Electro-hydrogen coupling energy storage system power distribution control method based on double-layer fuzzy mapping

Abstract

The invention provides an electro-hydrogen coupling energy storage system power distribution control method based on double-layer fuzzy mapping, and the method comprises the steps: collecting the current of a battery in a battery energy storage system, and obtaining the new mapping of the battery through single-layer fuzzy mapping; the hydrogen energy storage system is simulated, and new mapping is obtained through a single-layer fuzzy mapping mechanism by means of the hydrogen state; judging the working area of the electrolytic cell at the transient moment according to the transient electrolytic cell energy conversion efficiency and the change of the electrolytic cell current, considering the electrolytic cell energy conversion efficiency, and obtaining new mapping of the electrolytic cell through a double-layer fuzzy mapping mechanism; the new mapping of the battery and the new mapping of the electrolytic cell are used as self-adaptive adjustment droop coefficients, and reference voltage is obtained through droop control, so that power distribution under different conditions is realized. According to the invention, the service life of the battery can be prolonged during the operation of the electro-hydrogen coupling micro-grid, the safe state of the hydrogen storage tank and the operation of the electrolytic cell with high energy conversion efficiency during the working process are ensured, and the stable operation of the system is ensured during reasonable power distribution.

Description

Technical Field

[0001] The present invention relates to the technical field of power electronics, and in particular to a power distribution control method for an electric-hydrogen coupled energy storage system. Background Art

[0002] With the continuous growth of global energy demand and the increasing severity of environmental problems, the use of traditional fossil energy is gradually being replaced by clean renewable energy. The utilization rate of renewable energy (such as solar energy, wind energy, etc.) continues to increase, but due to its intermittent and volatile nature, it poses a huge challenge to the stable operation of the power system. In order to cope with these problems, microgrid technology has emerged, which integrates distributed energy resources and energy storage equipment to achieve local self-regulation and optimization of electricity. However, traditional battery energy storage has limitations in capacity and life. Hydrogen energy storage technology has become an important supplement to microgrid systems with its advantages such as high energy density and long-term storage capacity. The electric-hydrogen coupled microgrid uses water electrolysis to produce hydrogen, hydrogen storage and fuel cell power generation technology to convert excess electricity into hydrogen energy for storage, and convert hydrogen energy into electricity when needed, thereby achieving efficient coordinated scheduling of electricity and hydrogen energy.

[0003] At present, the research methods for power distribution of electric-hydrogen coupled microgrids mainly include methods based on optimization algorithms and predictive control. Optimization algorithm is one of the most common methods in the study of power distribution of electric-hydrogen coupled microgrids. By establishing a mathematical model, the electricity and hydrogen energy in the microgrid are optimized and dispatched. However, the electric-hydrogen coupled microgrid involves the coupling of the power system and the hydrogen energy system. The system structure is complex, and the calculation complexity of the optimization scheduling algorithm is high. In practical applications, the model and algorithm need to be simplified. Predictive control predicts the system state in the future and optimizes the power distribution at the current moment based on the prediction results. However, predictive control is based on historical data, has a high dependence on data, and issues instructions through a central controller, which inevitably brings communication problems. Therefore, it is very necessary to consider how to achieve power distribution of electric-hydrogen coupled microgrids while reducing data communication and considering multiple factors.

[0004] Droop control has been deeply cultivated in the field of control systems for many years. It can achieve power distribution between different energy storage units by simply collecting local information, reducing information interaction. However, traditional droop control methods show limitations in dealing with the challenges of real-time changes in energy storage unit information in electric-hydrogen coupled microgrid systems. Therefore, by considering multiple state factors to design a time-varying droop coefficient, the system can adjust and optimize power distribution in real time, improving the stability and reliability of the system. By introducing multiple factors such as battery life, hydrogen storage tank safety, and electrolyzer energy conversion efficiency into the droop coefficient design, it is expected to promote the deep integration of hydrogen energy and power systems.

[0005] The invention patent with application number 202410143094.1 discloses a composite energy management strategy suitable for off-grid wind-solar-hydrogen storage coupling system. In view of the poor comprehensive performance of the current hybrid energy storage energy management, the off-grid wind-solar-hydrogen storage coupling system model is first constructed to divide the action time of the composite energy management strategy; then a state machine control strategy based on fuzzy control is established to divide the operation mode, and fuzzy control is introduced when the energy storage reserve capacity is sufficient to reasonably coordinate the electric / hydrogen hybrid energy storage power; finally, a weight adaptive model predictive control strategy is established, the system state space equation and objective function are constructed, and the weights are adaptively adjusted during the rolling optimization process to improve the energy management efficiency. The results show that the composite energy management strategy can take into account the accuracy, reliability and real-time performance of the system energy management. However, the above patent has high requirements for model accuracy and strong dependence on data requirements. Summary of the invention

[0006] In view of the technical problems that the existing power allocation method of electric-hydrogen coupled microgrid has high computational complexity, high demand for data communication, and dependence on model accuracy, the present invention proposes a power allocation control method for electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping to achieve reasonable power allocation of the system.

[0007] In order to achieve the above object, the technical solution of the present invention is implemented as follows: a power distribution control method of an electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping, the steps of which are as follows:

[0008] S1: Establish an electric-hydrogen coupled microgrid model, collect the battery current in the battery energy storage system, and obtain a new mapping soc considering battery life through a single-layer fuzzy mapping * ;

[0009] S2: Considering the safety of hydrogen storage tanks, the hydrogen energy storage system is simulated, and the hydrogen state sohs in the hydrogen storage tank is used to obtain a new mapping sohs through a single-layer fuzzy mapping mechanism. * ;

[0010] S3: According to the transient electrolytic cell energy conversion efficiency and the change of electrolytic cell current, the electrolytic cell working area at the transient moment is determined. Considering the electrolytic cell energy conversion efficiency, a new mapping sohs is obtained through a double-layer fuzzy mapping mechanism. ** ;

[0011] S4: Using the new mapping soc * and the new mapping sohs ** As the droop coefficient of adaptive regulation, the reference voltage is obtained through droop control, thereby realizing power distribution in different situations.

[0012] Preferably, the new mapping soc that takes into account the battery life is obtained by single-layer fuzzy mapping. *The method is as follows: the electric-hydrogen coupled microgrid model includes photovoltaic panels, a battery energy storage system and a hydrogen energy storage system, and the battery energy storage system includes batteries and supercapacitors SC b , hydrogen energy storage system includes fuel cell, supercapacitor SC h and electrolyzers;

[0013] The battery current value i is calculated by using the ampere-hour integration method. b The original soc of the battery is obtained by integration; the single-layer fuzzy mapping converts the battery current value i b The original soc of the battery is used as input to obtain the membership value through the divided range and membership function Then, the output membership value is obtained according to the fuzzy rules Membership value for the output Defuzzification and normalization are performed to obtain a new mapping soc * ;in, Represents the membership set corresponding to the output.

[0014] Preferably, the new mapping soc * The calculation method is: input set (i b ,soc) obtains the membership set corresponding to the input through the fuzzy mapping of the battery, in, are the battery current values ​​i b And the specific membership value corresponding to the original soc of the battery, x soc (1,) and x soc (,1) respectively represent the input battery current value i b and the original soc of the battery; the membership value of the output is obtained according to the fuzzy rule Representation Defuzzification and normalization give a new mapping in, Represents the normalization of the output new mapping value i=1,2;j=1,2,3;n=1,2···6

[0015] The maximum value should be Represents a new mapping set obtained by defuzzification and normalization; i takes 1 or 2 to represent the charge and discharge state, j takes 1, 2 or 3 to represent dividing the original soc of the battery into three different ranges: low, medium and high, and n is the index of the six fuzzy rules.

[0016] Preferably, the new mapping sohs is obtained by a single-layer fuzzy mapping mechanism * The method is: collect the electrolytic cell input current value i ele and the fuel cell current value i fc , add the two together to get the current working state of the hydrogen energy system i h ,ih Negative, i.e., hydrogen production state or i h The hydrogen energy system working state is i h The hydrogen state sohs in the hydrogen storage tank is used as the first layer fuzzy mapping input variable to obtain a new mapping sohs that considers the safety of the hydrogen storage tank * :The hydrogen energy system working state i h and hydrogen state sohs as two inputs, and the membership value u is obtained through the divided range and membership function ih,i (x sohs (1,)),u sohs,j (x sohs (,1)), and then the output membership value is obtained according to the fuzzy rule Finally, defuzzification and normalization are performed to obtain the new mapping sohs * ;in, Represents the membership set corresponding to the output.

[0017] Preferably, the new mapping sohs * The calculation method is:

[0018]

[0019] Among them, i is 1 or 2, indicating the current working state of the hydrogen energy system, i.e., the electrolyzer or fuel cell is working; j is 1, 2, or 3, indicating that the hydrogen state sohs is divided into three different ranges; n is the index of the six fuzzy rules; f sohs,fuzzy represents the fuzzy mapping of the first layer of the hydrogen energy system, X sohs represents the input set, (i h ,sohs) is the specific value of the input set; Y sohsF Represents the membership set corresponding to the input, They are working status i h and the specific membership value corresponding to the hydrogen state sohs, x sohs (1,) and x sohs (,1) respectively represent the input working state i h and hydrogen state sohs; Represents the membership set corresponding to the output, To output specific membership values; represents the new set of mappings obtained by defuzzification and normalization, Represents the maximum value corresponding to the normalization of the output new mapping value.

[0020] Preferably, in the hydrogen energy storage system, the mathematical model of the electrolyzer is:

[0021]

[0022] Among them, V ele is the voltage at the cell terminals, V rev 、V ohm 、V con are respectively the reversible voltage, the resistance overvoltage caused by ohmic polarization and the concentration polarization overvoltage, N is the number of electrolytic cells, V o output voltage for the entire electrolyzer unit;

[0023] In the hydrogen energy storage system, the mathematical model of the fuel cell is:

[0024]

[0025] Among them, V fc is the fuel cell operating voltage, i fc is the fuel cell operating current, A is the cross-sectional area of ​​the proton exchange membrane, n fc is the number of fuel cell units, P H2 and P O2 are the inlet pressures of hydrogen and oxygen, respectively, l is the equivalent voltage at the minimum calorific value of hydrogen, σ, δ 1 , δ 2 , δ 3 , δ 4 、m 1 、m 2 , R t All are empirical coefficients;

[0026] In the hydrogen energy storage system, the mathematical model of the hydrogen storage tank is:

[0027]

[0028] Among them, T s is the hydrogen storage tank temperature, V s is the capacity of the hydrogen storage tank, R s is the gas constant, n eleH2 is the rate of hydrogen production, n fcH2 is the rate at which the fuel cell consumes hydrogen, sohs is the state of hydrogen in the hydrogen storage tank, P s is the real-time pressure of the hydrogen storage tank, P SMAX is the maximum pressure of the hydrogen storage tank.

[0029] Preferably, the reversible voltage, the resistance overvoltage caused by ohmic polarization and the concentration polarization overvoltage

[0030]

[0031] Where T is the operating temperature, i ele is the working current of the electrolytic cell, A ele is the cathode plate area, r 1 、r2 、s 1 、s 2 、s 3 ,t 1 ,t 2 ,t 3 , α are adjustment coefficients;

[0032] The rate at which the electrolyzer produces hydrogen The rate at which the fuel cell consumes hydrogen Where z is the change in the chemical valence of the reactants.

[0033] Preferably, a new mapping sohs will be considered for the safety of the hydrogen storage tank when the electrolyser is in operation * The working area of ​​the electrolytic cell at the instantaneous state is used as the input of the fuzzy mapping, and the working area is determined and the new mapping sohs * As input, the membership value is obtained through the membership function Then, the output membership value is obtained according to the fuzzy rules Finally, defuzzification and normalization are performed to obtain the new mapping sohs ** , the calculation method is:

[0034]

[0035] in, Fuzzy mapping representing the second layer of the hydrogen energy system, sohs * For the input set The specific value of The membership set Y corresponding to the output sohs*F The specific membership value of Represents the new mapping sohs of the input * ;sohs ** Get a new set of mappings for defuzzification and normalization New mapping of ; Represents the maximum value corresponding to the normalization of the output new mapping value.

[0036] Preferably, the method for determining the working area of ​​the electrolytic cell at the transient moment is: according to the working state of the electrolytic cell, the current value i of the electrolytic cell is collected by a sensor. ele And calculate the energy conversion efficiency η from electrical energy to chemical energy in the electrolytic cell; according to the electrolytic cell current value i ele The energy conversion efficiency η divides the working state of the electrolytic cell into four regions when the transient power fluctuates: Region 1, the electrolytic cell current value i ele As the energy conversion efficiency η increases, the energy conversion efficiency η also increases; in area 2, the electrolytic cell value i ele As the current increases, the energy conversion efficiency η decreases; in region 3, the electrolytic cell current value iele decreases, the energy conversion efficiency η decreases accordingly; in area 4, the electrolytic cell current value i ele decreases, and the energy conversion efficiency η increases instead.

[0037] Preferably, the energy conversion efficiency η is:

[0038]

[0039] Where K is the electrochemical reaction coefficient, R h is the chemical calorific value of hydrogen, β is the temperature adjustment coefficient, F is the Faraday constant, λ is the heat dissipation coefficient, and S is the entropy value at the working temperature T;

[0040] The droop control is as follows: the voltage reference values ​​of the battery energy storage system and the hydrogen energy storage system are respectively:

[0041] V b,ref =V nom -R 1 ·i bdc

[0042] V h,ref =V nom -R 2 ·i hdc

[0043]

[0044] Where V nom is the rated voltage, V b,ref and V h,ref are the voltage reference values ​​of the battery energy storage system and the hydrogen energy storage system, R 1 , R 2 is the time-varying droop coefficient, i bdc 、i hdc They are the current values ​​output by the battery energy storage and hydrogen energy storage through the converter respectively;

[0045] The time-varying droop coefficients are Among them, charge means that the battery is in a charging state, discharge means that the battery is in a discharging state, fc means that the fuel cell is working, and ele means that the electrolyzer is working.

[0046] Compared with the prior art, the present invention has the following beneficial effects: the battery energy storage and hydrogen energy storage are realized by adaptively adjusting the droop coefficient through a double-layer fuzzy mapping mechanism, and the battery life, hydrogen storage tank safety status, electrolyzer energy conversion efficiency and other issues are considered at the same time during power distribution, and the battery energy storage and hydrogen energy storage in the isolated DC microgrid are realized by adjusting the droop coefficient under the condition of a double-layer fuzzy mapping mechanism to realize adaptive droop control, and then the duty cycle is generated by the voltage and current loop to control the power distribution of the battery energy storage and hydrogen energy storage. The present invention first samples the battery current and considers the battery life through a single-layer fuzzy mapping to obtain a new mapping relationship of soc (battery state of charge) * ; Secondly, the electrolyzer current is sampled and the energy conversion efficiency is calculated. After the double-layer fuzzy mapping mechanism is used to consider the safety of the hydrogen storage tank in the hydrogen energy system and the energy conversion efficiency of the electrolyzer during operation, a double-layer mapping relationship about sohs (hydrogen state of the hydrogen storage tank) is obtained: sohs ** ; After that, the new SOC mapping relationship and the double-layer mapping relationship of SOHS are normalized and adjusted as the time-varying droop coefficient to perform adaptive droop control on battery energy storage and hydrogen energy storage. In this way, the present invention can extend the battery life of the electric-hydrogen coupled microgrid during operation, ensure the safe state of the hydrogen storage tank, and realize the operation of the electrolyzer with a higher energy conversion efficiency during the working process, while ensuring the stable operation of the system when the power is reasonably distributed. The present invention is suitable for the power distribution task of the electric-hydrogen coupled microgrid, and can reasonably control the power distribution of the battery energy storage system and the hydrogen energy storage system according to the intermittent fluctuations of renewable energy and changes in load demand, maintain the bus voltage stability, and protect the safety of electric energy. Compared with other power control methods for electric-hydrogen coupled microgrids, the present invention reduces the communication burden through droop control, and when distributing power, it also takes into account the battery life, ensures the safety of the hydrogen storage tank and takes into account the energy conversion efficiency of the electrolyzer, which is in line with actual engineering applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1 It is a flow chart of the present invention.

[0049] Figure 2 It is a schematic diagram of the system model structure of the present invention.

[0050] Figure 3 It is a fuzzy surface diagram of the battery energy storage system under the single-layer fuzzy mapping of the present invention.

[0051] Figure 4 It is a fuzzy surface diagram of the hydrogen energy storage system under the single-layer fuzzy mapping of the present invention.

[0052] Figure 5 It is a transient working area diagram of the electrolytic cell of the present invention.

[0053] Figure 6 It is a fuzzy surface diagram of the hydrogen energy storage system under the double-layer fuzzy mapping of the present invention.

[0054] Figure 7 It is a diagram of the simulation results of system power allocation under the double-layer fuzzy mapping mechanism of the present invention.

[0055] Figure 8 The system power distribution of the present invention is the electrolytic cell working area judgment and R 2 Variation of droop coefficient.

[0056] Fig. 9 It is a system power allocation flow chart of the present invention. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] like Figure 1 The present invention is a power distribution control method for an electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping, comprising designing a new mapping soc that considers battery life by sampling battery current through single-layer fuzzy mapping. * , design the sampling electrolyzer current through the double-layer fuzzy mapping mechanism to obtain a new mapping sohs that takes into account the safety of the hydrogen storage tank and the energy conversion efficiency ** , introduce state judgment to obtain the electrolyzer working area at the transient moment, obtain the reference voltage by adaptively adjusting the droop coefficient through droop control, track the reference voltage generated by the droop control through the voltage and current loop, and realize reasonable power distribution among different energy storage systems. Through this method, the battery life, hydrogen storage tank safety, and electrolyzer energy conversion efficiency are guaranteed while power distribution, while maintaining the stability of the bus voltage. The present invention specifically includes the following steps:

[0059] S1: Establish an electric-hydrogen coupled microgrid model, collect battery current, and obtain a new mapping soc considering battery life through single-layer fuzzy mapping * .

[0060] S1.1. Establish a microgrid battery energy storage and hydrogen energy storage system model, such as Figure 2 As shown, it includes photovoltaic panels, battery energy storage system and hydrogen energy storage system. The battery energy storage system includes batteries and supercapacitors SC b , hydrogen energy storage system includes fuel cell, supercapacitor SC h and electrolyzer. The current sensor collects the photovoltaic panel current value i pv , battery current value i in battery energy storage system b and the supercapacitor current value i bsc , the fuel cell current value i in the hydrogen energy storage system fc and the supercapacitor current value i hsc and the electrolytic cell current value i ele , battery energy storage and hydrogen energy storage after passing through the converter bdc and the current value i hdc The voltage sensor collects the battery voltage value v b 、Supercapacitor voltage value v in battery energy storage system bsc , Supercapacitor SC in hydrogen energy storage system h The voltage value v hsc and bus voltage value v o . L and C represent the inductance and capacitance of the link energy storage element.

[0061] S1.2, the original soc of the battery adopts the common ampere-hour integration method Calculate, where soc(t 0 ) is the initial soc value, C bat is the rated capacity of the battery, i b is the battery current value. 0 and t represent the starting time and current time of the battery current value respectively.

[0062] S1.3, the sampled battery current value i b and the calculated original soc as input, a new soc mapping considering battery life is obtained through a single-layer fuzzy mapping, which is defined as the new mapping soc * , as shown in formula (1) and Figure 3 As shown in the figure, i is 1 or 2 to indicate the charge and discharge state, j is 1, 2 or 3 to indicate that the SOC is divided into three different ranges: low (0-20%), medium (20%-80%) and high (80%-100%), and n is the index of the six fuzzy rules. First, the battery current value i b The original soc is used as two inputs to obtain the membership value through the divided range and membership function. Then, the output membership value is obtained according to the fuzzy rules Use w n Simple representation, finally defuzzification and normalization to get the new mapping soc * .

[0063]

[0064] Among them, f soc,fuzzy Represents the fuzzy map of the battery, X soc represents the input set, (i b ,soc) is the specific value; Y socF Represents the membership set corresponding to the input, for i b , the specific membership value corresponding to soc, x sohs (1,) and x sohs (,1) respectively represent the input working state i h and hydrogen state sohs; Represents the membership set corresponding to the output, is the specific membership value; represents the new mapping set obtained by defuzzification and normalization, soc * is a specific value; Represents the maximum value corresponding to the normalization of the output new mapping value. Figure 3 According to the membership function and fuzzy rules, Figure 3 It can be seen that the relationship between the designed battery fuzzy mapping input and output.

[0065] In this example, the photovoltaic, battery and supercapacitor input voltages are 12V, the inductance value L is 3mH, the capacitance value C is 500μF, and the sampling frequency is 10000HZ, which is convenient for experimental verification and testing.

[0066] S2: Considering the safety of hydrogen storage tanks, a new mapping sohs is obtained through a single-layer fuzzy mapping mechanism * .

[0067] S2.1: In the hydrogen energy storage system, the mathematical model of the electrolyzer is:

[0068]

[0069] Among them, V ele is the voltage at the cell terminals, V rev 、V ohm 、V con are respectively the reversible voltage, the resistance overvoltage caused by ohmic polarization and the concentration polarization overvoltage, N is the number of electrolytic cells, V o Output voltage for the entire electrolytic cell unit. In this example, the number of electrolytic cells is set to 4. And

[0070]

[0071] Where T is the operating temperature, i ele is the working current of the electrolytic cell, Aele is the cathode plate area, r 1 、r 2 、s 1 、s 2 、s 3 ,t 1 ,t 2 ,t 3 , α are adjustment coefficients.

[0072] In this example, the operating temperature T is 40°C and the cathode plate area A ele 0.2m 2 , adjustment coefficient r 1 、r 2 、s 1 、s 2 、s 3 ,t 1 ,t 2 ,t 3 and α are 2.3e-3Ωm respectively 2 、-1.107e-7Ωm 2 ℃ -1 ,1.286e-1V, 2.378e-3V℃, -0.606e-5V℃ -2 , 3.559e-2m 2 A -1 、-1.3029e-2m 2 ℃A -1 , 2.513e-3m 2 ℃ 2 A -1 , 2m -2 . This makes the model voltage-current curve more consistent with the electrical characteristics of the actual object.

[0073] The energy conversion efficiency from electrical energy to chemical energy in the electrolyzer is:

[0074]

[0075] Among them, η is the energy conversion efficiency, K is the electrochemical reaction coefficient, R h is the chemical calorific value of hydrogen, β is the temperature adjustment coefficient, F is the Faraday constant, λ is the heat dissipation coefficient, and S is the entropy value at the working temperature T.

[0076] In this example, the electrochemical reaction coefficient K is 1300 and the chemical energy calorific value R h 284.7 kJmol -1 , the temperature adjustment coefficient β is 2.98e-3, and the Faraday constant F is 96485Cmol -1 , the heat dissipation coefficient λ is 0.3, and the entropy value S is 90 Jmol -1 K-1 . This makes the model efficiency-current curve more consistent with the actual electrical characteristics.

[0077] S2.2: In the hydrogen energy storage system, the mathematical model of the fuel cell is:

[0078]

[0079] Among them, V fc is the fuel cell operating voltage, i fc is the fuel cell operating current, A is the cross-sectional area of ​​the proton exchange membrane, n fc is the number of fuel cell units, P H2 and P O2 are the inlet pressures of hydrogen and oxygen, respectively, l is the equivalent voltage at the minimum calorific value of hydrogen, σ, δ 1 ,δ 2 ,δ 3 ,δ 4 、m 1 、m 2 , R t All are empirical coefficients. Fuel cell operating voltage V fc Used to calculate the power of fuel cells in simulation tests.

[0080] In this example, the cross-sectional area of ​​the proton exchange membrane is 50 cm 2 , the number of fuel cells n fc is 2, the equivalent voltage l is 1.5, and the empirical coefficients σ and δ 1 ,δ 2 ,δ 3 ,δ 4 、m 1 、m 2 , R t They are 15.9, 0.4185, 0.0135, 0.2, -4e-5, 0.2083, 50.73, and 4e-5 respectively, making the model voltage-current curve more consistent with the electrical characteristics of the real object.

[0081] S2.3: In the hydrogen energy storage system, the mathematical model of the hydrogen storage tank is:

[0082]

[0083] Among them, T s is the hydrogen storage tank temperature, V s is the capacity of the hydrogen storage tank, R s is the gas constant, n eleH2 is the rate of hydrogen production, n fcH2 is the rate at which the fuel cell consumes hydrogen, sohs is the state of hydrogen in the hydrogen storage tank, P s is the real-time pressure of the hydrogen storage tank, PSMAX is the maximum pressure of the hydrogen storage tank. In this example, the hydrogen storage tank temperature T s At 25℃, the hydrogen storage tank capacity is v s is 30, the maximum pressure of the hydrogen storage tank is P SMAX is 100. This is convenient for simulation and experimental verification.

[0084] The rate at which the electrolyzer produces hydrogen and the rate at which the fuel cell consumes hydrogen are:

[0085]

[0086] Where z is the change in the chemical valence of the reactants. The rate at which the electrolyzer produces hydrogen The rate at which the fuel cell consumes hydrogen Used to calculate the hydrogen content in the hydrogen storage tank.

[0087] The working principle of the hydrogen energy storage system is: the electrolyzer converts electrical energy into hydrogen and stores it in the hydrogen storage tank, and the hydrogen storage tank converts hydrogen back into electrical energy through the fuel cell, achieving a closed-loop operation of hydrogen production-storage-use. The model of the hydrogen energy storage system in the simulation is completed through steps S2.1-S2.3, and the energy conversion efficiency η and the hydrogen state sohs in the hydrogen storage tank are obtained, which is convenient for the fuzzy mapping in the next step S2.4.

[0088] S2.4: If Figure 2 As shown, the input current value i of the electrolyzer is collected in the hydrogen energy storage system ele and the fuel cell current value i fc , add the two together to get the current working state of the hydrogen energy system i h ,i h Negative, i.e., hydrogen production state or i h The hydrogen energy system working state is i h The hydrogen state sohs in the hydrogen storage tank is used as the first layer fuzzy mapping input variable to obtain a new mapping sohs that considers the safety of the hydrogen storage tank * ,like Figure 4 As shown. i is 1 or 2, indicating that the current working state of the hydrogen energy system is that the electrolyzer or fuel cell is working. j is 1, 2, or 3, indicating that sohs is divided into three different ranges: low (0-20%), medium (20%-80%), and high (80%-100%). n is the index of the six fuzzy rules. First, the working state of the hydrogen energy system i is h and hydrogen state sohs as two inputs to obtain the membership value through the divided range and membership function Then, the output membership value is obtained according to the fuzzy rules Finally, defuzzification and normalization are performed to obtain the new mapping sohs * .

[0089]

[0090] Among them, f sohs,fuzzy represents the fuzzy mapping of the first layer of the hydrogen energy system, X sohs represents the input set, (i h , sohs) is the specific value; Y sohsF Represents the membership set corresponding to the input, Working status i h and the specific membership value corresponding to the hydrogen state sohs; Represents the membership set corresponding to the output, is the specific membership value; represents the new mapping set obtained by defuzzification and normalization, sohs * is a specific value; Represents the maximum value corresponding to the normalization of the output new mapping value. Figure 4 According to the membership function and fuzzy rules, Figure 4 It can be seen that the relationship between the input and output of the first layer of fuzzy mapping of the designed hydrogen energy system.

[0091] S3: According to the change of transient electrolytic cell energy conversion efficiency and electrolytic cell current, the electrolytic cell working area at the transient moment is obtained. Considering the electrolytic cell energy conversion efficiency, a new mapping sohs is obtained through a double-layer fuzzy mapping mechanism. ** .

[0092] S3.1: Based on the working state of the electrolytic cell, the current value i of the electrolytic cell is collected through the sensor ele The energy conversion efficiency η of the electrolytic cell is calculated using formula (4).

[0093] S3.2: If Figure 5 As shown, according to the electrolytic cell current value i ele The energy conversion efficiency η divides the working state of the electrolytic cell into four regions when the transient power fluctuates: Region 1, the electrolytic cell current value i ele As the current of the electrolytic cell increases, the energy conversion efficiency η also increases; in region 2, the electrolytic cell current increases, but the energy conversion efficiency η decreases; in region 3, the electrolytic cell current decreases, and the energy conversion efficiency η decreases accordingly; in region 4, the electrolytic cell current decreases, but the energy conversion efficiency increases. That is, the partition function is:

[0094]

[0095] Among them, i ele (t) and η(t) represent the electrolytic cell current value and energy conversion efficiency at time t, respectively.

[0096] S3.3: New mapping sohs to consider the safety of hydrogen storage tanks when the electrolyser is in operation * The transient working state Area of ​​the electrolyzer is used as the input of the fuzzy mapping to obtain a double-layer mapping sohs that takes into account both the safety of the hydrogen storage tank and the energy conversion efficiency of the electrolyzer. ** First determine the working area Area and map the first layer sohs * As input, the membership value is obtained through the membership function Then, the output membership value is obtained according to the fuzzy rules Finally, defuzzification and normalization are performed to obtain the new mapping sohs ** ,like Figure 6 shown.

[0097]

[0098] in, Represents the fuzzy mapping of the second layer of the hydrogen energy system, For the input set, sohs * is a specific value; Y sohs*F Represents the membership set corresponding to the output, is the specific membership value, Represents the new mapping sohs of the input * ; represents the new mapping set obtained by defuzzification and normalization, sohs ** is a specific value; Represents the maximum value corresponding to the normalization of the output new mapping value. Compared with the first layer fuzzy mapping, the second layer fuzzy mapping does not need to fuzzify the specific measurement value, and can directly use the mapping value sohs obtained in the first layer * as input. Figure 6 According to the membership function and fuzzy rules, Figure 6 It can be seen that the relationship between the input and output of the second-layer fuzzy mapping of the designed hydrogen energy system.

[0099] S4: Using the new mapping soc * and the new mapping sohs ** As an adaptive adjustment of the droop coefficient, the reference voltage is obtained through droop control, thereby achieving power distribution in different situations.

[0100] S4.1: The voltage reference values ​​of the battery energy storage system and the hydrogen energy storage system are obtained by droop control through adaptive adjustment of the droop coefficient:

[0101]

[0102] Where V nom is the rated voltage, Vb,ref and V h,ref are the voltage reference values ​​of the battery energy storage system and the hydrogen energy storage system, R 1 , R 2 is the time-varying droop coefficient, i bdc 、i hdc They are the current values ​​output by the battery energy storage and hydrogen energy storage through the converter. Usually, when the line impedance is ignored, the ratio of the current values ​​output by the two converters is inversely proportional to the time-varying droop coefficient. charge means that the battery is in the charging state, discharge means that the battery is in the discharging state, fc means that the fuel cell is working, and ele means that the electrolyzer is working.

[0103] In this example, the rated voltage V nom Set to 24V.

[0104] S4.2: The voltage reference values ​​V of the voltage loops of the battery energy storage system and the hydrogen energy storage system are obtained through adaptive droop control. b,ref 、V h,ref The voltage loop and current loop are used to realize the power distribution of batteries, electrolyzers, and fuel cells under different conditions, and the supercapacitors compensate for the high-frequency power when the power fluctuates, such as Fig. 9 As shown. The simulation experiment was carried out by Matlab / simulink simulation software according to the established model and the designed control algorithm. Figure 7 and Figure 8 ,pass Figure 7 and Figure 8 The simulation results show that the designed control algorithm can reasonably distribute the power of the battery energy storage system and the hydrogen energy storage system according to the system status, and can allocate the power of the battery energy storage system and the hydrogen energy storage system according to the system power fluctuation. Figure 5 Determine the current working status of the electrolytic cell.

[0105] At this point, the power distribution control method of the electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping has been completed for the power distribution of the microgrid. It can achieve power distribution while extending the battery life, ensuring the safety of the hydrogen storage tank in the hydrogen energy storage system, and making the energy conversion efficiency of the electrolyzer work in a more flexible area.

[0106] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A power distribution control method for an electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping, characterized in that: The steps are as follows: S1: Establish an electric-hydrogen coupled microgrid model, collect the battery current in the battery energy storage system, and obtain a new mapping soc considering battery life through a single-layer fuzzy mapping * ; S2: Considering the safety of hydrogen storage tanks, the hydrogen energy storage system is simulated, and the hydrogen state sohs in the hydrogen storage tank is used to obtain a new mapping sohs through a single-layer fuzzy mapping mechanism. * ; S3: According to the transient electrolytic cell energy conversion efficiency and the change of electrolytic cell current, the electrolytic cell working area at the transient moment is determined. Considering the electrolytic cell energy conversion efficiency, a new mapping sohs is obtained through a double-layer fuzzy mapping mechanism. ** ; S4: Using the new mapping soc * and the new mapping sohs ** As the droop coefficient of adaptive regulation, the reference voltage is obtained through droop control, thereby realizing power distribution in different situations.

2. The power distribution control method of the electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping according to claim 1 is characterized in that: The new mapping soc that takes into account the battery life is obtained by single-layer fuzzy mapping * The method is as follows: the electric-hydrogen coupled microgrid model includes photovoltaic panels, a battery energy storage system and a hydrogen energy storage system, and the battery energy storage system includes batteries and supercapacitors SC b , hydrogen energy storage system includes fuel cell, supercapacitor SC h and electrolyzers; The battery current value i is calculated by using the ampere-hour integration method. b Integrate to get the original soc of the battery; The single-layer fuzzy mapping transforms the battery current value i b The original soc of the battery is used as input to obtain the membership value u through the divided range and membership function ib,i (x soc (1,)),u soc,j (x soc (,1)), and then the output membership value is obtained according to the fuzzy rule Membership value for the output Defuzzification and normalization are performed to obtain a new mapping soc * ;in, Represents the membership set corresponding to the output.

3. The power distribution control method of the electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping according to claim 2 is characterized in that: The new mapping soc * The calculation method is: input set (i b ,soc) obtains the membership set corresponding to the input through the fuzzy mapping of the battery, in, are the battery current values ​​i b And the specific membership value corresponding to the original soc of the battery, x soc (1,) and x soc (,1) respectively represent the input battery current value i b and the original soc of the battery; the membership value of the output is obtained according to the fuzzy rule Representation Defuzzification and normalization give a new mapping in, Represents the normalization of the output new mapping value i=1,2;j=1,2,3;n=1,2···6 The maximum value should be represents a new mapping set obtained by defuzzification and normalization; i takes 1 or 2 to represent the charge and discharge state, j takes 1, 2 or 3 to represent dividing the original soc of the battery into three different ranges: low, medium and high, and n is the index of the six fuzzy rules.

4. The power distribution control method of the electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping according to any one of claims 1 to 3, characterized in that: The new mapping sohs is obtained by the single-layer fuzzy mapping mechanism * The method is: collect the electrolytic cell input current value i ele and the fuel cell current value i fc , add the two together to get the current working state of the hydrogen energy system i h ,i h Negative, i.e., hydrogen production state or i h The hydrogen energy system working state is i h The hydrogen state sohs in the hydrogen storage tank is used as the first layer fuzzy mapping input variable to obtain a new mapping sohs that considers the safety of the hydrogen storage tank * :The hydrogen energy system working state i h and hydrogen state sohs as two inputs to obtain the membership value through the divided range and membership function Then, the output membership value is obtained according to the fuzzy rules Finally, defuzzification and normalization are performed to obtain the new mapping sohs * ;in, Represents the membership set corresponding to the output.

5. The power distribution control method of the electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping according to claim 4 is characterized in that: The new map sohs * The calculation method is: Among them, i is 1 or 2, indicating the current working state of the hydrogen energy system, i.e., the electrolyzer or fuel cell is working; j is 1, 2, or 3, indicating that the hydrogen state sohs is divided into three different ranges; n is the index of the six fuzzy rules; f sohs,fuzzy represents the fuzzy mapping of the first layer of the hydrogen energy system, X sohs represents the input set, (i h ,sohs) is the specific value of the input set; Y sohsF Represents the membership set corresponding to the input, They are working status i h and the specific membership value corresponding to the hydrogen state sohs, x sohs (1,) and x sohs (,1) respectively represent the input working state i h and hydrogen state sohs; Represents the membership set corresponding to the output, To output specific membership values; represents the new set of mappings obtained by defuzzification and normalization, Represents the maximum value corresponding to the normalization of the output new mapping value.

6. The power distribution control method of the electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping according to claim 5 is characterized in that: In the hydrogen energy storage system, the mathematical model of the electrolyzer is: Among them, V ele is the voltage at the cell terminals, V rev 、V ohm 、V con are respectively the reversible voltage, the resistance overvoltage caused by ohmic polarization and the concentration polarization overvoltage, N is the number of electrolytic cells, V o output voltage for the entire electrolyzer unit; In the hydrogen energy storage system, the mathematical model of the fuel cell is: Among them, V fc is the fuel cell operating voltage, i fc is the fuel cell operating current, A is the cross-sectional area of ​​the proton exchange membrane, n fc is the number of fuel cell units, P H2 and P O2 are the inlet pressures of hydrogen and oxygen, respectively; l is the equivalent voltage at the minimum calorific value of hydrogen; σ, δ1, δ2, δ3, δ4, m1, m2, R t All are empirical coefficients; In the hydrogen energy storage system, the mathematical model of the hydrogen storage tank is: Among them, T s is the hydrogen storage tank temperature, V s is the capacity of the hydrogen storage tank, R s is the gas constant, n eleH2 is the rate of hydrogen production, n fcH2 is the rate at which the fuel cell consumes hydrogen, sohs is the state of hydrogen in the hydrogen storage tank, P s is the real-time pressure of the hydrogen storage tank, P SMAX It is the maximum pressure of the hydrogen storage tank.

7. The power distribution control method of the electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping according to claim 6 is characterized in that: The reversible voltage, resistance overvoltage caused by ohmic polarization and concentration polarization overvoltage Where T is the operating temperature, i ele is the working current of the electrolytic cell, A ele is the cathode plate area, r1, r2, s1, s2, s3, t1, t2, t3, α are all adjustment coefficients; The rate at which the electrolyzer produces hydrogen The rate at which the fuel cell consumes hydrogen Where z is the change in the chemical valence of the reactants.

8. The power distribution control method of the electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping according to claim 5 or 6 is characterized in that: New mapping sohs to consider hydrogen tank safety when electrolyser is in operation * The working area of ​​the electrolytic cell at the instantaneous state is used as the input of the fuzzy mapping, and the working area is determined and the new mapping sohs * As input, the membership value is obtained through the membership function Then, the output membership value is obtained according to the fuzzy rules Finally, defuzzification and normalization are performed to obtain the new mapping sohs ** , the calculation method is: in, Fuzzy mapping representing the second layer of the hydrogen energy system, sohs * For the input set The specific value of The membership set Y corresponding to the output sohs*F The specific membership value of Represents the new mapping sohs of the input * ;sohs ** Get a new set of mappings for defuzzification and normalization New mapping of ; Represents the maximum value corresponding to the normalization of the output new mapping value.

9. The power distribution control method of the electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping according to claim 8 is characterized in that: The method for determining the working area of ​​the electrolytic cell at the transient moment is: according to the working state of the electrolytic cell, the current value i of the electrolytic cell is collected by the sensor. ele And calculate the energy conversion efficiency η from electrical energy to chemical energy in the electrolytic cell; according to the electrolytic cell current value i ele The energy conversion efficiency η divides the working state of the electrolytic cell into four regions when the transient power fluctuates: Region 1, the electrolytic cell current value i ele As it increases, the energy conversion efficiency η also increases; Region 2, electrolytic cell value i ele As the current increases, the energy conversion efficiency η decreases; in region 3, the electrolytic cell current value i ele decreases, the energy conversion efficiency η decreases accordingly; in area 4, the electrolytic cell current value i ele decreases, and the energy conversion efficiency η increases instead.

10. The power distribution control method of the electric-hydrogen coupled energy storage system based on double-layer fuzzy mapping according to claim 9 is characterized in that: The energy conversion efficiency η is: Where K is the electrochemical reaction coefficient, R h is the chemical calorific value of hydrogen, β is the temperature adjustment coefficient, F is the Faraday constant, λ is the heat dissipation coefficient, and S is the entropy value at the working temperature T; The droop control is as follows: the voltage reference values ​​of the battery energy storage system and the hydrogen energy storage system are respectively: V b,ref =V nom -R1·i bdc V h,ref =V nom -R2·i hdc Where V nom is the rated voltage, V b,ref and V h,ref are the voltage reference values ​​of the battery energy storage system and the hydrogen energy storage system, R1 and R2 are the time-varying droop coefficients, and i bdc 、i hdc They are the current values ​​output by the battery energy storage and hydrogen energy storage through the converter respectively; The time-varying droop coefficients are Among them, charge means that the battery is in a charging state, discharge means that the battery is in a discharging state, fc means that the fuel cell is working, and ele means that the electrolyzer is working.

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