Systems and Methods for Local Demand Optimization

• US 20160276833A1
• Filed: 03/17/2016
• Published: 09/22/2016
• Est. Priority Date: 03/17/2015
• Status: Active Grant

• Current Assignee: Open Access Technology International
• Original Assignee: Open Access Technology International
• Inventors: Amundson, Erik Alan, Sorvari, Anthony Charles, Mokhtari, Sasan, Nodehi Fard Haghighi, Khashayar, Heim, David, Eriksson, Dean
• Granted Patent: US 10,243,363 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: H02J 13/00004 characterised by the power network being locally controlled
• CPC Class Codes: H02J 13/00006 characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
• CPC Class Codes: H02J 2300/24 of photovoltaic origin
• CPC Class Codes: H02J 2310/14 The load or loads being home appliances
• 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: H04L 12/2816 Controlling appliance services of a home automation network by calling their functionalities arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station; in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom H04Q9/00
• CPC Class Codes: H04L 12/2834 Switching of information between an external network and a home network access arrangements H04L12/2856
• CPC Class Codes: H04L 12/66 Arrangements for connecting between networks having differing types of switching systems, e.g. gateways
• CPC Class Codes: H04L 2012/40215 Controller Area Network CAN
• CPC Class Codes: H04L 2012/4026 Bus for use in automation systems
• CPC Class Codes: Y02B 70/30 Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
• 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 20/20 End-user application control systems
• CPC Class Codes: Y04S 20/221 General power management systems
• CPC Class Codes: Y04S 20/242 Home appliances
• CPC Class Codes: Y04S 40/12 : characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment

Abstract

Systems and methods are provided, which provide for the de-centralization of the logic necessary to perform electrical optimization of any contained electrical system. The systems and methods de-centralize, or distribute, electrical optimization logic into intelligent devices which are locally connected to both the generation and loads, in such a way that control can be asserted over these resources. The inventive systems and methods require less infrastructure and communication backbone to IT/Data Center infrastructure than are typically required by previous systems and methods known in the art.

Claims

1. A method for Local Demand Optimization of electricity market systems, said system that supports intelligent devices which are locally connected to generation(s) and load(s) comprising the following steps:

an Intelligent Gateway for monitoring and controlling equipment and devices;

generation from solar, status of storage, and power consumption from loads being monitored;

set points and/or forecasts for local decisions and optimization actions;

programmable limits and thresholds;

stepping on loads to gradually re-introduce them onto the larger grid; and

device default values or pre-configured information from a cloud connection allowing optimization actions to happen without instructions from a larger or centralized system.

2. The method of claim 1, further comprising a medium collecting data points very frequently (less than one second), wherein said medium can be, but is not limited to:

Zigbee;

WiFi;

Ethernet;

CAN bus;

Modbus;

BACnet and

DNP;

3. The method of claim 1, further comprising a medium wherein an integrated device controls all equipment involved.

4. The method of claim 1, further comprising uploading data points to a cloud-based system for higher-level application integration such as, but not limited to mobile or web-based software.

5. The method of claim 1, further comprising cloud data connection or home area networking protocol wherein the set points and/or forecasts can be obtained.

6. The method of claim 1, further comprising DR/DER decisions.

7. The method of claim 1, further comprising enacted by protocol or direct control.

8. The method of claim 1, further comprising programmable limits and thresholds, wherein optimization actions are performed.

9. The method of claim 8, further utilizing a proportional-integral-derivative controller (PID).

10. The method of claim 8, further utilizing a proportional-integral controller (PID).

11. The method of claim 8, further utilizing if-then clause rules.

12. The method of claim 1, further comprising an enterprise system integration via cloud connection.

13. The method of claim 12, further utilizing download of programmable limits and thresholds.

14. The method of claim 12, further utilizing re-introduction of loads onto the larger grid.

15. The method of claim 12, wherein the cloud connection can enhance local logic.

16. A system comprising:

An Intelligent Gateway configured to;

monitoring and controlling equipment and devices;

monitoring generation from solar, status of storage, and power consumption from loads being monitored;

monitoring set points and/or forecasts for local decisions and optimization actions;

programmable limits and thresholds;

stepping on loads to gradually re-introduce them onto the larger grid; and

device default values or pre-configured information from a cloud connection allowing optimization actions to happen without instructions from a larger or centralized system.

17. The system of claim 16, wherein said medium can be, but is not limited to;

Zigbee;

WiFi;

Ethernet;

CAN bus;

Modbus;

BACnet and

DNP;

18. The system of claim 16, further comprising a medium wherein an integrated device controls all equipment involved.

19. The system of claim 16, further comprising uploading data points to a cloud-based system for higher-level application integration such as, but not limited to mobile or web-based software.

20. The system of claim 16, further comprising cloud data connection or home area networking protocol wherein the set points and/or forecasts can be obtained.

21. The system of claim 16, further comprising DR/DER decisions.

22. The system of claim 16, further comprising enacted by protocol or direct control.

23. The system of claim 16, further comprising programmable limits and thresholds, wherein optimization actions are performed.

24. The method of claim 23, further utilizing a proportional-integral-derivative controller (PID).

25. The method of claim 23, further utilizing a proportional-integral controller (PID).

26. The method of claim 23, further utilizing if-then clause rules.

27. The system of claim 16, further comprising an enterprise system integration via cloud connection.

28. The method of claim 27, further utilizing download of programmable limits and thresholds.

29. The method of claim 27, further utilizing re-introduction of loads onto the larger grid.

30. The method of claim 27, wherein the cloud connection can enhance local logic.