Just an update on the Green Star daylighting credit. In my longer post above I referred to the Green Star - Design and As-Built v1.3 tool. Note that this rating tool has been superseded by the new Green Star Buildings v1 tool released 29/10/20, but projects can still be registered under the old tool until 17 December, 2021.
Sorry that I didn’t figure this out sooner but at the time I was working on a project under the old tool and am now working on one under the new tool…
In the new tool, high Levels of daylight are still deemed to have at least 160 lux due to daylight during 80% of the nominated hours.
However, they now make the following differentiation between space types:
For non-residential buildings, at least 40% of the principle area averaged across the building must receive high levels of daylight with no less than 20% on any floor or tenancy (whichever is smaller).
For residential buildings, 60% of the combined living and bedroom area of each apartment unit must comply with the daylight requirements. Kitchens are not included in the calculations. The daylight levels must also be present in at least 20% of the area of each bedroom and living area.
It will get complicated to account for how they want us to assess daylighting on a per-floor basis (or even per-tenancy), so I suggest that the recipe should just assess each point in the analysis mesh (using the threshold according to its space type) and let the user do the accounting of overall % compliance and Green Star points.
Essentially, I don’t think this changes anything about what we were planning to do anyway.
I think I can help with this but I sense that I might be missing something since, especially from your last post, it sounds like what you want is effectively what comes out of the Annual Daylight recipe + a native GH conditional statement. Am I right that you plan to take care of the hard part of defining the nominated area with sensor grids and the nominated time period with a schedule? And you also want to take care of the hard part of the calculation of floor area percentages from the pass/fail results? If so, why not just use the current recipe like so:
Green_Star_Annual_Daylight.gh (50.0 KB)
(note that I’m using the latest development version of the LBT plugin in the attached file)
I guess we could integrate the native GH conditional statement into a recipe that is specifically for Green Star and also set the default illuminance thresholds to be consistent with Green Star but these simple tweaks don’t seem like they are quite enough to merit a whole new recipe yet. If you wanted the recipe to take care of one of the “hard parts” that I listed above, then I could see the merit of adding a whole new recipe that is specifically Green Star. We could easily do the whole calculation of the passing floor area percentage with a DA above 80% using the mesh included with the sensor grids. You can also assign rooms to different stories using the “HB Set Story” component and we can try to evaluate the “no less than 20% on any floor or tenancy.”
Just let us know what would be most helpful and I am happy to assit.
Hey @chris, I think you’re right! I was probably overthinking things a bit…my initial hope was to get the recipe to take care of all the hard parts and output the overall number of Green Star points, but that might be overkill.
I wasn’t aware of the “HB Set Story” component! How about for my current project I try working with that, and get back to you if it becomes apparent that this warrants it’s own recipe? Thanks so much for your responses so far.
Sounds good. Just let us know if you think that using the “HB Set Story” component could allow you to group the different Rooms into floors/tenancy and I can write a post-processing function to report the percentage of each story in the output (assuming the sensor grids have room identifiers).
Alternatively (or additionally), we could give a grid-by-grid report of the percentage of the area meeting the criteria, which could allow you to easily assess whether the “bedrooms and living area” requirements for residential are being met. I guess you could also model each story as its own sensor grid if you wanted to use the same methods for nonresidential and maybe that would be simpler.
Once we know how we would want to structure the model, it shouldn’t take more than a couple of days to put together a recipe that does the postprocessing.
Thank you for your patience and sorry for the delay.