A Green Port Distributed Energy Pre-Grid Connection Control Method

Abstract

The present invention discloses a pre-grid connection control method for distributed energy in a green port, which relates to the technical field of port energy control. First, the virtual reactive power on the virtual reactance is calculated according to the voltage components of the dq coordinate axes on both sides of the distributed energy grid connection point; then, the virtual reactive power is controlled by an intelligent self-learning PID controller to obtain the inverter error compensation angular frequency and the inverter error compensation voltage amplitude; the inverter error compensation angular frequency and the inverter error compensation voltage amplitude are respectively introduced into the active frequency modulation control loop and the reactive voltage regulation control loop in the virtual synchronous generator control algorithm; finally, the pre-grid connection control is realized by controlling the amplitude and phase of the output voltage of the distributed energy inverter to be synchronized with the amplitude and phase of the ship power grid voltage. The present invention improves the problem of the generation of inrush current during the grid connection of distributed energy in the port to the port integrated power supply system, as well as the rapidity and stability of the distributed energy grid connection process in the port.

Description

Technical Field

[0001] The present invention belongs to the technical field of port energy control, and particularly relates to a pre-grid connection control method for distributed energy in a green port. Background Art

[0002] A green port is a new type of port that takes green environmental protection as the guiding concept and achieves a sustainable dynamic balance between environmental and economic development, realizes the rational application of resources, and has low pollution and low energy consumption. During the operation of a ship berthing at a port, the ship mainly relies on the four-stroke diesel generator on the ship to maintain the power required for various equipment and daily life on the ship. The large amounts of carbon dioxide, sulfides, and nitrides emitted by it cause serious pollution to the port area. Therefore, it is particularly important to build a ship power grid of a port integrated power supply system including wave energy, solar photovoltaic power, wind power, energy storage power supply, shore power, etc., and build a smart green energy platform to achieve green, low-carbon, and circular development of the port.

[0003] It should be noted that during the operation of a ship berthing at a port, when using high-power equipment such as shipboard cranes, due to the special complexity of port distributed energy, problems such as poor accuracy of pre-grid connection control of port distributed energy and long transition process time will occur, and it cannot better meet the requirements of port distributed energy for the rapidity and stability of pre-grid connection control. This poses higher requirements for the pre-grid connection control strategy of distributed energy in a green port.

[0004] In recent years, in order to ensure the normal operation of high-quality electric energy of distributed energy and local sensitive loads and the surplus power feeding into the grid, the traditional pre-grid connection control method based on virtual synchronous generator technology proposed by Professor Zhong Qingchang and others has been widely used. By designing a pre-synchronization unit based on a phase-locked loop to track the amplitude and phase of the grid voltage, the impact current caused by the phase difference between both sides of the grid connection point during the grid connection process can be avoided. However, during the start and stop of high-power equipment during the operation of a ship berthing at a port, due to the characteristics of the phase-locked loop itself, such as measurement data delay and long dynamic response time, when the phase difference obtained by phase locking is sent to the PI controller, problems such as poor accuracy of pre-grid connection control and long transition process time will occur. Therefore, the traditional pre-grid connection control method is difficult to meet the requirements of port distributed energy for the rapidity and stability of pre-grid connection control.

[0005] Intelligent self-learning PID learning control combines PID control with intelligent control algorithms to handle the strong nonlinearity and random disturbance problems encountered in the actual control process. It is a control algorithm for discrete-time nonlinear systems. For nonlinear uncertainties and unknown parameters, this algorithm designs an adaptive estimator and a time-difference estimator respectively to improve the adaptability and robustness of the intelligent self-learning PID controller. Moreover, the controller introduces an adaptive mechanism that only uses real-time I / O measurement data to update the local linear data model and is a data-driven controller. Its design and analysis do not depend on model information and are very suitable for application in the industrial control field.

[0006] The present invention considers the problem of inrush current generated during the grid connection of port distributed energy such as wave energy to participate in the energy scheduling and load distribution of berthing ships when a large merchant ship berths, as well as the problems of poor control accuracy and long transition process time of traditional pre-grid connection control methods, and proposes a pre-grid connection control method for green port distributed energy. This method only calculates the virtual reactive power on the virtual reactance using the dq-axis voltage components, controls the virtual reactive power through an intelligent self-learning PID controller to obtain the inverter error compensation angular frequency and the inverter error compensation voltage amplitude, and introduces them into the active frequency modulation control loop and the reactive power voltage regulation control loop in the virtual synchronous generator control algorithm respectively, thereby changing the output voltage phase and voltage amplitude of the port distributed inverter to achieve synchronization with the amplitude and phase of the ship's grid voltage, improving the generation of inrush current when the port distributed energy is connected to the port integrated power supply system and the rapidity and stability during the grid connection process of the port distributed energy. Summary of the Invention

[0007] The present invention considers the problem of inrush current generated during the grid connection of port distributed energy such as wave energy to participate in the energy scheduling and load distribution of berthing ships when a large merchant ship berths, as well as the problems of poor control accuracy and long transition process time of traditional pre-grid connection control methods, and provides a pre-grid connection control method for green port distributed energy to improve the inrush current generated when the port distributed energy is connected to the port integrated power supply system and achieve the rapid and stable grid connection of the port distributed energy.

[0008] To achieve the above-mentioned invention purpose, the present invention adopts the following technical solutions:

[0009] S1: Calculate the virtual reactive power on the virtual reactance according to the dq-axis voltage components;

[0010] S2: Control the virtual reactive power through an intelligent self-learning PID controller to obtain the inverter error compensation angular frequency and the inverter error compensation voltage amplitude;

[0011] S3: Introduce the inverter error compensation angular frequency and the inverter error compensation voltage amplitude into the active frequency modulation control loop and the reactive voltage regulation control loop in the virtual synchronous generator control algorithm respectively to achieve pre-grid connection control;

[0012] S4: Achieve pre-grid connection control by controlling the amplitude and phase of the output voltage of the distributed energy inverter to be synchronized with the amplitude and phase of the ship power grid voltage;

[0013] Furthermore, in step S1, the specific process of calculating the virtual reactive power on the virtual reactance according to the voltage components on the dq coordinate axes is as follows:

[0014] (1) Collect the three-phase output voltage U 0a 、U 0b 、U 0c of the distributed energy inverter and the three-phase voltage U ga 、U gb 、U gc of the ship power grid; respectively convert the three-phase output voltage U 0a 、U 0b 、U 0c of the distributed energy inverter and the three-phase voltage U ga 、U gb 、U gc of the ship power grid into the voltage components U 0d 、U 0q and U gd 、U gq in the dq coordinate axes;

[0015] (2) Assume that there is a virtual impedance between the ship power grid and the port distributed energy, equivalent the virtual impedance to a virtual reactance, and calculate the virtual reactive power between the ship power grid and the port distributed energy according to the voltage components U 0d 、U 0q and U gd 、U gq in the dq coordinate axes. The expression is as follows:

[0016]

[0017]

[0018]

[0019]

[0020] where Q V is the virtual reactive power between the ship power grid and the port distributed energy; X Vis the virtual reactance; Δθ is the phase difference between the ship power grid voltage and the output voltage of the port distributed energy inverter; U0 and U g are the effective values of the output voltage of the port distributed energy inverter and the ship power grid voltage, respectively;

[0021] Further, in step S2, the specific process of controlling the virtual reactive power through the intelligent self-learning PID controller to obtain the inverter error compensation angular frequency and the inverter error compensation voltage amplitude includes:

[0022] (1) Discretize the virtual reactive power expression:

[0023]

[0024]

[0025]

[0026] where ω(t + 1) is the inverter error compensation angular frequency at time t + 1;

[0027] ω(t) is the inverter error compensation angular frequency at time t;

[0028] E(t + 1) is the inverter error compensation voltage amplitude at time t + 1;

[0029] E(t) is the inverter error compensation voltage amplitude at time t;

[0030] Q V (t + 1) is the virtual reactive power at time t + 1;

[0031] Q V (t) is the virtual reactive power at time t;

[0032] h is the sampling period;

[0033] Further, the virtual reactive power discretization equation in step (1) satisfies:

[0034] The partial derivatives of the equation with respect to the control inputs ω(t) and E(t) exist, are continuous, and are bounded;

[0035] The equation satisfies the generalized Lipschitz condition, that is, for any t1 ≠ t2, t1, t2 ≥ 0 and there is where b > 0 is a positive constant; Q V (t i + 1) = γ[Q V (t i ),…Q V (t i - mQV ), ω(t i ), …, ω(t i -m ζ ), E(t i ), …, E(t i -m ζ ), i = 1, 2;

[0036] (2) Perform tight - format dynamic linearization to obtain a tight - format local linearization data model:

[0037] For the discretized equation of virtual reactive power, when , there exists a time - varying parameter called the pseudo - Jacobian matrix such that the discretized equation of virtual reactive power is transformed into a tight - format local linearization data model: where is bounded for any time t; γ c (t) is a non - linear term;

[0038] Furthermore, step (2) specifically includes the following steps:

[0039] (21) Establish a discrete - time non - linear system:

[0040]

[0041] where Q V (t) ∈ R represents the output ω(t) ∈ R of the system at time t, E(t) ∈ R represents the input of the system at time t, m ζ and are two unknown positive integers; γ(…) : is a non - linear function of the system that is unknown;

[0042] The partial derivatives of the system with respect to ω(t) and E(t) exist and are continuous;

[0043] The equation satisfies the generalized Lipschitz condition, that is, for any t1 ≠ t2, t1, t2 ≥ 0 and there is where b > 0 is a positive constant;

[0044] (22) From the discretized equation of virtual reactive power, the following two equations can be obtained:

[0045]

[0046] ξ(t) = Q V (t) - Q V (t - 1);

[0047] Since Therefore, the equation has a solution η(t);

[0048] Let

[0049] We can obtain |φ c (t)| ≤ b;

[0050] (3) Calculate the pseudo-Jacobian matrix estimation law of the virtual reactive power:

[0051]

[0052] For γ c (t), use the previous I / O information to estimate γ c (t) at the current moment by adopting the time difference estimation algorithm:

[0053]

[0054] Among them, is the estimated value of ;

[0055] is the estimated value of ;

[0056] is the estimated value of γ c (t);

[0057] η ∈ (0, 2] is the step size factor, aiming to make the control algorithm more general

[0058] μ > 0 is the weight factor;

[0059] Furthermore, step (3) specifically includes the following steps:

[0060] (31) Establish the parameter estimation index function

[0061]

[0062] (32) Take the derivative of both sides of the parameter estimation index function with respect to φ c (t) and set it to zero, then the pseudo-Jacobian matrix number estimation law can be obtained:

[0063]

[0064] (4) Design the intelligent self-learning PID controller of the virtual reactive power:

[0065] Define the output tracking error e(t) = Q Vr (t + 1) - Q V(t + 1), according to the equivalent feedback principle, and in introducing an error feedback term, we can obtain:

[0066]

[0067] where λ > 0 is a weight factor; is the desired output virtual power; ρ ∈ (0, 2] is the step factor, which is used to limit the change of the input quantity; k p and k i and k d are learning gains;

[0068] Furthermore, in step S3, the specific implementation of introducing the inverter error compensation angular frequency and the inverter error compensation voltage amplitude into the active frequency modulation control loop and the reactive power voltage regulation control loop in the virtual synchronous generator control algorithm to achieve pre-grid connection control includes:

[0069]

[0070] E = K Q (Q set - Q e ) + U0 + E(t);

[0071] where 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; D P is the damping coefficient; θ is the output reference voltage phase of the virtual synchronous generator; K Q is the reactive power voltage regulation coefficient; Q set is the virtual reactive power set value; Q e is the reactive power output by the virtual synchronous generator; E is the output reference voltage amplitude of the virtual synchronous generator;

[0072] By controlling the virtual reactive power to be equal to the virtual reactive power set value, the amplitude and phase of the output voltage of the distributed energy inverter are synchronized with the amplitude and phase of the ship power grid voltage, and the grid connection switch is closed, then the pre-grid connection control of the distributed energy in the green port can be achieved.

[0073] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0074] (1) Compared with the traditional pre-grid connection control method, the phase-locked loop link is omitted, avoiding the problems of poor pre-grid connection control accuracy and long transition process time caused by sending the phase difference measured by the phase-locked loop into the PI controller in the environment of starting and stopping high-power equipment during ship docking operations.

[0075] (2) Compared with the traditional pre-grid connection control strategy, the intelligent self-learning PID learning controller adopted in the present invention has stronger robustness and self-adaptability; in addition, only one controller is required, reducing the controller cost and avoiding the synchronization enabling link in the traditional pre-grid connection control method.

[0076] (3) It can quickly synchronize the output voltage phase and voltage amplitude of the port distributed inverter with the amplitude and phase of the ship's power grid voltage, improving the generation of inrush current during grid connection of port distributed energy to the port integrated power supply system and the stability during the grid connection process of port distributed energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 is a flowchart of an embodiment of a pre-grid connection control method for port distributed energy proposed by the present invention;

[0078] Figure 2 is a schematic diagram of the green port integrated power supply system described in the present invention;

[0079] Figure 3 is a control block diagram of a pre-grid connection control method for port distributed energy proposed by the present invention;

[0080] Figure 4 is a comparison diagram of the phase difference between the output voltage of the port distributed energy inverter and the ship's power grid voltage between the traditional pre-grid connection control method and the pre-grid connection control method proposed by the present invention;

[0081] Figure 5 is a comparison diagram of the output phase A voltage of the port distributed energy inverter and the phase A voltage of the ship's power grid under the traditional pre-grid connection control method and the pre-grid connection control method proposed by the present invention;

[0082] Figure 6 is a comparison diagram of the output current of the distributed energy between the traditional pre-grid connection control method and the pre-grid connection control method proposed by the present invention; DETAILED DESCRIPTION OF THE EMBODIMENTS

[0083] To make the objectives and technical solutions of the embodiments of the present invention clearer, the present invention will be more completely described below in conjunction with the drawings of the embodiments of the present invention.

[0084] Considering the problem of inrush current generated during the grid connection of port distributed energy such as wave energy to participate in the energy scheduling and load distribution of berthed ships when large merchant ships are berthed, as well as the problems of poor control accuracy and long transient process time of traditional pre-grid connection control methods, the present invention proposes a pre-grid connection control method for green port distributed energy. Next, a pre-grid connection control method for green port distributed energy will be described in detail.

[0085] Please refer to Figures 1 to 6 The pre-grid connection control method for green port distributed energy. Figure 1 It is a flowchart of an embodiment of a pre-grid connection control method for green port distributed energy proposed by the present invention. This method calculates the virtual reactive power on the virtual reactance by collecting the three-phase voltages output by the distributed energy inverter and the three-phase voltages of the ship's power grid after Park transformation. The virtual reactive power is controlled by an intelligent self-learning PID controller to obtain the inverter error compensation angular frequency and the inverter error compensation voltage amplitude, and they are respectively introduced into the active frequency modulation control loop and the reactive voltage regulation control loop in the virtual synchronous generator control algorithm. Furthermore, the output voltage phase and amplitude of the port distributed inverter are changed to achieve synchronization with the amplitude and phase of the ship's power grid voltage, improving the generation of inrush current when the port distributed energy is connected to the port integrated power supply system and the rapidity and stability during the grid connection process of the port distributed energy.

[0086] Figure 2 It is a schematic diagram of the green port integrated power supply system described in the present invention. During the berthing of large merchant ships, the green port integrated power supply system consists of the port shore power, the wave energy power generation device carried by the merchant ship, the photovoltaic array, the wind turbine, and the energy storage unit to jointly form the ship's power grid. Each distributed energy is connected to the AC bus through an inverter, and whether the distributed energy is connected to the grid is determined by a grid connection switch.

[0087] Figure 3 It is a control block diagram of a pre-grid connection control method for green port distributed energy proposed by the present invention. The specific steps are as follows:

[0088] Step 1: Calculate the virtual reactive power on the virtual reactance according to the voltage components on the dq coordinate axes

[0089] (1) Collect the three-phase voltages U 0a , U 0b , U 0c output by the distributed energy inverter and the three-phase voltages U ga , U gb , U gc of the ship's power grid; respectively transform the three-phase phase voltages U 0a , U 0b , U 0cWith the three-phase phase voltage U of the ship's power grid ga 、U gb 、U gc Convert to the voltage components U 0d 、U 0q and U gd 、U gq ;

[0090] (2) Assume that there is a virtual impedance Z g in the grid-connected switch S V , and the virtual impedance is equivalent to a virtual reactance X V And according to the voltage components U 0d 、U 0q and U gd 、U gq Calculate the virtual reactive power between the ship's power grid and the port distributed energy, and the expression is as follows:

[0091]

[0092]

[0093]

[0094]

[0095] Among them, Q V is the virtual reactive power between the ship's power grid and the port distributed energy; X V is the virtual reactance; Δθ is the phase difference between the ship's power grid and the port distributed energy; U0, U g are the effective value of the output voltage of the port distributed energy inverter and the effective value of the ship's power grid voltage respectively;

[0096] Step 2: Control the virtual reactive power through an intelligent self-learning PID controller to obtain the inverter error compensation angular frequency and the inverter error compensation voltage amplitude:

[0097] (1) Discretize the virtual reactive power expression:

[0098]

[0099]

[0100]

[0101] Among them, ω(t + 1) is the inverter error compensation angular frequency at time t + 1;

[0102] ω(t) is the inverter error compensation angular frequency at time t;

[0103] E(t + 1) is the amplitude of the inverter error compensation voltage at time t + 1;

[0104] E(t) is the amplitude of the inverter error compensation voltage at time t;

[0105] Q V (t + 1) is the virtual reactive power at time t + 1;

[0106] Q V (t) is the virtual reactive power at time t;

[0107] h is the sampling period;

[0108] To improve the accuracy of the discretized equation of the virtual reactive power, the discretized equation (5) satisfies the following assumptions:

[0109] Assumption 1: The partial derivatives of the equation with respect to the control inputs ω(t) and E(t) exist, are continuous, and are bounded;

[0110] Assumption 2: The equation satisfies the generalized Lipschitz condition, that is, for any t1 ≠ t2, t1, t2 ≥ 0 and there is

[0111]

[0112] where b > 0 is a positive constant;

[0113]

[0114] Since the discretized equation (5) is continuously differentiable with respect to all global variables, the partial derivatives of ω(t) and E(t) exist, are continuous, and are bounded, so Assumption 1 holds. In addition, the finite changes in the inverter error compensation angular frequency and the inverter error compensation voltage amplitude will not cause an infinite increase in the virtual reactive power, so Assumption 2 holds.

[0115] (2) Perform a compact - form dynamic linearization process to obtain a compact - form local linearization data model:

[0116] For the discretized equation of the virtual reactive power, when there exists a time - varying parameter called the pseudo - Jacobian matrix such that the discretized equation of the virtual reactive power is converted into a compact - form local linearization data model:

[0117]

[0118] where, is bounded for any time t; γ c (t) is a non - linear term;

[0119] Equation (7) is the obtained mathematical model.

[0120] Specifically:

[0121] (21) Establish a discrete-time nonlinear system:

[0122]

[0123] where Q V (t) ∈ R represents the output ω(t) ∈ R of the system at time t, E(t) ∈ R represents the input of the system at time t, m ζ and are two unknown positive integers; γ(…) : is the unknown nonlinear function of the system;

[0124] This system satisfies the following assumptions:

[0125] Assumption 3: The partial derivatives of this system with respect to ω(t) and E(t) exist and are continuous respectively;

[0126] Assumption 4: The equation satisfies the generalized Lipschitz condition, that is, for any t1 ≠ t2, t1, t2 ≥ and there is where b > 0 is a positive constant;

[0127] (22) From the discretized equation of the virtual reactive power, the following two equations can be obtained:

[0128]

[0129] ξ(t) = Q V (t) - Q V (t - 1) (10)

[0130] Since so the equation has a solution η(t);

[0131] Let

[0132] It can be obtained that

[0133]

[0134] (3) Calculate the pseudo-Jacobian matrix estimation law of the virtual reactive power:

[0135] (31) Establish a parameter estimation index function

[0136]

[0137] (32) Differentiate both sides of this parameter estimation index function with respect to φc (t) is differentiated and set to zero, and the pseudo-Jacobian matrix number estimation law can be obtained:

[0138]

[0139] (33) For γ c (t), the I / O information before is used to estimate γ c (t) at the current moment by adopting the time difference estimation algorithm:

[0140]

[0141] where is the estimated value of;

[0142] is the estimated value of;

[0143] is the estimated value of γ c (t);

[0144] η ∈ (0, 2] is the step size factor, aiming to make the control algorithm more general

[0145] μ > 0 is the weight factor;

[0146] (4) Design an intelligent self-learning PID controller for the virtual reactive power:

[0147] (41) According to the equivalent feedback principle, from Equation (7), we can obtain

[0148]

[0149] ρ ∈ (0, 2] is the step size factor; λ > 0 is a weight factor used to control the change of the input quantity; Q Vr (t + 1) is the expected output virtual reactive power;

[0150] (42) Define the output tracking error

[0151]

[0152] According to the equivalent feedback principle, and by introducing the error feedback term in Equation (16), we can obtain:

[0153]

[0154] where k p 、k i 、k d are the learning gains;

[0155] In summary, the intelligent self-learning PID control scheme is as follows:

[0156]

[0157] Step 3: Respectively introduce the inverter error compensation angular frequency and the inverter error compensation voltage amplitude into the active frequency modulation control loop and the reactive voltage regulation control loop in the virtual synchronous generator control algorithm to achieve pre-parallel grid control, which specifically includes:

[0158] (1) Introduce the inverter error compensation angular frequency into the active frequency modulation control loop in the virtual synchronous generator control algorithm:

[0159]

[0160] where 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; D P is the damping coefficient; θ is the output reference voltage phase of the virtual synchronous generator;

[0161] (2) Introduce the inverter error compensation voltage amplitude into the reactive voltage regulation control loop in the virtual synchronous generator control algorithm:

[0162] E = K Q (Q set - Q e ) + U0 + E(t) (21)

[0163] where K Q is the reactive voltage regulation coefficient; Q set is the virtual reactive power set value; Q e is the reactive power output by the virtual synchronous generator; E is the output reference voltage amplitude of the virtual synchronous generator;

[0164] Step 4: When the virtual reactive power is controlled to be equal to the virtual reactive power set value, the amplitude and phase of the output voltage of the distributed energy inverter are synchronized with the amplitude and phase of the ship's power grid voltage, and pre-parallel grid control can be achieved.

[0165] Therefore, the control method of this embodiment takes into account the problems of inrush current generated during the grid connection of port distributed energy such as wave energy participating in the energy dispatching and load distribution of berthing ships and the poor control accuracy and long transition process time of traditional pre-grid connection control methods in the case of large merchant ships berthing. By collecting the three-phase voltage output by the distributed energy inverter and the three-phase voltage of the ship's power grid and calculating the virtual reactive power on the virtual reactance through Park transformation, the virtual reactive power is controlled by an intelligent self-learning PID controller to obtain the inverter error compensation angular frequency and the inverter error compensation voltage amplitude, and they are respectively introduced into the active frequency modulation control loop and the reactive voltage regulation control loop of the virtual synchronous generator control algorithm, so as to change the output voltage phase and voltage amplitude of the port distributed inverter, realize the synchronization of the amplitude and phase of the voltage with the ship's power grid voltage, and improve the generation of inrush current when the port distributed energy is connected to the port integrated power supply system and the rapidity and stability during the grid connection process of the port distributed energy. The traditional virtual synchronous generator pre-grid connection control method and the control method of this embodiment are compared and analyzed below.

[0166] Taking the direct-drive wave energy generation device of the float as an example, when the port shore power integrated power supply system is in a stable state and there is no frequent load fluctuation, the smooth grid connection of the wave energy generation device is realized through the pre-grid connection control of the wave energy generation device, and the power supply rate of the ship's power grid is improved. The parameters of the port integrated power supply system refer to the China Merchants Pier of Qingdao Port, that is, the voltage level is 380V and the power supply frequency is 50Hz. A single green port distributed energy pre-grid connection control system is built through MATLAB / Simulink, and a traditional pre-grid connection control method is designed for comparison. The wave energy generation device realizes the AC-DC conversion through the machine-side converter and then accesses the ship's power grid through the inverter. When the wave energy generation device is under the input wave excitation force f s = 2000sin(πt / 2), the DC side voltage of the wave energy generation device is stable at 800V. Therefore, the parameters of the distributed energy inverter using the virtual synchronous generator algorithm are set as follows: the inverter filter inductor is taken as 0.07H; the inverter filter capacitor is 5μF; the stator armature resistance is 0.01 Ω; the moment of inertia J = 0.5kg·m 2 ; the damping coefficient D p is taken as 100; the virtual input mechanical power is 10kW; the virtual reactive power set value is 5kVar, and it is assumed that the initial phase difference between the inverter and the ship's power grid voltage is set to 35°.

[0167] Initially, the wave energy generation device operates in the island mode to supply power to a local AC load of 10kW, and the total simulation duration is set to 5s. The pre-grid connection controller is put into operation at 2s. Figure 4 And Figure 5respectively show the comparison diagram of the phase difference between the output voltage of the port distributed energy inverter and the ship power grid voltage, and the comparison diagram of the output phase A voltage of the port distributed energy inverter and the phase A voltage of the ship power grid under the traditional pre-parallel grid control method and the pre-parallel grid control method proposed by the present invention; According to Figure 4 it can be seen that the phase difference between the output voltage of the distributed energy inverter and the ship power grid voltage under the traditional pre-parallel grid control method tends to be synchronized at 2.25 s, and the phase difference under the pre-parallel grid method proposed by the present invention tends to be synchronized at 2.08 s. For Figure 5 , after the pre-parallel grid controller is put into operation, the output phase A voltage of the distributed energy inverter and the phase A voltage of the ship power grid under the pre-parallel grid method proposed by the present invention are synchronized within a limited time compared with the traditional pre-parallel grid control method. Due to the existence of the PI controller, the control time of the traditional pre-synchronization control method is longer.

[0168] Figure 5 shows the comparison diagram of the output current of the port distributed energy inverter under the traditional pre-parallel grid control method and the pre-parallel grid control method proposed by the present invention. It can be seen that under the traditional pre-parallel grid control method, the output current of the distributed energy inverter is significantly distorted during the grid connection process, that is, the grid connection of the distributed energy inverter will generate a significant grid connection impact current on the ship power grid, which is not conducive to the stable operation of the port integrated power supply system. However, the output current of the port distributed energy inverter under the pre-parallel grid control method proposed by the present invention has no obvious distortion. Compared with the traditional pre-parallel grid control method, the grid connection impact current generated on the ship power grid is smaller, which is more conducive to realizing the grid connection of port distributed energy to participate in the energy scheduling and load distribution of ships at berth.

[0169] This embodiment proposes a pre-parallel grid method for green port distributed energy. Through simulation experiments, the pre-parallel grid performance of the traditional pre-parallel grid control method and the pre-parallel grid control method proposed by the present invention is compared. The results show that the impact current generated when the port distributed energy is connected to the ship power grid under the pre-parallel grid control method proposed by the present invention is smaller, and at the same time, the pre-parallel grid speed and control accuracy of the port distributed energy are optimized, and the stability of the port distributed energy grid connection is improved.

[0170] The above content is the technical idea of the present invention. Those skilled in the art can make various corresponding changes, modifications, simplifications, and combinations according to the above-described technical solutions and ideas, and all changes, modifications, simplifications, and combinations are included in the protection scope of the claims of the present invention.

Claims

1. A pre-grid connection control method for distributed energy in a green port, characterized in that The method includes the following steps: S1: Calculate the virtual reactive power on the virtual reactance according to the voltage components of the dq coordinate axes on both sides of the distributed energy grid connection point; S2: Design a pre-grid connection controller based on intelligent self-learning PID control, and obtain the inverter error compensation angular frequency and the inverter error compensation voltage amplitude by controlling the virtual reactive power, specifically including: S21: Discretize the virtual reactive power expression: where ω(t + 1) is the inverter error compensation angular frequency at time t + 1; ω(t) is the inverter error compensation angular frequency at time t; E(t + 1) is the inverter error compensation voltage amplitude at time t + 1; E(t) is the inverter error compensation voltage amplitude at time t; Q V (t + 1) is the virtual reactive power at time t + 1; Q V (t) is the virtual reactive power at time t; h is the sampling period; S22: Perform compact-form dynamic linearization processing to obtain a compact-form local linearization data model: For the virtual reactive power discretization equation, when there exists a time-varying parameter called the pseudo-Jacobian matrix such that the virtual reactive power discretization equation is transformed into a compact-form locally linearized data model: wherein, is bounded for any time t; γ c (t) is a non-linear term; ΔQ V (t) = Q V (t) - Q V (t - 1); Δω(t + 1) = ω(t + 1) - ω(t); ΔE(t + 1) = E(t + 1) - E(t); S23: Calculate the pseudo-Jacobian matrix estimation law of the virtual reactive power: For γ c (t), the previous I / O information is used to estimate the current moment γ c (t) by adopting the time difference estimation algorithm: Among them, is estimated value; is estimated value; is the estimated value of γ c (t); η ∈ (0, 2] is the step size factor, aiming to make the control algorithm more general; μ > 0 is the weight factor; S24: Design an intelligent self-learning PID controller for the virtual reactive power: Define the output tracking error \(e(t)=Q Vr (t + 1)-Q V (t + 1)\). According to the equivalent feedback principle, and by introducing an error feedback term, we can obtain: where λ > 0 is a weight factor; Q Vr (t + 1) is the desired output virtual power; ρ ∈ (0, 2] is the step factor, which is used to limit the change of the input quantity; k p 、k i 、k d are learning gains; S3: Introduce the inverter error compensation angular frequency and the inverter error compensation voltage amplitude into the active frequency modulation control loop and the reactive power voltage regulation control loop in the virtual synchronous generator control algorithm respectively; S4: Realize pre-grid connection control by synchronizing the amplitude and phase of the output voltage of the distributed energy inverter with the amplitude and phase of the ship power grid voltage.

2. The green port distributed energy pre-grid connection control method according to claim 1, characterized in that In step S1, the specific process of calculating the virtual reactive power on the virtual reactance according to the voltage components of the dq coordinate axes on both sides of the distributed energy grid connection point includes: (1) Collect the three-phase voltages U 0a , U 0b , U 0c of the distributed energy inverter output and the three-phase voltages U ga , U gb , U gc of the ship power grid; respectively convert the three-phase voltages U 0a , U 0b , U 0c of the distributed energy inverter output and the three-phase voltages U ga , U gb , U gc of the ship power grid into voltage components U 0d , U 0q and U gd , U gq in the dq coordinate axis; (2) Assume that there is a virtual impedance between the ship's power grid and the port distributed energy. Equivalent the virtual impedance to a virtual reactance and calculate the virtual reactive power between the ship's power grid and the port distributed energy according to the voltage components U 0d 、U 0q and U gd 、U gq The expression is as follows: Among them, Q V is the virtual reactive power between the ship's power grid and the port distributed energy; X V is the virtual reactance; Δθ is the phase difference between the ship's power grid voltage and the output voltage of the port distributed energy inverter; U0 and U g are the effective values of the output voltage of the port distributed energy inverter and the ship's power grid voltage, respectively.

3. The method according to claim 1, characterized in that: The virtual reactive power discretization equation in step S21 satisfies: The partial derivatives of the equation with respect to the control inputs ω(t) and E(t) exist, are continuous and bounded; The equation satisfies the generalized Lipschitz condition, that is, for any \(t_1\neq t_2\), \(t_1,t_2\geq0\) and there is where \(b > 0\) is a positive constant; 4. The method according to claim 1, wherein: Step S21 specifically includes the following steps: S211: Establish a discrete-time nonlinear system: Among them, Q V (t) ∈ R represents the output of the system at time t, ω(t) ∈ R, E(t) ∈ R represent the inputs of the system at time t, m ζ and are two unknown positive integers; γ(…) : is a non - linear function unknown to the system; The partial derivatives of this system with respect to ω(t) and E(t) exist and are continuous; The equation satisfies the generalized Lipschitz condition, that is, for any \(t_1\neq t_2\), \(t_1,t_2\geq0\) and there is where \(b > 0\) is a positive constant; S212: The following two equations can be obtained from the virtual reactive power discretization equation: ξ(t) = Q V (t) - Q V (t - 1); Since the equation has a solution η(t); Let Can be obtained 5. The method according to claim 1, wherein: Step S22 specifically includes the following steps: S221: Establish a parameter estimation index function: S222: Differentiate both sides of the parameter estimation index function with respect to and set it to zero, then the pseudo-Jacobian matrix number estimation law can be obtained:

6. A pre-grid connection control method for distributed energy in a green port according to claim 1, characterized in that, In step S3, the specific process of introducing the inverter error compensation angular frequency and the inverter error compensation voltage amplitude into the active frequency modulation control loop and the reactive power voltage regulation control loop in the virtual synchronous generator control algorithm to realize pre-grid connection control includes: E = K Q (Q set -Q e ) + U0 + E(t); Among them, 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; D P is the damping coefficient; θ is the phase of the output reference voltage of the virtual synchronous generator; K Q is the reactive power voltage regulation coefficient; Q set is the set value of the virtual reactive power; Q e is the reactive power output by the virtual synchronous generator; E is the amplitude of the output reference voltage of the virtual synchronous generator.

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