A ship micro-grid secondary frequency modulation method based on model-free adaptive control

Abstract

This invention discloses a secondary frequency regulation method for ship microgrids based on model-free adaptive control, belonging to the field of microgrid control technology. The steps include: acquiring the output frequency of a virtual synchronous generator in the ship microgrid; calculating the output angular frequency of the virtual synchronous generator based on the frequency; establishing and discretizing the rotor motion equation of the virtual synchronous generator; performing dynamic linearization to obtain a data model; calculating the pseudo-partial derivative estimation rate of the angular frequency; designing a model-free adaptive controller for the angular frequency; and achieving secondary frequency regulation of the ship microgrid by improving the virtual synchronous generator control through model-free adaptive control, dynamically adjusting the virtual input mechanical power of the virtual synchronous generator. This invention optimizes the response speed of frequency regulation in ship microgrids, which is beneficial for improving the frequency deviation problem caused by load switching in islanded mode under complex sea conditions.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of micro-grid control, and particularly relates to a ship micro-grid secondary frequency modulation control method based on model-free adaptive control. BACKGROUND

[0002] With the increasing seriousness of global energy crisis and environmental pollution, the development and utilization of clean energy have attracted extensive attention, especially the micro-grid technology which can combine distributed power generation. The micro-grid technology can solve the problem of non-dispatchable distributed power generation, better organize resources, and improve controllability and reliability. As an important member of the transportation industry, the shipping industry has attracted extensive attention in the research of energy saving and emission reduction. In the past few decades, the main power source of ships was high-power ship diesel generators. However, due to the influence of factors such as harsh ship operating environment, poor quality of heavy oil, serious pollution, and complex control mechanism, the traditional generator has certain application limitations. In the future, in order to meet the requirements of ships on energy in terms of environmental protection, reliability, and low cost, the use of distributed power generation devices of renewable new energy on ships will become the development trend of the shipping industry.

[0003] Distributed energy generally adopts high-power power electronic devices for inverter grid connection. Due to the rapid reaction of power electronic devices themselves, the influence of external disturbances, and the low anti-disturbance ability, the output power quality cannot be guaranteed. Delivering such power to the power grid will seriously pollute the large power grid and even cause the large power grid to collapse, resulting in serious consequences. The voltage amplitude and frequency are important indicators of power quality, so it is particularly important to ensure the stability of the two parameters. In view of this, Professor Zhong Qingchang proposed the virtual synchronous generator technology. This method mainly simulates the output characteristics of the traditional synchronous generator through the control of the inverter. Specifically, an algorithm is used to obtain a mathematical model similar to the active frequency regulation, reactive voltage regulation, and rotor motion equation of the synchronous generator, so that the inverter has the ability to imitate the output characteristics of the synchronous generator. In this way, the anti-disturbance and stability of the distributed power supply can be improved to some extent, and the impact on the power grid can be reduced.

[0004] Compared with the land power grid, the load capacity of the ship micro-grid is relatively large. At the same time, in the wide sea conditions, due to the complexity of the sea conditions, complex operating conditions such as large load switching often occur, at this time the system frequency will exist the problem of off-limit, and the response speed of the frequency regulation of the traditional virtual synchronous generator is slow. Therefore, how to ensure that the frequency drop is within a certain range, improve the power quality, realize the rapid response of frequency regulation, maintain the stable operation of the ship micro-grid, and develop a practical and economical micro-grid control scheme has become the main research direction.

[0005] The current secondary frequency modulation methods for virtual synchronous generators mainly include: the improved droop coefficient method proposed by Professor Zhong Qingchang et al., which automatically adjusts the droop coefficient according to the real-time power flow direction and capacity shortage of the microgrid as a whole. However, this method has the problems of large calculation amount and high complexity; the adaptive rotational inertia control strategy based on secondary frequency modulation proposed by Yang Duan et al. of Lanzhou Jiaotong University, which introduces the angular frequency offset and the rate of change into the rotational inertia control to form adaptive inertia control, thereby reducing the overshoot and oscillation time of the system under load disturbance. However, this method still has the problems of large calculation amount and high system complexity, and it is difficult to apply to ship microgrids; the PI element is introduced into the frequency modulation unit to realize error-free frequency modulation by Li Bin et al. of Chongqing University. However, due to the use of the “error-based error elimination” idea of PID, the system frequency has small amplitude oscillation, which cannot meet the demand of sensitive load on frequency. The model-free adaptive control is proposed by Professor Hou Zhongsheng in his doctoral thesis in 1994, which is a typical data-driven control method. This method uses a new dynamic linearization method to estimate the pseudo partial derivative or gradient of the controlled system online by using the I / O data of the controlled system, and then designs a weighted one-step forward controller to realize data-driven model-free adaptive control of nonlinear systems. Compared with traditional adaptive control, model-free adaptive control has the following characteristics: the controller only needs the I / O data of the controlled system and does not need any model information, which is very suitable for application in industrial control field. Secondly, model-free adaptive control has small calculation amount, simple structure and high robustness, and is a low-cost controller. In addition, the model-free adaptive control method can realize adaptive control of nonlinear systems with parameter variation and structural parameter variation.

[0006] Based on the above analysis, the present application provides a secondary frequency modulation control method for ship microgrids, which only uses the input and output data of the prime mover control system of the virtual synchronous generator of the ship microgrid, changes the virtual input mechanical power of the virtual synchronous generator to improve the frequency out-of-limit problem caused by load switching, and has the advantages of few online adjustment parameters, small calculation burden, strong robustness and fast response speed, thereby improving the stability and power quality of the ship microgrid power supply. SUMMARY

[0007] Therefore, the present application provides a secondary frequency modulation method for ship microgrids based on model-free adaptive control, which uses model-free adaptive control to improve the control of virtual synchronous generators, designs adaptive adjustment of secondary frequency modulation parameters, dynamically adjusts the virtual input mechanical power of the virtual synchronous generator of the ship, optimizes the response speed of the frequency regulation of the ship microgrid, limits the frequency fluctuation within a safe range, and further improves the frequency offset out-of-limit problem of the ship microgrid in island mode caused by load switching under complex sea conditions.

[0008] To achieve the above object of the application, the application adopts the following technical solutions:

[0009] S1: virtual synchronous generator control and secondary frequency modulation;

[0010] S2: adaptive adjustment of virtual synchronous generator secondary frequency modulation parameters based on model-free adaptive control;

[0011] Further, in step S1, the virtual synchronous generator control specifically includes: the function of simulating the synchronous generator rotor motion equation is realized by the prime mover controller in the virtual synchronous generator, and the rotor motion equation of the virtual synchronous generator is as follows:

[0012]

[0013] Wherein, J is the virtual moment of inertia of the virtual synchronous generator;

[0014] P set is the virtual input mechanical power;

[0015] P e is the output electromagnetic power of the virtual synchronous generator;

[0016] ω is the output angular frequency of the virtual synchronous generator;

[0017] ω n is the rated output angular frequency of the virtual synchronous generator;

[0018] D p is the damping coefficient;

[0019] Further, in step S1, the ship micro-grid secondary frequency modulation method based on model-free adaptive control specifically includes: introducing the frequency deviation feedback instruction based on droop control into the virtual input mechanical power to realize primary frequency modulation, as shown in the formula:

[0020]

[0021] Wherein, P ref is the rated mechanical power; f is the output frequency of the ship virtual synchronous generator; f N is the micro-grid reference frequency; k is the frequency modulation coefficient;

[0022] The prime mover controller is designed based on model-free adaptive control to realize secondary frequency modulation, as shown in the formula:

[0023]

[0024] Further, in step S2, the adaptive adjustment of the virtual synchronous generator secondary frequency modulation coefficient based on model-free adaptive control specifically includes:

[0025] (1) Signal acquisition and processing:

[0026] Collect the output frequency f of the ship's virtual synchronous generator; calculate the output angular frequency of the virtual synchronous generator based on its output frequency.

[0027] ω = 2πf;

[0028] (2) Establish the motion equations of the virtual synchronous generator rotor of the ship's microgrid and discretize them:

[0029]

[0030]

[0031]

[0032]

[0033]

[0034] Wherein, ω(t+1) is the output angular frequency of the virtual synchronous generator at time t+1;

[0035] ω(t) is the output angular frequency of the virtual synchronous generator at time t;

[0036] P m (t) represents the output of the model-free adaptive controller at time t;

[0037] h is the sampling period;

[0038] (3) Perform dynamic linearization to obtain the data model:

[0039] For the aforementioned dynamic equation, when ΔP m When (t)≠0, there exists a pseudo-partial derivative φ(t) such that: Δω(t+1)=φ(t)ΔP e (t), |φ(t)|≤b1; where b1 is a positive constant;

[0040] ΔP m (t)=P m (t)-P m (t-1);Δω(t+1)=ω(t+1)-ω(t);

[0041] (4) Calculate the pseudo-partial derivative estimation law for angular frequency:

[0042]

[0043] in, This is an estimate of φ(t);

[0044] This is an estimate of φ(t-1);

[0045] γ∈(0,1] is the step size factor, and μ>0 is the weight factor;

[0046] (5) Design a model-free adaptive controller for angular frequency:

[0047] J[P m [(t)]=|ω r (t+1)-ω(t+1)| 2 +λ|P m (t)-P m (t-1)| 2 In the middle, for P m Differentiate (t) and set the differentiated expression equal to zero to obtain:

[0048]

[0049] Where λ > 0 is a weighting factor used to control the change in the input quantity; ω r (t+1) is the desired output angular frequency; η∈(0,1] is the step size factor;

[0050] The model-free adaptive controller utilizes the output angular frequency and the desired output angular frequency from the ship's virtual synchronous generator, and its output P m (t) Real-time tracking of load changes. That is, when there is a load disturbance in the ship's microgrid, the P value at the next moment is calculated by combining a model-free adaptive control algorithm with primary frequency regulation based on droop control. set That is, virtual input mechanical power P set It can be adjusted in real time according to load disturbances, that is, the output of the inverter can be controlled to simulate the secondary frequency regulation characteristics of a generator.

[0051] Furthermore, the rotor motion equation in step (2) satisfies:

[0052] Equation with respect to P m The partial derivatives of (t) exist and are continuous;

[0053] The equation satisfies the generalized Lipschitz condition, that is, for any t, when ΔP m When (t)≠0, there is |Δω(t+1)|≤Q|ΔP m (t)|; Among them, Δω(t+1)=ω(t+1)-ω(t), ΔP m (t)=P m (t)-P m (t-1), where Q is a positive constant.

[0054] Furthermore, step (3) specifically includes the following steps:

[0055] (31) The discrete-time nonlinear system is established as follows:

[0056]

[0057] wherein P m (t)∈R, ω(t)∈R represent the input and output of the system at time t respectively; m ω and are two unknown positive integers; γ(…) is an unknown nonlinear function of the system;

[0058] The partial derivative of the system with respect to P m (t) exists and is continuous;

[0059] The system satisfies the generalized Lipschitz condition, that is, for any t, when ΔP m (t)≠0, |Δω(t+1)|≤Q|ΔP m (t)|; wherein Δω(t+1)=ω(t+1)-ω(t), ΔP m (t)=P m (t)-P m (t-1), and Q is a normal number;

[0060] (32) The following two equations can be obtained from the rotor motion equation:

[0061]

[0062] ξ(t)=f[ω(t)]+Aω(t)-f[ω(t-1)]-Aω(t-1);

[0063] Since ΔP m (t)≠0, the equation ξ(t)=η(t)P m (t) has a solution η(t); let φ(t)=B+η(t);

[0064] Δω(t+1)=φ(t)ΔP m (t) and |φ(t)|≤Q can be obtained;

[0065] Further, step (4) specifically comprises the following steps:

[0066] (41) A criterion function is established as follows:

[0067]

[0068] (42) The extreme value of the criterion function with respect to φ(t) is obtained, and a pseudo partial derivative estimation law is obtained as follows:

[0069] ​

[0070] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention acquires the output frequency of the ship's virtual synchronous generator; calculates the output angular frequency of the ship's virtual synchronous generator based on the output frequency; establishes and discretizes the rotor motion equation of the ship's microgrid virtual synchronous generator; performs dynamic linearization processing to obtain a data model; calculates the pseudo-partial derivative estimation rate of the angular frequency; designs a model-free adaptive controller for the angular frequency; and introduces model-free adaptive control into the frequency deviation feedback command of the prime mover controller to achieve adaptive adjustment of the secondary frequency regulation parameters. Therefore, the control method of this embodiment improves the control of the ship's virtual synchronous generator through model-free adaptive control, designs adaptive adjustment of the secondary frequency regulation parameters, dynamically adjusts the virtual input mechanical power of the ship's virtual synchronous generator, reduces the frequency deviation of the ship's microgrid system under severe sea conditions, optimizes the response speed of the ship's microgrid frequency regulation, and meets the requirements of stable microgrid operating frequency. Attached Figure Description

[0071] Figure 1 This is a block diagram of the prime mover controller.

[0072] Figure 2 This is a principle block diagram of a secondary frequency regulation method for a ship microgrid proposed in this invention;

[0073] Figure 3 This is a flowchart of an embodiment of a secondary frequency regulation method for a ship microgrid proposed in this invention;

[0074] Figure 4 This is a general structural diagram of a ship microgrid system;

[0075] Figure 5 It is the frequency curve of the ship microgrid operating system of the traditional virtual synchronous generator control system;

[0076] Figure 6 This is the frequency curve under the secondary frequency regulation method of a ship microgrid proposed in this invention; Detailed Implementation

[0077] The present invention will now be described in more detail with reference to the accompanying drawings.

[0078] This invention addresses the issues of frequency shift caused by frequent load switching in ship microgrids under complex sea conditions and the slow frequency regulation response of traditional virtual synchronous generators. By combining the microgrid inverter control method of virtual synchronous generators, a secondary frequency regulation method for ship microgrids based on model-free adaptive control is proposed. The following is a detailed description of this model-free adaptive control-based secondary frequency regulation method for ship microgrids.

[0079] Referring to Figures 1-6 The application discloses a ship micro-grid secondary frequency modulation control method.

[0080] Figure 3 The application discloses a ship micro-grid secondary frequency modulation control method, and a flow chart of the method is shown in the figure, and the method specifically comprises the following steps:

[0081] Step one: virtual synchronous generator frequency modulation principle

[0082] (1) Virtual synchronous generator control

[0083] The virtual synchronous generator control technology is to use a mathematical model similar to the active frequency modulation, reactive voltage regulation and rotor motion equation of the synchronous generator, so that the inverter has the ability to simulate the output characteristics of the synchronous generator. In this way, the distributed power supply can be improved in terms of disturbance resistance and stability, and the impact on the power grid can be reduced. The function of simulating the synchronous generator rotor motion equation is realized by the prime mover controller in the virtual synchronous generator, and the principle block diagram is shown in the figure. Figure 1 Wherein, J is the virtual moment of inertia of the virtual synchronous generator; P set is the virtual input mechanical power; P e is the output electromagnetic power of the virtual synchronous generator; ω is the output angular frequency of the virtual synchronous generator; ω n is the rated output angular frequency of the virtual synchronous generator; T m , T e , T d are the set mechanical torque, electromagnetic torque and damping torque respectively; θ is the power angle.

[0084] Therefore, the rotor motion equation of the virtual synchronous generator can be obtained as shown in the following formula:

[0085]

[0086] (2) Virtual synchronous generator secondary frequency modulation

[0087] The frequency deviation feedback instruction based on the droop control is introduced into the virtual input mechanical power to realize the primary frequency modulation, as shown in formula (2):

[0088]

[0089] Wherein, P refPnom is the rated mechanical power; f is the output frequency of the ship VSG; f N f0 is the reference frequency of the microgrid; k is the frequency modulation coefficient;

[0090] The prime mover controller is designed based on the model-free adaptive control to realize the secondary frequency modulation, as shown in the formula:

[0091]

[0092] Step two: adaptive adjustment of the secondary frequency modulation parameters of the VSG based on model-free adaptive control:

[0093] (1) Signal acquisition and processing

[0094] The output frequency f of the ship VSG is collected; the output angular frequency of the VSG is calculated according to the output frequency of the ship VSG;

[0095] ω = 2πf (4)

[0096] where ω is the output angular frequency of the VSG

[0097] (2) Establish the rotor motion equation of the ship microgrid VSG and perform discretization processing.

[0098]

[0099]

[0100] where, ω n is the rated output angular frequency of the VSG; J is the virtual moment of inertia of the VSG; D p is the damping coefficient; T e is the electromagnetic torque of the VSG; T m is the virtual input mechanical torque of the VSG;

[0101] For the VSG, the electromagnetic torque calculation equation is

[0102]

[0103] P e = u a i a + u b i b + u c i c

[0104] P e is the electromagnetic power output by the VSG, u a , u b , and uc are the terminal voltages of A, B and C phase of the virtual synchronous generator, respectively, i a b c are the terminal currents of A, B and C phase of the virtual synchronous generator, respectively;

[0105] Substituting formula (7) and (6) into formula (5), the virtual synchronous generator rotor kinematic equation is obtained and discretized:

[0106]

[0107]

[0108]

[0109]

[0110]

[0111] wherein ω(t+1) is the output angular frequency of the virtual synchronous generator at t+1 time;

[0112] ω(t) is the output angular frequency of the virtual synchronous generator at t time;

[0113] h is the sampling period;

[0114] P m (t) is the output of the model-free adaptive controller at t time;

[0115] h is the sampling period;

[0116] In order to improve the accuracy of the rotor kinematic equation, the dynamic equation (8) meets the following requirements:

[0117] Requirement 1: the partial derivative of the rotor kinematic equation with respect to P m (t) exists and is continuous;

[0118] Requirement 2: the equation meets the generalized Lipschitz condition, i.e. for any t, when ΔP m (t)≠0, there is |Δω(t+1)|≤Q|ΔP m (t)| (9)

[0119] In the formula, Δω(t+1)=ω(t+1)-ω(t), ΔP m (t)=P m (t)-P m (t-1), and Q is a normal number.

[0120] Since formula (4)-(8) are continuous and differentiable for global variables, it is obvious that the control input signal P​​m Since the partial derivatives of (t) exist and are continuous, requirement 1 holds. Furthermore, for a virtual synchronous generator system, a finite change in mechanical power will not cause an infinite increase in the angular frequency of the virtual synchronous generator, so requirement 2 obviously holds.

[0121] (3): Perform dynamic linearization to obtain the data model.

[0122] For the aforementioned dynamic equation, when ΔP m When (t)≠0, there exists a pseudo-partial derivative φ(t) such that:

[0123] Δω(t+1)=φ(t)ΔP e (t), |φ(t)|≤b1 (10)

[0124] Where b1 is a positive constant;

[0125] Formula (10) is the obtained mathematical model.

[0126] Specifically:

[0127] (31) The discrete-time nonlinear system is established as follows:

[0128]

[0129] Among them, P m Let ω(t)∈R and ω(t)∈R represent the system's input and output at time t, respectively; m ω and There are two unknown positive integers; γ(...): It is an unknown nonlinear function of the system;

[0130] The system meets the following conditions:

[0131] Condition 3: System (11) about P m (t) The partial derivatives exist and are continuous;

[0132] Condition 4: The equation satisfies the generalized Lipschitz condition, that is, for any t, when ΔP m When (t)≠0, there is |Δω(t+1)|≤Q|ΔP m (t)|; In the formula, Δω(t+1)=ω(t+1)-ω(t), ΔP m (t)=P m (t)-P m (t-1), where Q is a positive constant.

[0133] (32) From the dynamic equation (8), we can obtain the following two equations:

[0134]

[0135] ξ(t) = f [ω(t)] + Aω(t) - f [ω(t-1)] - Aω(t-1) (13)

[0136] Since ΔP m (t)≠0, equation ξ(t) = η(t)P m (t) (14)

[0137] There must be a solution η(t);

[0138] Let φ(t) = B + η(t) (15) Then from equations (8), (10) we have

[0139] Δω(t+1) = φ(t)ΔP m (t), |φ(t)| ≤ Q. (16)

[0140] (4) Calculate the pseudo-derivative estimation law.

[0141] (41) Establish the criterion function

[0142]

[0143] (42) Take the extreme value of the criterion function with respect to φ(t), we get the pseudo-derivative estimation law:

[0144]

[0145] where, is the estimated value of φ(t);

[0146] is the estimated value of φ(t-1);

[0147] γ ∈ (0,1] is the step factor, μ > 0 is the weight factor;

[0148] (51) Set the control input criterion function as follows:

[0149] J(P m (t)) = |ω r (t+1) - ω(t+1)| 2 + λ |P m (t) - P m (t-1)| 2 (19)

[0150] λ > 0 is a weight factor to control the change of input; ω r (t+1) is the desired output angular frequency

[0151] Substitute equation (10) in (3) into the criterion function, we getm (t) Derivation, and let the formula after derivation equal to zero, to get the following formula

[0152]

[0153] In summary, the model-free adaptive control scheme is as follows:

[0154]

[0155] The ship micro-grid secondary frequency modulation method based on model-free adaptive control of the embodiment, by collecting the output frequency of the ship virtual synchronous generator, the output angular frequency of the virtual synchronous generator is calculated according to the output frequency of the ship virtual synchronous generator; the ship micro-grid virtual synchronous generator rotor motion equation is established and discretized; dynamic linearization is carried out to obtain the data model; the angular frequency pseudo partial derivative estimation rate is calculated; the angular frequency model-free adaptive controller is designed; the prime mover controller is designed based on model-free adaptive control to realize secondary frequency modulation. When there is load disturbance in the ship micro-grid, the P set , that is, the virtual input mechanical power P set can be changed in real time according to external disturbance, that is, the output of the inverter simulates the secondary frequency modulation characteristics of the generator.

[0156] Therefore, the control method of the embodiment improves the ship virtual synchronous generator control through model-free adaptive control, and dynamically adjusts the virtual input mechanical power of the ship virtual synchronous generator through adaptive adjustment of the secondary frequency modulation parameters, reduces the frequency deviation of the ship micro-grid system caused by load switching in severe sea conditions, optimizes the response speed of the ship micro-grid frequency regulation, and meets the requirements of micro-grid operation frequency stability.

[0157] The traditional virtual synchronous generator control system and the control system of the embodiment are analyzed as follows.

[0158] The ship micro-grid secondary frequency modulation control system is established in the MATLAB / Simulink simulation environment, and the system parameters are: rated voltage 700V; filter inductance 9mH; filter capacitance 5μF; parasitic resistance 0.00001Ω; moment of inertia J=1kg.m 2 ; frequency modulation coefficient k=0.0001; D p 50; D q 0.0001; rated frequency 50Hz; rated active frequency 20kW;

[0159] Under off-grid conditions, the local load active power is 20kW, and the total simulation time is 1.5s. The simulation method is ode-23, and a 5kW active load is added at 0.5s and removed after 1s. For Figure 5 , the frequency of the VSG tends to be stable after 0.14s. Before 0.14s, the VSG has an overshoot in frequency adjustment, and reaches a peak of 50.01Hz at 0.07s; after 0.14s, it stabilizes at about 50Hz, and at 0.50s, the frequency starts to deviate downward due to the addition of a 5kW active load, and stabilizes at 49.96Hz at 0.6s; at 1s, the system frequency recovers to 50Hz at 1.14s, and stabilizes at 50Hz after 1.20s. From this, it can be seen that the maximum frequency deviation of the traditional virtual synchronous generator system is 0.04Hz, which is a large frequency deviation, and is not conducive to the stable operation of the ship microgrid.

[0160] When the virtual synchronous generator control based on model-free adaptive control performs secondary frequency regulation, for Figure 6 , the frequency of the VSG tends to be stable after 0.12s. Before 0.12s, the VSG has an overshoot in frequency adjustment, and reaches a peak of 50.02Hz at 0.09s; after 0.12s, it stabilizes at about 50Hz, and at 0.5s, the frequency starts to deviate downward due to the addition of a 5kW active load, and stabilizes at 49.985Hz at 0.56s; at 1s, the system frequency recovers to 50Hz at 1.1s, but overshoots at 1.05s with a maximum peak of 50.01Hz, and stabilizes at 50Hz after 1.12s. From this, it can be seen that when the virtual synchronous generator control based on model-free adaptive controller performs secondary frequency regulation, the maximum frequency deviation of the system is 0.05Hz, which is smaller than that of the traditional virtual synchronous generator, and is more conducive to the stable operation of the ship microgrid. It can be seen that the frequency curve of the VSG under model-free adaptive control is less affected by load switching, and has strong anti-disturbance ability, and is more rapid and smooth in the adjustment process.

[0161] The embodiment proposes a ship microgrid secondary frequency modulation method based on model-free adaptive control, and proves the convergence. Through simulation experiments, the frequency modulation performance of the traditional virtual synchronous generator control system and the improved ship virtual synchronous generator control system based on model-free adaptive control are compared, and the results show that when the virtual synchronous generator control based on model-free adaptive controller performs secondary frequency regulation, the frequency deviation of the ship microgrid is smaller during load switching, i.e. the frequency excursion problem is improved, and the frequency response speed of the ship microgrid is optimized, and the frequency modulation effect of the ship microgrid is improved.

[0162] For those skilled in the art, other various corresponding changes and modifications can be made to the above described technical solutions and concepts, and all these changes and modifications should belong to the protection scope of the claims of the present application.

Claims

1. A method for secondary frequency regulation of a ship microgrid based on model-free adaptive control, characterized in that: The method improves the control of the virtual synchronous generator through a model-free adaptive control algorithm, designs adaptive adjustment of secondary frequency modulation parameters, dynamically adjusts the virtual input mechanical power of the virtual synchronous generator of the ship, optimizes the response speed of frequency regulation of the ship microgrid, limits frequency fluctuation within a safe range, and further improves the frequency deviation out-of-limit problem of the ship microgrid in island mode due to load switching under complex sea conditions, and the method comprises the following steps: S1: virtual synchronous generator control and secondary frequency modulation, specifically comprising: S11: virtual synchronous generator control: The function of simulating the rotor motion equation of the synchronous generator is realized by the prime mover controller in the virtual synchronous generator, and the rotor motion equation of the virtual synchronous generator is as shown in the following formula: ； wherein, is a virtual moment of inertia of the virtual synchronous generator; Virtual input mechanical power; to output electromagnetic power of the virtual synchronous generator; output angular frequency for the virtual synchronous generator; ωref is the nominal output angular frequency of the virtual synchronous generator; is the damping coefficient; S12: secondary frequency modulation: The frequency deviation feedback instruction based on droop control is introduced into the virtual input mechanical power to realize primary frequency modulation, as shown in the formula: ； wherein, is the rated mechanical power; is the output frequency of the ship's virtual synchronous generator; is the microgrid reference frequency; is the frequency modulation coefficient; The prime mover controller is designed based on model-free adaptive control to realize secondary frequency modulation, as shown in the following formula: ； The model-free adaptive controller utilizes the output angular frequency of the ship virtual synchronous generator and the desired output angular frequency, and the output quantity of the model-free adaptive controller is Real-time tracking of load changes, that is, when there is a load disturbance in the ship micro-grid, the next time That is, the virtual input mechanical power Real-time changes according to load disturbances, that is, the output of the inverter simulates the secondary frequency modulation characteristics of the generator; S2: adaptive adjustment of secondary frequency modulation parameters of the virtual synchronous generator based on model-free adaptive control.

2. The method of claim 1, wherein the method is based on model-free adaptive control. In step S2, the adaptive adjustment of the secondary frequency modulation parameters of the virtual synchronous generator based on model-free adaptive control specifically comprises: (1) signal acquisition and processing: Collecting an output frequency of a ship virtual synchronous generator ; calculating an output angular frequency of the virtual synchronous generator from the output frequency of the ship virtual synchronous generator: ； (2) discretization processing is performed on the rotor motion equation of the virtual synchronous generator of the ship microgrid to obtain a rotor motion discretization equation: ； ； ； ； ； wherein, is the momentary virtual synchronous generator output angular frequency; for instant virtual synchronous generator output angular frequency; T is the sampling period; (3) dynamic linearization processing is performed to obtain a data model: For the discretized equation of rotor motion, when there exists a pseudo partial derivative such that: , ; where is a positive constant; ； ； (4) calculation of the pseudo-derivative estimation law of the angular frequency: ； wherein is an estimate of For an estimate of the value of is a step factor, is a weight factor; (5) design of the model-free adaptive controller of the angular frequency: In some embodiments, the method further comprises determining the concentration of the target analyte in the sample. Differentiating and setting the differentiated equation to zero, we get: ； wherein, is a weight factor to control the change of the input quantity; is the desired output angular frequency; is a step factor.

3. The method of claim 2, wherein: The rotor motion discretization equation of step (2) satisfies: Equations exist and are continuous with respect to the partial derivatives of ; The equation satisfies the generalized Lipschitz condition, that is, satisfies for any When , ; wherein, , , is a normal number.

4. The method of claim 2, wherein: Step (3) specifically comprises the following steps: (31) establish a discrete-time nonlinear system: ； wherein, , respectively represent the input and output of the system at time instant t; and are two unknown positive integers; : is an unknown nonlinear function of the system. The system is about The partial derivative of the function exists and is continuous; The system satisfies the generalized Lipschitz condition, when satisfying for any When , there is ; wherein , , is a normal number; (32) the following two formulas can be obtained from the rotor motion discretization equation: ； ； Since , the equation has a solution ; let ; may be obtained , .

5. The method of claim 2, wherein: Step (4) specifically comprises the following steps: (41) Establishing a criterion function ; (42) The criterion function is maximized with respect to The pseudo-derivative estimation law is obtained 。

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