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Green Building Bible, Fourth Edition
Green Building Bible, fourth edition (both books)
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      CommentAuthorSteamyTea
    • CommentTimeAug 14th 2012 edited
     
    This is a follow on from a previous discussion. http://www.greenbuildingforum.co.uk/forum114/comments.php?DiscussionID=9445&page=1#Comment_153976
    Thoughts are needed as to how this could be done.
    •  
      CommentAuthorSteamyTea
    • CommentTimeAug 14th 2012
     
    As HDDs use the modal value above or below a reference value, should we use the modal windspeed and solar radiation figures for the UK or should it be more regional as the baseline?
    •  
      CommentAuthorDamonHD
    • CommentTimeAug 14th 2012
     
    Might do it on the basis of the number of sigmas or km/h over the (known imperfect) km-squares data? But I'd claim that as with temperature each building would have to find its own baseline rather than a regional or national value necessarily making sense.

    Rgds

    Damon
    •  
      CommentAuthorSteamyTea
    • CommentTimeAug 14th 2012 edited
     
    I know what your getting at about the buildings being different and this may cause a problem as for each building to be the same, they would have to be the same and if they are not, would that not just cause a positive or negative offset?
    So if your house has HDDs of 12 °C and most people use 15.5 °C but your internal temp is 16.5 °C rather than 20 °C, does that not amount to the same thing? Those iButton should show what your modal temp is as they have a histogram built in.
    • CommentAuthorskyewright
    • CommentTimeAug 14th 2012
     
    Posted By: SteamyTeaAs HDDs use the modal value above or below a reference value

    Unless I'm misunderstanding something (which is quite possible) modal values are not what people like the Met Office and Degree Days.net use?
    http://www.degreedays.net/calculation
    • CommentAuthorskyewright
    • CommentTimeAug 14th 2012
     
    Posted By: DamonHDBut I'd claim that as with temperature each building would have to find its own baseline rather than a regional or national value necessarily making sense.

    baseline and data sourses aside, my understanding is that the aim of the topic is to come up with a way of incorporating wind &/or solar data into a HDD calculation to give a meaningful figures than can then be used for further analysis.

    Any thoughts on that?

    Might one of the Wind Chill calculations offer a starting point?
    http://en.wikipedia.org/wiki/Wind_chill
    •  
      CommentAuthorSteamyTea
    • CommentTimeAug 14th 2012
     
    Well I have just had a look at windspeed and Air Temp down here, seems the faster the windspeed the less temperature varies.
    But is just one month in one year. Shall have a look at more later.

    HDDs can be calculated using any average I shoudl think, each will have a limitation.
    One advantage of using the mode is that it gets rid of the outliers right from the start and does, to a certain extend, take time into account (though that has to be checked as you may have 98 different readings and 2 the same). I shall ponder it at work later.
    • CommentAuthorskyewright
    • CommentTimeAug 14th 2012 edited
     
    Posted By: SteamyTeaHDDs can be calculated using any average I shoudl think, each will have a limitation.

    Can't say fairer than that. :bigsmile:

    Posted By: SteamyTeaOne advantage of using the mode is that it gets rid of the outliers right from the start

    Oddly perhaps the "classic" method seems to use the outliers as the basis for the calculation, i.e. it uses an average based on (max + min) / 2! Presumably that's because the 'logging device' used to be a max-min thermometer? Almost anything else is probably an improvement on that approach?

    As I'm recording the data on a real computer I ought to be able to manage the "integration approach" (i.e. a sum of many part days). The integration approach might be especially appropriate where the sun is involved as it would automatically cover the day/night problem?

    There seem to be many variations on "Feels like" or "Apparent" temperatures. Here's one that is used in Australia with variants for both temperature, humidity, and wind and temperature, humidity, wind and radiation.
    http://www.bom.gov.au/info/thermal_stress/#atapproximation
    Worth noting however that that index is designed to give an idea of how a human stood outdoors feels, whereas we want to use if for a building.
    •  
      CommentAuthorSteamyTea
    • CommentTimeAug 15th 2012
     
    One thing to try and work around is that wind direction generally affects the amount of cloud cover, may be a bit different for us on the west coast, but then we are extremes. Then there is the effect of different building materials when subjected to solar radiation, glass and brick behave different from slate and timber.
    A statistical approach can be taken to this i.e. what is the power in the sun for any given wind direction and what is the windspeed for any given wind direction, then plot the results against each other (could do any combination of bases, windspeed, direction, sun power).
    I only have one internal dataset of internal temperature measurements (kitchen that faces north east), so any correlations would have to take that into account, easy enough to do as I can work out when the sun stops falling on the back wall (before noon). Also as this is in the lee of the prevailing wind, that would have to be taken into account.
    Summer figures (non heating season anyway) are quite useful as they show what the weather is actually doing to the house i.e. temperature rise/fall.
    As solar effects do not extend into night time, but air temperature, windspeed and direction do, it may be worth splitting the datasets into two, day and night (though a reference to how clear the day was may be useful as it may show a more rapid decline in night time temperature).

    Not sure if the datasets should be done at the daily, weekly or monthly level, or if they should be presented as absolute or relative values. If relative values then what should the 'zero' value be, the daily, weekly or monthly value (and should it be mean, mode or median, or a time, say solar noon).
    Just some thoughts so far.
    •  
      CommentAuthorSteamyTea
    • CommentTimeAug 17th 2012 edited
     
    Right, had a little play with July's data and have charted wind direction, wind speed and solar power.
    Wind Direction is a fraction of the datapoint count (bottom x axis), Wind speed and Solar are decimal fraction above or below the months mean.
    Not had time to do any stats tests on the data yet as I am going to try and do the air temperature (external and internal) next.
    What it does show is that it is calm a lot more than I imagined and it is not very sunny when calm. There seems to be a correlation between wind direction and solar power, the more northerly the wind (in July) the sunnier it is.
    Bear in mind that the first chart shows solar for the who period, so takes night time into account and that lowers the mean.

    The charts:
    •  
      CommentAuthorSteamyTea
    • CommentTimeAug 17th 2012
     
    Right, had a look at temperature now, Day is warmer than night, and the reason that the All Temperatures (red bar) is higher than the mid point between the Day and Night is because of the longer days (this will be tested when more months are showing.
    Now to sort out the house temperatures.

    The Chart.
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