Security constrained optimal power flow method

• US 6,775,597 B1
• Filed: 03/19/1999
• Issued: 08/10/2004
• Est. Priority Date: 05/13/1998
• Status: Expired due to Term

• Current Assignee: Siemens AG
• Original Assignee: Siemens Power Transmission & Distribution Incorporated (Siemens AG)
• Inventors: Ristanovic, Petar, Aganagic, Muhamed, Obadina, Oladiran
• Primary Examiner(s): Picard, Leo
• Assistant Examiner(s): FRANK, ELLIOT L
• Application Number:
  US09/273,148
• Time in Patent Office: 1,971 Days
• Field of Search: 700/293, 700/294, 700/297, 700/298, 703/2, 703/4, 703/18
• US Class Current: 700/293
• CPC Class Codes: G06F 17/11 for solving equations , e.g. nonlinear equations, general mathematical optimization problems optimization specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

A Security-Constrained Optimal Power Flow (SCOPF) process employing a quadratic programming (QP) primal-dual interior point (IP) solution method. The IP method efficiently solves practical SCOPF problems involving large numbers of contingencies and controls in preventive and preventive/corrective operating modes. An EMS system is described incorporating the inventive SCOPF process. The SCOPF process can be used in a variety of additional arrangements including a locational marginal pricing scheme and a power transmission rights auction system. An infeasibility detection method is also described.

Claims

1. A security-constrained optimal power flow (OPF) method of operating a power system, comprising the steps of:

determining power flows for a base case operation and at least one contingency case operation of the power system;

linearizing an optimal power flow (OPF) problem formulation;

linearizing incremental network models for the base case and the at least one contingency case;

determining a solution based on the linearized OPF problem and the linearized incremental network models;

determining incremental control variables;

updating control variables with the incremental control variables;

determining power flows for the base case and the at least one contingency case using the updated control variables;

comparing the incremental control variables to a preselected threshold value and if the incremental control variables exceed the threshold, then repeating the previous steps; and

controlling the power system in accordance with the control variables.

2. The method of claim 1, wherein the step of determining a solution includes performing a quadratic programming primal-dual interior point method.

3. The method of claim 1, wherein the step of determining a solution is based on a solution which prevents a violation under the at least one contingency case.

4. The method of claim 1, wherein the step of determining a solution is based on a solution which requires corrective action under the at least one contingency case.

5. The method of claim 1, comprising the step of determining locational marginal pricing.

6. The method of claim 1, comprising the step of detecting a solution infeasibility.

7. The method of claim 1, wherein the step of determining a solution includes respecting ramping constraints of power generating units.

8. A security-constrained optimal power flow (OPF) method of operating a power system, comprising the steps of:

determining power flows for a base case operation and at least one contingency case operation of the power system;

linearizing an optimal power flow (OPF) problem formulation;

linearizing incremental network models for the base case and the at least one contingency case;

determining a solution based on the linearized OPF problem and the linearized incremental network models, the solution requiring integrated preventive corrective action under the at least one contingency case;

determining incremental control variables;

updating control variables with the incremental control variables;

determining power flows for the base case and the at least one contingency case using the updated control variables;

comparing the incremental control variables to a preselected threshold value and if the incremental control variables exceed the threshold, then repeating the previous steps; and

controlling the power system in accordance with the control variables.

9. The method of claim 8, wherein the step of determining a solution includes performing a quadratic programming primal-dual interior point method.

10. The method of claim 8, wherein the step of determining a solution is based on a solution which prevents a violation under the at least one contingency case.

11. The method of claim 8, wherein the step of determining a solution is based on a solution which requires corrective action under the at least one contingency case.

12. The method of claim 8, comprising the step of determining locational marginal pricing.

13. The method of claim 8, comprising the step of detecting a solution infeasibility.

14. The method of claim 8, wherein the step of determining a solution includes respecting ramping constraints of power generating units.

15. A security-constrained optimal power flow (OPF) method of operating a power system, comprising the steps of:

determining power flows for a base case operation and at least one contingency case operation of the power system;

linearizing an optimal power flow (OPF) problem formulation;

linearizing incremental network models for the base case and the at least one contingency case;

determining a solution based on the linearized OPF problem and the linearized incremental network models, the solution requiring integrated preventive corrective action under the at least one contingency case;

determining incremental control variables;

updating control variables with the incremental control variables;

determining power flows for the base case and the at least one contingency case using the updated control variables;

repeating the previous steps if a convergence test has not been satisfied; and

controlling the power system in accordance with the control variables.

16. The method of claim 15, wherein the step of determining a solution includes performing a quadratic programming primal-dual interior point method.

17. The method of claim 15, wherein the step of determining a solution is based on a solution which prevents a violation under the at least one contingency case.

18. The method of claim 15, wherein the step of determining a solution is based on a solution which requires corrective action under the at least one contingency case.

19. The method of claim 15, comprising the step of detecting a solution infeasibility.

20. The method of claim 15, wherein the step of determining a solution includes respecting ramping constraints of power generating units.