Stepped efficient electric green hydrogen production method for new energy consumption

Abstract

The invention discloses a stepped efficient electric green hydrogen production method for new energy consumption, and belongs to the technical field of electric power systems, and the method comprises the following steps: collecting data in a new energy hydrogen production process; hydrogen electrolysis factors based on new energy power fluctuation are calculated; based on the hydrogen electrolysis factors, dividing power operation intervals of the electrolytic cell according to geometric intersection points; on the basis of the operation interval, according to the power of the new energy, different electrolytic cells are called in a stepped mode for electrolytic hydrogen production; according to the stepped efficient electric green hydrogen production method oriented to new energy consumption, the influence of new energy volatility is considered, the accuracy of electrolytic hydrogen production is improved, multiple types of electrolytic cells are adopted, stepped regulation and control are conducted on the electrolytic cells, and the new energy consumption capacity is improved; the electric hydrogen production efficiency is improved, and the energy consumption level is improved; the high-efficiency and low-cost electrolytic cell material is realized, the operation condition is optimized, and the control strategy is advanced.

Description

Technical Field

[0001] The present invention belongs to the technical field of power systems, and particularly relates to a stepped high-efficiency electrolytic green hydrogen production method for new energy consumption. Background Art

[0002] Electrolytic hydrogen production is of great significance for new energy consumption. By carrying out electrolytic hydrogen production during low electricity consumption periods, the surplus new energy power can be consumed, reducing the phenomena of wind and light abandonment. During peak electricity consumption periods, hydrogen production is reduced and electricity is released to the power grid to balance power supply and demand. Converting excess renewable energy such as wind energy and solar energy into hydrogen through electrolysis of water can be stored for use when needed, thereby improving the utilization rate of new energy. The green hydrogen produced by electrolytic hydrogen production can be used in multiple fields such as transportation, industry, and power generation, promoting the development of the hydrogen energy economy, reducing dependence on fossil energy, and reducing carbon emissions. No greenhouse gases such as carbon dioxide are produced during the electrolytic hydrogen production process. Using green hydrogen to replace traditional fossil fuels can significantly reduce greenhouse gas emissions. However, the current electrolytic hydrogen production technology faces the following problems: 1) The types of electrolyzers are single. Currently, the types of electrolyzers used in the electrolysis process are relatively single, such as using only alkaline electrolyzers (ALK) or proton exchange membrane electrolyzers (PEM) alone, without comprehensively considering the coupling between electrolyzers; 2) Poor adaptability to new energy fluctuations. New energy (such as wind energy and solar energy) is volatile and intermittent, resulting in unstable power supply. This volatility has an adverse impact on the operation of the electrolyzer and the efficiency of electrolytic hydrogen production. The current electrolyzer technology still has deficiencies in dealing with these fluctuations; 3) The level of new energy consumption is not high. The consumption capacity of new energy power generation is limited, resulting in waste of some renewable energy. Improving the efficiency and flexibility of electrolytic hydrogen production technology to better consume fluctuating renewable energy is an urgent problem to be solved; 4) Efficiency and cost issues. The efficiency and cost of the existing electrolytic hydrogen production technology still need to be further optimized. Therefore, it is necessary to develop a new stepped high-efficiency electrolytic green hydrogen production method for new energy consumption to solve the existing problems. Summary of the Invention

[0003] The purpose of the present invention is to provide a stepped high-efficiency electrolytic green hydrogen production method for new energy consumption to solve the above problems.

[0004] To achieve the above purpose, the present invention provides the following technical solution: A stepped high-efficiency electrolytic green hydrogen production method for new energy consumption, comprising:

[0005] Collecting data during the new energy hydrogen production process;

[0006] Calculating a hydrogen electrolysis factor based on new energy power fluctuations;

[0007] Based on the hydrogen electrolysis factor, dividing the electrolyzer power operation interval according to the geometric intersection point;

[0008] Based on the operating range, different electrolyzers are called step by step according to the power of new energy for hydrogen production by electrolysis.

[0009] Preferably, the data collected during the new energy hydrogen production process includes: electrolyzer temperature, electrolyte concentration, input power, and the amount of hydrogen generated, as shown in formula (1):

[0010] X = [T, C, P, H] (1)

[0011] Where: X is the new energy hydrogen production data collected, T is the electrolyzer temperature data collected, C is the electrolyte concentration data collected, P is the new energy power data input collected, and H is the amount of hydrogen generated data collected.

[0012] Preferably, the calculation of the hydrogen electrolysis factor based on the new energy power fluctuation is as shown in formula (2);

[0013]

[0014] Where represents the electrolyzer efficiency; represents the amount of hydrogen generated per unit power; represents the influence of new energy fluctuation on the hydrogen electrolysis efficiency;

[0015] η is the hydrogen electrolysis factor considering the new energy power fluctuation; k a and k b are both electrolyzer fitting factors, k c is the new energy power fluctuation factor; E a is the activation energy, R is the gas constant, T is the electrolyzer temperature; C is the electrolyte concentration; H is the amount of hydrogen generated by electrolysis; P is the electrolysis power; △P is the amplitude of power fluctuation within △t time.

[0016] Preferably, the solution of the electrolyzer fitting factor k a includes: constructing an LSTM model;

[0017] The input sample is: Z(t) = [k a (t), T(t), C(t), P(t)]; t represents time; the output is: F C (t + △t) = [k a (t + △t)];

[0018] Taking the electrolyzer temperature, electrolyte concentration, and power under different historical working conditions as input samples, inputting the standard electrolyzer fitting factor in the hidden layer; then training the LSTM model based on the input sample data and cell state information, and the training process is as shown in formula (3):

[0019]

[0020] In the formula, σ is the activation function of the electrolytic cell fitting factor model; f t is the output of the forget gate of the electrolytic cell fitting factor model, and W f , b f are the corresponding forget gate matrices of the electrolytic cell fitting factor model; i t is the output of the input gate of the electrolytic cell fitting factor model, and W i , b i are the corresponding input gate weight matrices of the electrolytic cell fitting factor model; C t-1 is the old cell state information of the electrolytic cell fitting factor model, is the candidate state information selected and added by the electrolytic cell fitting factor model, and C t is the updated cell information of the electrolytic cell fitting factor model, and W C , b C are the corresponding neuron matrices of the electrolytic cell fitting factor model; o t is the output of the output gate of the electrolytic cell fitting factor model, and W o , b o are the corresponding output gate matrices of the electrolytic cell fitting factor model; Y t-1 represents the output result of the electrolytic cell fitting factor model at time t - 1; Z is the input sample at time t;

[0021] The final electrolytic cell fitting factor k a model is shown in formula (4):

[0022] k a (t + △t) = f a (k a (t), T(t), C(t), P(t)) (4)

[0023] In the formula: f a () is the LSTM prediction model of the electrolytic cell fitting factor k a . According to this model, when the input is k a (t), T(t), C(t), P(t), the electrolytic cell fitting factor k a (t + △t) at future time t + △t can be predicted.

[0024] Preferably, the solution of the electrolytic cell fitting factor k b includes:

[0025] Based on the LSTM model, the electrolytic cell fitting factor k b model can be obtained as shown in formula (5):

[0026] k b (t + △t) = f b (k b(t), T(t), C(t), P(t)) (5)

[0027] Where: f b () is the fitting factor k of the electrolyzer b of the LSTM prediction model. According to this model, when inputting k b (t), T(t), C(t), P(t), the fitting factor k of the electrolyzer at the future time t + △t can be predicted b (t + △t).

[0028] Preferably, the new energy power fluctuation factor k c is solved including:

[0029] Based on the LSTM algorithm, the new energy power fluctuation factor k can be obtained c The model is shown in formula (6):

[0030] k c (t + △t) = f c (k c (t), H(t), △P(t), △t) (6)

[0031] Where: f c () is the LSTM model of the new energy power fluctuation factor k. According to this model, when inputting k c (t), H(t), △P(t), △t, the new energy power fluctuation factor k at the future time t + △t can be predicted c (t + △t). c (t + △t).

[0032] Preferably, the division of the electrolyzer power operation range according to the geometric intersection points includes:

[0033] Four types of electrolyzers, namely electrolyzers θ1 - θ4,

[0034] Take the geometric intersection points B, C, D of the curves of each type of electrolyzer. The power decomposition points corresponding to these geometric intersection points are p2, p3, p4 respectively;

[0035] Combined with the new energy power operation range (p1, p5), the efficient operation area of new energy electrolytic hydrogen production is obtained.

[0036] Preferably, different electrolyzers are called step by step for electrolytic hydrogen production according to the power of the new energy;

[0037] When p1 ≤ p < p2, electrolyzer θ1 is called to participate in electrolytic hydrogen production, and the operating range is section AB; when p2 ≤ p < p3, electrolyzer θ2 is called to participate in electrolytic hydrogen production, and the operating range is section BC; when p3 ≤ p < p4, electrolyzer θ3 is called to participate in electrolytic hydrogen production, and the operating range is section CD; when p4 ≤ p ≤ p5, electrolyzer θ4 is called to participate in electrolytic hydrogen production, and the operating range is section DE;

[0038] Among them, λ represents the electrolyzer participating in electrolytic hydrogen production.

[0039] Technical effects and advantages of the present invention: This stepped high-efficiency electrolytic green hydrogen production method for new energy consumption takes into account the influence of new energy volatility, improves the accuracy of electrolytic hydrogen production, adopts various types of electrolyzers, and conducts stepped regulation on them to improve the new energy consumption capacity; improves the electrolytic hydrogen production efficiency and the energy consumption level; realizes high-efficiency and low-cost electrolyzer materials, optimizes the operating conditions, and has advanced control strategies. Description of the Drawings

[0040] Figure 1 is a schematic flow chart of the method of the present invention;

[0041] Figure 2 is the electrolyzer fitting factor k a model based on LSTM of the present invention;

[0042] Figure 3 is a schematic diagram of the high-efficiency operating area of multiple electrolyzers based on geometric decomposition of the present invention;

[0043] Figure 4 is a schematic diagram of the stepped operation method of new energy electrolytic hydrogen production of the present invention. Detailed Embodiments

[0044] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0045] The present invention provides as Figure 1A stepped high-efficiency electrolytic hydrogen production method for new energy accommodation is shown as follows. First, a new energy electrolytic hydrogen production data acquisition technology is proposed to collect the electrolytic cell temperature, electrolyte concentration, input power, and hydrogen production amount during the new energy electrolytic hydrogen production process. Then, a hydrogen electrolysis factor considering the new energy power fluctuation is proposed. During the electrolysis process, the influence of the new energy power fluctuation on the hydrogen electrolysis efficiency is considered, and factors such as temperature and electrolyte concentration are comprehensively considered to obtain a more accurate electrolytic hydrogen efficiency. Secondly, a method for solving the high-efficiency operation area of multiple electrolytic cells based on geometric decomposition is proposed. A variety of electrolytic cells are used for electrolytic hydrogen production. According to the power operation range of each type of electrolytic cell and the geometric characteristics of the hydrogen electrolysis factor curve, the high-efficiency operation area is divided to improve the accommodation level of new energy. Finally, a stepped operation method for new energy electrolytic hydrogen production based on the hydrogen electrolysis factor is proposed. According to the highest hydrogen electrolysis factor of each electrolytic cell, different electrolytic cells are steppedly scheduled for electrolytic hydrogen production, greatly improving the accommodation level of new energy. The stepped high-efficiency electrolytic hydrogen production method for new energy accommodation provided by the present invention improves the electrolytic hydrogen production efficiency and the accommodation ability of new energy, which has important significance.

[0046] The steps are as follows:

[0047] Step 1: Propose a new energy electrolytic hydrogen production data acquisition technology. Collect the electrolytic cell temperature, electrolyte concentration, input power, and hydrogen production amount during the new energy electrolytic hydrogen production process. For the electrolytic cell temperature, it can be collected by sensors such as thermocouples, RTDs (Platinum Resistance Thermometers), and thermistors. The temperature sensors are usually installed inside the electrolytic cell or near the electrodes to ensure accurate temperature readings. In the present invention, multi-point temperature measurement is used to monitor the temperature of different parts of the electrolytic cell, and the average value is taken as the final temperature. For the electrolyte concentration, the present invention uses an online conductivity meter for collection, and the online conductivity meter is installed at the inlet and outlet of the electrolytic cell or in the electrolyte circulation system. For the input power, the present invention uses current sensors and voltage sensors for measurement. The current sensors are installed in the power supply line of the electrolytic cell, and the voltage sensors should be connected to the electrodes of the electrolytic cell. For the hydrogen production amount, the present invention uses a gas flow meter for measurement, and a gas flow meter is installed on the hydrogen output pipeline to measure the hydrogen flow rate in real time.

[0048] Step 2: Propose a hydrogen electrolysis factor considering the power fluctuation of new energy. The hydrogen electrolysis process is affected by the power magnitude and power fluctuation. Different powers result in different hydrogen electrolysis efficiencies, and the power fluctuation affects the hydrogen electrolysis efficiency mainly in the following aspects: First, the instantaneous power change will cause the overpotential change. The electrode overpotential in the electrolyzer will change with the change of current density, leading to the fluctuation of efficiency. Second, the power fluctuation will affect the temperature control of the electrolyzer. The temperature change will affect the electrolyte conductivity and reaction rate, and thus affect the efficiency. Finally, the power fluctuation may cause the instability of mass transfer phenomena (such as bubble formation and diffusion), affecting the reaction efficiency. The traditional method does not consider the influence of new energy fluctuation on the hydrogen electrolysis efficiency, resulting in inaccurate electrolytic hydrogen results. The present invention proposes a hydrogen electrolysis factor considering the power fluctuation of new energy, taking into account the influence of new energy power fluctuation on the hydrogen electrolysis efficiency during the electrolysis process, and comprehensively considering factors such as temperature and electrolyte concentration, so as to obtain a more accurate electrolytic hydrogen efficiency.

[0049] Step 3: Propose a method for solving the high-efficiency operation area of multiple electrolyzers based on geometric decomposition. The traditional method mainly electrolyzes hydrogen based on a single type of electrolyzer. The electrolyzer generally operates within a certain power range. When the new energy power exceeds its operating range, the hydrogen electrolysis efficiency of the electrolyzer decreases or it is difficult to operate, resulting in the phenomenon of abandoned wind or abandoned light of new energy and affecting the consumption of new energy. To improve the consumption level of new energy, the present invention proposes to use multiple types of electrolyzers to electrolyze hydrogen. The high-efficiency operation area is divided according to the power operation range of each type of electrolyzer and the geometric characteristics of the hydrogen electrolysis factor curve, so as to improve the consumption level of new energy. First, based on the hydrogen electrolysis factor considering the power fluctuation of new energy proposed in Step 2, the curves of the hydrogen electrolysis factors of each type of electrolyzer with respect to the new energy power are drawn. The upper geometric intersection points of each curve are taken, and the high-efficiency operation range of the electrolyzer power is divided according to the geometric intersection points, so as to improve the consumption level of new energy.

[0050] Step 4: Propose a stepped operation method for new energy electrolytic hydrogen based on the hydrogen electrolysis factor. Different from the traditional mode of electrolyzing hydrogen relying on a single type of electrolyzer, the present invention hierarchically schedules different electrolyzers to electrolyze hydrogen according to the highest hydrogen electrolysis factors of each electrolyzer, greatly improving the consumption level of new energy. According to the high-efficiency operation area and geometric intersection points divided in Step 3, according to the magnitude of the new energy power, when the new energy power is within the stepped scheduling of different types of electrolyzers for electrolytic hydrogen, the consumption level of new energy is improved.

[0051] For Step (1), the new energy hydrogen production data collected is shown in Formula (1). It mainly includes the electrolyzer temperature, electrolyte concentration, input power, and hydrogen production amount during the new energy hydrogen production process.

[0052] X = [T, C, P, H] (1)

[0053] Where: X is the new energy hydrogen production data collected, T is the electrolyzer temperature data collected, C is the electrolyte concentration data collected, P is the new energy power data of the input collected, and H is the hydrogen production data generated.

[0054] For step (2), a hydrogen electrolysis factor considering the new energy power fluctuation is proposed as shown in formula (2). Among them represents the electrolyzer efficiency; represents the hydrogen production per unit power; represents the influence of new energy fluctuation on hydrogen electrolysis efficiency.

[0055]

[0056] Where: η is the hydrogen electrolysis factor considering the new energy power fluctuation; k a and k b are both electrolyzer fitting factors, k c is the new energy power fluctuation factor; E a is the activation energy, that is, the minimum energy required for electrolyzing hydrogen. The activation energies of different electrolysis systems are different. The activation energy of pure water electrolysis is usually between 50 - 70 kJ / mol. The activation energy of acidic electrolytes (such as sulfuric acid) is approximately in the range of 40 - 60 kJ / mol. The activation energy of alkaline electrolytes (such as sodium hydroxide or potassium hydroxide) is approximately in the range of 30 - 50 kJ / mol. The activation energy of neutral electrolytes is usually between 50 - 70 kJ / mol; R is the gas constant, and in this invention, it is taken as 8.314 kJ / mol; T is the electrolyzer temperature; C is the electrolyte concentration; H is the hydrogen production of electrolysis; P is the electrolysis power; △P is the amplitude of power fluctuation within △t time, and e represents the base of the natural logarithm, which is an irrational number, and its value is approximately equal to 2.71828.

[0057] This invention is based on the LSTM algorithm to solve the electrolyzer fitting factors k a and k b , and the new energy power fluctuation factor k c , and LSTM models are respectively constructed. Taking the solution of the electrolyzer fitting factor k a as an example to illustrate the solution process, as Figure 2 shown, the electrolyzer fitting factor k a is related to the electrolyzer temperature T, electrolyte concentration C, and power P. This invention solves the electrolyzer fitting factor k a through the training of the above data.

[0058] The input sample is: Z(t) = [k a (t), T(t), C(t), P(t)], where t represents time;

[0059] The output is: F C (t + △t) = [ka (t + △t)]

[0060] Taking the electrolyzer temperature, electrolyte concentration, and power under different historical operating conditions as input samples, input the standard electrolyzer fitting factor into the hidden layer. Then, based on the input sample data and cell state information, train the LSTM model. The training process is shown in Equation (3).

[0061]

[0062] In the formula, σ is the activation function of the electrolyzer fitting factor model; f t is the output of the forget gate of the electrolyzer fitting factor model, W f , b f are the corresponding forget gate matrices of the electrolyzer fitting factor model; i t is the output of the input gate of the electrolyzer fitting factor model, W i , b i are the corresponding input gate weight matrices of the electrolyzer fitting factor model; C t-1 is the old cell state information of the electrolyzer fitting factor model, is the candidate state information selected to be added by the electrolyzer fitting factor model, C t is the updated cell information of the electrolyzer fitting factor model, W C , b C are the corresponding neuron matrices of the electrolyzer fitting factor model; o t is the output of the output gate of the electrolyzer fitting factor model, W o , b o are the corresponding output gate matrices of the electrolyzer fitting factor model; Y t-1 represents the output result of the electrolyzer fitting factor model at time t - 1; Z is the input sample at time t;.

[0063] The final electrolyzer fitting factor k a model is shown in Equation (4):

[0064] k a (t + △t) = f a (k a (t), T(t), C(t), P(t)) (4)

[0065] In the formula: f a () is the LSTM prediction model of the electrolyzer fitting factor k a . According to this model, when inputting k a (t), T(t), C(t), P(t), the electrolyzer fitting factor k a (t + △t) at future time t + △t can be predicted.

[0066] Similarly, based on the LSTM model, the electrolyzer fitting factor k can be obtained. b The model is shown in Equation (5):

[0067] k b (t + △t) = f b (k b (t), T(t), C(t), P(t)) (5)

[0068] Where: f b () is the LSTM prediction model of the electrolyzer fitting factor k. According to this model, when inputting k b (t), T(t), C(t), P(t), the electrolyzer fitting factor k at future time t + △t can be predicted. b (t + △t). b

[0069] Similarly, based on the LSTM algorithm, the new energy power fluctuation factor k can be obtained. c The model is shown in Equation (6):

[0070] k c (t + △t) = f c (k c (t), H(t), △P(t), △t) (6)

[0071] Where: f c () is the LSTM model of the new energy power fluctuation factor k. According to this model, when inputting k c (t), H(t), △P(t), △t, the new energy power fluctuation factor k at future time t + △t can be predicted. c (t + △t). c

[0072] For step (3), first, based on the hydrogen electrolysis factor considering the new energy power fluctuation proposed in step 2, curves of the hydrogen electrolysis factor of various electrolyzers with respect to the new energy power are plotted, as Figure 3 shown. Figure 3 There are four types of electrolyzers, namely electrolyzers θ1 - θ4. Then, geometric intersection points B, C, and D of the curves of each type of electrolyzer are taken, and the corresponding power decomposition points of these geometric intersection points are p2, p3, and p4 respectively. Finally, combined with the new energy power operation range (p1, p5), the efficient operation area of new energy electrolytic hydrogen production is obtained, as Figure 2 shown by the shaded part in.

[0073] For step (4), according to step 3, the efficient operation area as Figure 4 shown can be obtained. The core of the stepped operation method of new energy electrolytic hydrogen production based on the hydrogen electrolysis factor lies in stepwise calling different electrolyzers for electrolytic hydrogen production according to the power of new energy.

[0074] The present invention stepwise calls different electrolyzers to participate in electrolytic hydrogen production according to formula (7), improving the accommodation level of new energy. When p1 ≤ p < p2, electrolyzer θ1 is called to participate in electrolytic hydrogen production, and the operating range is the AB section; when p2 ≤ p < p3, electrolyzer θ2 is called to participate in electrolytic hydrogen production, and the operating range is the BC section; when p3 ≤ p < p4, electrolyzer θ3 is called to participate in electrolytic hydrogen production, and the operating range is the CD section; when p4 ≤ p ≤ p5, electrolyzer θ4 is called to participate in electrolytic hydrogen production, and the operating range is the DE section;

[0075] where λ represents the electrolyzer participating in electrolytic hydrogen production;

[0076] Through the above steps, the overall efficiency of new energy electrolytic hydrogen production can be improved, and the accommodation level of new energy can be improved.

[0077] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A stepped high-efficiency electrolytic green hydrogen production method for new energy consumption, characterized in that: Including: Collecting data during the process of hydrogen production from new energy; Calculating the hydrogen electrolysis factor based on the power fluctuation of new energy; Dividing the power operation range of the electrolyzer based on the hydrogen electrolysis factor according to the geometric intersection points; Based on the operation range, stepwise calling different electrolyzers for electrolytic hydrogen production according to the power of new energy.

2. The stepped high-efficiency electrolysis method for green hydrogen production for new energy accommodation according to claim 1, wherein: The collecting data during the process of hydrogen production from new energy includes: the temperature of the electrolyzer, the concentration of the electrolyte, the input power, and the amount of hydrogen generated, as shown in formula (1): X = [T, C, P, H] (1) Where: X is the data of hydrogen production from new energy collected, T is the data of the temperature of the electrolyzer collected, C is the data of the concentration of the electrolyte collected, P is the data of the input new energy power collected, and H is the data of the amount of hydrogen generated collected.

3. A stepped high-efficiency electrolysis method for green hydrogen production for new energy consumption according to claim 1, characterized in that: The calculating the hydrogen electrolysis factor based on the power fluctuation of new energy includes: As shown in formula (2); Among them represents the electrolyzer efficiency; represents the amount of hydrogen produced per unit power; represents the impact of new energy fluctuations on the hydrogen electrolysis efficiency; η is the hydrogen electrolysis factor considering the power fluctuation of new energy; k a and k b are both electrolyzer fitting factors, k c is the new energy power fluctuation factor; E a is the activation energy, R is the gas constant, T is the electrolyzer temperature; C is the electrolyte concentration; H is the amount of hydrogen generated by electrolysis; P is the electrolysis power; △P is the amplitude of power fluctuation within △t time.

4. The stepped high-efficiency electrolysis method for green hydrogen production for new energy accommodation according to claim 3, characterized in that: The fitting factor k of the electrolytic cell a The solution includes: constructing an LSTM model; the input sample is: Z(t) = [k a (t), T(t), C(t), P(t)], where t represents time; the output is: F C (t + △t) = [k a (t + △t)]; Taking the temperature of the electrolyzer, the concentration of the electrolyte, and the power under different historical working conditions as input samples, and inputting the standard electrolyzer fitting factor into the hidden layer; then training the LSTM model based on the input sample data and the cell state information, and the training process is as shown in formula (3): Where, σ is the activation function of the electrolytic cell fitting factor model; f t is the output of the forget gate of the electrolytic cell fitting factor model, W f , b f are the corresponding forget gate matrices of the electrolytic cell fitting factor model; i t is the output of the input gate of the electrolytic cell fitting factor model, W i , b i are the corresponding input gate weight matrices of the electrolytic cell fitting factor model; C t-1 is the old cell state information of the electrolytic cell fitting factor model, is the candidate state information selected and added by the electrolytic cell fitting factor model, C t is the updated cell information of the electrolytic cell fitting factor model, W C , b C are the corresponding neuron matrices of the electrolytic cell fitting factor model; o t is the output of the output gate of the electrolytic cell fitting factor model, W o , b o are the corresponding output gate matrices of the electrolytic cell fitting factor model; Y t-1 represents the output result of the electrolytic cell fitting factor model at time t - 1; Z is the input sample at time t; Final electrolyzer fitting factor k a The model is shown in Equation (4): k a (t + Δt) = f a (k a (t), T(t), C(t), P(t)) (4) where: f a () is the fitting factor k of the electrolytic cell a of the LSTM prediction model. According to this model, when the input is k a (t), T(t), C(t), P(t), the fitting factor k of the electrolytic cell at the future time t + △t can be predicted a (t + △t).

5. A stepped high-efficiency electrolysis method for green hydrogen production for new energy accommodation according to claim 4, characterized in that: The fitting factor k of the electrolytic cell b The solution includes: Based on the LSTM model, the fitting factor k of the electrolytic cell can be obtained b The model is shown in formula (5): k b (t + Δt) = f b (k b (t), T(t), C(t), P(t)) (5) Where: f b () is the electrolytic cell fitting factor k b of the LSTM prediction model. When the inputs are k b (t), T(t), C(t), P(t), the electrolytic cell fitting factor k b (t + △t) at the future time t + △t can be predicted.

6. The stepped high-efficiency electrolytic green hydrogen production method for new energy accommodation according to claim 4, characterized in that: The new energy power fluctuation factor k c The solution includes: Based on the LSTM algorithm, the new energy power fluctuation factor k is obtained c The model is shown in Equation (6): k c (t + Δt) = f c (k c (t), H(t), ΔP(t), Δt) (6) where: f c () is the new energy power fluctuation factor k c of the LSTM model. When inputting k c (t), H(t), △P(t), △t, the new energy power fluctuation factor k c (t + △t) at the future time t + △t can be predicted.

7. A stepped high-efficiency electrolytic green hydrogen production method for new energy consumption according to claim 1, characterized in that: The dividing the power operation range of the electrolyzer according to the geometric intersection points includes: Four types of electrolyzers, namely electrolyzers θ1 - θ4, Taking the geometric intersection points B, C, and D of the curves of each type of electrolyzer, and the power decomposition points corresponding to the geometric intersection points are p2, p3, and p4 respectively; Combining the power operation range (p1, p5) of new energy to obtain the efficient operation area of new energy electrolytic hydrogen production.

8. A stepped high-efficiency electrolysis method for green hydrogen production for new energy accommodation according to claim 1, characterized in that: The stepwise calling different electrolyzers for electrolytic hydrogen production according to the power of new energy includes; When p1 ≤ p < p2, calling electrolyzer θ1 to participate in electrolytic hydrogen production, and the operation range is section AB; when p2 ≤ p < p3, calling electrolyzer θ2 to participate in electrolytic hydrogen production, and the operation range is section BC; when p3 ≤ p < p4, calling electrolyzer θ3 to participate in electrolytic hydrogen production, and the operation range is section CD; when p4 ≤ p ≤ p5, calling electrolyzer θ4 to participate in electrolytic hydrogen production, and the operation range is section DE; Among them, λ represents the electrolyzer involved in electrolytic hydrogen production.

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