A micro-grid cluster double-layer resilient distributed control method against FDI attack

Abstract

The application provides a kind of micro-grid group double-layer flexible distributed control method against FDI attack, it is related to the security control technical field of micro-grid group.This method includes: according to the double-layer communication topology of micro-grid cluster and droop control principle, establish micro-grid distributed control model;According to the upper limit of the time derivative of the micro-grid distributed control model, false data injection interference signal and false data injection interference signal, determine the fixed time interference estimator, the fixed time interference estimator is used to estimate the interference in fixed time;According to the micro-grid distributed control model and the fixed time interference estimator, determine the double-layer flexible controller, the double-layer flexible controller is used to realize the recovery of frequency and voltage of micro-grid cluster, and simultaneously realize the sharing of active power of micro-grid cluster.Such that the speed of observing FDI interference signal is faster and the system stability of micro-grid cluster is higher.

Description

Technical Field

[0001] This invention relates to the field of security control technology for microgrid clusters, and in particular to a two-layer resilient distributed control method for microgrid clusters that resists False Data Injection (FDI) attacks. Background Technology

[0002] With the widespread application of distributed energy resources, microgrids, as an effective energy utilization method, can integrate various distributed generators and improve energy efficiency. However, individual microgrids have limitations in terms of operating capacity, flexibility, and reliability. Therefore, interconnecting them to form microgrid cluster systems has become a feasible solution. Microgrid cluster control faces greater challenges than individual microgrid systems, especially in multi-regional, multi-layer, and multi-objective coordinated control across different time scales. To improve the system's energy efficiency and power quality, researching fast control strategies that meet the time scale requirements of two-layer networks is of great significance. However, microgrid cluster systems are vulnerable to FDI interference, which can send erroneous signals to the controller, potentially causing frequency and voltage deviations from rated values, active power imbalances, and even regional power outages, resulting in significant economic losses and social harm.

[0003] Currently, secondary control strategies for microgrid clusters mainly include centralized control, single-layer distributed control, and two-layer distributed control. To accelerate frequency and voltage recovery and active power sharing, finite-time and fixed-time algorithms have been applied to the secondary control of individual microgrids. Furthermore, to mitigate the impact of FDI interference, existing research has proposed safety strategies such as resilient controllers based on hidden layers and distributed iterative estimators for estimating and compensating for unknown FDI signals. However, these existing technologies still have some shortcomings. Existing interference estimators do not fully consider key indicators, and their design contains oversights, resulting in slow observation of FDI interference signals. The existing microgrid cluster control strategies are only designed for single-layer communication networks and are difficult to adapt to the commonly used two-layer communication architecture in microgrid clusters. Since microgrid clusters generally adopt a two-layer communication architecture, random interference occurring in either layer can threaten system stability. Existing microgrid cluster control strategies can only achieve asymptotic or exponentially convergent stability, failing to meet the stability requirements of systems using two-layer communication architectures, resulting in low system stability for microgrid clusters. Summary of the Invention

[0004] The purpose of this invention is to provide a two-layer elastic distributed control method for microgrid clusters that resists FDI attacks, addressing the problems of slow FDI attack signal observation speed and low system stability of microgrid clusters.

[0005] To address the aforementioned technical problems, the embodiments of the present invention provide the following technical solutions:

[0006] The first aspect of this invention provides a two-layer resilient distributed control method for microgrid groups resistant to FDI attacks, comprising:

[0007] Based on the two-layer communication topology and droop control principle of microgrid clusters, a distributed control model for microgrids is established.

[0008] Based on the microgrid distributed control model, the spurious data injection interference signal, and the upper bound of the time derivative of the spurious data injection interference signal, a fixed-time interference estimator is determined. The fixed-time interference estimator is used to estimate the interference at a fixed time.

[0009] Based on the microgrid distributed control model and fixed-time disturbance estimator, a two-layer resilient controller is determined. The two-layer resilient controller is used to realize the frequency and voltage recovery of the microgrid cluster, and at the same time realize the sharing of active power of the microgrid cluster.

[0010] A second aspect of the present invention provides a two-layer resilient distributed control device for microgrid groups resistant to FDI attacks, comprising:

[0011] A module is established to build a distributed control model for microgrids based on the two-layer communication topology and droop control principle of microgrid clusters.

[0012] The first determining module is used to determine a fixed-time interference estimator based on the microgrid distributed control model, the spurious data injection interference signal, and the upper bound of the time derivative of the spurious data injection interference signal. The fixed-time interference estimator is used to estimate the interference at a fixed time.

[0013] The second determining module is used to determine a two-layer resilient controller based on the microgrid distributed control model and the fixed-time disturbance estimator. The two-layer resilient controller is used to restore the frequency and voltage of the microgrid cluster and simultaneously realize the sharing of active power of the microgrid cluster.

[0014] Compared to existing technologies, this invention provides a two-layer resilient distributed control method for microgrid clusters to resist FDI attacks. Based on the two-layer communication topology and droop control principle of the microgrid cluster, a distributed control model of the microgrid is established. A fixed-time interference estimator is determined based on the microgrid distributed control model, the spurious data injection interference signal, and the upper bound of the time derivative of the spurious data injection interference signal. This fixed-time interference estimator is used to estimate the interference at a fixed time. Based on the microgrid distributed control model and the fixed-time interference estimator, a two-layer resilient controller is determined. This two-layer resilient controller is used to restore the frequency and voltage of the microgrid cluster and simultaneously achieve active power sharing. Thus, the determined fixed-time interference estimator can quickly observe the spurious data injection interference signal, resulting in faster observation of FDI interference signals. The determined two-layer resilient controller, based on the microgrid distributed control model and the fixed-time interference estimator, achieves multi-objective coordinated control of frequency and voltage restoration and active power sharing, effectively improving the operational reliability of the microgrid cluster under network interference and resulting in higher system stability. Attached Figure Description

[0015] The above and other objects, features, and advantages of exemplary embodiments of the present invention will become readily apparent upon reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of the invention are illustrated by way of example and not limitation, with the same or corresponding reference numerals denoteing the same or corresponding parts, wherein:

[0016] Figure 1 A flowchart illustrating a two-layer resilient distributed control method for microgrid groups resistant to FDI attacks is shown schematically.

[0017] Figure 2 The schematic diagram illustrates the framework of a two-layer resilient distributed control method for microgrid groups resistant to FDI attacks.

[0018] Figure 3 A schematic diagram of a microgrid group test system is shown.

[0019] Figure 4 A schematic diagram of the frequency output without interference compensation is shown.

[0020] Figure 5 A schematic diagram of active power output without interference compensation is shown.

[0021] Figure 6 A schematic diagram of the voltage output without interference compensation is shown.

[0022] Figure 7 A schematic diagram of frequency output under flexible control is shown.

[0023] Figure 8 A schematic diagram of voltage output under flexible control is shown.

[0024] Figure 9 A schematic diagram of power output under flexible control is shown. Detailed Implementation

[0025] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0026] It should be noted that, unless otherwise stated, the technical or scientific terms used in this invention should have the ordinary meaning as understood by one of ordinary skill in the art.

[0027] The methods described in the embodiments of the present invention will be explained in detail below.

[0028] Figure 1 The flowchart of a two-layer resilient distributed control method for microgrid groups against FDI attacks, as illustrated in an embodiment of the present invention, is shown schematically. Figure 2 The schematic diagram illustrates the framework of a two-layer resilient distributed control method for microgrid groups resistant to FDI attacks. (See attached diagram.) Figure 1 and Figure 2 As shown, this two-layer resilient distributed control method for microgrid groups resistant to FDI attacks may include:

[0029] S101. Based on the two-layer communication topology and droop control principle of the microgrid cluster, establish a distributed control model for the microgrid.

[0030] Among them, the microgrid distributed control model is a control model that realizes frequency and voltage recovery and power sharing.

[0031] Specifically, suppose there exists an AC microgrid cluster containing a total of R microgrids, denoted as: .in Indicates the first The microgrid, in the first microgrid Within this framework, all distributed generation units (DGs) can be classified into a main DG and... One from DG. The first microgrid The lower-level communication topology in the graph is represented by the first undirected graph as follows: Define the first undirected graph. A set of DG nodes in a microgrid Represented as , No. The edge set of a microgrid Represented as This corresponds to the communication link between DGs. Furthermore, Used to indicate the first The set of all first neighboring units of a microgrid from a distributed generation unit. For the first One from distributed generation unit, For the first The first neighbor unit. The first undirected graph. Adjacency matrix of a microgrid Represented as , For the first The first microgrid The distributed generation unit and the first The adjacency matrix elements corresponding to the first neighboring units, where if but ,otherwise . No. The Laplace matrix of a microgrid from its distributed generation units is defined as follows: Adjacency matrix of virtual leaders Represented as , For the first The second element of the underlying virtual leader adjacency matrix of the microgrid from the distributed generation unit, if the first... Each distributed generation unit can receive information from the main DG, then ,otherwise , For the first The first microgrid Each element is a virtual leader adjacency matrix element from the bottom layer of a distributed generation unit.

[0032] In the upper-level communication network, each microgrid selects a master direct generation (DG) to be driven, facilitating information exchange between all microgrid clusters. The upper-level communication topology between microgrids with multiple master DGs is defined as a second undirected graph. Define the set of primary DG nodes in the second undirected graph. The set of edges in the second undirected graph is This corresponds to the communication link between the main DGs. Furthermore, Used to indicate the first The set of second neighbor cells of all main DGs in a microgrid. The adjacency matrix in the second undirected graph is represented as: , For the first The main distributed generation unit of the microgrid and the first The adjacency matrix elements corresponding to the second neighbor units, where if but ,otherwise . No. The Laplace matrix of the primary distributed generation unit of a microgrid is defined as follows: The upper-level adjacency matrix is ​​defined as follows: , For the first The upper-level adjacency matrix element of the second primary distributed generation unit within a microgrid, if the... If the primary DG can receive the primary reference information, then ,otherwise In the upper-layer communication network, at least one designated master DG can receive frequency / voltage reference information.

[0033] In the hierarchical control of microgrids, droop control is typically used for primary control, as follows:

[0034] ;

[0035] in, For the first The first microgrid The frequency of a distributed generation unit, For the first The first microgrid The voltage from the distributed generation unit, The rated frequency for droop control. It is the rated voltage for droop control. For the first The first microgrid Active power droop coefficient of each distributed generation unit For the first The first microgrid The reactive power droop factor of each distributed generation unit For the first The first microgrid Active power output of each distributed generation unit For the first The first microgrid The reactive power output of each distributed generation unit. However, droop control causes the frequency to deviate from the rated value after load changes or operating mode switching. Therefore, it is necessary to use secondary control to correct the deviation. The improved droop control expression is:

[0036] ;

[0037] in, For the first The first microgrid The frequency secondary control output is from the distributed generation unit. For the first The first microgrid The voltage secondary control output is from the distributed generation unit. Taking the derivative of the improved droop control expression above, we get:

[0038] ;

[0039] in, For the first The first microgrid One frequency auxiliary control input from the distributed generation unit, For the first The first microgrid One voltage auxiliary control input from the distributed generation unit, For the first The first microgrid An auxiliary control input from the active power of the distributed generation unit. For the first The first microgrid The frequency of each distributed generation unit The corresponding derivative, For the first The first microgrid Voltage of each distributed generation unit The corresponding derivative, For the first The first microgrid Active power droop coefficient of each distributed generation unit , and the The first microgrid The derivative of the active power output of a distributed generation unit The product of , , , For the first The first microgrid Reactive power droop coefficient of each distributed generation unit , No. The first microgrid The derivative of the active power output of a distributed generation unit The product of. For microgrid clusters with a large number of distributed generation (DG), two-layer control only needs to manage a portion of the DG through simple feedback control, which significantly reduces communication costs. Therefore, under FDI interference, the control objective of the lower layer is to achieve frequency, voltage recovery, and active power sharing, where the individual AC's The control objectives are as follows:

[0040] ;

[0041] in, For the first The frequency of the main distributed generation unit within a microgrid For the first The voltage of the main distributed generation unit within a microgrid For the first The first microgrid Active power droop coefficient of each distributed generation unit For the first The first microgrid The active power droop coefficient of the first neighboring unit For the first The first microgrid The active power output from the distributed generation unit For the first The first microgrid The active power output of the first neighboring unit, The convergence time of the system. The estimator error corresponding to the frequency of the distributed generation unit is the system settling time. The estimator error corresponding to the voltage of the distributed generation unit represents the system's settling time. Let be the estimator error corresponding to the active power of the distributed generation unit, and be the system settling time. The upper-level control objective is to design a resilient controller that recovers the frequency and average voltage, while simultaneously regulating the power flow between multiple microgrids to ensure power sharing based on the maximum capacity of each microgrid. The upper-level control objective is as follows:

[0042] ;

[0043] in, This is a global frequency reference value. This is the global voltage reference value. For the first Total active power output of the microgrid , It is the first The maximum associated capacity of a microgrid For the first The associated capacity of a microgrid For the first The first microgrid The total active power output of the second neighboring units. Based on the lower-level active power control objective, the upper-level power control objective will be achieved:

[0044] ;

[0045] in, For the first Active power reduction factor of the main DG of a microgrid For the first Active power output of the main DG of a microgrid For the first The first main distributed generation unit in the microgrid The active power reduction factor of the second neighboring unit. For the first The first main distributed generation unit in the microgrid The active power output of the second neighboring unit.

[0046] S102. Based on the microgrid distributed control model, the spurious data injection interference signal, and the upper bound of the time derivative of the spurious data injection interference signal, determine the fixed-time interference estimator.

[0047] The fixed-time interference estimator is used to estimate the interference at fixed intervals. False data injection interference signals include frequency-based, voltage-based, and active power-based false data injection interference signals.

[0048] Specifically, based on the microgrid distributed control model, the spurious data injection interference signal, and the upper bound of the time derivative of the spurious data injection interference signal, a fixed-time interference estimator is determined, including:

[0049] Step A1: Based on the state vectors of the distributed generation units, controller inputs, and interference signals injected by spurious data in the microgrid distributed control model, construct the extended state equations.

[0050] Specifically, step A1 includes:

[0051] Step A11: Inject spurious frequency data, spurious voltage data, and spurious active power data into the interference signal to determine the interference vector in the extended state equation.

[0052] Step A12: Determine the derivative of the interference vector based on the derivatives of the spurious frequency data, the spurious voltage data, and the spurious power data injected into the interference signal.

[0053] Step A13: Based on the disturbance vector and controller input, determine the derivative of the state vector from the distributed generation unit to construct the extended state equation.

[0054] Specifically, FDI is considered a typical form of network interference, where attackers can inject false data into the controller of a microgrid cluster. This leads to frequency and voltage deviations from rated values, as well as imbalances in active power distribution. Under FDI interference, the dynamic changes in DG can be expressed as:

[0055] ;

[0056] in, For the first The first microgrid The frequency of each distributed generation unit The corresponding derivative, For the first The first microgrid Voltage of each distributed generation unit The corresponding derivative, For the first The first microgrid Active power droop coefficient of each distributed generation unit , and the The first microgrid The derivative of the active power output of a distributed generation unit The product of.

[0057] Assumption 1: The time derivative of the interference signal is bounded, and the... The first microgrid The spurious data injection interference signal of a distributed generation unit meets the following conditions:

[0058] ;

[0059] in, For the first The first microgrid False data injection interference signals from a distributed generation unit For the first The first microgrid The derivative of the spurious data injection interference signal of a distributed generation unit. For norm, The upper bound of the time derivative for injecting interference signals into spurious data. Take a constant and , For the first One portion, The corresponding number is The first microgrid The frequency components corresponding to each distributed generation unit, i.e. hour, Pick , The corresponding number is The first microgrid The voltage components corresponding to each distributed generation unit, i.e. hour, Pick , The corresponding number is The first microgrid The active power component corresponding to each distributed generation unit, i.e. hour, Pick .

[0060] To mitigate the impact of FDI interference on microgrid systems, a fixed-time interference estimator is implemented to estimate the FDI interference signal. Based on the dynamic changes of the distributed generation (DG), the extended state equation is expressed as follows:

[0061] ;

[0062] in, For the first The first microgrid A state vector from a distributed generation unit. For the first The first microgrid The derivative of the state vector of a distributed generation unit. , For the first The first microgrid The frequency of a distributed generation unit, For the first The first microgrid The voltage from the distributed generation unit, For the first The first microgrid The active power droop factor from the distributed generation unit For the first The first microgrid The active power output from the distributed generation unit For the first The first microgrid One input from the controller of the distributed generation unit, , For the first The first microgrid One frequency auxiliary control input from the distributed generation unit, For the first The first microgrid One voltage auxiliary control input from the distributed generation unit, For the first The first microgrid An auxiliary control input from the active power of the distributed generation unit. For the first The first microgrid An interference vector from a distributed generation unit, , For the first The first microgrid A spurious data source from the frequency of the distributed generation unit injects interference signals. For the first The first microgrid A spurious voltage data from a distributed generation unit is injected to create interference signals. For the first The first microgrid An interference signal is injected by injecting false data on the active power of distributed generation units. For the first The first microgrid The derivative of the disturbance vector from the distributed generation unit. For the first The first microgrid A spoofing signal was injected from the distributed generation unit. For the first The first microgrid The derivative corresponding to the spurious data injection interference signal from the distributed generation unit. For the first One portion, The corresponding number is The first microgrid A component of the frequency corresponding to the distributed generation unit. The corresponding number is The first microgrid The voltage component corresponding to the distributed generation unit, The corresponding number is The first microgrid The active power component corresponding to the distributed generation unit.

[0063] Step A2: Construct a fixed-time interference estimator based on the extended state equation and the upper bound of the time derivative of the spurious data-injected interference signal.

[0064] To quickly estimate the interference signal, a fixed-time interference estimator needs to be constructed. The expression for the fixed-time interference estimator is as follows:

[0065] ;

[0066] in, For the first The first microgrid A state vector from a distributed generation unit. For the first The first microgrid A state vector from the distributed generation unit The estimated state, For the first The first microgrid The estimated state from the state vector of the distributed generation unit The derivative, For the first The first microgrid One input from the controller of the distributed generation unit, For the first The first microgrid An interference vector from a distributed generation unit, For the first The first microgrid An interference vector from a distributed generation unit The estimated state, For the first The first microgrid The estimated state of the disturbance vector from the distributed generation unit. The derivative, The first gain of the observer, , For the first The first microgrid The estimated state from the state vector of the distributed generation unit , and the The first microgrid A state vector from the distributed generation unit The estimation error, , As the first coefficient, As the second coefficient, The third coefficient, The second gain of the observer, , .

[0067] definition , , For the first The first microgrid The estimated state of the disturbance vector from the distributed generation unit. , and the The first microgrid An interference vector from a distributed generation unit The estimation error, for The symbolic power function with simplified notation. for The absolute value of . To prove the effectiveness of the fixed-time interference estimator and simplify the notation, we first consider the frequency interference estimator, i.e. season , Two-dimensional vector The estimation error state variable, by combining the expression of the extended state equation and the expression of the fixed-time disturbance estimator, can be expressed as follows:

[0068] ;

[0069] in, The derivative of the first estimated error state variable, The first estimated error state variable, It is the fourth coefficient. Let be the sign power function of the first estimated error state variable. For the second estimation error state variable, The derivative of the second estimated error state variable, For the disturbance term, .

[0070] Theorem 1: Considering a frequency recovery system for a microgrid, for appropriate parameters... , , , , If so, the estimation error system is stable over a fixed time.

[0071] Similar to the estimation error system, the frequency, voltage, and active power controllers of other DGs (including slave DGs and master DGs) in a microgrid cluster also have estimator error systems, and the corresponding stability timelines can be expressed as: , , , The estimator error corresponding to the frequency of the distributed generation unit is the system settling time. The estimator error corresponding to the voltage of the distributed generation unit represents the system's settling time. The estimator error corresponding to the active power of the distributed generation unit represents the system's settling time. For the first Within the first microgrid An upper limit to the settling time required by the frequency error estimation system from the DG. For the first The upper limit of the settling time required for the frequency error estimation system of the main DG in a microgrid. For the first Within the first microgrid The upper limit of the settling time required by the voltage error estimation system from the DG. For the first The upper limit of the settling time required for the voltage error estimation system of the main distributed generation (DG) in a microgrid. For the first Within the first microgrid An upper limit to the settling time required by the active power error estimation system from DG. For the first The upper limit of the settling time required for the active power error estimation system of the main DG in a microgrid.

[0072] S103. Based on the microgrid distributed control model and the fixed-time disturbance estimator, determine the two-layer resilient controller.

[0073] The two-layer resilient controller is used to restore the frequency and voltage of the microgrid cluster and simultaneously enable the sharing of active power within the microgrid cluster. The two-layer resilient controller consists of an upper-layer resilient controller and a lower-layer resilient controller.

[0074] Specifically, based on the microgrid distributed control model and the fixed-time disturbance estimator, a two-layer resilient controller is determined, including:

[0075] Step B1: Based on the state vector of the distributed generation unit, the first target state vector in the microgrid distributed control model, and the interference signal injected by the spurious data from the distributed generation unit in the fixed-time interference estimator, determine the first cooperative elastic control signal to construct the underlying elastic controller.

[0076] The first target state vector is the state vector of the first neighboring unit of the distributed generation unit.

[0077] Since microgrid clusters contain a large number of distributed generation (DG) systems, a two-layer control scheme avoids the need for large-scale communication networks, thus effectively saving communication resources. Furthermore, to mitigate the impact of interference and enhance the security of the microgrid cluster system, a two-layer distributed resilient control scheme, namely the dual-layer resilient controller scheme, is proposed.

[0078] In the In a microgrid, all slave stations (DGs) communicate with their neighbors through the underlying communication network. Under FDI interference, the expression for the underlying resilient controller is:

[0079] ;

[0080] in, For the first The first microgrid The underlying frequency coordination error of distributed generation units For the first The first microgrid The distributed generation unit and the first The adjacency matrix elements corresponding to the first neighbor unit For the first The first microgrid The frequency of a distributed generation unit, For the first The first microgrid The frequency of the first neighboring unit, For the first The first microgrid An element of the underlying virtual leader adjacency matrix of the distributed generation unit. For the first The frequency of the main distributed generation unit within a microgrid For the first The first microgrid The underlying active power coordination error of distributed generation units The number of distributed generation units contained in each microgrid. For the first The first microgrid The active power output from the distributed generation unit For the first The first microgrid The active power output of the first neighboring unit, For the first Active power output of the main distributed generation unit within a microgrid For the first The first microgrid The underlying voltage coordination error of the distributed generation unit For the first The first microgrid The voltage of the first neighboring unit, For the first The first microgrid The voltage from the distributed generation unit, For the first The voltage of the main distributed generation unit within a microgrid For the first The first microgrid One frequency auxiliary control input from the distributed generation unit, The first gain of the underlying elastic controller. The ratio of the first positive odd number. , The ratio of the second positive odd number. , For the first The first microgrid The underlying frequency coordination error is determined by the ratio of the first positive odd number corresponding to the distributed generation unit. The second gain of the underlying elastic controller. For the first The first microgrid The underlying frequency coordination error corresponding to the second positive odd number of the distributed generation unit. The third gain for the underlying elastic controller. , For the first The first microgrid A spurious interference signal is injected using frequency data estimated from distributed generation units. For the first The first microgrid An auxiliary control input from the active power of the distributed generation unit. For the first The first microgrid The underlying active power coordination error corresponding to the first positive odd number of the distributed generation unit. For the first The first microgrid The second positive odd number of underlying active power coordination error corresponding to the distributed generation unit. For the first The first microgrid A spurious data point is injected with interference signals based on the estimated active power from the distributed generation unit. For the first The first microgrid One voltage auxiliary control input from the distributed generation unit, For the first The first microgrid The first positive odd-numbered underlying voltage coordination error corresponding to the distributed generation unit. For the first The first microgrid The second positive odd number of underlying voltage coordination error corresponding to the distributed generation unit. For the first The first microgrid A spurious voltage estimate from a distributed generation unit is used to inject interference signals.

[0081] Step B2: Based on the state vector of the main distributed generation unit and the second target state vector in the microgrid distributed control model, and the spurious data injection interference signal of the main distributed generation unit in the fixed-time interference estimator, determine the second cooperative elastic control signal to construct the upper-level elastic controller.

[0082] Among them, the second target state vector is the state vector of the second neighboring unit of the main distributed generation unit.

[0083] All primary DGs communicate with their neighbors through the upper-layer communication network. The expression for the upper-layer resilient controller is:

[0084] ;

[0085] in, For the first The upper-level frequency coordination error of the main distributed generation unit of a microgrid. For the first The main distributed generation unit of the microgrid and the first The adjacency matrix elements corresponding to the second neighbor units For the first The frequency of the main distributed generation unit within a microgrid For the first The first main distributed generation unit in the microgrid The frequency of the second neighboring unit, For the first Upper-level adjacency matrix elements of the main distributed generation unit within a microgrid This is a global frequency reference value. For the first The upper-level active power coordination error of the main distributed generation unit within a microgrid For the first Active power output of the main distributed generation unit within a microgrid For the first The first main distributed generation unit in the microgrid The active power output of the second neighboring unit, For the first Voltage coordination error at the upper level of the main distributed generation unit within a microgrid. For the first The voltage of the main distributed generation unit within a microgrid For the first The first main distributed generation unit in the microgrid The voltage of the second neighboring unit, This is the global voltage reference value. For the first Frequency auxiliary control input for the main distributed generation unit of a microgrid The first gain of the upper-level elastic controller. This is the second gain of the upper-level elastic controller. The third gain of the upper-level elastic controller, , The ratio of the first positive odd number. , The ratio of the second positive odd number. , For the first The upper-level frequency coordination error corresponding to the first positive odd number of the main distributed generation unit within a microgrid. For the first The upper-level frequency coordination error corresponding to the second positive odd number of the main distributed generation unit within a microgrid. For the first Spurious frequency data estimated by the main distributed generation unit within a microgrid is injected as interference signals. For the first Auxiliary control inputs for active power of the main distributed generation unit within a microgrid. For the first The first positive odd number of upper-level active power coordination error corresponding to the main distributed generation unit within a microgrid. For the first The second positive odd number of upper-level active power coordination error corresponding to the main distributed generation unit within a microgrid. For the first The upper-level active power coordination error of the main distributed generation unit within a microgrid For the first The estimated active power data of the main distributed generation unit in the microgrid is used to inject interference signals. For the first Voltage auxiliary control input of the main distributed generation unit within a microgrid For the first The upper-level frequency coordination error corresponding to the first positive odd number of the main distributed generation unit within a microgrid. For the first The upper-level frequency coordination error corresponding to the second positive odd number of the main distributed generation unit within a microgrid. For the first Voltage coordination error at the upper level of the main distributed generation unit within a microgrid. For the first The estimated voltage data of the main distributed generation unit within the microgrid is used to inject interference signals. The number of primary distributed generation units contained in each microgrid.

[0086] Double-layer elastic secondary control frame, such as Figure 2 As shown, for ease of mathematical analysis, it is assumed that each microgrid contains the same number of slave DGs, i.e.: Within the microgrid One DG is the main DG, that is However, the general case can be analyzed in a similar way. Definition: , For the first The frequency of a microgrid For the first The first frequency of the microgrid from the distributed generation unit, , For the first The voltage of a microgrid For the first The voltage of the first unit in the microgrid is from the distributed generation unit. , , For the first Active power output of a microgrid For the first The first active power output from the distributed generation unit of the microgrid. , For the frequency of distributed generation units, This is the first transposition of the frequency from the distributed generation unit. , For the voltage from the distributed generation unit, This is the first voltage transposition from the distributed generation unit. , To obtain the active power from the distributed generation unit, This is the first transfer of active power from distributed generation units. , For the communication matrix of the first microgrid, The diagonal matrix formed by the communication matrix of the microgrid. , For the traction matrix of the first microgrid, The diagonal matrix formed by the traction matrix of the microgrid. , The active power output of the main distributed generation unit. This refers to the active power output of the primary distributed generation unit within the first microgrid. , The frequency of the main distributed generation unit, Let be the frequency of the primary distributed generation unit within the first microgrid. The error variables for frequency, voltage, and active power are defined as follows: , , , for and Error variables, for and Error variables, for and Error variables, This is the rated voltage value. for A dimensional vector of all 1s for A dimensional vector of all 1s For Kronecker product, , for and Error variables, , for and Error variables, This is the rated frequency value. , for and Error variables, For the first Active power output of the main distributed generation unit within a microgrid.

[0087] Theorem 2: Assume two strongly connected communication networks (i.e., the lower-level communication network and the upper-level communication network). Under FDI interference, the two-layer distributed resilient control scheme can ensure that the recovery errors of frequency, voltage, and power corresponding to the master DG and slave DG are consistent within a fixed time, eventually achieving bounded convergence. Assume the existence of parameters... This requires the gain of the two-layer elastic controller to satisfy the following constraint: , For the first One stability condition. , The first stability condition is, , This is the second stability condition. , This is the third stability condition. , This is the fourth stability condition. , This is the fifth stability condition. , This is the 6th stability condition.

[0088] This invention addresses the issue of spurious data injection (FDI) interference by employing a two-layer distributed fixed-time elastic secondary control strategy to achieve stable operation of an AC microgrid cluster. First, a fixed-time interference estimator is designed using the double-limit homogeneity technique to quickly estimate unknown FDI interference signals. Then, based on the interference signals estimated by the time-based interference estimator, a two-layer elastic controller, i.e., a distributed fixed-time elastic control scheme, is presented to achieve frequency and voltage recovery, as well as active power sharing. Furthermore, considering the variations in energy flow within and between microgrids at different time scales, the gain conditions for eliminating dependence on communication topology in the two-layer controller are derived by analyzing the stability of the entire AC microgrid cluster, thus coordinating the power flow within the microgrid cluster. Finally, the effectiveness and superiority of this FDI-resistant two-layer elastic distributed control for microgrid clusters are verified using a hardware-in-the-loop simulation platform in an AC microgrid cluster system.

[0089] To address the problem of spurious data injection in distributed secondary control of microgrid clusters, this invention proposes a novel two-layer distributed elastic secondary control scheme. Based on a fixed-time disturbance estimator designed using double-limit homogeneity technology, it can rapidly observe spurious data injection interference signals, providing real-time and reliable information support for system security. The distributed fixed-time elastic control scheme utilizes the estimated interference signal to achieve multi-objective coordinated control of frequency voltage recovery and active power equalization, effectively improving the operational reliability of microgrid clusters under network interference. By analyzing the overall stability of AC microgrid clusters, the gain conditions of the two-layer controller, independent of the communication topology, are derived, solving the control challenges caused by multi-timescale energy flow changes within and between microgrid clusters. A hardware-in-the-loop experimental platform based on OPAL-RT verifies the effectiveness and superiority of the proposed control method in AC microgrid cluster systems, providing reliable technical support for practical engineering applications. In summary, this invention significantly enhances the anti-interference capability and operational stability of microgrid clusters under network security threats, possessing significant engineering application value and remarkable beneficial effects.

[0090] The effects of this invention can be further illustrated by the following simulation experiments.

[0091] Simulation conditions: This invention was simulated and verified using MATLAB 2020b, RT-LAB, hardware controller, and switch on an Intel(R) Core(TM) i7-4790 3.60GHz CPU, NVIDIA Titan X GPU, and Ubuntu 16.04 operating system.

[0092] Simulation content: Utilizing a hardware-in-the-loop semi-physical simulation platform based on microgrid clusters, where... The upper-level secondary resilient controller of the distributed power supply (DG) is implemented using Python scripts and deployed on the development board. Communication between nodes on the development board and with the RTLAB platform is achieved via TCP / IP protocol. The power circuit and droop control model of the power grid cluster are deployed on the OPAL-RT real-time simulator to perform high-precision dynamic circuit simulation.

[0093] Figure 3 A schematic diagram of a microgrid group test system is shown. Figure 3 The microgrid group test system diagram in the image is a publicly available microgrid group test system. (See also...) Figure 3 As shown, the physical components and two-layer communication topology of the microgrid cluster are presented. Detailed electrical parameters of the microgrid cluster in the microgrid cluster test system are specified in Table 1. Table 1 lists the parameters of the microgrid cluster system, including specific generator units, droop coefficients, circuit resistances, loads, estimator parameters, and the two-layer resilient controller. This is the first distributed generation unit of the first microgrid. This represents the circuit resistance value of the first distributed generation unit in the first microgrid. This is the load of the first distributed generation unit in the first microgrid. The reference signals for frequency and voltage are 50Hz and 380V, respectively. To verify the effectiveness of the two-layer resilient controller, two experimental scenarios were conducted: Experiment 1 was a comparison with existing two-layer secondary control, and Experiment 2 was a resilient test against different FDI disturbances.

[0094] Table 1 Parameters of the microgrid group system

[0095]

[0096] Experiment 1: Comparison with existing two-level secondary control strategies.

[0097] To demonstrate the effectiveness and superiority of the two-layer fixed-time control strategy corresponding to the two-layer flexible controller, a comparative study was conducted with existing frequency, voltage, and active power controllers. The two-layer control parameters for the microgrid cluster are shown in Table 1 above. The process of the two-layer fixed-time control strategy of this invention is as follows:

[0098] Phase 1: During the time interval, the load and The connection only has droop control implemented.

[0099] Phase 2: During the time interval, droop control and the proposed fixed-time elastic secondary control are implemented.

[0100] Phase 3: During the time interval, droop control and the proposed fixed-time flexible secondary control are implemented. In the connected microgrid group.

[0101] Phase 4: During the time interval, droop control and the proposed fixed-time flexible secondary control are implemented. Disconnect from the microgrid group.

[0102] Using the fixed-time control strategy proposed in this invention, in the initial stage, due to droop control, the frequency and voltage of each DG deviate from the nominal values. After secondary control is implemented, the microgrid cluster control objective will be achieved. The two-layer fixed-time control strategy of this invention achieves the microgrid cluster control objective more quickly. Furthermore, when the load changes, the two-layer fixed-time control strategy of this invention can achieve frequency and voltage recovery and active power sharing in a shorter time.

[0103] Experiment 2: The resilience of microgrid groups after being subjected to FDI interference.

[0104] To verify the effectiveness of the two-layer fixed-time control strategy of this invention under varying FDI interference, a set of comparative experiments needs to be conducted. Table 2 shows the FDI interference signals. As shown in Table 2, the frequency, voltage, and power controllers were all injected with different types of FDI interference, including bounded and unbounded FDI interference. To inject interference signals into the spurious frequency data, To inject interference signals into the false active power data, To inject interference signals into the false voltage data.

[0105] Simulation results on different controllers, such as Figure 4-9 As shown, Figure 4 A schematic diagram of the frequency output without interference compensation is shown. Figure 4 The horizontal axis represents time and the vertical axis represents frequency. The frequency output under interference-free compensation is given for the two-layer fixed-time control strategy corresponding to the distributed generation unit of 10 different microgrids. Figure 5 A schematic diagram illustrating the active power output without interference compensation is shown. Figure 5 The horizontal axis represents time, and the vertical axis represents power. The active power output under non-interference compensation for the two-layer fixed-time control strategy corresponding to the distributed generation unit of 10 different microgrids is given. Figure 6 A schematic diagram of the voltage output without interference compensation is shown. Figure 6 The horizontal axis represents time and the vertical axis represents voltage. The voltage output under interference-free compensation is given for the two-layer fixed-time control strategy corresponding to the distributed generation unit of 10 different microgrids. Figure 7 A schematic diagram of frequency output under flexible control is shown. Figure 7 The horizontal axis represents time, and the vertical axis represents frequency. The frequency output under elastic control of two-layer fixed-time control strategies corresponding to 10 different distributed generation units of microgrids is given. Figure 8 A schematic diagram of voltage output under flexible control is shown. Figure 8 The horizontal axis represents time, and the vertical axis represents voltage. The voltage output under elastic control of two-layer fixed-time control strategies corresponding to 10 different distributed generation units of microgrids is given. Figure 9 A schematic diagram illustrating power output under flexible control is shown. Figure 9 The x-axis represents time, and the y-axis represents power. The power output under elastic control using a two-layer fixed-time control strategy is presented for 10 different distributed generation units in a microgrid. From... Figure 4-9 It can be seen that when a microgrid cluster is disturbed, system stability cannot be maintained without interference compensation. However, the fixed-time elastic control strategy of this invention can maintain system stability even under multiple FDI interferences. In summary, the proposed two-layer elastic distributed control method for microgrid clusters with FDI interference resistance can effectively resist FDI interference and maintain system stability.

[0106] Table 2 FDI Interference Signals

[0107]

[0108] Based on the above Figure 1As can be seen from the implementation method, this embodiment of the invention establishes a distributed control model for the microgrid based on the two-layer communication topology and droop control principle of the microgrid cluster. Based on the microgrid distributed control model, the spurious data injection interference signal, and the upper bound of the time derivative of the spurious data injection interference signal, a fixed-time interference estimator is determined. This fixed-time interference estimator is used to estimate the interference at a fixed time. Based on the microgrid distributed control model and the fixed-time interference estimator, a two-layer elastic controller is determined. This two-layer elastic controller is used to restore the frequency and voltage of the microgrid cluster and simultaneously achieve the sharing of active power. Thus, the determined fixed-time interference estimator can quickly observe the spurious data injection interference signal, making the observation speed of the FDI interference signal faster. Based on the microgrid distributed control model and the fixed-time interference estimator, the determined two-layer elastic controller achieves multi-objective coordinated control of frequency and voltage restoration and active power sharing, effectively improving the operational reliability of the microgrid cluster when subjected to network interference, resulting in higher system stability of the microgrid cluster.

[0109] Based on the same inventive concept, as an implementation of the aforementioned two-layer resilient distributed control method for microgrid groups resistant to FDI attacks, this embodiment of the invention also provides a two-layer resilient distributed control device for microgrid groups resistant to FDI attacks. This two-layer resilient distributed control device for microgrid groups resistant to FDI attacks may include:

[0110] A module is established to build a distributed control model for microgrids based on the two-layer communication topology and droop control principle of microgrid clusters.

[0111] The first determining module is used to determine a fixed-time interference estimator based on the microgrid distributed control model, the spurious data injection interference signal, and the upper bound of the time derivative of the spurious data injection interference signal. The fixed-time interference estimator is used to estimate the interference at a fixed time.

[0112] The second determining module is used to determine a two-layer resilient controller based on the microgrid distributed control model and the fixed-time disturbance estimator. The two-layer resilient controller is used to restore the frequency and voltage of the microgrid cluster and simultaneously realize the sharing of active power of the microgrid cluster.

[0113] It should be noted that the above description of the embodiment of the two-layer resilient distributed control device for microgrids against FDI attacks is similar to the description of the embodiment of the two-layer resilient distributed control method for microgrids against FDI attacks, and has similar beneficial effects. For any technical details not disclosed in the embodiments of the two-layer resilient distributed control device for microgrids against FDI attacks of the present invention, please refer to the description of the embodiment of the two-layer resilient distributed control method for microgrids against FDI attacks of the present invention for understanding.

[0114] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A two-layer resilient distributed control method for microgrid groups resistant to FDI attacks, characterized in that, include: Based on the two-layer communication topology and droop control principle of microgrid clusters, a distributed control model for microgrids is established. Based on the microgrid distributed control model, the spurious data injection interference signal, and the upper bound of the time derivative of the spurious data injection interference signal, a fixed-time interference estimator is determined, which is used to estimate the interference at a fixed time. Based on the microgrid distributed control model and the fixed-time disturbance estimator, a two-layer resilient controller is determined. The two-layer resilient controller is used to realize the restoration of frequency and voltage of the microgrid cluster, and at the same time realize the sharing of active power of the microgrid cluster. The step of determining a fixed-time interference estimator based on the microgrid distributed control model, the spurious data injection interference signal, and the upper bound of the time derivative of the spurious data injection interference signal includes: Based on the state vectors of the distributed generation units, the controller inputs, and the interference signals injected by the spurious data in the microgrid distributed control model, an extended state equation is constructed. Based on the extended state equation and the upper bound of the time derivative of the spurious data injection interference signal, the fixed-time interference estimator is constructed. The spoofing data injection interference signals include frequency spoofing data injection interference signals, voltage spoofing data injection interference signals, and active power spoofing data injection interference signals. The step of constructing extended state equations based on the state vectors of distributed generation units, controller inputs, and the spurious data injection interference signals in the microgrid distributed control model includes: The spurious data of the frequency, the spurious data of the voltage, and the spurious data of the active power are injected into the interference signal and determined as the interference vector in the extended state equation. The derivative of the interference vector is determined based on the derivatives corresponding to the spurious data injection interference signal of the frequency, the spurious data injection interference signal of the voltage, and the spurious data injection interference signal of the active power. Based on the disturbance vector and the controller input, the derivative of the state vector from the distributed generation unit is determined to construct the extended state equation.

2. The two-layer resilient distributed control method for microgrid groups resistant to FDI attacks according to claim 1, characterized in that, The expression for the extended state equation is: ； in, For the first The first microgrid A state vector from a distributed generation unit. For the first The first microgrid The derivative of the state vector of a distributed generation unit. , For the first The first microgrid The frequency of a distributed generation unit, For the first The first microgrid The voltage from the distributed generation unit, For the first The first microgrid The active power droop factor from the distributed generation unit For the first The first microgrid The active power output from the distributed generation unit For the first The first microgrid One input from the controller of the distributed generation unit, , For the first The first microgrid One frequency auxiliary control input from the distributed generation unit, For the first The first microgrid One voltage auxiliary control input from the distributed generation unit, For the first The first microgrid An auxiliary control input from the active power of the distributed generation unit. For the first The first microgrid An interference vector from a distributed generation unit, , For the first The first microgrid A spurious data source from the frequency of the distributed generation unit injects interference signals. For the first The first microgrid A spurious voltage data from a distributed generation unit is injected to create interference signals. For the first The first microgrid An interference signal is injected by injecting false data on the active power of distributed generation units. For the first The first microgrid The derivative of the disturbance vector from the distributed generation unit. For the first The first microgrid A spoofing signal was injected from the distributed generation unit. For the first The first microgrid The derivative corresponding to the spurious data injection interference signal from the distributed generation unit. For the first One portion, Corresponding to the first The first microgrid A component of the frequency corresponding to the distributed generation unit. Corresponding to the first The first microgrid The voltage component corresponding to the distributed generation unit, The corresponding one is the first The first microgrid The active power component corresponding to the distributed generation unit.

3. The two-layer resilient distributed control method for microgrid groups resistant to FDI attacks according to claim 1, characterized in that, The expression for the fixed-time interference estimator is: ； in, For the first The first microgrid A state vector from a distributed generation unit. For the first The first microgrid A state vector from the distributed generation unit The estimated state, For the first The first microgrid The estimated state from the state vector of the distributed generation unit The derivative, For the first The first microgrid One input from the controller of the distributed generation unit, For the first The first microgrid An interference vector from a distributed generation unit, For the first The first microgrid An interference vector from a distributed generation unit The estimated state, For the first The first microgrid The estimated state of the disturbance vector from the distributed generation unit. The derivative, The first gain of the observer, , For the first The first microgrid The estimated state from the state vector of the distributed generation unit , and the first The first microgrid A state vector from the distributed generation unit The estimation error, , As the first coefficient, As the second coefficient, The third coefficient, The second gain of the observer, , .

4. The two-layer resilient distributed control method for microgrid groups resistant to FDI attacks according to claim 1, characterized in that, The two-layer resilient controller includes an upper-layer resilient controller and a lower-layer resilient controller. The determination of the two-layer resilient controller based on the microgrid distributed control model and the fixed-time disturbance estimator includes: Based on the state vector of the distributed generation unit in the microgrid distributed control model, the first target state vector, and the spurious data injection interference signal of the distributed generation unit in the fixed-time interference estimator, a first cooperative elastic control signal is determined to construct the underlying elastic controller. The first target state vector is the state vector of the first neighboring unit of the state vector of the distributed generation unit. Based on the state vector of the primary distributed generation unit and the second target state vector in the microgrid distributed control model, and the spurious data injection interference signal of the primary distributed generation unit in the fixed-time interference estimator, a second cooperative elastic control signal is determined to construct the upper-level elastic controller. The second target state vector is the state vector of the second neighbor unit of the primary distributed generation unit's state vector.

5. The two-layer resilient distributed control method for microgrid groups resistant to FDI attacks according to claim 4, characterized in that, The expression for the underlying elastic controller is: ； in, For the first The first microgrid The underlying frequency coordination error of distributed generation units For the first The first microgrid The distributed generation unit and the first The adjacency matrix elements corresponding to the first neighbor unit For the first The first microgrid The frequency of a distributed generation unit, For the first The first microgrid The frequency of the first neighboring unit, For the first The first microgrid An element of the underlying virtual leader adjacency matrix of the distributed generation unit. For the first The frequency of the main distributed generation unit within a microgrid For the first The first microgrid The underlying active power coordination error of distributed generation units The number of distributed generation units contained in each microgrid. For the first The first microgrid The active power output from the distributed generation unit For the first The first microgrid The active power output of the first neighboring unit, For the first Active power output of the main distributed generation unit within a microgrid For the first The first microgrid The underlying voltage coordination error of the distributed generation unit For the first The first microgrid The voltage of the first neighboring unit, For the first The first microgrid The voltage from the distributed generation unit, For the first The voltage of the main distributed generation unit within a microgrid For the first The first microgrid One frequency auxiliary control input from the distributed generation unit, This is the first gain of the underlying elastic controller. The ratio of the first positive odd number. , The ratio of the second positive odd number. , For the first The first microgrid The underlying frequency coordination error is determined by the ratio of the first positive odd number corresponding to the distributed generation unit. This is the second gain of the underlying elastic controller. For the first The first microgrid The underlying frequency coordination error corresponding to the second positive odd number of the distributed generation unit. This is the third gain of the underlying elastic controller. , For the first The first microgrid A spurious interference signal is injected using frequency data estimated from distributed generation units. For the first The first microgrid An auxiliary control input from the active power of the distributed generation unit. For the first The first microgrid The underlying active power coordination error corresponding to the first positive odd number of the distributed generation unit. For the first The first microgrid The second positive odd number of underlying active power coordination error corresponding to the distributed generation unit. For the first The first microgrid A spurious data point is injected with interference signals based on the estimated active power from the distributed generation unit. For the first The first microgrid One voltage auxiliary control input from the distributed generation unit, For the first The first microgrid The first positive odd-numbered underlying voltage coordination error corresponding to the distributed generation unit. For the first The first microgrid The second positive odd number of underlying voltage coordination error corresponding to the distributed generation unit. For the first The first microgrid A spurious voltage estimate from a distributed generation unit is used to inject interference signals.

6. The two-layer resilient distributed control method for microgrid groups resistant to FDI attacks according to claim 4, characterized in that, The expression for the upper-level elastic controller is: ； in, For the first The upper-level frequency coordination error of the main distributed generation unit of a microgrid. For the first The main distributed generation unit of the microgrid and the first The adjacency matrix elements corresponding to the second neighbor units For the first The frequency of the main distributed generation unit within a microgrid For the first The first main distributed generation unit in the microgrid The frequency of the second neighboring unit, For the first Upper-level adjacency matrix elements of the main distributed generation unit within a microgrid This is a global frequency reference value. For the first The upper-level active power coordination error of the main distributed generation unit within a microgrid For the first Active power output of the main distributed generation unit within a microgrid For the first The first main distributed generation unit in the microgrid The active power output of the second neighboring unit, For the first Voltage coordination error at the upper level of the main distributed generation unit within a microgrid. For the first The voltage of the main distributed generation unit within a microgrid For the first The first main distributed generation unit in the microgrid The voltage of the second neighboring unit, This is the global voltage reference value. For the first Frequency auxiliary control input for the main distributed generation unit of a microgrid This is the first gain of the upper-layer elastic controller. This is the second gain of the upper-layer elastic controller. This is the third gain of the upper-layer elastic controller. , The ratio of the first positive odd number. , The ratio of the second positive odd number. , For the first The upper-level frequency coordination error corresponding to the first positive odd number of the main distributed generation unit within a microgrid. For the first The upper-level frequency coordination error corresponding to the second positive odd number of the main distributed generation unit within a microgrid. For the first The estimated frequency of the main distributed generation unit within the microgrid is used to inject spurious interference signals. For the first Auxiliary control inputs for active power of the main distributed generation unit within a microgrid. For the first The first positive odd number of upper-level active power coordination error corresponding to the main distributed generation unit within a microgrid. For the first The second positive odd number of upper-level active power coordination error corresponding to the main distributed generation unit within a microgrid. For the first The upper-level active power coordination error of the main distributed generation unit within a microgrid For the first The estimated active power data of the main distributed generation unit in the microgrid is used to inject interference signals. For the first Voltage auxiliary control input of the main distributed generation unit within a microgrid For the first The upper-level frequency coordination error corresponding to the first positive odd number of the main distributed generation unit within a microgrid. For the first The upper-level frequency coordination error corresponding to the second positive odd number of the main distributed generation unit within a microgrid. For the first Voltage coordination error at the upper level of the main distributed generation unit within a microgrid. For the first The estimated voltage data of the main distributed generation unit within the microgrid is used to inject interference signals. The number of primary distributed generation units contained in each microgrid.

7. A two-layer resilient distributed control device for microgrid groups resistant to FDI attacks, used to implement the two-layer resilient distributed control method for microgrid groups resistant to FDI attacks as described in any one of claims 1-6, characterized in that, include: A module is established to build a distributed control model for microgrids based on the two-layer communication topology and droop control principle of microgrid clusters. The first determining module is used to determine a fixed-time interference estimator based on the microgrid distributed control model, the spurious data injection interference signal, and the upper bound of the time derivative of the spurious data injection interference signal. The fixed-time interference estimator is used to estimate the interference at a fixed time. The second determining module is used to determine a two-layer resilient controller based on the microgrid distributed control model and the fixed-time disturbance estimator. The two-layer resilient controller is used to restore the frequency and voltage of the microgrid cluster and simultaneously realize the sharing of active power of the microgrid cluster.

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