h Shading--DC to AC derate Factor--Photovoltaics Module, can calculate the ACenergy of different pv arrays by Galapagos. The process can evaluate the self shading from the input analysisGeometry and surrounding shading from the input context.
2. PV SWH Systemsize, can also do that, but there would be no second type of self shading for the chosen minimalSpacingPeriod_ criteria.
3. TOF outputs optimal angle and azimuth.
So my question is, if I choose to make a curved roof to form a best pv array with best ACenergy, whether should I only choose the first above, the second PV SWH Systemsize can only deal with the angled or flat surface, not the curved? What's the relationship between TOF and PV SWH Systemsize?
Also, I'll do my best to make a parametric model as soon as possible and upload it to you, so we can make the discussion more detailed.
Best regards.…
face, the larger the number of modules and system size, there for the higher annual energy generation.baseSurface_ - this input exists only for "PV SWH system size" component. It's purpose is to represent a mounting plane on which the PV modules will be put onto. The dark blue colored roof in the photo below is that mounting surface in this case:
So the size of area of the baseSurface_ is not important but its plane.
2) It is important. It basically sets the initial losses of the system.
If that is the soiling value you have, then yes, you need to add it to the DC to AC derate factor component, and then plug its output to "DCtoACderateFactor_" input. I did that in the attached definition below.
3) The north vector/numeric value is not propagated due to possible independent usage of components.I plugged the 0 value to all three component's which have "north_" input. You can change it to what ever value you need.
Please let me know if I didn't answer completely to your questions, or if you have more of them.…
an that HashCodes well ... since they are "unique" per item (even if this - for the one reason or the other - is created at the same location with that) I barely can see how one can use them in order to get rid if "equal" items (Lines in this occasion).
On the other hand ... well ... using HashSets sampling the Line center and testing length and direction ... well ... this works but why bother? > if you are not doing business with code (thus you need this "check" internally) > use the Kangaroo1 component.
That said the topic of "equality" is rather huge and most people are confusing a lot of things on that matter: for instance a point not equal to another ... well ... that's rather simple but a brep "not equal" with some else ... this is not that easy (if it's solvable).…
it seems that was this. Now all is working fine !
Glad that it worked! But I am still a bit worried. Gismo components only modify the gdal-data/osmconf.ini file and no other MapWinGIS file. So your MapWinGIS installation files should not be compromised. The fact that you did not get the "COM CLSID" error message when running the "Gismo Gismo" component suggests that MapWinGIS has been properly installed. So I wonder if the cause for the permanent "invalid shapes" warning has again something with the fact that your system is again not allowing the MapWinGIS to properly edit the osmconf.ini. Maybe this problem will appear again, and again, and reinstallation of MapWinGIS every time can be somewhat bothersome.
- About the terrain generation, is it possible to have the texture from google or other provider mapped onto the terrain surface from gismo component ? (Same as using the ladybug terrain generator in fact). I try to used the image extracted by ladybug component and then applied it to the gismo terrain but the texture is rotated by 90°.
The issue with the rotation can be solved by swapping/reversing the U,V directions of the terrain surface. A slightly more important issue is that terrain surface generated with Gismo "Terrain Generator" component might have a bit smaller radius than what the radius_ input required. This stems from the fact that the terrain data first needs to be downloaded in geographic coordinate system, and then projected. Some projecting issues may occur at the very edges of the projected terrain, so I had to slightly cut out the very edges of the terrain which results in the actual terrain diameters being slightly shorted in both directions. This means that if you apply the same satellite image from Ladybug "Terrain Generator" component to Gismo "Terrain Generator" component the results may not be the same.I attached below a python component which tries to solve this issue by extending the edges of Gismo "Terrain Generator" terrain, and then cutting them with the cuboid of the exact dimensions as the radius_ input. Have in mind that this extension of the original terrain at its edges is not a correct representation of the actual terrain in that location. But rather just an extension of the isoparameteric curve of the terrain surface. So basically: some 0 to 10% (0 to 10 percent of the width and length) of the terrain around all four edges is not the actual terrain for that location, but rather just its extension.The python component is located at the very right of the definition attached below.
Also, if you would like to use the satellite images from Ladybug "Terrain Generator" component along with "OSM shapes", sometimes you may find slight differences in position of the shapes. This is due to openstreetmap data not being based on Google Maps (that's what Ladybug "Terrain Generator" component is using), but rather on Bing, MapQuest and a few others.
- About the requiredKeys_ input of OSM shapes, I understand what you mean and your advice, but in most cases I use it, the component was working fine even without input. I think it's better to extract all tags, values and keys of the selected area, instead of searching for specific ones as I try to find all data related to what I want after, isn't it ? To check what keys are present on the area also.
Ineed, you are correct.I though you were trying to only create a terrain, 3d buildings and maybe find some school or similar 3d building, for these two locations. The recommendation I mentioned previously is due to shapefiles having a limit (2044) to how many keys it can contain. This requires further testing of some big cities locations with maybe larger radii, which I haven't performed due to my poor PC configuration. But in theory, I imagine that it may happen that a downloaded .osm file may have more than 2044 keys. In that case shapefile will only record 2044 of them, and disregard the others. That was my point.But again 2044 is a lot of keys, and I haven't been checking much this in practice. For example, when I set the radius_ to 1000 meters, and use your "3 Rue de Bretonvilliers Paris" location I get around 350 something keys, which is way below the 2044.Another reason why one should use the requiredKeys_ input is to make the Gismo OSM components run quicker: for example, the upper mentioned 350 something keys will result in 350 values for each branch of the "OSM shapes" component's "values" output.Which means if you have 10 000 shapes, the "OSM shapes" component will have 10 000 branches with 350 items on each branch (values). This can make all Gismo OSM components very heavy, and significantly elongate the calculation process.With requiredKeys_ input you may end up with only a couple of tens of items per each branch.Sorry for the long reply.…
Added by djordje to Gismo at 8:57am on June 11, 2017
(twice the amount of lines, it'll take twice as long).
If you nest two loops you're iterating over each line, and then you iterate again over each line. So when you now have twice as many lines, it takes four times as long O(N*N) or O(N²)
With an octree you can reduce the second iteration from O(N) to O(log N). The reason octrees are fast is because they allow you to quickly reject large amounts of lines in your set. Lines are no longer stored in a list, but rather in recursive spatial buckets. If we determine that a certain bucket is too far away to possibly yield any valid results, we can instantly skip all the lines in that buckets and any sub-buckets. If you're lucky, you can reject ~85% of the local data in every iteration, which means even large collections of lines are reduced to only a few potential candidates very quickly.
Thinking about this I'm actually not sure now whether lookup in my Tree3d class is O(log N) or O(sqrt N), but the basic principle holds. The reason the resulting algorithm is O(N * log N) is because the outer loop is still O(N) but the inner loop is now replaced with an O(log N) searcher, so you end up with O(N) * O(log N) = O(N log N)
At least that's how I think it works, computational theory has never been my strong suit.
--
David Rutten
david@mcneel.com
Poprad, Slovakia…
Added by David Rutten at 4:55pm on November 29, 2012
try now to integrate Geco in an interdisciplinary architectural engineering studio: hoping we can show you some nice applications of your tool, I'll keep you update and sending now details by e-mail. Here the file (very welcome to be shared). It most probably contais trivial errors by me, thanks for helping and giving some tip! Gr. Michela
FILE:
Ok, right, I see the outputs update correctly. Origin of problems must be in some different mistake I do:
- Incident radiation: I am not sure I understand what is going on: why I get so many 'not a number' ? (The Galapagos report is full of NaNs).
Bio-Diversity: 0.887 Genome[0], Fitness=NaN, Genes [89% · 44%] { Record: Too many fitness values supplied } ...
Genome[7], Fitness=NaN, Genes [74%] { Record: No fitness value was supplied } ....
Genome[9], Fitness=NaN, Genes [37% · 11%] { Record: Genome was mutated to avoid collision Record: Too many fitness values supplied }
- Daylight calculations: the geometry accumulates withouth deleting the previous models. As a consequance, results almost do not change after few varations (so, outputs get updated but do not vary). In current daylight definition: the first object being imported is the one where the grid has to fit; its setting makes it cancelling all the other objects during import. All the others, do not delete anything when imported. When running loops (manual or GA) that vary parameters, the entire geometry do not get cancelled - so I guess the loop does not pass back by the cancelling step, but imports only the geometry which has been varied by the parameters using the setting of that import component only? I will then try again by changing the order of the operations, but if you have specfic tips, let me know.
THANKS!
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