Hello SAM team,
First of all, thanks for implementing the cost optimization approach for battery dispatch in the latest release. However, I am facing some significant slowdown using this feature and I am wondering if there is something unexpected going on and if there are any ways to mitigate this (even at the expense of optimization quality).
Using the SAM app, the simulation takes about ten times longer using price signal forecasting. I also tried this with PySAM (batt_dispatch_choice=5) the performance hit there is about 7 times. Is this a know issue or is there something about my setup that could be causing this? If it is known, is there any configuration available to speed it up, even if the model is simplified?
Thank you
These are the simulation times I get on an out-of-the-box PV-Battery Residential model.
With Peak-Shaving Look Ahead Dispatch:
Simulation report
Total time: 12729 msSSC time: 12586 msSSC version: 250 (OS X 64 bit GNU/C++ Nov 29 2020 03:26:17)Models (5): belpe pvsamv1 grid utilityrate5 cashloan
With Price Signal Forecast:
Simulation report
Total time: 136044 msSSC time: 135899 msSSC version: 250 (OS X 64 bit GNU/C++ Nov 29 2020 03:26:17)Models (5): belpe pvsamv1 grid utilityrate5 cashloan