Method for evaluating elasticity of alternating-current and direct-current hybrid electric power information physical system under cooperative attack

Abstract

The invention discloses an elastic evaluation method for an AC / DC hybrid power information physical system under cooperative attack, and the method comprises the steps: building a multi-dimensional heterogeneous model of the AC / DC hybrid power information physical system according to an actual information network architecture, and completing the matrix modeling of the AC / DC hybrid power information physical system based on an incidence matrix method. And then information physical cooperative attacks are constructed based on a matrix modeling method, so that diversified cooperative attacks can be carried out on the multi-dimensional heterogeneous model and cascade fault diffusion is caused. And finally, a new elastic index-cascading failure recovery index CFRI is proposed, and the index considers factors such as the node number, the branch number and the load capacity of the system during cascade failure diffusion so as to evaluate the splitting capability and the recovery capability of the AC / DC hybrid power information physical system facing the cascade failure. According to the method, the elastic evaluation of the AC-DC hybrid power information physical system under the cooperative attack can be effectively completed, and the influence of an attacker on a power grid is reduced to the maximum extent.

Description

Technical Field

[0001] The present invention relates to the technical field of power system resilience assessment, and in particular to a method for assessing the resilience of an AC / DC hybrid power information-physical system under coordinated attacks. Background Art

[0002] As traditional power grids continue to transform into smart grids, building a new type of power system that is intelligent, efficient, safe and stable has become a general trend. The introduction of a large number of intelligent electronic devices has deeply integrated the communication network system with the power physical system to form a power information physical system, which not only improves the working efficiency of the power system, but also brings more convenience in the coordinated control, allocation and dispatching and unified management of the regional power grid. The fast start and stop function, fast power control, power reversal function and short-circuit current limiting function of the DC transmission system have greatly improved the voltage stability and power control capability of the AC system, reducing transmission losses while increasing transmission distances. These advantages have led to an increasing number of large-capacity and long-distance cross-regional DC interconnection lines in power grid construction in recent years, and AC and DC power systems have been widely used and promoted in modern power networks. Multi-hybrid transmission modes and heterogeneous networks have not only brought development and opportunities to the new smart grid, but their multiple uncertainties have also brought dual challenges of reliability and stability to the AC and DC hybrid power information physical system.

[0003] With the commissioning of large-scale DC transmission lines, once an AC side operation fault occurs, it may cause the DC line to lock and exit operation, leading to an increase in fault propagation. At the same time, the propagation of network faults caused by deep cyber-physical coupling may also increase the risk of major power outages. Therefore, it is necessary to conduct a resilience assessment of the AC / DC hybrid power cyber-physical system, clarify the resilience threshold of the system in possible cascading failures, and provide a reliable basis for responding to possible problems in the new power grid, formulating a safety protection resource allocation strategy, and establishing a new power grid protection system. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, and to provide a method for evaluating the resilience of an AC / DC hybrid power information-physical system under a coordinated attack. A multidimensional heterogeneous model of an AC / DC hybrid power information-physical system is established according to the actual information network architecture, and the matrix modeling of the AC / DC hybrid power information-physical system is completed based on the correlation matrix method. Then, based on the matrix modeling method, an information-physical coordinated attack is constructed, which can carry out diversified coordinated attacks on the constructed multidimensional heterogeneous model of the AC / DC hybrid power information-physical system and cause cascading faults to spread. Finally, a new resilience index, the cascading failure recovery index (CFRI), is proposed. This index takes into account factors such as the number of nodes, the number of branches, and the load of the system when the cascading fault spreads, so as to evaluate the decoupling capability and recovery capability of the AC / DC hybrid power information-physical system in the face of cascading faults. The resilience evaluation of the power information-physical system under a coordinated attack is completed, and the impact of the attacker on the power grid is minimized.

[0005] To achieve the above-mentioned purpose, the technical solution provided by the present invention is: a method for evaluating the resilience of an AC / DC hybrid power cyber-physical system under a coordinated attack, comprising the following steps:

[0006] S1. Based on the characteristics of high coupling between the information side and the physical side of the AC / DC hybrid power cyber-physical system and frequent two-way information interaction, a multi-dimensional heterogeneous model of the AC / DC hybrid power cyber-physical system is established. The model reflects the coupling characteristics between the information side and the physical side of the AC / DC hybrid power cyber-physical system, and based on the modeling method of the association matrix, the intra-layer information transmission and inter-layer information interaction between the information side and the physical side are modeled in detail to improve the accuracy of the model;

[0007] S2. Based on the multi-dimensional heterogeneous model established in step S1, a cyber-physical collaborative attack is developed through the correlation matrix modeling method. The attack can be launched in the measurement information collection stage and the control command issuance stage of the AC / DC hybrid power cyber-physical system, resulting in local unobservability and uncontrollability effects in the AC / DC hybrid power cyber-physical system. Launching a collaborative attack on the constructed multi-dimensional heterogeneous model will lead to the occurrence, propagation and aggravation of cascading failures.

[0008] S3. Based on the multi-dimensional heterogeneous model established in step S1 and the cyber-physical coordinated attack established in step S2, a cascading failure model of the AC / DC hybrid power cyber-physical system is established. The model can accurately reflect the evolution process of the cascading failure through the relevant parameters of the AC / DC hybrid power cyber-physical system under the cascading failure, including the number of lost nodes, the number of lost branches, the amount of lost load, and the size and state of the subsystem;

[0009] S4. A “cascading failure recovery index” is proposed as a comprehensive evaluation indicator, which takes into account the system scale and load level of the AC / DC hybrid power cyber-physical system during the cascading failure recovery process to evaluate the resilience and recovery capability of the AC / DC hybrid power cyber-physical system in the face of cascading failures.

[0010] Further, the specific operation steps of step S1 are as follows:

[0011] S11. Considering the information interaction tasks between the information side and the physical side of the AC / DC hybrid power information-physical system, including data uploading and command issuing, a multi-dimensional heterogeneous model of the AC / DC hybrid power information-physical system is established based on the information network architecture of hierarchical control of the power grid. The model includes a control layer, an interval layer and a processing layer; the control layer is composed of a monitor host, a remote control interface and a remote monitoring interface, and is responsible for real-time monitoring of the operating status of the AC / DC hybrid power information-physical system; the interval layer is composed of intelligent electronic devices, including relay protection devices and control switches, and is responsible for processing data uploaded by the processing layer and commands issued by the control layer; the processing layer uses intelligent monitoring terminals and intelligent dispatching terminals to monitor, manage and coordinate power plants, converter stations and transmission lines of the AC / DC hybrid power information-physical system;

[0012] S12. A coupling model of the information side and the physical side is constructed using an association matrix modeling method. The model includes the system topology, state transition process, control strategy transmission and information exchange process. The system modeling process for n physical nodes, k intelligent electronic device nodes and m information monitoring nodes is as follows:

[0013] S121, modeling the nodes within the layer to obtain the interval layer node model: using the tuple model to describe the functional characteristics of each layer of nodes, for the interval layer nodes, the i-th node model is:

[0014] S ii =[F sii ,P sii (F sii ),T sii (F sii ),…]

[0015] In the formula, S ii is the i-th node model in the interval layer, F sii Information processing algorithms for intelligent electronic devices, including data packet parsing F 1s , Data Processing 2s and data packet encryption F 3s , denoted as F sii =F 1s *F 2s *F 3s …;P sii With T siiare the error probability and delay in the information processing process, and the information processing algorithm F sii related;

[0016] S122, modeling of intra-layer branches, obtaining the interval layer branch model: Each layer network model reflects the information exchange of nodes within the layer, and the intra-layer branch performance tuple between nodes i and j is expressed as: S ij =[B ij ,P ij ,T ij ,…], where S ij is the branch model between node i and node j, B ij Indicates communication interruption state, P ij With T ij They are the error probability and delay in information transmission process respectively;

[0017] S123, intra-layer network modeling, to obtain an intra-layer network model: Based on the interval layer node model established in step S121 and the interval layer branch model established in step S122, the intra-layer network model is represented by a correlation characteristic matrix S:

[0018]

[0019] In the formula, S ij is the branch model between node i and node j. If i=j, it corresponds to the bay layer node. If i≠j, it corresponds to the bay layer branch. k is the total number of intelligent electronic device nodes in the bay layer.

[0020] S124, inter-layer coupling modeling: The intra-layer network model of the spacing layer is interconnected with the intra-layer network model of the control layer. In order to describe the relationship between the intelligent electronic device uploading information to the monitoring node and issuing instructions, the correlation characteristic matrix S from the spacing layer to the control layer is established. C :

[0021]

[0022] In the formula, Describes the coupling relationship between the interval layer nodes and the control layer nodes. The communication from the bay layer to the control layer is interrupted; is the communication bit error probability from the bay layer to the control layer; It is the communication delay from the bay layer to the control layer;

[0023] Based on the above modeling, a multi-dimensional heterogeneous model including the control layer, the spacing layer and the processing layer can be constructed. The model not only includes the node and network models of each layer, but also includes the correlation characteristic matrix between each layer, specifically: the correlation characteristic matrix P from the processing layer to the spacing layer S , the correlation characteristic matrix S from the interval layer to the processing layer P, the correlation characteristic matrix S from the interval layer to the control layer C And the correlation characteristic matrix C from the control layer to the interval layer S , which can clearly show the information flow and interactive coupling between the information side and the physical side; the information transmission between different layers is calculated through the correlation matrix, and the control layer sends control instructions to the interval layer through C*C S *S, where C is the control layer network correlation characteristic matrix, C S is the inter-layer correlation characteristic matrix from the control layer to the spacing layer, and S is the network correlation characteristic matrix of the spacing layer.

[0024] Further, in step S2, the cyber-physical coordinated attack consists of two parts: an information attack and a physical attack. The information attack includes an attack A on the AC / DC branch status information upload channel. u and attacks on the generator and load adjustment command issuing channel A d , where A u Abbreviated as uplink channel attack, A d The physical attack is aimed at the AC and DC branch circuit breaker equipment. l ; The coordinated attack is launched by physical attack, which controls the opening and closing of the branch by tampering with the state of the branch circuit breaker. In the AC / DC hybrid power information-physical system, the AC / DC branch belongs to the physical layer, and the circuit breaker device is a processing layer node. The two correspond one to one, so the physical attack is expressed as:

[0025] P a =P×A l =[B Pij ×A lij ,P Pij ,T Pij ,…]

[0026] In the formula, A l is the attack matrix for the circuit breaker device at the processing layer, where the vector A lij =[A Pij ,1,1,…],A Pij is the attack vector against the communication interruption state; P and P a are the branch correlation matrices of the processing layer or physical layer before and after the attack, respectively, Pij , P Pij , T Pij are the communication interruption state of the processing layer, the error probability and delay in the information transmission process; if B Pij =1, B Pij ×A lij = 0, it means that the branch between node i and node j is attacked and disconnected; if B Pij ×A lij =1, it means the branch is not attacked;

[0027] The uplink channel attack and downlink channel attack on the information side are launched by injecting attack vectors into the inter-layer correlation characteristic matrix; the attack A on the uplink channel of the AC and DC branch status information u It is the correlation characteristic matrix P from the processing layer to the interval layer S The specific form is:

[0028] S a =P×P a S ×S=P×(P S ×A u )×S

[0029] In the formula, A u is the attack matrix for the uplink channel from the processing layer to the spacer layer, P a S =P S ×A u is the correlation characteristic matrix from the processing layer to the spacer layer after the attack; S and S a are the network correlation characteristic matrices of the spacer layer before and after the attack. The branch status information received by the spacer layer is collected by the processing layer, and then transmitted to the spacer layer through the correlation characteristic matrix of the processing layer to the spacer layer. The upstream channel information attack injected during this period will change the original matrix P S The communication error probability in makes the interval layer matrix S after the attack a Receiving wrong information affects the judgment of the control layer;

[0030] Attack on the generator and load adjustment command issuing channel A d The attack principle is similar to A u Similarly, by calculating the inter-layer correlation characteristic matrix S from the spacing layer to the processing layer P The attack tampers with the generator's adjustment instructions to achieve the attack effect.

[0031] Further, the specific operation steps of step S3 are as follows:

[0032] S31. Based on the constructed multi-dimensional heterogeneous model and cyber-physical coordinated attack, a cascading failure model of AC / DC hybrid power cyber-physical system is established. The specific situation is as follows:

[0033] First, the basic fault is set according to the probability model of disturbance events, and the distribution of power grid flow under the fault is obtained according to the AC / DC power grid flow calculation. When a branch exceeds the limit, whether the branch is disconnected is related to the degree of its exceeding the limit. When the degree of branch power exceeding the threshold is within the allowable range, it can be maintained for a short time; when the threshold is exceeded but not within the allowable range, an emergency control action will be triggered to disconnect immediately. Therefore, the decoupling of the AC / DC hybrid power information-physical system may occur during the spread of cascading faults.

[0034] In the cascading failure model, there are also channels for information uploading and command issuing. Information-side attacks may attack the information transmitted in the channel to achieve a synergistic effect, exacerbating the spread of cascading failures. Each evolution of the AC / DC hybrid power information-physical system involves three situations: maintaining a system, splitting into multiple subsystems, and completely splitting. When the first two situations occur, it is necessary to record the resilience evaluation indicators of the AC / DC hybrid power information-physical system and continue to evolve until the AC / DC hybrid power information-physical system can be completely stable or completely split.

[0035] Whenever an electric device is out of operation, the AC / DC power flow calculation is first used to obtain the power flow distribution of the entire AC / DC hybrid power cyber-physical system. If there are still devices that may fail in the AC / DC hybrid power cyber-physical system, the AC / DC power grid emergency control model is used to solve the generator power adjustment and load reduction of each power node. In the process of uploading measurement data and issuing control instructions, the risk of cross-domain propagation of faults caused by secondary attacks on the information side is considered, which can fully reflect the occurrence of disturbance events and state transfer processes under network attacks.

[0036] S32. It is proposed to use the AC linearization method to construct an AC / DC power grid emergency control model. When a disturbance event caused by a network attack occurs, the safe and stable operation of the AC / DC hybrid power information-physical system is maintained through adjustment processing, load shedding and machine cutting measures. The optimization control objective function of the AC / DC power grid emergency control model is:

[0037]

[0038] Where ΔP di , ΔP gj are the power regulation of load node i and generator node j respectively, N b' 、N g are the load and the number of generators respectively; the constraints of the AC / DC power grid emergency control model include active power transmission constraints, node voltage amplitude constraints, generator power regulation constraints and maximum load reduction constraints.

[0039] Further, the specific operation steps of step S4 are as follows:

[0040] S41. The fault evolution process of the AC / DC hybrid power cyber-physical system after being attacked can be represented by the elastic system recovery process. According to the elastic system evaluation theory, a system response index that can reflect the system response of the AC / DC hybrid power cyber-physical system after being attacked is proposed, namely, the cascading failure recovery index (CFRI), which is expressed as:

[0041]

[0042] In the formula, α is the scale stability factor; β is the performance stability factor; N b 、N acl 、N dcl are the total number of nodes, the number of AC branches, and the number of DC branches of the AC / DC hybrid power cyber-physical system, where the total number of nodes of the AC / DC hybrid power cyber-physical system includes load nodes and generator nodes; N b,x 、N acl,x 、N dcl,x are the number of system nodes, number of AC branches and number of DC branches of the AC / DC hybrid power cyber-physical system at time x; N b,x-1 、N acl,x-1 、N dcl,x-1 are the number of system nodes, number of AC branches and number of DC branches of the AC / DC hybrid power cyber-physical system at time x-1; L x , L all are the load and total load of the AC / DC hybrid power cyber-physical system at the evolution time x, respectively; ω1, ω2, ω3 are the node influence factor, AC branch influence factor, and DC branch influence factor, respectively; is the AC / DC power grid scale calculation function; since the scale of the AC / DC hybrid power cyber-physical system is taken into account, including nodes, branches and load, the changes in the system scale and load of the AC / DC hybrid power cyber-physical system from fault diffusion to decoupling after a cascading fault occurs are quantified, reflecting the evolution of the fault in the AC / DC hybrid power cyber-physical system. This indicator can be used as an indicator for comprehensively evaluating the decoupling process of cascading faults, and evaluating the recovery capability of the AC / DC hybrid power cyber-physical system in the face of cascading faults;

[0043] S42. In order to more quickly evaluate the CFRI changes and robustness performance of the AC / DC hybrid power cyber-physical system after being attacked, improvements were made on the basis of CFRI, and the CFRI area model was used to score the CFRI level of the AC / DC hybrid power cyber-physical system. The formula of the CFRI area model is as follows:

[0044]

[0045] Where R is the robustness index of the CFRI curve; T is the evolution time; t0 is the simulation start time, t r is the moment when the AC / DC hybrid power information-physical system recovers to stability, that is, the AC / DC hybrid power information-physical system no longer experiences disconnection or load loss; CFRI(t) is the cascade disconnection resilience index curve of the AC / DC hybrid power information-physical system, which depicts the change of the cascade disconnection index of the AC / DC hybrid power information-physical system from being attacked to recovering to stability.

[0046] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0047] Existing resilience indicators include load resilience indicators and energy storage resilience indicators. These resilience indicators are generally helpful in evaluating the robustness, adaptability and reliability of power systems. However, when facing malicious cyber attacks or cyber-physical coordinated attacks, the above indicators have several problems:

[0048] 1. Lack of consideration for nonlinear responses: Current resilience indicators are usually based on the assumption of linear response, which means that the response of the system changes proportionally. However, in the presence of large-scale attacks or extreme situations, the system may exhibit nonlinear responses, such as system crashes or cascading failures. Current resilience indicators cannot accurately capture these nonlinear reactions and may underestimate the vulnerability of the system.

[0049] 2. Lack of comprehensiveness: Current resilience indicators are usually single or local indicators that cannot fully evaluate the resilience of the entire system. Power system resilience includes multiple aspects, including supply and demand balance, system stability, and recovery capabilities. Taking these aspects into account can more accurately assess the overall resilience level of the system.

[0050] 3. Lack of dynamics: Current power system resilience indicators are usually derived from static system models and historical data. However, the power system is a dynamic model, and its state and conditions may change in different time periods. Existing resilience indicators fail to fully consider this dynamic and cannot accurately reflect the resilience level of the system under different operating conditions.

[0051] In order to solve the above problems, the present invention studies the resilience assessment of AC / DC hybrid power cyber-physical systems, which will effectively fill this gap in the field and provide a reference for research and development in this direction. The contributions of the present invention are summarized as follows:

[0052] 1. A multi-dimensional heterogeneous model of AC / DC hybrid power cyber-physical system is established, which reflects the coupling characteristics between the information side and the physical side. Based on the correlation matrix method, hierarchical matrix modeling and inter-layer interaction matrix modeling are applied to the information network to improve the accuracy of the model.

[0053] 2. The cyber-physical collaborative attack developed based on the matrix modeling method can launch attacks during the measurement information collection and control command issuance stages, resulting in local unobservable and uncontrollable effects in the system.

[0054] 3. A cascading failure model of AC / DC hybrid power cyber-physical system is established, which can accurately reflect the evolution of cascading failures through parameters such as the number of lost nodes, the number of lost branches, the amount of lost load, and the size and status of subsystems, paving the way for resilience assessment.

[0055] 4. A comprehensive resilience evaluation index named cascading failure recovery index (CFRI) is proposed, which broadly considers the system scale and load level during the cascading failure recovery process. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 Schematic diagram of the multi-dimensional heterogeneous model of the AC / DC hybrid power information-physical system.

[0057] Figure 2 Schematic diagram of the cascading failure model of the AC / DC hybrid power cyber-physical system.

[0058] Figure 3 Schematic diagram of resilience assessment of AC / DC hybrid power cyber-physical system under cascading failures. DETAILED DESCRIPTION

[0059] The present invention is further described in detail below in conjunction with embodiments and drawings, but the embodiments of the present invention are not limited thereto.

[0060] This embodiment discloses a method for evaluating the resilience of an AC / DC hybrid power cyber-physical system under coordinated attacks, and the specific situation is as follows:

[0061] According to the characteristics of the AC / DC hybrid power cyber-physical system with high coupling between the information side and the physical side and frequent two-way information interaction, a multi-dimensional heterogeneous model of the AC / DC hybrid power cyber-physical system is established. Figure 1 shown.

[0062] Depend on Figure 1It can be seen that the multi-dimensional heterogeneous model consists of a four-layer architecture. The bottom layer is the physical layer, including power plants, substations, converters, AC transmission lines, DC transmission lines, loads and other power equipment. The information network is a three-layer architecture. The top layer is the control layer, which is the key part responsible for system monitoring and control. The control layer consists of a monitor host, a remote control interface, and a remote monitoring interface. The monitor host is the core component of the control layer and is responsible for real-time monitoring of the operating status, parameters and performance of the power system; the remote control interface is used to remotely control various devices and components of the power system and provides the ability to communicate with remote control devices (such as switches, circuit breakers, transformers, etc.) in the power system; the remote monitoring interface is used to communicate and exchange data with the remote monitoring system and provides the ability to transmit system monitoring data to the remote monitoring center or other related entities. The second layer is the interval layer, which is composed of multiple intelligent electronic devices, including intelligent relays, intelligent protection devices, intelligent switches, etc., and is responsible for processing data uploaded by the process layer and control instructions issued by the control layer. The third layer is the process layer, which is connected to the physical layer. Its main function is to realize the monitoring, management and coordination of various subsystems and equipment in the power system. Intelligent electronic terminals are key components in the process layer, including intelligent monitoring terminals, intelligent dispatching terminals, etc., which are used for real-time monitoring, data collection, operation dispatch, optimization management and regulation of various subsystems and equipment in the power system.

[0063] The coupling model of the information side and the physical side is constructed by the association matrix modeling method. The model includes the system topology, state transition process, control strategy transmission and information exchange process. The system modeling process for n physical nodes, k intelligent electronic device nodes and m information monitoring nodes is as follows (because the modeling principles of nodes, branches and coupling between layers in different layers are similar, the modeling of the interval layer and the modeling of the interlayer coupling from the interval layer to the control layer are used as examples):

[0064] 1) Modeling of nodes within the layer to obtain the interval layer node model: The tuple model is used to describe the functional characteristics of each layer of nodes. For the interval layer nodes, the i-th node is modeled as:

[0065] S ii =[F sii ,P sii (F sii ),T sii (F sii ),…]

[0066] In the formula, S ii is the i-th node model in the interval layer, F sii Information processing algorithms for intelligent electronic devices, including data packet parsing F 1s , Data Processing 2s and data packet encryption F 3s , denoted as F sii=F 1s *F 2s *F 3s …;P sii With T sii are the error probability and delay in the information processing process, and the information processing algorithm F sii related;

[0067] 2) Intra-layer branch modeling, to obtain the interval layer branch model: Each layer network model reflects the information exchange of nodes within the layer, and the intra-layer branch performance tuple between nodes i and j is expressed as: S ij =[B ij ,P ij ,T ij ,…], where S ij is the branch model between node i and node j, B ij Indicates communication interruption state, P ij With T ij They are the error probability and delay in information transmission process respectively;

[0068] 3) Intra-layer network modeling, obtaining an intra-layer network model: Based on the interval layer node model established in step S121 and the interval layer branch model established in step S122, the intra-layer network model is represented by a correlation characteristic matrix S:

[0069]

[0070] In the formula, S ij is the branch model between node i and node j. If i=j, it corresponds to the bay layer node. If i≠j, it corresponds to the bay layer branch. k is the total number of intelligent electronic device nodes in the bay layer.

[0071] 4) Interlayer coupling modeling: The intralayer network model of the spacer layer is interconnected with the intralayer network model of the control layer. In order to describe the relationship between the intelligent electronic device uploading information to the monitoring node and issuing instructions, the correlation characteristic matrix S from the spacer layer to the control layer is established. C :

[0072]

[0073] In the formula, Describes the coupling relationship between the interval layer nodes and the control layer nodes. The communication from the bay layer to the control layer is interrupted; is the communication bit error probability from the bay layer to the control layer; It is the communication delay from the interval layer to the control layer.

[0074] Based on the above modeling, a multi-dimensional heterogeneous model including the control layer, the spacing layer and the processing layer can be constructed. The model not only includes the node and network models of each layer, but also includes the correlation characteristic matrix between each layer, specifically: the correlation characteristic matrix P from the processing layer to the spacing layer S , the correlation characteristic matrix S from the interval layer to the processing layer P , the correlation characteristic matrix S from the interval layer to the control layer C And the correlation characteristic matrix C from the control layer to the interval layer S , which can clearly show the information flow and interactive coupling between the information side and the physical side; the information transmission between different layers is calculated through the correlation matrix, and the control layer sends control instructions to the interval layer through C*C S *S, where C is the control layer network correlation characteristic matrix, C S is the inter-layer correlation characteristic matrix from the control layer to the spacing layer, and S is the network correlation characteristic matrix of the spacing layer.

[0075] The cyber-physical coordinated attack consists of two parts: information attack and physical attack. The information attack includes the attack on the AC and DC branch status information upload channel. u and attacks on the generator and load adjustment command issuing channel A d , where A u Abbreviated as uplink channel attack, A d Downstream channel attack; physical attack is an attack on AC and DC branch circuit breaker equipment. l ; The coordinated attack is launched by physical attack, which controls the opening and closing of the branch by tampering with the state of the branch circuit breaker. In the AC / DC hybrid power information-physical system, the AC / DC branch belongs to the physical layer, and the circuit breaker device is a processing layer node. The two correspond one to one, so the physical attack is expressed as:

[0076] P a =P×A l =[B Pij ×A lij ,P Pij ,T Pij ,…]

[0077] In the formula, A l is the attack matrix for the circuit breaker device at the processing layer, where the vector A lij =[A Pij ,1,1,…],A Pij is the attack vector against the communication interruption state; P and P a are the branch correlation matrices of the processing layer or physical layer before and after the attack, respectively, Pij , P Pij , T Pij are the communication interruption state of the processing layer, the error probability and delay in the information transmission process; if BPij =1, B Pij ×A lij = 0, it means that the branch between node i and node j is attacked and disconnected; if B Pij ×A lij =1, it means the branch is not attacked;

[0078] The uplink channel attack and downlink channel attack on the information side are launched by injecting attack vectors into the inter-layer correlation characteristic matrix; the attack A on the uplink channel of the AC and DC branch status information u It is the correlation characteristic matrix P from the processing layer to the interval layer S The specific form is:

[0079] S a =P×P a S ×S=P×(P S ×A u )×S

[0080] In the formula, A u is the attack matrix for the uplink channel from the processing layer to the spacer layer, P a S =P S ×A u is the correlation characteristic matrix from the processing layer to the spacer layer after the attack; S and S a are the network correlation characteristic matrices of the spacer layer before and after the attack. The branch status information received by the spacer layer is collected by the processing layer, and then transmitted to the spacer layer through the correlation characteristic matrix of the processing layer to the spacer layer. The upstream channel information attack injected during this period will change the original matrix P S The communication error probability in makes the interval layer matrix S after the attack a Receiving error information affects the further judgment of the control layer;

[0081] Based on the multi-dimensional heterogeneous model and cyber-physical collaborative attack constructed in the above steps, a cascading failure model of AC / DC hybrid power cyber-physical system is established, such as Figure 2 As shown. First, the basic fault is set according to the probability model of disturbance events, and the grid power flow distribution under the fault is calculated according to the AC / DC grid power flow. When a branch exceeds the limit, whether the branch is disconnected is related to the degree of its exceeding the limit. When the branch power exceeds the threshold to a certain extent, it can be maintained for a short time; when it exceeds the threshold to a certain extent, it will trigger an emergency control action to disconnect immediately. Therefore, the decoupling of the AC / DC hybrid power information-physical system may occur during the spread of cascading faults.

[0082] In the cascading failure model, there are also channels for information uploading and command issuing. Information-side attacks may attack the information transmitted in the channel to achieve a synergistic effect, exacerbating the spread of cascading failures. Each evolution of the AC / DC hybrid power information-physical system has three situations: maintaining a system, splitting into multiple subsystems, and completely splitting. When the first two situations occur, it is necessary to record the elasticity evaluation indicators of the AC / DC hybrid power information-physical system and continue to evolve until the AC / DC hybrid power information-physical system can be completely stable or completely split.

[0083] Whenever an electric device is out of operation, the AC / DC power flow calculation is first used to obtain the power flow distribution of the entire AC / DC hybrid power cyber-physical system. If there are still devices that may fail in the AC / DC hybrid power cyber-physical system, the AC / DC power grid emergency control model of the AC / DC hybrid power cyber-physical system is used to solve the generator power adjustment and load reduction of each power node. In the process of uploading measurement data and issuing control instructions, the risk of cross-domain propagation of faults caused by secondary attacks on the information side is considered, which can fully reflect the occurrence of disturbance events and state transfer processes under network attacks.

[0084] The AC linearization method is used to construct an AC / DC power grid emergency control model. When a disturbance event caused by a network attack occurs, the safe and stable operation of the power grid is maintained through adjustment processing, load shedding, and machine shedding. The objective function of the optimal control of the AC / DC power grid emergency control model is:

[0085]

[0086] Where ΔP di , ΔP gj are the power regulation of load node i and generator node j respectively, N b' and N g are the load and the number of generators respectively; the constraints of the AC / DC power grid emergency control model include active power transmission constraints, node voltage amplitude constraints, generator power regulation constraints and maximum load reduction constraints.

[0087] The fault evolution process of the AC / DC hybrid power cyber-physical system after being attacked can be represented by the elastic system recovery process. According to the elastic system evaluation theory, a system response index, the cascading failure recovery index (CFRI), is proposed to reflect the system response of the AC / DC hybrid power cyber-physical system after being attacked. The expression is:

[0088]

[0089] In the formula, α is the scale stability factor; β is the performance stability factor; N b 、N acl、N dcl are the total number of nodes, the number of AC branches, and the number of DC branches of the AC / DC hybrid power cyber-physical system, where the total number of nodes of the AC / DC hybrid power cyber-physical system includes load nodes and generator nodes; N b,x 、N acl,x 、N dcl,x are the number of system nodes, number of AC branches and number of DC branches of the AC / DC hybrid power cyber-physical system at time x; N b,x-1 、N acl,x-1 、N dcl,x-1 are the number of system nodes, number of AC branches and number of DC branches of the AC / DC hybrid power cyber-physical system at time x-1; L x , L all are the load and total load of the AC / DC hybrid power cyber-physical system at the evolution time x, respectively; ω1, ω2, ω3 are the node influence factor, AC branch influence factor, and DC branch influence factor, respectively; is the AC / DC power grid scale calculation function; since the scale of the AC / DC hybrid power cyber-physical system is taken into account, including nodes, branches and load, the changes in the system scale and load of the AC / DC hybrid power cyber-physical system from fault diffusion to decoupling after a cascading fault occurs are quantified, reflecting the evolution of the fault in the AC / DC hybrid power cyber-physical system. This indicator can be used as an indicator for comprehensively evaluating the decoupling process of cascading faults, and evaluating the recovery capability of the AC / DC hybrid power cyber-physical system in the face of cascading faults;

[0090] In order to more quickly evaluate the CFRI changes and robustness performance of the AC / DC hybrid power cyber-physical system after being attacked, an improvement was made on the basis of CFRI, and the CFRI area model was used to score the CFRI level of the AC / DC hybrid power cyber-physical system. Figure 3 As shown, the formula is as follows:

[0091]

[0092] Where R is the robustness index of the CFRI curve; T is the evolution time; t0 is the simulation start time, t r is the moment when the AC / DC hybrid power information-physical system recovers to stability, that is, the AC / DC hybrid power information-physical system no longer experiences disconnection or load loss; CFRI(t) is the cascade disconnection resilience index curve of the AC / DC hybrid power information-physical system, which depicts the change of the cascade disconnection index of the AC / DC hybrid power information-physical system from being attacked to restoring stability. Figure 3 In, t0-t e This is the prevention period. At this time, the AC / DC hybrid power cyber-physical system operates stably. The CFRI value at this time is shown as point A. At t eAt time t, the AC / DC hybrid power cyber-physical system is attacked by cyber-physical coordination, and the CFRI value drops rapidly to point B. e -t d After a period of fault evolution, the performance of the AC / DC hybrid power cyber-physical system reaches the minimum value C; t d -t r This is the recovery period, during which the AC / DC hybrid power cyber-physical system gradually recovers its performance due to emergency control measures that suppress the continued spread of the fault. Figure 3 Point D is an ideal situation. In actual situations, the AC / DC hybrid power cyber-physical system often cannot recover to its initial performance.

[0093] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention.

Claims

1. A method for evaluating the resilience of AC / DC hybrid power cyber-physical systems under coordinated attacks, characterized in that: The following steps are involved: S1. Based on the characteristics of high coupling between the information side and the physical side of the AC / DC hybrid power cyber-physical system and frequent two-way information interaction, a multi-dimensional heterogeneous model of the AC / DC hybrid power cyber-physical system is established. The model reflects the coupling characteristics between the information side and the physical side of the AC / DC hybrid power cyber-physical system, and based on the modeling method of the association matrix, the intra-layer information transmission and inter-layer information interaction between the information side and the physical side are modeled in detail to improve the accuracy of the model; S2. Based on the multi-dimensional heterogeneous model established in step S1, a cyber-physical collaborative attack is developed through the correlation matrix modeling method. The attack can be launched in the measurement information collection stage and the control command issuance stage of the AC / DC hybrid power cyber-physical system, resulting in local unobservability and uncontrollability effects in the AC / DC hybrid power cyber-physical system. Launching a collaborative attack on the constructed multi-dimensional heterogeneous model will lead to the occurrence, propagation and aggravation of cascading failures. S3. Based on the multi-dimensional heterogeneous model established in step S1 and the cyber-physical coordinated attack established in step S2, a cascading failure model of the AC / DC hybrid power cyber-physical system is established. The model can accurately reflect the evolution process of the cascading failure through the relevant parameters of the AC / DC hybrid power cyber-physical system under the cascading failure, including the number of lost nodes, the number of lost branches, the amount of lost load, and the size and state of the subsystem; S4. A "cascading fault recovery index" is proposed as a comprehensive evaluation indicator, which takes into account the system scale and load level of the AC / DC hybrid power cyber-physical system during the cascading fault recovery process to evaluate the resilience and recovery capability of the AC / DC hybrid power cyber-physical system in the face of cascading faults.

2. The method for evaluating the resilience of an AC / DC hybrid power cyber-physical system under coordinated attacks according to claim 1 is characterized in that: The specific operation steps of step S1 are as follows: S11. Considering the information interaction tasks between the information side and the physical side of the AC / DC hybrid power information-physical system, including data uploading and command issuing, a multi-dimensional heterogeneous model of the AC / DC hybrid power information-physical system is established based on the information network architecture of hierarchical control of the power grid. The model includes a control layer, an interval layer and a processing layer; the control layer is composed of a monitor host, a remote control interface and a remote monitoring interface, and is responsible for real-time monitoring of the operating status of the AC / DC hybrid power information-physical system; the interval layer is composed of intelligent electronic devices, including relay protection devices and control switches, and is responsible for processing data uploaded by the processing layer and commands issued by the control layer; the processing layer uses intelligent monitoring terminals and intelligent dispatching terminals to monitor, manage and coordinate power plants, converter stations and transmission lines of the AC / DC hybrid power information-physical system; S12. A coupling model of the information side and the physical side is constructed using an association matrix modeling method. The model includes the system topology, state transition process, control strategy transmission and information exchange process. The system modeling process for n physical nodes, k intelligent electronic device nodes and m information monitoring nodes is as follows: S121, modeling the nodes within the layer to obtain the interval layer node model: using the tuple model to describe the functional characteristics of each layer of nodes, for the interval layer nodes, the i-th node model is: S ii =[F sii ,P sii (F sii ),T sii (F sii ),…] In the formula, S ii is the i-th node model in the interval layer, F sii Information processing algorithms for intelligent electronic devices, including data packet parsing F 1s , Data Processing 2s and data packet encryption F 3s , denoted as F sii =F 1s *F 2s *F 3s …;P sii With T sii are the error probability and delay in the information processing process, and the information processing algorithm F sii related; S122, modeling of intra-layer branches, obtaining the interval layer branch model: Each layer network model reflects the information exchange of nodes within the layer, and the intra-layer branch performance tuple between nodes i and j is expressed as: S ij =[B ij ,P ij ,T ij ,…], where S ij is the branch model between node i and node j, B ij Indicates communication interruption state, P ij With T ij They are the error probability and delay in information transmission process respectively; S123, intra-layer network modeling, to obtain an intra-layer network model: Based on the interval layer node model established in step S121 and the interval layer branch model established in step S122, the intra-layer network model is represented by a correlation characteristic matrix S: In the formula, S ij is the branch model between node i and node j. If i=j, it corresponds to the bay layer node. If i≠j, it corresponds to the bay layer branch. k is the total number of intelligent electronic device nodes in the bay layer. S124, inter-layer coupling modeling: The intra-layer network model of the spacing layer is interconnected with the intra-layer network model of the control layer. In order to describe the relationship between the intelligent electronic device uploading information to the monitoring node and issuing instructions, the correlation characteristic matrix S from the spacing layer to the control layer is established. C : In the formula, Describes the coupling relationship between the interval layer nodes and the control layer nodes. The communication from the bay layer to the control layer is interrupted; is the communication bit error probability from the bay layer to the control layer; It is the communication delay from the bay layer to the control layer; Based on the above modeling, a multi-dimensional heterogeneous model including the control layer, the spacing layer and the processing layer can be constructed. The model not only includes the node and network models of each layer, but also includes the correlation characteristic matrix between each layer, specifically: the correlation characteristic matrix P from the processing layer to the spacing layer S , the correlation characteristic matrix S from the interval layer to the processing layer P , the correlation characteristic matrix S from the interval layer to the control layer C And the correlation characteristic matrix C from the control layer to the interval layer S , which can clearly show the information flow and interactive coupling between the information side and the physical side; the information transmission between different layers is calculated through the correlation matrix, and the control layer sends control instructions to the interval layer through C*C S *S, where C is the control layer network correlation characteristic matrix, C S is the inter-layer correlation characteristic matrix from the control layer to the spacing layer, and S is the network correlation characteristic matrix of the spacing layer.

3. The method for evaluating the resilience of AC / DC hybrid power cyber-physical system under coordinated attack according to claim 1 is characterized in that: In step S2, the cyber-physical coordinated attack consists of two parts: an information attack and a physical attack. The information attack includes an attack A on the AC / DC branch status information upload channel. u and attacks on the generator and load adjustment command issuing channel A d , where A u Abbreviated as uplink channel attack, A d The physical attack is aimed at the AC and DC branch circuit breaker equipment. l ; The coordinated attack is launched by physical attack, which controls the opening and closing of the branch by tampering with the state of the branch circuit breaker. In the AC / DC hybrid power information-physical system, the AC / DC branch belongs to the physical layer, and the circuit breaker device is a processing layer node. The two correspond one to one, so the physical attack is expressed as: P a =P×A l =[B Pij ×A lij ,P Pij ,T Pij ,…] In the formula, A l is the attack matrix for the circuit breaker device at the processing layer, where the vector A lij =[A Pij ,1,1,…],A Pij is the attack vector against the communication interruption state; P and P a are the branch correlation matrices of the processing layer or physical layer before and after the attack, respectively, Pij , P Pij 、T Pij are the communication interruption state of the processing layer, the error probability and delay in the information transmission process; if B Pij =1, B Pij ×A lij = 0, it means that the branch between node i and node j is attacked and disconnected; if B Pij ×A lij =1, it means the branch is not attacked; The uplink channel attack and downlink channel attack on the information side are launched by injecting attack vectors into the inter-layer correlation characteristic matrix; the attack A on the uplink channel of the AC and DC branch status information u It is the correlation characteristic matrix P from the processing layer to the interval layer S The specific form is: In the formula, A u This is the attack matrix for the uplink channel from the processing layer to the spacing layer. is the correlation characteristic matrix from the processing layer to the spacer layer after the attack; S and S a are the network correlation characteristic matrices of the spacer layer before and after the attack. The branch status information received by the spacer layer is collected by the processing layer, and then transmitted to the spacer layer through the correlation characteristic matrix of the processing layer to the spacer layer. The upstream channel information attack injected during this period will change the original matrix P S The communication error probability in makes the interval layer matrix S after the attack a Receiving wrong information affects the judgment of the control layer; Attack on the generator and load adjustment command channel A d The attack principle is similar to A u Similarly, by calculating the inter-layer correlation characteristic matrix S from the spacing layer to the processing layer P The attack tampers with the generator's adjustment instructions to achieve the attack effect.

4. The method for evaluating the resilience of an AC / DC hybrid power cyber-physical system under coordinated attacks according to claim 1 is characterized in that: The specific operation steps of step S3 are as follows: S31. Based on the constructed multi-dimensional heterogeneous model and cyber-physical coordinated attack, a cascading failure model of AC / DC hybrid power cyber-physical system is established. The specific situation is as follows: Firstly, the basic fault is set according to the probability model of disturbance event occurrence, and the power flow distribution under the fault is obtained according to the AC and DC power flow calculation. When a branch exceeds the limit, whether the branch is disconnected is related to the degree of its exceeding the limit. When the degree of branch power exceeding the threshold is within the allowable range, it can be maintained for a short time. When the threshold is exceeded and not within the permissible range, an emergency control action will be triggered to disconnect immediately, so the AC / DC hybrid power cyber-physical system may be disconnected during the spread of cascading failures; In the cascading failure model, there are also channels for information uploading and command issuing. Information-side attacks may attack the information transmitted in the channel to achieve a synergistic effect, exacerbating the spread of cascading failures. Each evolution of the AC / DC hybrid power information-physical system involves three situations: maintaining a system, splitting into multiple subsystems, and completely splitting. When the first two situations occur, it is necessary to record the resilience evaluation indicators of the AC / DC hybrid power information-physical system and continue to evolve until the AC / DC hybrid power information-physical system can be completely stable or completely split. Whenever an electric device is out of operation, the AC / DC power flow calculation is first used to obtain the power flow distribution of the entire AC / DC hybrid power cyber-physical system. If there are still devices that may fail in the AC / DC hybrid power cyber-physical system, the AC / DC power grid emergency control model is used to solve the generator power adjustment and load reduction of each power node. In the process of uploading measurement data and issuing control instructions, the risk of cross-domain propagation of faults caused by secondary attacks on the information side is considered, which can fully reflect the occurrence of disturbance events and state transfer processes under network attacks. S32. It is proposed to use the AC linearization method to construct an AC / DC power grid emergency control model. When a disturbance event caused by a network attack occurs, the safe and stable operation of the AC / DC hybrid power information-physical system is maintained through adjustment processing, load shedding and machine cutting measures. The optimization control objective function of the AC / DC power grid emergency control model is: In the formula, ΔP di , ΔP gj are the power regulation of load node i and generator node j respectively, N b' 、N g are the load and the number of generators respectively; the constraints of the AC / DC power grid emergency control model include active power transmission constraints, node voltage amplitude constraints, generator power regulation constraints and maximum load reduction constraints.

5. The method for evaluating the resilience of AC / DC hybrid power cyber-physical system under coordinated attack according to claim 1 is characterized in that: The specific operation steps of step S4 are as follows: S41. The fault evolution process of the AC / DC hybrid power cyber-physical system after being attacked can be represented by the elastic system recovery process. According to the elastic system evaluation theory, a cascading fault recovery index CFRI is proposed to reflect the system response index of the AC / DC hybrid power cyber-physical system after being attacked. The expression is: In the formula, α is the scale stability factor; β is the performance stability factor; N b 、N acl 、N dcl are the total number of nodes, the number of AC branches, and the number of DC branches of the AC / DC hybrid power cyber-physical system, where the total number of nodes of the AC / DC hybrid power cyber-physical system includes load nodes and generator nodes; N b,x 、N acl,x 、N dcl,x are the number of system nodes, number of AC branches and number of DC branches of the AC / DC hybrid power cyber-physical system at time x; N b,x-1 、N acl,x-1 、N dcl,x-1 are the number of system nodes, number of AC branches and number of DC branches of the AC / DC hybrid power cyber-physical system at time x-1; L x , L all are the load and total load of the AC / DC hybrid power cyber-physical system at the evolution time x, respectively; ω1, ω2, ω3 are the node influence factor, AC branch influence factor, and DC branch influence factor, respectively; is the AC / DC power grid scale calculation function; since the scale of the AC / DC hybrid power cyber-physical system is taken into account, including nodes, branches and load, the changes in the system scale and load of the AC / DC hybrid power cyber-physical system from fault diffusion to decoupling after a cascading fault occurs are quantified, reflecting the evolution of the fault in the AC / DC hybrid power cyber-physical system. This indicator can be used as an indicator for comprehensively evaluating the decoupling process of cascading faults, and evaluating the recovery capability of the AC / DC hybrid power cyber-physical system in the face of cascading faults; S42. In order to more quickly evaluate the CFRI changes and robustness performance of the AC / DC hybrid power cyber-physical system after being attacked, improvements were made on the basis of CFRI, and the CFRI area model was used to score the CFRI level of the AC / DC hybrid power cyber-physical system. The formula of the CFRI area model is as follows: Where R is the robustness index of the CFRI curve; T is the evolution time; t0 is the simulation start time, t r is the moment when the AC / DC hybrid power information-physical system recovers to stability, that is, the AC / DC hybrid power information-physical system no longer experiences disconnection or load loss; CFRI(t) is the cascade disconnection resilience index curve of the AC / DC hybrid power information-physical system, which depicts the change of the cascade disconnection index of the AC / DC hybrid power information-physical system from being attacked to recovering to stability.

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