Power grid and photovoltaic combined hydrogen production energy scheduling method

Abstract

The invention relates to an energy scheduling method for hydrogen production by combining a power grid with photovoltaic power, which comprises the following steps of: analyzing the technical problems of a wind-solar coupled hydrogen production system, establishing a dynamic mathematical model which conforms to each component subsystem of the system, and performing simulation analysis on the model characteristics of the subsystems; on the basis of a system integration model and a control strategy, system characteristic analysis and a simulation experiment of the control strategy are carried out on a built system in a grid-connected operation mode, so that the reliability of the designed system model and the control strategy is checked, the problem of system energy scheduling management in the grid-connected operation mode is solved, the characteristics of the system are well reflected, and the reliability of the system is improved. The method has a fast suppression effect on the power change of the hybrid system, the control effect is better than that of a traditional control strategy based on a state method, the stability and reliability of the system are improved, meanwhile, the power grid and hydrogen production load requirements are met, and power balance of the power grid and the wind-solar coupled hydrogen production system is achieved.

Description

Technical Field

[0001] The invention belongs to the technical field of clean energy power generation dispatching, and relates to an energy dispatching method for hydrogen production combining a power grid and photovoltaics. Background Art

[0002] Renewable energy includes technologies such as wind power generation and solar power generation. Wind and solar energy are highly random, which can lead to power generation fluctuations, voltage, frequency fluctuations, and power quality problems. In order to solve this technical problem, the main technical solution currently used is to connect wind and solar power generation to the power grid, and use electrolysis to produce hydrogen at the same time. In view of the nonlinear, strongly coupled, and complex characteristics of the energy management system, the wind-solar coupling hydrogen production technology based on microgrid control is used to improve the stability and reliability of the system, while meeting the power grid and hydrogen production load requirements, and achieving power balance between the power grid and the wind-solar coupling hydrogen production system.

[0003] However, the combination of wind and solar power to produce hydrogen also faces a series of problems. Among them, how to solve the system energy scheduling and management under the grid-connected operation mode is the key issue currently faced. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide an energy scheduling method for hydrogen production combining power grid and photovoltaic, to model the wind-solar coupled hydrogen production system, to optimize system energy management and to perform energy optimization scheduling on the system based on distributed energy prediction integrated control technology.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: an energy scheduling method for hydrogen production by combining power grid and photovoltaic, comprising the following steps: S1, wind power generation system modeling, establish mathematical models of wind speed model, power conversion model, variable pitch system model and permanent magnet synchronous motor rotor; S2, photovoltaic power generation system modeling, establishing a photovoltaic cell model based on the equivalent circuit of the photovoltaic cell; S3, SOFC modeling, to establish an electrochemical model based on solid-state fuel cell SOFC; S4, PEMFC modeling, establish a cathode and anode model based on proton exchange membrane fuel cell; S5, electrolyzer modeling, establishing an electrolyzer model based on PEME and AE models; S6, hydrogen energy storage modeling, establish a pressure model based on hydrogen storage tanks; S7, energy storage battery modeling, establishing an equivalent mathematical model based on an equivalent circuit; S8, power converter modeling, build Boost and Buck DC / DC converter models; S9, simulation, numerical simulation verification of each system to obtain system performance related parameters; S10, energy scheduling, uses the hydrogen fuel cell power generation system to compensate for the fluctuation component of a specific frequency band in the output power fluctuation of renewable energy, and adjusts the hydrogen fuel cell power generation power in real time.

[0006] In S1, the wind speed model divides the wind speed into four components: basic component, slope component, gust component and turbulence component, which are used in the relevant simulation of wind power generation process and power system; the power conversion model outputs mechanical power by power conversion based on the theory of aerodynamics and combined with the steady-state power characteristics of the wind turbine; the variable pitch system model uses the closed-loop structure of the variable pitch system to simplify it into a first-order dynamic system, including speed limit and amplitude limit links; in the mathematical model, the permanent magnet synchronous generator is completely decoupled from the power grid, and the exchange of reactive power with the power grid is completely carried out through the network-measured inverter.

[0007] In S2, without considering the connection line loss and component differences, the photovoltaic cell array is composed of solar cell components connected in series and parallel.

[0008] In S3, the low-order SOFC stack model is simplified, the physical process is ignored, and the Nernst equation is used to define the Nernst voltage, activation voltage drop, ohmic voltage drop, and concentration polarization voltage drop of the SOFC operating voltage.

[0009] In S4, the low-order PEMFC stack model is simplified, the physical process is ignored, and the thermodynamic electromotive force, activation overvoltage, ohmic voltage drop and concentration overvoltage are defined by the output voltage of the solid-state fuel cell and the PEM fuel cell. The dynamic characteristics of the cathode are defined by the energy conservation theorem, and the cathode pressure is defined according to the ideal gas law.

[0010] In S5, the model of the electrolyzer stack is simplified, assumptions are made for it, and a proton exchange membrane electrolyzer model, an alkaline electrolyzer model, and an electrolyzer thermal model are established.

[0011] In S6, the pressure of the hydrogen storage tank is expressed by the Biting-Bridgeman equation, and the change in the hydrogen in the hydrogen storage tank, the net input molar flow rate of hydrogen, and the power consumed by the compressor for compressing the gas are calculated.

[0012] In S7, the Thevenin equivalent circuit model is applied, based on fitting the general battery model to the battery discharge characteristic curve, which consists of a controlled voltage source connected in series with a constant resistance.

[0013] In S8, the power DC-DC converters are selected as Buck type and Boost type. Based on the analysis of each system, the typical non-isolated Boost converter, non-isolated Buck converter and non-isolated bidirectional half-bridge converter models are established.

[0014] In S10, energy management tasks are established, energy management goals are formulated, and scheduling is coordinated and optimized; energy scheduling based on the state control method includes the following steps: S10-1, net power is negative, hydrogen storage is positive, and the state of charge of the energy storage battery is below 20% ( Pnet <0, LH2 >0, SOC ≤20), the renewable energy will store the excess electricity in the battery and will not provide electricity for hydrogen production; S10-2, net power is negative, hydrogen storage is positive, and the state of charge of the energy storage battery is above 20% ( Pnet <0, LH2 >0, SOC >20), the renewable energy will store the excess electricity in the hydrogen tank and will not provide electricity for the battery; S10-3, net power is negative, hydrogen storage is non-positive ( Pnet <0, LH2 ≤0), the renewable energy will store the excess electricity in the hydrogen tank and will not provide electricity to the battery; S10-4, net power is non-negative, hydrogen storage is non-positive, and battery state of charge is below 20% ( Pnet >0, LH2 ≤0, SOC ≤20), the power grid neither provides power for the battery nor for hydrogen production; S10-5, net power is non-negative, hydrogen storage is positive, and battery state of charge is above 20% ( Pnet ≥0, LH2 >0, SOC ≤20), the grid stores the excess electricity in the hydrogen tank and does not provide electricity to the battery; S10-6, net power is non-negative, hydrogen storage is positive, and battery state of charge is above 20% ( Pnet ≥0, LH2 >0, SOC ≥20), the grid stores the excess electricity in the battery and does not provide electricity for hydrogen production; S10-7, net power is non-negative, hydrogen storage is non-positive, and battery state of charge is above 20% ( Pnet ≥0, LH2 ≤0, SOC ≥20), the grid stores the excess electricity in the battery and does not provide electricity for hydrogen production.

[0015] The main beneficial effects of the present invention are: The technical issues of the wind-solar coupled hydrogen production system are analyzed to provide a theoretical basis for subsystem selection, capacity configuration, energy management, etc.

[0016] A model of the wind-solar coupled hydrogen production system was established to study the working mechanism of each subsystem in the system. A modular modeling method was used to model each subsystem in the system separately, including direct-drive permanent magnet synchronous wind turbines, photovoltaic cells, fuel cells, electrolyzers, energy storage batteries, and power conversion devices.

[0017] The characteristic curves of each subsystem of the wind-solar coupled hydrogen production system were analyzed to verify the correctness and applicability of the established model.

[0018] Based on the operation strategy of the wind-solar coupled hydrogen production system under the grid-connected operation mode, a hierarchical control method is proposed to optimize the scheduling of the monitoring layer and compare it with the traditional state control method; at the same time, the local layer formulates the control strategy and simulates it. It is proved that according to the output power forecast value of wind and solar renewable energy, the load forecast value and the power generation plan, the hydrogen fuel cell power generation power is adjusted in real time, which is in line with the system power output plan arrangement. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0020] Figure 1 This is a diagram of the hydrogen production system of the present invention.

[0021] Figure 2 This is a working principle diagram of the solid-state fuel cell SOFC of the present invention.

[0022] Figure 3 This is a working principle diagram of the proton exchange membrane fuel cell PEMFC of the present invention.

[0023] Figure 4 This is a diagram of the Thevenin equivalent circuit model of the present invention.

[0024] Figure 5 It is a constant current discharge characteristic curve diagram of the battery of the present invention.

[0025] Figure 6 This is a diagram of the energy management structure of the wind-solar coupled hydrogen production system of the present invention.

[0026] Figure 7 This is a control block diagram of the monitoring system based on ANFIS of the present invention. DETAILED DESCRIPTION

[0027] like Figure 1 to Figure 7 In the invention, a method for energy dispatching of hydrogen production by combining power grid and photovoltaic power generation comprises the following steps: S1, wind power generation system modeling, establish mathematical models of wind speed model, power conversion model, variable pitch system model and permanent magnet synchronous motor rotor; S2, photovoltaic power generation system modeling, establishing a photovoltaic cell model based on the equivalent circuit of the photovoltaic cell; S3, SOFC modeling, to establish an electrochemical model based on solid-state fuel cell SOFC; S4, PEMFC modeling, establish a cathode and anode model based on proton exchange membrane fuel cell; S5, electrolyzer modeling, establishing an electrolyzer model based on PEME and AE models; S6, hydrogen energy storage modeling, establishing a pressure model based on hydrogen storage tanks; S7, energy storage battery modeling, establishing an equivalent mathematical model based on an equivalent circuit; S8, power converter modeling, build Boost and Buck DC / DC converter models; S9, simulation, numerical simulation verification of each system to obtain system performance related parameters; S10, energy scheduling, uses the hydrogen fuel cell power generation system to compensate for the fluctuation component of a specific frequency band in the output power fluctuation of renewable energy, and adjusts the hydrogen fuel cell power generation power in real time.

[0028] Embodiment 1, like Figure 1 In the process, the hydrogen production system includes the following parts: Wind power generation system: adopts maximum power tracking control strategy to maximize the wind turbine output power under full wind speed conditions.

[0029] Photovoltaic power generation system: The maximum power point tracking control strategy is adopted to maximize the output power of the photovoltaic array.

[0030] Electrolyzer: Uses electricity to electrolyze water to produce hydrogen.

[0031] Hydrogen storage tank: stores hydrogen in the form of liquefied energy storage.

[0032] Fuel cell: converts the chemical energy of hydrogen and oxygen into electrical energy.

[0033] DC / DC converter: It increases or decreases direct current into stable direct current.

[0034] Inverter and grid: The inverter is the DC part of the system connected to the grid. The DC side passes through the inverter and is converted into AC power for connection to the grid.

[0035] Data acquisition system: Use sensors to detect the power changes emitted by each subsystem and the voltage and inverter voltage of the system's DC part, classify and process the collected data, and provide it to the energy management system for output analysis.

[0036] Energy management system: According to the output power forecast values ​​of wind power subsystem, photovoltaic power generation subsystem, electrolysis hydrogen production forecast value and power generation plan of the power grid, reasonable indicators are set and the system output power is arranged reasonably.

[0037] In the preferred scheme, in S1, the wind speed model divides the wind speed into four components: basic component, slope component, gust component and turbulence component, which are used in the relevant simulation of wind power generation process and power system; the power conversion model outputs mechanical power by power conversion based on the theory of aerodynamics and combined with the steady-state power characteristics of the wind turbine; the variable pitch system model uses the closed-loop structure of the variable pitch system to simplify it into a first-order dynamic system, including speed limit and amplitude limit links; in the mathematical model, the permanent magnet synchronous generator is completely decoupled from the power grid, and the exchange of reactive power with the power grid is completely carried out through the network-measured inverter.

[0038] Preferably, a four-part model is used to divide the wind speed into four components: basic component, slope component, gust component and turbulence component. It is mainly used in the simulation of wind power generation process and power system. The main parameters of the model are also calculated according to the corresponding power system parameters. ; In the formula for Wind speed at the moment (m / s); = average wind speed (m / s); Slope component (m / s); is the gust component (m / s); is the turbulent air volume (m / s).

[0039] Average wind speed It is obtained based on the rated power of the wind power generation system and the output power calculated by the flow. However, for variable speed and variable pitch wind power generation systems, there is no unique correspondence between the output power calculated by the flow and the wind speed, and the initial value of the wind speed or pitch angle needs to be given.

[0040] Preferably, the electrical system is the final link of energy conversion in the wind power generation process. For a direct-drive permanent magnet synchronous wind power generation system, it mainly includes electrical equipment such as generators and frequency converters. For the convenience of modeling, the following assumptions are made: magnetic saturation is ignored; all spatial harmonics in the magnetic field are ignored, and the magnetic flux distribution is sinusoidal; the fundamental frequency of the stator voltage and current is sinusoidal; any loss is ignored, excluding copper loss.

[0041] The mathematical model of the permanent magnet synchronous generator is established in the rotating coordinate system of constant power transformation. The model is built using the law of the generator and the positive direction is set according to the conventional method. The relationship between voltage and current can be derived from the voltage and flux equation. Compared with the dynamic simulation time of the electrical system, the transient-related time constant of the model used is very small, so the related transient quantity can be ignored.

[0042] The magnetic material of the permanent magnet synchronous generator rotor replaces the traditional rotor excitation winding, so the rotor voltage equation is ignored in the generator voltage equation.

[0043] In a preferred solution, in S2, without considering the connection line loss and component differences, the photovoltaic cell array is composed of solar cell components in series and parallel.

[0044] In a preferred solution, in S3, the low-order SOFC stack model is simplified, the physical process is ignored, and the Nernst equation and the working voltage of the SOFC define the Nernst voltage, activation voltage drop, ohmic voltage drop and concentration polarization voltage drop.

[0045] Preferably, if Figure 2 The figure shows the working principle of solid-state fuel cell SOFC. Its electrode reaction formula is as follows: Anode: H2+O 2 H2+2e - ; Cathode: O 2+ 4e - 2O 2- ; Overall reaction equation: H2+ O2 H2O.

[0046] In the preferred scheme, in S4, the low-order PEMFC stack model is simplified, the physical process is ignored, and the thermodynamic electromotive force, activation overvoltage, ohmic voltage drop and concentration overvoltage are defined by the output voltage of the solid-state fuel cell and the PEM fuel cell single cell; the dynamic characteristics of the cathode are defined by the law of conservation of energy, and the cathode pressure is defined according to the ideal gas law.

[0047] Preferably, the proton exchange membrane fuel cell PEMFC is mainly composed of a bipolar plate and a gas diffusion electrode, and the working principle diagram is as shown in Figure 3 , and its electrode reaction is as follows: Anode: H2 2H + +2e - ; cathode: O2+2H + O 2+ +2e -- 2H2O; Overall reaction equation: H2+ O2 H2O.

[0048] In a preferred solution, in S5, the model of the electrolyzer stack is simplified, assumptions are made for it, and a proton exchange membrane electrolyzer model, an alkaline electrolyzer model and an electrolyzer thermal model are established.

[0049] In a preferred embodiment, in S6, the pressure of the hydrogen storage tank is expressed by the Biting-Bridgeman equation, and the change in the hydrogen in the hydrogen storage tank, the net input molar flow of hydrogen, and the power consumed by the compressor for compressing the gas are calculated.

[0050] In a preferred solution, in S7, a Thevenin equivalent circuit model is applied, based on fitting a general battery model to a battery discharge characteristic curve, and is composed of a controlled voltage source connected in series with a constant resistor.

[0051] Preferably, if Figure 4 In the figure, it is the Thevenin equivalent circuit model, where is the battery terminal voltage (V); is the battery current (A); is the open circuit voltage of the battery (V); is the internal resistance of the battery (mΩ); is the polarization resistance (mΩ); is the capacitance (F).

[0052] Preferably, if Figure 5 In the figure, the voltage characteristic curves of different batteries during constant current discharge are similar.

[0053] In the preferred solution, in S8, the power DC-DC converter selects Buck type and Boost type, and based on the analysis of each system, a typical non-isolated Boost converter, a non-isolated Buck converter and a non-isolated bidirectional half-bridge converter model are established.

[0054] In the preferred solution, in S10, energy management tasks are established, energy management goals are formulated, and coordinated optimization scheduling is performed; energy scheduling based on the state control method includes the following steps: S10-1, net power is negative, hydrogen storage is positive, and the state of charge of the energy storage battery is below 20% ( Pnet <0, LH2 >0, SOC ≤20), the renewable energy will store the excess electricity in the battery and will not provide electricity for hydrogen production; S10-2, net power is negative, hydrogen storage is positive, and the state of charge of the energy storage battery is above 20% ( Pnet <0, LH2 >0, SOC >20), the renewable energy will store the excess electricity in the hydrogen tank and will not provide electricity for the battery; S10-3, net power is negative, hydrogen storage is non-positive ( Pnet <0, LH2 ≤0), the renewable energy will store the excess electricity in the hydrogen tank and will not provide electricity to the battery; S10-4, net power is non-negative, hydrogen storage is non-positive, and battery state of charge is below 20% ( Pnet >0, LH2 ≤0, SOC ≤20), the power grid neither provides power for the battery nor for hydrogen production; S10-5, net power is non-negative, hydrogen storage is positive, and battery state of charge is above 20% ( Pnet ≥0, LH2 >0, SOC ≤20), the grid stores the excess electricity in the hydrogen tank and does not provide electricity to the battery; S10-6, net power is non-negative, hydrogen storage is positive, and battery state of charge is above 20% ( Pnet ≥0, LH2 >0, SOC ≥20), the grid stores the excess electricity in the battery and does not provide electricity for hydrogen production; S10-7, net power is non-negative, hydrogen storage is non-positive, and battery state of charge is above 20% ( Pnet ≥0, LH2 ≤0, SOC ≥20), the grid stores the excess electricity in the battery and does not provide electricity for hydrogen production.

[0055] Embodiment 2, The operation requirements of the wind-solar coupled hydrogen production system include: 1. Wind power generation system operation requirements: The change of wind speed affects the output power of the wind turbine, and each curve has only one optimal wind energy utilization point. The control of the speed of the wind turbine can realize the control of the output power, maximize the capture of wind energy, and improve the utilization of wind energy; reduce the mechanical load of the unit and prevent the sudden change of mechanical load under various extreme conditions. Minimize the instantaneous overload, resonance, high-frequency load, etc. of the unit to ensure the safe and reliable operation of the unit; through the innovation of control technology and the improvement of control strategy, simplify the structure of the wind turbine generator set and reduce costs.

[0056] 2. Photovoltaic power generation system operation requirements: Ambient temperature and light intensity affect the output characteristics of photovoltaic cells. As light intensity and temperature change, the output characteristics of photovoltaic cell modules also change. The main parameters of photovoltaic cells include open circuit voltage, short circuit current, maximum operating current and maximum operating voltage. Each operating curve has only one maximum power point. Apply maximum power point tracking output power to the photovoltaic array to improve operating efficiency.

[0057] 3. Fuel cell power generation system operation requirements: The change of fuel cell stack operating temperature affects its output performance. Increasing the stack temperature is beneficial to improving the fuel Battery performance. In addition, increasing the pressure can also improve the performance of the fuel cell. These can be better reflected from the perspectives of thermodynamics and kinetics. Due to technical limitations, the pressure cannot be increased excessively to avoid 4. Electrolyzer operation requirements: From the analysis of the electrolyzer structure, it can be seen that the structural design of the proton exchange membrane limits its internal pressure from being too high, otherwise it will cause gas leakage between the two electrodes. Usually the internal pressure of the electrolyzer is around 0.3MPa. In addition, electrolyzers with different structures have different corresponding operating parameters.

[0058] The rate of hydrogen generation in the electrolytic cell is proportional to the current density. To avoid equipment damage. The current density of the electrolytic cell cannot exceed the limiting current density when it is working.

[0059] Embodiment 3, The wind-solar coupled hydrogen production system is a nonlinear, strongly coupled, multi-parameter high-order system, and its coordinated control strategy is relatively complex. It is necessary to control various system parameters and improve the overall performance to meet the actual engineering application.

[0060] The main functions of energy management of wind-solar coupled hydrogen production system include: collecting information such as power grid, renewable energy generation and load based on real-time monitoring system; realizing power generation forecast and load forecast of renewable energy such as wind power generation and photovoltaic power generation, formulating reasonable total output power target curve, and adjusting hydrogen fuel cell power generation power in real time to make the total output power of the system meet the planned arrangement; realizing seamless switching between multiple working modes of wind-solar coupled hydrogen production system; smooth output operation mode, using hydrogen fuel cell power generation system to compensate for the fluctuation component of a specific frequency band in the output power fluctuation of renewable energy power generation, so as to achieve the purpose of smoothing the output power of distributed power sources, etc.

[0061] like Figure 6 The energy management of wind-solar coupled hydrogen production system is composed of: 1. Real-time power balance of wind-solar coupled hydrogen production system. Mainly includes: adjusting the output of wind turbines and photovoltaic arrays according to the capacity of renewable energy such as wind turbines and photovoltaic arrays and the energy storage level of energy storage devices, tracking load changes in real time, and realizing voltage adjustment and frequency control.

[0062] Energy management. Mainly includes: predicting the output of renewable energy and the capacity that the energy storage unit should maintain based on the changes in renewable energy, environmental factors, detection cycles, etc.; specifying the output of each power generation unit in the system based on economic scheduling and optimized operation strategies, etc.

[0063] 2. The goals of energy management of wind-solar coupled hydrogen production systems include: developing coordinated optimization control technologies for the grid-connected operation of multiple renewable energy sources, such as wind-solar-hydrogen complementary optimization control, utilizing the characteristics of fuel cell energy storage systems, effectively suppressing the volatility of renewable energy power generation output power, and promoting the development of renewable energy technologies.

[0064] When connected to the grid, the system provides two operating modes: using the hydrogen fuel cell power generation system to compensate for the fluctuation component of a specific frequency band in the output power fluctuation of renewable energy, so as to achieve the purpose of smoothing the output power of renewable energy; according to the predicted value of renewable energy output power, the power generation plan of the power grid, etc., a reasonable total output power target curve is formulated, the hydrogen fuel cell power generation power is adjusted in real time, and the planned output curve is tracked to ensure that the total output power of the system meets the planned arrangement.

[0065] 3. The wind-solar coupled hydrogen production system is a highly strongly coupled nonlinear system, and the control of this type of system has always been a hot topic of research. Fuzzy logic control (FLC) is a rule-based control. Since it directly adopts language-based control rules, it is not necessary to establish an accurate mathematical model of the controlled object during the design process. The system is highly robust and has great advantages in solving nonlinear control problems.

[0066] Artificial neural networks (ANNs) are mathematical models with learning and parallel data processing capabilities, which use computational neurons (nonlinear units) formed in layers and connected to each other through weight factors. Due to its nonlinear and adaptive structure, it has good generalization ability and the advantages of being independent of system parameter design. But it is like a black box, lacks transparency, and cannot express the reasoning function of the human brain well. The adaptive neural fuzzy reasoning system (ANFIS) combines the autonomous learning ability of neural networks and the advantages of fuzzy systems in interpreting complex systems. It overcomes the shortcomings of neural network algorithms that are prone to fall into local optimal values ​​and the need for complete expert experience in fuzzy systems. It is very suitable for wind-solar coupled hydrogen production systems with strong nonlinearity and large environmental impact.

[0067] ANFIS is an inference system with autonomous learning ability. After obtaining a large amount of training data, it adjusts various parameters, including membership functions and fuzzy rules, through autonomous learning. The membership function parameters must be adjusted through training data. The adaptive error back propagation method is used to update the weights of each period. In order to avoid overfitting problems during estimation, the data set is randomly divided into two groups: training set (70% of the data) and validation data set (30%), including a test data set (15%) to check the generalization ability of the generated ANFIS, and a test data set (15%) to control the possibility of the model overfitting the data. Both data sets (test data set and verification data set) are different from the training data set. The final error is defined by the root mean square error between the current value and the expected output value.

[0068] From the structure of ANFIS, we can know that this algorithm is a typical adaptive network. When the parameters of the antecedent are fixed, the total output can be expressed as a linear combination of the parameters of the consequent. The algorithm can be implemented by gradient descent or hybrid algorithm. Methods such as BP and least squares estimation are used to learn and adjust the antecedent and consequent parameters of the system.

[0069] In the process of the development of the ANFIS algorithm, scholars have improved it to better suit it to solve problems in different fields. The complexity of the problem itself, the number of data points selected in the training set, the setting of relevant target errors and other factors affect the improvement of the BP algorithm. Through a large number of algorithms in different research fields, the following conclusions were drawn: when the network weight is within a few hundred, the least squares estimation method is selected. This method has the fastest convergence speed and is suitable for solving function approximation problems; when the number of network weights is large, or high training accuracy is required, the conjugate gradient method is selected. This method has a faster convergence speed than other methods. The proportional conjugate gradient method has obvious advantages over other algorithms in solving such problems. The elastic BP method has advantages in solving pattern recognition problems.

[0070] like Figure 7 The overall control block diagram of the ANFIS-based monitoring system is shown in Figure 2. The control system has three inputs, namely, battery state of charge, hydrogen tank capacity, and net power. netP (Power required by the grid dP Renewable power generated with wind turbines and photovoltaic arrays wxya The system has one output, the battery reference power. The hydrogen reference power (fuel cell and electrolyzer) is calculated as the difference between the net power and the battery reference power. This power is limited to avoid over-charging or over-discharging of the battery or hydrogen tank.

[0071] The demand power is determined by the power dispatch system based on the reference power required by the system operator, which is defined taking into account the maximum available power in the hybrid system. Vp ) is the sum of the power generated by renewable energy (wind turbines and photovoltaics), hydrogen and the maximum available power in the battery. The maximum available power of hydrogen is defined as the maximum power of the fuel cell that can be generated by exhausting the current hydrogen capacity in a day. Similarly, the maximum available power in the battery is defined as the maximum power that the battery consumes until 20% of the state of charge in a day. The required power should be less than or equal to the maximum available power.

[0072] To determine the membership function, sufficient training and test data are selected from the results obtained from the energy management system and applied to the hybrid system study. In fact, each process is simulated by randomly inputting the battery state of charge, hydrogen capacity and net power to obtain the battery power values ​​used as training and test data. The battery state of charge (SOC) and hydrogen capacity ( H 2 L ) varies between 0 and 100%. The net power limit is the sum of the maximum electrolyzer power and the maximum battery charging power (minimum value), and the sum of the maximum fuel cell power and the maximum battery discharging power (maximum value).

[0073] The above-mentioned embodiments are only preferred technical solutions of the present invention and should not be regarded as limitations of the present invention. The embodiments and features in the embodiments of the present application can be arbitrarily combined with each other without conflict. The protection scope of the present invention shall be the technical solutions recorded in the claims, including the equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. An energy dispatching method for hydrogen production by combining power grid and photovoltaic, characterized in that: The steps include: S1, wind power generation system modeling, establish mathematical models of wind speed model, power conversion model, variable pitch system model and permanent magnet synchronous motor rotor; S2, photovoltaic power generation system modeling, establishing a photovoltaic cell model based on the equivalent circuit of the photovoltaic cell; S3, SOFC modeling, to establish an electrochemical model based on solid-state fuel cell SOFC; S4, PEMFC modeling, establish a cathode and anode model based on proton exchange membrane fuel cell; S5, electrolyzer modeling, establishing an electrolyzer model based on PEME and AE models; S6, hydrogen energy storage modeling, establishing a pressure model based on hydrogen storage tanks; S7, energy storage battery modeling, establishing an equivalent mathematical model based on an equivalent circuit; S8, power converter modeling, build Boost and Buck DC / DC converter models; S9, simulation, numerical simulation verification of each system to obtain system performance related parameters; S10, energy scheduling, uses the hydrogen fuel cell power generation system to compensate for the fluctuation component of a specific frequency band in the output power fluctuation of renewable energy, and adjusts the hydrogen fuel cell power generation power in real time.

2. The energy dispatching method for hydrogen production by combining power grid and photovoltaic power generation according to claim 1 is characterized in that: In S1, the wind speed model divides the wind speed into four components: basic component, slope component, gust component and turbulence component, which are used in the simulation of wind power generation process and power system; The power conversion model outputs mechanical power through power conversion based on the theory of aerodynamics and combined with the steady-state power characteristics of the wind turbine; the variable pitch system model uses the closed-loop structure of the variable pitch system to simplify it into a first-order dynamic system, including speed limit and amplitude limit links; in the mathematical model, the permanent magnet synchronous generator is completely decoupled from the power grid, and the exchange of reactive power with the power grid is completely carried out through the network-measured inverter.

3. The energy dispatching method for hydrogen production by combining power grid and photovoltaic power generation according to claim 1 is characterized by: In S2, without considering the connection line loss and component differences, the photovoltaic cell array is composed of solar cell components connected in series and parallel.

4. The energy dispatching method for hydrogen production by combining power grid and photovoltaic power generation according to claim 1 is characterized by: In S3, the low-order SOFC stack model is simplified, the physical process is ignored, and the Nernst equation is used to define the Nernst voltage, activation voltage drop, ohmic voltage drop, and concentration polarization voltage drop of the SOFC operating voltage.

5. The energy dispatching method for hydrogen production by combining power grid and photovoltaic power generation according to claim 1 is characterized in that: In S4, the low-order PEMFC stack model is simplified, the physical process is ignored, and the thermodynamic electromotive force, activation overvoltage, ohmic voltage drop and concentration overvoltage are defined by the output voltage of the solid-state fuel cell and the PEM fuel cell. The dynamic characteristics of the cathode are defined by the energy conservation theorem, and the cathode pressure is defined according to the ideal gas law.

6. The energy dispatching method for hydrogen production by combining power grid and photovoltaic power generation according to claim 1 is characterized by: In S5, the model of the electrolyzer stack is simplified, assumptions are made for it, and a proton exchange membrane electrolyzer model, an alkaline electrolyzer model, and an electrolyzer thermal model are established.

7. The energy dispatching method for hydrogen production by combining power grid and photovoltaic power generation according to claim 1 is characterized in that: In S6, the pressure of the hydrogen storage tank is expressed by the Biting-Bridgeman equation, and the change in the hydrogen in the hydrogen storage tank, the net input molar flow rate of hydrogen, and the power consumed by the compressor for compressing the gas are calculated.

8. The energy dispatching method for hydrogen production by combining power grid and photovoltaic power generation according to claim 1 is characterized by: In S7, the Thevenin equivalent circuit model is applied, based on fitting the general battery model to the battery discharge characteristic curve, which consists of a controlled voltage source connected in series with a constant resistance.

9. The energy dispatching method for hydrogen production by combining power grid and photovoltaic power generation according to claim 1 is characterized in that: In S8, the power DC-DC converters are selected as Buck type and Boost type. Based on the analysis of each system, the typical non-isolated Boost converter, non-isolated Buck converter and non-isolated bidirectional half-bridge converter models are established.

10. The energy dispatching method for hydrogen production by combining power grid and photovoltaic power generation according to claim 1 is characterized in that: In S10, energy management tasks are established, energy management goals are formulated, and scheduling is coordinated and optimized; energy scheduling based on the state control method includes the following steps: S10-1, net power is negative, hydrogen storage is positive, and the state of charge of the energy storage battery is below 20% ( Pnet <0, LH2 >0, SOC ≤20), the renewable energy will store the excess electricity in the battery and will not provide electricity for hydrogen production; S10-2, net power is negative, hydrogen storage is positive, and the state of charge of the energy storage battery is above 20% ( Pnet <0, LH2 >0, SOC >20), the renewable energy will store the excess electricity in the hydrogen tank and will not provide electricity for the battery; S10-3, net power is negative, hydrogen storage is non-positive ( Pnet <0, LH2 ≤0), the renewable energy will store the excess electricity in the hydrogen tank and will not provide electricity to the battery; S10-4, net power is non-negative, hydrogen storage is non-positive, and battery state of charge is below 20% ( Pnet >0, LH2 ≤0, SOC ≤20), the power grid neither provides power for the battery nor for hydrogen production; S10-5, net power is non-negative, hydrogen storage is positive, and battery state of charge is above 20% ( Pnet ≥0, LH2 >0, SOC ≤20), the grid stores the excess electricity in the hydrogen tank and does not provide electricity to the battery; S10-6, net power is non-negative, hydrogen storage is positive, and battery state of charge is above 20% ( Pnet ≥0, LH2 >0, SOC ≥20), the grid stores the excess electricity in the battery and does not provide electricity for hydrogen production; S10-7, net power is non-negative, hydrogen storage is non-positive, and battery state of charge is above 20% ( Pnet ≥0, LH2 ≤0, SOC ≥20), the grid stores the excess electricity in the battery and does not provide electricity for hydrogen production.

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