Method and System for Forecasting Power Requirements Using Granular Metrics

• US 20140336960A1
• Filed: 05/28/2014
• Published: 11/13/2014
• Est. Priority Date: 11/29/2011
• Status: Active Grant

• Current Assignee: Generac Power Systems Incorporated (Generac Holdings Incorporated)
• Original Assignee: Energy Process Technologies Incorporated (Energy Process Tech)
• Inventors: HAGHIGHAT-KASHANI, Ali, CHEAM, Janice Tze-Nee, HALLAM, Jonathan Mark, GUO, Zhenyu
• Granted Patent: US 9,366,704 B2
• Time in Patent Office: Days
• US Class Current: 702/60
• CPC Class Codes: G01R 21/133 by using digital technique
• CPC Class Codes: G06F 16/212 with details for data modelling support
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 13/00002 characterised by monitoring
• CPC Class Codes: H02J 13/00016 using a wired telecommunication network or a data transmission bus
• CPC Class Codes: H02J 13/00026 involving a local wireless network, e.g. Wi-Fi, ZigBee or Bluetooth
• CPC Class Codes: H02J 13/00028 involving the use of Internet protocols
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 10/30 State monitoring, e.g. fault, temperature monitoring, insulator monitoring, corona discharge
• 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
• CPC Class Codes: Y04S 40/124 using wired telecommunication networks or data transmission busses
• CPC Class Codes: Y04S 40/126 using wireless data transmission

Abstract

A method for modeling power usage within a macrogrid uses data relating to the behavioral patterns and states (“BA”) of the users, data relating to external impacts on power usage and disaggregated power consumption data in at least one premises within the macrogrid (forming “power usage model data”) and thereafter a method of forecasting and predicting future power requirements within the macrogrid uses such power usage model data.

Claims

1. A computer implemented method of modeling power usage within a macrogrid, the macrogrid being within a region, the method comprising:

a) obtaining disaggregated power consumption data in at least one premise within the macrogrid to determine at least one behavioral pattern according to usage behaviors for at least one appliance or device within the macrogrid;

b) obtaining data relating to the at least one behavioral pattern and a state of a user;

c) obtaining data relating to at least one external impact on power usage;

d) using the obtained data from one or more of a) to c) to create an individual consumer forecast of power usage, said consumer forecast being collectively aggregated across a plurality of users;

e) using data from one or more of a) to d) to perform a demographic analysis;

f) collecting macrogrid aggregate power consumption data for the region;

g) determining power consumption requirements across the macrogrid for the region using data from at least one of a) to e); and

h) determining future power requirements within the macrogrid, using the data obtained in at least one of a) to g).

2. The method of claim 1 wherein the determining power requirements is performed for at least one the following:

decreasing and tracking consumer usage of the power resource, decreasing consumer costs for power, maximizing revenue for the power provider, minimizing consumer discomfort, and identifying future peak usage times and requirements.

3. The method of claim 1 wherein appliance is any consumer of power within a premise.

4. A computer implemented method of modeling power usage within a macrogrid the method comprising:

a) periodically receiving granular power consumption data from a statistically significant portion of a target population of power users within the macrogrid for a region;

b) using the power consumption data to perform a consumer load disaggregation to determine usage behaviors for at least one appliance or device;

c) obtaining data relating to at least one behavioral pattern and a state of a user;

d) obtaining data relating to external impacts on power usage;

e) using obtained data from at least one of a) to d) to generate an individual consumer forecast of power usage, the consumer forecast being collectively aggregated across a plurality of users;

f) using data from one or more of a) to e) to perform a demographic analysis;

g) collecting aggregate power consumption data for a region associated with the macrogrid;

h) determining power consumption requirements across the macrogrid for the region using data from at least one of more of a) to g); and

i) determining future power requirements within the macrogrid, using the data obtained in at least one of a) to h).

5. The method of claim 4 wherein periodically comprises receiving data within a five minute interval or less.

6. The method of claim 4 wherein periodically comprises receiving data within a one hour interval or less.

7. The method of claim 4 wherein the determining power requirements is performed for at least one the following:

decreasing and tracking consumer usage of the power resource, decreasing consumer costs for power, maximizing revenue for the power provider, minimizing consumer discomfort, and identifying future peak usage times and requirements.

8. The method of claim 5 wherein external impacts are selected from any one of:

weather patterns and predictions, calendar month, economic indicators, world events, television programming, equipment age and maintenance, and population mobility.

9. The method of claim 5 wherein the at least one behavioral pattern comprises data related to user behavioral states selected from one or more of the following states:

sleeping, just awoken, on vacation, working from home, charging electric vehicles, and extended absence.

10. A system for modeling power usage within a macrogrid for determining future power requirements within the macrogrid, the system comprising a server and one or more databases, the server comprising a processor and memory, the memory comprising computer executable instructions for:

a) obtaining disaggregated power consumption data in at least one premise within the macrogrid to determine at least one behavioral pattern according to usage behaviors for at least one appliance or device within the macrogrid;

b) obtaining data relating to the at least one behavioral pattern and a state of a user;

c) obtaining data relating to at least one external impact on power usage;

d) using the obtained data from one or more of a) to c) to create an individual consumer forecast of power usage, said consumer forecast being collectively aggregated across a plurality of users;

e) using data from one or more of a) to d) to perform a demographic analysis;

f) collecting macrogrid aggregate power consumption data for the region;

g) determining power consumption requirements across the macrogrid for the region using data from at least one of a) to e); and

h) determining future power requirements within the macrogrid, using the data obtained in at least one of a) to g).

11. The system of claim 10 wherein external impacts are selected from any one of:

weather patterns and predictions, calendar month, economic indicators, world events, television programming, equipment age and maintenance, and population mobility.

12. The system of claim 10 wherein the at least one behavioral pattern comprises data related to user behavioral states selected from one or more of the following states:

sleeping, just awoken, on vacation, working from home, charging electric vehicles, and extended absence.

13. The system of claim 10 wherein the at least one behavioral pattern comprises data related to user behavioral patterns selected from one or more of the following patterns:

sleeping hours, weekend schedules, weekday schedules, departure to work and arrival home from work, and amount of time spent away from home.

14. The system of claim 10 wherein a forecast period is selected as being one of:

minutes, hours, days, months, seasonal and years.

15. The system of claim 10 further comprising instructions for using the forecast for at least one of:

regulating power supply and distribution, and operational planning to identify timing and location of future upgrades.

16. The system of claim 10 further comprising instructions for using the forecast to dynamically evaluate power consumption patterns in a selected demographic sector of the population.

17. The system of claim 10 further comprising instructions for using the forecast to identify at least one demographic categorization with a higher predictability value than those previously known.

18. The system of claim 10 further comprising instructions for interpolating a sample user forecast onto larger populations with at least one diverse demographic variation.

19. The system of claim 10 further comprising instructions for using the forecast to identify one or more periods in a user'"'"'s billing cycle in which a potential for energy conservation is high for that user.

20. The system of claim 10 further comprising instructions for using the forecast to identify a power consumption reduction and budget reduction plan.

21. The system of claim 10 wherein a population is selected from at least one of:

consumers, commercial operations and industrial operations.

22. The system of claim 10, wherein a statistical sample size is a population sample which is larger than or equal to the smallest possible sample for which the patterns of the entire population can be observed and modeled within a required accuracy.

23. A system for forecasting and predicting power usage within a macrogrid, the system comprising a server and one or more databases, the server comprising a processor and memory, the memory comprising computer executable instructions for:

a) periodically receiving granular power consumption data from a statistically significant portion of a target population of power users within the macrogrid for a region;

b) using the power consumption data to perform a consumer load disaggregation to determine usage behaviors for at least one appliance or device;

c) obtaining data relating to at least one behavioral pattern and a state of a user;

d) obtaining data relating to external impacts on power usage;

e) using obtained data from at least one of a) to d) to generate an individual consumer forecast of power usage, the consumer forecast being collectively aggregated across a plurality of users;

f) using data from one or more of a) to e) to perform a demographic analysis;

g) collecting aggregate power consumption data for a region associated with the macrogrid;

h) determining power consumption requirements across the macrogrid for the region using data from at least one of more of a) to g); and

i) determining future power requirements within the macrogrid, using the data obtained in at least one of a) to h).