Automatic utility usage rate analysis methodology

• US 20090006279A1
• Filed: 06/29/2007
• Published: 01/01/2009
• Est. Priority Date: 06/29/2007
• Status: Active Grant

• Current Assignee: Square D Company (Schneider Electric SE)
• Original Assignee: Square D Company (Schneider Electric SE)
• Inventors: Buettner, William L., Austin, Stephen B.
• Granted Patent: US 7,684,901 B2
• Time in Patent Office: Days
• US Class Current: 705/412
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 3/00 Circuit arrangements for ac mains or ac distribution networks
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: Y04S 10/50 Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

An automatic method of which days/hours represent good candidates for reducing demand to achieve potential savings and the amount of demand reduction that can be achieved with a tolerable level of disruption to status quo operations. Demand interval data including utility usage rate (UUR) values is received from one or more utility monitoring devices, and are sorted in descending order. A percent difference is calculated for each UUR value relative to the previous one, and a cumulative percent difference accumulates the percent differences from the preceding rows. The average cumulative percent difference is divided by the total number of UUR values in the measured period to produce a ratio. The standard deviation of time is determined, and from those demand data associated with ratios greater than a ratio threshold and standard deviations less than a standard deviation threshold the demand reduction amount and the number of control hours are determined.

Claims

1. A method of automatically identifying candidates for reducing demand, comprising:

receiving, over a measured period, demand interval data collected by at least one utility monitoring device, the demand interval data including a number of utility usage rate values and associated dates and times;

sorting the utility usage rate values in descending order to produce sorted utility usage rate values and storing the sorted utility usage rate values in rows of a table;

for each of the rows, calculating a percent difference as a function of the sorted utility usage rate value and the previous sorted utility usage rate value in the table;

for each of the rows, summing previous percent difference values to produce a cumulative percent difference;

for each of the rows, dividing the average cumulative percent difference across the previous rows by the total number of utility usage rate values in the measured period to produce a ratio;

determining the largest row number whose associated ratio is less than a ratio threshold;

for at least each of the rows up to the largest row, calculating a standard deviation of time as a function of the times associated with the utility usage rate values;

determining the row number whose associated standard deviation of time is less than a standard deviation threshold to produce a number of intervals of control; and

storing in the memory data representative of the number of intervals of control and representative of the cumulative percent difference associated with the row number corresponding to the number of intervals of control.

2. The method of claim 1, further comprising, based on at least the rows up to the row number corresponding to the number of intervals of control, determining at least a time during which demand reduction will decrease overall peak demand during the measured period.

3. The method of claim 2, further comprising, based on at least the rows up to the row number corresponding to the number of intervals of control, determining at least a day during which demand reduction will decrease overall peak demand during the measured period.

4. The method of claim 3, further comprising, based on at least the rows up to the row number corresponding to the number of intervals of control, determining whether there exists any consecutive intervals of time during which demand reduction will decrease overall peak demand during the measured period.

5. The method of claim 1, further comprising displaying the data on a video display.

6. The method of claim 1, wherein the receiving includes reading the demand interval data from a file.

7. The method of claim 1, wherein the receiving includes querying the demand interval data from a database coupled to the at least one utility monitoring device.

8. The method of claim 1, further comprising calculating a savings amount from the data representative of the cumulative percent difference associated with the row number corresponding to the number of intervals of control, and displaying the savings amount.

9. The method of claim 1, further comprising plotting the ratio against at least some of the rows to produce a slope plot and displaying the slope plot.

10. The method of claim 1, further comprising plotting the standard deviation of time against at least some of the rows to produce a standard deviation plot and displaying the standard deviation plot.

11. The method of claim 1, wherein the ratio threshold is at least 10.

12. The method of claim 1, wherein the standard deviation threshold is no less than 1.5.

13. The method of claim 11, wherein the ratio threshold is no less than 10.

14. The method of claim 12, wherein the standard deviation threshold is at least 1.5.

15. The method of claim 1, wherein the ratio threshold is 10 and the standard deviation threshold is 1.5.

16. The method of claim 1, wherein the utility usage rate is kilowatts.

17. The method of claim 1, wherein the utility usage rate is gallons per unit time.

18. The method of claim 1, wherein the utility usage rate is therms per unit time.

19. The method of claim 1, wherein the utility usage rate is pounds per unit time.

20. The method of claim 1, wherein the utility usage rate is a hundred cubic feet (CCF) per unit time.