Real time microgrid power analytics portal for mission critical power systems

• US 8,321,194 B2
• Filed: 09/30/2010
• Issued: 11/27/2012
• Est. Priority Date: 10/01/2009
• Status: Active Grant

• Current Assignee: Bentley Systems Incorporated
• Original Assignee: Power Analytics Corporation (PAC Global, Inc.)
• Inventors: Meagher, Kevin, Loiselle, David, Koopman, Rodger
• Primary Examiner(s): Patel, Shambhavi
• Application Number:
  US12/895,586
• Publication Number:
  US 20110082596A1
• Time in Patent Office: 789 Days
• Field of Search: 703/1, 703/2, 703/13, 703/14, 703/18, 700/286, 700/291
• US Class Current: 703/14
• CPC Class Codes: H02J 13/00001 characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
• CPC Class Codes: H02J 13/00002 characterised by monitoring
• CPC Class Codes: H02J 13/00017 using optical fiber
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 10/30 State monitoring, e.g. fault, temperature monitoring, insulator monitoring, corona discharge
• CPC Class Codes: Y04S 10/40 Display of information, e.g. of data or controls
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Abstract

Systems and method for providing a microgrid power analytics portal for mission critical power systems are provided. The techniques disclosed herein provides for real-time modeling, evaluation, and commodity market pricing and optimization for an electrical network that includes microgrids using data collected from virtually any digital data source. The portal is platform independent and can be configured to collect and aggregate real-time data from sensors interfaced with components of the electrical network regardless of proprietary architectures or vendor-specific limitations imposed by the sensors or data collection software.

Claims

1. A system for real-time modeling of electrical system performance of a microgrid electrical system, comprising:

a plurality of sensors interfaced with components of the electrical system;

an analytics server, comprising a virtual system modeling engine configured to generate predicted data output for the electrical system utilizing a virtual system model of the electrical system; and

a microgrid portal comprising

a device driver database configured to store a plurality of device drivers associated with sensors interfaced with components of an electrical system,

a portal configuration engine configured to

receive a copy of the virtual model of the electrical system,

parse the virtual model of the electrical system to identify sensor devices interfaced with components of the electrical system,

identify device drivers in the device driver database that can be used to interface each sensor device with the analytics server, and

send the identified device drivers to the analytics server, wherein the analytics server is configured to receive the device drivers from the portal configuration engine, install the device drivers, and establish a bidirectional communication link with the plurality of sensors interfaced with components of the electrical system using the device drivers, and

a portal access engine configured to receive real-time data, analytics data, and predicted data from the analytics server and display the data to an operator on a display of the client terminal.

2. The system of claim 1 wherein the analytics server further comprises:

an analytics engine configured to monitor real-time data output and the predicted data output of the electrical system, the analytics engine further configured to initiate a calibration and synchronization operation to update the virtual system model when a difference between the real-time data output and the predicted data output exceeds a threshold.

3. The system of claim 1 wherein the portal configuration engine provides a virtual model upload interface that allows a user to upload a virtual model of an electrical system to be parsed by the portal configuration engine.

4. The system of claim 1 wherein the portal configuration engine is further configured to:

request a copy of the virtual model of the electrical system from the analytics server via a network connection; and

receive a copy of the virtual model from the analytics server via the network connection.

5. The system of claim 1 wherein the portal configuration engine provides a device driver upload interface that allows a user to upload a device driver for a sensor device, and wherein the portal configuration module is configured to add the device driver to the device driver database.

6. The system of claim 5 wherein the portal configuration engine is configured to prompt a user to upload a device driver if a device driver for a sensor device included in the virtual model is not found in the device driver database.

7. The system of claim 1 wherein the portal configuration engine is configured to execute an online search for a device driver if a device driver for a particular sensor device is not found in the device driver database.

8. The system of claim 7 wherein the portal configuration engine is configured to upload the device driver into the device driver database if the device driver is found by the online search.

9. A computer implemented method for real-time modeling of the performance of a microgrid electrical system, the method comprising comprising:

by one or more processors of a microgrid portal,

receiving a virtual model of a microgrid electrical system,

parsing the virtual model of the microgrid electrical system to identify a plurality of sensor devices interfaced with components of the microgrid electrical system,

identifying device drivers in a device driver database, wherein the device drivers can be used to interface each sensor device with an analytics server,

sending the identified device drivers to the analytics server,

receiving real-time data, analytics data, and predicted data for the microgrid electrical system from the analytics server, and

providing the received real-time data, analytics data, and predicted data to an operator; and

by one or more processors of the analytics server,

receiving and installing the device drivers on the analytics server,

establishing a bidirectional communication link with a plurality of sensors interfaced with components of the microgrid electrical system using the device drivers,

acquiring the real-time data from the plurality of sensors using the device drivers, and

generating the predicted data for the microgrid electrical system utilizing the virtual model of the microgrid electrical system.

10. The method of claim 9, wherein generating predicted data output comprises:

calculating predicated data forecasting the performance of the microgrid electrical system; and

initiating a calibration and synchronization operation to update the virtual model when a difference between the real-time data and the predicted data exceeds a threshold.

11. The method of claim 10, further comprising:

acquiring additional real-time data from sensors interfaced with components of the microgrid electrical system;

generating additional predicted data regarding the performance of the microgrid electrical system using the calibrated virtual model; and

presenting the additional predicted data, the additional real-time data, and pattern recognition data on a display of a client terminal.

12. The method of claim 9 further comprising:

displaying a virtual model upload interface that allows a user to upload a copy of a virtual model of an electrical system to be parsed; and

receiving the copy of the virtual model via the interface.

13. The method of claim 9 further comprising:

requesting a copy of the virtual model of the electrical system from the analytics server via a network connection; and

receiving a copy of the virtual model from the analytic server via the network connection.

14. The method of claim 9 further comprising:

displaying a device driver upload interface that allows a user to upload a device driver for a sensor device;

receiving a device driver uploaded via the device driver user interface; and

adding the device driver to the device driver database.

15. The method of claim 13 further comprising:

displaying a message prompting a user to upload a device driver if a device driver for a sensor device included in the virtual model is not found in the device driver database.

16. The method of claim 9 further comprising:

automatically executing an online search for a device driver if a device driver for a particular sensor device is not found in the device driver database.

17. The method of claim 16 further comprising:

uploading the device driver into the device driver database if the device driver is found by the online search.