Method and system for determining cross-domain propagation path of high-risk information-physical cooperative fault of electric power information physical system

Abstract

The invention discloses a method for determining a cross-domain propagation path of a high-risk information-physical cooperative fault of an electric power information physical system. The method comprises the following steps: acquiring data information of a target electric power information physical system; obtaining observability data of all lines after the uplink communication channel fails; establishing observability constraints; a controllability constraint is established; and with load loss maximization as an upper-layer target and load loss minimization as a lower-layer target, constructing a double-layer optimization model and solving to obtain a cross-domain propagation path of the high-risk information-physical cooperative fault of the target power information physical system. The invention also discloses a system for realizing the method for determining the cross-domain propagation path of the high-risk information-physical cooperative fault of the electric power information physical system. According to the method, the cross-domain propagation path of the high-risk information-physical cooperative fault of the electric power information physical system can be determined, the reliability is higher, and the accuracy is better.

Description

Technical Field

[0001] The present invention belongs to the field of electrical automation, and specifically relates to a method and system for determining a cross-domain propagation path of a high-risk information-physical collaborative fault in an electric power information-physical system. Background Art

[0002] With the development of economy and technology and the improvement of people's living standards, electricity has become an indispensable secondary energy source in people's production and life, bringing endless convenience to people's production and life. Therefore, ensuring the stable and reliable supply of electricity has become one of the most important tasks of the power system.

[0003] At present, with the application of advanced communication technology, the traditional power system has gradually evolved into a power cyber-physical system with deep integration of information and physics. The deep integration of information and physics not only ensures the efficient operation of the power system, but also ensures that the failure of a single physical component or information component will not have a significant impact on the power system. However, in the power cyber-physical system, the frequent interaction of information flow and energy flow increases the correlation between fault propagation and regeneration between various nodes, and the probability of occurrence of information-physical collaborative failures and the cross-domain propagation path of failures increase significantly, which may cause multi-component failures in the power cyber-physical system and ultimately cause a major power outage in the power system. Therefore, the determination of the cross-domain propagation path of high-risk information-physical collaborative failures in the power cyber-physical system is of great significance to the power cyber-physical system.

[0004] At present, traditional Nk analysis methods usually only focus on the consequences of physical component failures in power information-physical systems, without considering that failures in a single space will spread across domains between information networks and physical networks with the deep integration of information and physics, forming cross-domain chain failures; therefore, this scheme ignores the dynamic process of coordinated fault propagation and risk amplification, and cannot achieve the prediction of cross-domain fault paths. Summary of the invention

[0005] One of the purposes of the present invention is to provide a method for determining the cross-domain propagation path of high-risk information-physical collaborative faults in an electric power information-physical system with high reliability and good accuracy.

[0006] The second objective of the present invention is to provide a system for realizing a method for determining a cross-domain propagation path of a high-risk information-physical collaborative fault in the electric power information-physical system.

[0007] The method for determining the cross-domain propagation path of a high-risk information-physical collaborative fault in an electric power information-physical system provided by the present invention comprises the following steps:

[0008] S1. Obtain data information of the target power cyber-physical system;

[0009] S2. Analyze the impact of the uplink communication channel failure on the observability of the target power cyber-physical system according to the data information obtained in step S1, so as to obtain the observability data of all lines after the uplink communication channel failure;

[0010] S3. According to the observability data obtained in step S2, analyze the changes in the operating state of the line at different fault propagation stages and establish observability constraints;

[0011] S4. Analyze the impact of downlink communication channel failure on the controllability of the target power cyber-physical system, so as to establish controllability constraints;

[0012] S5. Based on the data information obtained in step S3 and step S4, a two-layer optimization model is constructed with maximizing load loss as the upper layer goal and minimizing load loss as the lower layer goal;

[0013] S6. Solve the two-layer optimization model constructed in step S5 based on the duality principle to obtain the cross-domain propagation path of high-risk information-physical collaborative failures of the target power information-physical system.

[0014] According to the data information obtained in step S1, the influence of the uplink communication channel failure on the observability of the target power cyber-physical system is analyzed in step S2, so as to obtain the observability data of all lines after the uplink communication channel failure, which specifically includes the following steps:

[0015] In the target power cyber-physical system, there are A1 nodes, A2 lines, A3 generators, and A4 loads; the number of nodes, the number of uplink communication channels, and the number of downlink communication channels correspond to each other.

[0016] Arbitrarily select k1 uplink communication channels to fail, expressed as where c n is a 0-1 variable indicating whether the uplink communication channel fails, c n =1 indicates that the nth uplink communication channel is operating normally, c n =0 indicates that the nth uplink communication channel fails;

[0017] According to the status of the uplink communication channel at both ends of line l, the following formula is used to determine whether line l is observable:

[0018]

[0019] Where δ l is a 0-1 variable indicating whether line l is observable, δ l =1 means that the line l is observable, δ l =0 means line l is not observable; c n＝o(l) and c n＝d(l)A 0-1 variable indicating whether the corresponding uplink communication channels at both ends of line l are faulty.

[0020] The step S3, according to the observability data obtained in step S2, analyzes the changes in the operation state of the line at different fault propagation stages and establishes observability constraints, which specifically includes the following steps:

[0021] According to the observability data obtained in step S2, the following formula is used to determine whether line l is observable and overloaded in the fault propagation stage s:

[0022]

[0023] Where a l,s is a 0-1 variable indicating whether line l is observable and overloaded during the fault propagation stage s, a l,s =1 means that line l is observable and overloaded during the fault propagation stage s, otherwise a l,s =0; f l,s is the power flow of line l in the fault propagation stage s; f l max is the maximum transmission capacity of line l;

[0024] According to the observability data obtained in step S2, the following formula is used to determine whether line l is unobservable and overloaded in the fault propagation stage s:

[0025]

[0026] Where p l,s is a 0-1 variable indicating whether line l is unobservable and overloaded during the fault propagation stage s, p l,s =1 means that line l is unobservable and overloaded during the fault propagation stage s, otherwise p l,s =0;

[0027] When there is a considerable line overload in the target power cyber-physical system, the target power cyber-physical system can perform optimal scheduling to eliminate the overload of the corresponding line, and the operating status of all lines remains unchanged in the fault propagation stage s;

[0028] When only an unobservable line overload exists in the target power cyber-physical system, the line is tripped in the fault propagation stage s, and the operating status of the remaining lines is kept unchanged in the fault propagation stage s, and the tripped line is recorded as the fault cross-domain propagation path; the constraint is expressed as

[0029]

[0030] Where e l,s is a 0-1 variable indicating whether line l trips during the fault propagation stage s, e l,s=1 means that line l trips at fault propagation stage s, e l,s =0 means that line l did not trip during the fault propagation stage s; q s is a 0-1 variable indicating whether the system has significant line overload, q s =1 indicates that there is a significant line overload in the system, q s =0 means that there is no significant line overload in the system; w l,s is a 0-1 variable representing the operating status of line l at fault propagation stage s, w l,s =1 means that line l operates normally in the fault propagation stage s, w l,s =0 means that line l trips at the fault propagation stage s.

[0031] The power flow is specifically calculated by the following steps:

[0032] The calculation is performed using DC power flow;

[0033] The DC power flow calculation includes node power balance constraints and line power flow constraints, which can be expressed as

[0034]

[0035] Where CL n,l is a 0-1 variable indicating whether line l is connected to node n. If line l is not connected to node n, then CL n,l = 0, line l is connected to node n and its direction is toward node n. n,l =1, line l is connected to node n and points away from node n when CL n,l =-1; CP n,g is a 0-1 variable indicating whether node n is connected to generator g. When node n is connected to generator g, CP n,g =1, when node n is not connected to generator g, CP n,g =0;P g,s is the output of generator g at fault propagation stage s; CD n,d is a 0-1 variable indicating whether node n is connected to load d. When node n is connected to load d, CD n,d =1, when node n is not connected to load d, CD n,d =0;D d,s is the load value of load d in fault propagation stage s; b l is the admittance of line l; θ n,s is the voltage phase angle of node n at fault propagation stage s.

[0036] The analysis of the impact of the downlink communication channel failure on the controllability of the target power cyber-physical system described in step S4, thereby establishing controllability constraints, specifically includes the following steps:

[0037] Arbitrarily select k2 downlink communication channels to fail, expressed as where t n is a 0-1 variable indicating whether the nth downlink communication channel fails, t n =1 indicates that the nth downlink communication channel is operating normally, t n =0 indicates that the nth downlink communication channel fails;

[0038] According to the running status of the downlink communication channel, determine whether the output of the generator g can be changed:

[0039] If the downlink communication channel corresponding to generator g fails, the output of generator g remains unchanged at the initial output; if the downlink communication channel corresponding to generator g does not fail, the output of generator g can be changed, and Among them, t n＝o(g) is a 0-1 variable indicating whether the communication channel corresponding to the generator g is faulty, P g,0 is the initial output of generator g, is the output of generator g, is the upper limit of the output of generator g;

[0040] According to the running status of the downlink communication channel, determine whether the load d can be changed:

[0041] If the downlink communication channel corresponding to load d fails, load d remains unchanged from the initial load; if the downlink communication channel corresponding to load d does not fail, load d can be changed, and in, is the load loss of load d, t n＝o(d) D is a 0-1 variable indicating whether the communication channel corresponding to load d is faulty. d,0 is the initial load.

[0042] According to the data information obtained in step S3 and step S4, the double-layer optimization model is constructed with maximizing load loss as the upper layer goal and minimizing load loss as the lower layer goal, which specifically includes the following steps:

[0043] Taking load loss maximization as the upper objective function, it can be expressed as

[0044]

[0045] Where u l is a 0-1 variable indicating whether line l is faulty, u l =0 means line l fails, u l =1 means that line l has no fault;

[0046] The following formula is used as the constraint condition:

[0047] Line fault quantity constraint: k3 is the number of line faults;

[0048] At the source fault stage, the line operation state constraint is w l,0 is a 0-1 variable representing the operating status of line l during the source fault phase, w l,0 =1 means that line l is operating normally at the source fault stage, w l,0 =0 means that line l fails at the source fault stage;

[0049] Observability-related constraints:

[0050] Generator operating state constraints: and Among them, λ g,s is a 0-1 variable indicating whether the generator g is disconnected. g,s =1, when the generator g is not disconnected g,s =0; L(g) is the set of lines l connected to the generator g;

[0051] Load operation status constraints: and Among them, χ d,s is a 0-1 variable indicating whether load d is disconnected. d,s =1, when load d is not disconnected d,s =0; L(d) is the set of lines l connected to load d;

[0052] Island processing constraints: Among them, T n,s is the node power of the unbalanced node in the system; is the node power of the system balancing node; n is the set of system balancing nodes;

[0053] Taking load loss minimization as the lower objective function, it can be expressed as

[0054]

[0055] In the formula is the output of the lower generator g;

[0056] The following formula is used as the constraint condition:

[0057] Node power balance constraints: in, is the lower line l flow;

[0058] Line flow constraints: Where o is the total number of fault propagation stages, w l,o is the operating status of line l at the last fault propagation stage o;

[0059] Flow limit constraints:

[0060] Phase angle limit constraint: in, is the voltage phase angle of the lower node n; θ max is the maximum voltage phase angle of node n;

[0061] Controllability constraints: in, is the maximum output of the generator g.

[0062] Step S6 solves the two-layer optimization model constructed in step S5 based on the duality principle to obtain the cross-domain propagation path of the high-risk information-physical collaborative fault of the target power information-physical system, which specifically includes the following steps:

[0063] For the two-layer optimization model constructed in step S5, dual constraints and strong dual constraints are added using the duality principle to transform the two-layer optimization model constructed in step S5 into a single-layer mixed integer programming model:

[0064] The added dual constraints are:

[0065]

[0066] Where η n is the first dual variable; is the second dual variable; v l is the third dual variable; ψ l is the fourth dual variable; is the fifth dual variable; β g is the sixth dual variable; is the seventh dual variable; α d is the eighth dual variable; is the ninth dual variable; ε n is the tenth dual variable;

[0067] The added strong dual constraints are:

[0068]

[0069] Finally, the transformed single-layer mixed integer programming model is solved by the optimization solver Gurobi to obtain the result corresponding to the maximum output load loss, which serves as the final cross-domain propagation path of high-risk cyber-physical collaborative failures in the target power cyber-physical system.

[0070] The present invention also provides a system for implementing the method for determining the cross-domain propagation path of the high-risk information-physical collaborative fault of the power information-physical system, including a data acquisition module, an observable determination module, an observable constraint module, a controllable constraint module, a model construction module and a path determination module; the data acquisition module, the observable determination module, the observable constraint module, the controllable constraint module, the model construction module and the path determination module are connected in series in sequence; the data acquisition module is used to acquire data information of the target power information-physical system, and upload the data information to the observable determination module; the observable determination module is used to analyze the impact of the uplink communication channel failure on the observability of the target power information-physical system based on the received data information and the acquired data information, so as to obtain the observability data of all lines after the uplink communication channel failure, and upload the data information to the observable constraint module; the observable constraint module is used to obtain the observability data of all lines after the uplink communication channel failure based on the received data information data information, analyzes the changes in the line's operating status at different fault propagation stages based on the acquired observability data, establishes observability constraints, and uploads the data information to the controllable constraint module; the controllable constraint module is used to analyze the impact of the downlink communication channel fault on the controllability of the target power information-physical system based on the received data information, thereby establishing controllability constraints, and uploading the data information to the model construction module; the model construction module is used to construct a two-layer optimization model based on the received data information, with load loss maximization as the upper-level goal and load loss minimization as the lower-level goal, and upload the data information to the path determination module; the path determination module is used to solve the constructed two-layer optimization model based on the duality principle according to the received data information, and obtain the cross-domain propagation path of high-risk information-physical collaborative faults of the target power information-physical system.

[0071] The method and system for determining the cross-domain propagation path of high-risk information-physical coordinated faults in an electric power information-physical system provided by the present invention transform the problem of calculating the cross-domain propagation path of high-risk cascading faults in an electric power information-physical system into a multi-stage two-layer mixed integer programming problem, and integrate the dynamic process of cross-domain propagation of faults into the multi-stage two-layer optimization model; therefore, the present invention can not only realize the cross-domain propagation path determination of high-risk information-physical coordinated faults in an electric power information-physical system, but also has higher reliability and better accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 The figure is a schematic diagram of the method flow of the present invention.

[0073] Figure 2 The system topology diagram of the method embodiment of the present invention is shown in FIG.

[0074] Figure 3 Schematic diagram of the functional modules of the system of the present invention. DETAILED DESCRIPTION

[0075] like Figure 1 The method flow diagram of the method of the present invention is shown as follows: the method for determining the cross-domain propagation path of a high-risk information-physical collaborative fault in an electric power information-physical system disclosed in the present invention comprises the following steps:

[0076] S1. Obtain data information of the target power cyber-physical system;

[0077] S2. According to the data information obtained in step S1, the influence of the uplink communication channel failure on the observability of the target power cyber-physical system is analyzed, so as to obtain the observability data of all lines after the uplink communication channel failure; specifically comprising the following steps:

[0078] In the target power cyber-physical system, there are A1 nodes, A2 lines, A3 generators, and A4 loads; the number of nodes, the number of uplink communication channels, and the number of downlink communication channels correspond to each other.

[0079] Arbitrarily select k1 uplink communication channels to fail, expressed as where c n is a 0-1 variable indicating whether the uplink communication channel fails, c n =1 indicates that the nth uplink communication channel is operating normally, c n =0 indicates that the nth uplink communication channel fails;

[0080] According to the status of the uplink communication channel at both ends of line l, the following formula is used to determine whether line l is observable:

[0081]

[0082] Where δ l is a 0-1 variable indicating whether line l is observable, δ l =1 means that the line l is observable, δ l =0 means line l is not observable; c n＝o(l) and c n＝d(l) A 0-1 variable indicating whether the corresponding uplink communication channel at both ends of line l has a fault;

[0083] S3. According to the observability data obtained in step S2, analyze the changes in the operating state of the line at different fault propagation stages and establish observability constraints; specifically, the following steps are included:

[0084] According to the observability data obtained in step S2, the following formula is used to determine whether line l is observable and overloaded in the fault propagation stage s:

[0085]

[0086] Where a l,sis a 0-1 variable indicating whether line l is observable and overloaded during the fault propagation stage s, a l,s =1 means that line l is observable and overloaded during the fault propagation stage s, otherwise a l,s =0; f l,s is the power flow of line l in the fault propagation stage s; f l max is the maximum transmission capacity of line l;

[0087] According to the observability data obtained in step S2, the following formula is used to determine whether line l is unobservable and overloaded in the fault propagation stage s:

[0088]

[0089] Where p l,s is a 0-1 variable indicating whether line l is unobservable and overloaded during the fault propagation stage s, p l,s =1 means that line l is unobservable and overloaded during the fault propagation stage s, otherwise p l,s =0;

[0090] When there is a considerable line overload in the target power cyber-physical system, the target power cyber-physical system can perform optimal scheduling to eliminate the overload of the corresponding line, and the operating status of all lines remains unchanged in the fault propagation stage s;

[0091] When only an unobservable line overload exists in the target power cyber-physical system, the line is tripped in the fault propagation stage s, and the operating status of the remaining lines is kept unchanged in the fault propagation stage s, and the tripped line is recorded as the fault cross-domain propagation path; the constraint is expressed as

[0092]

[0093] Where e l,s is a 0-1 variable indicating whether line l trips during the fault propagation stage s, e l,s =1 means that line l trips at fault propagation stage s, e l,s =0 means that line l did not trip during the fault propagation stage s; q s is a 0-1 variable indicating whether the system has significant line overload, q s =1 indicates that there is a significant line overload in the system, q s =0 means that there is no significant line overload in the system; w l,s is a 0-1 variable representing the operating status of line l at fault propagation stage s, w l,s =1 means that line l operates normally in the fault propagation stage s, w l,s =0 means that line l trips at fault propagation stage s;

[0094] In specific implementation, DC power flow is used for power flow calculation;

[0095] The DC power flow calculation includes node power balance constraints and line power flow constraints, which can be expressed as

[0096]

[0097] Where CL n,l is a 0-1 variable indicating whether line l is connected to node n. If line l is not connected to node n, then CL n,l = 0, line l is connected to node n and its direction is toward node n. n,l =1, line l is connected to node n and points away from node n when CL n,l =-1; CP n,g is a 0-1 variable indicating whether node n is connected to generator g. When node n is connected to generator g, CP n,g =1, when node n is not connected to generator g, CP n,g =0;P g,s is the output of generator g at fault propagation stage s; CD n,d is a 0-1 variable indicating whether node n is connected to load d. When node n is connected to load d, CD n,d =1, when node n is not connected to load d, CD n,d =0;D d,s is the load value of load d in fault propagation stage s; b l is the admittance of line l; θ n,s is the voltage phase angle of node n at fault propagation stage s;

[0098] S4. Analyze the impact of the downlink communication channel failure on the controllability of the target power cyber-physical system, so as to establish controllability constraints; specifically, the steps include:

[0099] Arbitrarily select k2 downlink communication channels to fail, expressed as where t n is a 0-1 variable indicating whether the nth downlink communication channel fails, t n =1 indicates that the nth downlink communication channel is operating normally, t n =0 indicates that the nth downlink communication channel fails;

[0100] According to the running status of the downlink communication channel, determine whether the output of the generator g can be changed:

[0101] If the downlink communication channel corresponding to generator g fails, the output of generator g remains unchanged at the initial output; if the downlink communication channel corresponding to generator g does not fail, the output of generator g can be changed, and Among them, t n＝o(g)is a 0-1 variable indicating whether the communication channel corresponding to the generator g is faulty, P g,0 is the initial output of generator g, is the output of generator g, is the upper limit of the output of generator g;

[0102] According to the running status of the downlink communication channel, determine whether the load d can be changed:

[0103] If the downlink communication channel corresponding to load d fails, load d remains unchanged from the initial load; if the downlink communication channel corresponding to load d does not fail, load d can be changed, and in, is the load loss of load d, t n＝o(d) D is a 0-1 variable indicating whether the communication channel corresponding to load d is faulty. d,0 is the initial load;

[0104] S5. Based on the data information obtained in step S3 and step S4, a two-layer optimization model is constructed with maximizing load loss as the upper layer goal and minimizing load loss as the lower layer goal; specifically, the following steps are included:

[0105] Taking load loss maximization as the upper objective function, it can be expressed as

[0106]

[0107] Where u l is a 0-1 variable indicating whether line l is faulty, u l =0 means line l fails, u l =1 means that line l has no fault;

[0108] The following formula is used as the constraint condition:

[0109] Line fault quantity constraint: k3 is the number of line faults;

[0110] At the source fault stage, the line operation state constraint is w l,0 is a 0-1 variable representing the operating status of line l during the source fault phase, w l,0 =1 means that line l is operating normally at the source fault stage, w l,0 =0 means that line l fails at the source fault stage;

[0111] Observability-related constraints:

[0112] Generator operating state constraints: and Among them, λ g,s is a 0-1 variable indicating whether the generator g is disconnected. g,s =1, when the generator g is not disconnected g,s =0; L(g) is the set of lines l connected to the generator g;

[0113] Load operation status constraints: and Among them, χ d,s is a 0-1 variable indicating whether load d is disconnected. d,s =1, when load d is not disconnected d,s =0; L(d) is the set of lines l connected to load d;

[0114] Island processing constraints: Among them, T n,s is the node power of the unbalanced node in the system; Node power for system balancing nodes; Balancing the set of nodes for the system;

[0115] Taking load loss minimization as the lower objective function, it can be expressed as

[0116]

[0117] In the formula is the output of the lower generator g;

[0118] The following formula is used as the constraint condition:

[0119] Node power balance constraints: in, is the lower line l flow;

[0120] Line flow constraints: Where o is the total number of fault propagation stages, w l,o is the operating status of line l at the last fault propagation stage o;

[0121] Flow limit constraints:

[0122] Phase angle limit constraint: in, is the voltage phase angle of the lower node n; θ max is the maximum voltage phase angle of node n;

[0123] Controllability constraints: in, is the maximum output of the generator g;

[0124] S6. Solve the two-layer optimization model constructed in step S5 based on the duality principle to obtain the cross-domain propagation path of the high-risk information-physical collaborative fault of the target power information-physical system; specifically, the following steps are included:

[0125] For the two-layer optimization model constructed in step S5, dual constraints and strong dual constraints are added using the duality principle to transform the two-layer optimization model constructed in step S5 into a single-layer mixed integer programming model:

[0126] The added dual constraints are:

[0127]

[0128] Where η n is the first dual variable; is the second dual variable; v l is the third dual variable; ψ l is the fourth dual variable; is the fifth dual variable; β g is the sixth dual variable; is the seventh dual variable; α d is the eighth dual variable; is the ninth dual variable; ε n is the tenth dual variable;

[0129] The added strong dual constraints are:

[0130]

[0131] Finally, the transformed single-layer mixed integer programming model is solved by the optimization solver Gurobi to obtain the result corresponding to the maximum output load loss, which serves as the cross-domain propagation path of the high-risk cyber-physical collaborative fault of the final target power cyber-physical system.

[0132] The method of the present invention is further described below in conjunction with an embodiment:

[0133] The IEEE 39-node system is used for simulation analysis. The IEEE 39-node system has a total of 39 nodes and 46 lines. Its topology, node and line numbers are as follows: Figure 2As shown, the upstream and downstream communication channel numbers correspond to the node numbers one by one. Compared with the disconnection of the line connected to the generator, which will cause a large load loss to the system and is more harmful, the impact of the disconnection of ordinary transmission lines on the system is difficult to directly identify. Therefore, in this example simulation, only ordinary transmission lines that are not connected to the generator are identified. Use python and Gurobi for simulation. Assuming that the number of line faults k3 increases from 1 to 3, and the number of communication channel faults increases, the identification results of high-risk information-physical collaborative faults and fault cross-domain propagation paths under different Nk scenarios are obtained, as shown in Table 1:

[0134] Table 1 Schematic diagram of identification results

[0135]

[0136] Each row in Table 1 shows the high-risk information-physical collaborative failure scenarios and fault cross-domain propagation path identification results when the load loss caused by the failure of only the uplink communication channel, the downlink communication channel, and the failure of both the uplink and downlink communication channels under different Nk scenarios is greater than 5%, 10%, and 20% for the first time.

[0137] Taking the N-2 scenario as an example for analysis, in the N-2 scenario, when the uplink communication channels 1, 2, 3, 4, 5, and 14 fail, the system loses partial observability. At this time, lines 26 and 42 fail, causing the power flow of lines 1, 3, 6, 8, and 9 to exceed the limit and cannot be detected in time, causing a chain failure, and ultimately causing a load loss of 1261MW, which is greater than 10%.

[0138] When the downlink communication channel 30 fails, although the failure of lines 35 and 38 will not cause a chain failure, the generator of bus 30 is uncontrollable and cannot participate in the optimal dispatch, and the final load loss is 696.73MW, which is greater than 10%.

[0139] In particular, when lines 9 and 10 fail, there will be no load loss in the system. However, when the uplink communication channels 6 and 7 and the downlink communication channels 30 and 39 fail at the same time, line 12 loses its observability and trips due to power flow overload. At the same time, the output of the generators on busbars 30 and 39 is limited, resulting in a large amount of load shedding. The final load loss is 738.4MW, which is greater than 10%. Therefore, cyber-physical collaborative failures will further amplify the harm of the failure, and the consequences are more serious than those caused by a single physical failure.

[0140] Based on the above analysis, the present invention can effectively identify high-risk information-physical collaborative faults and cross-domain fault propagation paths in the system.

[0141] like Figure 3The figure shows a schematic diagram of the functional modules of the system of the present invention: the system disclosed in the present invention for realizing the method for determining the cross-domain propagation path of the high-risk information-physical coordinated fault of the electric power information-physical system comprises a data acquisition module, an observable determination module, an observable constraint module, a controllable constraint module, a model construction module and a path determination module; the data acquisition module, the observable determination module, the observable constraint module, the controllable constraint module, the model construction module and the path determination module are connected in series in sequence; the data acquisition module is used to acquire the data information of the target electric power information-physical system, and upload the data information to the observable determination module; the observable determination module is used to analyze the influence of the uplink communication channel fault on the observability of the target electric power information-physical system according to the received data information and the acquired data information, so as to obtain the observability data of all lines after the uplink communication channel fault, and upload the data information to the observable constraint module; the observable constraint module The block is used to analyze the changes in the operating state of the line at different fault propagation stages according to the received data information and the acquired observability data, establish observability constraints, and upload the data information to the controllable constraint module; the controllable constraint module is used to analyze the impact of the downlink communication channel fault on the controllability of the target power information-physical system according to the received data information, thereby establishing controllability constraints, and uploading the data information to the model construction module; the model construction module is used to construct a two-layer optimization model based on the received data information and the obtained data information, with load loss maximization as the upper-level goal and load loss minimization as the lower-level goal, and upload the data information to the path determination module; the path determination module is used to solve the constructed two-layer optimization model based on the duality principle according to the received data information, and obtain the cross-domain propagation path of high-risk information-physical collaborative faults of the target power information-physical system.

Claims

1. A method for determining a cross-domain propagation path of a high-risk information-physical collaborative fault in an electric power information-physical system, comprising the following steps: S1. Obtain data information of the target power cyber-physical system; S2. Analyze the impact of the uplink communication channel failure on the observability of the target power cyber-physical system according to the data information obtained in step S1, so as to obtain the observability data of all lines after the uplink communication channel failure; S3. According to the observability data obtained in step S2, analyze the changes in the operating state of the line at different fault propagation stages and establish observability constraints; S4. Analyze the impact of downlink communication channel failure on the controllability of the target power cyber-physical system, so as to establish controllability constraints; S5. Based on the data information obtained in step S3 and step S4, a two-layer optimization model is constructed with maximizing load loss as the upper layer goal and minimizing load loss as the lower layer goal; S6. Solve the two-layer optimization model constructed in step S5 based on the duality principle to obtain the cross-domain propagation path of high-risk information-physical collaborative failures of the target power information-physical system.

2. The method for determining the cross-domain propagation path of high-risk information-physical collaborative faults in the power information-physical system according to claim 1 is characterized in that According to the data information obtained in step S1, the influence of the uplink communication channel failure on the observability of the target power cyber-physical system is analyzed in step S2, so as to obtain the observability data of all lines after the uplink communication channel failure, which specifically includes the following steps: In the target power cyber-physical system, there are A1 nodes, A2 lines, A3 generators, and A4 loads; the number of nodes, the number of uplink communication channels, and the number of downlink communication channels correspond to each other. Arbitrarily select k1 uplink communication channels to fail, expressed as where c n is a 0-1 variable indicating whether the uplink communication channel fails, c n =1 indicates that the nth uplink communication channel is operating normally, c n =0 indicates that the nth uplink communication channel fails; According to the status of the uplink communication channel at both ends of line l, the following formula is used to determine whether line l is observable: Where δ l is a 0-1 variable indicating whether line l is observable, and δ l =1 means that the line l is observable, δ l =0 means line l is not observable; c n＝o(l) and c n＝d(l) The table is a 0-1 variable indicating whether the corresponding uplink communication channels at both ends of line l are faulty.

3. The method for determining the cross-domain propagation path of high-risk information-physical collaborative faults in the power information-physical system according to claim 2 is characterized in that The step S3, according to the observability data obtained in step S2, analyzes the changes in the operation state of the line at different fault propagation stages and establishes observability constraints, which specifically includes the following steps: According to the observability data obtained in step S2, the following formula is used to determine whether line l is observable and overloaded in the fault propagation stage s: Where a l,s is a 0-1 variable indicating whether line l is observable and overloaded during the fault propagation stage s, a l,s =1 means that line l is observable and overloaded during the fault propagation stage s, otherwise a l,s =0; f l,s is the power flow of line l in the fault propagation stage s; f l max is the maximum transmission capacity of line l; According to the observability data obtained in step S2, the following formula is used to determine whether line l is unobservable and overloaded in the fault propagation stage s: Where p l,s is a 0-1 variable indicating whether line l is unobservable and overloaded during the fault propagation stage s, p l,s =1 means that line l is unobservable and overloaded during the fault propagation stage s, otherwise p l,s =0; When there is a considerable line overload in the target power cyber-physical system, the target power cyber-physical system can perform optimal scheduling to eliminate the overload of the corresponding line, and the operating status of all lines remains unchanged in the fault propagation stage s; When only an unobservable line overload exists in the target power cyber-physical system, the line is tripped in the fault propagation stage s, and the operating status of the remaining lines is kept unchanged in the fault propagation stage s, and the tripped line is recorded as the fault cross-domain propagation path; the constraint is expressed as Where e l,s is a 0-1 variable indicating whether line l trips during the fault propagation stage s, e l,s =1 means that line l trips at fault propagation stage s, e l,s =0 means that line l did not trip during the fault propagation stage s; q s is a 0-1 variable indicating whether the system has significant line overload, q s =1 indicates that there is a significant line overload in the system, q s =0 means that there is no significant line overload in the system; w l,s is a 0-1 variable representing the operating status of line l at fault propagation stage s, w l,s =1 means that line l operates normally in the fault propagation stage s, w l,s =0 means that line l trips at the fault propagation stage s.

4. The method for determining the cross-domain propagation path of high-risk information-physical collaborative faults in the power information-physical system according to claim 3 is characterized in that The power flow is specifically calculated by the following steps: The calculation is performed using DC power flow; The DC power flow calculation includes node power balance constraints and line power flow constraints, which can be expressed as Where CL n,l is a 0-1 variable indicating whether line l is connected to node n. If line l is not connected to node n, then CL n,l = 0, line l is connected to node n and its direction is toward node n. n,l =1, line l is connected to node n and points away from node n when CL n,l = -1; CP n,g is a 0-1 variable indicating whether node n is connected to generator g. When node n is connected to generator g, CP n,g =1, when node n is not connected to generator g, CP n,g =0;P g,s is the output of generator g at fault propagation stage s; CD n,d is a 0-1 variable indicating whether node n is connected to load d. When node n is connected to load d, CD n,d =1, when node n is not connected to load d, CD n,d =0;D d,s is the load value of load d in fault propagation stage s; b l is the admittance of line l; θ n,s is the voltage phase angle of node n at fault propagation stage s.

5. The method for determining the cross-domain propagation path of high-risk information-physical collaborative faults in the power information-physical system according to claim 4 is characterized in that The analysis of the impact of the downlink communication channel failure on the controllability of the target power cyber-physical system described in step S4, thereby establishing controllability constraints, specifically includes the following steps: Arbitrarily select k2 downlink communication channels to fail, expressed as where t n is a 0-1 variable indicating whether the nth downlink communication channel fails, t n =1 indicates that the nth downlink communication channel is operating normally, t n =0 indicates that the nth downlink communication channel fails; According to the running status of the downlink communication channel, determine whether the output of the generator g can be changed: If the downlink communication channel corresponding to generator g fails, the output of generator g remains unchanged at the initial output; if the downlink communication channel corresponding to generator g does not fail, the output of generator g can be changed, and Among them, t n＝o(g) is a 0-1 variable indicating whether the communication channel corresponding to the generator g is faulty, P g,0 is the initial output of generator g, is the output of generator g, is the upper limit of the output of generator g; According to the running status of the downlink communication channel, determine whether the load d can be changed: If the downlink communication channel corresponding to load d fails, load d remains unchanged from the initial load; if the downlink communication channel corresponding to load d does not fail, load d can be changed, and in, is the load loss of load d, t n＝o(d) D is a 0-1 variable indicating whether the communication channel corresponding to load d is faulty. d,0 is the initial load.

6. The method for determining the cross-domain propagation path of high-risk information-physical collaborative faults in the power information-physical system according to claim 5 is characterized in that According to the data information obtained in step S3 and step S4, the double-layer optimization model is constructed with maximizing load loss as the upper layer goal and minimizing load loss as the lower layer goal, which specifically includes the following steps: Taking load loss maximization as the upper objective function, it can be expressed as Where u l is a 0-1 variable indicating whether line l is faulty, u l =0 means line l fails, u l =1 means that line l has no fault; The following formula is used as the constraint condition: Line fault quantity constraint: k3 is the number of line faults; In the source fault stage, the line operation state constraint is w l,0 =u l w l,0 is a 0-1 variable representing the operating status of line l during the source fault phase, w l,0 =1 means that line l is operating normally at the source fault stage, w l,0 =0 means that line l fails at the source fault stage; Observability-related constraints: Generator operating state constraints: and P g,s =(1-λ g,s )·P g,0 Among them, λ g,s is a 0-1 variable indicating whether the generator g is disconnected. g,s =1, when the generator g is not disconnected g,s =0; L(g) is the set of lines l connected to the generator g; Load operation status constraints: and D d,s =(1-χ d,s )·D d,0 Among them, χ d,s is a 0-1 variable indicating whether load d is disconnected. d,s =1, when load d is not disconnected d,s =0; L(d) is the set of lines l connected to load d; Island processing constraints: Among them, T n,s is the node power of the unbalanced node in the system; Node power for system balancing nodes; Balancing the set of nodes for the system; Taking load loss minimization as the lower objective function, it can be expressed as The following formula is used as the constraint condition: Node power balance constraints: in, is the lower line l flow; Line flow constraints: Where o is the total number of fault propagation stages, w l,o is the operating status of line l at the last fault propagation stage o; Flow limit constraints: Phase angle limit constraint: in, is the voltage phase angle of the lower node n; θ max is the maximum voltage phase angle of node n; Controllability constraints: in, is the maximum output of the generator g.

7. The method for determining the cross-domain propagation path of high-risk information-physical coordinated faults in the power information-physical system according to claim 6 is characterized in that Step S6 solves the two-layer optimization model constructed in step S5 based on the duality principle to obtain the cross-domain propagation path of the high-risk information-physical collaborative fault of the target power information-physical system, which specifically includes the following steps: For the two-layer optimization model constructed in step S5, dual constraints and strong dual constraints are added using the duality principle to transform the two-layer optimization model constructed in step S5 into a single-layer mixed integer programming model: The added dual constraints are: Where η n is the first dual variable; is the second dual variable; v l is the third dual variable; ψ l is the fourth dual variable; is the fifth dual variable; β g is the sixth dual variable; is the seventh dual variable; α d is the eighth dual variable; is the ninth dual variable; ε n is the tenth dual variable; The added strong dual constraints are: Finally, the transformed single-layer mixed integer programming model is solved by the optimization solver Gurobi to obtain the result corresponding to the maximum output load loss, which serves as the cross-domain propagation path of the high-risk cyber-physical collaborative fault of the final target power cyber-physical system.

8. A system for implementing the method for determining the cross-domain propagation path of a high-risk information-physical coordinated fault in an electric power information-physical system as claimed in any one of claims 1 to 7, characterized in that It includes a data acquisition module, an observable determination module, an observable constraint module, a controllable constraint module, a model construction module and a path determination module; the data acquisition module, the observable determination module, the observable constraint module, the controllable constraint module, the model construction module and the path determination module are connected in series in sequence; the data acquisition module is used to acquire data information of the target power information-physical system and upload the data information to the observable determination module; The observability determination module is used to analyze the impact of the uplink communication channel failure on the observability of the target power cyber-physical system according to the received data information, so as to obtain the observability data of all lines after the uplink communication channel failure, and upload the data information to the observability constraint module; The observable constraint module is used to analyze the changes in the operation status of the line at different fault propagation stages according to the received data information and the acquired observability data, establish observability constraints, and upload the data information to the controllable constraint module; The controllable constraint module is used to analyze the impact of the downlink communication channel failure on the controllability of the target power cyber-physical system based on the received data information, thereby establishing controllability constraints and uploading the data information to the model construction module; The model building module is used to build a two-layer optimization model based on the received data information, taking load loss maximization as the upper layer goal and load loss minimization as the lower layer goal, and upload the data information to the path determination module; The path determination module is used to solve the constructed two-layer optimization model based on the duality principle according to the received data information, and obtain the cross-domain propagation path of high-risk information-physical collaborative faults of the target power information-physical system.

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