module/inverter but with different battery size options and different weather resource files and different loads (since location has now changed) and hence electricity rates have changed and typical loads have changed. I have done this with one specific location in SAM.

I am aware we can model in SAM and input to pySAM. How can I achieve this in pySAM ?

For e.g I want to be able to model location-1 with manual dispatch and location-2 with price/signals but these locations are arbitrary and I want to supply this in pySAM. There are a lot of inputs in pvsam1 so I am not sure whether this means I have to model each location first in SAM and then use the inputs in pySAM.

Second question is I saw the presentation with self-consumption dispatch which is not available in the stable release, would this be available anytime soon ? Is there a way I can experiment with this algorithm ?

Hi Sunil,

The Self-consumption dispatch option is available for behind-the-meter batteries in SAM 2023.12.17:

 

As for your PySAM question, my recommendation would be to set up a base case in SAM with the inputs you want, then use the code generator to generate JSON for PySAM files and get that case working in PySAM so that its results match SAM. Then you can identify the inputs to change in PySAM and change only those inputs.

For instructions, see the PySAM documentation: nrel-pysam.readthedocs.io

Note that PySAM has not been updated to match SAM 2023.12.17 yet, so you should continue to work with SAM 2022.11.21 for this purpose until PySAM is updated.

Best regards,
Paul.

Thank you, I will try and identify only the inputs that need to change.

I tried using the Beta link to try self-consumption, but it had expired. Is there a revised link ?

So to use self-consumption I guess I would need to use a different battery_dispatch_choice if i use pvsam1 once pySAM gets that capability.

It is a bit unclear what battery_targer_power means. Its set to all 1s for the hourly values when I exported the pySAM json.

Hi Sunil,

We just released SAM 2023.12.17 that includes the new battery dispatch option for self-consumption.

The battery_target_power input only applies with the "input battery power targets" battery dispatch option. For this option, you provide the target battery power (negative to charge the battery, positive to discharge) in each time step and the model attempts to operate the battery according to the target power values.

Best regards,
Paul.

Has a new version of pySaM released that is compatible with the latest desktop version ?

thanks

Hi Sunil,

Yes. PySAM Version 5 goes with SAM 2023.12.17:

nrel-pysam.readthedocs.io/en/main/versions.html

github.com/NREL/pysam/releases

Best regards,
Paul.