Wind and wave combined power generation device and wind-wave-storage island micro-grid control method thereof

Abstract

The invention relates to a wind and wave combined power generation device and a wind-wave-storage island micro-grid control method thereof.The power generation device comprises a wind power unit, a wave energy unit and an energy coupling unit, and the wind power unit and the wave energy unit which are connected through a coupler both drive hydraulic motors to rotate and do work in a hydraulic transmission mode; the two are fixedly connected through a coupler to couple and superpose wind wave power, and energy is supplied to the island micro-grid through the energy conversion process of mechanical energy-hydraulic energy-mechanical energy-electric energy. The inertia supporting capacity of a rotating element is reserved through a wind wave storage multi-energy networking structure without a current converter, the volatility of wind energy and wave energy can be effectively reduced, the advantages of wind wave storage power response and supporting are coupled while the wind energy and the wave energy participate in island micro-grid frequency modulation, multi-energy joint participation in micro-grid frequency modulation is achieved, and the micro-grid frequency modulation efficiency is improved. And the stability and the survivability of the island micro-grid system are effectively improved.

Description

Technical Field

[0001] The present invention relates to a technology in the field of electric power systems, specifically a wind-wave combined power generation device and a wind-wave-storage island microgrid control method thereof. Background Art

[0002] Existing independent wind, wave and storage units can all adjust power output within a certain range to stabilize system frequency. Their frequency regulation capabilities vary in response speed and continuous working time. Limited by factors such as response speed, support depth, and power stability, a single energy storage network or wind-wave network solution cannot cope with the changing working environment of island microgrids, and it is difficult to ensure a stable and reliable energy supply. Summary of the invention

[0003] The present invention aims at addressing the shortcomings of the existing control methods, such as the lack of refined modeling of the island microgrid system, the unclear interaction mechanism of each unit, and the inability to consider the comprehensive operating performance of the system; the existing combined power generation device adopts the electrical side power coupling method, which not only increases the difficulty of power control, but also introduces the mechanical rotational inertia loss of the converter, which is not conducive to the stability of the system under the island environment; and the energy storage unit and the wind and wave combined power generation device have certain limitations in response speed and support depth, and it is difficult to undertake the frequency regulation task of the island microgrid alone. A wind and wave combined power generation device and a wind-wave-storage island microgrid control method thereof are proposed. The inertia support capacity of the rotating elements is retained through the wind-wave-storage multi-energy networking structure without an inverter, which can effectively reduce the volatility of wind energy and wave energy, so that it can participate in the frequency regulation of the island microgrid while coupling the advantages of wind and wave storage power response and support, so as to realize the joint participation of multiple energy sources in the microgrid frequency regulation, and effectively improve the stability performance and survivability of the island microgrid system.

[0004] The present invention is achieved through the following technical solutions:

[0005] The present invention relates to a wind-wave combined power generation device, comprising: a wind power unit, a wave energy unit and an energy coupling unit, wherein: the wind power unit and the wave energy unit connected by a coupling both adopt hydraulic transmission to drive a hydraulic motor to rotate and perform work, and the two are fixedly connected by a coupling to couple and superimpose wind and wave power, and supply energy to an island microgrid through an energy conversion process of mechanical energy-hydraulic energy-mechanical energy-electrical energy.

[0006] The coupling is a rotating workpiece with stiffness and damping, and its equivalent model is inertia-spring-damper, which realizes the rotation speed balance of the hydraulic motor by absorbing the torque difference on both sides through torsional deformation.

[0007] The wind-wave combined power generation device floats on the sea to capture wind and wave energy and convert it into electrical energy on site.

[0008] The present invention relates to a wind-wave-storage island microgrid control method based on the above-mentioned wind-wave combined power generation device. A microgrid system state prediction model is constructed for the frequency response state space model of the wind-wave-storage island microgrid system. When an over-limit occurs, the system state quantity is updated by predicting the optimal adjustment values ​​of the motor opening and droop coefficient in the future n steps and executing the first step instruction therein. When the frequency offset is restored to within the limit, the motor opening is no longer adjusted, and only the droop coefficient is adjusted.

[0009] The island microgrid system state space model includes:

[0010] ① State space equations of system frequency, motor opening and energy storage droop coefficient as well as

[0011] ②System frequency Where: P m , P b , P L , f are the output power of wind-wave combined power generation device, the output power of energy storage unit, the load demand power and the system frequency respectively; T m is the equivalent time constant of the hydraulic motor, H is the system moment of inertia, f0 and Δf are the frequency reference value and system frequency deviation, SOC and W b is the energy storage state of charge and capacity, ω out is the coupling speed; I is the identity matrix of the same dimension as matrix A, T s is the system sampling period, k is the sampling time. x, u, y represent the state variable, control variable and output variable respectively; A, B u , B d , C represent the state matrix, control input matrix, non-control input matrix and output matrix in discrete time domain, and the subscript c represents the corresponding matrix in continuous time domain.

[0012] The microgrid system state prediction model is specifically: Among them: Y(k+n|k) and U(k) are the output prediction sequence and control quantity sequence within the n-step prediction interval, respectively, S x , S u , S d They represent the state prediction matrix, the control quantity prediction matrix and the non-control quantity prediction matrix respectively, and Δ represents the difference of the state quantity within two sampling times. Technical Effects

[0013] The present invention exploits the complementary characteristics of wind-wave-storage multi-energy response speed and supporting depth, and couples the characteristics of rapid response of energy storage units and high-power and long-term output of wind-wave power generation units; conducts fine modeling of the state space of the island microgrid, clarifies the system variables and their interaction mechanisms that affect the comprehensive operation characteristics of the system, and selects key variables for precise constraints; constructs an MPC cost function that penalizes system frequency deviation, motor opening increment, and droop coefficient deviation, takes the minimum cost function as the system operation optimization target, and can take into account multiple control targets of power distribution and frequency optimization; designs adaptive cost functions under different scenarios, takes reducing the power margin difference and reducing frequency overshoot as the optimization targets, dynamically adjusts the size of the motor opening increment weight, and realizes balanced power distribution and dynamic frequency optimization of wind-wave-storage multi-power sources. Compared with the prior art, the present invention couples the advantages of wind-wave-storage multiple power sources in frequency support, broadens the time scale for the system to respond to microgrid frequency fluctuations, and improves the stability and survivability of the island microgrid; it can effectively consider the complex state constraints and operation constraints of the system, and take into account the multiple control objectives of power allocation and frequency optimization; it can adaptively adjust the absolute size of the weight of the motor opening increment according to the system frequency deviation, and when the frequency deviation decreases, increase the weight coefficient of the motor opening increment, and reduce the sensitivity of the wind-wave motor response frequency dynamic deviation, thereby achieving a rapid response of wind and wave power and effectively avoiding frequency overshoot; it can adaptively adjust the relative size of the motor opening increment weight according to the current power margin of the wind and waves, and the power source with a large weight will increase or decrease less power during the power change process, thereby reducing the power margin difference of the wind and wave unit and achieving balanced power distribution of multiple power sources. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a flow chart of the present invention;

[0015] Figure 2 It is a schematic diagram of an embodiment scenario;

[0016] Figure 3 It is a scene model diagram of an embodiment;

[0017] Figure 4 It is a schematic diagram of the embodiment system;

[0018] Figure 5 is a flow chart of an embodiment;

[0019] Figure 6 This is a schematic diagram of the frequency control model of the wind-wave combined power generation device;

[0020] Figure 7 Schematic diagram of adaptive weight change characteristics;

[0021] Figure 8 This is a schematic diagram comparing the frequency modulation performance of different networking solutions;

[0022] Fig. 9 This is a schematic diagram of wind, wave and storage jointly participating in the frequency regulation of the island microgrid system;

[0023] In the figure: (a) is the system frequency and the output power of each unit (b) is the motor opening and the energy storage droop coefficient;

[0024] Fig.10 This is a schematic diagram comparing the frequency modulation performance of different networking solutions when the wind and wave output is insufficient;

[0025] In the figure: (a) is the system frequency and (b) is the energy storage output power;

[0026] Fig.11 It is a schematic diagram of system frequency response characteristics under different control methods;

[0027] Fig.12 Schematic diagram of power output characteristics of wind-wave combined power generation device under different control methods;

[0028] Fig.13 It is a schematic diagram for comparing the system state quantities under fixed weight and adaptive weight;

[0029] In the figure: (a) is the system frequency comparison (b) is the motor opening change comparison;

[0030] Fig.14 Schematic diagram of adaptive weight change. DETAILED DESCRIPTION

[0031] like Figure 2 As shown, the application scenario of this embodiment, namely, the wind-wave-storage island microgrid system, includes: a wind-wave combined power generation device, an energy storage unit and an island load, wherein: the wind-wave combined power generation device collects wind and wave energy in the form of an offshore floating platform; the energy storage unit is connected to the AC bus after the inverter droop control, and together with the wind-wave combined power generation device, supplies energy for the island load.

[0032] like Figure 3 As shown, the wind-wave combined power generation device includes: a wind power unit and a wave energy unit connected thereto via a coupling ⑦, the coupling ⑦ is connected to a synchronous generator ⑧ to drive power generation, wherein: the wind power unit and the wave energy unit both use hydraulic transmission to supplement the kinetic energy of wind and waves, and supply energy to the island microgrid through an energy conversion process of mechanical energy-hydraulic energy-mechanical energy-electrical energy.

[0033] The wave energy unit comprises: a plurality of bidirectional hydraulic cylinders ① with one-way valves ② connected in parallel and a hydraulic motor ⑥ connected to a coupling ⑦, wherein: wave energy is supplemented to the hydraulic cylinder ① and drives the variable displacement hydraulic motor ⑥ through a rectifying circuit of the one-way valve ②.

[0034] An inflatable accumulator ③, a pressure relief valve ④ and a hydraulic tank ⑤ are provided between the bidirectional hydraulic cylinder ① and the hydraulic motor ⑥. The rapid changes in flow and pressure in the circuit are smoothed by compressing the internal air, thereby reducing output power fluctuations. When the pressure in the circuit exceeds the threshold set by the pressure relief valve, the excess energy is discharged from the system in the form of hydraulic energy.

[0035] The wind power unit comprises: a wind turbine ⑩, a hydraulic pump ⑨ and a variable displacement hydraulic motor ⑥ connected in sequence, wherein: the wind turbine ⑩ drives the fixed displacement hydraulic pump ⑨ to rotate and pump out hydraulic oil, which drives the variable displacement hydraulic motor after passing through the hydraulic circuit.

[0036] The coupling ⑦ is equivalent to an inertia-spring-damping system, which realizes the speed synchronization of the two hydraulic motors and the superposition of mechanical power.

[0037] The output power of the wind-wave combined power generation device Where: η is the energy transfer efficiency of the hydraulic motor, p is the hydraulic circuit pressure, V max is the maximum displacement of the hydraulic motor, S is the opening of the hydraulic motor, and the subscript i=1, 2 corresponds to the wind power unit and the wave energy unit.

[0038] like Figure 6 As shown, the output power of the wind-wave combined power generation device and the system frequency of the energy storage unit are specifically: Where: P m , P b , P L and f are the reference values ​​ΔS of the wind-wave combined power generation device based on the motor opening increment. * output power, energy storage unit output power, load demand power and system frequency; T m is the equivalent time constant of the hydraulic motor, H is the system moment of inertia, and s represents the differential link.

[0039] The active regulation means that when the system frequency f is disturbed, the mechanical power P of the system is controlled by adjusting the motor opening S and the energy storage droop coefficient m. m and battery power P b , thereby optimizing the dynamic response process of the frequency.

[0040] like Figure 4As shown, a wind-wave-storage island microgrid control system of a wind-wave combined power generation device involved in this embodiment includes: a DSQ controller connected to a state monitoring device and an execution device respectively, and the DSQ controller includes: a data storage module, a space matrix update module, a control determination module, a solution calculation module and an instruction update module, wherein: the state monitoring device collects system frequency, voltage, circuit pressure, flow, motor opening, coupling speed, and charge state and droop coefficient of the energy storage unit in real time in the wind-wave combined power generation device, and integrates it with the time series to form a discrete system state data sequence, and the data storage module stores the system state information according to time, and sends it to the controller according to the accuracy requirement. The system status information is transmitted, and the space matrix update module updates the weight matrix according to the transmitted status information and the preset weight adjustment function. The control judgment module selects the frequency modulation instruction to be executed according to the current frequency deviation value of the system and sends it to the solution calculation module. The solution calculation module converts the optimization constraint problem into a quadratic programming problem according to the updated weight matrix and the preset cost function and system constraints, and selects the first step increment of the control amount as the optimal increment. The instruction update module updates the reference instructions of the motor opening and the droop coefficient according to the solved optimal increment of the control amount. The execution device controls the servo mechanism and the electronic module to adjust the hydraulic motor opening and the energy storage droop coefficient according to the reference instruction information.

[0041] like Figure 1 As shown, this is a control method based on the above system in this embodiment, which controls the opening of the hydraulic motor of the wind-wave combined power generation device and the droop coefficient of the energy storage unit in the wind-wave-storage island microgrid system respectively. When the system frequency is disturbed, the optimal motor opening and droop coefficient increment are calculated and the hydraulic motor opening is actively adjusted to control the output power, control the coordinated output of multiple power sources, and realize the balanced distribution of wind-wave-storage power and dynamic optimization of system frequency. The specific steps include:

[0042] Step ① Model establishment: Establish a frequency response state space model based on system parameters;

[0043] Step ② System setup: Input the initial system state, adaptive weight setting function, system cost function, state constraints and operation constraints into the controller;

[0044] Step 3 Data collection: The status monitoring device collects the real-time operating status parameters of the system;

[0045] Step ④ parameter update: update the state space matrix and weight matrix according to the current state parameters;

[0046] Step ⑤ Algorithm solution: After the constrained optimization problem is converted, the optimal control increment of the motor opening and the droop coefficient is solved using the model predictive control algorithm;

[0047] Step ⑥ Instruction execution: adjust the hydraulic motor opening and energy storage droop coefficient according to the solution result;

[0048] Step ⑦ loop work: repeat ③-⑥ to achieve real-time control of the system.

[0049] The system cost function described in step ② is specifically: Among them: α, β, γ are penalty coefficients, weight coefficient Weight coefficient Among them: Δf1 and Δf2 are the frequency deviation reference points. When the system frequency is lower than the rated value, the wind and wave unit needs to increase its output. At this time, the power source with a high power margin increases more power output, so the weight of its motor adjustment amount is smaller; conversely, when the system frequency is higher than the rated value, the power source with a high power margin needs to have a larger weight. This reduces the margin gap between the wind energy unit and the wave energy unit.

[0050] As the frequency deviation decreases, the weights of ΔS1 and ΔS2 gradually increase. At this time, the sensitivity of the wind-wave combined power generation device to the frequency deviation decreases. At the same time, the relative size of the weights of the two is also adaptively adjusted according to the margin and frequency deviation to achieve a balanced distribution of wind and wave output power, such as Figure 7 shown.

[0051] The larger the penalty coefficient, the greater the penalty for the corresponding item. Reducing this value will bring greater benefits to reducing the "cost" of the system. The three items in the cost function represent the impact of dynamic frequency deviation, motor opening adjustment, and droop coefficient deviation on the overall performance of the system. Since the power response of the energy storage unit is positively correlated with the droop coefficient, in order to avoid over-response of the energy storage unit when the system frequency fluctuates slightly, the droop coefficient needs to be maintained near the reference value when the system is running stably. Therefore, when the droop coefficient deviation increases, the third penalty item can speed up the adjustment of the droop coefficient to the reference value.

[0052] The transformation of the constrained optimization problem described in step ⑤ means: considering that the rapid and large changes in the motor opening and droop coefficient will cause the output power to over-respond, thus affecting the system frequency stability, in addition, the controlled quantity and the speed of change are subject to certain restrictions. Combining the cost function and the constraints of various physical quantities, the system frequency transient process optimization problem can be transformed into a constrained optimization problem with the controlled quantity increment ΔU(x) as the optimization variable, specifically: Where: x′(k) is the system state quantity that is not defined as a control quantity, such as p i , λ, μ, etc., P b0 and R b0 is the rated output power and rated ramp rate of the energy storage unit, k p and k r is the correction factor for output power and ramp rate.

[0053] The output power is constrained by the state of charge SOC of the energy storage unit and is in the form of a piecewise linear function, specifically: Where: a, b are energy storage output constraint parameters.

[0054] The solution described in step ⑤ refers to: transforming the constrained optimization problem into a quadratic programming problem for solution. The specific transformation relationship is: Among them: U is the independent variable, H is the coefficient of the quadratic term, G is the coefficient of the linear term, satisfying Where: Q, R1, R2 are the weight matrices of frequency deviation, motor opening increment, and droop coefficient deviation, Ref is the reference value matrix, m ref is the reference value of the droop coefficient, y c is the system output vector.

[0055] After specific practical experiments, the RTLAB semi-physical simulation model of a typical island microgrid power system was established, including a wind and wave capture unit, a hydraulic transmission device, a synchronous generator, an energy storage unit and other equivalent loads. The RT-LAB OP7000 hardware simulation real-time simulator was used, and the AN706 controller sampled system frequency, power output, motor opening, and hydraulic system internal state signals. The model predictive control algorithm was implemented based on the FPGA development board of XLINX FPGA ZYNQ7020, and the simulation results were obtained by measuring with a TektronixMSO44 oscilloscope. A wind-wave-load-storage island microgrid power system was constructed based on an island in the South China Sea, and the parameters are shown in Table 1.

[0056] Table 1 Island microgrid power system parameters

[0057] The frequency regulation of the island microgrid system adopts the online model predictive control method. To ensure the rapidity and accuracy of the solution, the sampling step length T s Set it to 0.02s and control the time domain to 5 steps.

[0058] The constraints are selected from the real state constraints and operation constraints of the island microgrid system, and the sensitivity analysis of the cost function weight is performed to select the appropriate weight coefficient. The system constraints and weight settings are shown in Table 2.

[0059] Table 2 System state constraints and weight coefficients

[0060] Compared with wind-wave frequency regulation and single energy storage frequency regulation, the transient and steady-state characteristics of the frequency regulation of the island microgrid with the coupled wind-wave-storage unit are improved. In order to compare the system operation characteristics of different networking schemes, the frequency regulation effects of the three networking schemes are compared and analyzed under the same operating parameters and system constraints.

[0061] The wind and wave inputs of the wind-wave combined power generation device are: mean 8m / s, variance 0.25m 2 / s 2 The wave force has a period of 2πs and an amplitude of 400kN. When the system load demand increases by 20kW (accounting for 25% of the installed capacity) within 1s, the system frequency response characteristics of the three networking schemes of wind-wave-storage combined frequency regulation, wind-wave combined frequency regulation and single energy storage droop frequency regulation are as follows: Figure 8 shown.

[0062] Individual wind-wave frequency modulation control can restore the system frequency to the rated value when the wind and wave energy is sufficient, but the long mechanical adjustment response time worsens the transient process of frequency recovery; individual energy storage droop control can respond quickly to frequency changes, but there is a difference between the steady-state operating point of the adjusted system frequency and the rated value, and the energy storage unit needs to output continuously, which has high requirements for capacity configuration and charge state.

[0063] Compared with wind-wave frequency modulation and energy storage frequency modulation, the present invention shows better performance in frequency recovery transient process and reducing energy storage output, reducing the maximum frequency deviation by 89.3% and 51.9% respectively. In the stage of rapid frequency drop, the energy storage unit quickly outputs to ensure that the lowest frequency point does not exceed the limit. At the same time, the wind-wave unit responds to the frequency change and increases the output power by adjusting the motor opening. As the system frequency recovers, the energy storage gradually exits operation, and the droop coefficient gradually decreases to the rated value to improve the system's anti-interference ability, such as Fig. 9 shown.

[0064] In addition, when the wind and wave power is insufficient, the wind and wave units output at full power, and the power gap is supported by the energy storage unit to maintain the system frequency stability to the greatest extent. The test simulates a scenario where the wind and wave input is reduced to 50% of the current at a certain moment. At this time, even if the hydraulic motor runs at full power, the output of the wind and waves is still not enough to meet the load demand.

[0065] The frequency modulation performance of the three networking solutions is as follows: Fig.10As shown. The frequency transient fluctuation stage of the separate wind-wave frequency modulation system is the process in which the gas-filled accumulator slowly releases energy to maintain stable power output. After a period of time, the system enters a steady state, but there are still periodic frequency fluctuations, which are caused by the periodic changes in wave force input. At this time, the hydraulic motor of the combined power generation unit works at full power, and the wind and wave units no longer have frequency modulation capabilities. After the wind and wave output of the separate energy storage droop frequency modulation system decreases, the energy storage unit further increases the output power, and the frequency of the island microgrid reaches a new steady-state operating point, but it causes the steady-state frequency deviation to further expand and the energy storage SOC to drop rapidly. In contrast, the present invention has a higher power output capacity and can adjust the system power output within a wider time scale range. The maximum steady-state frequency deviation is reduced by 98.2% and 71.4%, respectively, and the time to restore the steady state is reduced by 95.7% and 80%. The volatility of wind and wave input power will also have an impact on the frequency of the combined power generation system, but the fast power response characteristics of the energy storage unit effectively smooth out the frequency fluctuations. As the output capacity of wind, waves and storage further decreases, the frequency deviation of the microgrid will not be able to be maintained within the limit. At this time, non-essential equipment can be shut down to reduce system power imbalance.

[0066] Further comparison is made under the same system parameters and constraints, and the variation characteristics of system frequency and wind-wave combined power generation unit power output under different PI parameters are compared, as shown in Table 3.

[0067] Table 3 PI parameter settings

[0068] The system frequency response curves under different control methods and control parameters are as follows: Fig.11 As shown. As the proportional gain increases, the frequency response speed continues to increase, but too large a proportional gain will cause frequency overshoot; comparing the frequency modulation results of the present invention and PI1, the present invention reduces the maximum frequency deviation by 53.6% and the frequency recovery time by 66% compared with the hybrid frequency modulation method.

[0069] The performance difference between the two control methods is mainly caused by the different control speed and accuracy of the output power of the combined power generation unit, such as Fig.12 As shown, the response speed of the output power corresponds to the frequency dynamic characteristics. The faster the power response, the faster the corresponding frequency control transient process and the higher the lowest frequency point.

[0070] By further comparing the system operation characteristics under the adaptive weight and fixed weight cost functions, we focus on the indicators such as frequency recovery time, frequency overshoot and margin difference change. The results are as follows: Fig.13 As shown in Table 4:

[0071] Compared with the model predictive control using a fixed weight cost function, the control method using adaptive weights reduces the maximum frequency deviation by 7% and the frequency recovery time by 60%, and avoids frequency overshoot; at the same time, during the transient process of frequency regulation, the motor opening difference that measures the wind and wave power margin is reduced by 63%, verifying that the output power of the wind and wave unit is allocated according to the margin during the transient process. In this process, the weight change process of ΔS1 and ΔS2 is as follows Fig.14 shown.

[0072] When the system frequency decreases, the weights of ΔS1 and ΔS2 decrease, the sensitivity of the motor opening change to frequency deviation increases, and wind energy and wave energy can respond quickly to frequency changes; at the same time, the weight of the wave energy unit with a larger margin decreases to a greater extent, ensuring that it is allocated more power output indicators during the transient process, thereby narrowing the power margin difference between the wind power unit and the wave energy unit; as the system frequency returns to the rated value, the weights of ΔS1 and ΔS2 increase, and the sensitivity of the combined power generation unit to frequency deviation decreases, avoiding excessive power regulation leading to system frequency overshoot.

[0073] Experiment 1: Comparison of different networking solutions

[0074] Table 4 Performance comparison of different networking solutions (sufficient wind and wave energy)

[0075] Table 5 Performance comparison of different networking solutions (insufficient wind and wave energy)

[0076] Experiment 2: Comparison of different control methods

[0077] Table 6 Performance comparison of different control methods

[0078] Experiment 3: Comparison between adaptive weight and fixed weight control

[0079] Table 7 Comparison of adaptive weight and fixed weight control performance

[0080] In summary, the present invention can realize the joint participation of multiple energy sources in microgrid frequency regulation, and effectively improve the stability and survivability of the island microgrid system.

[0081] The above-mentioned specific implementation can be partially adjusted in different ways by those skilled in the art without departing from the principle and purpose of the present invention. The protection scope of the present invention shall be based on the claims and shall not be limited by the above-mentioned specific implementation. Each implementation scheme within its scope shall be subject to the constraints of the present invention.

Claims

1. A wind and wave combined power generation device, It is characterized in that include: Wind power unit, wave energy unit and energy coupling unit, wherein: the wind power unit and wave energy unit connected by a coupling both use hydraulic transmission to drive the hydraulic motor to rotate and do work, and the two are fixedly connected by a coupling equivalent to an inertia-spring-damping system to couple and superimpose wind and wave power, and supply energy to the island microgrid through the energy conversion process of mechanical energy-hydraulic energy-mechanical energy-electrical energy; The output power of the wind-wave combined power generation device Where: η is the energy transfer efficiency of the hydraulic motor, p is the hydraulic circuit pressure, V max is the maximum displacement of the hydraulic motor, S is the opening of the hydraulic motor, and the subscript i=1, 2 corresponds to the wind power unit and the wave energy unit.

2. The wind-wave combined power generation device according to claim 1, Its characteristics are: The wave energy unit comprises: a plurality of bidirectional hydraulic cylinders with one-way valves connected in parallel and a hydraulic motor connected to a coupling, wherein: wave energy is collected to the hydraulic cylinder and driven to drive a variable displacement hydraulic motor through a rectifying circuit of the one-way valve; The wind power unit comprises: a wind turbine, a hydraulic pump and a variable displacement hydraulic motor connected in sequence, wherein: the wind turbine drives the fixed displacement hydraulic pump to rotate and pump out hydraulic oil, which drives the variable displacement hydraulic motor after passing through the hydraulic circuit.

3. The wind-wave combined power generation device according to claim 2, Its characteristics are: An inflatable accumulator, a pressure relief valve and a hydraulic tank are provided between the bidirectional hydraulic cylinder and the hydraulic motor. The rapid changes in flow and pressure in the circuit are smoothed by compressing the internal air, thereby reducing output power fluctuations. When the pressure in the circuit exceeds the threshold set by the pressure relief valve, the excess energy is discharged from the system in the form of hydraulic energy.

4. The wind-wave combined power generation device according to claim 1, Its characteristics are: The output power of the wind-wave combined power generation device and the system frequency of the energy storage unit are specifically: Where: P m , P b , P L and f are the reference values ​​ΔS of the wind-wave combined power generation device based on the motor opening increment. * output power, energy storage unit output power, load demand power and system frequency; T m is the equivalent time constant of the hydraulic motor, H is the moment of inertia of the system, and s represents the differential link; The active regulation means that when the system frequency f is disturbed, the mechanical power P of the system is controlled by adjusting the motor opening S and the energy storage droop coefficient m. m and battery power P b , thereby optimizing the dynamic response process of the frequency.

5. A method for controlling a wind-wave-storage island microgrid based on the wind-wave combined power generation device according to any one of claims 1 to 4, It is characterized in that A microgrid system state prediction model is constructed based on the frequency response state space model of the wind-wave-storage island microgrid system. When an over-limit occurs, the system state quantity is updated by predicting the optimal adjustment values ​​of the motor opening and the droop coefficient in the next n steps and executing the first step instruction. When the frequency offset returns to within the limit, the motor opening is no longer adjusted and only the droop coefficient is adjusted.

6. The wind-wave-storage island microgrid control method according to claim 5, Its characteristics are: The island microgrid system state space model includes: ① State space equations of system frequency, motor opening and energy storage droop coefficient as well as ②System frequency Where: P m , P b , P L , f are the output power of wind-wave combined power generation device, the output power of energy storage unit, the load demand power and the system frequency respectively; T m is the equivalent time constant of the hydraulic motor, H is the system moment of inertia, f 0 , Δf is the frequency reference value and system frequency deviation, SOC, W b is the energy storage state of charge and capacity, ω out is the coupling speed; I is the identity matrix of the same dimension as matrix A, T s is the system sampling period, k is the sampling time, x, u, y represent the state variable, control variable and output variable respectively; A, B u , B d , C represent the state matrix, control input matrix, non-control input matrix and output matrix in discrete time domain, and the subscript c represents the corresponding matrix in continuous time domain.

7. The wind-wave-storage island microgrid control method according to claim 5, Its characteristics are: The microgrid system state prediction model is specifically: Among them: Y(k+n|k) and U(k) are the output prediction sequence and control quantity sequence within the n-step prediction interval, respectively, S x , S u , S d They represent the state prediction matrix, the control quantity prediction matrix and the non-control quantity prediction matrix respectively, Δ represents the difference of the state quantity within two sampling times, 8. The wind-wave-storage island microgrid control method according to any one of claims 5 to 7, Its characteristics are that include: Step ① Model establishment: Establish a frequency response state space model based on system parameters; Step ② System setup: Input the initial system state, adaptive weight setting function, system cost function, state constraints and operation constraints into the controller; Step 3 Data collection: The status monitoring device collects the real-time operating status parameters of the system; Step ④ parameter update: update the state space matrix and weight matrix according to the current state parameters; Step ⑤ Algorithm solution: After the constrained optimization problem is converted, the optimal control increment of the motor opening and the droop coefficient is solved using the model predictive control algorithm; Step ⑥ Instruction execution: adjust the hydraulic motor opening and energy storage droop coefficient according to the solution result; Step ⑦ loop work: repeat ③-⑥ to achieve real-time control of the system.

9. The wind-wave-storage island microgrid control method according to claim 8, Its characteristics are: The system cost function described in step ② is specifically: Among them: α, β, γ are penalty coefficients, weight coefficient Weight coefficient Where: Δf 1 and Δf 2 It is the frequency deviation reference point. When the system frequency is lower than the rated value, the wind and wave unit needs to increase its output. At this time, the power source with a high power margin increases more power output, so the weight of its motor adjustment amount is smaller. Conversely, when the system frequency is higher than the rated value, the power source with a high power margin needs to have a larger weight, thereby reducing the margin gap between the wind energy unit and the wave energy unit.

10. The wind-wave-storage island microgrid control method according to claim 8, Its characteristics are: The conversion of the constrained optimization problem described in step ⑤ means: considering that the rapid and large changes in the motor opening and the droop coefficient will cause the output power to over-respond, thereby affecting the system frequency stability, in addition, the controlled quantity and the speed of change are both subject to certain restrictions. Combining the cost function and the constraints of various physical quantities, the system frequency transient process optimization problem is converted into a constrained optimization problem with the controlled quantity increment ΔU(x) as the optimization variable, specifically: Where: x′(k) is the system state quantity that is not defined as a control quantity, such as p i , λ, μ, etc., P b0 and R b0 is the rated output power and rated ramp rate of the energy storage unit, k p and k r is the correction factor for output power and climbing rate; The solution described in step ⑤ refers to: transforming the constrained optimization problem into a quadratic programming problem for solution. The specific transformation relationship is: Among them: U is the independent variable, H is the coefficient of the quadratic term, G is the coefficient of the linear term, satisfying Where: Q, R 1 , R 2 are the weight matrices of frequency deviation, motor opening increment, and droop coefficient deviation, Ref is the reference value matrix, m ref is the reference value of the droop coefficient, y c is the system output vector.

11. The wind-wave-storage island microgrid control method according to claim 8, Its characteristics are: The output power is constrained by the state of charge SOC of the energy storage unit and is in the form of a piecewise linear function, specifically: Where: a, b are energy storage output constraint parameters.

12. A wind-wave-storage island microgrid control system for a wind-wave combined power generation device implementing the method described in any one of claims 5 to 11, It is characterized in that include: The DSQ controller is connected to the state monitoring device and the execution device respectively, and the DSQ controller includes: a data storage module, a space matrix update module, a control judgment module, a solution calculation module and an instruction update module, wherein: the state monitoring device collects system frequency, voltage, circuit pressure, flow, motor opening, coupling speed and charge state, droop coefficient and other information of the energy storage unit in real time, and integrates with the time series to form a discrete system state data sequence, the data storage module stores the system state information according to time, and transmits the system state information to the controller according to the accuracy requirement, and the space matrix update module collects the system state information according to the transmission. The input status information and the preset weight adjustment function update the weight matrix. The control judgment module selects the frequency modulation instruction to be executed according to the current frequency deviation value of the system and sends it to the solution calculation module. The solution calculation module converts the optimization constraint problem into a quadratic programming problem according to the updated weight matrix and the preset cost function and system constraints, and selects the first step increment of the control amount as the optimal increment. The instruction update module updates the reference instructions of the motor opening and the droop coefficient according to the solved optimal increment of the control amount. The execution device controls the servo mechanism and the electronic module to adjust the hydraulic motor opening and the energy storage droop coefficient according to the reference instruction information.

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