Voltage elastic tracking control method, computer device and storage medium

Abstract

The application belongs to the field of security control of micro-grid systems, and discloses a voltage elastic tracking control method, computer equipment and a storage medium. The method can solve the secondary side voltage elastic tracking control problem of the micro-grid system under denial of service attack, and can make the system run stably through attack compensation mechanism when the micro-grid system is attacked maliciously in the running process, so as to avoid serious consequences. The method solves the unobservable state through the design of a state observer, and realizes accurate acquisition of the voltage state. Compared with the complex micro-grid system without the design of the observer, the introduction of the observer has more application value in actual engineering application. The method is an elastic tracking controller designed under a completely distributed control framework, and improves the scalability and flexibility of the system. In addition, the introduction of the event triggering mechanism not only saves the communication network resources of the micro-grid system, but also reduces the risk of system attack to a certain extent.

Description

Technical Field

[0001] This invention belongs to the field of security control of microgrid systems, and relates to a fully distributed event-triggered secondary voltage elastic tracking control method, computer equipment, and storage medium for microgrids based on observers under denial-of-service attacks. Background Technology

[0002] A microgrid is a small-scale power system composed of distributed generators, power electronic conversion devices, distributed energy storage, and loads, possessing power generation, distribution, and consumption capabilities. It is a new type of network structure in my country's power grid construction. A microgrid system is formed by multiple distributed generators communicating with each other through a network. Typically, a microgrid operates in grid-connected mode; however, when the system is unstable due to external interference, it will operate as an island. Due to the openness and vulnerability of the network, it is inevitably susceptible to damage by malicious attackers. Furthermore, continuous communication between distributed generators not only wastes communication resources but also provides attackers with more opportunities to disrupt the microgrid system. The power system, as a crucial infrastructure, ensures the normal production and daily life of people. Damage to the power system will lead to economic losses and even hinder social development. Therefore, researching safe and reliable microgrid systems remains a continuous focus and research object.

[0003] Considering the issue of communication resource utilization, several intelligent sampling and transmission mechanisms have been extensively studied, including static event-triggered mechanisms, self-triggered mechanisms, adaptive event-triggered mechanisms, dynamic event-triggered mechanisms, and data-driven mechanisms. Furthermore, existing methods, while considering the introduction of event-triggered mechanisms to improve communication resource utilization, are only suitable for power grid systems that do not exhibit severe dynamic or stability issues. Additionally, some control methods have been designed to address the stability of microgrid systems under denial-of-service attacks; however, the controllers designed for such attacks are unstable and prone to damaging the system. In summary, to better ensure the safe and reliable operation of microgrid systems, more effective control strategies are needed.

[0004] Furthermore, due to the openness and vulnerability of network links in microgrid systems, a large amount of critical information flow and data transmission occur during peak operation periods, attracting denial-of-service (DoS) attackers who can launch malicious attacks, seize network servers, or maliciously tamper with transmitted data, leading to system collapse. Traditional communication networks are often susceptible to interference from channel bandwidth limitations, data transmission congestion, and limited communication resources, resulting in a significant reduction in the control performance of microgrids and, in severe cases, causing system instability. A large amount of state information often presents unpredictable conditions during transmission, which can cause instability in a distributed generator due to its inability to obtain state information from neighboring generators in a timely manner, subsequently causing problems with the entire system, or even paralyzing it, resulting in severe economic losses. Therefore, research on secondary-side voltage elastic tracking control methods for microgrid systems under DoS attacks has significant practical implications and application value. Summary of the Invention

[0005] The purpose of this invention is to provide a fully distributed event-triggered secondary voltage elastic tracking control method for microgrids based on observers under denial-of-service attacks, so as to ensure the stability of microgrid systems under unpredictable system states and network attacks, while reducing the number of communications and improving the utilization rate of communication resources.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A voltage elastic tracking control method includes the following steps:

[0008] Step 1. Establish a dynamic model of the distributed generator and provide a dynamic model of the reference generator signal;

[0009] Step 2. Establish the operational model of the state observer based on the dynamic model in Step 1;

[0010] Step 3. Based on the attack mechanism of denial-of-service attacks, we give the piecewise functions representing the occurrence and non-occurrence of the attack, as well as the assumptions about the attack duration and frequency that denial-of-service attacks satisfy.

[0011] Step 4. Based on the distributed microgrid dynamic model and state observer operation model described in Steps 1 and 2, and the attack forms considered in Step 3, give the control objective;

[0012] Step 5. Based on the control objective described in Step 4, obtain the controller gain and the observer gain;

[0013] Step 6. Based on the piecewise function described in Step 3 and the controller gain and observer gain in Step 5, give the attack compensation mechanism and event triggering mechanism;

[0014] Step 7. Based on the controller gain obtained in Step 5 and the attack compensation mechanism designed in Step 6, an event-triggered elastic controller is obtained. By comparing the voltage state information of its own generator, the voltage state information received from neighboring generators, and the reference voltage information, the voltage state information of its own generator is continuously adjusted to reduce the difference between its own generator voltage and the reference voltage, thereby completing the voltage tracking control task.

[0015] Furthermore, based on the aforementioned voltage elastic tracking control method, this invention also proposes a computer device, which includes a memory and one or more processors.

[0016] The memory stores executable code, and when the processor executes the executable code, it implements the steps of the voltage elastic tracking control method described above.

[0017] Furthermore, based on the aforementioned voltage elastic tracking control method, this invention also proposes a computer-readable storage medium on which a program is stored.

[0018] When the program is executed by the processor, it is used to implement the steps of the voltage elastic tracking control method described above.

[0019] Compared with the prior art, the present invention has the following advantages:

[0020] As described above, this invention discloses a fully distributed event-triggered resilient voltage tracking control method for microgrids based on an observer under denial-of-service attacks. This method can solve the problem of resilient voltage tracking control on the secondary side of a microgrid system under denial-of-service attacks. Therefore, when a microgrid system is maliciously attacked during operation, the attack compensation mechanism can ensure stable system operation and avoid serious consequences. This method solves the problem of unmeasurable state by designing a state observer, achieving accurate acquisition of voltage state. Compared with complex microgrid systems without observers, the introduction of observers has greater application value in practical engineering applications and is very much in line with the needs of critical facilities like microgrid systems that are closely related to people's lives. In addition, the resilient tracking controller designed under the fully distributed control framework of this invention improves the scalability and flexibility of the system. Furthermore, the introduction of the event-triggered mechanism not only saves communication network resources of the microgrid system but also reduces the risk of system attacks to a certain extent. This is also a crucial issue for power systems. Attached Figure Description

[0021] Figure 1 This is a flowchart of the voltage elastic tracking control method in an embodiment of the present invention.

[0022] Figure 2This is a microgrid structure diagram under the control method in the embodiments of the present invention. Detailed Implementation

[0023] Example 1

[0024] This embodiment 1 describes a fully distributed event-triggered secondary voltage elastic tracking control method for microgrids based on observers under denial-of-service attacks, in order to solve the technical shortcomings of current methods that simultaneously consider state unpredictability and network security issues in microgrid systems, as well as the technical problem of effective utilization of communication resources.

[0025] Inspired by the simple design, accurate observation, experience in designing compensation mechanisms, and event triggering mechanisms of observers, this invention designs an observer to solve the problem of unpredictable state. By using the state information of the most recently successfully transmitted state information of a neighboring generator as a compensation term, the stability of the controller is guaranteed. Furthermore, a reasonable and effective event triggering mechanism is designed using known state information, which is beneficial for solving the problem of elastic tracking control of the secondary voltage of a microgrid under denial-of-service attacks, thereby improving the stability of system operation.

[0026] like Figure 1 As shown, the voltage elastic tracking control method in this embodiment includes the following steps:

[0027] Step 1. Establish a dynamic model of the distributed generator and provide a dynamic model of the reference generator signal.

[0028] A dynamic model of the distributed generator is established using linearization techniques, as follows:

[0029]

[0030] Where, x i (t) represents the system state. It is x i The derivative of (t), u i (t) represents the controller input, A represents the system matrix, B represents the input matrix, and i represents the i-th distributed generator in the microgrid system, i = 1, ..., N.

[0031] N represents the number of distributed generators in the microgrid system; the dynamic model of the reference generator signal is represented as:

[0032]

[0033] in, The reference signal is time-invariant and the control input u0 = 0;

[0034] v ref This represents the magnitude of the secondary voltage and is a constant, i.e., v ref =220V.

[0035] Step 2. Establish the operational model of the state observer based on the dynamic model in Step 1.

[0036] The operational model of the state observer is expressed as:

[0037]

[0038] in, To observe the system status; yes The derivative of , where F represents the observation gain.

[0039] Step 3. Consider the case of a denial-of-service attack on a microgrid system. Based on the attack mechanism of denial-of-service attacks, we give piecewise functions representing the events of attack occurrence and non-occurrence, as well as the assumptions about the attack duration and frequency that a denial-of-service attack must satisfy.

[0040] The attack mechanism of a denial-of-service attack is as follows:

[0041] By sending a large number of useless data packets to the system, the communication channel is blocked, preventing normal system data packets from being transmitted to the control center in a timely manner, thus preventing the control center from generating effective control signals in a timely manner.

[0042] definition This is the (k+1)th attack range. t represents the time interval during which an attacker will not launch a malicious attack on the system. 2k t 2k+1 t 2k+2 These represent the 2k, 2k+1, and 2k+2 time points, respectively.

[0043] Therefore, the definition Ξ represents the total duration of the attack by the attacker. s (0,t)=[0,t) / Ξ a (0,t) represents the total duration during which the attacker does not launch an attack.

[0044] in, Let represent the set of positive integers. For ease of analysis, piecewise functions are given below to represent the events of an attack occurring and not occurring:

[0045]

[0046] Wherein, the system is initially unaffected by attacks, i.e., θ(0) = 0; τ is a time variable; Ξ s (τ,t),Ξ a (τ,t) represent the time intervals during which the attack does not occur and the time intervals during which the attack occurs, respectively.

[0047] The assumptions regarding attack duration and frequency required for a denial-of-service attack are expressed as follows:

[0048] Definition Ξ a (0,t) represents the total duration of the attack over the entire time span [0,t), where there exist positive constants N1 and τ1 such that the following inequality holds:

[0049] Define Ω(0,t) as the number of times the attack occurs over the entire time span [0,t). Then there exist positive constants N² and τ² such that the following inequality holds:

[0050] Step 4. Based on the distributed microgrid dynamic model and state observer operational model described in Steps 1 and 2, and the attack forms considered in Step 3, the control objective is given, which is expressed as:

[0051] ξ i (t)=x i (t)-x0;

[0052] Where, ξ i (t) represents the voltage tracking error; the controller input u is designed to... i (t), making the state x of each distributed generator system i (t) approaches the reference signal x0, making the tracking error ξ i (t) converges to a bound, thus achieving voltage tracking control.

[0053] Step 5. Based on the control objective described in Step 4, obtain the controller gain and the observer gain.

[0054] The method for obtaining the controller gain and observer gain is expressed as follows:

[0055] Step 5.1. Solve the following Riccati equation:

[0056]

[0057] We obtain solutions P > 0 and Q > 0; P > 0 and Q > 0 indicate that matrices P and Q are positive definite.

[0058] Where I represents the identity matrix of the corresponding dimension.

[0059] Step 5.2. Select controller gain K = B T P, observer gain

[0060] Step 6. Based on the piecewise function described in Step 3 and the controller gain and observer gain in Step 5, give the attack compensation mechanism and event triggering mechanism.

[0061] The described attack compensation mechanism is expressed as follows:

[0062] in, This represents the k′-th trigger time of the j-th distributed generator. This indicates the moment when distributed generator j most recently successfully transmitted information to the target generator before the system was attacked.

[0063] The design process of the event triggering mechanism is as follows:

[0064] First, define e i (t) represents the measurement error of the i-th distributed generator, and its expression is:

[0065]

[0066] in, These represent the trigger times of the k-th and k+1-th events for the i-th distributed generator, respectively; additionally, the event trigger time... This is determined by the event triggering mechanism designed below.

[0067] Secondly, the designed event triggering function f is given. i The expression for (t) is as follows:

[0068] f i (t)=(1-θ(t))f i s (t)+θ(t)f i a (t).

[0069] Where, γ i and l i It is a positive scalar, and Γ = PBB T P;a ij This indicates the communication status between distributed generator i and distributed generator j; when a ij When a = 1, it indicates that distributed generator i and distributed generator j can communicate; when a ij When = 0, it means that there is no communication between distributed generator i and distributed generator j.

[0070]

[0071]

[0072] When j = 0, it represents a reference generator. i (t) is the adaptive parameter, c i The expression for (t) and its update law are described as follows:

[0073]

[0074] in:

[0075]

[0076]

[0077] Where, π ij =π ji >0, p ij =p ji >0, c ij (t)=c ji (t)>0.

[0078] Define q i (t) is an internal dynamic variable, q i The dynamic equation of (t) is expressed as:

[0079]

[0080] Where, α i >0, μ i ∈(0,1), q i The initial value of (t) is q i (0)>0.

[0081] Finally, the event triggering time sequence Determined by the following conditions:

[0082]

[0083] Where inf{·} denotes the lower bound function. This represents the k-th triggering time of the i-th distributed generator.

[0084] Step 7. Based on the controller gain obtained in Step 5 and the attack compensation mechanism designed in Step 6, an event-triggered elastic controller is obtained. By comparing the voltage state information of its own generator, the voltage state information received from neighboring generators, and the reference voltage information, the voltage state information of its own generator is continuously adjusted to reduce the difference between its own generator voltage and the reference voltage, thereby completing the voltage tracking control task.

[0085] In step 7, the event triggers the controller input u of the elastic controller. i (t) is represented as:

[0086]

[0087] in:

[0088] By comparing the voltage of its own generator in the event-triggered elastic controller with the voltage received from neighboring generators and the reference voltage information, the voltage of its own generator is continuously adjusted to reduce the difference between the voltage and the reference voltage, thus completing the voltage tracking control task.

[0089] Specifically, such as Figure 2 As shown, a reference voltage signal x0 is sent to distributed generator i, and the voltage sensor senses the voltage information x0 sent by distributed generator i. i (t), considering the possibility of inaccurate information acquisition, an observer is designed to obtain the observed voltage state. To reduce the number of communications and avoid wasting resources, trigger voltage information will be used. During transmission, the trigger voltage information is activated. The information is transmitted to distributed generator j via the network link. Similarly, distributed generator j will transmit the trigger voltage information it generates. Send the trigger voltage information to distributed generator i. and This voltage is sent as a controller input to actuators, such as household appliances, to regulate the voltage to the required 220V AC power for normal operation. When the network is under a denial-of-service attack, the trigger voltage information of distributed generator j cannot be transmitted normally to distributed generator i. In this case, the voltage information most recently successfully transmitted from distributed generator j to distributed generator i will be added as a compensation term to the controller input to stabilize the system and achieve the goal of voltage tracking.

[0090] Example 2

[0091] This embodiment 2 describes a computer device used to implement the steps of the voltage elastic tracking control method described in embodiment 1 above.

[0092] The computer device includes a memory and one or more processors. Executable code is stored in the memory, and when the processor executes the executable code, it is used to implement the steps of the voltage elastic tracking control method described above.

[0093] In this embodiment, the computer device can be any device or apparatus with data processing capabilities, and will not be described in detail here.

[0094] Example 3

[0095] This embodiment 3 describes a computer-readable storage medium for implementing the steps of the voltage elastic tracking control method described in embodiment 1 above.

[0096] The computer-readable storage medium in this embodiment 3 stores a program that, when executed by a processor, is used to implement the steps of the voltage elastic tracking control method described above.

[0097] The computer-readable storage medium can be an internal storage unit of any device or apparatus with data processing capabilities, such as a hard disk or memory, or an external storage device of any device with data processing capabilities, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc.

[0098] Of course, the above description is only a preferred embodiment of the present invention. The present invention is not limited to the above-described embodiments. It should be noted that any equivalent substitutions or obvious modifications made by those skilled in the art under the guidance of this specification fall within the scope of this specification and should be protected by the present invention.

Claims

1. A voltage elastic tracking control method, characterized in that, Includes the following steps: Step 1. Establish a dynamic model of the distributed generator and provide a dynamic model of the reference generator signal; In step 1, a dynamic model of the distributed generator is established using linearization techniques, as shown below: ； in, Indicates the system status. yes The derivative, Indicates controller input, Represents the system matrix. Let i represent the input matrix, and let i represent the i-th distributed generator in the microgrid system. ; N indicates that there are microgrid systems. A distributed generator, the dynamic model of the reference generator signal is represented as: ； in, Time-invariant and control input Reference signal; This represents the magnitude of the secondary voltage and is a constant. Step 2. Establish the operational model of the state observer based on the dynamic model in Step 1; Step 3. Based on the attack mechanism of denial-of-service attacks, provide piecewise functions representing the events of attack occurrence and non-occurrence. And the attack duration and attack frequency assumptions that a denial-of-service attack must satisfy; Step 4. Based on the distributed microgrid dynamic model and state observer operation model described in Steps 1 and 2, and the attack forms considered in Step 3, give the control objective; Step 5. Based on the control objective described in Step 4, obtain the controller gain and the observer gain; In step 5, the method for obtaining the controller gain and the observer gain is as follows: Step 5.

1. Solve the following Riccati equation: ； The solution is obtained and , and Representation matrix , It is positive definite; Where I represents the identity matrix of the corresponding dimension; Step 5.

2. Select controller gain Observer gain ; Step 6. Based on the piecewise function described in Step 3 and the controller gain and observer gain in Step 5, give the attack compensation mechanism and event triggering mechanism; In step 6, the attack compensation mechanism described is expressed as follows: ； in, Indicates the first The first distributed generator A trigger moment, This indicates that before the system was attacked, the distributed generator... The moment when information was most recently successfully transmitted to the target generator; The design process of the event triggering mechanism is as follows: First, define For the first The measurement error of a distributed generator is expressed as follows: ； in, , They represent the first The first distributed generator There are k+1 event trigger times; additionally, the event trigger times... This is determined by the event triggering mechanism designed below; Secondly, provide the event triggering function of the design. The expression is as follows: ； in, and It is a positive scalar, and ; Distributed generator With distributed generators The communication status between them; when When, it indicates a distributed generator. With distributed generators They can communicate with each other when When, it indicates a distributed generator. With distributed generators They do not communicate with each other; ； ； When j=0, it represents a reference generator; For adaptive parameters, The expression and update law are described as follows: ； in: ； ； in, , , ; definition For internal dynamic variables, The dynamic equation is expressed as: ； in, , , initial value ; Finally, the event triggering time sequence Determined by the following conditions: ≜ ； in, This indicates a function that takes a lower bound. Indicates the first The first distributed generator One trigger moment; Step 7. Based on the controller gain obtained in Step 5 and the attack compensation mechanism designed in Step 6, an event-triggered elastic controller is obtained. By comparing the voltage state information of its own generator, the voltage state information received from neighboring generators, and the reference voltage information, the voltage state information of its own generator is continuously adjusted to reduce the difference between its own generator voltage and the reference voltage, thereby completing the voltage tracking control task. In step 7, the event triggers the controller input of the elastic controller. Represented as: ； in, ; .

2. The voltage elastic tracking control method according to claim 1, characterized in that, In step 2, the operational model of the state observer is expressed as follows: ； in, To observe the system status; yes The derivative, Indicates observation gain.

3. The voltage elastic tracking control method according to claim 2, characterized in that, In step 3, the definition is... For the first One attack range, This refers to the time interval during which an attacker will not launch a malicious attack on the system. in, , , These represent the 2kth, 2k+1th, and 2k+2th time points, respectively. Therefore, the definition The total duration of the attack by the attacker. This represents the total duration during which the attacker does not launch an attack. in, Representing the set of positive integers, the following piecewise functions are given to represent the events of an attack occurring and not occurring: ； Among them, the system is initially immune to attack, that is ; It is a time variable; , These represent the time intervals during which the attack does not occur and the time intervals during which the attack occurs, respectively. The assumptions regarding attack duration and frequency required for a denial-of-service attack are expressed as follows: definition Indicates the attack over the entire time span The total duration of the event has a normal value. and This makes the following inequality true: ; definition Indicates the attack over the entire time span The number of times this occurs is a positive constant. and This makes the following inequality true: .

4. The voltage elastic tracking control method according to claim 3, characterized in that, In step 4, the control objective is expressed as: ; in, This is expressed as voltage tracking error; it is input through the design of the controller. This makes the state of each distributed generator system... Approaching reference signal This causes tracking error The voltage converges to a bound, achieving voltage tracking control.

5. A computer device comprising a memory and one or more processors, wherein the memory stores executable code, characterized in that, When the processor executes the executable code The steps of implementing the voltage elastic tracking control method as described in any one of claims 1 to 4.

6. A computer-readable storage medium having a program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the voltage elastic tracking control method as described in any one of claims 1 to 4.

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