US2015142193A1PendingUtilityA1

Utility console for controlling energy resources

Assignee: GRIDPOINT INCPriority: Jan 3, 2007Filed: Oct 7, 2014Published: May 21, 2015
Est. expiryJan 3, 2027(~0.5 yrs left)· nominal 20-yr term from priority
G05F 1/66G06N 5/04G05B 2219/2642H04L 67/10G05B 15/02H02J 3/32Y02B70/30Y04S20/20Y02P80/10
51
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Claims

Abstract

A system and method for managing power consumption and storage in a power grid. Measurements are received from a plurality of geographically distributed energy management controllers. Each energy management controllers has energy storage units with stored energy. The measurements comprise the energy production and storage capacity of the energy management controllers and their associated energy storage units. The measurements are processed, e.g., aggregated, and displayed on a graphical user interface. Commands are transmitted to a first subset of the energy management controllers to command the units to discharge their stored energy into a power grid through an inverter. Commands are transmitted to a second subset of the plurality of energy management controllers to store energy in each unit's energy storage unit.

Claims

exact text as granted — not AI-modified
We claim: 
     
         1 . A method of controlling energy consumption of a plurality of energy consuming devices at a premises, each of the plurality of energy consuming devices being controlled by a corresponding load controller having integrated measurement capability, each load controller being communicatively coupled to one of a plurality of distributed energy management controllers, the plurality of distributed energy management controllers being communicatively coupled to a computer system of an operations control center, comprising:
 measuring the individual energy load of each of the plurality of energy consuming devices, the measurement being performed by corresponding load controller;   communicating the individual energy load measurements from each load controller to a corresponding one of the plurality of distributed energy management controllers;   communicating the individual energy load measurements of each of the plurality of energy consuming devices from the plurality of distributed energy management controllers to the operations control center;   processing, by the computer system, the individual energy load measurements received from the plurality of distributed energy management controllers; and   transmitting a command from the operations control center to at least one of the plurality of distributed energy management controllers based on said processed energy load measurements to curtail/engage one or more of the plurality of energy consuming devices.   
     
     
         2 . The method of  claim 1 , wherein at least one of the plurality of distributed energy management controllers is controlled by a consumer using a graphical user interface and is also being remotely by a utility. 
     
     
         3 . The method of  claim 1 , wherein the individual energy load measurement is a demand measurement. 
     
     
         4 . The method of  claim 1 , wherein the individual energy load measurement is an energy use measurement. 
     
     
         5 . The method of  claim 1 , wherein the individual energy load measurement is an energy consumption measurement. 
     
     
         6 . The method of  claim 1 , further comprising:
 transmitting energy usage data and conservation data from at least one of the plurality of energy management controllers associated with a consumer to the operation center; and   displaying the energy usage data and conservation data to the consumer via a website.   
     
     
         7 . The method of  claim 1 , further comprising:
 controlling the plurality of energy management controllers by the operations center; and   monitoring the at least one of the plurality of energy management controllers by a consumer via a website provided by the operation center.   
     
     
         8 . The method of  claim 1 , wherein the processing further comprises:
 aggregating data from individual energy load measurements of a plurality of the energy consuming devices.   
     
     
         9 . The method of  claim 1 , wherein the processing further comprises:
 applying algorithms to individual energy load measurements; and   aggregating the results of the algorithms.   
     
     
         10 . The method of  claim 1 , wherein the processing further comprises:
 applying algorithms to the individual energy load measurements; and   associating current and predicted weather data with the individual energy load measurements.   
     
     
         11 . The method of  claim 1 , wherein the processing further comprises:
 applying algorithms to individual energy load measurements; and   applying user-defined rules to the individual energy load measurements.   
     
     
         12 . The method of  claim 1 , further comprising:
 sending a notification of a demand response request from the operations center to customers associated with each energy management controller, the notification including a schedule of an associated demand response event;   receiving acknowledgement of the demand response request from one or more customers associated with each one of the plurality of energy management controllers;   generating a report that indicates how much load can be expected to be shed from each premises associated with a corresponding energy management controller based upon the acknowledgement from each customer; and   generating an aggregated estimate of the size of the expected load reduction from a plurality of premises having an associated energy management controller based at least in part on historical load measurements.   
     
     
         13 . The method of  claim 12 , wherein each of the energy management controller executes the curtailment commands associated with the demand response request, records the performance of the demand response event triggered by the demand response request, and reports the performance of the demand response event back to the operations center. 
     
     
         14 . The method of  claim 1 , further comprising:
 performing calculations on the real-time measurements of the individual energy loads in iterative predictions of the performance of the demand response event while a demand response event triggered by the command is underway; and   determining, based on revised predictions, if the demand response event is not expected to be achieved, or may be achieved more effectively, and if so, automatically alter the command based upon defined constraints and rules.   
     
     
         15 . The method of  claim 1 , further comprising:
 aggregating categories of real-time energy load data associated with one or more of the plurality of energy management controllers;   displaying, on a utility console, the aggregated categories of individual real-time energy load data over a first predetermined time period;   calculating load forecasts for categories of the energy consuming devices using historical measured energy usage, the forecasts representing demand reduction potential available from selected categories of curtailable loads; and   displaying the load forecasts on a time scale representing future potential demand reduction potential.   
     
     
         16 . The method of  claim 15 , wherein the load forecast calculation uses exogenous data. 
     
     
         17 . The method of  claim 16 , wherein the exogenous data is predicted weather data. 
     
     
         18 . The method of  claim 1 , wherein the command is a demand response command that instructs the one or more of the plurality of energy management controllers to curtail energy use of one or more categories of power consuming devices, further comprising:
 controlling the one or more of the plurality of load controllers to reduce energy consumption of one or more categories of energy consuming devices;   receiving a load profile of an individual circuit of a customer;   comparing the load profile of the individual circuit to the actual load during the demand response event; and   compensating the consumer for the actual customer's individual load that was reduced.   
     
     
         19 . The method of  claim 1 , wherein at least one of the plurality of load controllers is a thermostat. 
     
     
         20 . The method of  claim 1 , wherein at least one of the plurality of load controllers is in-line with the circuit being controlled. 
     
     
         21 . A method of controlling energy consumption of a plurality of energy consuming devices at a premises, each of the plurality of energy consuming devices being controlled by a corresponding load controller, each load controller being communicatively coupled to one of a plurality of distributed energy management controllers, the plurality of distributed energy management controllers being communicatively coupled to a computer system of an operations control center, comprising:
 measuring the individual energy load of each one of the plurality of energy consuming devices;   communicating the individual energy load measurements to corresponding ones of the plurality of distributed energy management controllers;   communicating the individual energy load measurements of each of the plurality of energy consuming devices from the plurality of distributed energy management controllers to the operations control center;   processing, by the computer system, the individual energy load measurements received from the plurality of distributed energy management controllers;   transmitting a command from the operations control center to at least one of the plurality of distributed energy management controllers based on said processed individual energy load measurements to curtail/engage one or more of the plurality of energy consuming devices;   performing calculations on the real-time measurements of the individual energy load measurements in iterative predictions of the performance of a demand response event, triggered by the command, from the operations center while the demand response event is underway; and   determining, based on the iterative predictions, if the demand response event is not expected to be successfully achieved or may be achieved more effectively, and if so, automatically altering the command based upon defined constraints and rules.

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