Energy and cost savings calculation system

• US 20060167591A1
• Filed: 04/28/2005
• Published: 07/27/2006
• Est. Priority Date: 01/26/2005
• Status: Abandoned Application

• Current Assignee: Siemens Industry Incorporated (Siemens AG)
• Original Assignee: Siemens Industry Incorporated (Siemens AG)
• Inventors: McNally, James T.
• Application Number:
  US11/118,598
• Publication Number:
  US 20060167591A1
• Time in Patent Office: Days
• US Class Current: 700/291
• 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: Y02E 40/70 Smart grids as climate change mitigation technology in the energy generation sector
• 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 Energy and Cost Savings Calculation System is provided that automates the determination of energy and cost savings due to energy conservation measures. The system provides Multi-Variant, Non-Linear (MVNL) load forecasting techniques, energy and cost savings calculations, and Weather Ranking. The load forecasting technique may accept numerous external parameters as input. The technique may use multiple Baselines. It may also use multiple Basic Reference Periods to reduce the load forecasting error. The load forecasting technique may utilize external parameters that are updated on a daily basis, such as dry bulb temperature, dew point temperature, solar condition, and interval meter data. The technique may use Baseline Extensions to perform forecasts and Reference Period Modifications to enhance accuracy. The system may calculate energy and cost savings using Complex Rates and time-of-use (TOU) energy data. The system may rank a plurality of sources providing weather data to identify the most accurate weather data.

Claims

1. A data processing system for forecasting energy loads, the system comprising:

a processing unit operable to receive a plurality of external parameters, wherein the processing unit forecasts energy loads for a building based upon the external parameters by utilizing multi-variant non-linear (MVNL) load forecasting.

2. The system of claim 1, wherein the external parameters include daily weather data.

3. The system of claim 2, wherein the daily weather data includes dew point temperature data.

4. The system of claim 2, wherein the daily weather data includes solar condition data.

5. The system of claim 2, wherein the daily weather data includes outside air dry bulb temperature data.

6. The system of claim 1, wherein the external parameters include type of day data, the type of day being a weekend, a weekday, or a holiday.

7. The system of claim 1, wherein the external parameters include calendar data, the calendar data identifies the day of the week or the day of the year for a given day.

8. The system of claim 1, wherein the external parameters include daily time-of-use energy data, the daily time-of-use energy data is related to on-peak, shoulder, and off-peak electric rates.

9. The system of claim 1, wherein the MVNL load forecasting technique uses multiple reference periods within a baseline, each reference period corresponding to a different time period.

10. The system of claim 9, wherein the MVNL load forecasting technique calculates a first baseline extension from data obtained before the installation of an energy conservation measure and a second baseline extension from data obtained after the installation of the energy conservation measure.

11. The system of claim 1, wherein the MVNL load forecasting technique uses reference period modifications within the baseline to more accurately represent the actual outside air temperature.

12. The system of claim 1, wherein the external parameters include data from automatically read meters.

13. The system of claim 1, wherein the processor calculates actual cost savings and forecast cost savings.

14. The system of claim 13, wherein the processor calculates actual savings slip and forecast savings slip.

15. The system of claim 14, wherein the processor generates energy usage reports.

16. The system of claim 1, wherein the external parameters include weather data received from a plurality of sources and the processor identifies the most accurate weather data available to be used by the MVNL load forecasting technique.

17. A data processing system for forecasting energy loads, the system comprising:

a processing unit operable to receive a plurality of variables that are updated at least daily, the variables include daily weather data, wherein the processing unit forecasts energy loads for a building based upon the variables.

18. The system of claim 17, wherein the daily weather data includes dew point temperature data.

19. The system of claim 17, wherein the daily weather data includes solar condition data.

20. The system of claim 17, wherein the daily weather data includes outside air dry bulb temperature data.

21. The system of claim 17, wherein the system uses multiple reference periods within the baseline and reference period modifications to more accurately represent the outside air temperature conditions of the reporting period.

22. A method for calculating energy loads, the method comprising:

receiving weather and energy data, the weather and energy data containing information regarding a plurality of parameters;

calculating multiple reference periods from the weather and energy data, each reference period corresponding to a different time period; and

forecasting energy loads for a building using the multiple reference periods.

23. The method of claim 22, wherein each reference period corresponds to a different month.

24. The method of claim 22, comprising:

calculating a first baseline from data obtained before the installation of an energy conservation measure; and

calculating a second baseline from data obtained after the installation of the energy conservation measure.

25. The method of claim 22, comprising modifying at least one reference period to more accurately represent the outside air temperature conditions of the reporting period.

26. The method of claim 22, wherein the weather data includes dew point temperature data.

27. A computer-readable medium having instructions executable on a computer stored thereon, the instructions comprising:

receiving weather data associated with a plurality of weather parameters;

receiving energy data associated with energy usage; and

forecasting the energy load for a building during a specific time period by using Multi-Variant Non-Linear technology.

28. The computer-readable medium of claim 27, comprising determining the cost of the energy load based upon time-of-use electric rates.

29. The computer-readable medium of claim 27, wherein the weather parameters include solar condition, outside air dry-bulb temperature, dew point temperature, and barometric pressure.

30. The computer-readable medium of claim 29, comprising assigning solar condition coefficients based upon the solar condition.

31. The computer-readable medium of claim 27, comprising:

calculating a first baseline for energy usage from data obtained before the installation of an energy conservation measure; and

calculating a second baseline for energy usage from data obtained after the installation of the energy conservation measure.

32. The computer-readable medium of claim 31, comprising extending at least one reference period to more accurately reflect the outside air temperature range of the reporting period.