Energy and cost savings calculation system

• US 7,451,017 B2
• Filed: 07/02/2007
• Issued: 11/11/2008
• Est. Priority Date: 01/26/2005
• Status: Active Grant

• Current Assignee: Siemens Industry Incorporated (Siemens AG)
• Original Assignee: Siemens Building Technologies Incorporated (Siemens AG)
• Inventors: McNally, James T.
• Primary Examiner(s): Masinick; Michael D
• Application Number:
  US11/772,436
• Publication Number:
  US 20070244604A1
• Time in Patent Office: 498 Days
• Field of Search: 700/275, 700/276, 700/278, 700/291
• 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 method of forecasting energy loads, the method comprising:

forecasting an energy load for a building using a multi-variant non-linear (MVNL) load forecasting technique, the MVNL load forecasting technique accounts for the effect of weather in forecasting the energy load by modifying a reference period having associated energy and weather data such that the weather data of the reference period as modified approximately matches weather experienced during a current reporting period to provide an indication of the effect of weather on energy usage during the current reporting period.

2. The method of claim 1, the method comprising:

receiving solar condition data associated with at least one solar condition from a weather data provider; and

assigning the at least one solar condition a corresponding numerical value, wherein the MVNL load forecasting technique uses the corresponding numerical value to account for the effect of solar conditions on building thermal load.

3. The method of claim 1, the method comprising extending a baseline of energy usage data to account for changes in weather or building occupancy, wherein the MVNL load forecasting technique uses the baseline extension in forecasting the energy load.

4. The method of claim 1, wherein the MVNL load forecasting technique uses a schedule proportional adjustment to the baseline extension in forecasting the energy load, wherein the schedule proportional adjustment accounts for a change associated with the building.

5. The method of claim 1, wherein the MVNL load forecasting technique accounts for a changeover temperature in forecasting the energy load, the changeover temperature being the temperature at which a building heating system and a building cooling system switch, with one system becoming operative and the other system becoming inoperative as temperature crosses the changeover temperature.

6. The method of claim 1, the method comprising receiving interval data automatically read from meters, the automatically read interval data being used by the MVNL load forecasting technique in forecasting the energy load.

7. The method of claim 1, the method comprising:

establishing a baseline from collected weather and energy usage data;

dividing the baseline into a plurality of reference periods, each of the plurality of reference periods having a separate temperature range and corresponds to a specific time period;

identifying the reference period from among the plurality of basic reference periods having associated weather data representing past weather that approximately matches weather experienced during the current reporting period.

8. The method of claim 7, the method comprising modifying the weather data associated with the reference period if the outside air temperature of the current reporting period is outside a temperature range associated with the reference period.

9. The method of claim 8, wherein the modification to the the weather data associated with the reference period involves extending the reference period further backward and/or forward in time until the outside air temperature of the current reporting period falls within a temperature range associated with the reference period as modified.

10. The method of claim 1, the method comprising:

calculating a first baseline reference that estimates an energy usage prior to a retrofit or an energy conservation measure being implemented;

extending the first baseline reference forward in time subsequent to a retrofit or an energy conservation measure being implemented to form a first baseline extension; and

calculating an actual savings associated with the retrofit or the energy conservation measure by subtracting an actual energy usage from the first baseline extension.

11. The method of claim 10, the method comprising:

calculating a second baseline reference that estimates an energy usage subsequent to a retrofit or an energy conservation measure being implemented;

extending the second baseline reference to the present time period and beyond to form a second baseline extension;

calculating the ideal savings associated with the retrofit or the energy conservation measure by subtracting the second baseline extension from the first baseline extension; and

calculating an actual slip by subtracting the second baseline extension from the actual energy usage.

12. The method of claim 1, the method comprising:

preparing load forecasts for the building for each time-of-use period associated with a time-of-use electric rate; and

calculating energy savings using complex rates.

13. A method of forecasting energy loads, the method comprising:

receiving weather data associated with a plurality of weather parameters;

receiving energy data associated with energy usage;

performing Multi-Variant Non-Linear (MVNL) load forecasting using the weather data and the energy data received as inputs;

adjusting the load forecasting based upon billing determinants; and

further adjusting the load forecasting based upon complex rate schedules to determine a cost or cost savings, wherein the MVNL load forecasting modifies a reference period having associated energy and weather data such that the weather data of the reference period as modified approximately matches weather experienced during a current reporting period to provide an indication of the effect of weather on energy usage during the current reporting period.

14. The method of claim 13, wherein the billing determinants include energy rates adjusted for time of use and the complex rates include on-peak, shoulder, and off-peak consumption periods.

15. The method of claim 13, wherein load forecasts are prepared for each time-of-use period of the day, with each time-of-use period having associated consumption and demand elements.

16. The method of claim 13, wherein the MVNL load forecasting accounts for the effect of solar conditions on thermal load in forecasting the energy load.

17. A method of forecasting energy loads, the method comprising:

establishing a baseline from weather and energy data collected;

dividing the baseline into basic reference periods corresponding to specific time periods, each of the basic reference periods having a corresponding weather data set;

identifying a past weather data set associated with a basic reference period from among all of the weather data sets that most closely resembles weather during a current reporting period; and

using past energy usage associated with the past weather data set identified as a starting point in calculating energy usage during the current reporting period, wherein if outside air temperature of the current reporting period is outside a temperature range associated with the basic reference period, adjusting the past weather data set associated with the basic reference period to more accurately reflect the weather during the current reporting period.

18. The system of claim 17, wherein the adjustment to the past weather data set associated with the basic reference period extends the basic reference period further backward and/or forward in time within the baseline such that the basic reference period as modified more accurately represents actual outside air temperature of the current reporting period.