Automatic energy management and energy consumption reduction, especially in commercial and multi-building systems

• US 8,078,330 B2
• Filed: 08/14/2007
• Issued: 12/13/2011
• Est. Priority Date: 03/08/2002
• Status: Expired due to Term

• Current Assignee: Intercap Capital Partners LLC
• Original Assignee: Intercap Capital Partners LLC
• Inventors: Brickfield, Peter J., Mahling, Dirk, Noyes, Mark, Weaver, David
• Primary Examiner(s): JARRETT, RYAN A
• Application Number:
  US11/889,513
• Publication Number:
  US 20080177423A1
• Time in Patent Office: 1,582 Days
• Field of Search: 700/291, 700/286
• US Class Current: 700/291
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 2310/60 Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
• CPC Class Codes: H02J 2310/64 The condition being economic, e.g. tariff based load management
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/008 involving trading of energy or energy transmission rights
• CPC Class Codes: H02J 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02E 40/70 Smart grids as climate change mitigation technology in the energy generation sector
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y02P 80/10 Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
• 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 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security
• CPC Class Codes: Y04S 50/10 Energy trading, including energy flowing from end-user application to grid

Abstract

Automatic energy management is provided, in even the most complex multi-building system. The necessity of a human operator for managing energy in a complex, multi-building system is reduced and even eliminated. Computer-based monitoring and computer-based recognition of adverse energy events (such as the approach of a new energy peak) is highly advantageous in energy management. Immediate automatic querying of energy users within a system of buildings for energy curtailment possibilities is provided. Such immediate, automatic querying may be answered by the energy users through artificial intelligence and/or neural network technology provided to or programmed into the energy users, and the queried energy users may respond in real-time. Those real-time computerized responses with energy curtailment possibilities may be received automatically by a data processing facility, and processed in real-time. Advantageously, the responses from queried energy users with energy curtailment possibilities may be automatically processed into a round-robin curtailment rotation which may be implemented by a computer-based control system. Thus, impact on occupants is minimized, and energy use and energy cost may be beneficially reduced in an intelligent, real-time manner. The invention also provides for early-recognition of impending adverse energy events, optimal response to a particular energy situation, real-time analysis of energy-related data, etc.

Claims

1. A method of managing energy usage in a building system, comprising:

managing energy usage history data of a plurality of energy consumption devices in the building system, the energy usage history data comprising one or more energy usage peaks previously reached by the building system;

monitoring current energy usage of the plurality of energy consumption devices in the building system;

monitoring a plurality of global variables comprising a building temperature, a building humidity, a building CO₂ level, a weather forecast and a real-time energy price;

forecasting whether or not a new energy usage peak is approaching based on the current energy usage and the energy usage history data; and

automatically initiating a real-time control of each energy consumption device based on the plurality of global variables in response to a forecast that a new energy usage peak is approaching.

2. The method of claim 1, wherein the building system comprises at least two buildings.

3. The method of claim 1, wherein the managing the energy usage history data comprises:

compiling the current energy usage to generate the energy usage history data of the building system; and

determining one or more energy usage patterns from the energy usage history data, and

wherein the forecasting whether or not a new energy usage peak is approaching comprises comparing the current energy usage with the one or more energy usage patterns.

4. The method of claim 1, wherein the forecasting whether or not a new energy usage peak is approaching is based on neural network based prediction.

5. The method of claim 1, wherein the forecasting whether or not a new energy usage peak is approaching involves no human operator intervention.

6. The method of claim 1, wherein the monitoring the current energy usage comprises collecting energy usage data from the plurality of energy consumption devices in the building system.

7. The method of claim 1, wherein the monitoring the current energy usage comprises collecting energy usage data from one or more energy usage monitoring sources, wherein the one or more energy usage monitoring sources comprises at least one of a sensing device and an electric meter used for billing.

8. The method of claim 7, wherein the plurality of global variables further comprise one or more energy usage patterns of each energy consumption device and an occupancy of a portion of the building system where each energy consumption device is located.

9. A computer for managing energy usage in a building system, comprising:

a data management unit configured to manage energy usage history data of a plurality of energy consumption devices in the building system, the energy usage history data comprising one or more energy usage peaks previously reached by the building system;

a first monitoring unit configured to monitor current energy usage of the plurality of eneroy consumption devices in the building system;

a second monitoring unit configured to monitor a pluralty of global variables comprising a building temperature, a building humidity, a building CO₂ level, a weather forecast and a real-time energy price;

a forecasting unit configured to forecast whether or not a new energy usage peak is approaching based on the current energy usage and the energy usage history data; and

a control unit configured to automatically initiate a real-time control of each energy consumption device based on the plurality of global variables in response to a forecast that a new energy usage peak is approaching.

10. The computer of claim 9, wherein the building system comprises at least two buildings.

11. The computer of claim 9, wherein the data management unit comprises:

a compilation unit for compiling the current energy usage of the building system to generate the energy usage history data; and

a data processing unit for determining one or more energy usage patterns from the energy usage history data, and

wherein the forecasting unit compares the current energy usage with the one or more energy usage patterns to forecast if a new energy usage peak is approaching.

12. The computer of claim 9, wherein the forecasting unit forecasts whether or not a new energy usage peak is approaching based on neural network based prediction.

13. The computer of claim 9, wherein the forecasting unit forecasts whether or not a new energy usage peak is approaching without human operator ntervention.

14. The computer of claim 9, wherein the first monitoring unit collects energy usage data from the plurality of energy consumption devices in the building system.

15. The computer of claim 9, wherein the first monitoring unit collects energy usage data from one or more energy usage monitoring sources comprising at least one of a sensing device and an electric meter.

16. The computer of claim 9, wherein the plurality of global variables further comprise one or more energy usage patterns of each energy consumption device and an occupancy of a portion of the building system where each energy consumption device is located.