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Doc# E151701 12-8
12: Meter Calculations
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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 Nexus® 1262/1272 mimics tradi-
tional 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 Nexus® 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 Nexus® 1250/1252 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 subinter-
vals 12:00-12:05 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
Содержание Nexus 1262
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