Download EPM 9900 Electronic Meter Chapter 1

CHAPTER 2: OVERVIEW AND SPECIFICATIONS
Rolling (Sliding) Window Demand:
Rolling Window Demand functions like multiple overlapping Block Window Demands. The
programmable settings provided are the number and length of demand subintervals. At
every subinterval, an average (arithmetic mean) of power readings over the subinterval is
internally calculated. This new subinterval average is then averaged (arithmetic mean),
with as many previous subinterval averages as programmed, to produce the Rolling
Window Demand.
Example: With settings of 3 five-minute subintervals, subinterval averages are
computed every 5 minutes (12:00, 12:05, 12:15, etc.) for power readings over the previous
five-minute interval (11:55-12:00, 12:00-12:05, 12:05-12:10, 12:10-12:15, etc.). Further,
every 5 minutes, the subinterval averages are averaged in groups of 3 (12:00. 12:05, 12:10,
12:15. etc.) to produce a fifteen (5x3) minute average every 5 minutes (rolling (sliding) every
5 minutes) (11:55-12:10, 12:00-12:15, etc.).
Thermal Demand:
Traditional analog Watt-hour (Wh) meters use heat-sensitive elements to measure
temperature rises produced by an increase in current flowing through the meter. A pointer
moves in proportion to the temperature change, providing a record of demand. The
pointer remains at peak level until a subsequent increase in demand moves it again, or
until it is manually reset. The EPM 9900 meter mimics traditional meters to provide
Thermal Demand readings.
Each second, as a new power level is computed, a recurrence relation formula is applied.
This formula recomputes the thermal demand by averaging a small portion of the new
power value with a large portion of the previous thermal demand value. The proportioning
of new to previous is programmable, set by an averaging interval. The averaging interval
represents a 90% change in thermal demand to a step change in power.
Predictive Window Demand:
Predictive Window Demand enables the user to forecast average demand for future time
intervals. The EPM 9900 meter uses the delta rate of change of a Rolling Window Demand
interval to predict average demand for an approaching time period. The user can set a
relay or alarm to signal when the Predictive Window reaches a specific level, thereby
avoiding unacceptable demand levels. The EPM 9900 calculates Predictive Window
Demand using the following formula.
Example:
Using the previous settings of 3 five-minute intervals and a new setting of 120% prediction
factor, the working of the Predictive Window Demand could be described as follows:
At 12:10, we have the average of the subintervals from 11:55-12:00, 12:00-12:05 and
12:05-12:10. In five minutes (12:15), we will have an average of the subintervals 12:0012:05 and 12:05-12:10 (which we know) and 12:10-12:15 (which we do not yet know). As a
guess, we will use the last subinterval (12:05-12:10) as an approximation for the next
subinterval (12:10-12:15). As a further refinement, we will assume that the next subinterval
might have a higher average (120%) than the last subinterval. As we progress into the
subinterval, (for example, up to 12:11), the Predictive Window Demand will be the average
of the first two subintervals (12:00-12:05, 12:05-12:10), the actual values of the current
subinterval (12:10-12:11) and the prediction for the remainder of the subinterval, 4/5 of the
120% of the 12:05-12:10 subinterval.
2–8
EPM 9900 MULTI-FUNCTION POWER METERING SYSTEM – USER GUIDE