Search

CN-122026341-A - Rapid assessment method and system for ultra-short-term transient stability risk of power system

CN122026341ACN 122026341 ACN122026341 ACN 122026341ACN-122026341-A

Abstract

The invention discloses a method and a system for rapidly evaluating the ultra-short-term transient stability risk of a power system, wherein the method comprises the steps of determining a clustered expected fault subset according to the latest evaluation result of the transient stability margin and the source load influence degree under the expected fault; the method comprises the steps of determining critical expected faults of all subsets according to transient stability margin, determining the random source load ultrashort-period active power corresponding to all the critical expected faults according to the random source load ultrashort-period confidence interval and the transient stability and fixation loudness, combining an ultrashort-period planned running state and an automatic power generation control/automatic voltage control strategy to generate a system ultrashort-period risk running state corresponding to all the critical expected faults, and determining the ultrashort-period transient stability risk of a power system through transient stability assessment of the critical expected faults under the state. Corresponding systems are also disclosed. According to the method, the short-term transient stability risk rapid assessment considering the source load randomness is realized by identifying the key expected faults and the corresponding high-risk running states in the short-term period.

Inventors

  • XU TAISHAN
  • WU FENG
  • REN XIANCHENG
  • BAO YANHONG
  • ZHANG JINLONG
  • XU WEI
  • DU XUN

Assignees

  • 国电南瑞科技股份有限公司
  • 南瑞集团有限公司

Dates

Publication Date
20260512
Application Date
20241107

Claims (10)

  1. 1. The quick assessment method for the ultra-short-term transient stability risk of the power system is characterized by comprising the following steps of: step 1, clustering the predicted faults in a predicted fault set according to the latest evaluation results of the transient stability margin and the source load influence degree under the predicted faults, and determining a clustered transient stability predicted fault subset; Step 2, determining key expected faults corresponding to each expected fault subset according to the transient stability margin under the expected faults, and obtaining a key expected fault set with transient stability; step 3, determining the ultrashort-period active power of the random source load corresponding to each key expected fault in the transient stability key expected fault set according to the ultrashort-period confidence interval of the random source load and the influence degree of the ultrashort-period confidence interval on the transient stability under the key expected faults; Step 4, generating an ultra-short-term risk operation state of the power system corresponding to each key expected fault in the transient stability key expected fault set according to the ultra-short-term plan operation state, the random source load ultra-short-term active power corresponding to the key expected fault, and an automatic power generation control and automatic voltage control strategy; Aiming at each key expected fault in the key expected fault set of the transient stability, respectively carrying out transient stability evaluation under the key expected faults according to the ultra-short-term risk operation state of the power system corresponding to the key expected fault; And 6, determining the ultra-short-term transient stability risk of the power system according to the transient stability evaluation result.
  2. 2. The method for rapidly assessing the risk of ultra-short-term transient stability of a power system according to claim 1, wherein the transient stability comprises transient power angle stability, transient high-voltage stability, transient low-voltage stability, transient high-frequency stability and transient low-frequency stability; The transient stability margin comprises a transient power angle stability margin, each preset node transient high voltage stability margin for investigating transient high voltage stability, each preset node transient low voltage stability margin for investigating transient low voltage stability, each preset node transient high frequency stability margin for investigating transient high frequency stability and each preset node transient low frequency stability margin for investigating transient low frequency stability; The source load influence degree refers to influence degree of power supply and load of each node of an access power grid on transient power angle stability, and refers to influence degree of power supply and load of each node of the access power grid on transient high-voltage stability, transient low-voltage stability, transient high-frequency stability and transient low-frequency stability of each preset node for investigating transient high-voltage stability, transient low-voltage stability of each preset node for investigating transient low-voltage stability, transient high-frequency stability of each preset node for investigating transient high-frequency stability and transient low-frequency stability of each preset node for investigating transient low-frequency stability.
  3. 3. The method for rapidly assessing the risk of ultra-short-term transient stability of a power system according to claim 2, wherein the step 1 specifically comprises the following steps: determining an expected fault subset of transient power angle stability after clustering by solving the following formula: Wherein F is an expected failure set, N a is the number of expected failure subsets of transient power angle stability after clustering, F a.n is the nth expected failure subset of transient power angle stability after clustering, I n is a source load union with the ratio of the absolute value of the transient power angle stability influence degree under the expected failure in F a.n to the maximum value in the absolute value of the transient power angle stability influence degree under the expected failure in F a.n being larger than r a , r a is a set parameter, lambda a.f.i is the influence degree of a power supply or load I under the expected failure F on the transient power angle stability, epsilon a is a set parameter; Determining an expected fault subset of transient high voltage stability after clustering by solving the following formula: wherein F is an expected failure set, N vu is the number of expected failure subsets of transient high voltage stability after clustering, F vu.n is the nth expected failure subset of transient high voltage stability after clustering, B vu.n is a node union set with a transient high voltage stability margin smaller than η vu.cr in F vu.n , η vu.cr and α are set parameters, α is greater than 0, η vu.b,f is a transient high voltage stability margin of node B in F expected failure, J n.b is a set of power and load components with a ratio of a transient high voltage stability loudness of node B in F vu.n to a maximum value of a transient high voltage stability loudness of node B in F vu.n greater than r vu , r vu is a set parameter, λ vu.b.f.j is a transient high voltage stability loudness of power or load J to node B in F expected failure, and ε vu is a set parameter; determining an expected fault subset of transient low voltage stability after clustering by solving the following formula: Wherein F is an expected failure set, N vd is the number of expected failure subsets of transient low voltage stability after clustering, F vd.n is the nth expected failure subset of transient low voltage stability after clustering, B vd.n is a node union set with an expected failure transient low voltage stability margin smaller than η vd.cr in F vd.n , η vd.cr and α are set parameters, α is greater than 0, η vd.b,f is an expected failure transient low voltage stability margin of node B in F vd.n , K n.b is a set of power and load components with a ratio of the expected failure transient low voltage stability loudness to node B in F vd.n to the maximum value of the expected failure transient low voltage stability loudness to node B in F vd.n greater than r vd , r vd is a set parameter, λ vd.b.f.j is an expected failure transient low voltage stability loudness of power or load K to node B, and ε vd is a set parameter; determining an expected fault subset of transient high-frequency stability after clustering by solving the following formula: Wherein F is an expected failure set, N fu is the number of expected failure subsets of transient high-frequency stabilization after clustering, F fu.n is the nth expected failure subset of transient high-frequency stabilization after clustering, B fu.n is a node union set with a transient high-frequency stabilization margin smaller than η fu.cr in F fu.n , η fu.cr and α are set parameters, α is greater than 0, η fu.b,f is a transient high-frequency stabilization margin of node B in expected failure F, L n.b is a set of power and load components with a ratio of the transient high-frequency stabilization loudness of node B in expected failure to the maximum value of the transient high-frequency stabilization loudness of node B in expected failure F fu.n greater than r fu , r fu is a set parameter, λ fu.b.f.l is the transient high-frequency stabilization loudness of power or load L to node B in expected failure F, and ε fu is a set parameter; Determining an expected fault subset of transient low frequency stability after clustering by solving the following formula: Where F is an expected failure set, N fd is the number of transient low-frequency stable expected failure subsets after clustering, F fd.n is the nth expected failure subset after clustering, B fd.n is a node union set where the transient low-frequency stability margin under expected failure is smaller than η fd.cr in F fd.n , η fd.cr and α are set parameters, α is greater than 0, η fd.b,f is the transient low-frequency stability margin of node B under expected failure, M n.b is a set of power and load components where the ratio of the transient low-frequency stable fixed loudness to node B under expected failure in F fd.n to the maximum value in the transient low-frequency stable fixed loudness to node B under expected failure in F fd.n is greater than r fd , r fd is a set parameter, λ fd.b.f.m is the transient low-frequency stable fixed loudness of power or load M to node B under expected failure, and epsilon fd is a set parameter.
  4. 4. The method for rapidly assessing risk of ultra-short-term transient stability of a power system according to claim 2, wherein said step 2 comprises the steps of: Aiming at each predicted fault subset of the clustered transient power angle stability, respectively taking the predicted fault corresponding to the minimum value of the transient power angle stability margin as a key predicted fault corresponding to each predicted fault subset, and taking a set formed by all key predicted faults as a key predicted fault set corresponding to the transient power angle stability; Aiming at all the predicted fault subsets of the clustered transient high voltage stability, respectively taking the predicted fault corresponding to the minimum value of the node transient high voltage stability margin as the key predicted fault corresponding to each predicted fault subset, and taking the set consisting of all the key predicted faults as the key predicted fault set corresponding to the transient high voltage stability; Aiming at all the predicted fault subsets of the clustered transient low voltage stability, respectively taking the predicted fault corresponding to the minimum value of the node transient low voltage stability margin as the key predicted fault corresponding to each predicted fault subset, and taking the set consisting of all the key predicted faults as the key predicted fault set corresponding to the transient low voltage stability; aiming at each predicted fault subset of the clustered transient high-frequency stability, respectively taking the predicted fault corresponding to the minimum value of the node transient high-frequency stability margin as a key predicted fault corresponding to each predicted fault subset, and taking a set formed by all key predicted faults as a key predicted fault set corresponding to the transient high-frequency stability; Aiming at all the predicted fault subsets of the clustered transient low frequency stability, the predicted faults corresponding to the minimum value of the node transient low frequency stability margin are respectively used as key predicted faults corresponding to all the predicted fault subsets, and the set consisting of all the key predicted faults is used as the key predicted fault set corresponding to the transient low frequency stability.
  5. 5. The method for rapidly assessing risk of ultra-short-term transient stability of a power system according to claim 2, wherein said step 3 comprises the steps of: Aiming at each key expected fault in a key expected fault set corresponding to the transient power angle stability, firstly, respectively determining a set GL a formed by a random power supply and a load, wherein the ratio of the absolute value of the transient power angle stability influence degree to the maximum value in the absolute value of the transient power angle stability influence degree is larger than r a under the key expected fault, respectively determining the active power of the random source load in GL a corresponding to each key expected fault, which is injected into the power grid in an ultra-short period, and setting the active power of the random source load which does not belong to GL a into the power grid in an ultra-short period as a corresponding active predicted value; Wherein, P i0 is the active power of the injection power grid of the random power supply or load i under the running state of the power system corresponding to the latest evaluation results of the transient stability margin and the source load influence degree, P i is the active power of the injection power grid of the random power supply or load i in an ultra-short period, P i.d 、P i.u is the lower limit and the upper limit of the confidence interval of the random power supply or load i in the ultra-short period respectively, lambda a.i is the influence degree of the random power supply or load i on the transient power angle stability under the key expected faults, the influence degree is larger than 0, the active power increase of the injection power grid is favorable for the transient power angle stability, the larger the value is, the active power of the injection power grid with the same size is favorable for the transient power angle stability, the influence degree is smaller than 0, the active power increase of the injection power grid with the same size is unfavorable for the transient power angle stability, and the smaller the active power of the injection power grid with the same size is unfavorable. Aiming at each key expected fault in a key expected fault set corresponding to the transient high voltage stability, firstly respectively determining a node set B vu with a transient high voltage stability margin smaller than eta vu.cr under the key expected fault, a set GL vu composed of a random power supply and a load, wherein the ratio of the transient high voltage stable fixation loudness to the maximum value in the transient high voltage stable fixation loudness of the node in B vu under the key expected fault is larger than r vu , and respectively determining the active power of the random source load in the GL vu corresponding to each key expected fault in an ultra-short period injection mode by solving the following formula, and setting the active power of the ultra-short period injection mode into a corresponding active predicted value for the random source load not belonging to the GL vu ; In the formula, eta vu.b is a transient high-voltage stability margin of a node b under a key expected fault, alpha is a set parameter, alpha is larger than 0, P i0 is the active power of an injection power grid of a random power supply or a load i under the power system operation state corresponding to the latest evaluation result of the influence degree of source load, P i is the active power of the random power supply or the load i injected into the power grid in an ultra-short period, P i.d 、P i.u is the lower limit and the upper limit of the confidence interval of the random power supply or the load i in the ultra-short period respectively, lambda vu.b.i is the stable fixation degree of the random power supply or the load i on the transient high voltage of the node b under the key expected fault, the influence degree is larger than 0, the active power reduction of the injection power grid is favorable for the transient high-voltage stability, and the larger the active power of the injection power grid with the same size is favorable for the transient high-voltage stability. Aiming at each key expected fault in a key expected fault set corresponding to the transient low voltage stability, firstly respectively determining a node set B vd with a transient low voltage stability margin smaller than eta vd.cr under the key expected fault, a set GL vd composed of a random power supply and a load, wherein the ratio of the transient low voltage stable fixation loudness to the maximum value in the transient low voltage stable fixation loudness of the node in B vd under the key expected fault is larger than r v d, respectively determining the active power of the random source load in the GL vd corresponding to each key expected fault in an ultra-short period injection mode by solving the following formula, and setting the active power of the ultra-short period injection mode into a corresponding active predicted value for the random source load which does not belong to the GL vd ; In the formula, eta vd.b is a transient low-voltage stability margin of a node b under a key expected fault, alpha is a set parameter, alpha is larger than 0, P i0 is the active power of an injection power grid of a random power supply or a load i under the power system operation state corresponding to the latest evaluation result of the influence degree of source load, P i is the active power of the random power supply or the load i injected into the power grid in an ultra-short period, P i.d 、P i.u is the lower limit and the upper limit of the confidence interval of the random power supply or the load i in the ultra-short period respectively, lambda vd.b.i is the stable fixed degree of the random power supply or the load i to the transient low voltage of the node b under the key expected fault, the influence degree is larger than 0, the active power increase of the injection power grid is favorable for the transient low-voltage stability, and the larger the active power of the injection power grid with the same size is favorable for the transient low-voltage stability. Aiming at each key expected fault in a key expected fault set corresponding to the transient high-frequency stability, firstly respectively determining a node set B fu with a transient high-frequency stability margin smaller than eta fu.cr under the key expected fault, a set GL fu composed of a random power supply and a load, wherein the ratio of the transient high-frequency stable fixation loudness to the maximum value in the transient high-frequency stable fixation loudness of the node in B fu under the key expected fault is larger than r fu , respectively determining the active power of the random source load in GL fu corresponding to each key expected fault in an ultra-short period injection mode, and setting the active power of the ultra-short period injection mode into a corresponding active predicted value for the random source load which does not belong to GL fu ; In the formula, eta fu.b is a transient high-frequency stability margin of a node b under a key expected fault, alpha is a set parameter, alpha is larger than 0, P i0 is the active power of an injection power grid of a random power supply or a load i under the power system operation state corresponding to the latest evaluation result of the influence degree of source load, P i is the active power of the random power supply or the load i injected into the power grid in an ultra-short period, P i.d 、P i.u is the lower limit and the upper limit of the confidence interval of the random power supply or the load i in the ultra-short period respectively, lambda fu.b.i is the transient high-frequency stability and fixation degree of the random power supply or the load i on the node b under the key expected fault, the influence degree is larger than 0, the active power reduction of the injection power grid is favorable for the transient high-frequency stability, and the larger the active power of the injection power grid with the same size is favorable for the transient high-frequency stability. Aiming at each key expected fault in a key expected fault set corresponding to the transient low-frequency stability, firstly respectively determining a node set B fd with a transient low-frequency stability margin smaller than eta fd.cr under the key expected fault, a set GL fd composed of a random power supply and a load, wherein the ratio of the transient low-frequency stable fixation loudness to the maximum value in the transient low-frequency stable fixation loudness of the node in B fd under the key expected fault is larger than r fd , respectively determining the active power of the random source load in GL fd corresponding to each key expected fault in an ultra-short period injection mode, and setting the active power of the ultra-short period injection mode into a corresponding active predicted value for the random source load which does not belong to GL fd ; In the formula, eta fd.b is a transient low-frequency stability margin of a node b under a key expected fault, alpha is a set parameter, alpha is larger than 0, P i0 is the active power of an injection power grid of a random power supply or a load i under the power system operation state corresponding to the latest evaluation result of the influence degree of source load, P i is the active power of the random power supply or the load i injected into the power grid in an ultra-short period, P i.d 、P i.u is the lower limit and the upper limit of the confidence interval of the random power supply or the load i in the ultra-short period respectively, lambda fd.b.i is the transient low-frequency stability and fixation degree of the random power supply or the load i on the node b under the key expected fault, the influence degree is larger than 0, the active power increase of the injection power grid is favorable for transient low-frequency stability, and the larger value indicates that the active power of the injection power grid with the same size is more favorable for transient low-frequency stability.
  6. 6. The method for rapidly assessing the risk of ultra-short-term transient stability of an electric power system according to claim 2, wherein the step 4 is specifically, Aiming at each key expected fault in the key expected fault set corresponding to the transient power angle stability, the transient high voltage stability, the transient low voltage stability, the transient high frequency stability and the transient low frequency stability respectively, the following processing is carried out: Step 4-1, according to the active power of the random source load ultra-short period injection power grid corresponding to the ultra-short period non-random source load active power plan/direct current power plan/energy storage power plan/tie line power plan and key expected faults, calculating the active power and direct current power/energy storage power/tie line power of each power supply and load injection power grid in the power system by adopting an automatic power generation control (AGC) strategy in the energy management system; Step 4-2, according to the current state of reactive power and reactive power equipment of a power supply and load currently injected into a power grid, and the calculated active power and direct current power/energy storage power/tie line power of the power supply and load injected into the power grid in the power system, calculating the state of reactive power and reactive power equipment of the power supply and load injected into the power grid and the voltage of each node in the power system by adopting an automatic voltage control AVC strategy in an energy management system; And 4-3, injecting the calculated active, reactive and reactive equipment states of each power supply and load in the power system into a power grid, voltage of each node and direct current power/energy storage power/tie line power as the ultra-short-term risk running state of the power system corresponding to the key expected faults.
  7. 7. The method for rapidly assessing the risk of ultra-short-term transient stability of an electrical power system according to claim 2, wherein step 6 is specifically, And (3) taking the transient power angle stability, the transient high-voltage stability, the transient low-voltage stability, the transient high-frequency stability and the transient low-frequency stability obtained in the step (5) as transient power angle stability margin, transient high-voltage stability margin, transient low-voltage stability margin, transient power angle stability margin minimum value, transient high-voltage stability margin minimum value, transient low-voltage stability margin minimum value, transient high-frequency stability margin minimum value and transient low-frequency stability margin minimum value and corresponding key expected faults, power system ultra-short-term risk running state and source influence degree of the power system as power system ultra-short-term transient stability risk assessment information.
  8. 8. The rapid assessment system for the ultra-short-term transient stability risk of the power system is characterized by comprising, The expected fault clustering module is used for clustering expected faults in the expected fault set according to the latest evaluation results of the transient stability margin and the source load influence degree under the expected faults, and determining a transient stability expected fault subset after clustering; the key expected fault set generation module is used for determining key expected faults corresponding to each expected fault subset according to the transient stability margin under the expected faults to obtain a key expected fault set with transient stability; The random source load ultra-short term active power determining module determines the random source load ultra-short term active power corresponding to each key expected fault in the key expected fault set of transient stability according to the ultra-short term confidence interval of the random source load and the influence degree of the random source load on the transient stability under the key expected faults; The ultra-short-term risk state generation module is used for generating an ultra-short-term risk operation state of the power system corresponding to each key expected fault in the transient stability key expected fault set according to the ultra-short-term plan operation state, the random source load ultra-short-term active power corresponding to the key expected fault, and the automatic power generation control and automatic voltage control strategy; aiming at each key expected fault in the key expected fault set of the transient stability, the transient stability evaluation module respectively evaluates the transient stability under the key expected faults according to the ultra-short-term risk running state of the power system corresponding to the key expected fault; and the ultra-short-term risk determination module is used for determining the ultra-short-term transient stability risk of the power system according to the transient stability evaluation result.
  9. 9. A computer readable storage medium storing one or more programs, characterized in that the one or more programs comprise instructions, which when executed by a computing device, cause the computing device to perform any of the method of rapid assessment of ultra-short term transient stability risk of a power system according to claims 1-7.
  10. 10. A computing device comprising one or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and configured to be executed by the one or more processors, the one or more programs comprising instructions for performing any of the power system ultra-short term transient stability risk rapid assessment methods of claims 1-7.

Description

Rapid assessment method and system for ultra-short-term transient stability risk of power system Technical Field The invention belongs to the technical field of stability analysis of power systems, and relates to a method and a system for rapidly evaluating the risk of ultra-short-term transient stability of a power system. Background As the uncertainty of the two sides of the source load increases, the possibility that the running state of the power system determined by the scheduling plan has large deviation from the actual running state increases, and the risk prevention and control mode for performing stable check on the scheduling plan is difficult to avoid potential risks in the running of the power system at present. For this reason, a stable evaluation under expected failure needs to be performed for the power system operation state that may occur during the ultra-short period. Because the running state of the power system which can occur in the ultra-short period is inexhaustible, if the running state of the power system is generated by the mode of sampling and combining the uncertainty source load variables, for a large power system, the mode can generate combined explosion in thousands of uncertainty source load variables. In addition, even if the stable evaluation of all the expected faults is performed for only one operation state, the calculation amount is large for a large-scale expected fault set. Therefore, a breakthrough is urgently needed from the aspects of reducing the number of faults and the number of running states, so that the rapid assessment of the ultra-short-term transient stability risk can be realized. Disclosure of Invention Aiming at the problems, the invention aims to provide the method and the system for rapidly evaluating the transient stability risk of the power system in the ultra-short period, which can accurately identify key expected faults affecting the transient stability in the ultra-short period and the corresponding high risk running state of the power grid, and realize rapid evaluation of the transient stability risk of the power system in the ultra-short period. The technical scheme is that the method for rapidly evaluating the ultra-short-term transient stability risk of the power system comprises the following steps: step 1, clustering the predicted faults in a predicted fault set according to the latest evaluation results of the transient stability margin and the source load influence degree under the predicted faults, and determining a clustered transient stability predicted fault subset; Step 2, determining key expected faults corresponding to each expected fault subset according to the transient stability margin under the expected faults, and obtaining a key expected fault set with transient stability; step 3, determining the ultrashort-period active power of the random source load corresponding to each key expected fault in the transient stability key expected fault set according to the ultrashort-period confidence interval of the random source load and the influence degree of the ultrashort-period confidence interval on the transient stability under the key expected faults; Step 4, generating an ultra-short-term risk operation state of the power system corresponding to each key expected fault in the transient stability key expected fault set according to the ultra-short-term plan operation state, the random source load ultra-short-term active power corresponding to the key expected fault, and an automatic power generation control and automatic voltage control strategy; Aiming at each key expected fault in the key expected fault set of the transient stability, respectively carrying out transient stability evaluation under the key expected faults according to the ultra-short-term risk operation state of the power system corresponding to the key expected fault; And 6, determining the ultra-short-term transient stability risk of the power system according to the transient stability evaluation result. Further, the transient stability comprises transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability and transient low frequency stability; The transient stability margin comprises a transient power angle stability margin, each preset node transient high voltage stability margin for investigating transient high voltage stability, each preset node transient low voltage stability margin for investigating transient low voltage stability, each preset node transient high frequency stability margin for investigating transient high frequency stability and each preset node transient low frequency stability margin for investigating transient low frequency stability; The source load influence degree refers to influence degree of power supply and load of each node of an access power grid on transient power angle stability, and refers to influence degree of power supply and load of each node of t