Micro-grid control method for resisting false data injection attack

Abstract

The invention relates to the field of resistance of a micro-grid to a false data injection attack, and particularly discloses a micro-grid control method for resisting the false data injection attack, so as to quickly improve the influence caused by the false data injection attack. Due to the fact that the fault-tolerant rate of switching control is low, a self-adaptive control method based on frequency-voltage errors is combined, recovery of frequency and voltage operation states and adjustment of compensation accuracy are achieved, the frequency and voltage operation states and the self-adaptive control method are combined for use, and a dual-safety control framework with attack and fault defense capacity is established. Compared with a traditional switching control method, the method can keep the running state stable when the micro-grid is attacked by false data injection. According to the mechanism, the stability and the function of the system are maintained by dynamically responding to the existence of false data, the micro-grid can be ensured to continuously, safely and effectively run even if the micro-grid is in the face of network physical threats, and reasonable distribution and stable running of the power of the micro-grid are realized.

Description

Technical Field

[0001] The present invention relates to the field of microgrid defense against false data injection attacks, and in particular to a microgrid control method for defense against false data injection attacks. Background Art

[0002] In recent years, microgrids have become a promising system for future distribution networks. Microgrid systems consist of distributed power sources, energy storage and conversion equipment, loads, monitoring and protection equipment, which can effectively alleviate the problems of distributed generation access and consumption. These systems usually use a hierarchical control method to operate effectively. The hierarchical control framework usually contains primary and secondary control. The primary control aims to achieve frequency and voltage stability for each individual inverter. However, the primary droop power distribution often causes frequency and voltage deviations. The purpose of secondary control is to generate compensating frequency and voltage signals to restore the errors caused by primary control. Secondary control can use a distributed control architecture, but although this architecture can achieve coordination and synchronization between distributed nodes in the network system, it may be vulnerable to false data injection attacks. When a node is attacked by the network, it will affect the safety and stability of the entire power system. Therefore, ensuring the security of the node will be an important task. Summary of the invention

[0003] The purpose of the present invention is to switch the integral coefficient of the secondary control of the microgrid when the microgrid is attacked by false data injection, and at the same time adaptively compensate the secondary control based on the frequency-voltage error, thereby achieving resistance to false data injection attacks and recovery of the operating state. To this end, a microgrid control method for resisting false data injection attacks is provided.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0005] A microgrid control method for resisting false data injection attacks comprises the following steps:

[0006] Step S1: Establish a microgrid model using distributed control to achieve power conversion;

[0007] Step S2: Establishing the state space equation of the distributed control microgrid;

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

[0009] Step S4: designing a microgrid network security switching controller;

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

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

[0012] Step S7: designing a microgrid coordinated control strategy of switching-adaptive secondary control;

[0013] Step S8: Establish the Lyapunov function of the closed-loop system model of the ith distributed generation unit of the island microgrid at time t and prove the system convergence.

[0014] The following is a technical solution further defined by the present invention, in which a microgrid model using distributed control is established in step S1, including:

[0015] Establish the main circuit structure of the distributed control microgrid: distributed power sources, inverter circuits, filters, connecting lines, public buses, and local / public loads that are electrically connected in sequence;

[0016] Establish the local control link of distributed microgrid: droop controller, power calculator, voltage and current dual loop, PWM generator;

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

[0018] The following is a technical solution further defined by the present invention, in which a state space equation of a distributed control microgrid is established in step S2, including:

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

[0020]

[0021] Where: x i is the state vector of each distributed power model; y i is the output vector of each distributed power model; For x i The derivative with respect to time t; f i , k i They are respectively represented as the two coupling state matrices of the i-th distributed power model in the isolated microgrid at time t; D i It is represented as: the i-th distributed power model in the isolated microgrid at time t is composed of state variables x i The disturbance vector that causes system fluctuations; g iIt is represented as the state matrix of the nonlinear disturbance of the i-th distributed power model in the isolated microgrid at time t; P i , Q i They represent the output active / reactive power of the i-th distributed power model in the isolated microgrid; γ di , γ qi is the component of the auxiliary variable of the current inner loop controller on the d-axis and q-axis; i Ldi 、i Lqi is the component of the filter inductor current on the d-axis and q-axis; v odi 、v oqi 、i odi 、i oqi are the components of the output voltage and current on the d-axis and q-axis respectively; h i It is represented as the state matrix of the output voltage of the i-th distributed power model in the isolated microgrid at time t; d i It is represented as the coefficient of the nonlinear disturbance of the i-th distributed generation model in the isolated microgrid at time t; u i It is represented as the input quantity of the nonlinear disturbance of the i-th distributed power model in the isolated microgrid at time t; ω com is the disturbance of the system frequency; v bdi 、v bqi are the voltage disturbances of the d-axis and q-axis respectively;

[0022] And v bdi 、v bqi The expression is:

[0023]

[0024] γ N is the virtual resistance between nodes; i odi 、i oqi are the d-axis and q-axis currents output by each distributed power source in the isolated microgrid at time t; i load,di 、i load,qi are the d-axis and q-axis currents of each distributed power load in the isolated microgrid at time t; i line,d(i,j) 、i line,q(i,j) They are the d-axis and q-axis currents between each distributed power supply line in the isolated microgrid at time t.

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

[0026]

[0027] Where: x k , x k+1 are the state vectors at time k and k+1 respectively; yk is the output vector at time k; f() is the spatial state transfer function; h() is the observation state transfer 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, 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] When the distributed generation units in the microgrid are connected in parallel and the output impedance is inductive, the following distribution algorithm based on consistent secondary control is adopted:

[0029]

[0030] Where: 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 of each distributed power source after filtering; Ω i Especially 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 frequency; Q i is the reactive power output by each distributed power source after filtering; ε i Especially 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 frequency; a ij is the adjacency matrix element (1 if connected, otherwise 0); g i is the gain matrix G = diag{g 1 ,g 2 ,…,g N}; if the i-th distributed generation unit receives the reference value, then g i =1, otherwise g i =0;c i To control the gain.

[0031] The following is a technical solution further defined by the present invention, wherein a microgrid network security switching controller is designed in step S4, including:

[0032] Adapt and respond to extreme situations and minimize the impact of extreme events. Since the secondary control is to restore the deviated frequency and voltage to the nominal value, it allows continuous measurement of the inverter output port to define the condition trigger. The switching mechanism is used for the auxiliary controller, which is expressed as:

[0033]

[0034] Where: e fi is the tracking error of the frequency of the ith distributed generation unit; e pi Tracking error of active power of the i-th distributed generation unit; e Ei is the tracking error of the output voltage of the i-th distributed generation unit; e qi is the tracking error of the reactive power of the ith distributed generation unit; h f ,h p ,h E ,h q is a constant coefficient, whose setting directly affects the collaborative performance and requires a trade-off between response speed and transient oscillation; w s1 , w s2 , w s3 , w s4 is the control gain group.

[0035] The following is a technical solution further defined by the present invention, in which a switching-adaptive control gain group is established in step S5, comprising:

[0036]

[0037]

[0038] Where: f tri is the preset trigger threshold of frequency; E tri is the preset trigger threshold of the output voltage; Δf iSTW and ΔE iSTW 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 technical solution further defined by the present invention, wherein in step S6, a distributed generation unit error adaptive controller is designed, comprising:

[0040] When the secondary controller fails, a new secondary controller will be switched to restore the frequency and voltage to stability; Δf iADP and ΔEiADP Related to the auxiliary controller based on a linear control mechanism, it is used to restore the deviated frequency and voltage by controlling the gain group:

[0041]

[0042] Where: f tri2 is the preset trigger threshold of frequency; E tri2 is the preset trigger threshold of the output voltage; g f1 , g f2 , g f3 , g f4 are the control gain groups associated with the secondary frequency-voltage control; Δf iSTW , ΔE iSTW , Δf iADP , ΔE iADP Related to the auxiliary controller based on linear control mechanism, used to restore the deviated frequency / voltage by switching the control gain set, different Δf iSTW and ΔE iSTW The switching frequency and the corresponding output voltage quality will be improved.

[0043] The following is a technical solution further defined by the present invention, in which a switching-adaptive secondary control microgrid coordinated control strategy is established in step S7, including: detecting the frequency and voltage changes of the distributed power generation unit in each control cycle, and once the switchable condition is triggered, the switching controller switches to a suitable control system, and at the same time detects the error after switching, and performs frequency and voltage compensation through the adaptive controller, thereby achieving the purpose of the microgrid system resisting false data injection attacks and recovering the operating status.

[0044] The following is a technical solution further defined by the present invention, in step S8, a Lyapunov function of a closed-loop system model of the i-th distributed generation unit of the island 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 generation unit of the island microgrid at time t is constructed as follows:

[0046]

[0047] Where: e di (t) represents the estimated value of the i-th distributed generation unit in the island microgrid at time t and the actual nonlinear disturbance u i The deviation, for e di The transpose of (t);

[0048] Proving the convergence of the system involves:

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

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

[0051]

[0052] According to the above formula, we can prove that: when the nonlinear disturbance input u di (t),u fdi (t), the disturbance deviation e i (t) and its derivative tends to 0 and the disturbance estimation error e di (t) also tends to 0, realizing that the state quantity of the i-th distributed generation unit follows the reference value of the state quantity.

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

[0054] The present invention proposes a microgrid control method for resisting false data injection attacks based on switching-adaptive secondary control, so as to quickly improve the impact of 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 used in combination to generate a switching-adaptive based secondary control method, dynamically adjust the accuracy of compensation, and establish a dual safety control architecture with attack and fault defense capabilities; compared with the traditional switching control method, the method of the present invention can maintain the stability of the operating state when the microgrid is attacked by false data injection, and at the same time realize the reasonable distribution of power.

[0055] The present invention is further described below in conjunction with the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 A simplified model diagram of parallel connection of unit inverters within a microgrid of the present invention;

[0058] Figure 2 is a control block diagram of the method of the present invention;

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

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

[0061] Figure 5 is the inverter frequency diagram using the traditional method;

[0062] Figure 6 is an active power amplitude diagram of an inverter using the method of the present invention;

[0063] Figure 7 is the inverter active power amplitude diagram using the traditional method;

[0064] Figure 8 is a diagram of the output voltage amplitude of the inverter using the method of the present invention;

[0065] Fig. 9 is a graph of the inverter output voltage amplitude using the traditional method;

[0066] Fig.10 A reactive power amplitude diagram of an inverter using the method of the present invention;

[0067] Fig.11 Figure 2 is a graph of the reactive power amplitude of the inverter using the traditional method. DETAILED DESCRIPTION

[0068] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific embodiments disclosed below.

[0069] like Figure 1-11 As shown, this embodiment provides a microgrid control method for resisting false data injection attacks, comprising the following steps:

[0070] Step S1: Establish a microgrid model using distributed control to achieve power conversion;

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

[0072] Step S3: Design 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 group;

[0075] Step S6: designing a distributed generation unit error adaptive controller;

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

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

[0078] In step S1, a microgrid model using distributed control is established, as follows:

[0079] Step S1.1, establish the main circuit structure of the distributed control microgrid: the distributed power source, inverter circuit, filter, connection line, public bus, local / public load that are electrically connected in sequence;

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

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

[0082] In step S2, the state space equation of the distributed control microgrid is established as follows:

[0083] With the goal of voltage / frequency stability and power distribution of the microgrid, the state space variables are selected with the actual frequency, actual voltage effective value, actual active power output, and actual reactive power output of the i-th distributed generation unit as the observation quantity of the distributed generation unit agent, and the state space is established:

[0084]

[0085] Where: x i is the state vector of each distributed power model; y i is the output vector of each distributed power model; For x i The derivative with respect to time t; f i , k i They are respectively represented as the two coupling state matrices of the i-th distributed power model in the isolated microgrid at time t; D i It is represented as: the i-th distributed power model in the isolated microgrid at time t is composed of state variables x i The disturbance vector that causes system fluctuations; gi It is represented as the state matrix of the nonlinear disturbance of the i-th distributed power model in the isolated microgrid at time t; P i , Q i They represent the output active / reactive power of the i-th distributed power model in the isolated microgrid; γ di , γ qi is the component of the auxiliary variable of the current inner loop controller on the d-axis and q-axis; i Ldi 、i Lqi is the component of the filter inductor current on the d-axis and q-axis; v odi 、v oqi 、i odi 、i oqi are the components of the output voltage and current on the d-axis and q-axis respectively; h i It is represented as the state matrix of the output voltage of the i-th distributed power model in the isolated microgrid at time t; d i It is represented as the coefficient of the nonlinear disturbance of the i-th distributed generation model in the isolated microgrid at time t; u i It is represented as the input quantity of the nonlinear disturbance of the i-th distributed power model in the isolated microgrid at time t; ω com is the disturbance of the system frequency; v bdi 、v bqi are the voltage disturbances of the d-axis and q-axis respectively;

[0086] And v bdi 、v bqi The expression is:

[0087]

[0088] γ N is the virtual resistance between nodes; i odi 、i oqi are the d-axis and q-axis currents output by each distributed power source in the isolated microgrid at time t; i load,di 、i load,qi are the d-axis and q-axis currents of each distributed power load in the isolated microgrid at time t; i line,d(i,j) 、i line,q(i,j) They are the d-axis and q-axis currents between each distributed power supply line in the isolated microgrid at time t.

[0089] Step S3, establish an FDI attack signal observer, and derive the AC microgrid model containing FDI according to the state space model of step S2, as follows:

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

[0091]

[0092] By taking the differential derivative of both sides of the above equation with respect to time t, we can obtain the following formula:

[0093]

[0094] Furthermore, the state space equation of the multi-DG microgrid can be linearly transformed and simplified to obtain the following formula:

[0095]

[0096] Among them, z i is the state vector of the nonlinear disturbance observer; is the nonlinear disturbance u of the i-th distributed generation unit in the isolated microgrid at time t i The estimated value of i () is the state equation of the i-th distributed generation unit in the island microgrid at time t.

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

[0098]

[0099] Establish a false data injection attack signal observer, including:

[0100]

[0101] Where: x k , x k+1 are the state vectors at time k and k+1 respectively; y k is the output vector at time k; f() is the spatial state transfer function; h() is the observation state transfer 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, and both are Gaussian white noise; δ is the size of the false data injection attack; g k is the position matrix of false data injection attack at time k.

[0102] Since the distributed generation units in the microgrid are operated in parallel and the output impedance is inductive, the following distribution algorithm based on consistent secondary control is adopted:

[0103]

[0104] Where: m i is the active frequency droop characteristic coefficient; n i is the reactive voltage droop characteristic coefficient; P iis the active power output of each distributed power source after filtering; Ω i Especially 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 frequency; Q i is the reactive power output by each distributed power source after filtering; ε i Especially 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 frequency; a ij is the adjacency matrix element (1 if connected, otherwise 0); g i is the gain matrix G = diag{g 1 ,g 2 ,…,g N}; if the i-th distributed generation unit receives the reference value, then g i =1, otherwise g i =0;c i To control the gain.

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

[0106] According to past experience, setting c i The larger the value of , the faster the response speed, but the larger the transient oscillation. In order to cope with abnormal extreme events such as communication signal interruption, control command abnormality and sudden stop of unit inverter, a switching controller is designed here. It can adapt to and cope with extreme situations and 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 can be continuously measured to define the condition trigger. The switching mechanism can be used for the auxiliary controller, expressed as:

[0107]

[0108] Where: e fi is the tracking error of the frequency of the ith distributed generation unit; e pi Tracking error of active power of the i-th distributed generation unit; e Ei is the tracking error of the output voltage of the i-th distributed generation unit; e qi is the tracking error of the reactive power of the ith distributed generation unit; h f ,hp ,h E ,h q is a constant coefficient, whose setting directly affects the collaborative performance and requires a trade-off between response speed and transient oscillation; w s1 , w s2 , w s3 , w s4 is the control gain group.

[0109] In step S5, a switching-adaptive control gain group is established, and its configuration is as follows:

[0110]

[0111] Where: f tri is the preset trigger threshold of frequency; E tri is the preset trigger threshold of the output voltage; Δf iSTW and ΔE iSTW 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.

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

[0113] When the secondary controller fails, it will switch to a new secondary controller to restore the frequency and voltage to stability; Δf iADP and ΔE iADP Related to the auxiliary controller based on a linear control mechanism, it is used to restore the deviated frequency and voltage by controlling the gain group:

[0114]

[0115] Where: f tri2 is the preset trigger threshold of frequency; E tri2 is the preset trigger threshold of the output voltage; g f1 , g f2 , g f3 , g f4 are the control gain groups associated with the secondary frequency-voltage control; Δf iSTW , ΔE iSTW , Δf iADP , ΔE iADP Related to the auxiliary controller based on linear control mechanism, used to restore the deviated frequency / voltage by switching the control gain set, different Δf iSTWand ΔE iSTW The switching frequency and the corresponding output voltage quality will be improved.

[0116] In step S7, a switching-adaptive secondary control microgrid coordinated control strategy is established, including: detecting the frequency and voltage changes of the distributed generation units in each control cycle, and once the switchable condition is triggered, the switching controller switches to a suitable control system, and at the same time detects errors after switching, and performs frequency and voltage compensation through the adaptive controller, thereby achieving the purpose of the microgrid system resisting false data injection attacks and restoring the operating status.

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

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

[0119]

[0120] Where: e di (t) represents the estimated value of the i-th distributed generation unit in the island microgrid at time t and the actual nonlinear disturbance u i The deviation, for e di The transpose of (t);

[0121] Proving the convergence of the system involves:

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

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

[0124]

[0125] According to the above formula, we can prove that: when the nonlinear disturbance input u di (t),u fdi (t), the disturbance deviation e i (t) and its derivative tends to 0 and the disturbance estimation error e di (t) also tends to 0, realizing that the state quantity of the i-th distributed generation unit follows the reference value of the state quantity.

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

[0127] In this embodiment, the effect diagram of the switching-adaptive control method used in the present invention is as follows: Figure 4 , Figure 6 , Figure 8 , Fig.10 As shown; Figure 5 , Figure 7 , Fig. 9 , Fig.11 This is the effect diagram of using the traditional switching control method. For easy identification and comparison, the state waveform of DG4 is set as a dotted line. Figure 5 and Figure 6 They are respectively the active power diagrams of each inverter using the switching-adaptive control of the present invention and the active power diagrams of each inverter using the traditional switching control, Figure 5 Compared to Figure 6 The active power deviation of DG4 is about 6kw, which is nearly 40% smaller than that of the previous generation. Fig.10 and Fig.11 They are respectively the reactive power diagram of each inverter using the switching-adaptive control of the present invention and the reactive power diagram of each inverter using the traditional switching control, Fig.10 Compared to Fig.11 The peak deviation is about 1kvar, which is nearly 50% smaller than the error.

[0128] Regarding the system operation status, Figure 4 The frequency error is about 0.1Hz, while Figure 4 The frequency error of the detector is about 0.2 Hz. In contrast, the method of the present invention can reduce the error by nearly 50%. Figure 8 and Fig. 9 The following are the output voltage amplitude diagrams of the inverter using the switching-adaptive control of the present invention and the output voltage amplitude diagrams of the inverter using the traditional switching control. It can be seen that the output voltage of the inverter after the switching-adaptive control can still remain basically constant after being attacked by the network. Fig. 9 The output voltage fluctuation of the inverter using traditional switching control is large, about 0.5V. It can be seen that there is an obvious deviation between the state quantity under the traditional method and the rated value.

[0129] The above is only a preferred embodiment of the present invention, and does not limit the present invention in any form. Any technician familiar with the art can make many possible changes and modifications to the technical solution of the present invention by using the above disclosed methods and technical contents without departing from the scope of the technical solution of the present invention, or modify it into an equivalent embodiment of equivalent changes. Therefore, all equivalent changes made according to the shape, structure and principle of the present invention without departing from the content of the technical solution of the present invention should be included in the protection scope of the present invention.

Claims

1. A microgrid control method for resisting false data injection attacks, characterized in that: The following steps are involved: Step S1: Establish a microgrid model using distributed control to achieve power conversion; Step S2: Establishing the state space equation of the distributed control microgrid; Step S3: Design a false data injection attack signal observer; Step S4: designing a microgrid network security switching controller; Step S5: Establishing a switching-adaptive control gain group; Step S6: designing a distributed generation unit error adaptive controller; Step S7: designing a microgrid coordinated control strategy of switching-adaptive secondary control; Step S8: Establish the Lyapunov function of the closed-loop system model of the ith distributed generation unit of the island microgrid at time t and prove the system convergence.

2. A microgrid control method for resisting false data injection attacks as claimed in claim 1, characterized in that: In step S1, a microgrid model using distributed control is established, including: Establish the main circuit structure of the distributed control microgrid: distributed power sources, inverter circuits, filters, connecting lines, public buses, and local / public loads that are electrically connected in sequence; Establish the local control link of distributed microgrid: droop controller, power calculator, voltage and current dual loop, PWM generator; Firstly, the voltage and current at the filter port are collected, and the active power and reactive power output by the distributed generation unit are calculated by the power calculator. According to the output power, the voltage / frequency reference value is obtained through the droop controller. Then, the PWM reference modulation signal is generated through the voltage and current dual-loop control. Finally, the inverter circuit is controlled by the PWM generator to realize the power conversion.

3. A microgrid control method for resisting false data injection attacks as claimed in claim 2, characterized in that: In step S2, the state space equation of the distributed control microgrid is established, including: With the goal of voltage / frequency stability and power distribution of the microgrid, the state space variables are selected with the actual frequency, actual voltage effective value, actual active power output, and actual reactive power output of the i-th distributed generation unit as the observation quantity of the distributed generation unit agent, and the state space is established: Where: x i is the state vector of each distributed power model; y i is the output vector of each distributed power model; For x i The derivative with respect to time t; f i , k i They are respectively represented as the two coupling state matrices of the i-th distributed power model in the isolated microgrid at time t; D i It is represented as: the i-th distributed power model in the isolated microgrid at time t is composed of state variables x i The disturbance vector that causes system fluctuations; g i It is represented as the state matrix of the nonlinear disturbance of the i-th distributed power model in the isolated microgrid at time t; P i , Q i They represent the output active / reactive power of the i-th distributed power model in the isolated microgrid; γ di , γ qi is the component of the auxiliary variable of the current inner loop controller on the d-axis and q-axis; i Ldi 、i Lqi is the component of the filter inductor current on the d-axis and q-axis; v odi 、v oqi 、i odi 、i oqi are the components of the output voltage and current on the d-axis and q-axis respectively; h i It is represented as the state matrix of the output voltage of the i-th distributed power model in the isolated microgrid at time t; d i It is represented as the coefficient of the nonlinear disturbance of the i-th distributed generation model in the isolated microgrid at time t; u i It is represented as the input quantity of the nonlinear disturbance of the i-th distributed power model in the isolated microgrid at time t; ω com is the disturbance of the system frequency; v bdi 、v bqi are the voltage disturbances of the d-axis and q-axis respectively; And v bdi 、v bqi The expression is: γ N is the virtual resistance between nodes; i odi 、i oqi are the d-axis and q-axis currents output by each distributed power source in the isolated microgrid at time t; i load,di 、i load,qi are the d-axis and q-axis currents of each distributed power load in the isolated microgrid at time t; i line,d(i,j) 、i line,q(i,j) They are the d-axis and q-axis currents between each distributed power supply line in the isolated microgrid at time t.

4. A microgrid control method for resisting false data injection attacks as claimed in claim 3, characterized in that: In step S3, a false data injection attack signal observer is established, including: Where: x k , x k+1 are the state vectors at time k and k+1 respectively; y k is the output vector at time k; f() is the spatial state transfer function; h() is the observation state transfer 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, 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; When the distributed generation units in the microgrid are connected in parallel and the output impedance is inductive, the following distribution algorithm based on consistent secondary control is adopted: Where: 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 of each distributed power source after filtering; Ω i Especially 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 frequency; Q i is the reactive power output by each distributed power source after filtering; ε i Especially 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 frequency; a ij is the adjacency matrix element (1 if connected, otherwise 0); g i is the gain matrix G = diag{g1,g2,…,g N }; if the i-th distributed generation unit receives the reference value, then g i =1, otherwise g i =0;c i To control the gain.

5. A microgrid control method for resisting false data injection attacks as claimed in claim 4, characterized in that: In step S4, a microgrid network security switching controller is designed, including: Adapt and respond to extreme situations and minimize the impact of extreme events. Since the secondary control is to restore the deviated frequency and voltage to the nominal value, it allows continuous measurement of the inverter output port to define the condition trigger. The switching mechanism is used for the auxiliary controller, which is expressed as: Where: e fi is the tracking error of the frequency of the ith distributed generation unit; e pi Tracking error of active power of the i-th distributed generation unit; e Ei is the tracking error of the output voltage of the i-th distributed generation unit; e qi is the tracking error of the reactive power of the ith distributed generation unit; h f ,h p ,h E ,h q is a constant coefficient, whose setting directly affects the collaborative performance and requires a trade-off between response speed and transient oscillation; w s1 , w s2 , w s3 , w s4 is the control gain group.

6. A microgrid control method for resisting false data injection attacks as claimed in claim 5, characterized in that: In step S5, a switching-adaptive control gain group is established, including: Where: f tri is the preset trigger threshold of frequency; E tri is the preset trigger threshold of the output voltage; Δf iSTW and ΔE iSTW 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.

7. A microgrid control method for resisting false data injection attacks as claimed in claim 6, characterized in that: In step S6, a distributed generation unit error adaptive controller is designed, including: When the secondary controller fails, a new secondary controller will be switched to restore the frequency and voltage to stability; Δf iADP and ΔE iADP Related to the auxiliary controller based on a linear control mechanism, it is used to restore the deviated frequency and voltage by controlling the gain group: Where: f tri2 is the preset trigger threshold of frequency; E tri2 is the preset trigger threshold of the output voltage; g f1 , g f2 , g f3 , g f4 are the control gain groups associated with the secondary frequency-voltage control; Δf iSTW , ΔE iSTW , Δf iADP , ΔE iADP Related to the auxiliary controller based on linear control mechanism, used to restore the deviated frequency / voltage by switching the control gain set, different Δf iSTW and ΔE iSTW The switching frequency and the corresponding output voltage quality will be improved.

8. A microgrid control method for resisting false data injection attacks as claimed in claim 7, characterized in that: In step S7, a switching-adaptive secondary control microgrid coordinated control strategy is established, including: detecting the frequency and voltage changes of the distributed generation units in each control cycle, and once the switchable condition is triggered, the switching controller switches to a suitable control system, and at the same time detects the error after switching, and performs frequency and voltage compensation through the adaptive controller, so as to achieve the purpose of the microgrid system resisting false data injection attacks and recovering the operating status.

9. A microgrid control method for resisting false data injection attacks as claimed in claim 8, characterized in that: In step S8, the Lyapunov function of the closed-loop system model of the i-th distributed generation unit of the island microgrid at time t is established and the system convergence is proved, including: The Lyapunov function of the closed-loop system model of the i-th distributed generation unit of the island microgrid at time t is constructed as follows: Where: e di (t) represents the estimated value of the i-th distributed generation unit in the island microgrid at time t and the actual nonlinear disturbance u i The deviation, for e di The transpose of (t); Proving the convergence of the system involves: If the Lyapunov function satisfies, Vi(xi(t))>0, Then the equilibrium state of the system is asymptotically stable; The first-order time derivative of the Lyapunov function of the closed-loop system model of the i-th distributed generation unit of the isolated microgrid at time t is: According to the above formula, we can prove that: when the nonlinear disturbance input u di (t),u fdi (t), the disturbance deviation e i (t) and its derivative tends to 0 and the disturbance estimation error e di (t) also tends to 0, realizing that the state quantity of the i-th distributed generation unit follows the reference value of the state quantity.

Images