Frequency control method of power system containing electric vehicles based on fusion event triggering

Abstract

The present invention discloses a frequency control method for an electric power system containing electric vehicles based on fusion event triggering. The steps include: step 1, based on the dynamic characteristics of the electric power system containing electric vehicles, establish its state space model; step 2, considering the random fluctuations caused by noise or disturbance in the measurement data in actual working conditions, establish an event trigger control mechanism based on historical data fusion to reduce false triggering caused by random fluctuations of signals; step 3, use Simpson's law and linear matrix inequality technology to obtain a fusion event trigger controller, and control the electric power system containing electric vehicles. Compared with the traditional event trigger mechanism based on instantaneous measurement data, this patent provides a fusion event trigger mechanism with the ability to suppress random fluctuations, effectively reducing the false triggering of control signals caused by data fluctuations, saving limited network resources, and having certain engineering application value.

Description

Technical Field

[0001] The present invention relates to a frequency control method of an electric power system containing electric vehicles based on fusion event triggering, in particular to an event triggered control method for an electric power system containing electric vehicles. Background Art

[0002] In recent years, networked power systems have become the main direction of power system development due to their high flexibility and intelligence. At the same time, with the vigorous development of the new energy vehicle industry and cyber-physical systems, the access of large-scale electric vehicles will inevitably lead to grid frequency fluctuations and affect the quality of power. Considering the load frequency control problem of networked power systems containing electric vehicles can improve the stability of power system frequency and has important theoretical and engineering value. However, the introduction of communication networks also brings corresponding problems and risks. As the scale of the system continues to expand, massive devices compete for limited communication network resources, resulting in a sharp increase in channel burden and network congestion. In order to overcome this difficulty, researchers adopted an event-triggered control strategy to save limited network resources and achieved a series of results.

[0003] However, existing research works all assume that the measurement signal is not affected by any interference, and the event triggering mechanism is mostly based on instantaneous sampling data. However, in actual engineering environments, factors such as random interference, noise, and data mutations can cause random fluctuations in the measurement signal. The existing event triggering mechanism based on instantaneous measurement data is sensitive to random fluctuations and is prone to false triggering, which in turn leads to waste of communication resources and degradation of control performance. In order to solve the above problems, it is necessary to design a new event triggering control mechanism to suppress false triggering caused by random fluctuations in the measurement signal, improve network resource utilization, and improve the stability of the power system frequency. Summary of the invention

[0004] Purpose of the invention: Based on the above analysis, in order to effectively solve the problem of load frequency control of a power system containing electric vehicles with random fluctuations in measurement signals, the present invention designs a load frequency control method based on fusion event triggering.

[0005] The specific technical solution of the present invention is as follows: A method for controlling the load frequency of a power system containing electric vehicles based on fusion event triggering, comprising the following steps:

[0006] Based on the dynamic characteristics of the power system containing electric vehicles, its state space model is established;

[0007] Design a fusion event-triggered control mechanism based on historical data;

[0008] Solve the load frequency event trigger controller that stabilizes the system frequency and controls the power system including electric vehicles.

[0009] Technical solution: A load frequency control method for a power system containing electric vehicles based on fusion event triggering, which is implemented in the following steps:

[0010] The load frequency control method of the power system containing electric vehicles based on the fusion event trigger mechanism according to claim 1 is characterized in that the established state space model is as follows:

[0011]

[0012] In the formula, Indicates the system status. represents the system output, u(t) is the control input of the system, d(t) corresponds to the disturbance input of the system, and A, B, F, C are the system parameter matrices in the following form.

[0013] 3. The load frequency control method of the power system containing electric vehicles based on the fusion event trigger mechanism according to claim 2 is characterized in that the fusion event trigger mechanism based on historical data is as follows:

[0014]

[0015] Where: t k , t k+1 Respectively represent the current trigger time and the next trigger time, Ω, σ∈(0,1) represent the positive definite weight matrix and the trigger threshold parameter, Indicates the output of the current moment that integrates the historical measurement data. Indicates the output of the previous triggering moment that integrates the historical measurement data, e(t) = y * (t)-y * (t k ) represents the error between the two.

[0016] Given a proportional-integral event-triggered controller based on output feedback:

[0017]

[0018] Where K is the control system that needs to be designed to satisfy the given H ∞ Controller gain in performance.

[0019] By using Simpson's law to approximate the integral term in the above controller and substituting the controller into the state space expression in (1), the closed-loop event-triggered system can be expressed as follows:

[0020]

[0021] 4. The load frequency control method of the power system containing electric vehicles based on the fusion event trigger mechanism according to claim 3 is characterized in that the derivative of the Lyapunov function of the closed-loop control system is obtained and required to be negative definite, and H ∞ Control theory derives the linear matrix inequality conditions corresponding to the controller solution, including:

[0022] 1) Choose the Lyapunov-Krasovskii functional as shown below:

[0023] V(t)=V1(t)+V2(t)+V3(t), (5)

[0024] in:

[0025]

[0026] P, S1, S2, R1, R2 are symmetric positive definite matrices.

[0027] 2) Based on the previous step, calculate the derivative of the Lyapunov-Krasovskii functional and require it to be negative definite:

[0028]

[0029] 3) Jensen inequality is used to process the integral term, and the event trigger condition and H are combined ∞ Performance constraints require that the following matrix inequality form holds to ensure that the above formula holds:

[0030]

[0031] in:

[0032]

[0033] 4) Based on Fisher's lemma, we can further obtain the following matrix inequality:

[0034]

[0035] in:

[0036]

[0037]

[0038] 5) The quadratic term GBKC is decoupled by using the left-right multiplication technique and the Schur complement technique, and the following linear matrix inequality can be obtained:

[0039]

[0040] Among them: α>0, v>0,

[0041]

[0042] 6) Through the mincx solver in the LMI toolbox of MATLAB, the system can be solved to meet the given H ∞ Performance of output feedback controller:

[0043] K=YX -1 .

[0044] The above method for obtaining linear matrix inequality conditions starts from the Lyapunov stability theorem, uses the Simpson criterion to process the integral term that integrates historical data, introduces a new variable matrix with the help of Fisher's lemma, removes the coupling between the Lyapunov variable matrix and the control matrix, and further gives a convex optimization method for the design of static output feedback event-triggered controller based on the left-right multiplication technique and the Schur complement technique. Compared with the traditional inequality scaling method, this method removes the coupling relationship between the Lyapunov variable matrix and the control matrix, overcomes the error caused by scaling, and effectively reduces the conservatism of the controller design.

[0045] Beneficial effects of the present invention: Compared with the traditional event trigger mechanism based on instantaneous sampling data, the method of the present invention takes into account the random fluctuation phenomenon of measurement signals existing in actual engineering environments, and proposes a new event trigger mechanism based on historical data fusion, which effectively reduces false triggering caused by random fluctuations of measurement signals, improves network resource utilization, and improves the stability of power system frequency, and has certain engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a flow chart of a method according to an embodiment of the present invention;

[0047] Figure 2 The system frequency response curve of the embodiment using the method proposed by the present invention compared with the traditional method;

[0048] Figure 3 The triggering time and interval of the embodiment using the method proposed by the present invention are compared with the traditional method. DETAILED DESCRIPTION

[0049] The present invention is further explained below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. After reading the present invention, various equivalent forms of modifications to the present invention by those skilled in the art all fall within the scope defined by the claims attached to this application.

[0050] like Figure 1 As shown, a load frequency control method of a power system containing electric vehicles based on fusion event triggering comprises the following steps:

[0051] Step 1: Based on the dynamic characteristics of the power system containing electric vehicles, establish its state space model, specifically:

[0052] (1) The state space model is as follows:

[0053]

[0054] In the formula, Indicates the system status. represents the system output, u(t) is the control input of the system, d(t) corresponds to the disturbance input of the system, A, B, F, C are the system parameter matrices in the following form,

[0055]

[0056] The physical meaning of each parameter in the above formula is shown in the following table:

[0057] Table 1 Physical meaning of power system parameters including electric vehicles

[0058]

[0059] Step 2: Design a fusion event trigger control mechanism based on historical data to reduce false triggering of control signals. The specific steps are as follows:

[0060] 1) Design a fusion event trigger mechanism based on historical data, as follows:

[0061]

[0062] Where: t k , t k+1 Respectively represent the current trigger time and the next trigger time, Ω, σ∈(0,1) represent the positive definite weight matrix and the trigger threshold parameter, Indicates the output of the current moment that integrates the historical measurement data. Indicates the output of the previous triggering moment that integrates the historical measurement data, e(t) = y * (t)-y * (t k ) represents the error between the two. T (t)Ωe(t)≤σy *T (t)Ωy * (t), the fusion data is not triggered at the current moment, and the controller input remains unchanged; when e T (t)Ωe(t)>σy *T (t)Ωy * At (t), the current moment fusion data is triggered and the controller input is updated.

[0063] 2) Give a proportional-integral event-triggered controller based on output feedback

[0064]

[0065] Where K is the control system that needs to be designed to satisfy the given H ∞ Controller gain in performance.

[0066] 3) Using Simpson's law, the above controller can be approximately written as

[0067]

[0068] 4) Substituting the above equation into the state space expression in (1), the closed-loop event trigger system can be expressed as follows:

[0069]

[0070] Step 3: Solve the load frequency event trigger controller that stabilizes the system frequency and controls the power system containing electric vehicles. The specific steps are as follows:

[0071] 1) Construct a positive definite Lyapunov-Krasovskii functional:

[0072] V(t)=V1(t)+V2(t)+V3(t).

[0073] 2) Calculate the derivative of the Lyapunov-Krasovskii functional and ask:

[0074]

[0075] 3) Use Jensen inequality to deal with the integral term, and combine the event trigger condition and H ∞ Performance constraints require that the following matrix inequality form holds to ensure that the above formula holds:

[0076]

[0077] in:

[0078]

[0079] (7) Based on Fisher’s lemma, we can further obtain the following matrix inequality:

[0080]

[0081] in:

[0082]

[0083] 4) The left-right multiplication technique and Schur complement technique are used to decouple the quadratic term PBKC, and the following linear matrix inequality can be obtained:

[0084]

[0085] Among them: α>0, v>0,

[0086]

[0087] 5) Through the mincx solver in the LMI toolbox of MATLAB, the system can be solved to meet the given H ∞ Performance of output feedback controller:

[0088] K=YX -1 .

[0089] In step 2 of the present invention, the phenomenon of random fluctuations of measurement signals existing in actual engineering environments is taken into consideration, and a fusion event trigger mechanism based on historical data is proposed. Compared with the traditional event trigger mechanism based on instantaneous measurement data, this method effectively reduces the false triggering caused by random fluctuations of measurement signals, saves network bandwidth, and improves network resource utilization. In addition, in step 3 of the present invention, the Simpson criterion is used to process the integral term of the fusion of historical data, and a new variable matrix is ​​introduced with the help of Fisher's lemma to remove the coupling between the Lyapunov variable matrix and the control matrix, and a convex optimization method for the design of a static output feedback event trigger controller is given. Compared with the traditional inequality scaling method, this method removes the coupling relationship between the Lyapunov variable matrix and the control matrix, overcomes the error caused by scaling, and effectively reduces the conservatism of the controller design.

[0090] An embodiment of the present invention is described below:

[0091] Consider the power system model containing electric vehicles in system (1), where the parameters are selected as shown in the following table:

[0092] Table 2 Parameters of power system including electric vehicles

[0093]

[0094] Select the following parameters σ=0.05, λ=0.05, solve the linear matrix inequality in step (9), and get the proportional-integral controller gain and trigger matrix based on output feedback as follows:

[0095]

[0096] When simulating the system, the simulation step size is selected as 0.005s, and the system disturbance d(t) = 0.1a(t)e -1t, a(t) is a random variable that satisfies uniform distribution, and |a(t)|<5. Figure 1 Flowchart of the algorithm used in the embodiment. Figure 2 The figure is a comparison of the system frequency response curves when the method proposed in the present invention is used and the traditional method, wherein curve a represents the system frequency response curve obtained by adopting the fusion event trigger control mechanism proposed in the present invention, and curve b represents the system frequency response curve obtained by adopting the traditional event trigger control mechanism. Figure 3 The figure shows the comparison of event triggering time and interval when the method proposed in the present invention is used and the traditional method is used, wherein curve a represents the triggering time and interval obtained by adopting the fusion event triggering control mechanism proposed in the present invention, and curve b represents the triggering time and interval obtained by adopting the traditional event triggering control mechanism. Figure 2 and Figure 3 Note: Under the two event trigger control mechanisms, the system frequency response curves are almost the same, but the fusion event trigger mechanism proposed in the present invention reduces the number of triggers by 24.8% compared with the traditional trigger mechanism, which can effectively save more network bandwidth and communication resources.

Claims

1. A frequency control method for an electric vehicle-containing power system based on fusion event triggering, characterized in that: The following steps are included: Step 1: Based on the dynamic characteristics of the power system containing electric vehicles, establish its state space model, including: In the formula, Indicates the system status. represents the system output, u(t) is the control input of the system, d(t) corresponds to the disturbance input of the system, f(t) is the system frequency, P t (t) is the turbine output power, P g (t) is the speed regulating valve position, P e (t) is the electric vehicle power, ACE(t) is the area control error, and A, B, F, C are system parameter matrices in the following form: Where: T g is the time constant of the speed regulating valve, T t is the turbine time constant, T e is the electric vehicle time constant, K e is the electric vehicle gain, α g is the turbine participation factor, β is the frequency offset constant, R f is the droop coefficient, D is the generator damping constant, M is the generator time constant, ρ e is the droop characteristic constant of electric vehicles, ɑ e is the electric vehicle participation factor; Step 2: In order to reduce false triggering of control signals, a fusion event trigger mechanism based on historical data is designed, including: Where: t k , t k+1 Respectively represent the current trigger time and the next trigger time, Ω, σ∈(0,1) represent the positive definite weight matrix and the trigger threshold parameter, Indicates the output of the current moment that integrates the historical measurement data. Indicates the output of the previous triggering moment that integrates the historical measurement data, e(t) = y * (t)-y * (t k ) represents the error between the two; Step 3: Find the load frequency event trigger controller that stabilizes the system frequency and controls the power system containing electric vehicles, including: 1) Give a proportional-integral event-triggered controller based on output feedback: Where K is the control system that needs to be designed to satisfy the given H ∞ controller gain in performance; 2) Using Simpson's law to approximate the integral term in the above controller, and substituting the controller into the state space expression in (1), the closed-loop event trigger system can be expressed as follows: 3) Select the Lyapunov-Krasovskii functional as shown below: V(t)=V1(t)+V2(t)+V3(t), (5) in: P, S1, S2, R1, R2 are symmetric positive definite matrices; 4) Based on the previous step, calculate the derivative of the Lyapunov-Krasovskii functional and require it to be negative definite: 5) Use Jensen inequality to deal with the integral term, and combine the event trigger condition and H ∞ Performance constraints require that the following matrix inequality form holds to ensure that the above formula holds: in: 6) Based on Finsler's lemma, we can further obtain the following matrix inequality: in: 7) The quadratic term PBKC is decoupled by using the left-right multiplication technique and the Schur complement technique, and the following linear matrix inequality can be obtained: Among them: ɑ>0, v>0, 8) Through the mincx solver in MATLAB's LMI toolbox, we can find the solution that satisfies the given H ∞ Performance of the output feedback controller K = YX -1 , and frequency control of power systems containing electric vehicles.

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