DoS attack-considered power system dynamic event-triggered load frequency control method

Abstract

The invention discloses an electric power system dynamic event trigger load frequency control method considering DoS attack, and belongs to the technical field of electric power system load frequency control, and the method comprises the steps: collecting electric power system physical parameters, and building an electric power system dynamic mathematical model; designing a state estimator and a hybrid dynamic event triggering mechanism based on the power system model; designing a load frequency regulation controller based on a hybrid dynamic event triggering mechanism; converting an original physical system into a hybrid system closed-loop model by considering a network communication DoS attack factor; based on a hybrid system theory, stability criteria related to DoS attack signal duration and attack frequency parameters are established. According to the invention, when the frequency and duration of DoS attack are maintained in a clear range, the designed event trigger control strategy can ensure that the power system is stable and occupies fewer communication resources.

Description

Technical Field

[0001] The invention relates to the technical field of power system load frequency control, and in particular to a power system dynamic event triggered load frequency control method considering DoS attacks. Background Art

[0002] As an important pillar of national development, the power system plays an important role in daily life and industry. Load frequency control has been commonly used in power system control for many years as a common method to ensure that the grid frequency is maintained at a stable value. In recent years, with the popularization of electric vehicles, the change of grid load frequency caused by electric vehicle charging has also attracted widespread attention.

[0003] As a typical physical information interaction system, the power system has distributed resources and assets connected through a wide area transmission network, and the operation involves information exchange between the physical layer and the network layer. Compared with traditional control methods, it breaks through the limitations of the physical area, has lower costs, and is easier to maintain. But on the other hand, it also brings many theoretical and practical challenges to the frequency regulation of the power system, such as transmission delays, sensor failures, etc. At the same time, the power system transmits data through the network, and the vulnerability of the network layer brings huge challenges to the reliability of the power system. Common network attacks, such as DoS attacks, will damage the availability of data, resulting in data packet loss. Therefore, the security issues of the power system have attracted great attention.

[0004] Traditional load frequency control methods are implemented through a sampling-data scheme, which usually adopts a time-triggered sampling method. In this framework, network congestion may occur due to excessive transmission data or node energy. Event-triggered control updates the control input only when the designed trigger rules are met, which can reduce the use of communication resources and has been proven to be an effective transmission data preservation strategy. However, most studies on event-triggered control are based only on sampling signals and do not focus on information security issues in networked control. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a method for dynamic event-triggered load frequency control of a power system taking into account DoS attacks. When the frequency and duration of DoS attacks are maintained within a clear range, the designed event-triggered control strategy can ensure the stability of the power system, occupy less communication resources, effectively ensure the stable operation of the power system frequency control, effectively eliminate the impact of DoS attacks, and improve security and stability.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: a method for controlling load frequency of a power system under dynamic event triggering considering DoS attacks, characterized in that: considering the power system under DoS attacks, a hybrid dynamic event triggering mechanism and a state estimator are designed based on the established hybrid system model, and a feedback controller is designed. The specific steps are as follows:

[0007] Step 1: Collect the physical parameters of the power system and establish a dynamic mathematical model of the power system;

[0008] Step 2: Design a state estimator and a hybrid dynamic event triggering mechanism based on the power system model;

[0009] Step 3: Design a load frequency regulation controller based on a hybrid dynamic event triggering mechanism;

[0010] Step 4: Considering the network communication DoS attack factor, the original physical system is transformed into a hybrid system closed-loop model;

[0011] Step 5: Based on the hybrid system theory, establish the stability criterion related to the DoS attack signal duration and attack frequency parameters.

[0012] The further improvement of the technical solution of the present invention is that the dynamic mathematical model of the power system established in step 1 is:

[0013]

[0014] y(t)=Cx(t)

[0015] where x T (t) = [f(t) X g (t) P g (t) P e (t) Δ(t)], u(t) is the controller input signal, ω(t) is the DoS attack signal, matrix A, B u , B W and C looks like this:

[0016]

[0017] Where D is the load damping coefficient; M is the inertia constant; R g is the speed regulator droop characteristic; T g is the speed regulator constant; T t is the turbine time constant; ρ e is the droop characteristic of electric vehicles; a e , a g They are expressed as the electric vehicle participation factor and the electric vehicle thermal turbine coefficient respectively; T eare the electric vehicle gain and the electric vehicle time constant respectively; b is the frequency deviation constant; f(t) is the frequency deviation function; X g is the speed regulator value position; P g is the turbine output power, P e is the incremental change of the electric vehicle, Δ(t) is the regional control error;

[0018] The mth DoS attack period is represented as H m ={h m}∪[h m ,h m +τ m ),in Represents the time when the mth DoS attack cycle starts. Represents the length of the DoS attack cycle; for the time constant Where T1<T2, definition in represents the set of time instants when communication is denied during the interval [T1, T2]; then the set of communications that are not affected by the DoS attack during the time interval [T1, T2] is Θ(T1, T2): = [T1, T2]\Ξ(T1, T2); the number of attacks on the power system during the time interval [T1, T2] is defined as n(T1, T2); Δ represents the minimum sample interval, and satisfies The frequency of DoS attacks is expressed as:

[0019]

[0020] in is a parameter. The DoS attack duration is expressed as:

[0021]

[0022] in as a parameter.

[0023] A further improvement of the technical solution of the present invention is that the state estimator designed in step 2 is used to estimate the state variables of the system, specifically:

[0024] Step 2.1: Design the state estimator as:

[0025]

[0026] where t k The trigger time of the event trigger. Estimate the state for the observer.

[0027] A further improvement of the technical solution of the present invention is that the mixed dynamic event triggering mechanism designed in step 2 is a dynamic mixed event triggering mechanism, specifically:

[0028] Step 2.2: Design a dynamic hybrid time trigger mechanism;

[0029] Step 2.21: Introduce the variable τ(t) and set its hybrid dynamics to:

[0030]

[0031] in is a continuous flow set, is a discrete transition set;

[0032] Step 2.22: Design a mixed dynamic event trigger mechanism

[0033]

[0034] Where m(t) is a symbolic variable used to indicate the permission or rejection status of the most recent transmission attempt at time t. When m(t) = 0, the most recent transmission is allowed; when m(t) = 1, it means that the most recent transmission is rejected. is the preset minimum event trigger interval, which satisfies and The dynamic variable η(t) satisfies the following hybrid dynamics:

[0035]

[0036] in φ∈[λ,λ -1 ] is an auxiliary variable, 0<λ<1 is a tuning parameter, satisfying where f φ (t) is in the following form:

[0037]

[0038] Where γ is a constant, L = |A + B u K|; No more than τ M , τ M In the following form:

[0039]

[0040] in The event trigger function Ψ(·) is designed as:

[0041]

[0042] in can be Solved.

[0043] A further improvement of the technical solution of the present invention is that the load frequency regulation controller designed in step 3 is:

[0044]

[0045] in, is the feedback matrix, α is a positive constant, and given a positive definite matrix Q, the matrix P can be obtained by solving the algebraic Riccati equation get.

[0046] A further improvement of the technical solution of the present invention is that under the DoS attack established in step 4, the hybrid system closed-loop model of the power system is:

[0047]

[0048] Where ξ(t): = [x T (t), e T (t), η T (t), τ T (t),φ T (t)] T , F(ξ(t), ω(t)) is continuous dynamics, and G(ξ(t)) is discrete jump dynamics. The continuous dynamics F(ξ(t), ω(t)) can be expressed as:

[0049]

[0050] in

[0051]

[0052] In the formula,

[0053] Continuous Stream Collection in The discrete jump dynamics G(ξ(t)) is expressed as:

[0054]

[0055] in

[0056]

[0057] The discrete transition set is expressed as

[0058] The further improvement of the technical solution of the present invention is that the specific steps of step 5 are as follows:

[0059] Step 5.1: Choose an appropriate Lyapunov function:

[0060] V(ξ(t))=x T(t)Px(t)+γφ(t)|e(t)| 2 +η(t)

[0061] When the system is in the trigger triggering moment, that is hour, It can be seen that the power system is not affected by the DoS attack at this time. According to the event triggering mechanism in step 2.2, at this time η(t k )=0, combined with the discrete jump dynamics of the system, we can get:

[0062]

[0063] Because at the triggering moment So φ(t)=φ miet Available

[0064] V(ξ + (t))-V(ξ(t))=0

[0065] when When, according to its discrete jump dynamics, e + (t)=e(t),φ + (t) = φ(t), η + (t) = η(t) It can be seen that the above formula still holds true. Therefore, it is believed that at the triggering moment, regardless of whether the transmission channel is attacked or not, the constructed Lyapunov function does not increase;

[0066] Step 5.2: Based on the Lyapunov function designed in step 5.1, analyze the stability of the closed-loop system during the power flow process and the parameter selection range of the event trigger mechanism.

[0067] The further improvement of the technical solution of the present invention is that the specific steps of step 5.2 are as follows:

[0068] Step 5.21: Consider the case where the most recent transmission attempt was successful, that is, m(t) = 0; in this case, the Lyapunov function is differentiated and the parameters c,∈,γ,ρ,γ are selected. ω Satisfies the matrix inequality

[0069]

[0070] Established; among them Π 11 =-(1-ρ)Q+(B u K) T B u K, Π 13 =(B u K) T B w +PB w , Π 22 =-γ 2+c+∈, The range of design parameters is ∈>0,γ>∈+c,0<ρ<1,γ ω >0; we can get

[0071]

[0072] Design parameters It can be seen that the system is stable; at the same time When , we know that the system is stable;

[0073] Step 5.22: Consider the case where the most recent control signal transmission was rejected, that is, m(t) = 1; in this case, the derivative of the Lyapunov function yields

[0074]

[0075] Design parameters It can be seen that the system is stable at this time;

[0076] Step 5.23: Consider the driver delay caused by DoS attack; for any time 0≤T1≤T2, define the interval Then the interval [T1, T2] is and disjoint; and is the union of subintervals of [T1, T2], and transmission is reliable over these subintervals. It is easy to obtain that the mth effective time interval is and the corresponding attack-induced driving delay; from step 5.21 and step 5.22, we can get The upper bound of is:

[0077]

[0078] The parameters

[0079] Step 5.24: For analysis and The stability of is expressed as:

[0080]

[0081] in

[0082]

[0083] Auxiliary sequence representing the instant when the effective attack starts, v k Indicates from k The time until the next allowed transmission attempt, interval Z kand W k In fact, it represents the stable mode and unstable mode of the power system under DoS attack. It can be obtained that the derivative of the Lyapunov function in step 5.21 satisfies:

[0084]

[0085] where κ * =(λs + λ u )κ dos ,λ * =λ s -(λ s +λ u ) / τ dos , when ω(t)=0

[0086]

[0087] in When ω(t)≠0

[0088]

[0089] It is easy to obtain that when the design parameter λ s , u satisfy

[0090]

[0091] When , the global index of the power system is stable.

[0092] Due to the adoption of the above technical solution, the technical progress achieved by the present invention is as follows: by considering the impact of DoS attacks, a nonlinear dynamic model of the power system that is more in line with actual working conditions is established. By designing a hybrid dynamic event triggering mechanism, a novel hybrid dynamic model of the power system is established. When the frequency and duration of DoS attacks are maintained in a clear range, the designed event triggering control strategy can ensure the stability of the power system and occupy less communication resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.

[0094] Figure 1 It is a schematic diagram of the process of the present invention;

[0095] Figure 2is the introduced DoS attack response curve;

[0096] Figure 3 is the state response curve of the power system under DoS attack;

[0097] Figure 4 is the observer error curve;

[0098] Figure 5 It is the triggering time of the event trigger. DETAILED DESCRIPTION

[0099] The present invention is further described in detail below in conjunction with embodiments:

[0100] like Figure 1 As shown, it is a flow chart of a method for dynamic event-triggered load frequency control of a power system considering DoS attacks. First, according to the dynamics theorem, a power system model is established; then an estimator is set to design a load frequency controller of the power system; then, considering the impact of DoS attacks, a hybrid dynamic event triggering mechanism is designed; then, a hybrid dynamic model of the power system is established according to the designed event triggering mechanism; finally, a power system load frequency controller based on a hybrid event triggering mechanism is designed in combination with the established hybrid dynamic system model of the power system. The specific steps of the method are as follows:

[0101] Step 1: Collect the physical parameters of the power system as shown in Table 1 and establish a dynamic mathematical model of the power system;

[0102] Table 1 Power system simulation parameters

[0103]

[0104] Establishment of dynamic mathematical model of power system:

[0105]

[0106] y(t))=Cx(t)

[0107] where x T (t) = [f(t) X g (t) P g (t) P e (t) Δ(t)], u(t) is the controller input signal, ω(t) is the DoS attack signal, and the matrix A, B u , B W and C looks like this:

[0108]

[0109] Where D is the load damping coefficient; M is the inertia constant; R g is the speed regulator droop characteristic; Tg is the speed regulator constant; T t is the turbine time constant; ρ e is the droop characteristic of electric vehicles; a e , a g They are expressed as the electric vehicle participation factor and the electric vehicle thermal turbine coefficient respectively; T e are the electric vehicle gain and the electric vehicle time constant respectively; b is the frequency deviation constant; f(t) is the frequency deviation function; X g is the speed regulator value position; P g is the turbine output power, P e is the incremental change of the electric vehicle, and Δ(t) is the regional control error.

[0110] The mth DoS attack period is represented as H m ={h m}∪[h m ,h m +τ m ),in Represents the time when the mth DoS attack cycle starts. Represents the length of the DoS attack cycle. For the time constant Where T1<T1, definition in represents the set of time instants during the interval [T1, T2] when communication is denied. Then, the set of communications that are not affected by the DoS attack during the time interval [T1, T2] is Θ(T1, T2): = [T1, T2]\Ξ(T1, T2). Define the number of attacks on the power system during the time interval [T1, T2] as n(T1, T2). Δ represents the minimum sample interval and satisfies In this patent, the frequency of DoS attacks is expressed as:

[0111]

[0112] in is a parameter. The DoS attack duration is expressed as:

[0113]

[0114] in as a parameter.

[0115] Step 2: Design a state estimator and a hybrid dynamic event triggering mechanism based on the power system model;

[0116] Step 2.1: Design the state estimator as:

[0117]

[0118] where t k The trigger time of the event trigger. Estimate the state for the observer.

[0119] Step 2.2: Design a dynamic hybrid time trigger mechanism;

[0120] Step 2.21: Introduce the variable τ(t) and set its hybrid dynamics to:

[0121]

[0122] in is a continuous flow set, is a discrete transition set;

[0123] Step 2.22: Design a mixed dynamic event trigger mechanism

[0124]

[0125] Where m(t) is a symbolic variable used to indicate the permission or rejection status of the most recent transmission attempt at time t. When m(t) = 0, the most recent transmission is allowed; when m(t) = 1, it means that the most recent transmission is rejected. is the preset minimum event trigger interval, which satisfies and The dynamic variable η(t) satisfies the following hybrid dynamics:

[0126]

[0127] in φ∈[λ,λ -1 ] is an auxiliary variable, 0<λ<1 is a tuning parameter, satisfying where f φ (t) is in the following form:

[0128]

[0129] Where γ is a constant, L = |A + B u K|; No more than τ M , τ M In the following form:

[0130]

[0131] in The event trigger function Ψ(·) is designed as:

[0132]

[0133] in can be Solved.

[0134] Step 3: Design a load frequency regulation controller based on a hybrid dynamic event triggering mechanism;

[0135] The load frequency regulation controller is:

[0136]

[0137] in, is the feedback matrix, α is a positive constant, and given a positive definite matrix Q, the matrix P can be obtained by solving the algebraic Riccati equation get.

[0138] Step 4: Considering the network communication DoS attack factor, the original physical system is transformed into a hybrid system closed-loop model;

[0139] Considering the network communication DoS attack factor, the hybrid mechanics model of the power system is established as follows:

[0140]

[0141] Where ξ(t): = [x T (t), e T (t), η T (t), τ T (t),φ T (t)] T , F(ξ(t), ω(t)) is continuous dynamics, and G(ξ(t)) is discrete jump dynamics. The continuous dynamics F(ξ(t), ω(t)) can be expressed as:

[0142]

[0143] in

[0144]

[0145] In the formula,

[0146] Continuous Stream Collection in The discrete jump dynamics G(ξ(t)) is expressed as

[0147]

[0148] in

[0149]

[0150] The discrete transition set is expressed as

[0151] Step 5: Based on the hybrid system theory, establish the stability criterion related to the DoS attack signal duration and attack frequency parameters.

[0152] Step 5.1: Choose an appropriate Lyapunov function:

[0153] V(ξ(t))=x T (t)Px(t)+γφ(t)|e(t)| 2 +η(t)

[0154] When the system is in the trigger triggering moment, that is hour, It can be seen that the power system is not affected by the DoS attack at this time. According to the event triggering mechanism in step 2.2, at this time η(t k )=0, combined with the discrete jump dynamics of the system, we can get:

[0155]

[0156] Because at the triggering moment So φ(t)=φ miet Available

[0157] V(ξ + (t))-V(ξ(t))=0

[0158] when When, according to its discrete jump dynamics, e + (t)=e(t),φ + (t) = φ(t), η + (t) = η(t) It can be seen that the above formula still holds true. Therefore, it is believed that at the triggering moment, regardless of whether the transmission channel is attacked or not, the constructed Lyapunov function does not increase;

[0159] Step 5.2: Based on the Lyapunov function designed in step 5.1, analyze the stability of the closed-loop system during the power flow process and the parameter selection range of the event trigger mechanism.

[0160] Step 5.21: Consider the case where the most recent transmission attempt was successful, that is, m(t) = 0; in this case, the Lyapunov function is differentiated and the parameters c,∈,γ,ρ,γ are selected. ω Satisfies the matrix inequality

[0161]

[0162] Established; among them Π 11 =-(1-ρ)Q+(B u K) T B u K, Π 13 =-(Bu K) T B w +PB w ,∏ 22 =-γ 2 +c+ε, The range of design parameters is ε>0,γ>∈+c,0<ρ<1,γ ω >0; we can get

[0163]

[0164] Design parameters It can be seen that the system is stable; at the same time When , we know that the system is stable;

[0165] Step 5.22: Consider the case where the most recent control signal transmission was rejected, that is, m(t) = 1; in this case, the derivative of the Lyapunov function yields

[0166]

[0167] Design parameters It can be seen that the system is stable at this time;

[0168] Step 5.23: Consider the driver delay caused by DoS attack; for any time 0≤T1≤T2, define the interval Then the interval [T1, T2] is and disjoint; and is the union of subintervals of [T1, T2], and transmission is reliable over these subintervals. It is easy to obtain that the mth effective time interval is and the corresponding attack-induced driving delay; from step 5.21 and step 5.22, we can get The upper bound of is:

[0169]

[0170] The parameters

[0171] Step 5.24: For analysis and The stability of is expressed as:

[0172]

[0173] in

[0174]

[0175] Auxiliary sequence representing the instant when the effective attack starts, v k Indicates from k The time until the next allowed transmission attempt, interval Z k and W k In fact, it represents the stable mode and unstable mode of the power system under DoS attack. It can be obtained that the derivative of the Lyapunov function in step 5.21 satisfies:

[0176]

[0177] where κ * =(λ s +λ u )κ dos ,λ * =λ s -(λ s +λ u ) / τ dos , when ω(t)=0

[0178]

[0179] in When ω(t)≠0

[0180]

[0181] It is easy to obtain that when the design parameter λ s , u satisfy

[0182]

[0183] When , the global index of the power system is stable.

[0184] According to the above control method, simulation is performed. Figure 2 The figure shows the DoS attack curve of the power system. The controller gain is selected as K = [0.0863 0.0936 0.0651 0.2812 0.2828] After applying the designed load frequency controller, Figure 3 The response curve of the system state is given. Figure 4 The error between the system state and the state estimator is given, and it can be seen that the observation error is converged. Figure 5 The triggering time of the designed mixed dynamic event trigger is given in . It can be seen that the load frequency controller designed by the present invention can ensure the stability of the power system when the power system is attacked by DoS.

[0185] The embodiments described above are merely descriptions of preferred implementation modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for controlling load frequency in a power system under dynamic event triggering considering DoS attacks, characterized in that: Considering the power system under DoS attack, the hybrid dynamic event triggering mechanism and state estimator are designed based on the established hybrid system model, and the feedback controller is designed. The specific steps are as follows: Step 1: Collect the physical parameters of the power system and establish a dynamic mathematical model of the power system; Step 2: Design a state estimator and a hybrid dynamic event triggering mechanism based on the power system model; Step 3: Design a load frequency regulation controller based on a hybrid dynamic event triggering mechanism; Step 4: Considering the network communication DoS attack factor, the original physical system is transformed into a hybrid system closed-loop model; Step 5: Based on the hybrid system theory, establish the stability criterion related to the DoS attack signal duration and attack frequency parameters.

2. The method for controlling load frequency of a power system triggered by dynamic events considering DoS attacks according to claim 1, characterized in that: The dynamic mathematical model of the power system established in step 1 is: y(t)=Cx(t) where x T (t) = [f(t) X g (t) P g (t) P e (t) Δ(t)], u(t) is the controller input signal, ω(t) is the DoS attack signal, and the matrix A, B u , B W and C looks like this: Where D is the load damping coefficient; M is the inertia constant; R g is the speed regulator droop characteristic; T g is the speed regulator constant; T t is the turbine time constant; ρ e is the droop characteristic of electric vehicles; a e , a g They are expressed as the electric vehicle participation factor and the electric vehicle thermal turbine coefficient respectively; T e are the electric vehicle gain and the electric vehicle time constant respectively; b is the frequency deviation constant; f(t) is the frequency deviation function; X g is the speed regulator value position; P g is the turbine output power, P e is the incremental change of the electric vehicle, Δ(t) is the regional control error; The mth DoS attack period is represented as H m ={h m }U[h m ,h m +τ m ),in Represents the time when the mth DoS attack cycle starts. Represents the length of the DoS attack cycle; for the time constant Where T1<T2, definition in represents the set of time instants during which communication is denied during the interval [T1, T2]; then the set of communications not affected by the DoS attack during the time interval [T1, T2] is Θ(T1, T2): = [T1, T2]\Ξ(T1, T2); the number of attacks on the power system during the time interval [T1, T2] is defined as n(T1, T2); Δ represents the minimum sample interval and satisfies The frequency of DoS attacks is expressed as: in is a parameter. The DoS attack duration is expressed as: in as a parameter.

3. The method for controlling load frequency of a power system triggered by dynamic events considering DoS attacks according to claim 1, characterized in that: The state estimator designed in step 2 is used to estimate the state variables of the system, specifically: Step 2.1: Design the state estimator as: where t k The trigger time of the event trigger. Estimate the state for the observer.

4. The method for controlling load frequency in a power system triggered by dynamic events considering DoS attacks according to claim 1, characterized in that: The mixed dynamic event triggering mechanism designed in step 2 is a dynamic mixed event triggering mechanism, specifically: Step 2.2: Design a dynamic hybrid time trigger mechanism; Step 2.21: Introduce the variable τ(t) and set its hybrid dynamics to: in is a continuous flow set, is a discrete transition set; Step 2.22: Design a mixed dynamic event trigger mechanism Where m(t) is a symbolic variable used to indicate the permission or rejection status of the most recent transmission attempt at time t. When m(t) = 0, the most recent transmission is allowed; when m(t) = 1, it means that the most recent transmission is rejected. is the preset minimum event trigger interval, which satisfies and The dynamic variable η(t) satisfies the following hybrid dynamics: in φ∈[λ,λ -1 ] is an auxiliary variable, 0<λ<1 is a tuning parameter, satisfying. where f φ (t) is in the following form: Where γ is a constant, L = |A + B u K|; No more than τ M , τ M In the following form: in The event trigger function Ψ(·) is designed as: in can be Solved.

5. The method for controlling load frequency of a power system triggered by dynamic events considering DoS attacks according to claim 1, characterized in that: The load frequency regulation controller designed in step 3 is: in, is the feedback matrix, α is a positive constant, and given a positive definite matrix Q, the matrix P can be obtained by solving the algebraic Riccati equation get.

6. The method for controlling load frequency of a power system triggered by dynamic events considering DoS attacks according to claim 1, characterized in that: Under the DoS attack established in step 4, the hybrid system closed-loop model of the power system is: Where ξ(t): = [x T (t), e T (t), η T (t), τ T (t),φ T (t)] T , F(ξ(t), ω(t)) is continuous dynamics, and G(ξ(t)) is discrete jump dynamics. The continuous dynamics F(ξ(t), ω(t)) can be expressed as: in In the formula, Continuous Stream Collection in The discrete jump dynamics G(ξ(t)) is expressed as: in The discrete transition set is expressed as 7. The method for controlling load frequency of a power system triggered by dynamic events considering DoS attacks according to claim 1, characterized in that: Step 5 The specific steps are as follows: Step 5.1: Choose an appropriate Lyapunov function: V(ξ(t))=x T (t)Px(t)+γφ(t)|e(t)| 2 +η(t) When the system is in the trigger triggering moment, that is hour, It can be seen that the power system is not affected by the DoS attack at this time. According to the event triggering mechanism in step 2.2, at this time η(t k )=0, combined with the discrete jump dynamics of the system, we can get: Because at the triggering moment So φ(t)=φ miet Available V(ξ + (t))-V(ξ(t))=0 when When, according to its discrete jump dynamics, e + (t)=e(t),φ + (t) = φ(t), η7 + (t)= ηη (t) It can be seen that the above formula still holds true. Therefore, it is believed that at the triggering moment, regardless of whether the transmission channel is attacked or not, the constructed Lyapunov function does not increase; Step 5.2: Based on the Lyapunov function designed in step 5.1, analyze the stability of the closed-loop system during the power flow process and the parameter selection range of the event trigger mechanism.

8. The method for controlling load frequency in a power system triggered by dynamic events considering DoS attacks according to claim 7, characterized in that: Step 5.2 The specific steps are as follows: Step 5.21: Consider the case where the most recent transmission attempt was successful, that is, m(t) = 0; in this case, the Lyapunov function is differentiated and the parameters c,∈,γ,ρ,γ are selected. ω Satisfies the matrix inequality Established; among them Π 11 =-(1-ρ)Q+(B u K) T B u K, Π 13 =-(B u K) T B w +PB ω , Π 22 =-γ 2 +c+∈, The range of design parameters is ∈>0,γ>∈+c,0<ρ<1,γ ω >0; we can get Design parameters It can be seen that the system is stable; at the same time When , we know that the system is stable; Step 5.22: Consider the case where the most recent control signal transmission was rejected, that is, m(t) = 1; in this case, the derivative of the Lyapunov function yields Design parameters It can be seen that the system is stable at this time; Step 5.23: Consider the driver delay caused by DoS attack; for any time 0≤T1≤T2, define the interval Then the interval [T1, T2] is and disjoint; and is the union of subintervals of [T1, T2], and transmission is reliable over these subintervals. It is easy to obtain that the mth effective time interval is and the corresponding attack-induced driving delay; from step 5.21 and step 5.22, we can get The upper bound of is: The parameters Step 5.24: For analysis Hehe The stability of is expressed as: in {ζ k } k∈N Auxiliary sequence representing the instant when the effective attack starts, v k Indicates that from k The time until the next allowed transmission attempt, interval Z k and W k In fact, it represents the stable mode and unstable mode of the power system under DoS attack. It can be obtained that the derivative of the Lyapunov function in step 5.21 satisfies: where κ * = (λ s + λ u ) κ dos , λ * = λ s - (λ s + λ u ) / τ dos when ω(t) = 0 in When ω(t)≠0 It is easy to obtain that when the design parameter λ s , u satisfy When , the global index of the power system is stable.

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