Metabolic heat gains #24
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Currently the load per appliance is calculated for each person and just added together. This means that for example for the fridge the load is added multiple times. The load for the fridge will therefore be overestimated. To allow for sharing: the load calculation in 'residential.py' is adapted for each type of appliance. An extra function was added in 'stats.py'.
Currently the load per appliance is calculated for each person and just added together. But this means that for example for the fridge the load is added multiple times. This does not represent the reality. Changes are made in residential.py and stats.py. In residential.py the load of appliances is calculated based on the type of appliance (shared or not, and continuously used or not). For this an extra function was added in stats.py.
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IDEAS already includes models for getting the metabolic heat gain, latent heat, etc. Therefore it might be interesting to output the number of occupants, rather than computing the heat gain. The number of occupants can then be input into the zone model. |
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I think it would be useful to have this, even if only optional, since it has some advantages:
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| x = [0.8, 1.25] | ||
| f = [70,110] | ||
| sleep = np.interp(met_sl, x, f) | ||
| active = np.interp(met_act, x, f) |
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Could you add an explanation? My understanding is that x is the metabolic rate in Met units, and then you use this interpolation to go to heat in Watts given in f, based on the assumption of linear relation between the two (0.8Met->70W, 1.25Met->110W). Is this the case?
Then I'm concerned that np.interp gives a fixed value outside the given range, such that for 2Met we still get 110W. Or am I mistaken? Maybe the range could be expanded to cover all cases, or if the relation is not linear (I don't really know), add more points.
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Your explanation is correct. I assumed the np.interp makes an interpolation as well outside the given range. But I did not check that. I went back to some previous result files and in fact I did not find any metabolic loads higher than 110 W. Will it be solved if we just expand the range?
| tl = -1 # time counter for minutes | ||
| # the heat a person produces is dependent on the metabolism | ||
| met_sl = random.gauss(0.8,0.05) # metabolism when sleeping | ||
| met_act = random.gauss(2,0.1) # metabolism when active |
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Is the range for active occupants purposely chosen to be so narrow? I understand that the Met could vary much more, but is the idea here to keep an average value, because it will be used constantly throughout the year?
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it is based on this data I received from Jelle. So actually the active metabolism considered here is for activities in the kitchen. I think it is indeed good to widen the range for active metabolism
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the most optimal would be if we link the metabolic gains with the specific activities, however, this is not that simple as the activities are only used for the appliance use and are not 'fixed profiles' in the same way as the occupancy.
In the original model the heat gains by persons are not included. Metabolic heat gains can be easily incorporated in the model since it is known when each occupant is active, asleep or away. The heat gains are calculated based on the metabolism of the occupant depending on the state of occupancy.