A control method for variable-temperature operation of an alkaline electrolyzer to improve the efficiency of a hydrogen production system

Abstract

The present invention relates to electrolytic hydrogen production control technology, aiming to provide a variable-temperature operation control method for an alkaline electrolyzer to improve the efficiency of a hydrogen production system. The method includes: obtaining the operation data of the alkaline electrolyzer; optimizing the hydrogen production rate of the alkaline electrolyzer based on considering its electrothermal characteristics to obtain the operating temperature at which the hydrogen production amount of the electrolyzer is maximized; adjusting the power of the auxiliary temperature adjustment device and the alkaline electrolyzer according to set conditions, and controlling the operating temperature of the electrolyzer based on the calculation results of the hydrogen production rate optimization model, so as to improve the efficiency of the hydrogen production system by maximizing the hydrogen production amount of the electrolyzer. The present invention innovatively proposes to consider the complex electrothermal characteristics of the alkaline electrolyzer in operation optimization. The model used is close to the actual working process of the electrolyzer, improving the practicality of the model optimization results; when the total power of the equipment is certain, it can maximize the hydrogen energy output of the electrolyzer, improve the resource utilization rate, and has the significance of low-carbon environmental protection.

Description

Technical Field

[0001] The present invention relates to the control technology of electrolytic hydrogen production, and particularly to a variable-temperature operation control method for an alkaline electrolyzer to improve the efficiency of a hydrogen production system. Background Art

[0002] As one of the most environmentally friendly hydrogen production methods, water electrolysis for hydrogen production has become an important way to alleviate resource and environmental crises. Water electrolysis for hydrogen production technology can be divided into alkaline electrolysis for hydrogen production, proton exchange membrane electrolysis for hydrogen production, and high-temperature solid oxide electrolysis for hydrogen production. Among them, alkaline electrolysis for hydrogen production has the highest degree of commercialization and the widest application.

[0003] At present, the research on the mechanism of water electrolysis in alkaline electrolyzers focuses on static modeling using theories such as electrochemistry and thermotics, and analyzing the characteristics of alkaline electrolyzers from the perspectives of thermal energy, electrical energy, and chemical energy of substances. There are complex non-linear relationships among variables such as the operating power, efficiency, temperature, voltage, and current of alkaline electrolyzers. For example, part of the power input to the alkaline electrolyzer is used for electrolysis, and the other part is converted into heat energy due to factors such as the overvoltage of the alkaline electrolyzer. When the self-generated heat of the alkaline electrolyzer is greater than the heat dissipated to the environment, the temperature of the alkaline electrolyzer rises. Conversely, the temperature of the alkaline electrolyzer drops. Therefore, the characteristics of alkaline electrolyzers will inevitably have a substantial impact on their operation control effects.

[0004] However, there are few research results on optimizing the operation process based on the characteristics of alkaline electrolyzers at present, and it is necessary to propose corresponding solutions. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies in the prior art and provide a variable-temperature operation control method for an alkaline electrolyzer to improve the efficiency of a hydrogen production system.

[0006] To solve the technical problem, the solution of the present invention is as follows:

[0007] Provide a variable-temperature operation control method for an alkaline electrolyzer to improve the efficiency of a hydrogen production system, including the following steps:

[0008] (1) Obtain the operation data of the alkaline electrolyzer through sampling;

[0009] (2) Optimize the hydrogen production rate of the alkaline electrolyzer based on considering its electrothermal characteristics to obtain the operating temperature that maximizes the hydrogen production amount of the electrolyzer:

[0010] First, analyze and model the electrothermal characteristics of the alkaline electrolyzer, including the relationship between the hydrogen production rate and the electrolysis power and temperature of the electrolyzer, as well as the dynamic equation of the temperature change of the electrolyzer. Secondly, with the goal of maximizing the hydrogen production rate, establish an optimization model of the hydrogen production rate considering the electrothermal characteristics of the alkaline electrolyzer. Then, use the least squares method to fit the complex non-linear constraints of the relationship between the hydrogen production rate and power and temperature, and transform them into polynomial constraints. Finally, solve the optimization model of the hydrogen production rate to obtain the operating temperature that maximizes the hydrogen production of the electrolyzer when the total power of the auxiliary temperature regulating device and the alkaline electrolyzer meets the set conditions.

[0011] (3) Adjust the power of the auxiliary temperature regulating device and the alkaline electrolyzer according to the set conditions, control the operating temperature of the electrolyzer based on the calculation results of the hydrogen production rate optimization model, and improve the efficiency of the hydrogen production system by maximizing the hydrogen production of the electrolyzer.

[0012] Compared with the prior art, the beneficial effects of the present invention are:

[0013] 1. Since the self-heat generation of the alkaline electrolyzer is generally not equal to the heat dissipated to the environment, the assistance of an auxiliary temperature regulating device is required to control the temperature of the electrolyzer. Obviously, when optimizing the operation of the electrolyzer, considering the energy consumed by the auxiliary temperature regulating device can make the optimization method more accurate and practical.

[0014] The present invention innovatively proposes to consider the complex electrothermal characteristics of the alkaline electrolyzer in the operation optimization. The model used is close to the actual working process of the electrolyzer, improving the practicality of the model optimization results. Since the power consumption of the auxiliary temperature regulating device of the alkaline electrolyzer is fully considered, when the total power including the power of the auxiliary temperature regulating device and the electrolysis power of the electrolyzer is certain, the hydrogen energy output of the electrolyzer can be maximized, improving the resource utilization rate.

[0015] 2. The present invention fits the complex non-linear constraints in the model, transforming the constraints into polynomial constraints that are easier to solve, improving the model solving speed and reducing the computing power required for model solving.

[0016] 3. The present invention solves the optimal operating temperature of the alkaline electrolyzer that maximizes the hydrogen production rate when the total power input including the power of the auxiliary temperature regulating device and the electrolysis power of the electrolyzer is certain, that is, reducing the power consumption for the same hydrogen energy output, which has the significance of low carbon and environmental protection.

[0017] 4. By analyzing and modeling the variable relationship, that is, the electrothermal characteristics of the electrolyzer, it can guide the optimal operation of the alkaline electrolyzer, thereby achieving higher energy conversion efficiency or economic benefits. Description of the Drawings

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0019] Figure 1 This is the implementation flowchart of a hydrogen production rate optimization method considering the electrothermal characteristics of an alkaline electrolyzer proposed by the present invention.

[0020] Figure 2 This is the comparison chart of the fitting results of Constraint 1 and the original data described in the example of the present invention.

[0021] Figure 3 This is for different inputs P at a room temperature of 20°C described in the example of the present invention. sys The obtained optimal temperature results. Detailed implementation manners

[0022] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will further describe the embodiments of the present invention in detail with reference to the accompanying drawings.

[0023] The first part: The implementation process of the present invention

[0024] The variable-temperature operation control method for an alkaline electrolyzer to improve the efficiency of a hydrogen production system according to the present invention includes the following three steps.

[0025] 1. Obtain the operation data of the alkaline electrolyzer through sampling.

[0026] The operation data of the alkaline electrolyzer can be obtained by using general monitoring instruments, including at least: the heating power of the auxiliary temperature regulation device, the electrolysis power of the alkaline electrolyzer, the hydrogen production amount of the alkaline electrolyzer, as well as the temperature, current, voltage, and sampling time node during the operation of the alkaline electrolyzer. Based on the sampled data, subsequent calculations can be further performed.

[0027] There are various specific implementation solutions for the auxiliary temperature regulation device. For example: electric heaters built into the electrolyzer for heating the electrolyte, external heating devices for circulating and heating the electrolyte, or heating jackets for maintaining the temperature of the electrolyzer, and so on. In specific actual application scenarios, it can be configured according to the actual situation of the electrolyzer. Or, to more precisely control the temperature, a cooling device can be further configured to assist in regulating the temperature.

[0028] 2. Optimize the hydrogen production rate of the alkaline electrolyzer based on considering the electrothermal characteristics, and obtain the operating temperature that maximizes the hydrogen production amount of the electrolyzer.

[0029] First, analyze and model the electrothermal characteristics of the alkaline electrolyzer, including the relationship between the hydrogen production rate and the electrolysis power and temperature of the electrolyzer, as well as the dynamic equation of the temperature change of the electrolyzer. Secondly, with the goal of maximizing the hydrogen production rate, establish an optimization model of the hydrogen production rate considering the electrothermal characteristics of the alkaline electrolyzer. Then, use the least squares method to fit the complex non-linear constraints of the relationship between the hydrogen production rate and power and temperature, and transform them into polynomial constraints. Finally, solve the optimization model of the hydrogen production rate to obtain the operating temperature that maximizes the hydrogen production of the electrolyzer when the total power of the auxiliary temperature regulation device and the alkaline electrolyzer meets the set conditions. The above content is specifically described as follows:

[0030] (1) Model the relationship between the hydrogen production rate and the electrolysis power and temperature of the electrolyzer:

[0031] (A1) Calculate the hydrogen production rate of the electrolyzer according to the following formula:

[0032]

[0033] In this formula, m(t) is the electrolytic hydrogen production rate at time t, with the unit of g / s; η f is the Faraday efficiency, with a value of 1; M H2 is the molar mass of hydrogen, with a value of 2; F is the Faraday constant, with a value of 96485 C / mol; n c is the number of electrolysis cells, which is related to the structure of the electrolyzer; I(t) is the electrolysis current at time t;

[0034] (A2) Calculate the electrolysis power of the electrolyzer according to the following formula:

[0035] First, the relationship between the voltage and current of the electrolyzer satisfies the following empirical formula:

[0036]

[0037] In this formula, U(t) is the voltage of the electrolyzer at time t; U rev is the reversible voltage of the electrolysis cell of the electrolyzer, with a value of 1.23 V; r 1 , r 2 , s 1 , t 1 , t 2 , t 3 are parameters related to the characteristics of the electrolyzer, obtained by fitting through measuring voltage-current groups; T(t) is the temperature of the electrolyzer at time t; I(t) is the electrolysis current at time t; A is the effective electrolysis area of the electrolyzer;

[0038] Then, calculate the electrolysis power of the electrolyzer according to the following formula:

[0039]

[0040] In this formula, P(t) is the electrolysis power of the electrolyzer at time t;

[0041] (A3) Combining the above hydrogen production rate and electrolysis power calculation formulas, the relationship between the hydrogen production rate, the electrolysis power of the electrolyzer, and the temperature is as follows:

[0042]

[0043] In this formula, m(t) is the electrolytic hydrogen production rate at time t; P(t) is the electrolysis power of the electrolyzer at time t; T(t) is the temperature of the electrolyzer at time t.

[0044] (2) Abstractly model the dynamic equation of the temperature change of the electrolyzer, as shown in the following formula:

[0045]

[0046] In this formula, C Elz is the heat capacity of the electrolyzer; T(t), P(t), m(t) are the temperature, operating power, and hydrogen production rate of the electrolyzer at time t; M H2 is the molar mass of hydrogen, with a value of 2; LHV is the lower heating value of hydrogen, taking the common value of 242 kJ / mol; P Eb (t) is the power consumption of the auxiliary heating equipment; η Eb is the heating efficiency of the auxiliary heating equipment; P Cs (t) is the power consumption of the cooling equipment, η Cs is the energy efficiency ratio of the cooling equipment; T a (t) is the ambient temperature at time t; R Elz is the thermal resistance of the electrolyzer.

[0047] (3) With the goal of maximizing the hydrogen production rate, establish a hydrogen production rate optimization model considering the electrothermal characteristics of the alkaline electrolyzer, specifically including the following steps:

[0048] (B1) According to the dynamic equation of the temperature change of the electrolyzer, when the temperature of the electrolyzer is stable, it is necessary to satisfy:

[0049]

[0050] In this formula, T(t), P(t), m(t) are the temperature, operating power, and hydrogen production rate of the electrolyzer at time t; LHV is the lower heating value of hydrogen, taking the common value of 242 kJ / mol; P Eb (t) is the power consumption of the auxiliary heating equipment; η Eb is the heating efficiency of the auxiliary heating equipment; P Cs (t) is the power consumption of the cooling equipment, η Cs is the energy efficiency ratio of the cooling equipment; Ta (t) is the ambient temperature at time t; R Elz is the thermal resistance of the electrolytic cell;

[0051] Since the simultaneous operation of the auxiliary heating device and the auxiliary cooling device will increase the additional energy consumption of the system, therefore, the power of the two satisfies:

[0052] P Eb (t)·P Cs (t) = 0

[0053] (B2) If the self-heating power of the electrolytic cell is greater than the heat dissipation power to the environment, that is:

[0054]

[0055] Then the total power including the power of the auxiliary temperature regulation device and the electrolysis power of the electrolytic cell is expressed as:

[0056] P Sys = P(t) + P Cs (t)

[0057] where P Sys is the total power including the power of the auxiliary temperature regulation device and the electrolysis power of the electrolytic cell;

[0058] (B3) If the self-heating power of the electrolytic cell is less than the heat dissipation power to the environment, that is:

[0059]

[0060] Then the total power including the power of the auxiliary temperature regulation device and the electrolysis power of the electrolytic cell is expressed as:

[0061] P Sys = P(t) + P Eb (t)

[0062] (B4) If the self-heating power of the electrolytic cell is equal to the heat dissipation power to the environment, that is:

[0063]

[0064] Then the total power including the power of the auxiliary temperature regulation device and the electrolysis power of the electrolytic cell is expressed as:

[0065] P Sys = P(t)

[0066] The above three cases described in (B2)-(B4) are combined into the following system of equations:

[0067]

[0068] (B5) For the given total power P Sys, an optimization model for hydrogen production rate considering the electrothermal characteristics of the alkaline electrolyzer is established;

[0069] The optimization model for hydrogen production rate takes the total power including the power of the auxiliary temperature regulation device and the electrolysis power of the electrolyzer as the main input quantity, and the ambient temperature T a (t) as the secondary input quantity; the goal of this model is to maximize the hydrogen production rate of the electrolyzer, and the solution result is the operating temperature T(t); the objective function and constraints of this model are specifically described as follows:

[0070] That is, the objective function is the hydrogen production rate m(t) of the electrolyzer: Max m(t)

[0071] Among the constraints of this model, in addition to the upper and lower limit constraints on the power of the auxiliary temperature regulation device and the electrolyzer, and the upper and lower limit constraints on the operating temperature of the electrolyzer, the following two constraints are also included:

[0072] Constraint 1: The relationship between hydrogen production rate and electrolysis power and temperature of the electrolyzer:

[0073]

[0074] Constraint 2: Based on the dynamic equation of the temperature change of the electrolyzer, to maintain the temperature stability of the electrolyzer, it should be satisfied that:

[0075]

[0076] P Eb (t)·P Cs (t) = 0

[0077] P Eb (t) + P Cs (t) + P(t) = P Sys .

[0078] (4) Using the least squares method to fit the complex nonlinear constraints of the relationship between hydrogen production rate and power and temperature, and converting them into polynomial constraints, specifically including:

[0079] (C1) Let i = 0, j = 0, P i,j (t) = 25% P Rated , T i,j (t) = T min ;

[0080] (C2) Let i = i + 1, P i,j (t) = P i-1,j (t) + Δ * P Rated , solve m i,j (t) according to Constraint 1, and record the data: [P i,j (t), T i,j (t), mi,j (t);

[0081] (C3) Determine whether P i,j (t) > (1 - Δ) * P Rated , if not, then jump to step C2, if so, then proceed to step C4;

[0082] (C4) Let i = 0, j = j + 1, T i,j (t) = T i,j-1 (t) + Δ * (T max -T min ), P i,j (t) = 25% P Rated , jump to step C2;

[0083] (C5) Determine whether T i,j (t) > T max -Δ * (T max -T min ), if not, then jump to step C4, if so, then proceed to step C6;

[0084] (C6) According to the recorded data set: [P i,j (t), T i,j (t), m i,j (t)], taking m(t) as the dependent variable, P(t) and T(t) as the independent variables, using the least squares method to fit the relationship among the three, using a polynomial function for fitting, increasing the degree of the polynomial function from small to large. If the determination coefficient R 2 > 0.95, it is considered that the fitted linear function is very close to the original constraint, and this polynomial function is used to replace the original constraint condition 1 to solve the model; if the degree of the polynomial function reaches 5 and there is still no determination coefficient R 2 > 0.95, then select the polynomial function with the largest determination coefficient R 2 for fitting;

[0085] Among them, i is the subscript for recording power data, and j is the subscript for recording temperature data; P Rated is the rated power of the electrolytic cell; T i,j (t) is the recorded temperature data with subscripts i, j; T max is the upper limit of the normal operating temperature of the electrolytic cell; T min is the lower limit of the normal operating temperature of the electrolytic cell; P i,j (t) is the recorded power data with subscripts i, j; m i,j(t) is the hydrogen production rate data recorded with subscripts i and j; Δ is the proportionality coefficient, with a range of 1% - 10%. The value of Δ is related to the fitting accuracy. The smaller Δ is, the more data the dataset contains and the higher the fitting accuracy; the larger Δ is, the fewer data the dataset contains and the lower the fitting accuracy.

[0086] (5) Use a commercial solver (such as Gurobi) to solve the hydrogen production rate optimization model to obtain the operating temperature that maximizes the hydrogen production of the electrolyzer when the total power of the auxiliary temperature regulating device and the alkaline solution electrolyzer meets the set conditions.

[0087] 3. Adjust the power of the auxiliary temperature regulating device and the alkaline solution electrolyzer according to the set conditions, control the operating temperature of the electrolyzer based on the calculation results of the hydrogen production rate optimization model, and improve the efficiency of the hydrogen production system by maximizing the hydrogen production of the electrolyzer.

[0088] The second part: A specific application example

[0089] The following provides a hydrogen production rate optimization method considering the electrothermal characteristics of an alkaline solution electrolyzer, which optimizes the operation of a 20kW alkaline solution electrolyzer. The auxiliary temperature regulating device of this electrolyzer includes: a cooling device and an external heating source. The upper limit of the operating temperature of the electrolyzer is 90°C, and the lower limit is 40°C.

[0090] The fitting results of the voltage-current equation of the electrolyzer in this example are as follows:

[0091]

[0092] Substitute the parameters in the above fitting results into the relationship equation between the electrolytic hydrogen production rate, electrolytic power, and temperature:

[0093] U rev = 1.23, r 1 = 8.957·10 -5 , r 2 = -3.34·10 -7

[0094] s 1 = 0.08, t 1 = 0.01, t 2 = -6.6·10 -3 , t 3 = 105

[0095] The relationship between the electrolytic hydrogen production rate, electrolytic power, and temperature can be expressed as:

[0096]

[0097] Substitute the physical parameter values into the relationship equation between the electrolytic hydrogen production rate, electrolytic power, and temperature:

[0098] n c = 42, η f = 1, M H2 = 2

[0099] F = 96485 C / mol, A = 0.27 m 2

[0100] Then the relationship equation between the electrolytic hydrogen production rate and the electrolytic power and temperature can be expressed as:

[0101]

[0102] Establish the following optimization model to solve the maximum hydrogen production rate of the electrolyzer and the corresponding operating temperature:

[0103] The objective of this model is to maximize the hydrogen production rate of the electrolyzer, and the objective function is the hydrogen production rate m(t) of the electrolyzer:

[0104] Max m(t)

[0105] The constraint conditions of this model mainly include two, in addition to the upper and lower limit power constraints on auxiliary equipment and the electrolyzer:

[0106] Constraint condition 1: The relationship between the hydrogen production rate and the electrolytic power and the electrolyzer temperature as described in the invention content:

[0107]

[0108] Constraint condition 2: The dynamic equation of the electrolyzer temperature change as described in the invention content, substituting:

[0109] LHV = 242 kJ / mol, R Elz = 0.0167 °C / W

[0110] η Eb = 0.95, η Cs = 3

[0111] Get the expression of constraint condition 2 in this example:

[0112]

[0113] P Eb (t)·P Cs (t) = 0

[0114] P Eb (t) + P Cs (t) + P(t) = P Sys

[0115] Next, first use the fitting method of the present invention to fit Constraint 1. Take Δ = 1, and it is found that fitting with a quadratic polynomial function is the most appropriate. The fitting result is:

[0116] m(t) = 3.4076·10 -4 + 5.67·10 -6 P(t)+7.2·10 -5 T(t)-7.2638·10 -11 P(t) 2 + 8.86·10 -9 T(t)P(t)-5.63·10 -7 T(t) 2

[0117] The fitting function surface and the original data graph are as Figure 2 shown. The fitting determination coefficient R 2 is 0.9999, which is very close to 1, indicating that the fitting function is very similar to the original function, and the original constraint condition can be replaced by the fitted constraint condition.

[0118] Therefore, the original optimization model is transformed into:

[0119] The objective of this model is to maximize the hydrogen production rate of the electrolytic cell, and the objective function is the hydrogen production rate m(t) of the electrolytic cell:

[0120] Max m(t)

[0121] The constraint conditions of this model mainly include two in addition to the upper and lower limit power constraints on auxiliary equipment and the electrolytic cell:

[0122] Constraint Condition 1:

[0123] m(t) = 3.4076·10 -4 + 5.67·10 -6 P(t)+7.2·10 -5 T(t)-7.2638·10 -11 P(t) 2 + 8.86·10 -9 T(t)P(t)-5.63·10 -7 T(t) 2

[0124] Constraint Condition 2:

[0125]

[0126] P Eb (t)·P Cs (t)=0

[0127] P Eb(t) + P Cs (t) + P(t) = P Sys

[0128] Given room temperature T a at time (t), for different P sys By solving the above optimization model, the operating temperature that maximizes the hydrogen production rate of the electrolyzer can be obtained.

[0129] Figure 3 Shows the optimal operating temperature results of the electrolyzer obtained by solving the above model when the P changes at a room temperature of 20 °C in this example. sys The results of the optimal operating temperature of the electrolyzer obtained by solving the above model when P changes.

[0130] In summary, this embodiment adopts the proposed hydrogen production rate optimization method considering the electro-thermal characteristics of the alkaline electrolyzer. For a 20 kW alkaline electrolyzer, when the total power including the power of the auxiliary temperature regulation device and the electrolysis power of the electrolyzer is constant, through fitting, modeling, and model solving, the operating temperature that maximizes the hydrogen production of the electrolyzer is obtained. This optimal temperature can provide a reference for the optimal operation of the electrolyzer in practice and improve the resource utilization rate.

Claims

1. A method for controlling the variable temperature operation of an alkaline solution electrolyzer to improve the efficiency of a hydrogen production system, characterized in that: The following steps are involved: (1) Obtaining the operating data of the alkali solution electrolytic cell by sampling; (2) The hydrogen production rate of the alkaline solution electrolyzer is optimized based on the electrothermal characteristics to obtain the operating temperature that maximizes the hydrogen production of the electrolyzer: Firstly, the electrothermal characteristics of the alkaline solution electrolyzer are analyzed and modeled, including modeling the relationship between the hydrogen production rate and the electrolysis power and temperature of the electrolyzer, as well as the dynamic equation of the temperature change of the electrolyzer; secondly, with the goal of maximizing the hydrogen production rate, a hydrogen production rate optimization model considering the electrothermal characteristics of the alkaline solution electrolyzer is established; then, the least squares method is used to fit the complex nonlinear constraints of the relationship between the hydrogen production rate and the power and temperature, and converted into polynomial constraints; finally, the hydrogen production rate optimization model is solved to obtain the operating temperature that maximizes the hydrogen production of the electrolyzer when the total power of the auxiliary temperature regulating device and the alkaline solution electrolyzer meets the set conditions; Specifically, the relationship between the hydrogen production rate and the electrolysis power and temperature of the electrolyzer is modeled according to the following steps: (A1) Calculate the hydrogen production rate of the electrolyzer according to the following formula: In this formula, m(t) is the electrolytic hydrogen production rate at time t, in g / s; η f is the Faraday efficiency, which takes a value of 1; is the molar mass of hydrogen, which is 2; F is the Faraday constant, which is 96485C / mol; n c is the number of electrolytic chambers, which is related to the structure of the electrolytic cell; I(t) is the electrolytic current at time t; (A2) Calculate the electrolytic power of the electrolytic cell according to the following formula: First, the relationship between the voltage and current of the electrolytic cell satisfies the following empirical formula: In this formula, U(t) is the voltage of the electrolytic cell at time t; U rev is the reversible voltage of the electrolytic cell chamber, which is 1.23V; r1, r2, s1, t1, t2, t3 are parameters related to the electrolytic cell characteristics, which are obtained by measuring the voltage and current group and fitting; T(t) is the electrolytic cell temperature at time t; I(t) is the electrolytic current at time t; A is the effective electrolytic area of ​​the electrolytic cell; Then, the electrolysis power of the electrolytic cell is calculated according to the following formula: In this formula, P(t) is the electrolysis power of the electrolytic cell at time t; (A3) Combining the above hydrogen production rate and electrolysis power calculation formula, the relationship between the hydrogen production rate and the electrolysis power and temperature of the electrolyzer is as follows: In this formula, m(t) is the electrolysis hydrogen production rate at time t; P(t) is the electrolysis power of the electrolytic cell at time t; T(t) is the electrolytic cell temperature at time t; According to the following steps, the temperature change dynamic equation of the electrolytic cell is abstracted and modeled, as shown in the following formula: In this formula, C Elz is the heat capacity of the electrolyzer; T(t), P(t), m(t) are the temperature, operating power and hydrogen production rate of the electrolyzer at time t; is the molar mass of hydrogen, which is taken as 2; LHV is the lower heating value of hydrogen, which is usually taken as 242 kJ / mol; P Eb (t) is the power consumption of the auxiliary heating equipment; η Eb is the heating efficiency of the auxiliary heating equipment; P Cs (t) is the power consumption of the cooling equipment, η Cs is the energy efficiency ratio of the cooling equipment; T a (t) is the ambient temperature at time t; R Elz is the thermal resistance of the electrolytic cell; (3) The power of the auxiliary temperature control device and the alkaline solution electrolyzer is adjusted according to the set conditions, and the operating temperature of the electrolyzer is controlled based on the calculation results of the hydrogen production rate optimization model, so as to improve the efficiency of the hydrogen production system by maximizing the hydrogen production of the electrolyzer.

2. The method according to claim 1, characterized in that In the step (1), the operating data of the alkaline liquid electrolyzer includes at least: the heating power of the auxiliary temperature regulating device, the electrolysis power of the alkaline liquid electrolyzer, the hydrogen production of the alkaline liquid electrolyzer, and the temperature, current, voltage and sampling time nodes when the alkaline liquid electrolyzer is in operation.

3. The method according to claim 1, characterized in that In the step (2), with the goal of maximizing the hydrogen production rate, a hydrogen production rate optimization model considering the electrothermal characteristics of the alkaline solution electrolyzer is established, which specifically includes the following steps: (B1) According to the dynamic equation of the temperature change of the electrolytic cell, when the temperature of the electrolytic cell is stable, it needs to satisfy: In the formula, T(t), P(t), m(t) are the temperature, operating power and hydrogen production rate of the electrolyzer at time t; LHV is the lower heating value of hydrogen, which is usually taken as 242 kJ / mol; P Eb (t) is the power consumption of the auxiliary heating equipment; η Eb is the heating efficiency of the auxiliary heating equipment; P Cs (t) is the power consumption of the cooling equipment, η Cs is the energy efficiency ratio of the cooling equipment; T a (t) is the ambient temperature at time t; R Elz is the thermal resistance of the electrolytic cell; Since the auxiliary heating device and the auxiliary cooling device running simultaneously will increase the system's additional energy consumption, the power of the two devices must meet the following requirements: P Eb (t)·P Cs (t)=0 (B2) If the heat generation power of the electrolytic cell itself is greater than the heat dissipation power to the environment, that is: The total power including the auxiliary temperature regulating device power and the electrolytic power of the electrolytic cell is expressed as: P Sys =P(t)+P Cs (t) Where P Sys It is the total power including the auxiliary temperature regulating device power and the electrolysis power of the electrolyzer; (B3) If the heat generation power of the electrolytic cell itself is less than the heat dissipation power to the environment, that is: The total power including the auxiliary temperature regulating device power and the electrolytic power of the electrolytic cell is expressed as: P Sys =P(t)+P Eb (t) (B4) If the heat generation power of the electrolytic cell itself is equal to the heat dissipation power to the environment, that is: The total power including the auxiliary temperature regulating device power and the electrolytic power of the electrolytic cell is expressed as: P Sys =P(t) The three situations described in (B2)-(B4) above are combined into the following set of equations: (B5) For a given total power P Sys , establish a hydrogen production rate optimization model considering the electrothermal characteristics of the alkaline solution electrolyzer; The hydrogen production rate optimization model takes the total power including the auxiliary temperature regulating device power and the electrolysis power of the electrolyzer as the main input and the ambient temperature T a (t) is a secondary input; the objective of the model is to maximize the hydrogen production rate of the electrolyzer, and the solution result is the operating temperature T(t); the objective function and constraints of the model are as follows: That is, the objective function is the electrolyzer hydrogen production rate m(t): Max m(t) The constraints of this model include the following two constraints in addition to the upper and lower limits of the power of the auxiliary temperature regulating device and the electrolyzer, and the upper and lower limits of the operating temperature of the electrolyzer: Constraint 1: Relationship between hydrogen production rate and electrolysis power and temperature of electrolyzer: Constraint 2: Based on the dynamic equation of the temperature change of the electrolytic cell, if the temperature of the electrolytic cell is to be kept stable, the following conditions must be met: P Eb (t)·P Cs (t)=0 P Eb (t)+P Cs (t)+P(t)=P Sys 。 4. The method according to claim 3, characterized in that In the step (2), the complex nonlinear constraints of the relationship between the hydrogen production rate, power and temperature are fitted by the least squares method and converted into polynomial constraints, which specifically include: (C1) Let i = 0, j = 0, P i,j (t) = 25%P Rated , T i,j (t) = T min ; (C2) Let i = i + 1, P i,j (t) = P i-1,j (t)+Δ*P Rated , solve m according to constraint 1 i,j (t), record data: [P i,j (t),T i,j (t),m i,j (t)]; (C3) Determine whether P i,j (t)>(1-Δ)*P Rated If not, go to step C2, if yes, go to step C4; (C4) Let i = 0, j = j + 1, T i,j (t) = T i,j-1 (t)+Δ*(T max -T min ), P i,j (t) = 25% P Rated , jump to step C2; (C5) Determine whether T i,j (t)>T max -Δ*(T max -T min ), if not, jump to step C4, if yes, proceed to step C6; (C6) According to the recorded data set: [P i,j (t),T i,j (t),m i,j (t)], taking m(t) as the dependent variable, P(t) and T(t) as the independent variables, using the least squares method to fit the relationship between the three, using a polynomial function for fitting, increasing the degree of the polynomial function from small to large, if the determination coefficient R of the fitting result is 2 >0.95, that is, the fitted linear function is considered to be very close to the original constraint, and the polynomial function replaces the original constraint 1 to solve the model; if the polynomial function reaches 5, there is still no determination coefficient R of the fitting result 2 >0.95, then select the determination coefficient R 2 The largest polynomial function is fitted; Where i is the subscript of the recorded power data, j is the subscript of the recorded temperature data; P Rated is the rated power of the electrolyzer; T i,j (t) is the recorded temperature data with subscript i,j; T max T is the upper limit of normal operating temperature of the electrolyzer; min is the lower limit of the normal operating temperature of the electrolytic cell; P i,j (t) is the power data recorded with the subscript i, j; m i,j (t) is the recorded hydrogen production rate data with subscripts i and j; Δ is the proportional coefficient, ranging from 1% to 10%. The value of Δ is related to the fitting accuracy. The smaller Δ is, the more data the data set contains and the higher the fitting accuracy is; the larger Δ is, the less data the data set contains and the lower the fitting accuracy is.

5. The method according to claim 1, characterized in that In the step (2), a commercial solver is used to solve the hydrogen production rate optimization model to obtain an operating temperature that maximizes the hydrogen production of the electrolyzer when the total power of the auxiliary temperature regulating device and the alkaline solution electrolyzer meets the set conditions.

6. The method according to claim 1, characterized in that The auxiliary temperature regulating device refers to: an electric heater built into the electrolytic cell for heating the electrolyte, an external heating device for circulating and heating the electrolyte, or a heating jacket for maintaining the temperature of the electrolytic cell.

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