2.46.00: Major Improvements to the refrigerants and PV modules

This release brings significant improvements to our Solar PV and Refrigerants modeling capabilities, offering users more granular control and precision in both areas. These updates are the culmination of our planned feature set for these modules, providing a more comprehensive and flexible approach to modeling their impacts 🎊

Solar PV Improvements

We've completely revamped how solar panels are specified in the API, moving from smart defaults to direct panel descriptions:

Added direct control over panel orientation with new tilt and azimuth parameters.
Replaced the obfuscatory
efficiency_metric
with a more direct and intuitive description of the panel
Simplified the model by removing an ambiguous orientation parameter, replacing it with a clearer
losses
parameter that uses our standard proportion format (0-1 range).

These changes allow for more accurate modeling of solar energy production across different panel configurations and installation scenarios.

Refrigerants Improvements

We've completely redesigned our refrigerants modeling to support both simplified and detailed approaches:

Simple Schema
: For users who need quick estimates, our updated simple schema makes intelligent assumptions about refrigerant charge and uses average GWP values based on building type.
Detailed Schema
: For users requiring precision, we've added a comprehensive refrigerants_present parameter that allows you to specify multiple refrigerant types from our expanded library, declaring a charge and leakage parameters for each.

This dual approach ensures that both casual users and detailed modelers have access to refrigerant emissions calculations at their preferred level of precision.

Backend Improvements

We've also made several improvements to our backend systems:

Refactored our time series calculation methods for better performance
Migrated reference data lookups to more performant data structures
Improved performance of our
interiors
takeoff engine, which had created some drag on overall response times in some circumstances

Regression

There is a regression in the calculation of panel area as we have re-set our default

ground_coverage_ratio

from 0.7 to 0.6 and upgraded our default panel capacity from 250W to 300W, reflective of user feedback about typical installations.