Bo, thanks. I will look more into applying a FFT. I see we have some
articles on it - http://code.jsoftware.com/wiki/Guides/Fourier_Transform -
I just need to study how to apply it. Thanks for the tip

On Fri, Aug 26, 2016 at 2:37 AM, 'Bo Jacoby' via Programming <
[email protected]> wrote:

> Hi!
> When you have got positive numbers only, then first take the logarithm,
> because whatever calculation you make you never want negative values. Next
> multiply by 100 because the accuracy of the measurements is around 1
> percent. Next round to integer values because the fractional part is
> uninteresting.
> ([:<.[:100&*^.)
>
> Then make a discrete fourier transform to get a power spectrum. Low
> frequency peaks tell the base load. High frequency peaks tell how often the
> air conditioner turns on.
> Good luck!
> Bo.
>
>
>
>     Den 7:20 fredag den 26. august 2016 skrev dhkelly <[email protected]>:
>
>
>
>  I would suggest that you could get away with samples taken at longer
> intervals. You won't lose useful information as none of the major
> appliances including the air conditioner should draw a startup peak
> power for over  6 seconds and what you really need is the increase in
> load over a longer time. In addition, the air conditioner is a motor
> load which has a lower power factor than something dominated by a heater
> element.
>
> A change  between two readings  at the interval you are using or an
> interval of the order of 60 seconds (or longer)  will essentially give
> the same information -something changed in the interval- whatever it
> is.  Determining whatever is a bit more iffy. If you get large jumps at
> 2AM- blame the air conditioner. If at 8AM it could be stove and/or water
> heater (breakfast and shower) indicating that you got up then.
> The trouble with a whole house monitor, is that a measure of changes in
> power alone, may not really give you all the data to distinguish
> sources. Another is that a high sampling rate may give variations that
> are really not of interest.  I think that a step would be to correlate
> the data with your direct observations of what went on or off - when(
> i.e at the time you turned on a major load such as a stove or dryer-
> both of which will cycle their power levels "on/off"  in the same way
> that an air-conditioner does.
> (e.g. an oven will turn on until the desired temperature is reached,
> then turn off , repeating this cycle to maintain a a given temperature
> (+/- a bit) just as an air conditioner or dryer does).
>
> Don Kelly
>
>
>
> Does the meter also measure power factor or "vars"?
>
>
>
> On 8/25/2016 8:05 PM, Joe Bogner wrote:
> > I posted an article that looks at some data I captured using a whole-home
> > energy monitor. I also posted the data.  I put up a challenge for anyone
> > who wants to take a stab at it.
> >
> > http://code.jsoftware.com/wiki/User:Joe_Bogner/EnergyUsageAnalysis
> >
> > How often does the air conditioner or clothes dryer turn on?
> > How long does it normally run, when did it run the longest?
> > Is it possible to determine when I go to bed or wake up?
> >
> > I'd be interested in any approaches to answering any of these questions
> or
> > other analysis on the data
> >
> > For example, the air conditioner draws a significant amount of energy.  I
> > just turned it on and my usage went from 1460-6000 watts.
> >
> > Looking at the change in prior reading may be a good start
> >
> > plot (}. reading - (_1 |.!.0 reading))
> >
> > I have an electric dryer and electric oven.
> >
> > I hope the data and article is interesting/useful
> > ----------------------------------------------------------------------
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>
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