Semi-physical simulation method and system for wind-solar coupled hydrogen production system

Abstract

The invention relates to a semi-physical simulation method and system for a wind-solar coupled hydrogen production system. The method comprises the following steps: constructing a simulation model of the wind-solar coupled hydrogen production system, compiling the simulation model, loading the compiled simulation model into a hardware simulation device of a semi-physical simulation platform, simulating a steady-state working condition or an unsteady-state working condition of the wind-solar coupled hydrogen production system, and controlling the simulation model to operate in the hardware simulation device. The output of the simulation model is sent to the physical converter and the controller through the power amplifier connected with the hardware simulation device, the output of the physical converter and the controller is collected by the signal collection device and is sent back to the simulation model, and the oscilloscope collects simulation data of the simulation model in real time. And analyzing the stability and accuracy of the simulation model according to the simulation data of the simulation model under the steady-state working condition and / or the non-steady-state working condition. According to the method, powerful model support and technical guarantee can be provided for optimal design and reliable operation of the wind-solar coupled hydrogen production system.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of renewable energy hydrogen production, and particularly relates to a semi-physical simulation method for a wind-solar coupling hydrogen production system. BACKGROUND

[0002] As a key carrier for the conversion of renewable energy and hydrogen energy, the wind-solar coupling hydrogen production system can effectively suppress the volatility of new energy output and improve energy utilization efficiency by integrating wind power, photovoltaic power generation, energy storage and water electrolysis hydrogen production technology, and has important significance for building a clean and low-carbon energy system. However, the existing technology still faces problems such as insufficient model accuracy and dynamic response, insufficient description of multi-time scale coupling mechanism in semi-physical simulation technology, and limitations of economic optimization.

[0003] At present, the modeling and simulation method for the wind-solar coupling hydrogen production system mainly regards the unit as an electrical system for studying electrical quantities, and has not yet solved the technical bottlenecks such as insufficient dynamic response accuracy of traditional wind-solar coupling hydrogen production model under complex working conditions, energy efficiency decline and equipment life shortening of hydrogen production system caused by wind-solar fluctuation, and insufficient description of multi-time scale coupling mechanism in semi-physical simulation. SUMMARY

[0004] Therefore, the embodiments of the present application aim to provide a semi-physical simulation method for a wind-solar coupling hydrogen production system, which can solve the technical bottlenecks such as insufficient dynamic response accuracy of traditional wind-solar coupling hydrogen production model under complex working conditions, energy efficiency decline and equipment life shortening of hydrogen production system caused by wind-solar fluctuation, and insufficient description of multi-time scale coupling mechanism in semi-physical simulation.

[0005] In one aspect, the present application provides a semi-physical simulation method for a wind-solar coupling hydrogen production system, comprising the following steps:

[0006] constructing a simulation model of the wind-solar coupling hydrogen production system, the wind-solar coupling hydrogen production system comprising a wind power generation device, a photovoltaic power generation device, an energy storage device and a hydrogen production device;

[0007] building a semi-physical simulation platform, the semi-physical simulation platform comprising a compiling control system, a hardware simulation device, a power amplifier, a physical converter and a controller, a signal acquisition device and an oscilloscope, and using the compiling control system to compile the simulation model and load it into the hardware simulation device;

[0008] The compiling control system simulates the steady state or non-steady state of the wind-solar coupled hydrogen production system, controls the simulation model to run in the hardware simulation device, the output of the simulation model is sent to the physical converter and controller through the power amplifier connected with the hardware simulation device, the output of the physical converter and controller is collected by the signal collection device and fed back to the simulation model, and the oscilloscope collects the simulation data of the simulation model in real time.

[0009] According to the simulation data of the simulation model under the steady state and / or non-steady state, the stability and accuracy of the simulation model are analyzed.

[0010] Further, the simulation model of the wind power generation device comprises:

[0011]

[0012] In the formula, P wind represents the mechanical conversion power of the wind power generation device, ρ represents the air density, R represents the impeller radius, v w represents the wind speed, C p (λ,β) represents the fan blade efficiency coefficient; λ i represents the intermediate variable parameter, λ represents the tip speed ratio, β represents the pitch angle; ω represents the rotor angular velocity.

[0013] Further, the simulation model of the photovoltaic power generation device comprises:

[0014]

[0015] C1=exp(-U m / C2U oc )×(1-I m / I sc ),

[0016]

[0017] dU=βdT-R s dI,

[0018] In the formula, U, I and T represent the output voltage, output current and temperature of the photovoltaic power generation device respectively, U oc and I sc represent the open circuit voltage and short circuit current of the photovoltaic power generation device respectively; α and β represent the current and voltage temperature change coefficients respectively; U m and I m represent the voltage and current of the maximum power point of the photovoltaic power generation device; N p and N srespectively represent the number of parallel and series of photovoltaic components in the photovoltaic power generation device; R s represents the photovoltaic series resistance, G and G ref respectively represent the solar radiation intensity and the solar radiation intensity rating; T c and T ref respectively represent the current ambient temperature and the temperature rating.

[0019] Further, the simulation model of the energy storage device includes:

[0020]

[0021] In the formula, E(t) represents the remaining power of the energy storage device at time t; E(t-1) represents the remaining power of the energy storage device at the last time; represents the self-discharge rate of the energy storage device; P N represents the charge-discharge power of the energy storage device, and δ represents the charge-discharge efficiency of the energy storage device; T N represents the charge-discharge time of the energy storage device; E n represents the rated capacity of the energy storage device, and SOC represents the state of charge of the energy storage battery.

[0022] Further, the hydrogen production device includes an alkaline electrolytic cell, and a simulation model of the alkaline electrolytic cell includes:

[0023] (1) The output voltage U cell of the alkaline electrolytic cell is:

[0024]

[0025] In the formula, r1 and r2 represent the ohmic resistance parameters of the electrolyte; T el represents the temperature in the tank; A cell represents the area of the electrolysis module; I el represents the direct current; s n and t n represent the overvoltage coefficient, wherein subscript n=1, 2, 3; U rev represents the inverse voltage of the alkaline electrolytic cell;

[0026] (2) The ohmic overvoltage U om,alk generated by the electrolysis reaction of the alkaline electrolytic cell is:

[0027] U om,alk = R om,alk I el ,

[0028] In the formula, R om,alk represents the ohmic resistance;

[0029] (3) the open-circuit voltage U of the alkaline electrolyzer ∞ is:

[0030]

[0031] wherein E0 is the theoretical electromotive force; T el represents the temperature in the cell; R0 represents the gas constant; and respectively represent the partial pressure of oxygen and hydrogen; represents the water activity between the membrane and the electrode;

[0032] (4) the hydrogen production rate of the alkaline electrolyzer comprises:

[0033]

[0034] wherein, represents the molar hydrogen production rate; η F represents the Faraday efficiency; a n represents the Faraday efficiency coefficient, wherein n = 1, 2, 3, 4, 5; N el represents the number of electrolytic cells connected in series in the alkaline electrolyzer.

[0035] Further, the hydrogen production device comprises a PEM electrolyzer, and a simulation model of the PEM electrolyzer comprises:

[0036] (1) the anode dynamic equation of the PEM electrolyzer is:

[0037]

[0038] wherein, and respectively represent the net oxygen production rate and the net water production rate on the anode side, and respectively represent the molar flow rate of oxygen flowing into and out of the anode; respectively represent the molar flow rate of water flowing into and out of the anode, wherein, is equal to zero; and respectively represent the electro-osmotic and diffusion flow rates; O 2g represents the oxygen flow rate of the anode;

[0039] (2) the cathode dynamic equation of the PEM electrolyzer is:

[0040]

[0041] wherein, and respectively represent the net oxygen production rate and the net water production rate on the cathode side, and represents the molar flow rate of hydrogen and water flowing into the cathode; and represents the molar flow rate of hydrogen and water flowing out of the cathode, respectively; and represents the electro-osmotic flow rate and the diffusion flow rate of hydrogen from the anode electrode through the proton exchange membrane, respectively; H 2g represents the hydrogen gas generated by the cathode;

[0042] (3) the activation overvoltage V el.act of the PEM electrolyzer is:

[0043]

[0044] wherein R is the gas constant; F is the Faraday constant; μ represents the transfer coefficient; T el represents the temperature in the cell; i md represents the current density, i0represents the exchange current density;

[0045] (4) the ohmic overvoltage V om,pem and the membrane resistance R om,pem of the PEM electrolyzer are:

[0046] V om,pem = i md R om,pem ,

[0047]

[0048] wherein R om,pem represents the ohmic resistance of the PEM electrolyzer; t em represents the thickness of the proton exchange membrane; σ em represents the membrane conductivity;

[0049] (5) the temperature model of the PEM electrolyzer comprises:

[0050]

[0051] wherein C stack represents the heat capacity of the PEM electrolyzer; T stack represents the outlet temperature of the PEM electrolyzer; T ex,h represents the inlet temperature of the PEM electrolyzer; q 1y represents the mass flow rate of the electrolyte; c 1y represents the specific heat capacity of the electrolyte, Q ele represents the heat generation power of the electrolyzer, Q dis stack represents the heat dissipated by the electrolyzer to the environment.

[0052] Further, the hydrogen production and heat generation power model of the hydrogen production device is a unified operation model as follows:

[0053]

[0054] In the formula: And Pi(t) is the input power and hydrogen production power of the electrolyzer mold i at time t; Si(t) is the running state of the electrolyzer mold i at time t, 1 represents running, and 0 represents stopping; Qi(t) is the heat production power of the electrolyzer mold i at time t; Pi(t) is the input power unit value of the electrolyzer mold i at time t; Ti(t) is the running temperature of the electrolyzer mold i at time t; And is the correlation coefficient obtained by experiment related to the electrolyzer type and the input power unit value range.

[0055] Further, the hydrogen production device includes an alkaline electrolyzer and a PEM electrolyzer, and the alkaline electrolyzer and the PEM electrolyzer work in coordination;

[0056] The coordination operation strategy of the alkaline electrolyzer and the PEM electrolyzer includes:

[0057] The load adjustment range of the alkaline electrolyzer is 20%-110%, and the alkaline electrolyzer runs at ≥80% rated power in a stable power supply period to bear the basic load; the load range of the PEM electrolyzer is 3%-135%, and the PEM electrolyzer quickly adjusts in the wind and light output fluctuation period to respond to fluctuating load, covering the low load below 20% and the excess rated power interval that the alkaline electrolyzer cannot respond to;

[0058] The capacity ratio of the alkaline electrolyzer and the PEM electrolyzer includes:

[0059]

[0060] In the formula: R ALK And R PEM are the capacities of the alkaline electrolyzer and the PEM electrolyzer respectively; M min And M max are the upper and lower limits of the proportion of the capacity of the PEM electrolyzer to the total electrolyzer capacity.

[0061] Further, the compiling control system is an RT-LAB simulation system, the hardware simulation device is an OPAL-RT OP5700 simulator, and the signal acquisition device is an NIPXIe-1071 case;

[0062] According to the simulation data of the simulation model under the steady state working condition, the stability and accuracy of the simulation model are analyzed, including:

[0063] Perform short-term fluctuation and long-term dynamic analysis on the electrical waveform data and hydrogen production data of the simulation model under the steady state condition and / or the non-steady state condition to obtain short-term fluctuation analysis data and long-term dynamic analysis data.

[0064] Compare the short-term fluctuation analysis data and the long-term dynamic analysis data with a traditional model to determine the stability and accuracy of the simulation model.

[0065] In another aspect, the embodiment of the present application also provides a wind-solar coupling hydrogen production system semi-physical simulation system, comprising:

[0066] A model construction module is configured to construct a simulation model of the wind-solar coupling hydrogen production system, wherein the wind-solar coupling hydrogen production system comprises a wind power generation device, a photovoltaic power generation device, an energy storage device and a hydrogen production device.

[0067] A semi-physical simulation platform comprises a compiling control system, a hardware simulation device, a power amplifier, a physical converter and a controller, a signal acquisition device and an oscilloscope. The simulation model is compiled and loaded into the hardware simulation device by using the compiling control system. The compiling control system simulates a steady state condition or a non-steady state condition of the wind-solar coupling hydrogen production system and controls the simulation model to run in the hardware simulation device. The output of the simulation model is sent to the physical converter and the controller through the power amplifier connected with the hardware simulation device. The output of the physical converter and the controller is collected by the signal acquisition device and fed back to the simulation model. The simulation data of the simulation model is collected by the oscilloscope in real time.

[0068] An analysis module is configured to analyze the stability and accuracy of the simulation model according to the simulation data of the simulation model under the steady state condition and / or the non-steady state condition.

[0069] Compared with the prior art, the embodiment of the present application can achieve at least one of the following beneficial effects:

[0070] The embodiment of the present application constructs an electrolytic cell refined model based on RT-LAB, reduces dynamic error and significantly improves dynamic response accuracy.

[0071] The embodiment of the present application realizes real-time interactive simulation of second-level wind-solar output fluctuation and hour-level hydrogen storage tank pressure change through OPAL-RT OP5700 multi-core parallel computing, shortens the step to 20 ms and breaks through the multi-time scale collaborative simulation capability.

[0072] The embodiment of the present application simulates extreme wind-solar fluctuation through a semi-physical simulation platform, verifies the reduction of energy storage system response delay, the reduction of active power fluctuation amplitude and the extension of equipment life, and realizes system stability and reliability verification.

[0073] The wind-solar coupling hydrogen production system semi-physical simulation method provided by the embodiment of the application can provide data support for capacity configuration and control parameter setting of the wind-solar coupling hydrogen production system through high-precision simulation results, improve wind-solar utilization, and realize engineering application value improvement.

[0074] The embodiment of the application solves the bottleneck of traditional semi-physical simulation in dynamic response, multi-time scale coupling and cost optimization through high-precision modeling, real-time simulation and economical control strategy, and provides reliable technical support for engineering application of the wind-solar coupling hydrogen production system.

[0075] The above technical solutions can be combined with each other to realize more preferred combination solutions. Other features and advantages of the application will be described in the subsequent specification, and some advantages will become apparent from the specification or be understood by implementing the application. The purpose and other advantages of the application can be realized and obtained from the contents specifically indicated in the specification and the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0076] The accompanying drawings are included to provide a further understanding of the embodiments, and are incorporated in and constitute a part of this specification, illustrate embodiments of the application, and together with the description serve to explain the principles of the application. In the drawings:

[0077] Figure 1 The flow chart of the wind-solar coupling hydrogen production system semi-physical simulation method of the embodiment of the application.

[0078] Figure 2 The composition schematic diagram of the semi-physical simulation platform of the embodiment of the application.

[0079] Figure 3 The construction schematic diagram of the simulation model of the wind-solar coupling hydrogen production system of the embodiment of the application.

[0080] Figure 4 The coupling structure schematic diagram of the wind-solar coupling hydrogen production system semi-physical simulation of the embodiment of the application.

[0081] Figure 5 The three-phase alternating voltage simulation schematic diagram of the wind power generation device and the photovoltaic power generation device incorporated into the grid side of the embodiment of the application.

[0082] Figure 6 The three-phase alternating current simulation schematic diagram of the wind power generation device and the photovoltaic power generation device of the embodiment of the application.

[0083] Figure 7 The total power simulation schematic diagram of the wind power generation device and the photovoltaic power generation device output of the embodiment of the application.

[0084] Figure 8 The direct current voltage simulation schematic diagram of the input hydrogen production device of the embodiment of the application.

[0085] Figure 9 A power and single cell voltage simulation comparison chart for the alkaline electrolyzer of the embodiment of the present application.

[0086] Figure 10 A power and single cell voltage simulation comparison chart for the PEM electrolyzer of the embodiment of the present application.

[0087] Figure 11 A hydrogen storage tank pressure simulation chart for the hydrogen production device of the embodiment of the present application.

[0088] Figure 12 A hydrogen production device AC side voltage and current waveform chart under stable working conditions of the embodiment of the present application.

[0089] Figure 13 A hydrogen production device active and reactive power waveform chart under unstable working conditions of the embodiment of the present application.

[0090] Figure 14 A hydrogen production device active and reactive power waveform chart under unstable working conditions of the conventional simulation model.

[0091] Figure 15 A hydrogen production device voltage and current waveform chart under unstable working conditions of the embodiment of the present application.

[0092] Figure 16 A hydrogen production device voltage and current power waveform chart under unstable working conditions of the conventional simulation model.

[0093] Figure 17 A time-hydrogen production amount curve comparison chart of the embodiment of the present application.

[0094] Figure 18 A composition schematic diagram of the wind-solar coupling hydrogen production system semi-physical simulation system of the embodiment of the present application. DETAILED DESCRIPTION

[0095] The preferred embodiments of the present application will be specifically described below in conjunction with the accompanying drawings, wherein the drawings form a part of the present application and are used to explain the principles of the embodiments of the present application, but are not used to limit the scope of the present application.

[0096] Embodiment one:

[0097] Figure 1 A flowchart of the wind-solar coupling hydrogen production system semi-physical simulation method of the embodiment of the present application. As shown in the figure, Figure 1 the present application provides a wind-solar coupling hydrogen production system semi-physical simulation method including steps S101 to S104.

[0098] Step S101, a simulation model of the wind-solar coupling hydrogen production system is constructed, the wind-solar coupling hydrogen production system includes a wind power generation device, a photovoltaic power generation device, an energy storage device and a hydrogen production device.

[0099] Step S102, a semi-physical simulation platform is built, the semi-physical simulation platform includes a compiling control system, a hardware simulation device, a power amplifier, a physical converter and a controller, a signal acquisition device and an oscilloscope, the simulation model is compiled by using the compiling control system and loaded into the hardware simulation device;

[0100] Step S103, the compiling control system simulates the steady state condition or the non-steady state condition of the wind-solar coupling hydrogen production system, and controls the simulation model to run in the hardware simulation device, the output of the simulation model is sent into the physical converter and the controller through the power amplifier connected with the hardware simulation device, the output of the physical converter and the controller is collected by the signal acquisition device and fed back to the simulation model, and the simulation data of the simulation model is collected by the oscilloscope in real time;

[0101] Step S104, according to the simulation data of the simulation model under the steady state condition and / or the non-steady state condition, the stability and accuracy of the simulation model are analyzed.

[0102] In the embodiment and some embodiments of the application, the subsystems of the wind-solar coupling hydrogen production system such as the wind power generation device, the photovoltaic power generation device, the energy storage device, the hydrogen production device (including the alkaline electrolytic cell and the PEM electrolytic cell) and the like are simulated and modeled by using the aerodynamic model, the photovoltaic array model, the state of charge (SOC) model, the electrochemical model and the anode / cathode dynamic equation and the like.

[0103] Further, the modeling of the wind power generation device includes:

[0104]

[0105] In the formula, P wind represents the mechanical conversion power of the wind power generation device, ρ represents the air density, R represents the impeller radius, v w represents the wind speed, C p (λ, β) represents the fan blade efficiency coefficient; λ i represents the intermediate variable parameter, λ represents the tip speed ratio, β represents the pitch angle; ω represents the rotor angular velocity.

[0106] Further, the modeling of the photovoltaic power generation device includes:

[0107]

[0108] C1=exp(-U m / C2U oc )×(1-I m / I sc ),

[0109]

[0110] dU = βdT - R s dI,

[0111] wherein U, I and T represent output voltage, output current and temperature of the photovoltaic power generation device, respectively, U oc and I sc represent open circuit voltage and short circuit current, respectively; a and β represent current and voltage temperature variation coefficients, respectively; U m and I m represent voltage and current of the maximum power point, respectively; N p and N s represent parallel number and series number of photovoltaic components in the photovoltaic power generation device, respectively; R s represents photovoltaic series resistance, G and G ref represent solar radiation intensity and solar radiation intensity rating, respectively; T c and T ref represent current environmental temperature and temperature rating, respectively.

[0112] Further, the energy storage device modeling comprises:

[0113]

[0114] wherein E(t) represents the remaining power of the energy storage device at time t; E(t-1) represents the remaining power of the energy storage device at the previous time; represents self-discharge rate of the energy storage device; P N represents charge and discharge power of the energy storage device, and δ represents charge and discharge efficiency of the energy storage device; T N represents charge and discharge time of the energy storage device; E n represents rated capacity of the energy storage device, and SOC represents state of charge of the energy storage battery.

[0115] Further, the alkaline electrolyzer (ALK) and the proton exchange membrane electrolyzer (PEM) are simulated and modeled using electrochemical models and anode / cathode dynamic equations.

[0116] Water electrolysis belongs to a redox reaction, and the chemical reaction equation is:

[0117] H2O→0.5O2(g)+H2(g)

[0118] The electrolyzer can be regarded as a nonlinear DC load sensitive to voltage variation. Its load voltage is positively correlated with input current, and the voltage rises with the increase of current. In practice, the electrolyzer load voltage is affected by many factors such as working pressure and temperature. Since there is no direct linear correlation between the current and voltage of the electrolyzer, a curve fitting method is used to analyze its characteristics.

[0119] (1) The simulation model of the alkaline electrolyzer comprises:

[0120] (1.1) The output voltage of the alkaline electrolyzer at different temperatures is:

[0121]

[0122] wherein r1 and r2 represent the ohmic resistance parameters of the electrolyte; T el represents the temperature in the tank; A cell represents the area of the electrolysis module; I el represents the direct current; s n and t n represent the overvoltage coefficient, wherein the subscript n = 1, 2, 3; U rev represents the inverse voltage of the alkaline electrolyzer, which is related to the change amount ΔG of the Gibbs free energy change ΔG of the electrochemical reaction process, and ΔG x U rev zF, z represents the number of electron transfers per reaction; F represents the Faraday constant.

[0123] (1.2) Ohmic resistance exists on the surface of the electrode, and the electrolysis reaction will generate ohmic overvoltage. The ohmic overvoltage U om,alk generated by the electrolysis reaction of the alkaline electrolyzer is:

[0124] U om,alk = R om,alk I el

[0125] wherein R om,alk represents the ohmic resistance.

[0126] (1.3) The open circuit voltage U ∞ of the alkaline electrolyzer can be derived from the Nernst equation of water electrolysis, and is:

[0127]

[0128] wherein E0 represents the theoretical electromotive force; T el represents the temperature in the tank; R0 represents the gas constant; and respectively represent the partial pressure of oxygen and hydrogen; represents the water activity between the membrane and the electrode; E0 is 1.23 V.

[0129] (1.4) The hydrogen production rate of the alkaline electrolyzer is expressed as:

[0130]

[0131]

[0132] wherein η H2 represents the molar hydrogen production rate; η F represents the Faraday efficiency; a n represents the Faraday efficiency coefficient, wherein n = 1, 2, 3, 4, 5; I el represents the direct current, A cell represents the electrolysis module area, N el represents the number of electrolytic cells in series in the electrolyzer, T el represents the temperature in the cell.

[0133] (2) The simulation model of the PEM electrolyzer comprises:

[0134] (2.1) The anode dynamic equation of the PEM electrolyzer is:

[0135]

[0136] wherein and respectively represent the net oxygen production rate and the net water production rate on the anode side, and respectively represent the molar flow rate of oxygen into and out of the anode; respectively represent the molar flow rate of water into and out of the anode, wherein, since only water is input, is equal to zero; and respectively represent the electro-osmotic and diffusion flow rates; O 2g represents the oxygen flow rate of the anode.

[0137] (2.2) The H3O+ion that passes through the proton exchange membrane from the anode to the cathode + undergoes a reduction reaction to generate H2, and the dynamic equation of oxygen and water at the cathode of the PEM electrolyzer is:

[0138]

[0139] wherein and respectively represent the net oxygen production rate and the net water production rate on the cathode side, and represent the molar flow rate of hydrogen and water into the cathode; and H2and H2O, respectively, are the molar flow rates of hydrogen and water leaving the cathode; and H2and H2O, respectively, are the molar flow rates of hydrogen and water leaving the cathode; 2g H2is the hydrogen gas produced at the cathode.

[0140] Within the proton exchange membrane, water is transported mainly by electroosmosis and diffusion, both of which are related to the water content of the membrane. The expression for the water transport by electroosmosis is:

[0141]

[0142] where n is the number of water molecules transported by electroosmosis per ion transported by diffusion, i is the current density, F is the Faraday constant, and M is the molar mass of water. d is the electro-osmotic coefficient, i md is the current density, and F is the Faraday constant. is the molar mass of water, and A is the area of the cell.

[0143]

[0144] where λ is the arithmetic mean of the water content of the anode and cathode membranes. m

[0145] where the function of the water content of the anode membrane and the water vapor activity a is λ = 0.43 + 17.81a - 39.85a 2 + 36a 3 and the function of the water content of the cathode membrane and the water vapor activity a is λ = 14 + 1.4(a - 1).

[0146] The activation overvoltage of the PEM cell can be expressed as:

[0147]

[0148] where R is the gas constant, F is the Faraday constant, μ is the transport coefficient, T el is the temperature in the cell, i md is the current density, and i0 is the exchange current density.

[0149] The ohmic overvoltage V om,pem of the PEM cell and the membrane resistance R om,pem can be expressed as:

[0150] V om,pem = i md R om,pem ,

[0151]

[0152] where R om,pem is the ohmic resistance of the PEM cell, and t​em denotes the thickness of the proton exchange membrane; σ em denotes the membrane conductivity; λ m denotes the arithmetic mean root of the water content of the anode and cathode membranes, T el denotes the temperature in the cell;

[0153] (2.5) The temperature model of the PEM electrolyzer comprises:

[0154]

[0155] Q ele = (U cell -V th )jA cell n cell ,

[0156]

[0157] wherein: C stack denotes the heat capacity of the PEM electrolyzer; T stack denotes the outlet temperature of the PEM electrolyzer; T ex,h denotes the inlet temperature of the PEM electrolyzer; q 1y denotes the mass flow of the electrolyte; c 1y denotes the specific heat capacity of the electrolyte, Q ele denotes the heat generation power of the electrolyzer, U cell denotes the single sheet voltage of the PEM electrolyzer, V th denotes the single sheet thermodynamic theoretical voltage of the PEM electrolyzer, j denotes the alternating current density, A cell denotes the active area of the PEM electrolyzer, n cell denotes the number of electrolysis cell sheets of the PEM electrolyzer, Q dis stack denotes the heat dissipated by the electrolyzer to the environment.

[0158] Further, the hydrogen production and heat generation power model of the hydrogen production device is a unified operation model as follows:

[0159]

[0160] In the formula: and are the input power and hydrogen production power of the electrolyzer mold i at time t; is the operation state of the electrolyzer mold i at time t, 1 represents operation and 0 represents stop; is the heat generation power of the electrolyzer mold i at time t; is the input power unit value of the electrolyzer mold i at time t; is the operation temperature of the electrolyzer mold i at time t; and are the coefficients obtained by experiments related to the type of electrolytic cell, input power scale range.

[0161] Further, the coordinated operation strategy of the alkaline electrolytic cell and the PEM electrolytic cell comprises:

[0162] The alkaline electrolytic cell is slow to start and stop, and the load adjustment range is 20%-110%. The low-cost advantage is utilized to run at >80% rated power during the stable power supply period, to bear the basic load, and to maximize the economy. The PEM electrolytic cell has fast response speed, and the load range is 3%-135%. The PEM electrolytic cell is quickly adjusted during wind and light output fluctuation, to respond to fluctuating load and cover the low load below 20% and the excess rated power range that the alkaline electrolytic cell cannot respond to.

[0163] The capacity ratio of the alkaline electrolytic cell and the PEM electrolytic cell comprises:

[0164]

[0165] In the formula, R ALK and R PEM are the capacities of the alkaline electrolytic cell and the PEM electrolytic cell respectively; M min and M max are the upper and lower limits of the proportion of the capacity of the PEM electrolytic cell to the total electrolytic cell capacity.

[0166] Figure 2 is a schematic diagram of the composition of the semi-physical simulation platform of the embodiment of the present application. Figure 3 is a schematic diagram of the construction of the simulation model of the wind and light coupled hydrogen production system of the embodiment of the present application. Figure 4 is a schematic diagram of the coupling structure of the semi-physical simulation of the wind and light coupled hydrogen production system of the embodiment of the present application.

[0167] In the embodiment and some embodiments of the present application, as shown in Figure 2 , the semi-physical simulation platform comprises an RT-LAB simulation system, an OPAL-RT OP5700 simulator, an NIPXIe-1071 case and an oscilloscope. Specifically, the compilation control system of the semi-physical simulation platform is the RT-LAB simulation system, the hardware simulation device is the OPAL-RT OP5700 simulator, and the signal acquisition device is the NIPXIe-1071 case. In these embodiments of the present application, the RT-LAB simulation system, the OPAL-RT OP5700, the NIPXIe-1071 case and the oscilloscope are used to complete the hardware configuration of the semi-physical simulation platform, the power signal output by the simulation model is driven through the power amplifier to drive the physical converter and the controller, and the response of the physical converter and the controller is collected through the data acquisition card and fed back to the simulation model to realize the real-time interaction of the semi-physical simulation platform.

[0168] Specifically, in the embodiments of the present invention, such as Figure 3 and Figure 4 As shown, wind power generation devices and photovoltaic power generation devices convert wind energy and solar energy into electrical energy, respectively, which are then connected to the wind-solar coupled hydrogen production system via transformers and other electrical components. Energy storage devices ( Figure 4 The energy storage batteries in the system store excess electrical energy, releasing it when needed to maintain power balance. The hydrogen production unit converts electrical energy into hydrogen for storage, achieving the conversion and storage of renewable energy from wind and solar power. The grid and the wind-solar coupled hydrogen production system interact electrically, both receiving excess energy and providing sufficient power to ensure power balance and stable operation. The RT-LAB platform signal acquisition device measures, collects, and processes electrical signals from various parts of the system.

[0169] Specifically, in the embodiments of the present invention, such as Figure 3 and Figure 4 As shown, a mathematical model of a wind-solar coupled hydrogen production system was built in the Simulink environment, and a digital weak grid scenario was integrated. Subsequently, using the RT-LAB software platform, this system model was deployed to the OPAL-RTOP5700 real-time simulator through its standard "Edit-Build-Load" workflow.

[0170] Next, the hardware-in-the-loop (HIL) testing phase begins. Key electrical quantities output by the simulation system, including the DC-side voltage (VDC) of the wind turbine / photovoltaic / energy storage unit and the voltage (Vgrid), current (Igrid), active power (P), and reactive power (Q) at the grid connection point, are acquired at high speed by the NIPXIe-1071 chassis. These analog signals undergo necessary signal conditioning and power / signal amplifier processing before being input to the physical devices, and their waveforms can be monitored in real time using an oscilloscope.

[0171] The processed signals are sent to the physical converters / controllers of the actual external wind turbines, photovoltaic systems, and energy storage systems to drive and control these hardware devices. Finally, the actual response of the physical converters / controllers (e.g., output power, status, etc.) is fed back as feedback signals to the OPAL-RT simulation platform, forming a closed-loop system with the running Simulink model. This closed-loop structure ensures that the simulation model can adjust according to the actual dynamic response of the physical hardware, thus operating precisely under preset conditions.

[0172] Specifically, in the embodiments of the present application, RT-LAB platform is used to simulate diversified natural conditions and various operating conditions in the wind-solar coupling hydrogen production system research. Real-time data interaction is carried out with actual hardware devices, the output signals of the simulation model are sent to the hardware devices (physical converters and controllers of photovoltaic, wind and energy storage), and the feedback signals of the hardware devices (voltage, current, active and reactive power of the photovoltaic, wind and grid-connected sides) are received. Some key hardware devices are connected to the simulation platform for testing, wind-solar fluctuation simulation is carried out, and the reliability of the wind-solar coupling hydrogen production system under wind-solar fluctuation is evaluated.

[0173] Specifically, in the embodiments of the present application, OPAL-RT OP5700 simulator is used to quickly process complex mathematical models, real-time solve the fine models of various links in the wind-solar coupling hydrogen production system such as wind power generation device, photovoltaic power generation device, energy storage system and hydrogen production system, and ensure the accuracy and real-time performance of the simulation. The rapid changes of wind-solar power generation are accurately simulated, the dynamic response process of the electrolytic cell and other devices in the hydrogen production system is accurately reflected, and multi-time scale collaborative simulation is realized.

[0174] Specifically, in the embodiments of the present application, NIPXIe-1071 chassis is used to collect various simulation signals in the wind-solar coupling hydrogen production system with high precision, and some plug-in modules have signal conditioning functions. The collected signals are amplified, filtered, isolated and processed to improve the quality and anti-interference ability of the signals, ensure the accuracy and reliability of the collected signals, and provide accurate basis for subsequent data analysis and control decision.

[0175] Specifically, in the embodiments of the present application, an oscilloscope is used to monitor voltage, current and power signals in the wind-solar coupling hydrogen production system in real time and accurately. By observing the changes of voltage, current and power waveforms, it can be known whether the device working state is stable and whether the output meets the expected target.

[0176] Further, in the embodiments of the present application and some embodiments of the present application, the stability and accuracy of the simulation model are analyzed according to the simulation data of the simulation model under the steady state condition, including:

[0177] The electrical waveform data and hydrogen production data of the simulation model under the steady state condition and / or the non-steady state condition are analyzed for short-time fluctuation and long-time dynamic analysis, and short-time fluctuation analysis data and long-time dynamic analysis data are obtained.

[0178] The short-time fluctuation analysis data and the long-time dynamic analysis data are compared with the traditional model to determine the stability and accuracy of the simulation model.

[0179] Specifically, in the embodiments of the present application, the dynamic analysis under the steady state condition is to analyze and verify the electrical waveform, hydrogen production performance and the like under the steady state condition; the dynamic analysis under the non-steady state condition is to analyze and verify the power fluctuation, hydrogen production prediction accuracy change and the like under the non-steady state condition; wherein the stability verification of the simulation model is to analyze and verify the stability of multi-time scale coupling for short-time fluctuation (second level) and long-time dynamic (hour level) respectively; the accuracy verification of the simulation model is to compare the dynamic accuracy, calculation efficiency and the like of the conventional model, and verify the accuracy of the model.

[0180] Specifically, in the embodiments of the present application, under the complex and variable non-steady state condition, the wind-solar coupling hydrogen production system model constructed and the conventional model are respectively subjected to systematic simulation test. Through comparative analysis of power fluctuation and response time, the results show that the model in this paper can maintain a more stable operation state when facing unstable conditions, and the stability advantage is significant. At the same time, the hydrogen production data of the semi-physical simulation platform is compared with the actual system operation data, which further verifies the accuracy of the model in the simulation of the wind-solar coupling hydrogen production system.

[0181] Specifically, the operation of the wind-solar coupling hydrogen production system model under actual working conditions is simulated to verify the stability and accuracy of the model. The wind power generation device model parameter settings are shown in Table 1, the photovoltaic power generation device model parameter settings are shown in Table 2, the energy storage device model parameter settings are shown in Table 3, and the hydrogen production device model parameter settings are shown in Table 4.

[0182] Table 1: Wind power generation device model parameters

[0183]

[0184] Table 2: Photovoltaic power generation device model parameters

[0185]

[0186] Table 3: Energy storage device model parameters

[0187]

[0188] Table 4: Hydrogen production device model parameters

[0189]

[0190] The RT-LAB platform measurement module measures, collects and processes the electrical signals of each part of the system through the signal processing unit. Figure 5 、 Figure 6 The three-phase alternating voltage and three-phase alternating current simulation waveforms of the wind power generation device and the photovoltaic power generation device connected to the grid side are shown in the figure, and it can be seen from the figure that the voltage and current waveforms are both stable periodic sinusoidal waveforms.

[0191] Figure 7 The total power output simulation schematic diagram of the wind power generation device and the photovoltaic power generation device of the embodiment of the present application is shown in FIG. 6. As shown in the figure, the wind power and the photovoltaic power can provide stable power for the system. The AC bus voltage is first reduced by a transformer, and then the AC power is converted into DC power by a rectifier converter, and finally the DC voltage is input to the hydrogen production system. Figure 7 The DC voltage input simulation schematic diagram of the hydrogen production device of the embodiment of the present application is shown in FIG. 7. As shown in the figure, the DC voltage simulation result is stable, which provides a reliable voltage environment for the hydrogen production system. Figure 8 The DC voltage input simulation schematic diagram of the hydrogen production device of the embodiment of the present application is shown in FIG. 7. As shown in the figure, the DC voltage simulation result is stable, which provides a reliable voltage environment for the hydrogen production system. Figure 8

[0192] Figure 9 , Figure 10 The running power of a single alkaline electrolyzer and a single PEM electrolyzer in the hydrogen production device and the single cell voltage simulation result are shown in FIGS. 8 and 9, respectively. As shown in the power and single cell voltage change over time in the figures, after the electrolyzer is started, it takes a period of time to reach a stable running state. Figure 11 The hydrogen storage tank pressure simulation result in the hydrogen production device is shown in FIG. 10, which indicates that the pressure in the hydrogen storage tank is continuously and stably increasing over time.

[0193] During the simulation process on the semi-physical simulation platform, an oscilloscope is used to collect the voltage, current and power waveforms of the wind-solar coupled hydrogen production device in real time. Figure 12 The AC side voltage and current waveforms of the hydrogen production device collected by the oscilloscope under stable working conditions are shown in FIGS. 11 and 12, both of which are regular sinusoidal waveforms with synchronous frequency and no waveform distortion and other abnormal conditions.

[0194] As shown in FIGS. 13 and 14, Figure 13 and Figure 14 in comparison, Figure 13 the active power and reactive power waveforms of the hydrogen production device collected by the oscilloscope during the unstable working condition period of the model built by the embodiment of the present application are shown, and the power waveform is smooth, indicating that the hydrogen production device runs stably. Figure 14 The active power and reactive power waveforms of the hydrogen production device collected by the oscilloscope during the unstable working condition period of the common model are shown, and the power waveform is distorted, indicating that the hydrogen production device runs unstably. As shown in FIGS. 15 and 16, Figure 15 and Figure 16 in comparison, Figure 15 the voltage and current waveforms of the hydrogen production device collected by the oscilloscope during the unstable working condition period of the model built by the embodiment of the present application are shown, both of which are regular sinusoidal waveforms with synchronous frequency and no waveform distortion and other abnormal conditions, indicating that the hydrogen production device runs stably. Figure 16 The voltage and current waveforms of the hydrogen production device collected by the oscilloscope during the unstable working condition period of the common model are shown, and the waveforms of both are distorted, indicating that the hydrogen production device runs unstably. Therefore, the model of the wind-solar coupled hydrogen production system built by the embodiment of the present application has good stability.​

[0195] As Figure 17 shown, the time-hydrogen production curve obtained under the cold start condition of the hydrogen production device is compared with the actual hydrogen production operation curve, and it can be seen from the figure that the black model curve is highly consistent with the red actual operation curve in the overall trend. In the initial stage, both curves rise rapidly, indicating that the growth trend of hydrogen production in the model prediction is consistent with that in the actual operation in the period when hydrogen production begins. With the passage of time, the rising speed gradually slows down and tends to be stable, and the two curves also change synchronously during this process. Although there are some slight fluctuations in the actual operation curve, the overall still closely fluctuates around the model curve and does not deviate greatly. This means that during the entire hydrogen production process, the model can accurately simulate the change of actual hydrogen production with time, which can indicate that the fitting degree of the two curves is high, that is, the model adopted can better reflect the actual hydrogen production operation process, thereby verifying the accuracy of the wind-solar coupled hydrogen production system model built in the embodiment of the present application.

[0196] In summary, the wind-solar coupled hydrogen production system semi-physical simulation method of the embodiment of the present application can accurately reflect the characteristics of each subsystem, and the accuracy of the wind-solar coupled hydrogen production system model and its stable operation ability are verified based on the simulation experiment results.

[0197] Embodiment two:

[0198] Another embodiment of the present application discloses a wind-solar coupled hydrogen production system semi-physical simulation system, thereby realizing the wind-solar coupled hydrogen production system semi-physical simulation method in embodiment one. The specific implementation mode of each module is referred to the corresponding description in embodiment one.

[0199] As Figure 18 shown, the system includes a model construction module, a semi-physical simulation platform, and an analysis module.

[0200] The model construction module is used to construct a simulation model of the wind-solar coupled hydrogen production system, which includes a wind power generation device, a photovoltaic power generation device, an energy storage device, and a hydrogen production device.

[0201] The semi-physical simulation platform comprises a compiling control system, a hardware simulation device, a power amplifier, a physical converter and a controller, a signal acquisition device and an oscilloscope, the simulation model is compiled by the compiling control system and loaded into the hardware simulation device; wherein the compiling control system simulates the steady state condition or the non-steady state condition of the wind-solar coupling hydrogen production system, and controls the simulation model to run in the hardware simulation device, the output of the simulation model is sent into the physical converter and the controller through the power amplifier connected with the hardware simulation device, the output of the physical converter and the controller is collected by the signal acquisition device and fed back to the simulation model, and the oscilloscope collects simulation data of the simulation model in real time.

[0202] The analysis module is used for analyzing the stability and accuracy of the simulation model according to the simulation data of the simulation model under the steady state condition and / or the non-steady state condition.

[0203] As can be known from the above description, the embodiment of the present application can at least achieve the following beneficial effects:

[0204] The embodiment of the present application constructs an electrolytic cell fine model based on RT-LAB, reduces dynamic error, and significantly improves dynamic response precision.

[0205] The embodiment of the present application realizes real-time interactive simulation of second-level wind-solar output fluctuation and hour-level hydrogen storage tank pressure change through OPAL-RT OP5700 multi-core parallel computing, shortens the step to 20 ms, and realizes a breakthrough in multi-time scale collaborative simulation capability.

[0206] The embodiment of the present application simulates extreme wind-solar fluctuation through a semi-physical simulation platform, verifies that the response delay of the energy storage system is reduced, the active power fluctuation amplitude is reduced, and the equipment life is prolonged, and realizes system stability and reliability verification.

[0207] The embodiment of the present application provides data support for capacity configuration and control parameter setting of the wind-solar hydrogen production system through high-precision simulation results, improves wind-solar utilization rate, and realizes engineering application value improvement.

[0208] The embodiment of the present application solves the bottleneck of traditional semi-physical simulation in dynamic response, multi-time scale coupling and cost optimization through high-precision modeling, real-time simulation and economical control strategy, and provides reliable technical support for engineering application of the wind-solar coupling hydrogen production system.

[0209] Since the system in the embodiment and the method in the first embodiment are related to each other and can be mutually referred to, this is repeated description, and therefore will not be described here. Since the system embodiment and the above-mentioned method embodiment have the same principle, the system embodiment also has the corresponding technical effects of the above-mentioned method embodiment.

[0210] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiment methods can be completed by instructing the relevant hardware by a computer program, and the program can be stored in a computer readable storage medium. The computer readable storage medium is a disk, an optical disk, a read-only memory, a random access memory, etc.

[0211] The above description is merely preferred specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for simulating a wind-solar coupled hydrogen production system, characterized in that The method comprises the following steps: a simulation model of the wind-solar coupled hydrogen production system is constructed, the wind-solar coupled hydrogen production system comprising a wind power generation device, a photovoltaic power generation device, an energy storage device and a hydrogen production device; a semi-physical simulation platform is built, the semi-physical simulation platform comprising a compiling control system, a hardware simulation device, a power amplifier, a physical converter and a controller, a signal acquisition device and an oscilloscope, the simulation model being compiled by the compiling control system and loaded into the hardware simulation device; the compiling control system simulates a steady state condition or a non-steady state condition of the wind-solar coupled hydrogen production system, and controls the simulation model to run in the hardware simulation device, the output of the simulation model being sent to the physical converter and the controller through the power amplifier connected with the hardware simulation device, the output of the physical converter and the controller being collected by the signal acquisition device and fed back to the simulation model, and the simulation data of the simulation model being collected in real time by the oscilloscope; the stability and accuracy of the simulation model are analyzed according to the simulation data of the simulation model under the steady state condition and / or the non-steady state condition.

2. The method of claim 1, wherein, the simulation model of the wind power generation device comprises: where P wind represents the mechanical conversion power of the wind power generation device, p represents the air density, R represents the impeller radius, v w represents the wind speed, C p (λ, β) represents the fan blade efficiency coefficient; λ i represents an intermediate variable parameter, λ represents the tip speed ratio, β represents the pitch angle; and ω represents the rotor angular velocity.

3. The method of claim 1, wherein, the simulation model of the photovoltaic power generation device comprises: C1 = exp(-U m / C2U oc ) x (1 - I m / I sc ), dU = βdΤ - R s dI, wherein U, I and T respectively represent output voltage, output current and temperature of the photovoltaic power generation device, U oc and I sc respectively represent open circuit voltage and short circuit current of the photovoltaic power generation device; a and b respectively represent current and voltage temperature variation coefficients; U m and I m respectively represent voltage and current of the maximum power point of the photovoltaic power generation device; N p and N s respectively represent parallel number and series number of photovoltaic components in the photovoltaic power generation device; R s represents photovoltaic series resistance, G and G ref respectively represent solar radiation intensity and solar radiation intensity rated value; T c and T ref respectively represent current environmental temperature and temperature rated value.

4. The method of claim 1, wherein, the simulation model of the energy storage device comprises: wherein E(t) represents the remaining electric quantity of the energy storage device at time t; E(t-1) represents the remaining electric quantity of the energy storage device at the previous time; represents the self-discharge rate of the energy storage device; P N represents the charge-discharge power of the energy storage device, and δ represents the charge-discharge efficiency of the energy storage device; T N represents the charge-discharge time of the energy storage device; E n represents the rated capacity of the energy storage device, and SOC represents the state of charge of the energy storage battery.

5. The method of claim 1, wherein, the hydrogen production device comprises an alkaline electrolyzer, and the simulation model of the alkaline electrolyzer comprises: (1) the output voltage U of the alkaline electrolyzer cell is: wherein r1 and r2 represent electrolyte ohmic resistance parameters; T el represents the temperature in the cell; A cell represents the area of the electrolysis module; I el represents the direct current; s n and t n represents the overvoltage coefficient, wherein the subscript n = 1, 2, 3; U rev represents the inverse voltage of the alkaline electrolysis cell; (2) the ohmic overvoltage U generated by the electrolysis reaction of the alkaline electrolyzer om,alk is: U om,alk = R om,alk I el , wherein R om,alk represents an ohmic resistance; (3) the open circuit voltage U of the alkaline electrolyzer ∞ is: where E0 is the theoretical electromotive force; T el represents the temperature in the tank; R0 represents the gas constant; and respectively represent the oxygen partial pressure and the hydrogen partial pressure; represents the water activity between the membrane and the electrode; (4) the hydrogen production rate of the alkaline electrolyzer comprises: wherein represents the molar hydrogen generation rate; η F represents the Faraday efficiency; a n represents the Faraday efficiency coefficient, wherein n = 1, 2, 3, 4, 5; N el represents the number of electrolytic cells in series in the alkaline electrolyzer.

6. The method of claim 1, wherein, the hydrogen production device comprises a PEM electrolyzer, and the simulation model of the PEM electrolyzer comprises: (1) the anode dynamic equation of the PEM electrolyzer is: wherein, and respectively represent the net generation rate of oxygen gas and the net generation rate of water on the anode side, and respectively represent the molar flow rate of oxygen gas into and out of the anode; respectively represent the molar flow rate of water into and out of the anode, wherein, is equal to zero; and respectively represent the electro-osmotic and the diffusion flow rate;O 2g represents the oxygen gas flow rate of the anode; (2) the cathode dynamic equation of the PEM electrolyzer is: wherein and respectively represent the net oxygen generation rate and the net water generation rate at the cathode side, and represent the molar flow rates of hydrogen and water flowing into the cathode; and respectively represent the molar flow rates of hydrogen and water flowing out of the cathode; and respectively represent the electro-osmotic flow rate and the diffusion flow rate across the proton exchange membrane from the anode electrode;H 2g represents the hydrogen gas produced at the cathode; (3) the activation overvoltage V of the PEM electrolyzer el.act is: where R is the gas constant; F is the Faraday constant; μ represents the transfer coefficient; T el represents the temperature in the cell; i md represents the current density, i0represents the exchange current density; (4) the ohmic overvoltage V of the PEM electrolyser om,pem and the membrane resistance R om,pem is: V om,pem = i md R om,pem , where R om,pem represents the ohmic resistance of the PEM cell; t em represents the thickness of the proton exchange membrane; σ em represents the membrane conductivity; (5) the temperature model of the PEM electrolyzer comprises: where: C stack represents the heat capacity of the PEM electrolyser; T stack represents the outlet temperature of the PEM electrolyser; T ex,h represents the inlet temperature of the PEM electrolyser; q 1y represents the mass flow rate of the electrolyte; c 1y represents the specific heat capacity of the electrolyte, Q ele represents the heat generation power of the electrolyser, Q disstack represents the heat lost by the electrolyser to the environment.

7. The method of claim 1, wherein the hydrogen production and heat production power model of the hydrogen production device is a unified operation model as follows: In the formula: and is the input power and hydrogen production power of the electrolytic cell mold i at time t; is the running state of the electrolytic cell mold i at time t, 1 represents running, and 0 represents stopping; is the heat production power of the electrolytic cell mold i at time t; is the input power unit value of the electrolytic cell mold i at time t; is the running temperature of the electrolytic cell mold i at time t; and is a correlation coefficient related to the electrolytic cell type and the input power unit value range obtained through experiments.

8. The method of claim 1, wherein, the hydrogen production device comprises an alkaline electrolyzer and a PEM electrolyzer, and the alkaline electrolyzer and the PEM electrolyzer work in coordination; the coordination operation strategy of the alkaline electrolyzer and the PEM electrolyzer comprises: the load adjustment range of the alkaline electrolyzer is 20%-110%, the alkaline electrolyzer is operated at ≥ 80% rated power during a stable power supply period, and undertakes basic load; the load range of the PEM electrolyzer is 3%-135%, the PEM electrolyzer is quickly adjusted during wind-solar output fluctuation, and responds to fluctuating load, covering the low load below 20% and the excess rated power interval that the alkaline electrolyzer cannot respond to; the capacity ratio of the alkaline electrolyzer and the PEM electrolyzer comprises:

9. The method of claim 1, wherein wherein: R ALK and R PEM are the capacities of the alkaline electrolyzer and the PEM electrolyzer, respectively; M min and M max are the upper and lower limits of the proportion of the PEM electrolyzer capacity to the total electrolyzer capacity. the compiling control system is an RT-LAB simulation system, the hardware simulation device is an OPAL-RT OP5700 simulator, and the signal acquisition device is an NIPXIe-1071 chassis; analyzing the stability and accuracy of the simulation model according to the simulation data of the simulation model under the steady state condition comprises: short-time fluctuation and long-time dynamic analysis are performed on the electrical waveform data and hydrogen production data of the simulation model under the steady state condition and / or the non-steady state condition, to obtain short-time fluctuation analysis data and long-time dynamic analysis data. ​ The short-time fluctuation analysis data and the long-time dynamic analysis data are compared with a traditional model to determine stability and accuracy of the simulation model. 10.A semi-physical simulation system of a wind-solar coupled hydrogen production system, characterized in that The method comprises the steps of: a model construction module, configured to construct a simulation model of the wind-solar coupled hydrogen production system, the wind-solar coupled hydrogen production system comprising a wind power generation device, a photovoltaic power generation device, an energy storage device, and a hydrogen production device; a semi-physical simulation platform, comprising a compiling control system, a hardware simulation device, a power amplifier, a physical converter and controller, a signal acquisition device, and an oscilloscope, the simulation model being compiled by the compiling control system and loaded into the hardware simulation device; wherein the compiling control system simulates steady-state conditions or non-steady-state conditions of the wind-solar coupled hydrogen production system and controls the simulation model to run in the hardware simulation device, the output of the simulation model being sent to the physical converter and controller through the power amplifier connected to the hardware simulation device, the output of the physical converter and controller being collected by the signal acquisition device and fed back to the simulation model, and the simulation data of the simulation model being collected in real time by the oscilloscope; an analysis module, configured to analyze stability and accuracy of the simulation model according to simulation data of the simulation model under the steady-state conditions and / or the non-steady-state conditions.

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