Tony wrote:
cjt wrote:
Ed Pawlowski wrote:

"Art Todesco" wrote

http://www.nordyne.com/literature/8569%20Compr.pdf
The best would be to compare the electric meter with the unit
running and not running. This way you will have actual watt-hours
and you don't have to think of things like power factor, etc. But,
it will change depending on temperature. And the run time will vary
when the temperatures are cooler than when it is just plain hot
outside.

Many electric bills give a 13 month use history. Mine even gives the
average temperature for the month. Look at months like April and
October when neither heat or AC is used much and compare to July and
August and you get a pretty good idea. Aside from that, the only
accurate method is a recording ammeter over time.



I think you mean a recording watt-meter. Amps don't account for power
factor.

Another question maybe you can help? If I buy a clamp on type ammeter
that plugs into my DMM to display the current... if my DMM measures AC
with true RMS, will that fix the problem of the power factor?

No. Power factor arises from the phase relationship between the voltage
and current. For purely resistive loads, they are in phase and the
power factor is one. For reactive loads, they are not in phase. It's
not a question of RMS vs something else.

BTW, if you're willing to try something a bit more interesting, you can
measure total daily power use and minutes your A/C is on each day over a
period of time. Plot the two against each other and fit a line to the
data using a least-squares fit. Done correctly (including scaling
minutes to hours, making the correct choice of axes, etc.), the slope
will be A/C watts and the intercept will be your background use (i.e.
the average energy consumed by the rest of your appliances) within a
margin of error that you might even be able to quantify statistically
(although if your background use varies too dramatically or is
correlated to A/C use, the analysis might fall apart or at least become
difficult). The longer the time period you incorporate in your analysis
(within reason -- you don't want seasonal changes in efficiency, etc. to
get involved), the more accurate you can be.

:-)