Intelligent power grid dispatching method based on non-periodic intermittent control under attack

Abstract

The invention belongs to the field of intelligent power grid energy-saving environment-friendly economic dispatching, and particularly relates to an intelligent power grid dispatching method based on non-periodic intermittent control under attack. The method comprises the following steps: firstly, establishing an intelligent power grid economic dispatching model, initializing related parameters, designing a non-periodic intermittent fixed time distributed consistency algorithm, updating power increment cost and power output power based on the algorithm, judging whether an upper limit of convergence time of the algorithm is reached or not, and if yes, updating the power increment cost and the power output power; if the convergence time upper limit of the algorithm is reached, introducing an intermediate variable, and setting an initial value for the intermediate variable; and secondly, designing a fixed-time intermediate variable consistency algorithm, updating the intermediate variable based on the algorithm, updating the power increment cost, processing the power increment cost, updating the power output power, finally judging whether the upper limit of the convergence time of the algorithm is reached or not, and outputting related parameters if the upper limit of the convergence time of the algorithm is reached. The method is completely distributed, and economic dispatching of the intelligent power grid is realized under attack.

Description

Technical Field

[0001] The present invention relates to the field of energy - saving, environmental - protection and economic dispatching of smart grids, and in particular to a smart grid dispatching method based on non - periodic intermittent control under attacks. Background Art

[0002] With the development of power systems and the increasing growth of grid loads, smart grids have become an important research direction in modern power systems. Through the deep integration of information and communication technologies with power systems, smart grids can achieve efficient energy distribution, reliable power supply, and effective utilization of renewable energy. However, during the operation of smart grids, due to their complex network structures and large amounts of information interaction, they are vulnerable to various external attacks and interferences, especially Denial of Service (DoS) attacks. DoS attacks disrupt normal communication links, affecting the real - time transmission of system information, thus posing a serious threat to the security and stability of smart grids.

[0003] In traditional power grid economic dispatching models, it is usually assumed that information transmission is reliable and real - time. However, in a non - periodic interference environment under DoS attacks, the uncertainty of communication will have a significant impact on the economy and dispatching performance of the system. To address this problem, many methods based on robust control and optimization algorithms have been proposed in the academic community to improve the robustness and recovery ability of smart grids in an attacked environment. However, these methods still have certain limitations when dealing with complex attack patterns, such as slow convergence speed, high computational complexity, and the inability to fully utilize network topology information.

[0004] In response to the above problems, researchers have gradually shifted their research focus to nonlinear optimization methods based on fixed - time control. Fixed - time control methods can achieve global convergence of the system within a fixed time range, regardless of the initial state. This method is particularly suitable for scenarios in smart grids with time - varying characteristics and multi - objective optimization requirements. By combining fixed - time control and distributed optimization algorithms, precise control of the power output of generator sets and effective optimization of system economy can be achieved under DoS attacks. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a smart grid dispatching method based on non - periodic intermittent control under attacks, which can perform economic dispatching on smart grids.

[0006] The present invention is implemented as follows: A smart grid dispatching method based on non - periodic intermittent control under attacks, comprising the following steps:

[0007] Step 1: Establish an economic dispatch model for the smart grid; determine the adjacency matrix based on the communication topology of the smart grid, and calculate the Laplacian matrix based on the adjacency matrix; initialize relevant parameters;

[0008] Step 2: Design a non-periodic intermittent fixed-time distributed consensus algorithm;

[0009] Step 3: Update the incremental power cost and power output based on the non-periodic intermittent fixed-time distributed consensus algorithm;

[0010] Step 4: Determine whether the convergence time upper limit of the non-periodic intermittent fixed-time distributed consensus algorithm is reached; if the convergence time upper limit of the non-periodic intermittent fixed-time distributed consensus algorithm is not reached, return to Step 3; if the convergence time upper limit of the non-periodic intermittent fixed-time distributed consensus algorithm is reached, enter Step 5;

[0011] Step 5: Introduce intermediate variables and set the initial values of the intermediate variables;

[0012] Step 6: Design a fixed-time intermediate variable consensus algorithm;

[0013] Step 7: Update the intermediate variables based on the fixed-time intermediate variable consensus algorithm; update the incremental power cost; process the incremental power cost and update the power output;

[0014] Step 8: Determine whether the convergence time upper limit of the fixed-time intermediate variable consensus algorithm is reached; if the convergence time upper limit of the fixed-time intermediate variable consensus algorithm is not reached, return to Step 7; if the convergence time upper limit of the fixed-time intermediate variable consensus algorithm is reached, output the incremental power cost and power output.

[0015] Furthermore, the specific content of Step 1 is as follows:

[0016] Establish an economic dispatch model for the smart grid, specifically:

[0017]

[0018] p i_min ≤p i (t)≤p i_max

[0019] where i = 1, 2,..., n; n is the number of generators in the smart grid; is the objective function of the economic dispatch problem, C i (p i (t)) is the power cost function of the i-th generator at time t and p i (t) is the power output of the i-th generator at time t, αpi > 0, β pi > 0 and γ pi > 0 is the power cost coefficient of the i-th generator; is the power supply-demand balance constraint condition; p i_min ≤ p i (t) ≤ p i_max is the power output power limit constraint condition; p d is the total power demand; p i_min is the minimum power output of the i-th generator; p i_max is the maximum power output of the i-th generator;

[0020] Determine the adjacency matrix A based on the communication topology of the smart grid, specifically:

[0021]

[0022] where a ij represents the element in the i-th row and j-th column of the adjacency matrix A, j = 1, 2,..., n; N i represents the set of generators communicating with the i-th generator;

[0023] Calculate the Laplacian matrix L based on the adjacency matrix, specifically:

[0024]

[0025] where l ij represents the element in the i-th row and j-th column of the Laplacian matrix L;

[0026] Initialize the relevant parameters, specifically:

[0027] Set the initial value of the power output of the i-th generator to p i (0), and satisfy The initial value of the incremental cost of the power of the i-th generator is λ pi (0) = 2α pi p i (0) + β pi .

[0028] Furthermore, the specific content of step 2 is:

[0029] Design a non-periodic intermittent fixed-time distributed consensus algorithm, specifically:

[0030]

[0031] where λ pi (t) is the incremental cost of the power of the i-th generator at time t, λ pj (t) is the incremental cost of the power of the j-th generator at time t; Denoted as λ pi (t), the derivative of with respect to time t; u(t) is the controller function; sig h (·) = |·| h sign(·), h is a positive constant, sign(·) is the sign function; ρ attack Indicates whether an attack occurs; ρ attack = 0 indicates that no attack occurs, and the time is t k to s k ; ρ attack = 1 indicates that an attack occurs, and the time is s k to t k+1 ; k is a non - negative integer, describing the number of attacks; C 1 、C 2 、C 3 All satisfy being greater than 0; m, n, p, q are all positive odd numbers, and satisfy m > n and p < q; σ ∈ (0, 1).

[0032] Furthermore, the non - periodic intermittent fixed - time distributed consensus algorithm in the second step can converge within a fixed time, specifically:

[0033] When holds, The upper bound of the convergence time is where Denoted as the maximum value among all generator power incremental costs at time T 0 ; Denoted as the minimum value among all generator power incremental costs at time T 0 ; When holds, The upper bound of the convergence time is where Denoted as the maximum value among all generator power incremental costs at time T 1 ; Denoted as the minimum value among all generator power incremental costs at time T 1 ; η is denoted as sup denotes the supremum.

[0034] Furthermore, the fifth step is specifically:

[0035] Introduce intermediate variables XX i (t), YY i (t), and set the initial values of the intermediate variables as follows:

[0036]

[0037] Among them, XX i (0) is an intermediate variable XX i (t) initial value; YY i (0) is an intermediate variable YY i (t) initial value; If the power output p i (t) of the i-th generator at time t exceeds its maximum power output p i_max , let If the power output p i (t) of the i-th generator at time t is lower than its minimum power output p i_min , let

[0038] Furthermore, the specific content of step six is as follows:

[0039] Design a fixed-time intermediate variable consistency algorithm, specifically:

[0040]

[0041] Among them, and respectively represent the derivatives of the intermediate variables XX i (t) and YY i (t) with respect to time t; This algorithm can converge within a fixed time. When , and the upper limits of the convergence time are both When , and the upper limits of the convergence time are both λ 2 (L) is the second smallest eigenvalue of the Laplacian matrix L.

[0042] Furthermore, the specific content of step seven is as follows:

[0043] Update the intermediate variables based on the fixed-time intermediate variable consistency algorithm; Update the incremental power cost. The update of the incremental power cost is as follows:

[0044]

[0045] Among them, represents the convergence value of the incremental power cost of the generator under the non-periodic intermittent fixed-time distributed consistency algorithm;

[0046] Process the incremental power cost, as follows:

[0047]

[0048] Among them, λ i_min and λ i_max respectively represent the minimum and maximum values of the incremental power cost of the i-th generator. Specifically, λ i_min = 2α pi p i_min + β pi and λ i_max = 2α pi p i_max + β pi ;

[0049] Update the power output as follows:

[0050]

[0051] The present invention provides an intelligent power grid scheduling method based on non-periodic intermittent control under attacks. Compared with the prior art, the beneficial effects of the present invention are as follows:

[0052] 1. The intelligent power grid scheduling method based on non-periodic intermittent control under attacks proposed by the present invention is completely distributed, and is more flexible and scalable than the centralized intelligent power grid economic scheduling method.

[0053] 2. The present invention adopts a non-periodic intermittent fixed-time distributed consensus algorithm, which can achieve the consistency of the incremental power cost and the incremental heat cost within a fixed time. Compared with the traditional iterative distributed method, the convergence speed is significantly improved, and the disadvantage that the convergence time depends on the number of iterations is avoided.

[0054] 3. When dealing with DoS attacks, the present invention effectively dynamically adjusts the control strategy by judging whether an attack occurs, thereby reducing the impact of communication link blockage on system performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 is the IEEE14-node standard power network of the present invention;

[0056] Figure 2 is the communication topology diagram of the generator of the present invention;

[0057] Figure 3 is the graph of the incremental power cost of the generator of the present invention changing with time;

[0058] Figure 4 is the graph of the power output of the generator of the present invention changing with time;

[0059] Figure 5 is the graph of the total power output of the present invention changing with time;

[0060] Figure 6 is the graph of ρ attack changing with time of the present invention. Detailed implementation manners

[0061] The following details the implementation manners of the present invention. Examples of the implementation manners are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The implementation manners described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention and should not be construed as limiting the present invention.

[0062] Example 1:

[0063] An intelligent power grid scheduling method based on non-periodic intermittent control under attack provided in this example specifically includes the following steps:

[0064] Step 1: Establish an economic scheduling model for the intelligent power grid; determine the adjacency matrix according to the communication topology of the intelligent power grid, and calculate the Laplacian matrix based on the adjacency matrix; initialize relevant parameters;

[0065] Step 2: Design a non-periodic intermittent fixed-time distributed consensus algorithm;

[0066] Step 3: Update the incremental power cost and power output power based on the non-periodic intermittent fixed-time distributed consensus algorithm;

[0067] Step 4: Determine whether the convergence time upper limit of the non-periodic intermittent fixed-time distributed consensus algorithm is reached; if the convergence time upper limit of the non-periodic intermittent fixed-time distributed consensus algorithm is not reached, return to Step 3; if the convergence time upper limit of the non-periodic intermittent fixed-time distributed consensus algorithm is reached, enter Step 5;

[0068] Step 5: Introduce an intermediate variable and set the initial value of the intermediate variable;

[0069] Step 6: Design a fixed-time intermediate variable consensus algorithm;

[0070] Step 7: Update the intermediate variable based on the fixed-time intermediate variable consensus algorithm; update the incremental power cost; process the incremental power cost and update the power output power;

[0071] Step 8: Determine whether the convergence time upper limit of the fixed-time intermediate variable consensus algorithm is reached; if the convergence time upper limit of the fixed-time intermediate variable consensus algorithm is not reached, return to Step 7; if the convergence time upper limit of the fixed-time intermediate variable consensus algorithm is reached, output the incremental power cost and the power output power.

[0072] In this example, Step 1 is specifically as follows:

[0073] Establish an economic scheduling model for the intelligent power grid, specifically as follows:

[0074]

[0075] p i_min ≤ p i (t) ≤ p i_max

[0076] where \(i = 1, 2, \cdots, n\); \(n\) is the number of generators in the smart grid; is the objective function of the economic dispatch problem, \(C\) i (p i (t)) is the power cost function of the \(i\)-th generator at time \(t\) and p i (t) is the power output of the \(i\)-th generator at time \(t\), \(\alpha\) pi > 0, \(\beta\) pi > 0 and \(\gamma\) pi > 0 are the power cost coefficients of the \(i\)-th generator; is the power supply - demand balance constraint condition; \(p\) i_min ≤ p i (t) ≤ p i_max is the power output limit constraint condition; \(p\) d is the total power demand; \(p\) i_min is the minimum power output of the \(i\)-th generator; \(p\) i_max is the maximum power output of the \(i\)-th generator;

[0077] Determine the adjacency matrix \(A\) according to the communication topology of the smart grid, specifically:

[0078]

[0079] where \(a\) ij represents the element in the \(i\)-th row and \(j\)-th column of the adjacency matrix \(A\), \(j = 1, 2, \cdots, n\); \(N\) i represents the set of generators communicating with the \(i\)-th generator;

[0080] Calculate the Laplacian matrix \(L\) based on the adjacency matrix, specifically:

[0081]

[0082] where \(l\) ij represents the element in the \(i\)-th row and \(j\)-th column of the Laplacian matrix \(L\);

[0083] Initialize the relevant parameters, specifically:

[0084] Set the initial value of the power output of the \(i\)-th generator to \(p\) i (0), and satisfy The initial value of the incremental cost of the \(i\)-th generator is \(\lambda\) pi(0) = 2α pi p i (0) + β pi 。

[0085] In this embodiment, the specific content of step two is as follows:

[0086] Design a non-periodic intermittent fixed-time distributed consensus algorithm, specifically:

[0087]

[0088] where λ pi (t) is the incremental power cost of the i-th generator at time t, and λ pj (t) is the incremental power cost of the j-th generator at time t; is denoted as the derivative of λ pi (t) with respect to time t; u(t) is the controller function; sig h (·) = |·| h sign(·), h is a positive constant, and sign(·) is the sign function; ρ attack indicates whether an attack occurs; ρ attack = 0 indicates that no attack occurs, and the time is from t k to s k ; ρ attack = 1 indicates that an attack occurs, and the time is from s k to t k+1 ; k is a non-negative integer describing the number of attacks; C 1 、C 2 、C 3 all satisfy being greater than 0; m, n, p, q are all positive odd numbers, and satisfy m > n and p < q; σ ∈ (0, 1).

[0089] In this embodiment, the non-periodic intermittent fixed-time distributed consensus algorithm in step two can converge within a fixed time, specifically:

[0090] When holds, the upper bound of the convergence time is where is denoted as the maximum value among the incremental power costs of all generators at time T 0 , is denoted as the minimum value among the incremental power costs of all generators at time T 0 ; when holds, the upper bound of the convergence time is where Denoted as the maximum value among the incremental power costs of all generators at time T 1 and denoted as the minimum value among the incremental power costs of all generators at time T Denoted as the maximum value among the incremental power costs of all generators at time T 1 and denoted as the minimum value among the incremental power costs of all generators at time T; η is denoted as sup is denoted as the supremum.

[0091] In this embodiment, step five is specifically as follows:

[0092] Introduce intermediate variables XX i (t) and YY i (t), and set the initial values of the intermediate variables as follows:

[0093]

[0094] where XX i (0) is the initial value of the intermediate variable XX i (t); YY i (0) is the initial value of the intermediate variable YY i (t); if the power output p i (t) of the i-th generator at time t exceeds its maximum power output p i_max , let if the power output p i (t) of the i-th generator at time t is lower than its minimum power output p i_min , let

[0095] In this embodiment, step six is specifically as follows:

[0096] Design a fixed-time intermediate variable consistency algorithm, specifically:

[0097]

[0098]

[0099] where and respectively represent the derivatives of the intermediate variables XX i (t) and YY i (t) with respect to time t; this algorithm can converge within a fixed time. When , and the upper bounds of the convergence times are both When , and the upper bounds of the convergence times are both λ 2(L) is the second smallest eigenvalue of the Laplacian matrix L.

[0100] In this embodiment, step seven is specifically as follows:

[0101] Update the intermediate variable based on the fixed-time intermediate variable consensus algorithm; update the incremental cost of electricity as follows:

[0102]

[0103] Where represents the convergence value of the incremental cost of electricity of the generator under the non-periodic intermittent fixed-time distributed consensus algorithm;

[0104] Process the incremental cost of electricity as follows:

[0105]

[0106] Where λ i_min and λ i_max respectively represent the minimum and maximum values of the incremental cost of electricity of the i-th generator, specifically λ i_min = 2α pi p i_min + β pi and λ i_max = 2α pi p i_max + β pi ;

[0107] Update the power output as follows:

[0108]

[0109] Embodiment 2:

[0110] Embodiment 2 uses the proposed intelligent grid scheduling method based on non-periodic intermittent control under attack to perform numerical simulation on the IEEE 14-node standard power network. There are 5 generators in total. Figure 1 is the IEEE 14-node standard power network. Figure 2 is the communication topology diagram of the generator of the present invention.

[0111] Table 1 shows the electricity cost coefficients α pi , β pi , the minimum power output p i_min of the i-th generator and the maximum power output p i_max of the i-th generator; the total power demand The initial value of the generator power output p 1 (0) = 30 MW, p 2 (0) = 15 MW, p3 p(0) = 20 MW 4 p(0) = 40 MW 5 p(0) = 45 MW; m = 9, n = 7, p = 3, q = 5, σ = 2 / 5, C 1 、C 2 、C 3 All take the value of 2; The time of attack is: [0.3 s, 1.5 s) ∪ [2 s, 2.5 s) ∪ [0.3 s, 1.5 s) ∪ [4 s, 5 s) ∪ [7 s, 7.5 s) ∪ [8.2 s, 9 s) ∪ [10.2 s, 11.3 s); The upper limit of the convergence time is 12.92 s; and The upper limits of the convergence time are both 1.37 s.

[0112] According to the communication topology of the generator, the adjacency matrix A is determined as:

[0113]

[0114] Table 1

[0115] Generator i <![CDATA[α pi > <![CDATA[β pi > <![CDATA[p i_max > <![CDATA[p i_min > 1 0.080 2.0 60 0 2 0.070 3.5 75 0 3 0.058 2.5 30 0 4 0.065 4.0 60 0 5 0.060 3.0 46 0

[0116] Finally, based on the given data, the effectiveness of the present invention is verified through numerical simulation.

[0117] Figure 3 is the graph of the incremental cost of generator power varying with time for the present invention; Figure 3 In it, the optimal value of the incremental cost of generator power changes from 6.96 $ / MW to 7.27 $ / MW, where λ 3 (t) exceeds the maximum value of the incremental cost of generator power, changing from 6.96 $ / MW to 5.98 $ / MW, resulting in failure to converge to a consistent value.

[0118] Figure 4 is the graph of the generator power output varying with time for the present invention; Figure 4 In it, the optimal value of the generator power output is p 1 = 32.94 MW, p 2 = 26.93 MW, p 3 = 30 MW, p 4 = 25.15 MW, p 5 = 35.58 MW.

[0119] Figure 5 is the graph of the total power output varying with time for the present invention; Figure 6 is ρ for the present invention attack varying with time graph.

[0120] It should be noted that the above are only preferred examples of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A smart grid dispatching method based on non-periodic intermittent control under attack, characterized in that: The following steps are involved: Step 1: Establish a smart grid economic dispatch model; determine the adjacency matrix based on the smart grid communication topology, and calculate the Laplace matrix based on the adjacency matrix; initialize relevant parameters; Step 2: Design a non-periodic intermittent fixed-time distributed consensus algorithm; Step 3: Update the electricity incremental cost and electricity output power based on a non-periodic intermittent fixed-time distributed consensus algorithm; Step 4: Determine whether the upper limit of the convergence time of the non-periodic intermittent fixed-time distributed consistency algorithm has been reached; if the upper limit of the convergence time of the non-periodic intermittent fixed-time distributed consistency algorithm has not been reached, return to step 3; if the upper limit of the convergence time of the non-periodic intermittent fixed-time distributed consistency algorithm has been reached, proceed to step 5; Step 5: Introduce intermediate variables and set their initial values; Step 6: Design a fixed-time intermediate variable consistency algorithm; Step 7: Update the intermediate variables based on the fixed time intermediate variable consistency algorithm; update the incremental power cost; process the incremental power cost and update the power output power; Step 8: Determine whether the upper limit of the convergence time of the fixed-time intermediate variable consistency algorithm has been reached; If the upper limit of the convergence time of the fixed-time intermediate variable consistency algorithm is not reached, return to step seven; if the upper limit of the convergence time of the fixed-time intermediate variable consistency algorithm is reached, output the incremental power cost and the power output power.

2. The smart grid dispatching method based on non-periodic intermittent control under attack according to claim 1 is characterized in that: The step 1 specifically includes the following steps: Establish a smart grid economic dispatch model, specifically: p i_min ≤p i (t)≤p i_max Where, i = 1, 2, ..., n; n is the number of generators in the smart grid; is the objective function of the economic dispatch problem, C i (p i (t)) is the electricity cost function of the i-th generator at time t and p i (t) is the power output of the i-th generator at time t, α pi >0,β pi >0 and γ pi >0 is the electricity cost coefficient of the i-th generator; is the power supply and demand balance constraint; p i_min ≤p i (t)≤p i_max is the power output power limit constraint; p d is the total power demand; p i_min is the minimum output power of the i-th generator; p i_max is the maximum output power of the i-th generator; The adjacency matrix A is determined according to the smart grid communication topology, specifically: Among them, a ij represents the element in the i-th row and j-th column of the adjacency matrix A, where j = 1, 2, ..., n; N i represents the set of generators communicating with the i-th generator; The Laplace matrix L is calculated based on the adjacency matrix, specifically: Among them, l ij represents the i-th row and j-th column element of the Laplace matrix L; Initialize related parameters, specifically: Set the initial value of the power output of the i-th generator to p i (0), and satisfies The initial value of the incremental electricity cost of the i-th generator is λ pi (0) = 2α pi p i (0)+β pi .

3. The smart grid dispatching method based on non-periodic intermittent control under attack according to claim 2 is characterized in that: The step 2 specifically includes the following steps: Design a non-periodic intermittent fixed-time distributed consensus algorithm, specifically: Among them, λ pi (t) is the incremental electricity cost of the i-th generator at time t, λ pj (t) is the incremental electricity cost of the jth generator at time t; Denoted as λ pi (t) is the derivative of time t; u(t) is the controller function; sig h (·)=|·| h sign(·), h is a positive constant, sign(·) is the sign function; ρ attack Indicates whether an attack occurs; ρ attack =0 means no attack occurs, and the time is t k to k ρ attack =1 means an attack occurs, and its time is s k to k+1 ; k is a non-negative integer describing the number of attacks; C1, C2, and C3 are all greater than 0; m, n, p, and q are all positive odd numbers, and m>n and p <q;σ∈(0,1)。 4. The smart grid dispatching method based on non-periodic intermittent control under attack according to claim 3 is characterized in that: The non-periodic intermittent fixed-time distributed consensus algorithm in step 2 can converge within a fixed time, specifically: when hour, The upper limit of convergence time is in It is expressed as the maximum value of the incremental electricity cost of all generators at time T0, It is expressed as the minimum value of the incremental power cost of all generators at time T0; when hour, The upper limit of convergence time is in It is expressed as the maximum value of the incremental electricity cost of all generators at time T1, It is expressed as the minimum value of the incremental power cost of all generators at time T1; η is expressed as sup stands for supremum.

5. The smart grid dispatching method based on non-periodic intermittent control under attack according to claim 4 is characterized in that: The step five specifically includes the following steps: Introduce intermediate variable XX i (t), YY i (t), and set the initial value of the intermediate variable as follows: Among them, XX i (0) is the intermediate variable XX i (t) Initial value; YY i (0) is the intermediate variable YY i (t) initial value; if the power output of the i-th generator at time t is p i (t) exceeds the maximum output power p of its generator i_max ,make If the power output of the i-th generator at time t is p i (t) is lower than the minimum output power p of its generator i_min ,make 6. The smart grid dispatching method based on non-periodic intermittent control under attack according to claim 5 is characterized in that: The step six specifically includes the following steps: Design a fixed-time intermediate variable consistency algorithm, specifically: in, and Represents the intermediate variable XX i (t) and YY i (t) is the derivative of time t; the algorithm can converge in a fixed time when hour, and The upper limit of convergence time is when hour, and The upper limit of convergence time is λ2(L) is the second smallest eigenvalue of the Laplace matrix L.

7. The smart grid dispatching method based on non-periodic intermittent control under attack according to claim 6 is characterized in that: The step seven specifically includes the following steps: Update the intermediate variables based on the fixed time intermediate variable consistency algorithm; Update the incremental power cost Update the incremental power cost as shown below: in, It is expressed as the convergence value of the incremental cost of the generator power under the non-periodic intermittent fixed-time distributed consensus algorithm; The incremental cost of electricity is processed as follows: Among them, λ i_min and λ i_max They represent the minimum and maximum values ​​of the incremental cost of electricity of the i-th generator, specifically λ i_min =2α pi p i_min +β pi and λ i_max =2α pi p i_max +β pi ; Update the power output as follows:

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