Dynamic load curtailment system and method

• US 8,862,280 B1
• Filed: 03/20/2012
• Issued: 10/14/2014
• Est. Priority Date: 06/13/2011
• Status: Active Grant

• Current Assignee: Gridpoint (Twenty First Century Utilities LLC)
• Original Assignee: Gridpoint (Twenty First Century Utilities LLC)
• Inventors: Dyess, Danny K., Tamagni, Armand J. Jr., Vinson, Mark W.
• Primary Examiner(s): JARRETT, RYAN A
• Application Number:
  US13/425,195
• Time in Patent Office: 938 Days
• Field of Search: None
• US Class Current: 700/291
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/46 Improving electric energy efficiency or saving
• CPC Class Codes: F24F 11/47 Responding to energy costs
• CPC Class Codes: F24F 11/56 Remote control
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 11/63 Electronic processing
• CPC Class Codes: F24F 11/64 using pre-stored data
• CPC Class Codes: F24F 11/65 for selecting an operating mode
• CPC Class Codes: F24F 2140/00 Control inputs relating to system states
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 19/048 Monitoring; Safety
• CPC Class Codes: G05B 2219/2614 HVAC, heating, ventillation, climate control
• CPC Class Codes: G05F 1/66 Regulating electric power
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 20/244 the home appliances being or involving heating ventilating and air conditioning [HVAC] units

Abstract

A system that dynamically learns the optimum energy consumption operating condition for a building and monitors/controls energy consuming equipment to keep the peak demand interval at a minimum. The algorithm employs two separate control schemes, one for HVAC loads and one for non-HVAC loads, and uses historical peak demand measurements in its real-time limiting strategy. The algorithm continuously attempts to reduce peak demand within user configured parameters. When a new peak is inevitable, the algorithm removes and/or introduces loads to limit the new peak magnitude and places the operating conditions within the user configured parameters. The algorithm can examine the previous seven days of metering information to identify a peak demand interval, use real-time load information to predict the demand peak of the upcoming interval, and curtail loads in order to limit the demand peak so as not to set a new peak.

Claims

1. A method of load curtailment for a facility, comprising:

examining a number of previous days of metering information to identify a demand peak target, wherein the examining step comprises

calculating a target total facility KW value such that the target total facility KW is the greater of;

a first proportion times recent total facility demand peak, where recent total facility demand peak is equal to the highest total facility demand value for the number of previous days, and

a second proportion times recent occupied average total facility load, where recent occupied average total facility load is equal to the average value of total facility load during occupied hours for the number of previous days;

utilizing real-time load information to predict the demand peak of the upcoming interval; and

,

strategically curtailing assigned loads in order to limit the demand peak so as not to set a new peak;

whereby an automated tuning operation is created and the building operates with improved efficiency.

2. The method of load curtailment in accordance with claim 1, wherein the first proportion is 0.95.

3. The method of load curtailment in accordance with claim 1, wherein the second proportion is 1.05.

4. The method of load curtailment in accordance with claim 1, wherein the first and second proportions are configurable.

5. The method of load curtailment in accordance with claim 1, wherein the number of previous days of metering information is configurable.

6. The method of load curtailment in accordance with claim 1, wherein the number of previous days of metering information that is examined is seven.

7. Computer program process code, tangibly stored on at least one non-transitory computer readable medium, the computer program process code comprising instructions implementing a method for using a computing device to perform dynamic load curtailment, comprising instructions for:

examining a number of previous days of metering information to identify a demand peak target, wherein the examining step comprises

calculating a target total facility KW value such that the target total facility KW is the greater of;

a first proportion times recent total facility demand peak, where recent total facility demand peak is equal to the highest total facility demand value for the number of previous days, and

a second proportion times recent occupied average total facility load, where recent occupied average total facility load is equal to the average value of total facility load during occupied hours for the number of previous days;

utilizing real-time load information to predict the demand peak of the upcoming interval; and

,

strategically curtailing assigned loads in order to limit the demand peak so as not to set a new peak;

whereby an automated tuning operation is created and the building operates with improved efficiency.