<div dir="ltr">Just a thought - You might want to give one of the auto calibration tools a spin for this one and see what parameter values it comes up with.<div>-Rohini<br><div><br></div></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Aug 27, 2015 at 2:44 PM, Chris Yates <span dir="ltr"><<a href="mailto:chris.malcolm.yates@gmail.com" target="_blank">chris.malcolm.yates@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div bgcolor="#FFFFFF" text="#000000">
Dear all,<br>
<br>
I have monthly gas data for a soccer stadium and I'm trying to
develop it toward daily (or even hourly) data so this can be used in
subsequent assessments.<br>
<br>
My own efforts on previous assessments have extended to relatively
crude application of multipliers (possibly based on a simulation
study) and an overall divisor. This is very limited, especially in
this case.<br>
<br>
In an ideal world, it would be helpful to develop the daily
consumption weighted with the following factors:<br>
<ul>
<li>Parasitic losses - these can be estimated from when the
facility is largely closed during the off season</li>
<li>Historic game fixtures - readily available from the web</li>
<li>Weather, including about 1MW of underpitch heating</li>
</ul>
<p>I'm surrendered to the possibility that this is well beyond me!
But, can anybody suggest excel functions or other software tools
they may have used, or even what math for me to look up on Google?
<br>
</p>
<p>Many thanks <br><span class="HOEnZb"><font color="#888888">
</font></span></p><span class="HOEnZb"><font color="#888888">
<p>Chris<br>
</p>
</font></span></div>
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