A micro-grid control method against false data injection attack

Abstract

The application discloses the field of micro-grid resisting false data injection attack, and specifically discloses a micro-grid control method resisting false data injection attack, which can quickly improve the influence caused by false data injection attack. Since the fault tolerance of switching control is low, the adaptive control method based on frequency-voltage error is combined to realize the recovery of frequency and voltage operation state, adjust the accuracy of compensation, and combine the two to establish a dual security control architecture with attack and fault defense capability. Compared with the traditional switching control method, the method can maintain the stability of the operation state when the micro-grid is attacked by false data injection. This mechanism can maintain the stability and function of the system by dynamically responding to the existence of false data, ensure that the micro-grid can continue to operate safely and effectively even when facing cyber-physical threats, and realize the reasonable distribution and stable operation of micro-grid power.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of micro-grid resisting false data injection attack, and particularly relates to a micro-grid control method resisting false data injection attack. BACKGROUND

[0002] In recent years, micro-grid has become a promising system for future power distribution network, and the micro-grid system is composed of distributed power supply, energy storage and conversion equipment, load, monitoring and protection equipment, and can effectively alleviate the problem of distributed power generation access and consumption. These systems usually use hierarchical control method to effectively operate, and the hierarchical control framework usually contains primary and secondary control. The primary control aims to realize the frequency and voltage stability of each individual inverter. However, the primary droop power distribution tends to cause deviation of frequency and voltage, and the purpose of the secondary control is to generate a compensating frequency and voltage signal to restore the error caused by the primary control. The secondary control can use a distributed control architecture, but this architecture, although it can realize coordination and synchronization between distributed nodes in the network system, may be vulnerable to false data injection attacks, which will affect the safety and stability of the entire power system when a node is attacked. Therefore, it is an important work to ensure the security of the node. SUMMARY

[0003] The purpose of the present application is to switch the integral coefficient of the secondary control of the micro-grid when the micro-grid is attacked by false data injection, and to realize the resistance to false data injection attack and the recovery of the running state based on the adaptive compensation of the frequency-voltage error. To this end, a micro-grid control method resisting false data injection attack is provided.

[0004] In order to achieve the above purpose, the technical scheme adopted by the present application is as follows:

[0005] A micro-grid control method resisting false data injection attack, comprising the following steps:

[0006] Step S1: establishing a micro-grid model using distributed control to realize electric energy conversion;

[0007] Step S2: establishing a state space equation of the distributed control micro-grid;

[0008] Step S3: designing a false data injection attack signal observer;

[0009] Step S4: designing a micro-grid network security switching controller;

[0010] Step S5: establishing a switching-adaptive control gain group;

[0011] Step S6: designing a distributed power generation unit error adaptive controller;

[0012] Step S7: design a micro-grid coordination control strategy of switching-adaptive secondary control;

[0013] Step S8: establish a Lyapunov function of the closed-loop system model of the i-th distributed power generation unit of the islanded micro-grid at time t and prove the system convergence.

[0014] The following is a further defined technical solution of the application, in step S1, a micro-grid model using distributed control is established, comprising:

[0015] Establish a main circuit structure of the distributed control micro-grid: sequentially electrically connected distributed power supply, inverter circuit, filter, connection line, common bus, local / common load;

[0016] Establish a local control link of the distributed micro-grid: droop controller, power calculator, voltage and current double loop, PWM generator;

[0017] First, the voltage and current at the filter port are collected, the active power and reactive power output by the distributed power generation unit are calculated through the power calculator, the voltage / frequency reference value is obtained through the droop controller according to the output power, then the PWM reference modulation signal is generated through the voltage and current double loop control, and finally the inverter circuit is controlled through the PWM generator to realize power conversion.

[0018] The following is a further defined technical solution of the application, in step S2, the state space equation of the distributed control micro-grid is established, comprising:

[0019] With the micro-grid voltage / frequency stability and power sharing as the goal, the state space variables are selected to be the actual frequency, actual voltage effective value, actual active power output and actual reactive power output of the i-th distributed power generation unit as the observation quantity of the distributed power generation unit agent, and the state space is established:

[0020]

[0021] In the formula: x i is the state vector of each distributed power supply model; y i is the output vector of each distributed power supply model; is the derivative of x i with respect to time t; f i , k i respectively represent two coupling state matrices of the i-th distributed power supply model in the islanded micro-grid at time t; D i represents the disturbance vector caused by the state variable x i of the i-th distributed power supply model in the islanded micro-grid at time t; g iState matrix of the nonlinear disturbance of the model of the i-th distributed power supply in the islanded microgrid at time t; P i , Q i Respectively, the output active / reactive power of the model of the i-th distributed power supply in the islanded microgrid; γ di , γ qi The components of the auxiliary variable of the current inner loop controller in the d-axis and q-axis; i Ldi , i Lqi The components of the filter inductance current in the d-axis and q-axis; v odi , v oqi , i odi , i oqi Respectively, the components of the output voltage and current in the d-axis and q-axis; h i State matrix of the output voltage of the model of the i-th distributed power supply in the islanded microgrid at time t; d i Coefficient of the nonlinear disturbance of the model of the i-th distributed power supply in the islanded microgrid at time t; u i Input quantity of the nonlinear disturbance of the model of the i-th distributed power supply in the islanded microgrid at time t; ω com The disturbance quantity of the system frequency; v bdi , v bqi Respectively, the voltage disturbance quantities in the d-axis and q-axis;

[0022] And the expressions of v bdi , v bqi are as follows:

[0023]

[0024] γ N The virtual resistance between nodes; i odi , i oqi Respectively, the d-axis and q-axis currents of the outputs of each distributed power supply in the islanded microgrid at time t; i load,di , i load,qi Respectively, the d-axis and q-axis currents on the loads of each distributed power supply in the islanded microgrid at time t; i line,d(i,j) , i line,q(i,j) Respectively, the d-axis and q-axis currents between the lines of each distributed power supply in the islanded microgrid at time t.

[0025] The following is a further defined technical solution of the present application, in step S3, a false data injection attack signal observer is established, comprising:

[0026]

[0027] In the formula: x k , x k+1 Respectively, the state vectors at times k and k+1; yk is the output vector at time k; f() is the spatial state transition function; h() is the observation state transition function; u k is the control input matrix at time k; w k， v k are the system noise and measurement noise matrices at time k, respectively, and both are Gaussian white noise; δ is the size of the false data injection attack; g k is the position matrix of the false data injection attack at time k;

[0028] In the case of parallel operation of the distributed power generation units in the microgrid, the output impedance is inductive, and the following formula is used for the distribution algorithm based on the consistent quadratic control:

[0029]

[0030] wherein: m i is the active frequency droop characteristic coefficient; n i is the reactive voltage droop characteristic coefficient; P i is the active power output after filtering of each distributed power supply; Ω i is the compensation for the frequency of each unit inverter; is the derivative of the frequency of each unit inverter; ω i is the frequency of each unit inverter; ω n is the input frequency of each unit inverter; ω ref is the rated value of the frequency; Q i is the reactive power output after filtering of each distributed power supply; ε i is the compensation for the frequency of each unit inverter; is the derivative of the voltage of each unit inverter; E i is the voltage of each unit inverter; E n is the input voltage of each unit inverter; E ref is the rated value of the frequency; a ij is the adjacency matrix element (1 if connected, otherwise 0); g i is the element of the gain matrix G = diag{g1, g2, …, g N} if the i-th distributed power generation unit receives the reference value, g i = 1, otherwise g i = 0; c i is the control gain.

[0031] The following is a further defined technical solution of the present application, in step S4, a microgrid network security switching controller is designed, comprising:

[0032] Adapt and cope with extreme situations, minimize the impact of extreme events, since the secondary control is to restore the deviated frequency and voltage to the nominal value, the inverter output port is measured continuously to define the condition trigger, the switching mechanism is used for the auxiliary controller, denoted as:

[0033]

[0034] wherein: e fi is the tracking error of the frequency of the ith distributed power generation unit; e pi is the tracking error of the active power of the ith distributed power generation unit; e Ei is the tracking error of the output voltage of the ith distributed power generation unit; e qi is the tracking error of the reactive power of the ith distributed power generation unit; h f , h p , h E , h q is a constant coefficient, the setting of which directly affects the cooperation performance, and needs to be balanced between response speed and transient oscillation; w s1 , w s2 , w s3 , w s4 is a control gain group.

[0035] The following is a further limited technical solution of the application, in step S5, the switching-adaptive control gain group is established, including:

[0036]

[0037]

[0038] wherein: f tri is the preset trigger threshold of the frequency; E tri is the preset trigger threshold of the output voltage; Δf iSTW and ΔE iSTW are coordinated by the trigger condition, that is, whether the trigger threshold is exceeded, which is regarded as a switchable condition, once the switchable condition is met, the gain command (w s1 , w s2 , w s3 , w s4 ) will be transmitted to the switching controller through the control signal link, and the switching controller will switch to use another control system.

[0039] The following is a further limited technical solution of the application, in step S6, the error adaptive controller of the distributed power generation unit is designed, including:

[0040] When the secondary controller fails, a new secondary controller is switched to restore the frequency and voltage to stable; Δf iADP and ΔEiADP The auxiliary controller based on the linear control mechanism is related to recovering the deviated frequency and voltage by controlling the gain group:

[0041]

[0042] Wherein: f tri2 is the preset trigger threshold of frequency; E tri2 is the preset trigger threshold of output voltage; g f1 , g f2 , g f3 , g f4 is the control gain group related to the quadratic frequency-voltage control respectively; Δf iSTW , ΔE iSTW , Δf iADP , ΔE iADP The auxiliary controller based on the linear control mechanism is related to recovering the deviated frequency / voltage by switching the control gain group, different Δf iSTW and ΔE iSTW The switching frequency and the corresponding output voltage quality will be improved.

[0043] The following is a further limited technical solution of the application, in step S7, the switching-adaptive quadratic control microgrid coordinated control strategy is established, including: detecting the frequency and voltage changes of the distributed power generation unit in each control period, once the switchable condition is triggered, the controller switches to the appropriate control system, and the error is detected after switching, the frequency and voltage compensation is carried out through the adaptive controller, so as to realize the purpose of resisting false data injection attack and restoring the running state of the microgrid system.

[0044] The following is a further limited technical solution of the application, in step S8, the Lyapunov function of the closed-loop system model of the i-th distributed power generation unit of the islanded microgrid at time t is established and the system convergence is proved, including:

[0045] The Lyapunov function of the closed-loop system model of the i-th distributed power generation unit of the islanded microgrid at time t is constructed as follows:

[0046]

[0047] In the formula: e di (t) represents the deviation of the estimated value of the i-th distributed power generation unit of the islanded microgrid at time t from the actual nonlinear disturbance u i , is the transpose of e di (t);

[0048] The proof of system convergence includes:

[0049] If the Lyapunov function satisfies Vi(xi(t))>0, The system equilibrium state is asymptotically stable.

[0050] The first-order time derivative of the Lyapunov function of the closed-loop system model of the i-th distributed power generation unit of the island micro-grid at time t is:

[0051]

[0052] According to the above formula, it is proved that under the action of the nonlinear disturbance input u di (t), u fdi (t), the disturbance deviation e i (t) and its derivative tend to 0, and the disturbance estimation error e di (t) also tends to 0, so that the state quantity of the i-th distributed power generation unit follows the reference value of the state quantity.

[0053] Compared with the prior art, the present application has the following technical effects:

[0054] The present application proposes a micro-grid control method based on switching-adaptive quadratic control to resist false data injection attacks, so as to quickly improve the influence caused by false data injection attacks. Since the fault tolerance rate of switching control is low, and the adaptive control method has the advantages of strong applicability and high flexibility, the two are combined to generate a switching-adaptive quadratic control method, dynamically adjust the accuracy of compensation, and establish a dual security control architecture with attack and fault defense capability. Compared with the traditional switching control method, the method of the present application can maintain the stability of the running state when the micro-grid is subjected to false data injection attacks, and at the same time, the reasonable distribution of power is realized.

[0055] The present application will be further described below in conjunction with the drawings and embodiments. DETAILED DESCRIPTION

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0057] Figure 1 A simplified model diagram of the internal unit inverter of the micro-grid of the present application;

[0058] Figure 2 A control block diagram of the method of the present application;

[0059] Figure 3A flow chart of the method of the present invention;

[0060] Figure 4 A frequency plot of an inverter using the method of the present invention;

[0061] Figure 5 A frequency plot of an inverter using a conventional method;

[0062] Figure 6 A plot of inverter active power magnitude using the method of the present invention;

[0063] Figure 7 A plot of inverter active power magnitude using a conventional method;

[0064] Figure 8 A plot of inverter output voltage magnitude using the method of the present invention;

[0065] Figure 9 A plot of inverter output voltage magnitude using a conventional method;

[0066] Figure 10 A plot of inverter reactive power magnitude using the method of the present invention;

[0067] Figure 11 A plot of inverter reactive power magnitude using a conventional method. DETAILED DESCRIPTION

[0068] In order to make the above objectives, features and advantages of the present invention more clear and comprehensible, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention can be implemented in many different ways other than those described herein, and one of ordinary skill in the art can make similar improvements without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.

[0069] As shown in Figures 1-11 , the present embodiment provides a microgrid control method against false data injection attack, comprising the following steps:

[0070] Step S1: establishing a microgrid model using distributed control to realize electric energy conversion;

[0071] Step S2: establishing a state space equation of the distributed control microgrid;

[0072] Step S3: designing a false data injection attack signal observer;

[0073] Step S4: designing a microgrid network security switching controller;

[0074] Step S5: establishing a switching-adaptive control gain set;

[0075] Step S6: Design an adaptive error controller for the distributed generation unit;

[0076] Step S7: Design a microgrid coordinated control strategy for switching-adaptive secondary control;

[0077] Step S8: Establish the Lyapunov function for the closed-loop system model of the i-th distributed generation unit of the islanded microgrid at time t and prove the system convergence.

[0078] In step S1, a microgrid model employing distributed control is established, as detailed below:

[0079] Step S1.1: Establish the main circuit structure of the distributed control microgrid: the distributed power source, inverter circuit, filter, connecting line, common bus, and local / common load are connected in sequence.

[0080] Step S1.2: Establish the local control components of the distributed microgrid: droop controller, power calculator, voltage and current dual loop, and PWM generator.

[0081] Its control process is as follows: First, the voltage and current at the filter port are collected. The active power and reactive power output by the distributed generation unit are calculated by the power calculator. Based on the output power, the voltage / frequency reference value is obtained by the droop controller. Then, the voltage and current dual-loop control generates the PWM reference modulation signal. Finally, the inverter circuit is controlled by the PWM generator to realize the power conversion.

[0082] In step S2, the state-space equations of the distributed control microgrid are established, as follows:

[0083] With the goals of microgrid voltage / frequency stability and power equalization, the state space variables are selected using the actual frequency, actual effective voltage value, actual active power output, and actual reactive power output of the i-th distributed generation unit as the observations of the distributed generation unit agent, and the state space is established as follows:

[0084]

[0085] In the formula: x i For each distributed power source model, y represents the state vector; i For each distributed power source model, the output vector is... For x i The derivative with respect to time t; f i k i Let D represent the two coupling state matrices of the i-th distributed generation model in the islanded microgrid at time t; i Let the i-th distributed generation model in the islanded microgrid at time t be represented by the state variable x. i The disturbance vector that causes system fluctuations; gi is the state matrix of the nonlinear disturbance of the ith distributed generator model in the islanded microgrid at time t; P i , Q i are the output active / reactive power of the ith distributed generator model in the islanded microgrid; γ di , γ qi are the components of the auxiliary variable of the current inner loop controller in the d-axis and q-axis; i Ldi , i Lqi are the components of the filter inductance current in the d-axis and q-axis; v odi , v oqi , i odi , i oqi are the components of the output voltage and current in the d-axis and q-axis; h i is the state matrix of the output voltage of the ith distributed generator model in the islanded microgrid at time t; d i is the coefficient of the nonlinear disturbance of the ith distributed generator model in the islanded microgrid at time t; u i is the input quantity of the nonlinear disturbance of the ith distributed generator model in the islanded microgrid at time t; ω com is the disturbance quantity of the system frequency; v bdi , v bqi are the voltage disturbance quantities in the d-axis and q-axis, respectively;

[0086] And the expressions of v bdi , v bqi are as follows:

[0087]

[0088] γ N is the virtual resistance between nodes; i odi , i oqi are the d, q-axis currents of the output of each distributed generator in the islanded microgrid at time t; i load,di , i load,qi are the d, q-axis currents on the load of each distributed generator in the islanded microgrid at time t; i line,d(i,j) , i line,q(i,j) are the d, q-axis currents between lines of each distributed generator in the islanded microgrid at time t.

[0089] Step S3, an FDI attack signal observer is established, and the AC microgrid model containing FDI can be derived according to the state space model of step S2, which is as follows:

[0090] The state space equation of the multi-DG microgrid is changed as follows:

[0091]

[0092] Taking the differential of both sides of the above formula with respect to time t, the following formula can be obtained:

[0093]

[0094] Further, the state space equation of the multi-DG microgrid can be linearly transformed, and the following formula can be obtained after simplification:

[0095]

[0096] wherein z i is the state vector of the nonlinear disturbance observer; is the estimated value of the nonlinear disturbance u i suffered by the i-th distributed generation unit of the islanded microgrid at time t; l i () is the state equation of the i-th distributed generation unit in the islanded microgrid at time t.

[0097] Further, the formula for calculating the deviation between the estimated value of the i-th distributed generation unit in the islanded microgrid at time t and the nonlinear disturbance is as follows:

[0098]

[0099] A false data injection attack signal observer is established, including:

[0100]

[0101] wherein x k , x k+1 are the state vectors at times k and k+1, respectively; y k is the output vector at time k; f() is the space state transition function; h() is the observation state transition function; u k is the control input matrix at time k; w k， v k are the system noise and measurement noise matrices at time k, respectively, and both are Gaussian white noise; δ is the size of the false data injection attack; g k is the position matrix of the false data injection attack at time k.

[0102] In the case of parallel operation of the distributed generation units in the microgrid and inductive output impedance, the following formula is used for the distribution algorithm based on the consistent quadratic control:

[0103]

[0104] wherein m i is the active frequency droop characteristic coefficient; n i is the reactive voltage droop characteristic coefficient; P iis the active power output from each distributed power filter; Ω i is the compensation for the frequency of each unit inverter; is the derivative of the frequency of each unit inverter; ω i is the frequency of each unit inverter; ω n is the input frequency of each unit inverter; ω ref is the rated value of the frequency; Q i is the reactive power output from each distributed power filter; ε i is the compensation for the frequency of each unit inverter; is the derivative of the voltage of each unit inverter; E i is the voltage of each unit inverter; E n is the input voltage of each unit inverter; E ref is the rated value of the frequency; a ij is the adjacency matrix element (1 if connected, otherwise 0); g i is the element of the gain matrix G = diag{g1, g2, …, g N} if the i-th distributed power unit receives a reference value, g i = 1, otherwise g i = 0; c i is the control gain.

[0105] Step S4 designs a microgrid network safety switching controller, as follows:

[0106] According to past experience, the greater the value of c i , the faster the response speed, but the greater the transient oscillation. In order to deal with extreme events such as communication signal interruption, control command abnormality and unit inverter sudden stop, a switching controller is designed here. It can adapt to and cope with extreme situations, minimizing the impact of extreme events. Since the secondary control restores the deviated frequency and voltage to the nominal value, the output port of the inverter can be continuously measured to define the condition trigger. The switching mechanism can be used as an auxiliary controller, denoted as:

[0107]

[0108] where: e fi is the tracking error of the frequency of the i-th distributed power unit; e pi is the tracking error of the active power of the i-th distributed power unit; e Ei is the tracking error of the output voltage of the i-th distributed power unit; e qi is the tracking error of the reactive power of the i-th distributed power unit; h f , h p , h E , hq is a constant coefficient, whose setting directly affects the cooperation performance, and needs to be balanced between response speed and transient oscillation; w s1 , w s2 , w s3 , w s4 is a control gain group.

[0109] The switching-adaptive control gain group is established in step S5, and the configuration is as follows:

[0110]

[0111] Wherein: f tri is a preset triggering threshold of frequency; E tri is a preset triggering threshold of output voltage; Δf iSTW and ΔE iSTW are coordinated by triggering conditions, that is, whether the triggering threshold is exceeded, which is regarded as a switchable condition, and once the switchable condition is met, the gain command (w s1 , w s2 , w s3 , w s4 ) will be transmitted to the switching controller through the control signal link, and the switching controller will switch to use another control system.

[0112] In step S6, the distributed generation unit error adaptive controller is designed, and the details are as follows:

[0113] When the secondary controller fails, it will switch to a new secondary controller to restore the frequency and voltage to stable; Δf iADP and ΔE iADP are related to the auxiliary controller based on the linear control mechanism, and are used to restore the deviated frequency and voltage through the control gain group:

[0114]

[0115] Wherein: f tri2 is a preset triggering threshold of frequency; E tri2 is a preset triggering threshold of output voltage; g f1 , g f2 , g f3 , g f4 is a control gain group related to the secondary frequency-voltage control respectively; Δf iSTW , ΔE iSTW , Δf iADP , ΔE iADP are related to the auxiliary controller based on the linear control mechanism, and are used to restore the deviated frequency / voltage through the switching control gain group, and different Δf iSTW and ΔE iSTWThe switching frequency and the corresponding output voltage quality will be improved.

[0116] The microgrid coordination control strategy of switching-adaptive secondary control is established in step S7, including: detecting the frequency and voltage changes of the distributed power generation unit in each control period, triggering the switchable condition, switching the controller to the appropriate control system, and detecting the error after switching, and compensating the frequency and voltage through the adaptive controller, so as to realize the purpose of resisting false data injection attacks and restoring the running state of the microgrid system.

[0117] The Lyapunov function of the closed-loop system model of the i-th distributed power generation unit of the islanded microgrid at time t is established in step S8, and the system convergence is proved, including:

[0118] The Lyapunov function of the closed-loop system model of the i-th distributed power generation unit of the islanded microgrid at time t is constructed as follows:

[0119]

[0120] In the formula: e di (t) represents the estimated value of the i-th distributed power generation unit in the islanded microgrid at time t and the actual nonlinear disturbance u i , the deviation of e (t) is the transpose of e di (t);

[0121] The system convergence includes:

[0122] If the Lyapunov function satisfies Vi(xi(t))>0, then the system equilibrium state is asymptotically stable;

[0123] The first-order time derivative of the Lyapunov function of the closed-loop system model of the i-th distributed power generation unit of the islanded microgrid at time t is:

[0124]

[0125] According to the above formula, it is proved that under the action of the nonlinear disturbance input u di (t), u fdi (t), the disturbance deviation e i (t) and its derivative tend to 0, and the disturbance estimation error e di (t) also tends to 0, realizing that the state quantity of the i-th distributed power generation unit follows the reference value of the state quantity.

[0126] A microgrid model with four parallel inverters is built, a switching-adaptive controller is designed and applied to the secondary control of the microgrid, and the output voltage and frequency of the inverters are observed and compared with the microgrid using the traditional switching method. The microgrid is operated in island mode, and at t = 2 seconds, the load on DG4 is attacked with Δe ifdi = 0.5, and the changes in the output voltage amplitude and frequency of the inverters of the microgrid during this period are observed, where the power of the common load is 20 kW.

[0127] In this embodiment, the effect diagram of the switching-adaptive control method used by the present application is shown in Figure 4 、 Figure 6 、 Figure 8 、 Figure 10 ; Figure 5 、 Figure 7 、 Figure 9 、 Figure 11 is the effect diagram of the traditional switching control method. For easy identification and comparison, the state quantity waveform of DG4 is set as a dashed line. For the power distribution, Figure 5 and Figure 6 are the active power diagrams of the inverters using the switching-adaptive control of the present application and the traditional switching control, respectively, Figure 5 the active power deviation of DG4 is about 6 kW, which is reduced by nearly 40% compared to Figure 6 . Figure 10 and Figure 11 are the reactive power diagrams of the inverters using the switching-adaptive control of the present application and the traditional switching control, respectively, Figure 10 the peak value deviation is about 1 kvar, which is reduced by nearly 50% compared to Figure 11 .

[0128] For the system operating state, Figure 4 the frequency error is about 0.1 Hz, while Figure 4 the frequency error is about 0.2 Hz, which is reduced by nearly 50% compared to the present application. Figure 8 and Figure 9 are the output voltage amplitude diagrams of the inverters using the switching-adaptive control of the present application and the traditional switching control, respectively. It can be seen that the output voltage of the inverter using the switching-adaptive control can still remain basically constant after being attacked by the network. In comparison, Figure 9 the output voltage of the inverter using the traditional switching control fluctuates greatly, about 0.5 V, and it can be seen that there is a significant deviation between the state quantity and the rated value under the traditional method.

[0129] The above merely describes preferred embodiments of the present application, and is not intended to limit the present application in any form. Any person skilled in the art, without departing from the technical scheme of the present application, can make many possible changes and modifications to the technical scheme of the present application, or modify equivalent embodiments, by using the disclosed methods and technical contents. Therefore, any equivalent changes made according to the shape, structure and principle of the present application, without departing from the technical scheme of the present application, should be covered by the protection scope of the present application.

Claims

1. A microgrid control method for resisting spoofed data injection attacks, characterized in that, Includes the following steps: Step S1: Establish a microgrid model using distributed control to realize power conversion; Step S2: Establish the state-space equations of the distributed control microgrid; Step S3: Design a fake data injection attack signal observer; Step S4: Design a network security switching controller for the microgrid; Step S5: Establish a switching-adaptive control gain group; Step S6: Design an adaptive error controller for the distributed generation unit; Step S7: Design a microgrid coordinated control strategy for switching-adaptive secondary control; Step S8: Establish the Lyapunov function of the closed-loop system model of the i-th distributed generation unit of the islanded microgrid at time t and prove the system convergence; In step S6, an adaptive controller for the distributed generation unit error is designed, including: When the secondary controller fails, a new secondary controller will be switched on to restore the frequency and voltage to a stable state. Δf iADP and ΔE iADP Related to an auxiliary controller based on a linear control mechanism, used to recover the deviated frequency and voltage by controlling the gain group: in: f tri2 It is the preset trigger threshold of the frequency; E tri2 It is the preset trigger threshold of the output voltage; g f1 , g f2 , g f3 , g f4 These are control gain groups that are respectively related to the secondary frequency-voltage control; Δf iSTW , ΔE iSTW , Δf iADP , ΔE iADP Related to an auxiliary controller based on a linear control mechanism, used to recover the deviated frequency / voltage by switching control gain groups, different Δ f iSTW and ΔE iSTW This will improve the switching frequency and the corresponding output voltage quality; In step S7, a microgrid coordinated control strategy of switching-adaptive secondary control is established, including: detecting the frequency and voltage changes of distributed generation units in each control cycle; once the switching condition is triggered, the switching controller switches to the appropriate control system; at the same time, the error is detected after switching, and frequency and voltage compensation is performed through the adaptive controller, thereby achieving the purpose of the microgrid system resisting false data injection attacks and restoring the operating state. In step S8, the Lyapunov function of the closed-loop system model of the i-th distributed generation unit of the islanded microgrid at time t is established and the system convergence is proven, including: structure t Time-isolated microgrids i The Lyapunov function for the closed-loop system model of a distributed generation unit is as follows: In the formula: e di (t) express t In the first time island microgrid i Estimates of individual distributed generation units u^ i With actual nonlinear disturbance u i deviation, eT di(t) for e di (t) transpose; Proving the convergence of the system includes: If the Lyapunov function satisfies Vi(xi(t))>0 , V·i(xi(t))<0 If so, the system equilibrium state is asymptotically stable; Pick t Time-isolated microgrids i The first-order time derivative of the Lyapunov function for the closed-loop system model of a distributed generation unit is: Based on the formula above, it is proved that: under nonlinear disturbance input... u di (t) , u fdi (t) Under the influence of disturbance deviation e i (t) and its derivative e· i (t) The error tends to 0 and the disturbance estimation error e di (t) It also tends to 0, achieving the first i The state variables of each distributed generation unit follow the reference values ​​of the state variables.

2. The microgrid control method for resisting spoofed data injection attacks as described in claim 1, characterized in that, In step S1, a microgrid model employing distributed control is established, including: Establish the main circuit structure of the distributed control microgrid: distributed power source, inverter circuit, filter, connection line, common bus, and local / common load connected in sequence; Establish local control components for the distributed microgrid: droop controller, power calculator, voltage and current dual-loop circuit, and PWM generator; First, the voltage and current at the filter port are collected. The active and reactive power output of the distributed generation unit are calculated by the power calculator. Based on the output power, the voltage / frequency reference value is obtained by the droop controller. Then, the voltage and current dual-loop control generates a PWM reference modulation signal. Finally, the inverter circuit is controlled by the PWM generator to realize the power conversion.

3. A microgrid control method for resisting spoofed data injection attacks as described in claim 2, characterized in that, In step S2, the state-space equations of the distributed control microgrid are established, including: With the goals of microgrid voltage / frequency stability and power equalization, the state space variables are selected using the actual frequency, actual effective voltage value, actual active power output, and actual reactive power output of the i-th distributed generation unit as the observations of the distributed generation unit agent, and the state space is established as follows: In the formula: x i For each distributed power source model, there is a state vector. y i For each distributed power source model, the output vector is... i for x i Regarding time t The derivative; f i 、k i They are respectively represented as t In the first time island microgrid i Two coupled state matrices of a distributed power source model; D i Represented as t In the first time island microgrid i A distributed power generation model consists of state variables. x i The disturbance vector that causes system fluctuations; g i Let t represent the time t of the islanded microgrid. i The state matrix of a distributed power source model under nonlinear perturbation; P i 、Q i point Don't represent the first in an islanded microgrid. i The output active / reactive power of a distributed power source model; γ di , γ qi It is an auxiliary variable of the current inner loop controller. d shaft and q The components of the axis; i Ldi , i Lqi Is the filter inductor current in d shaft and q The components of the axis; v odi , v oqi , i odi , i oqi These are the output voltage and current, respectively. d shaft and q The components of the axis; h i Represented as t In the first time island microgrid i The state matrix of the output voltage of a distributed power source model; d i Represented as t In the first time island microgrid i The coefficients of nonlinear disturbances in a distributed power source model; u i Represented as t In the first time island microgrid i The input of nonlinear disturbances to a distributed power source model; ω com It is the disturbance amount of the system frequency; v bdi , v bqi They are d shaft and q Voltage disturbance on the shaft; and v bdi , v bqi The expression is: γ N Virtual resistance between nodes; i odi , i oqi They are respectively t The output of each distributed power source in a time-isolated microgrid d , q shaft current; i load,di , i load,qi They are respectively t In a time-isolated microgrid, each distributed power source load... d , q The current in the shaft; i line,d(i,j) , i line,q(i,j) They are respectively t Interconnection between distributed power lines in a time-isolated microgrid d , q The current in the shaft.

4. A microgrid control method for resisting spoofed data injection attacks as described in claim 3, characterized in that, In step S3, a fake data injection attack signal observer is established, including: In the formula: x k , x k +1 They are respectively k , k+1 The state vector at any given time; y k for k Output vector at time step; f ( ) is the space state transition function; h ( ) represents the observation state transition function; u k for k Control the input matrix at all times; w k， v k They are respectively k The system noise and measurement noise matrices are time-based and are both Gaussian white noise. δ Injecting the size of the attack with fake data; g k for k Location matrix of real-time fake data injection attacks; When distributed generation units in a microgrid operate in parallel and have inductive output impedance, the following allocation algorithm based on consensus-based secondary control is used: in: m i This is the active frequency droop characteristic coefficient; n i P is the reactive voltage droop characteristic coefficient. i It is the active power output after filtering of each distributed power source; Ω i Specifically, this includes frequency compensation for each unit inverter; It is the derivative of the frequency of each unit inverter; ω i It is the frequency of each unit inverter; ω n It is the input frequency of each unit inverter; ω ref It is the rated value of the frequency; Q i It is the reactive power output after filtering of each distributed power source; ε i Specifically, this includes frequency compensation for each unit inverter; It is the derivative of the voltage of each unit inverter; E i It is the voltage of each unit inverter; E n It is the input voltage of each unit inverter; E ref It is the rated value of the frequency; a ij Elements of the adjacency matrix (1 for connected elements, 0 for otherwise); g i It is the gain matrix G=diag{g 1 ,g 2 ,…,g N } The element; if the first i If a distributed generation unit receives a reference value, then g i =1 ,otherwise g i =0 ; c i To control the gain.

5. A microgrid control method for resisting spoofed data injection attacks as described in claim 4, characterized in that, In step S4, a microgrid network security switching controller is designed, including: To adapt to and respond to extreme conditions and minimize the impact of extreme events, secondary control restores the deviated frequency and voltage to nominal values, allowing continuous measurement of the inverter output port to define conditional triggering. A switching mechanism is used for the auxiliary controller, as shown below: in: e fi It is the first i Tracking error of the frequency of each distributed generation unit; e pi No. i Tracking error of active power of each distributed generation unit; e Ei It is the first i The tracking error of the output voltage of each distributed generation unit; e qi It is the first i Tracking error of reactive power of a distributed generation unit; h f , h p , h E , h q It is a constant coefficient, and its setting directly affects the cooperative performance. A trade-off needs to be made between response speed and transient oscillation. w s1 , w s2 , w s3 , w s4 It is the control gain group.

6. A microgrid control method for resisting spoofed data injection attacks as described in claim 5, characterized in that, In step S5, a switching-adaptive control gain group is established, including: in: f tri It is the preset trigger threshold of the frequency; E tri It is the preset trigger threshold of the output voltage; Δf iSTW and ΔE iSTW Coordinated by triggering conditions, i.e., whether a trigger threshold is exceeded, this is considered a switchable condition. Once the switchable condition is met, the gain command ( w s1 , w s2 , w s3 , w s4 The signal will be transmitted to the switching controller via the control signal link, and the switching controller will then switch to using another control system.

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