Microgrid Model Based Automated Real Time Simulation for Market Based Electric Power System Optimization

• US 20150153757A1
• Filed: 02/09/2015
• Published: 06/04/2015
• Est. Priority Date: 10/01/2009
• Status: Abandoned Application

• Current Assignee: WaveTech Global Inc.
• Original Assignee: Power Analytics Corporation (PAC Global, Inc.)
• Inventors: Meagher, Kevin
• Application Number:
  US14/617,271
• Publication Number:
  US 20150153757A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05F 1/66 Regulating electric power
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 3/008 involving trading of energy or energy transmission rights
• CPC Class Codes: H02J 3/04 for connecting networks of the same frequency but supplied from different sources
• CPC Class Codes: H02J 3/38 Arrangements for parallely feeding a single network by two or more generators, converters or transformers
• CPC Class Codes: Y02E 40/70 Smart grids as climate change mitigation technology in the energy generation sector
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 10/50 Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security
• CPC Class Codes: Y04S 50/10 Energy trading, including energy flowing from end-user application to grid

Abstract

Systems and methods for optimizing energy consumption in multi-energy sources sites are provided. These techniques include developing a real-time model and a virtual model of the electrical system of a multi-energy source site, such as a microgrid. The real-time model represents a current state of the electrical system can be developed by collecting data from sensors interfaced with the various components of the electrical system. The virtual model of the electrical system mirrors the real-time model of the electrical system and can be used to generate predictions regarding the performance, availability, and reliability of cost and reliability of various distributed energy sources and to predict the price of acquiring energy from these sources. The virtual model can be used to test “what if” scenarios, such as routine maintenance, system changes, and unplanned events that impact the utilization and capacity of the microgrid.

Claims

1-20. -20. (canceled)

21. A system for optimizing operation of an electric power system of multiple distributed energy sources, comprising:

a data acquisition component configured to acquire real-time output data from sensors interfaced with components of the electric power system;

an analytics server communicatively connected to the data acquisition component, comprising;

a virtual system modeling engine configured to generate simulated output data for the electric power system utilizing a first virtual system model of the electric power system;

an analytics engine configured to monitor the real-time output data and the simulated output data of the electric power system; and

a network optimization simulation engine configured to forecast the cost of operation and reliability and availability of various distributed energy sources in the electric power system and optimize the performance of the electric power system.

22. The system of claim 21, wherein the analytics engine further configured to initiate a calibration and synchronization operation to update the first virtual system model when a difference between the real-time output data and the simulated output data exceeds a threshold.

23. The system of claim 22, wherein the threshold is a Defined Difference Tolerance (DDT) value for at least one of the frequency deviation, voltage deviation, power factor deviation, and other deviations between the real-time output data and simulated output data.

24. The system of claim 21, wherein the network optimization simulation engine is further configured to receive modified operational parameters for the first virtual system model to create a second virtual system model and to forecast the cost of operation and the reliability and availability of various distributed energy sources operating under the modified parameters of the second virtual system model.

25. The system of claim 24, wherein the modified parameters include changing a mix of distributed energy sources being used to generate power for the electric power system.

26. The system of claim 24, wherein the modified parameters include changing an electricity output of a distributed energy source being used to generate power for the electric power system.

27. The system of claim 24, wherein the modified parameters include changing a mix of energy obtained from distributed energy sources of the electric power system and energy from energy sources outside of the electric power system.

28. The system of claim 24, further comprising a client terminal configured to allow a system administrator to modify the parameters of the first virtual system model when the network optimization simulation engine is operating in the scenario builder mode and display a report of the forecasted aspects.

29. The system of claim 28, wherein the forecasted cost of operation and reliability and availability of various distributed energy sources in the electric power system is communicated by way of graphics on a display interfaced with the client terminal.

30. The system of claim 28, wherein the forecasted cost of operation and reliability and availability of various distributed energy sources in the electric power system is communicated by way of text on a display interfaced with the client terminal.

31. The system of claim 28, wherein the forecasted cost of operation and reliability and availability of various distributed energy sources in the electric power system is communicated by way of synthesized speech generated by the client terminal.

32. A system for optimizing operation of an electric power system of multi-energy source sites, comprising:

a data acquisition component configured to acquire real-time output data from sensors interfaced with components of the electric power system;

an analytics server communicatively connected to the data acquisition component, comprising;

a virtual system modeling engine configured to generate simulated output data for the electric power system utilizing a first virtual system model of the electric power system;

an analytics engine configured to monitor the real-time output data and the simulated output data of the electric power system, the analytics engine further configured to initiate a calibration and synchronization operation to update the first virtual system model when a difference between the real-time output data and the simulated output data exceeds a threshold; and

a network optimization simulation engine configured to generate predicated data based on the updated first virtual system model with the one or more iteratively received modified operational parameters and identify an optimal operating configuration based on the predicted data.

33. The system of claim 32, wherein the threshold is a Defined Difference Tolerance (DDT) value for at least one of the frequency deviation, voltage deviation, power factor deviation, and other deviations between the real-time output data and simulated output data.

34. The system of claim 32, wherein the predicted data comprises predicted utilization, capacity, and reliability information.

35. The system of claim 32, wherein the network optimization simulation engine is further configured to create a second virtual model based on the updated first virtual model and the modified operational parameters.

36. The system of claim 35, the network optimization simulation engine is further configured to identifying an optimal operating configuration for the electric power system based on comparison of a first set of predicted data generated from the updated first virtual model and a second set of predicted data generated from the second virtual model to the real-time output data.

37. The system of claim 36, further comprising a client terminal configured to display the comparison.

38. The system of claim 37, wherein the client terminal is configured to display the comparison as a set of graphics on a display interface of the client terminal.

39. The system of claim 37, wherein the client terminal is configured to display the comparison as text on a display interface of the client terminal.

40. The system of claim 32, wherein the modified operational parameters include changing a mix of distributed energy sources being used to generate power for the electric power system.

41. The system of claim 32, wherein the modified operational parameters include changing an electricity output of a distributed energy source being used to generate power for the electric power system.

42. The system of claim 32, wherein the modified operational parameters include changing a mix of energy obtained from distributed energy sources of the electric power system and energy from energy sources outside of the electric power system.