CLOUD-BASED CONTROL FOR POWER DISTRIBUTION SYSTEM

• US 20170250539A1
• Filed: 02/24/2017
• Published: 08/31/2017
• Est. Priority Date: 02/26/2016
• Status: Active Grant

• Current Assignee: ABB Schweiz AG (ABB Limited)
• Original Assignee: ABB Schweiz AG (ABB Limited)
• Inventors: Feng, Xianyong
• Granted Patent: US 10,411,475 B2
• Time in Patent Office: Days
• CPC Class Codes: H02J 13/00026 involving a local wireless network, e.g. Wi-Fi, ZigBee or Bluetooth
• CPC Class Codes: H02J 2300/24 of photovoltaic origin
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/381 Dispersed generators
• CPC Class Codes: Y02B 10/10 Photovoltaic [PV]
• CPC Class Codes: Y02B 90/20 Smart grids as enabling technology in buildings sector smart grids supporting the management or operation of end-user stationary applications in general, or like technologies with no associated climate change mitigation effect Y04S20/00
• CPC Class Codes: Y02E 10/56 Power conversion systems, e.g. maximum power point trackers
• CPC Class Codes: Y02E 40/70 Smart grids as climate change mitigation technology in the energy generation sector
• CPC Class Codes: Y04S 10/123 the energy generation units being or involving renewable energy sources
• CPC Class Codes: Y04S 40/126 using wireless data transmission

Abstract

Unique systems, methods, techniques and apparatuses for cloud-based control for power distribution systems are disclosed. One exemplary embodiment is a system comprising a microprocessor-based power management system in operative communication with a plurality of buildings located remotely from the power management system and a plurality of communication interface devices provided at corresponding ones of the plurality of buildings. The power management system is structured to perform a plurality of building unit-specific optimizations, evaluate a net power demand on the electrical power grid, reduce the net power demand on the electrical power grid while minimizing disruption to the resident-defined preference parameters, and transmit to each of the plurality of interface devices the one or more additional control commands corresponding to the specific building at which each interface device is provided.

Claims

1. A method for reducing peak power demands in a power distribution system, the system including a plurality of buildings structured to receive power from a utility grid, the buildings each having at least one controllable thermal load, the method comprising:

forecasting a future aggregate power demand peak of the power distribution system with a central load controller;

generating a thermal model for each controllable thermal load with the load controller;

receiving user-defined constraint data related to each controllable load including a temperature operating range with the load controller;

generating a plurality of optimized load commands based on the forecasted aggregate power demand, thermal models, and constraint data with the load controller; and

transmitting each load command with the load controller to a unique thermal load by way of an interface device located within the same building associated with the thermal load,

wherein the load commands from the load controller include a set of instructions to precool or preheat a thermal load within the user-defined constraints before the time period when the forecasted aggregate power demand peak is forecasted to occur.

2. The method of claim 1, wherein one controllable thermal load is one of a water heater and an HVAC system.

3. The method of claim 1, wherein the precooling or preheating of the thermal loads eliminates the need to operate auxiliary power generators.

4. The method of claim 3, wherein the load commands are optimized such that the deviation from the non-disturbed condition of the thermal loads is minimized but still sufficient to eliminate the need to operate the auxiliary power generators.

5. The method of claim 1, wherein the method additionally comprises:

receiving distributed energy resource data from a distributed energy resource with the interface device associated with the same building;

receiving energy storage data from an energy storage device with the interface device located within the same building;

transmitting the distributed energy storage data to the central load controller with the interface device;

generating a plurality of optimized operation commands based on the forecasted aggregate power demand, thermal models, and constraint data with the load controller; and

transmitting each operation command with the load controller to a unique distributed energy resource or energy storage device by way of the interface device located within the same building associated with the distributed energy resource or energy storage device.

6. The method of claim 4, additionally comprising:

receiving utility grid pricing data with the central load controller; and

transmitting a plurality of operation commands to the energy storage device by way of the interface device and a plurality of load commands to the thermal load by way of the interface device, the operation commands and load commands each having a set of instructions to operate the energy storage device and thermal load respectively so as to minimize the cost of power received from the utility grid.

7. The method of claim 1, additionally comprising optimizing the thermal model by identifying a plurality of known and estimated parameters and adjusting the weight of the estimated parameters in response to determining a difference between the expected temperature of each thermal load and the actual temperature of the same thermal load.

8. A system comprising:

a microprocessor-based power management system in operative communication with a plurality of buildings located remotely from the power management system; and

a plurality of communication interface devices provided at corresponding ones of the plurality of buildings, the interface devices being structured to provide communication between the power management system and a plurality of thermal energy storage (“

TES”

) loads associated with respective ones of the plurality of buildings, the thermal energy storage loads being configured to receive electrical power from an electrical grid and to provide at least one of heating and cooling of an associated thermal energy storage medium using the electrical power;

wherein the power management system is structured to;

perform a plurality of building unit-specific optimizations each pertaining to a specific building unit of the plurality of buildings, each of the optimizations using a dynamic thermal model of the specific building unit, resident-defined preference parameters for the specific building unit, and electrical power pricing information to determine one or more control commands for one or more of the TES loads at the specific building unit,

transmit to each of the plurality of interface devices the one or more control commands which correspond to the specific building unit at which each interface device is provided,

evaluate a net power demand on the electrical power grid,

if evaluation of the net power demand indicates an over power condition, determine one or more additional control commands for the one or more of the TES loads at the specific building, the one or more additional control commands being structured to reduce the net power demand on the electrical power grid while minimizing disruption to the resident-defined preference parameters, and

transmit to each of the plurality of interface devices the one or more additional control commands corresponding to the specific building at which each interface device is provided.

9. The system of claim 8 wherein each of the optimizations is effective to minimize electrical power cost for its respective specific building over an operating period subject to the constraints of the resident-defined preference parameters for the specific building.

10. The system of claim 8 wherein each thermal model includes a plurality of known and unknown parameters and the power management system is structured to accurately generate a thermal model by assigning a weighted value to each parameters, comparing the thermal model results to historical temperature data, and adjusting the weighted value for one or more of the parameters so as due reduce the margin of error between the thermal model and the actual temperature.

11. The system of claim 8 wherein:

the interface devices are structured to provide communication between the power management system and a plurality of distributed energy resources associated with respective ones of the plurality of buildings; and

the power management system is structured to determine one or more ancillary service commands for the one or more of the distributed energy resources, the one or more ancillary service commands being structured to store power generated by the distributed energy resource in anticipation of providing the power during a forecast ancillary service period.

12. The system of claim 8 wherein an over power condition is a time period in which an auxiliary power generating device must be operated in order to meet the net power demand on the electrical power grid.

13. The system of claim 8 wherein the power management system includes a cloud server.

14. The system of claim 8 wherein the power management system is structured to receive weather data from a weather station and use the weather data to determine one or more control commands for one or more of the TES loads at the specific building unit.

15. A method for operating a power distribution system including a microprocessor-based power management system and a plurality of remote communication interface devices, each communication interface device corresponding to one building including at least one thermal energy storage (TES) load, the method comprising:

performing, with the power management system, a plurality of building unit-specific optimizations each pertaining to a specific building unit of the plurality of buildings, each of the optimizations using a dynamic thermal model of the specific building unit, resident-defined preference parameters for the specific building unit, and electrical power pricing information to determine one or more control commands for one or more of the TES loads at the specific building unit,

Transmitting, with the power management system, to each of the plurality of interface devices the one or more control commands which correspond to the specific building unit at which each interface device is provided,

evaluating, with the power management system, a forecasted net power demand on the power distribution system,

if evaluation of the net power demand indicates an over power condition,

determining, with the power management system, one or more additional control commands for the one or more of the TES loads at the specific building, the one or more additional control commands being structured to reduce the net power demand on the electrical power grid while minimizing disruption to the resident-defined preference parameters, and

transmitting, with the power management system, to at least a portion of the plurality of interface devices the one or more additional control commands corresponding to the specific building at which each interface device is provided.

16. The method of claim 15 wherein performing the plurality of building unit-specific optimizations includes using weather data or utility grid data to determine the one or more control commands for one or more of the TES loads at the specific building unit.

17. The method of claim 15 wherein if evaluation of the net power demand does not indicate an over power condition, the one or more control commands transmitted to the interface devices with the power management system are structured to minimize the electric power cost for each of the plurality of buildings.

18. The method of claim 15 wherein at least one building includes a distributed energy resource and the power management system is structured to perform the plurality of building unit-specific optimizations using distributed energy resource data to determine one or more control commands for the one or more TES loads at the specific building unit including the distributed energy resource.

19. The method of claim 15 wherein each additional control command is structured to control a temperature setting of one of the TES loads.

20. The method of claim 19 wherein each additional control command is structured to operate one of the TES loads before the forecasted over power condition in order to reduce net power demand during the forecasted over power condition.