Time-delay island micro-grid load frequency control system and method based on adaptive event triggering mechanism

Abstract

The invention discloses a time-delay island micro-grid load frequency control system and method based on an adaptive event trigger mechanism, and relates to the technical field of micro-grid load frequency control. The invention provides a novel event triggering mechanism based on a self-adaptive threshold value, so as to solve the problem that the control performance is not ideal due to the fact that a micro-grid load frequency control system is limited by bandwidth. The method mainly comprises the following steps: step 1, establishing a state space model according to parameters of each distributed power supply and an energy storage system of the island microgrid; 2, introducing a self-adaptive event triggering mechanism considering communication delay into micro-grid load frequency control; step 3, based on a Lyapunov functional method, deducing a stability criterion of the time-delay island micro-grid; and step 4, solving a trigger matrix omega and a minimum performance index gamma min. According to the invention, a self-adaptive event triggering mechanism is introduced into the island micro-grid load frequency control system, so that the loss of communication resources of a communication system and the influence of communication delay are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of microgrid load frequency control, and in particular relates to a time-delay island microgrid load frequency control system and method based on an adaptive event triggering mechanism. Background Art

[0002] Microgrid has independent functions of power generation, transmission, transformation and distribution. It is a small power system that integrates distributed power sources, energy storage devices, loads and protection devices. Microgrid has two operating modes: grid-connected operation and island operation. However, the intermittent and unstable power output of renewable energy may cause frequency fluctuation or instability of microgrid, which brings great challenges to the load frequency control (LFC) of microgrid, especially island microgrid. In recent years, how to design effective solutions to solve the communication problems in load frequency control has become a hot topic.

[0003] With the rapid development of computer technology and communication technology, shared networks are widely used in load frequency control, but this will inevitably cause problems such as time lag and bandwidth blocking. In recent years, in order to reduce the loss of communication resources, event triggering mechanisms have gradually been introduced into load frequency control schemes. However, the interference caused by weather changes is unpredictable, resulting in continuous frequency fluctuations and frequent data transmission. The static threshold cannot be adaptively adjusted with the change of the system's frequency response deviation, and some unnecessary data is still transmitted. In this case, it is difficult for the static event triggering scheme to ensure good working performance when the number of communications is relatively small. The adaptive event triggering mechanism has stronger adaptability to the system state and dynamic characteristics of the disturbance of the controlled object, and can also intelligently adjust the control parameters according to the system state and interference. On this basis, the system works optimally according to predetermined standards. The introduction of the adaptive event triggering mechanism can further reduce the consumption of communication resources, while having better frequency response performance. In order to maintain a balance between the dynamic performance of the system and saving communication resources, we try to combine the adaptive event triggering mechanism with the control scheme to design a more effective controller. Summary of the invention

[0004] In order to solve the technical problems existing in the above-mentioned background technology, the present invention provides a time-delay island microgrid load frequency control system and method based on an adaptive event trigger mechanism, which has a reasonable design and greatly saves communication bandwidth.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] A time-delayed island microgrid load frequency control system based on adaptive event triggering mechanism Figure 3As shown, it includes a sensor, an event generator, a controller, a zero-order holder and an actuator;

[0007] Sensor: samples data from the system and transmits the sampled data to the event generator;

[0008] Event generator: receives the signal sent by the sensor and determines whether the latest measurement output y(t) meets the trigger condition. If it does, it sends the measurement output y(t) to the controller to generate a new control signal. If it does not, it determines the next measurement output y(t).

[0009] Controller: receives the signal sent by the event generator and generates a new control signal, and transmits it to the zero-order holder;

[0010] Zero-order holder: receives the discrete control signal generated by the controller, converts it into a continuous signal, and transmits it to the actuator;

[0011] Actuator: receives the continuous signal from the zero-order holder and executes the control command;

[0012] The island microgrid is sampled by sensors to obtain the system's measurement output y(t), which is then sent to the event generator to determine whether the latest measurement output y(t) meets the trigger condition. If so, the measurement output y(t) is sent to the controller. If not, the next measurement output y(t) is judged, and then the discrete signal is converted into a continuous signal through a zero-order holder. The actuator executes the control command to restore the system frequency.

[0013] The present invention also provides a time-delay island microgrid load frequency control method based on an adaptive event trigger mechanism, which can significantly save the consumption of communication resources while maintaining the dynamic performance of the system, and mainly includes the following steps:

[0014] S1: Establish the state space model of the closed-loop system based on the structural parameters of the island microgrid;

[0015] S2: Introduce the adaptive event triggering mechanism considering communication delay into microgrid load frequency control;

[0016] S3: Based on the Lyapunov functional method, the stability criterion of the time-delay islanded microgrid is derived and the Zeno phenomenon is eliminated;

[0017] S4: Use MATLAB / LMI toolbox to solve the trigger matrix Ω and the minimum performance index γ min ;

[0018] Preferably, the step S1 establishes an island microgrid closed-loop state space model including a controller based on the island microgrid system parameters, and the specific steps are:

[0019] S11: Define the state variable x(t), the measured output y(t), the target vector z(t), the system disturbance ω1(t) and the measured deviation ω2(t):

[0020]

[0021] ΔP wind (t), ΔP s (t) and ΔP d (t) represent the wind speed change of wind turbine, solar radiation intensity change and load power change, Δf represents the system frequency deviation, ΔP DEG , ΔP MTG , ΔP FC , ΔP V , ΔP WTG , ΔP FESS , ΔP BESS Respectively represent the power output changes of diesel generator, fuel cell, photovoltaic cell, wind turbine, flywheel energy storage system and battery energy storage system. In order to conveniently represent the system state, the intermediate variable ΔP is introduced DEG1 , ΔP MTG1 , ΔP FC1 , ΔP FC2 and ΔP V1 , Δf(t) is the system frequency deviation, z(t) is the target vector;

[0022] S12: Set the PI controller strategy and use the system frequency deviation Δf(t) as the input signal of the controller:

[0023] u(t)=-K P Δf(t)-K I ∫Δf(t)dt (1)

[0024] Among them, K P and K I are the proportional coefficient and integral coefficient of the system, and u(t) is the input signal of the PI controller;

[0025] S13: Define the augmented vector

[0026] S14: Establish a closed-loop state space model of the island microgrid:

[0027] The dynamic model of the load frequency control system of the island microgrid is as follows: Figure 2 As shown, combined Figure 1 And controller (1) can get the closed-loop state space model of the island microgrid including the controller as follows:

[0028]

[0029] in,

[0030]

[0031] C2=[1 0 0 0 0 0 0 0 0 0 0 0 0],

[0032]

[0033] Where H represents the mechanical inertia of the island microgrid, R1 and R2 are constants, and T WTG 、T PV Represent the dynamic parameters of wind turbine and photovoltaic system respectively, T IC 、T t 、T FC 、T IN Both represent the time constant of the converter, T DEG 、T MTG 、T FC 、T FESS 、T BESS They are the response times of diesel generator, micro turbine generator, fuel cell, flywheel energy storage system and battery energy storage system respectively;

[0034] Preferably, the step S2 introduces an adaptive event triggering mechanism to establish a time-delay island microgrid load frequency control system model including a communication scheme and a controller, and the specific steps are:

[0035] S21: Define a delay function τ(t)∈[τ m ,τ M ], where: τ = τ M -τ m (τ m ≥0), τ M and τ m Respectively represent the upper and lower limits of communication delay, t k represents the kth triggering time, k represents the kth triggering, h is defined as the sampling period, t k +ih represents the i-th sampling time after the k-th trigger. Assuming the trigger time s k =t k +τ(t k ),τ(t k )∈[τ m ,τ M ];

[0036] S22: The measured output y(t) can be expressed as:

[0037] y(t)=C1x(t k )+Dω2(t k ),t∈[s k,s k+1 ) (3)

[0038] S23: The error function can be expressed as:

[0039] e(t)=y(t k )-y(t k +ih)=y(t k )-y(t-τ(t)) (4)

[0040] S24: The control signal of the PI controller is:

[0041] u(t)=u(t k +τ k )=Ky(t k ),t∈[s k ,s k+1 ) (5)

[0042] S25: The state space model of the microgrid load frequency control system can be rewritten as:

[0043]

[0044] S26: Construct event trigger conditions:

[0045] An adaptive event trigger mechanism is introduced to reduce unnecessary data transmission. After the sensor samples the controlled device, it determines whether the transmission conditions are met. The sampling signal is sent to the controller only when the event trigger condition is met. Otherwise, the next sampling signal is not sent and judged. The adaptive event trigger condition is (7):

[0046]

[0047] In which, the trigger matrix Ω>0, and the dynamic threshold σ(t) satisfies the differential equation (8):

[0048]

[0049] Wherein, μ>0 and ρ>0 are given constants, and 0<1 / ρ<σ(t)<1;

[0050] If μ = 0, that is σ(t) becomes a constant, and the adaptive event triggering mechanism will be reduced to a static event triggering mechanism.

[0051] If the closed-loop system (6) satisfies the following two conditions under the event triggering condition (7), the system is asymptotically stable:

[0052] (3) When ω1(t) = 0, ω2(t) = 0, the system is asymptotically stable;

[0053] (4) For non-zero If there exists a positive constant γ>0, such that under zero initial conditions:

[0054]

[0055] Preferably, the step S3 is based on the Lyapunov functional method to derive the stability criterion of the time-delay island microgrid and eliminate the Zeno phenomenon, and the specific steps are:

[0056] S31: Select the augmented Lyapunov-Krasovskii functional:

[0057] Select the following Lyapunov functional and perform inequality scaling on it;

[0058]

[0059] V1(t)=x T (t)Px(t) (10a)

[0060]

[0061]

[0062]

[0063]

[0064] Where P>0, Q1>0, Q2>0, Q3>0, R>0 and S>0 are all positive definite matrices with appropriate dimensions, τ=τ M -τ m .

[0065] Taking the derivative of V(t) we can get:

[0066]

[0067]

[0068]

[0069]

[0070]

[0071]

[0072] S32: Solve the asymptotic stability criterion of the system:

[0073] Based on the closed-loop system (6), the following equation holds:

[0074]

[0075] Where M,N∈R n×n And ε is a given constant.

[0076] The integral term can be reduced to:

[0077]

[0078] in, Matrix R>0.

[0079] The integral term can be simplified as:

[0080]

[0081] Among them, S>0,ζ T (t) = [x T (t-τ m ),x T (t-τ(t)),x T (t-τ M )].

[0082] When t∈[s k ,s k+1 ), according to the adaptive event triggering condition (7):

[0083] σ(t)y T (t-τ(t))Ωy(t-τ(t))-e T (t)Ωe(t)≥0,t∈[s k ,s k+1 ) (15)

[0084] Further we can get:

[0085]

[0086] Assume that there exists a small enough positive number δ such that:

[0087]

[0088] Inequality (17) can be transformed into matrix form:

[0089] η T (t)Ψη(t)≤0 (18)

[0090] when When, because It is a continuous function, integrating both sides of equation (19) from 0 to +∞:

[0091]

[0092] When ω1(t)≡0 and ω2(t)≡0, it can be seen from (17):

[0093]

[0094] Therefore, in ensuring While the performance index γ is constant, the closed-loop system (6) is asymptotically stable.

[0095] S33: Island microgrid load frequency control system based on linear matrix inequality (6) Criteria:

[0096] According to step S31-step S32, the following stability criterion is obtained:

[0097] For a given sampling period h>0, constant ε>0, 0<1 / ρ<σ(t)<1, μ>0, For the suppression level γ>0 and the control matrix K, there exist matrices P>0, Q1>0, Q2>0, Q3>0, R>0, S>0, the trigger matrix Ω>0 and matrices M, N. If the following matrix inequality holds, the load frequency control system (6) of the island microgrid is asymptotically stable.

[0098]

[0099] In the formula,

[0100]

[0101]

[0102] Ψ 33 =-Q1+Q2+Q3-S-4R,Ψ 12 =P-M+εA T N T ,τ=τ M -τ m ,

[0103]

[0104] Φ 14 =col{ML,εML,0,0,0},Φ 15 =col{6R,0,6R,0,0},Φ 22 =D T ΩD-γ 2 I,

[0105]

[0106] Where I represents the identity matrix, * represents the transpose of the matrix in terms of its position, and all of the above matrices have the appropriate dimensions.

[0107] The stability criterion of formula (23) is derived on the basis of h>0. Another case is discussed below;

[0108] S34: Analysis of Zeno's phenomenon:

[0109] When h=0, the load frequency control system (6) of the isolated microgrid may experience the Zeno phenomenon. In order to avoid the Zeno phenomenon in the isolated microgrid, it is necessary to ensure that the previous signal is received by the controller before the next signal can be updated.

[0110] Combining the adaptive event triggering criterion (7) and σ(t)>0, we can obtain:

[0111] ||e(s k+1 )||>σ(t)||y(t)||,t∈[s k ,s k+1 ) (twenty two)

[0112] When ω2(t)≡0, then at t∈[s k ,s k+1 ) the derivative of e(t) is as follows:

[0113]

[0114] Among them, p1=||C1BKC1||1||x(t-τ(t))||1+||C1A||1||x(t)||1+||C1A||1||ω1(t)||1, p2=||C1BKC1||1.

[0115] From the definition of e(t), we know that e(s k )=0, combining (5) and the comparison inequality, solving equation (23) yields:

[0116]

[0117] Therefore, there exists a positive number The minimum execution time T satisfies:

[0118]

[0119] This means ensuring At the same time as the performance index γ, the island microgrid load frequency control system does not have the Zeno phenomenon when h = 0, and the proof is complete. The system based on continuous event triggering may have Zeno behavior. In order to prove that the system does not have the Zeno phenomenon, the present invention has carried out the above proof.

[0120] Preferably, the step S4 solves the trigger matrix Ω and the minimum performance index γ min ;

[0121] S41: Find feasible solution:

[0122] The feasp solver in MATLAB / LMI toolbox is used to solve a set of feasible solutions for the linear matrix inequality (21) as a constraint.

[0123] S42: Solving for the minimum performance index γ min :

[0124] When ω1(t)=0,ω2(t)=0, (20) shows that the closed-loop system (5) is asymptotically stable; if there is a non-zero disturbance The closed-loop system is asymptotically stable only if it meets certain system performance index γ. The smaller the value of performance index γ is, the better it is when the system stability is met. The minimum performance index γ is obtained by searching in the interval [γ1,γ2] using the least squares method. min . Set the precision to γ ac , γ1 and γ2 are the lower and upper limits of the pre-set performance indicators, respectively. The specific steps of the algorithm are as follows: Figure 4 As shown in the flow chart.

[0125] Compared with the prior art, the present invention has the following beneficial effects:

[0126] The present invention provides a time-delayed isolated island microgrid load frequency control system and method based on an adaptive event trigger mechanism, in order to solve the problem that the performance of the isolated island microgrid load frequency control system is limited by the communication bandwidth. Different from the static event trigger mechanism using a fixed trigger threshold, the present invention focuses on adaptive thresholds that are adaptively adjusted according to the real-time state of the system, which can further reduce unnecessary signal transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0127] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0128] Figure 1 It is the island microgrid connection line model of the present invention;

[0129] Figure 2 It is the dynamic response model of load frequency control of isolated island microgrid of the present invention;

[0130] Figure 3 It is a flow chart of the adaptive event-triggered control scheme of the time-delayed island microgrid of the present invention;

[0131] Figure 4The minimum system performance index γ is solved by the present invention min Flowchart of

[0132] Figure 5 It is the frequency deviation change of the present invention solving scenario 1;

[0133] Figure 6 The present invention solves the frequency deviation change of scenario 2;

[0134] Figure 7 This is the frequency deviation change of scenario 3 solved by the present invention. DETAILED DESCRIPTION

[0135] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0136] It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0137] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0138] Terminology explanation:

[0139] Sensor: samples data from the system and transmits the sampled data to the event generator;

[0140] Event generator: receives the signal sent by the sensor and determines whether the latest measurement output y(t) meets the trigger condition. If it does, it sends the measurement output y(t) to the controller to generate a new control signal. If it does not, it determines the next measurement output y(t).

[0141] Controller: receives the signal sent by the event generator and generates a new control signal, and transmits it to the zero-order holder;

[0142] Zero-order holder: receives the discrete control signal generated by the controller, converts it into a continuous signal, and transmits it to the actuator;

[0143] Actuator: receives the continuous signal from the zero-order holder and executes the control command;

[0144] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0145] Embodiment 1:

[0146] As attached Figure 2As shown, the embodiment of the present invention provides a time-delayed isolated island microgrid load frequency control system and method based on an adaptive event trigger mechanism to solve the problem of limited communication bandwidth of the isolated island microgrid. The specific implementation steps of the method are as follows:

[0147] Step S1: Based on the system parameters of the isolated microgrid, a closed-loop state space model of the isolated microgrid including a controller is established. The specific steps are as follows:

[0148] The island microgrid is sampled by sensors to obtain the system's measurement output y(t), which is then sent to the event generator to determine whether the latest measurement output y(t) meets the trigger condition. If so, the measurement output y(t) is sent to the controller. If not, the next measurement output y(t) is judged, and then the discrete signal is converted into a continuous signal through a zero-order holder. The actuator executes the control command to restore the system frequency.

[0149] S11: Define the state variable x(t), the measured output y(t), the target vector z(t), the system disturbance ω1(t) and the measured deviation ω2(t):

[0150]

[0151] ΔP wind (t), ΔP s (t) and ΔP d (t) represent the wind speed change of wind turbine, solar radiation intensity change and load power change respectively, and Δf represents the system frequency deviation. ΔP DEG , ΔP MTG , ΔP FC , ΔP V , ΔP WTG , ΔP FESS , ΔP BESS Respectively represent the power output changes of diesel generator, fuel cell, photovoltaic cell, wind turbine, flywheel energy storage system and battery energy storage system. In order to conveniently represent the system state, the intermediate variable ΔP is introduced. DEG1 , ΔP MTG1 , ΔP FC1 , ΔP FC2 and ΔP V1 , Δf(t) is the system frequency deviation, z(t) is the target vector;

[0152] S12: Set the PI controller strategy and use the system frequency deviation Δf(t) as the input signal of the controller:

[0153] u(t)=-K P Δf(t)-K I ∫Δf(t)dt (1)

[0154] Among them, K P and K I are the proportional coefficient and integral coefficient of the system, and u(t) is the input signal of the PI controller;

[0155] S13: Define the augmented vector

[0156] S14: Establish a closed-loop state space model of the island microgrid:

[0157] The dynamic model of the load frequency control system of the island microgrid is as follows: Figure 2 As shown, combined Figure 1 And controller (1) can get the closed-loop state space model of the island microgrid including the controller as follows:

[0158]

[0159] in,

[0160]

[0161] Where H represents the mechanical inertia of the island microgrid, R1 and R2 are constants, and T WTG 、T PV Represent the dynamic parameters of wind turbine and photovoltaic system respectively, T IC 、T t 、T FC 、T IN Both represent the time constant of the converter, T DEG 、T MTG 、T FC 、T FESS 、T BESS They are the response times of diesel generator, micro turbine generator, fuel cell, flywheel energy storage system and battery energy storage system respectively;

[0162] Step S2: Introduce an adaptive event triggering mechanism and establish a time-delay island microgrid load frequency control model including a communication scheme and a controller. The adaptive event triggering mechanism considering communication delay is as follows:

[0163] S21: Define a delay function τ(t)∈[τ m ,τ M ], where: τ = τ M -τ m (τ m ≥0), τ M and τ m Respectively represent the upper and lower limits of communication delay, t k represents the kth triggering time, k represents the kth triggering, h is defined as the sampling period, t k+ih represents the i-th sampling time after the k-th trigger. Assuming the trigger time s k =t k +τ(t k ),τ(t k )∈[τ m ,τ M ];

[0164] S22: The measured output y(t) can be expressed as:

[0165] y(t)=C1x(t k )+Dω2(t k ),t∈[s k ,s k+1 ) (3)

[0166] S23: The error function can be expressed as:

[0167] e(t)=y(t k )-y(t k +ih)=y(t k )-y(t-τ(t)) (4)

[0168] S24: The control signal of the PI controller is:

[0169] u(t)=u(t k +τ k )=Ky(t k ),t∈[s k ,s k+1 ) (5)

[0170] S25: The state space model of the microgrid load frequency control system can be rewritten as:

[0171]

[0172] S26: Construct event trigger conditions:

[0173] An adaptive event trigger mechanism is introduced to reduce unnecessary data transmission. After the sensor samples the controlled device, it determines whether the transmission conditions are met. The sampling signal is sent to the controller only when the event trigger conditions are met. Otherwise, the next sampling signal is not sent and judged. The adaptive event trigger condition is (7):

[0174]

[0175] In which, the trigger matrix Ω>0, and the dynamic threshold σ(t) satisfies the differential equation (8):

[0176]

[0177] Wherein, μ>0 and ρ>0 are given constants, and 0<1 / ρ<σ(t)<1.

[0178] Step S3: Based on the Lyapunov functional method, the stability criterion of the time-delay island microgrid is derived and the Zeno phenomenon is eliminated. The specific steps are as follows:

[0179] This part takes the load frequency control system of the time-delay island microgrid as the research object, constructs the augmented Lyapunov-Krasovskii functional, and derives the stability criterion of the closed-loop system. If the closed-loop system (6) satisfies the following two conditions under the event trigger condition (7), the system is asymptotically stable:

[0180] (5) When ω1(t) = 0, ω2(t) = 0, the system is asymptotically stable;

[0181] (6) For non-zero If there exists a positive constant γ>0, such that under zero initial conditions:

[0182]

[0183] Here are the two lemmas used in the derivation:

[0184] Lemma 1: For a given positive definite matrix R>0, constant α>0, for a continuously differentiable function ω(s) on [a,b], the following inequality holds:

[0185]

[0186] in,

[0187] Lemma 2: For a given positive definite matrix S>0,τ1<τ(t)<τ2, there exists a continuously differentiable function satisfy:

[0188]

[0189] Among them, ψ T (t) = [x T (t-τ1),x T (t-τ(t)),x T (t-τ2)].

[0190] S31: Select the augmented Lyapunov-Krasovskii functional:

[0191] Select the following Lyapunov functional and perform inequality scaling on it;

[0192]

[0193] V1(t)=x T (t)Px(t)(12a)

[0194]

[0195]

[0196]

[0197]

[0198] Where P>0, Q1>0, Q2>0, Q3>0, R>0 and S>0 are all positive definite matrices with appropriate dimensions, τ=τ M -τ m .

[0199] Taking the derivative of V(t) we can get:

[0200]

[0201]

[0202]

[0203]

[0204]

[0205]

[0206] S32: Solve the asymptotic stability criterion of the system:

[0207] Based on the closed-loop system (6), the following equation holds:

[0208]

[0209] Where M,N∈R n×n And ε is a given constant.

[0210] Combined with Lemma 1, the integral term in (13c) can be reduced to:

[0211]

[0212] in, Matrix R>0.

[0213] Based on Lemma 2, the integral term in (13d) can be simplified to:

[0214]

[0215] Among them, S>0,ζ T (t) = [x T (t-τ m ),x T (t-τ(t)),x T (t-τ M )].

[0216] When t∈[s k ,s k+1 ), according to the adaptive event triggering condition (7):

[0217] σ(t)y T (t-τ(t))Ωy(t-τ(t))-e T (t)Ωe(t)≥0,t∈[s k ,s k+1 ) (17)

[0218] Further we can get:

[0219]

[0220] Assume that there exists a small enough positive number δ such that:

[0221]

[0222] Inequality (19) can be transformed into matrix form:

[0223] η T (t)Ψη(t)≤0 (20)

[0224] when When, because It is a continuous function, integrating both sides of equation (19) from 0 to +∞:

[0225]

[0226] When ω1(t)≡0 and ω2(t)≡0, it can be seen from (19):

[0227]

[0228] Therefore, in ensuring While the performance index γ is constant, the closed-loop system (6) is asymptotically stable.

[0229] S33: Island microgrid load frequency control system based on linear matrix inequality (6) Criteria:

[0230] According to step S31-step S32, the following stability criterion is obtained:

[0231] For a given sampling period h>0, constant ε>0, 0<1 / ρ<σ(t)<1, μ>0, For the suppression level γ>0 and the control matrix K, there exist matrices P>0, Q1>0, Q2>0, Q3>0, R>0, S>0, the trigger matrix Ω>0 and matrices M, N. If the following matrix inequality holds, the load frequency control system (6) of the island microgrid is asymptotically stable.

[0232]

[0233] In the formula,

[0234]

[0235]

[0236] Ψ 33 =-Q1+Q2+Q3-S-4R,Ψ 12 =P-M+εA T N T ,τ=τ M -τ m ,

[0237]

[0238] Φ 14 =col{ML,εML,0,0,0},Φ 15 =col{6R,0,6R,0,0},Φ 22 =D T ΩD-γ 2 I,

[0239]

[0240] Where I represents the identity matrix, * represents the transpose of the matrix in terms of its position, and all of the above matrices have the appropriate dimensions.

[0241] The stability criterion of formula (23) is derived on the basis of h>0. Another case is discussed below;

[0242] S34: Analysis of Zeno's phenomenon:

[0243] When h=0, the load frequency control system (6) of the isolated microgrid may experience the Zeno phenomenon. In order to avoid the Zeno phenomenon in the isolated microgrid, it is necessary to ensure that the previous signal is received by the controller before the next signal can be updated.

[0244] Combining the adaptive event triggering criterion (7) and σ(t)>0, we can obtain:

[0245] ||e(sk+1 )||>σ(t)||y(t)||,t∈[s k ,s k+1 ) (twenty four)

[0246] When ω2(t)≡0, then at t∈[s k ,s k+1 ) the derivative of e(t) is as follows:

[0247]

[0248] Among them, p1=||C1BKC1||1||x(t-τ(t))||1+||C1A||1||x(t)||1+||C1A||1||ω1(t)||1, p2=||C1BKC1||1.

[0249] From the definition of e(t), we know that e(s k )=0, combining (5) and the comparison inequality, solving equation (25) yields:

[0250]

[0251] Therefore, there exists a positive number The minimum execution time T satisfies:

[0252]

[0253] This means ensuring At the same time as the performance index γ, the island microgrid load frequency control system does not have the Zeno phenomenon when h = 0, and the proof is complete. The system based on continuous event triggering may have Zeno behavior. In order to prove that the system does not have the Zeno phenomenon, the present invention has carried out the above proof.

[0254] Step S4: Solve the trigger matrix Ω and the minimum performance index γ min ;

[0255] S41: Find feasible solution:

[0256] The feasp solver in MATLAB / LMI toolbox is used to solve a set of feasible solutions for the linear matrix inequality (21) as a constraint.

[0257] S42: Solving for the minimum performance index γ min :

[0258] When ω1(t)=0,ω2(t)=0, (20) shows that the closed-loop system (5) is asymptotically stable; if there is a non-zero disturbance The closed-loop system is asymptotically stable only if it meets certain system performance index γ. The smaller the value of performance index γ is, the better it is when the system stability is met. The minimum performance index γ is obtained by searching in the interval [γ1,γ2] using the least squares method. min . Set the precision to γ ac , γ1 and γ2 are the lower and upper limits of the pre-set performance indicators, respectively. The specific steps of the algorithm are as follows: Figure 4 As shown in the flow chart.

[0259] Embodiment 2:

[0260] The embodiment of the present invention provides a time-delayed isolated island microgrid load frequency control system and method based on adaptive event triggering, which reduces the data transmission volume of the system. A specific embodiment of the present invention is as follows:

[0261] For the isolated microgrid load frequency control system model, in this embodiment, T DEG =0.8,T MTG =0.8,T FC =0.5,T PV =1.8,T WTG =1.5,T FESS =0.1,T BESS =0.1,T t =0.1,T IC =0.04,T IN =0.05, R1=0.05, R2=0.05, H=5.0, a=1.0, μ=0.05, ρ=20.0, ε=0.1.

[0262] Define the initial value of the event trigger threshold σ(0) = 0.06, the sampling period h = 0.5s, and the lower limit of the time lag τ m =0.5s, upper limit of time delay τ m =1.0s. The controller gain is set to: K P1 =1.2, K I1 =2.0, K P2 =2.0 and K I2 =3.0.

[0263] According to the above given parameters, according to step S41, the following trigger matrix can be obtained by solving the linear matrix inequality (23) using the MATLAB / LMI toolbox:

[0264]

[0265] According to the above given parameters, according to step 4.2, the system minimum performance index γ is obtained min =1.0>0, which indicates that the system is asymptotically stable.

[0266] Finally, the effectiveness of the proposed scheme is verified through simulations in various scenarios. Set the system initial state x(0) = [0.02, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] T . The other parameters are the same as mentioned above. The system load change ΔP d In the case of multiple steps, the change is as follows Figure 5 shown.

[0267] Scenario 1: Simulate the situation where the measurement noise ω2(t) undergoes multiple steps. In this scenario, the external disturbance ω2(t) is not considered, and only the situation where the measurement noise ω2(t) undergoes multiple steps is considered, where ω a (t)Select:

[0268]

[0269] Figure 5 It shows the frequency deviation change of the isolated island microgrid using the adaptive event triggered control (AET-LFC) mechanism of the present invention in scenario 1. The results show that the larger the measurement noise ω2(t), the larger the amplitude of the frequency change and the slower the frequency recovery speed.

[0270] Scenario 2: Simulate the situation where the renewable energy disturbance and the load have multiple steps at the same time. In this scenario, the measurement deviation ω2(t) is not considered, and the external disturbance ω1(t) has multiple steps, such as Figure 6 (a) shown. Figure 6 (b) shows the frequency deviation change of the isolated island microgrid in scenario 2 using the adaptive event trigger control mechanism, periodic sampling mechanism, static event trigger control mechanism and continuous event trigger control mechanism of the present invention, with the trigger times being 47, 200, 52 and 211 respectively. The results show that the adaptive event trigger control mechanism of the present invention has the smallest fluctuation overshoot and the fastest recovery speed, and the continuous event trigger control mechanism has the best frequency response performance. The results show that the adaptive event trigger control mechanism of the present invention has the smallest trigger times, saving network bandwidth resources, and at the same time, the frequency has a faster recovery speed.

[0271] Scenario 3: Simulate the situation where the renewable energy interference and load change randomly at the same time. In this scenario, the measurement deviation ω2(t) is not considered, and the external disturbance ω1(t) changes randomly, such as Figure 7 (a) shown. Figure 7(b) shows the frequency deviation change of the isolated island microgrid using the adaptive event-triggered control mechanism (AET-LFC), periodic sampling (PS-LFC), static event-triggered control (SET-LFC) and continuous event-triggered control (CET-LFC) of the present invention in scenario 3, with the triggering times being 86, 200, 93 and 389 respectively. The adaptive event-triggered control mechanism of the present invention has the least triggering times and the smallest response overshoot.

[0272] Figure 5-7 The comparison between scene 1, scene 2 and scene 3 under the adaptive event trigger control mechanism, static event trigger control mechanism and continuous event trigger control mechanism of the present invention shows that the adaptive event trigger control mechanism of the present invention has the least number of trigger times.

[0273] The embodiment of the present invention firstly takes communication delay into consideration when modeling the load frequency control system of the isolated island microgrid, and designs a time-delayed load frequency control of the isolated island microgrid based on an adaptive event triggering mechanism. Under the premise of avoiding the Zeno phenomenon and ensuring the frequency control performance of the system, it effectively saves the network bandwidth resources of the system and reduces the burden on the communication system.

[0274] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any changes, modifications, additions or substitutions made using the contents of the present invention description and drawings are also within the patent protection scope of the present invention.

Claims

1. A time-delay island microgrid load frequency control system based on an adaptive event trigger mechanism, characterized in that: Includes sensors, event generators, controllers, zero-order holders, and actuators; Sensor: samples data from the system and transmits the sampled data to the event generator; Event generator: receives the signal sent by the sensor and determines whether the latest measurement output y(t) meets the trigger condition. If it does, it sends the measurement output y(t) to the controller to generate a new control signal. If it does not, it determines the next measurement output y(t). Controller: receives the signal sent by the event generator and generates a new control signal, and transmits it to the zero-order holder; Zero-order holder: receives the discrete control signal generated by the controller, converts it into a continuous signal, and transmits it to the actuator; Actuator: Receives continuous signals from the zero-order holder and executes control commands.

2. The time-delayed isolated island microgrid load frequency control system based on the adaptive event triggering mechanism according to claim 1 is characterized in that: The island microgrid is sampled by sensors to obtain the system's measurement output y(t), which is then sent to the event generator to determine whether the latest measurement output y(t) meets the trigger condition. If so, the measurement output y(t) is sent to the controller. If not, the next measurement output y(t) is judged, and then the discrete signal is converted into a continuous signal through a zero-order holder. The actuator executes the control command to restore the system frequency.

3. A method for load frequency control of a time-delayed island microgrid based on an adaptive event trigger mechanism, characterized in that: The time-delayed island microgrid load frequency control system based on the adaptive event triggering mechanism described in any one of claims 1-2 is adopted, and the implementation of the method mainly includes the following steps: S1: Establish the state space model of the closed-loop system based on the structural parameters of the island microgrid; S2: Introduce the adaptive event triggering mechanism considering communication delay into microgrid load frequency control; S3: Lyapunov functional method; S4: Derive the stability criterion of time-delay islanded microgrid and eliminate the Zeno phenomenon; S5: Use MATLAB / LMI toolbox to solve the trigger matrix Ω and the minimum performance index γ min .

4. The method for load frequency control of time-delayed isolated island microgrid based on adaptive event triggering according to claim 3 is characterized in that: The specific process of step S1 to establish the closed-loop state space model of the isolated microgrid including the controller is as follows: S11: Define the state variable x(t), the measured output y(t), the target vector z(t), the system disturbance ω1(t) and the measured deviation ω2(t): ΔP wind (t), ΔP s (t) and ΔP d (t) represent the wind speed change of wind turbine, the change of solar radiation intensity and the load power change ΔP DEG , ΔP MTG , ΔP FC , ΔP V , ΔP WTG , ΔP FESS , ΔP BESS Respectively represent the power output changes of diesel generator, fuel cell, photovoltaic cell, wind turbine, flywheel energy storage system and battery energy storage system. In order to conveniently represent the system state, the intermediate variable ΔP is introduced DEG1 , ΔP MTG1 , ΔP FC1 , ΔP FC2 and ΔP V1 ; Δf(t) is the system frequency deviation, z(t) is the target vector; S12: Set the PI controller strategy and use the system frequency deviation Δf(t) as the input signal of the controller: u(t)=-K P Δf(t)-K I ∫Δf(t)dt (1) Among them, K P and K I are the proportional coefficient and integral coefficient of the system, and u(t) is the input signal of the PI controller; S13: Define the augmented vector S14: Establish a closed-loop state space model of the island microgrid: The closed-loop state space model of the island microgrid with the controller is established as: in, Where H represents the mechanical inertia of the island microgrid, R1 and R2 are constants, and T WTG , T PV Represent the dynamic parameters of wind turbine and photovoltaic system respectively, T IC , T t , T FC , T IN Both represent the time constant of the converter, T DEG , T MTG , T FC , T FESS , T BESS They are the response times of diesel generator, micro turbine generator, fuel cell, flywheel energy storage system and battery energy storage system respectively.

5. The method for load frequency control of time-delayed isolated island microgrid based on adaptive event triggering mechanism according to claim 3 is characterized in that: The step S2 establishes a time-delay island microgrid load frequency control system model based on an adaptive event trigger mechanism, and the specific steps are: S21: Define a delay function τ(t)∈[τ m ,τ M ], where: τ = τ M -τ m (τ m ≥0), τ M and τ m Respectively represent the upper and lower limits of communication delay, t k represents the kth triggering time, k represents the kth triggering, h is defined as the sampling period, t k +ih represents the i-th sampling time after the k-th trigger. Assuming the trigger time s k =t k +τ(t k ),τ(t k )∈[τ m ,τ M ]; S22: The measured output y(t) can be expressed as: y(t)=C1x(t k )+Dω2(t k ),t∈[s k ,s k+1 ) (3) S23: The error function can be expressed as: e(t)=y(t k )-y(t k +ih)=y(t k )-y(t-τ(t)) (4) S24: The control signal of the PI controller is: u(t)=u(t k +τ k )=Ky(t k ),t∈[s k ,s k+1 ) (5) S25: The state space model of the microgrid load frequency control system can be rewritten as: S26: Construct event trigger conditions: An adaptive event trigger mechanism is introduced to reduce unnecessary data transmission. After the sensor samples the controlled device, it determines whether the transmission conditions are met. The sampling signal is sent to the controller only when the event trigger condition is met. Otherwise, the next sampling signal is not sent and judged. The adaptive event trigger condition is (7): In which, the trigger matrix Ω>0, and the dynamic threshold σ(t) satisfies the differential equation (8): Wherein, μ>0 and ρ>0 are given constants, and 0<1 / ρ<σ(t)<1; If the closed-loop system (6) satisfies the following two conditions under the event triggering condition (7), the system is asymptotically stable: (1) When ω1(t) = 0, ω2(t) = 0, the system is asymptotically stable; (2) For non-zero If there exists a positive constant γ>0, such that under zero initial conditions:

6. The method for load frequency control of time-delayed isolated island microgrid based on adaptive event triggering mechanism according to claim 3 is characterized in that: The step S3 is based on the Lyapunov functional method to derive the stability criterion of the time-delay island microgrid and eliminate the Zeno phenomenon. The specific steps are: S31: Select the augmented Lyapunov-Krasovskii functional: Select the following Lyapunov functional and perform inequality scaling on it; V1(t)=x T (t)Px(t)(10a) Where P>0, Q1>0, Q2>0, Q3>0, R>0 and S>0 are all positive definite matrices with appropriate dimensions, τ=τ M -τ m ; Taking the derivative of V(t) we can get: S32: Solve the asymptotic stability criterion of the system: Based on the closed-loop system (6), the following equation holds: Where M,N∈R n×n And ε is a given constant; The integral term can be reduced to: in, Matrix R>0; The integral term can be simplified as: where S > 0, ζ T (t) = [x T (t - τ m ), x T (t - τ(t)), x T (t - τ M )]; When t∈[s k ,s k+1 ), according to the adaptive event triggering condition (7): σ(t)y T (t-τ(t))Ωy(t-τ(t))-e T (t)Ωe(t)≥0,t∈[s k ,s k+1 ) (15) Further we can get: Assume that there exists a small enough positive number δ such that: Inequality (17) can be transformed into matrix form: or T (t)Hη(t)≤0 (18) when When, because It is a continuous function, integrating both sides of equation (19) from 0 to +∞: When ω1(t)≡0 and ω2(t)≡0, it can be seen from (17): Therefore, in ensuring While the performance index γ, the closed-loop system (6) is asymptotically stable; S33: Island microgrid load frequency control system based on linear matrix inequality (6) Criteria: According to step S31-step S32, the following stability criterion is obtained: For a given sampling period h>0, constant ε>0, 0<1 / ρ<σ(t)<1, μ>0, For the suppression level γ>0 and the control matrix K, there exist matrices P>0, Q1>0, Q2>0, Q3>0, R>0, S>0, the trigger matrix Ω>0 and matrices M, N. If the following matrix inequality holds, the load frequency control system (6) of the island microgrid is asymptotically stable; In the formula, P 33 =-Q1+Q2+Q3-S-4R,Ψ 12 =P-M+εA T N T ,τ=τ M -t m , F 14 =col{ML,εML,0,0,0},Φ 15 =col{6R,0,6R,0,0},Φ 22 =D T ΩD-γ 2 I, Where I represents the identity matrix, * represents the transpose of the matrix relative to the position, and all the above matrices have appropriate dimensions; The stability criterion of formula (23) is derived on the basis of h>0.

7. According to the method for load frequency control of a time-delayed island microgrid based on an adaptive event trigger mechanism as described in claim 3, the stability criterion of the time-delayed island microgrid is derived and the Zeno phenomenon is eliminated, and the specific steps are as follows: When h=0, the load frequency control system (6) of the isolated microgrid may experience the Zeno phenomenon. In order to avoid the Zeno phenomenon in the isolated microgrid, it is necessary to ensure that the previous signal is received by the controller before the next signal can be updated. Combining the adaptive event triggering criterion (7) and σ(t)>0, we can obtain: ||e(s k+1 )||>σ(t)||y(t)||,t∈[s k ,s k+1 ) (22) When ω2(t)≡0, then at t∈[s k ,s k+1 ) the derivative of e(t) is as follows: in, p1=||C1BKC1||1||x(t-τ(t))||1+||C1A||1||x(t)||1+||C1A||1||ω1(t)||1,p2=||C1BKC1||1; From the definition of e(t), we know that e(s k )=0, combining (5) and the comparison inequality, solving equation (23) yields: Therefore, there exists a positive number The minimum execution time T satisfies: This means ensuring While the performance index γ is improved, the load frequency control system of the isolated microgrid does not have the Zeno phenomenon when h = 0.

8. The method for load frequency control of time-delayed isolated island microgrid based on adaptive event triggering mechanism according to claim 3 is characterized by: For non-zero perturbations The microgrid load frequency control system needs to meet certain performance indicators γ, and the smaller γ is, the better, under the premise of satisfying system stability. Based on the binary search algorithm, the search is performed to obtain the minimum performance indicator γ under the premise of satisfying system stability. min .

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