System and method for monitoring and managing electrical power transmission and distribution networks

• US 7,979,239 B2
• Filed: 04/02/2009
• Issued: 07/12/2011
• Est. Priority Date: 11/06/2002
• Status: Active Grant

• Current Assignee: Aplicaciones En Informtica Avanzada, S.A.
• Original Assignee: Aplicaciones en Informática Avanzada, S.A.
• Inventors: Trias, Antonio
• Primary Examiner(s): West; Jeffrey R
• Application Number:
  US12/384,254
• Publication Number:
  US 20090228154A1
• Time in Patent Office: 831 Days
• Field of Search: 702/57, 702/60, 702/61, 702/62, 702/64, 702/65, 702/182, 702/183, 700/286, 700/291, 700/295, 307/103, 307/147, 703/3, 703/4, 703/13, 703/18
• US Class Current: 702/182
• CPC Class Codes: G01R 19/2513 Arrangements for monitoring electric power systems, e.g. power lines or loads; Logging
• CPC Class Codes: G01R 21/00 Arrangements for measuring electric power or power factor G01R7/12 takes precedence
• CPC Class Codes: G01R 35/00 Testing or calibrating of apparatus covered by the other groups of this subclass
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 3/00 Circuit arrangements for ac mains or ac distribution networks
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Abstract

A system and method for monitoring and managing electrical power transmission and distribution networks through use of a deterministic, non-iterative method using an holomorphic embedding and algebraic approximants for determining the real-time load flow in a power generating system having an electrical grid. Such method may be employed for real-time or off-line applications for electric power systems reliability assessment, and is capable of determining whether or not a physical solution to the load flow problem exists, or if the system is in a state of voltage collapse.

Claims

1. A computer implemented method of measuring load flow in a power generating system having an electrical grid, comprising the steps of:

a. generating a first mathematical model of a known, physical solution to load flow equations (L) representing the electrical grid in which all voltages are equal to a normal or designed voltage level, and there is no energy flow in links of the electrical grid, said first mathematical model comprising a holomorphic embedding of the load flow equations (L(s)), where s is a variable in a complex domain that includes a value s=0 corresponding to a no load case (L(0)), in which all voltages are equal to a normal or designed voltage level and there is no energy flow in links of the electrical grid, and wherein each variable of the load flow equations (L) is contained in L(s) as a function of the complex variable s by said holomorphic embedding;

b. transcribing the holomorphic embedding into software for use in a computer processor adapted to execute said software;

c. using analytical continuation in said computer processor to develop a second mathematical model from said first mathematical model, said second mathematical model being of a known, physical solution to the load flow equations (L(s)), where s includes a value s=1corresponding to a current load flow case (L(1)) corresponding to a physical solution to the load flow equations in the power generating system; and

d. displaying a representation of the second mathematical model, developed in step c, as a measure of the load flow in the power generating system.

2. The method of claim 1, wherein said step of using analytical continuation in said computer processor to develop a second mathematical model further comprises using said computer processor to develop a power series expansion of all quantities in the holomorphic embedding (L(s)) formed from said load flow equations (L) in a neighborhood of the value of each variable of the load flow equations (L) for the first mathematical model.

3. The method of claim 2, further comprising using, with said computer processor, algebraic approximants to determine a sum of all coefficients of said power series expansion for the load flow equations representative of current, physical load flow that is to be determined.

4. The method of claim 3, further comprising the steps of confirming that a set of voltages and flows contained in said physical solution to said load flow equations (L) are representative of a physical electrical state.

5. The method of claim 1, further comprising the steps of:

prior to said step of using analytical continuation in said computer processor to develop a second mathematical model, receiving data from a supervisory and data acquisition system representative of conditions of the electrical grid, and forming said load flow equations (L) from said data.

6. The method of claim 5, further comprising the steps of repeating said receiving step and steps a through d continuously to provide a continuous, real time measure of the load flow in the power generating system.

7. A system for measuring load flow in a power generating system having an electrical grid with n nodes, said system comprising:

a supervisory control and data acquisition system adapted to collect data from said electrical grid indicative of electrical conditions in said electrical grid, and

a microprocessor-controlled energy management system

said supervisory control and data acquisition system being in communication with the microprocessor-controlled energy management system, said microprocessor-controlled energy management system further comprising a program of instructions executable by said energy management system to;

a. process said data received from said supervisory control and data acquisition system into load flow equations (L) representing the electrical grid;

b. generate a first mathematical model of a known, physical solution to the load flow equations (L), said first mathematical model comprising a holomorphic embedding of the load flow equations (L(s)), where s is a variable in a complex domain that includes a value s=0corresponding to a no load case (L(0)), in which all voltages are equal to a normal or designed voltage level and there is no energy flow in links of the electrical grid, and wherein each variable of the load flow equations (L) is contained in L(s) as a function of the complex variable s by said holomorphic embedding; and

c. develop a second mathematical model from said first mathematical model, said second mathematical model being of a known, physical solution to the load flow equations (L(s)), where s includes a value s=1 corresponding to a current load flow case (L(1)) corresponding to a physical solution to the load flow equations in the power generating system.

8. The system of claim 7, said microprocessor-controlled energy management system further comprising executable computer instructions to:

develop the second mathematical model by using a power series expansion of all quantities in the holomorphic embedding (L(s)) formed from said load flow equations (L) in a neighborhood of the value of each variable of the load flow equations (L) for the first mathematical model.

9. The system of claim 8, said microprocessor-controlled energy management system further comprising executable computer instructions to:

use algebraic approximants to determine a sum of all coefficients of said power series expansion for the load flow equations representative of current, physical load flow that is to be determined.

10. The system of claim 9, said microprocessor-controlled energy management system further comprising executable computer instructions to:

confirm that a set of voltages and flows contained in said physical solution to said load flow equations (L) are representative of a physical electrical state.

11. A computer implemented method of estimating a state of stability of a power generating system having an electrical grid, comprising the steps of:

a. generating a mathematical model of the power generating system using a topology that describes all possible connectivity points of the electrical grid;

b. embedding load flow equations (L) representing the mathematical model in a holomorphic embedding (L(s)) where s is a variable in a complex domain that includes a value s=0 corresponding to a no load case (L(0)), in which all voltages are equal to a normal or designed voltage level and there is no energy flow in links of the electrical grid and the value s=1corresponding to an objective case (L(1)) representative of the electrical grid in a condition for which stability is to be determined, wherein each variable of the load flow equations (L) is contained in L(s) as a function of the complex variable s by said holomorphic embedding;

c. transcribing the holomorphic embedding from step b into software for use in a computer processor adapted to execute said software;

d. developing in power series, values of unknowns in parameters of the holomorphic embedding (L(s)), using said computer processor, wherein the values of s are in a neighborhood of the value for the no load case of each parameter of the load flow equations;

e. using said computer processor to compute an n-order algebraic approximant to the power series produced in step d;

f. evaluating, using said computer processor, the n-order algebraic approximant produced in step e for the power series produced in step d to provide a solution to the load flow equations (L);

g. receiving data from the connectivity points of the electrical grid;

h. calculating, using said computer processor, a solution to the load flow equations (L) using the data from the connectivity points of the electrical grid; and

i. displaying the solution to the load flow equations as a measure of a state of stability of the electrical grid.

12. The method of claim 11, wherein said step of receiving data from the connectivity points of the electrical grid comprises receiving data from a supervisory and data acquisition system representative of conditions of the electrical grid, and forming said load flow equations (L) from said data.

13. The method of claim 12, wherein said data includes loads, generations, voltages, flows, and states of circuit breakers.

14. The method of claim 11, after said step of receiving data from the connectivity points of the electrical grid, testing said data in order to make inferences on any missing information and quality of available measurements.

15. The method of claim 14, wherein said step of testing said data includes logical considerations about the connectivity points and the data received from the connectivity points of the electrical grid.

16. The method of claim 11, further comprising the steps of:

calculating, using said computer processor a quality parameter that expresses confidence in the data received from the connectivity points of the electrical grid.

17. The method of claim 16, wherein said quality parameter is calculated from a historical comparison between the data received from the connectivity points of the electrical grid and corresponding estimated values.

18. The method of claim 11, wherein said step of calculating a solution to the load flow equations (L) consists of computing a standard least square minimization on weighted differences between the data received from the connectivity points of the electrical grid and the solution to the load flow equations (L).

19. The method of claim 18, wherein said computation takes place using Gauss Seidel analysis.