Method and system for on-line dynamical screening of electric power system

• US 6,868,311 B2
• Filed: 04/22/2003
• Issued: 03/15/2005
• Est. Priority Date: 04/22/2002
• Status: Active Grant

• Current Assignee: Hsiao-Dong Chiang, Tokyo Electric Power Company Holdings, Incorporated (Nuclear Damage Compensation Decommissioning Facilitation Corp.)
• Original Assignee: Korea Electric Power Corporation (Government of South Korea), Hsiao-Dong Chiang
• Inventors: Koyanagi, Kaoru, Tada, Yasuyuki, Chiang, Hsiao-Dong, Kurita, Atsushi, Zhou, Yicheng, Okamoto, Hiroshi, Tanabe, Ryuya
• Primary Examiner(s): Picard, Leo
• Assistant Examiner(s): Frank, Elliot L
• Application Number:
  US10/419,939
• Publication Number:
  US 20030200010A1
• Time in Patent Office: 693 Days
• Field of Search: 700/286, 700292-294, 702/58
• US Class Current: 700/293
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 3/0012 Contingency detection
• CPC Class Codes: H02J 3/24 Arrangements for preventing or reducing oscillations of power in networks by control effected upon a single generator H02P9/00
• CPC Class Codes: H02J 3/388 Islanding, i.e. disconnection of local power supply from the network
• 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 for on-line dynamic screening of contingencies comprising postulated disturbances which an electric power system may experience, the system comprising a dynamic contingency screening program for evaluating a plurality of contingencies with a plurality of contingency classifiers based on the method of finding the controlling unstable equilibrium point of the power system known as the boundary of stability region based controlling unstable equilibrium point method by sequentially applying the contingencies to a network islanding problem classifier, S.E.P problem classifier, a large stability regions classifier, an exist point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a CUEP convergence problem classifier, and a controlling UEP (unstable equilibrium point) classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies, and a time-domain simulation program for determining which of the second group of contingencies are unstable.

Claims

1. A method for on-line dynamic screening of contingencies comprising postulated disturbances which an electric power system may experience, said method comprising steps of:

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies; and

determining which of said second group of contingencies are unstable.

2. The method of claim 1, wherein said step of applying said network islanding problem classifier further comprises screening out highly unstable contingencies which result in a network islanding problem.

3. The method of claim 1, wherein said step of applying said stable equilibrium point problem classifier further comprises computing a post-fault stable equilibrium point starting from a pre-fault stable equilibrium point to detect potentially unstable contingencies.

4. The method of claim 1, wherein said step of applying said large stability regions classifier further comprises screening out highly stable contingencies which result in a large stability region of an underlying post-fault stable equilibrium point.

5. The method of claim 1, wherein said step of applying said exit point problem classifier further comprises screening out potentially unstable contingencies which result in an exit point problem employing some dynamic information during an exit point search.

6. The method of claim 1, wherein said step of applying said ray adjustment problem classifier further comprises screening out potentially unstable contingencies using some dynamic information during a minimum gradient point search.

7. The method of claim 1, wherein said step of applying said energy function problem classifier further comprises an index using a property that energy functions decrease along system trajectories to check a condition whether or not, when a potential energy at a minimum gradient point, if the condition satisfies, is greater than a potential energy at an exit point, a corresponding contingency is identified as causing an energy function problem and is classified as unstable.

8. The method of claim 1, wherein said step of applying said controlling unstable equilibrium point convergence problem classifier further comprises detecting a following unstable equilibrium point convergence problem which a robust nonlinear equation solver, such as Newton method, diverges when it is applied to compute the controlling unstable equilibrium point starling from a minimum gradient point.

9. The method of claim 1, wherein said step of applying said controlling unstable equilibrium point classifier further comprises using an energy value at the controlling unstable equilibrium point as a critical energy to classify each remaining contingency into stable or unstable.

10. The method of claim 1, wherein

said step of applying said network islanding problem classifier further comprises screening out highly unstable contingencies which result in a network islanding problem,

said step of applying said stable equilibrium point problem classifier further comprises computing a post-fault stable equilibrium point starting from a pre-fault stable equilibrium point to detect potentially unstable contingencies,

said step of applying said large stability regions classifier further comprises screening out highly stable contingencies which result in a large stability region of an underlying post-fault stable equilibrium point,

said step of applying said exit point problem classifier further comprises screening out potentially unstable contingencies which result in an exit point problem employing some dynamic information during an exit point search,

said step of applying said ray adjustment problem classifier further comprises screening out potentially unstable contingencies based on some dynamic information during a minimum gradient point search,

said step of applying said energy function problem classifier further comprises an index for screening out potentially unstable contingencies based on a potential energy at a minimum gradient point and a potential energy at an exit point,

said step of applying said controlling unstable equilibrium point convergence problem classifier further comprises detecting an unstable equilibrium convergence problem which a robust numerical method diverges when it is applied to compute the controlling unstable equilibrium point starting from the minimum gradient point, and

said step of applying said controlling unstable equilibrium point classifier further comprises using an energy value at the controlling unstable equilibrium point as a critical energy to classify each remaining contingency into stable or unstable.

11. The method of claim 1, further comprising steps of:

computing a minimum gradient point of a contingency when the step of applying the ray adjustment problem classifier determines the contingency without deciding that the electric power system is stable or unstable;

setting a critical energy as an energy value at an exit point V_cr=V_ep and finding a corresponding fault-on time t_ep from a fault-on trajectory, when the minimum gradient point is not found;

performing a time domain simulation with t_ep being a fault clearing time, if the post-fault system is stable, then setting V_ep to be critical energy V_cr and stopping the process;

performing a time-domain simulation of the post-fault system with a state of the fault clearing time t_cl as an initial condition if the post-fault system is stable;

setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable, and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable;

interpolating between (t₀, t₁) using a Golden bisection-based interpolation method to find an instant, denoted as t⁽⁰⁾; and

performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and an energy value at a corresponding state as the critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between an interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

12. The method of claim 1, further comprising steps of:

computing a minimum gradient point of a contingency when the step of applying the energy function problem classifier determines the contingency without deciding that the electric power system is stable or unstable;

performing a time-domain simulation of a post-fault system with t_cl as an initial condition if the post-fault system is stable;

setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable, and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable;

interpolating between (t₀, t₁) using a Golden bisection-based interpolation method to find an instant, denoted as t⁽⁰⁾; and

performing a time domain simulation with t⁽⁰⁾ being a fault clearing time and treating t⁽⁰⁾ as a critical clearing time and an energy value at a corresponding state as a critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between an interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

13. The method of claim 1, further comprising steps of:

computing a minimum gradient point of a contingency when the step of applying the controlling unstable equilibrium point convergence problem classifier determines the contingency without deciding that the electric power system is stable or unstable;

setting a critical energy as an energy value at the minimum gradient point V_cr=V_mgp, and finding a corresponding fault-on time t_mgp from a fault-on trajectory, when the controlling unstable equilibrium point is not found;

performing a time domain simulation with t_mpg being the fault clearing time, setting V_mgp as the critical energy and stopping the process, when the post-fault system is stable;

perforating a time-domain simulation of the post-fault system with t_cl as the initial condition, and setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable;

interpolating between (t₀, t₁) using the Golden bisection-based interpolation method to find the instant, denoted as t⁽⁰⁾; and

performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and the energy value at the corresponding state as the critical energy and stopping the process if the post-fault system is stable, setting t₁=t⁽⁰⁾ and interpolating between the interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

14. A system for on-line dynamic screening of contingencies comprising postulated disturbances which an electric power system may experience, said system comprising:

a dynamic contingency screening program configured to evaluate a plurality of contingencies with a plurality of contingency classifiers based on a method of finding the controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies; and

a time-domain simulation program configured to determine which of said second group of contingencies are unstable.

15. The system of claim 14, wherein said network islanding problem classifier further comprises means for screening out highly unstable contingencies which result in a network islanding problem.

16. The system of claim 14, wherein said stable equilibrium point problem classifier further comprises means for computing a post-fault stable equilibrium point starting from a pre-fault stable equilibrium point to detect potentially unstable contingencies.

17. The system of claim 14, wherein said large stability regions classifier further comprises means for screening out highly stable contingencies which result in a large stability region of an underlying post-fault stable equilibrium point.

18. The system of claim 14, wherein said exit point problem classifier further comprises means for screening out potentially unstable contingencies which result in an exit point problem based on some dynamic information during an exit point search.

19. The system of claim 14, wherein said ray adjustment problem classifier further comprises means for screening out potentially unstable contingencies based on some dynamic information during a minimum gradient point search.

20. The system of claim 14, wherein said energy function problem classifier further comprises means for screening out potentially unstable contingencies based on a potential energy at a minimum gradient point is and a potential energy at an exit point.

21. The system of claim 14, wherein said controlling unstable equilibrium point convergence problem classifier further comprises means for detecting an Unstable Equilibrium Point convergence problem which a robust numerical method diverges when it is applied to compute the controlling unstable equilibrium point starting from a minimum gradient point.

22. The system of claim 14, wherein said controlling UEP classifier further comprises means for classifying each remaining contingency into stable or unstable by using an energy value at the controlling unstable equilibrium point as a critical energy.

23. The system of claim 14, wherein

said network islanding problem classifier further comprises means for screening out highly unstable contingencies which result in a network islanding problem;

said stable equilibrium point problem classifier further comprises means for computing a post-fault stable equilibrium point starting from a pre-fault stable equilibrium point to detect potentially unstable contingencies;

said large stability regions classifier further comprises means for screening out highly stable contingencies which result in a large stability region of an underlying post-fault stable equilibrium point;

said exit point problem classifier further comprises means for screening out potentially unstable contingencies which result in an exit point problem based on some dynamic information during an exit point search;

said ray adjustment problem classifier further comprises means for screening out potentially unstable contingencies based on some dynamic information during a minimum gradient point search;

said energy function problem classifier further comprises means for screening out potentially unstable contingencies on a potential energy at a minimum gradient point and a potential energy at an exit point;

said controlling unstable equilibrium point convergence problem classifier further comprises means for detecting an Unstable Equilibrium Point convergence problem which a robust numerical method diverges when it is applied to compute the controlling unstable equilibrium point starting from a minimum gradient point; and

said controlling UEP classifier further comprises means for classifying each remaining contingency into stable or unstable by using energy value at the controlling unstable equilibrium point as a critical energy.

24. An on-line dynamic security assessment system adapted to perform an on-line dynamic screening of contingencies comprising postulated disturbances which an electric power system may experience, said assessment system comprising the system of any one of claims 14-23.

25. An energy management system adapted to perform an on-line dynamic screening of contingencies comprising postulated disturbances which an electric power system may experience, said management system comprising the system of any one of claims 14-23.

26. A BCU guided time-domain method which inputs a power system with related data for dynamic security assessment and a contingency and outputs a stability assessment and energy margin value for the contingency on the power system, comprising the steps of:

applying a boundary of stability region based controlling unstable equilibrium point method to compute an exit point; and

declaring the stability assessment to be highly stable and assigning a large value of the energy margin for a post-fault system if the computed exit point is not found within a predetermined time interval and if the energy value at an end point of the predetermined time interval is positive.

27. The method of claim 26, further comprising steps of:

computing a minimum gradient point;

setting a critical energy as an energy value at an exit point V_cr=V_ep, and finding a corresponding fault-on time t_ep from a fault-on trajectory, when the minimum gradient point is not found;

performing a time domain simulation with t_ep being a fault clearing time, if the post-fault system is stable, then setting V_ep to be critical energy V_cr and stopping the process;

performing a time-domain simulation of the post-fault system with a state of the fault clearing time t_cl as an initial conditions if the post-fault system is stable;

setting t₀=t_cl and t₁=t_ep, when the post-fault system is stable, and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable;

interpolating between (t₀, t₁) using a Golden bisection-based interpolation method to find an instant, denoted as t⁽⁰⁾; and

performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and an energy value at a corresponding state as the critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between an interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

28. The method of claim 27, further comprising steps of:

computing a controlling unstable equilibrium point;

setting a critical energy as an energy value at the minimum gradient point V_cr=V_mgp, and finding a corresponding fault-on time t_mgp from a fault on trajectory, when the controlling unstable equilibrium point is not found;

performing a time domain simulation with t_mgp being the fault clearing time, if the post-fault system is stable, then setting V_mgp was the critical energy and stopping the process;

performing a time-domain simulation of the post-fault system with state at fault-clearing time t_cl as the initial condition if the post-fault system is stable, then setting t₀=t_cl and t₁=t_mgp, otherwise, setting t₀=0 and t₁=t_cl;

interpolating between (t₀, t₁) using the Golden bisection-based interpolation method to find the instant, denoted as t⁽⁰⁾; and

perform performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and the energy value at the corresponding state as the critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between the interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

29. The method of claim 27 or 28, wherein the Golden bisection-based interpolation method comprises steps of:

using the Golden bisection method to calculate two fault clearing time instants from an interval [t₁, t₂], such that

t₀⁽¹⁾=0.168t₁+0.382t₂ and t₀⁽²⁾=0.168t₂+0.382t₁;

performing a time-domain stability analysis of the contingency with the fault clearing time t₀⁽¹⁾, and setting t₂=t₀⁽¹⁾ if the post-fault system is unstable and setting t₁=t₀⁽¹⁾ if the post-fault system is stable;

performing a time-domain stability analysis of the contingency with the fault clearing time t₀⁽²⁾, and setting t₁=t₀⁽²⁾, if the post-fault system is stable and setting t₂=t₀⁽²⁾ if the post-fault system is not stable;

checking convergence, if ∥

t₁−

t₂∥

≦

ε

, go to a following step, otherwise go to the using step; and

setting the critical clearing time as t₁ and setting the system energy at the critical clearing time as the critical energy.

30. An on-line dynamic security assessment system adapted to perform an on-line screening of contingencies comprising postulated disturbances which an electric power system may experience, said assessment system being configured to perform steps of:

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies; and

determining which of said second group of contingencies are unstable.

31. The assessment system of claim 30, wherein said step of applying said network islanding problem classifier further comprises screening out highly unstable contingencies which result in a network islanding problem.

32. The assessment system of claim 30, wherein said step of applying said stable equilibrium point problem classifier further comprises computing a post-fault stable equilibrium point starting from a pre-fault stable equilibrium point to detect potentially unstable contingencies.

33. The assessment system of claim 30, wherein said step of applying said large stability regions classifier further comprises screening out highly stable contingencies which result in a large stability region of an underlying post-fault stable equilibrium point.

34. The assessment system of claim 30, wherein said step of applying said exit point problem classifier further comprises screening out potentially unstable contingencies which result in an exit point problem employing some dynamic information during an exit point search.

35. The assessment system of claim 30, wherein said step of applying said ray adjustment problem classifier further comprises screening out potentially unstable contingencies based on some dynamic information during a minimum gradient point search.

36. The assessment system of claim 30, wherein said step of applying said energy function problem classifier further comprises an index using a property that energy functions decrease along method trajectories, when a potential energy at a minimum gradient point is greater than a potential energy at an exit point, a corresponding contingency is identified as causing an energy function problem and is classified as unstable.

37. The assessment system of claim 30, wherein said step of applying said controlling unstable equilibrium point convergence problem classifier further comprises detecting a following unstable equilibrium point convergence problem, when a robust numerical method diverges when it is applied to compute the controlling unstable equilibrium point starting from a minimum gradient point.

38. The assessment system of claim 30, wherein said step of applying said controlling unstable equilibrium point classifier further comprises using an energy value at the controlling unstable equilibrium point as a critical energy to classify each remaining contingency into stable or unstable.

39. The assessment system of claim 30, wherein

said step of applying said network islanding problem classifier further comprises screening out highly unstable contingencies which result in a network islanding problem,

said step of applying said stable equilibrium point problem classifier further comprises computing a post-fault stable equilibrium point starting from a pre-fault stable equilibrium point to detect potentially unstable contingencies,

said step of applying said large stability regions classifier further comprises screening out highly stable contingencies which result in a large stability region of an underlying post-fault stable equilibrium point,

said step of applying said exit point problem classifier further comprises screening out potentially unstable contingencies which result in an exit point problem employing some dynamic information during an exit point search,

said step of applying said ray adjustment problem classifier further comprises screening out potentially unstable contingencies based on some dynamic information during a minimum gradient point search,

said step of applying said energy function problem classifier further comprises an index using a property that energy functions decrease along method trajectories, when a potential energy at a minimum gradient point is greater than a potential energy at an exit point, a corresponding contingency is identified as causing an energy function problem and is classified as unstable,

said step of applying said controlling unstable equilibrium point convergence problem classifier further comprises detecting a following unstable equilibrium point convergence problem, when a robust numerical method diverges when it is applied to compute the controlling unstable equilibrium point starting from the minimum gradient point, and

said step of applying said controlling unstable equilibrium point classifier further comprises using an energy value at the controlling unstable equilibrium point as a critical energy to classify each remaining contingency into stable or unstable.

40. An energy management system adapted to perform an on-line dynamic screening of contingencies comprising postulated disturbances which an electric power system may experience, said management system comprising steps of:

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies; and

determining which of said second group of contingencies are unstable.

41. The energy management system of claim 40, wherein said step of applying said network islanding problem classifier further comprises screening out highly unstable contingencies which result in a network islanding problem.

42. The energy management system of claim 40, wherein said step of applying said stable equilibrium point problem classifier further comprises computing a post-fault stable equilibrium point starting from a pre-fault stable equilibrium point to detect potentially unstable contingencies.

43. The energy management system of claim 40, wherein said step of applying said large stability regions classifier further comprises screening out highly stable contingencies which result in a large stability region of an underlying post-fault stable equilibrium point.

44. The energy management system of claim 40, wherein said step of applying said exit point problem classifier further comprises screening out potentially unstable contingencies which result in an exit point problem employing some dynamic information during an exit point search.

45. The energy management system of claim 40, wherein said step of applying said ray adjustment problem classifier further comprises screening out potentially unstable contingencies using some dynamic information during a minimum gradient point search.

46. The energy management system of claim 40, wherein said step of applying said energy function problem classifier further comprises an index using a property that energy functions decrease along system trajectories to check a condition whether or not, when a potential energy at a minimum gradient point, if the condition satisfies, is greater than a potential energy at an exit point, a corresponding contingency is identified as causing an energy function problem and is classified as unstable.

47. The energy management system of claim 40, wherein said step of applying said controlling unstable equilibrium point convergence problem classifier further comprises detecting a following unstable equilibrium point convergence problem which a robust nonlinear equation solver, such as Newton method, diverges when it is applied to, compute the controlling unstable equilibrium point starting from a minimum gradient point.

48. The energy management system of claim 40, wherein said step of applying said controlling unstable equilibrium point classifier further comprises using an energy value at the controlling unstable equilibrium point as a critical energy to classify each remaining contingency into stable or unstable.

49. The energy management system of claim 40, wherein

said step of applying said network islanding problem classifier further comprises screening out highly unstable contingencies which result in a network islanding problem,

said step of applying said stable equilibrium point problem classifier further comprises computing a post-fault stable equilibrium point starting from a pre-fault stable equilibrium point to detect potentially unstable contingencies,

said step of applying said large stability regions classifier further comprises screening out highly stable contingencies which result in a large stability region of an underlying post-fault stable equilibrium point,

said step of applying said exit point problem classifier further comprises screening out potentially unstable contingencies which result in an exit point problem employing some dynamic information during an exit point search,

said step of applying said ray adjustment problem classifier further comprises screening out potentially unstable contingencies based on some dynamic information during a minimum gradient point search,

said step of applying said energy function problem classifier further comprises an index for screening out potentially unstable contingencies based on a potential energy at a minimum gradient point and a potential energy at an exit point,

said step of applying said controlling unstable equilibrium point convergence problem classifier further comprises detecting an unstable equilibrium point convergence problem which a robust numerical method diverges when it is applied to compute the controlling unstable equilibrium point starting from the minimum gradient point, and

said step of applying said controlling unstable equilibrium point classifier further comprises using an energy value at the controlling unstable equilibrium point as a critical energy to classify each remaining contingency into stable or unstable.

50. A system for planning an electric power system, the system comprising:

a provider configured to provide construction plans with an electric power system and a contingency list of the electric power system;

a BCU DSA system;

a detailed simulation system configured to perform a detailed simulation in accordance with an operation result of the BCU-DSA system,

wherein said BCU-DSA system is configured in accordance with any one of the construction plans and the contingency list to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable,

computing a minimum gradient point of a contingency when the step of applying the ray adjustment problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

setting a critical energy as an energy value at an exit point V_cr=V_ep, and finding a corresponding fault-on time t_ep from a fault-on trajectory, when the minimum gradient point is not found,

performing a time domain simulation with t_ep being a fault clearing time, if the post-fault system is stable, then setting V_ep to be critical energy V_cr and stopping the process,

performing a time-domain simulation of the post-fault system with a state of the fault clearing time t_cl as an initial condition if the post-fault system is stable, setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable, and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using a Golden bisection-based interpolation method to find an instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and an energy value at a corresponding state as the critical energy and slopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between an interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

51. A system for planning an electric power system, the system comprising:

a provider configured to provide construction plans with an electric power system and a contingency list of the electric power system;

a BCU-DSA system;

a detailed simulation system configured to perform a detailed simulation in accordance with an operation result of the BCU-DSA system,

wherein said BCU-DSA system is configured in accordance with any one of the construction plans and the contingency list to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable,

computing a minimum gradient point of a contingency when the step of applying the energy function problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

performing a time-domain simulation of a post-fault system with t_cl as an initial condition, if the post-fault system is stable,

setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable, and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using a Golden bisection-based interpolation method to find an instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being a fault clearing time and treating t⁽⁰⁾ as a critical clearing time and an energy value at a corresponding state as a critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between an interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

52. A system for planning an electric power system, the system comprising:

a provider configured to provide construction plans with an electric power system and a contingency list of the electric power system;

a BCU-DSA system;

a detailed simulation system configured to perform a detailed simulation in accordance with an operation result of the BCU-DSA system,

wherein said BCU-DSA system is configured in accordance with any one of the construction plans and the contingency list to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable, computing a minimum gradient point of a contingency when the step of applying the controlling unstable equilibrium point convergence problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

setting a critical energy as an energy value at the minimum gradient point V_cr=V_mgp, and finding a corresponding fault-on time t_mgp from a fault-on trajectory, when the controlling unstable equilibrium point is not found,

performing a time domain simulation with t_mgp being the fault clearing time, setting V_mgp as the critical energy and stopping the process when the post-fault system is stable,

performing a time-domain simulation of the post-fault system with t_cl as the initial condition, and setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using the Golden bisection-based interpolation method to find the instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and the energy value at the corresponding state as the critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between the interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

53. A system for analyzing an electric power system, the system comprising:

an acquisition system configured to acquire an information of the electric power system;

an energy management system configured to perform an energy management of the electric power system and configured to estimate an energy flow of the electric power system;

a database configured to store the energy flow estimated by the energy management system; and

a BCU-DSA system configured in accordance with the energy flow stored by the database and a contingency list to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable,

computing a minimum gradient point of a contingency when the step of applying the ray adjustment problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

setting a critical energy as an energy value at an exit point V_cr=V_ep, and finding a corresponding fault-on time t_ep from a fault-on trajectory, when the minimum gradient point is not found,

performing a time domain simulation with t_ep being a fault clearing time, if the post-fault system is stable, then setting V_ep to be critical energy V_cr and stopping the process,

performing a time-domain simulation of the post-fault system with a state of the fault clearing time t_cl as an initial condition if the post-fault system is stable,

setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable, and selling t₀=0 and t₁=t_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using a Golden bisection-based interpolation method to find an instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and an energy value at a corresponding state as the critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between an interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

54. A system for analyzing an electric power system, the system comprising:

an acquisition system configured to acquire an information of the electric power system;

an energy management system configured to perform an energy management of the electric power system and configured to estimate an energy flow of the electric power system;

a database configured to store the energy flow estimated by the energy management system; and

a BCU-DSA system configured in accordance with the energy flow stored by the database and a contingency list to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable,

computing a minimum gradient point of a contingency when the step of applying the energy function problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

performing a time-domain simulation of a post-fault system with t_cl as an initial condition, if the post-fault system is stable,

setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable, and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using a Golden bisection-based interpolation method to find an instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being a fault clearing time and treating t⁽⁰⁾ as a critical clearing time and an energy value at a corresponding state as a critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between an interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

55. A system for analyzing an electric power system, the system comprising:

an acquisition system configured to acquire an information of the electric power system;

an energy management system configured to perform an energy management of the electric power system and configured to estimate an energy flow of the electric power system;

a database configured to store the energy flow estimated by the energy management system; and

a BCU-DSA system configured in accordance with the energy flow stored by the database and a contingency list to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable,

computing a minimum gradient point of a contingency when the step of applying the controlling unstable equilibrium point convergence problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

setting a critical energy as an energy value at the minimum gradient point V_cr=V_mgp, and finding a corresponding fault-on time t_mgp from a fault-on trajectory, when the controlling unstable equilibrium point is not found,

performing a time domain simulation with t_mgp being the fault clearing time, setting V_mgp as the critical energy and stopping the process when the post-fault system is stable,

performing a time-domain simulation of the post-fault system with t_cl as the initial condition, and setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable and setting t₀=0 and t₁=_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using the Golden bisection-based interpolation method to find the instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and the energy value at the corresponding state as the critical energy and slopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between the interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

56. A system for operating an electric power system, the system comprising:

an acquisition system configured to acquire an information of the electric power system;

an energy management system configured to perform an energy management of the electric power system and configured to estimate an energy flow of the electric power system; and

a BCU-DSA system associated to the energy management system configured to calculate an energy margin index of the electric power system which utilizes a redistributing instruction of generator output of the electric power system, and configured to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable,

computing a minimum gradient point of a contingency when the step of applying the ray adjustment problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

setting a critical energy as an energy value at an exit point V_cr=V_ep, and finding a corresponding fault-on time t_ep from a fault-on trajectory, when the minimum gradient point is not found,

performing a time domain simulation with t_ep being a fault clearing time, if the post-fault system is stable, then setting V_ep to be critical energy V_cr and stopping the process,

performing a time-domain simulation of the post-fault system with a state of the fault clearing time t_cl as an initial condition if the post-fault system is stable,

setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable, and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using a Golden bisection-based interpolation method to find an instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and an energy value at a corresponding state as the critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between an interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

57. A system for operating an electric power system, the system comprising:

an acquisition system configured to acquire an information of the electric power system;

an energy management system configured to perform an energy management of the electric power system and configured to estimate an energy flow of the electric power system; and

a BCU-DSA system associated to the energy management system configured to calculate an energy margin index of the electric power system which utilizes a redistributing instruction of generator output of the electric power system, and configured to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable,

computing a minimum gradient point of a contingency when the step of applying the energy function problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

performing a time-domain simulation of a post-fault system with t_cl as an initial condition, if the post-fault system is stable,

setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable, and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using a Golden bisection-based interpolation method to find an instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being a fault clearing time and treating t⁽⁰⁾ as a ethical clearing time and an energy value at a corresponding state as a critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between an interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

58. A system for operating an electric power system, the system comprising:

an acquisition system configured to acquire an information of the electric power system;

an energy management system configured to perform an energy management of the electric power system and configured to estimate an energy flow of the electric power system; and

a BCU-DSA system associated to the energy management system configured to calculate an energy margin index of the electric power system which utilizes a redistributing instruction of generator output of the electric power system, and configured to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable,

computing a minimum gradient point of a contingency when the step of applying the controlling unstable equilibrium point convergence problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

setting a critical energy as an energy value at the minimum gradient point V_cr=V_mgp, and finding a corresponding fault on time t_mgp from a fault-on trajectory, when the controlling unstable equilibrium point is not found,

performing a time domain simulation with t_mgp being the fault clearing time, setting V_mgp the critical energy and slopping the process when the post-fault system is stable,

performing a time-domain simulation of the post-fault system with t_cl as the initial condition, and setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using the Golden bisection-based interpolation method to find the instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and the energy value at the corresponding state as the critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between the interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

59. An information system for a market of an electric power system, the information system comprising:

an acquisition system configured to acquire an information of the electric power system;

an energy management system configured to perform an energy management of the electric power system and configured to estimate an energy flow of the electric power system; and

a BCU-DSA system associated to the energy management system configured to calculate an energy margin index of the electric power system which utilizes a market of an electric power and a redistributing instruction of generator output of the electric power system, and configured to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable,

computing a minimum gradient point of a contingency when the step of applying the ray adjustment problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

setting a critical energy as an energy value at an exit point V_cr=V_ep, and finding a corresponding fault-on time t_ep from a fault-on trajectory, when the minimum gradient point is not found,

performing a time domain simulation with t_ep being a fault clearing time, if the post-fault system is stable, then setting V_ep to be critical energy V_cr and slopping the process,

performing a time-domain simulation of the post-fault system with a state of the fault clearing time t_cl as an initial condition if the post-fault system is stable,

setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable, and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using a Golden bisection-based interpolation method to find an instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and an energy value at a corresponding state as the critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between an interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

60. An information system for a market of an electric power system, the information system comprising:

an acquisition system configured to acquire an information of the electric power system;

an energy management system configured to perform an energy management of the electric power system and configured to estimate an energy flow of the electric power system; and

a BCU-DSA system associated to the energy management system configured to calculate an energy margin index of the electric power system which utilizes a market of an electric power and a redistributing instruction of generator output of the electric power system, and configured to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable,

computing a minimum gradient point of a contingency when the step of applying the energy function problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

performing a time-domain simulation of a post-fault system with t_cl as an initial condition, if the post-fault system is stable,

setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable, and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using a Golden bisection-based interpolation method to find an instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being a fault clearing time and treating t⁽⁰⁾ as a critical clearing lime and an energy value at a corresponding state as a critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between an interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.

61. An information system for a market of an electric power system, the information system comprising:

an acquisition system configured to acquire an information of the electric power system;

an energy management system configured to perform an energy management of the electric power system and configured to estimate an energy flow of the electric power system; and

a BCU-DSA system associated to the energy management system configured to calculate an energy margin index of the electric power system which utilizes a market of an electric power and a redistributing instruction of generator output of the electric power system, and configured to perform steps of

evaluating a plurality of contingencies with a plurality of contingency classifiers based on a method of finding a controlling unstable equilibrium point of said power system known as a boundary of stability region based controlling unstable equilibrium point method by sequentially applying said contingencies to a network islanding problem classifier, a stable equilibrium point problem classifier, a large stability regions classifier, an exit point problem classifier, a ray adjustment problem classifier, an energy function problem classifier, a controlling unstable equilibrium point convergence problem classifier, and a controlling unstable equilibrium point classifier to form a first group of stable contingencies and a second group of unstable or undecided contingencies,

determining which of said second group of contingencies are unstable,

computing a minimum gradient point of a contingency when the step of applying the controlling unstable equilibrium point convergence problem classifier determines the contingency without deciding that the electric power system is stable or unstable,

setting a critical energy as an energy value at the minimum gradient point V_cr=V_mgp, and finding a corresponding fault-on time t_mgp from a fault-on trajectory, when the controlling unstable equilibrium point is not found,

performing a time domain simulation with t_mgp being the fault clearing time, setting V_mgp as the critical energy and stopping the process when the post-fault system is stable,

performing a time-domain simulation of the post-fault system with as the initial condition, and setting t₀=t_cl and t₁=t_mgp, when the post-fault system is stable and setting t₀=0 and t₁=t_cl, when the post-fault system is not stable,

interpolating between (t₀, t₁) using the Golden bisection-based interpolation method to find the instant, denoted as t⁽⁰⁾, and

performing a time domain simulation with t⁽⁰⁾ being the fault clearing time and treating t⁽⁰⁾ as the critical clearing time and the energy value at the corresponding state as the critical energy and stopping the process if the post-fault system is stable, and setting t₁=t⁽⁰⁾ and interpolating between the interval (t₀, t⁽⁰⁾) if the post-fault system is not stable.