Method, device and equipment for optimizing operation interval parameters of electrolytic cell

Abstract

The invention provides a method, a device and equipment for optimizing operation interval parameters of an electrolytic cell. The method comprises the following steps: acquiring real-time running state data and external power system data of the electrolytic cell; obtaining the voltage and current efficiency of the electrolytic cell according to the real-time operation state data; hydrogen production energy consumption is obtained according to the voltage of the electrolytic cell and the current efficiency; according to the hydrogen production energy consumption, dividing an operation interval of an electrolytic bath to obtain a plurality of operation intervals; according to the external power system data, performing rolling optimization solution on a multi-objective optimization function, and dynamically determining an optimal operation interval of the electrolytic cell in a plurality of operation intervals; and the electrolytic cell is controlled to operate in the optimal operation interval. According to the scheme, the operation interval of the electrolytic cell can be divided into three dynamic control areas, and the optimal operation interval is dynamically solved through real-time electricity price, wind power and photovoltaic output prediction, so that the electrolysis efficiency is improved, and the electrolysis cost is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of hydrogen production, in particular to an electrolyzer operation interval parameter optimization method, device and equipment. BACKGROUND

[0002] The electrolyzer is a key device for realizing the conversion of electric energy to hydrogen energy, and its operation characteristics are affected by multiple factors. In the related field, the current efficiency of the electrolyzer will affect the hydrogen production energy consumption and actual yield, and there is a correlation between factors such as electrolyte temperature and current density and current efficiency. In the prior art, the control mode of the electrolyzer operation interval is relatively simple and extensive, and usually only a fixed power threshold is used to control the operation state of the electrolyzer, without fully considering the efficiency and energy consumption differences of the electrolyzer under different current densities and temperatures. This mode often causes the electrolyzer to operate in a low-efficiency and high-energy-consumption interval, and cannot be flexibly adjusted according to real-time power supply and demand and electricity price fluctuations, resulting in high hydrogen production costs, and the service life of the equipment is also affected. When facing fluctuating power sources such as wind power and photovoltaic power, it is difficult to effectively respond to power fluctuations, which easily causes the electrolyzer to frequently start and stop or run at reduced load. SUMMARY

[0003] The present application provides an electrolyzer operation interval parameter optimization method, device and equipment, which solves the problems of high hydrogen production cost, low service life of the electrolyzer and frequent start and stop or reduced load operation.

[0004] To solve the above technical problems, the technical solutions of the present application are as follows: The present application provides an electrolyzer operation interval parameter optimization method, device and equipment, which solves the problems of high hydrogen production cost, low service life of the electrolyzer and frequent start and stop or reduced load operation. Obtaining real-time operation state data of the electrolyzer and external power system data; According to the real-time operation state data, obtaining the electrolyzer voltage and current efficiency; According to the electrolyzer voltage and the current efficiency, obtaining the hydrogen production energy consumption; According to the hydrogen production energy consumption, dividing the operation interval of the electrolyzer to obtain a plurality of operation intervals; According to the external power system data, performing rolling optimization solution on the multi-objective optimization function to dynamically determine the optimal operation interval of the electrolyzer in the plurality of operation intervals; Controlling the electrolyzer to operate in the optimal operation interval.

[0005] Optionally, obtaining real-time operation state data of the electrolyzer and external power system data comprises: Obtaining at least one real-time operation state data of the electrolyte temperature and the input current of the electrolyzer; Obtaining at least two types of external power system data from real-time electricity price, wind power output prediction value and photovoltaic output prediction value.

[0006] Optionally, according to the real-time running state data, the electrolytic cell voltage and the current efficiency are obtained, comprising: According to the electrolyte temperature and the input current, the electrolytic cell voltage is obtained; According to the input current, the current efficiency is obtained by ; wherein, represents the current efficiency; is a first fitting parameter; is a second fitting parameter; is the input current; is the effective area of the electrolytic cell.

[0007] Optionally, according to the electrolytic cell voltage and the current efficiency, the hydrogen production energy consumption is obtained, comprising: According to , the hydrogen production rate is obtained; According to , the instantaneous power at the current moment is obtained; According to the hydrogen production rate and the instantaneous power, the hydrogen production energy consumption is obtained; wherein, V represents the hydrogen production rate; represents the current efficiency; represents the gas volume under standard conditions, and is 2÷89 for reducing error, unit: L / mol; is the input current; z is the number of transferred electrons in hydrogen production by water electrolysis; is the Faraday coefficient, which is a constant 96485 C / mol; represents the electrolytic cell voltage; P represents the instantaneous power.

[0008] Optionally, the construction process of the multi-objective optimization function comprises: The instantaneous power is integrated to obtain the cumulative energy consumption; According to , the change power is obtained; According to , the comprehensive running cost is obtained; According to the cumulative energy consumption, the change power and the comprehensive running cost, a multi-objective optimization function is constructed; the multi-objective optimization function is ; wherein, represents the change power; represents the instantaneous power; represents the instantaneous power of the previous period; represents the comprehensive running cost; represents the real-time electricity price cost; represents the maintenance cost of the electrolytic cell within the rolling period; represents the cumulative energy consumption; 、 、 denotes a first target weight, a second target weight and a third target weight in the multi-target weight; denotes the minimum value of the energy consumption of hydrogen production in the efficiency zone; denotes the rated power of the electrolytic cell; denotes the minimum cost of unit hydrogen production in the efficiency zone.

[0009] Optionally, according to the external power system data, the multi-target optimization function is solved by rolling optimization, and the optimal running interval of the electrolytic cell is dynamically determined in multiple running intervals, comprising: According to the external power system data, the multi-target weight is dynamically adjusted to obtain an updated multi-target optimization function; According to the updated multi-target optimization function, the optimal running interval at the current time is determined.

[0010] Optionally, the electrolytic cell is controlled to run in the optimal running interval, comprising: The electrolytic cell is controlled to run according to the input current corresponding to the optimal running interval, so as to run in the optimal running interval.

[0011] The embodiment of the application also provides an electrolytic cell running interval parameter optimization device, comprising: An acquisition module is configured to acquire real-time running state data of an electrolytic cell and external power system data; A processing module is configured to obtain electrolytic cell voltage and current efficiency according to the real-time running state data, obtain hydrogen production energy consumption according to the electrolytic cell voltage and the current efficiency, divide the running interval of the electrolytic cell according to the hydrogen production energy consumption to obtain multiple running intervals, solve a multi-target optimization function by rolling optimization according to the external power system data, dynamically determine the optimal running interval of the electrolytic cell in the multiple running intervals, and control the electrolytic cell to run in the optimal running interval.

[0012] The embodiment of the application also provides a computing device, comprising a processor and a memory storing a computer program, wherein the computer program is executed by the processor to perform the above method.

[0013] The embodiment of the application also provides a computer readable storage medium storing instructions, wherein when the instructions are executed on a computer, the computer performs the above method.

[0014] The technical scheme of the application at least has the following effects: The above-described solution of the present invention acquires real-time operating status data of the electrolyzer and external power system data; obtains the electrolyzer voltage and current efficiency based on the real-time operating status data; obtains the hydrogen production energy consumption based on the electrolyzer voltage and current efficiency; divides the electrolyzer into multiple operating ranges based on the hydrogen production energy consumption; performs rolling optimization on a multi-objective optimization function based on the external power system data, dynamically determines the optimal operating range of the electrolyzer among the multiple operating ranges; and controls the electrolyzer to operate within the optimal operating range. The electrolyzer operating range can be divided into three dynamically controlled regions. By predicting real-time electricity prices, wind power, and photovoltaic output, the optimal operating range is dynamically solved, thereby improving electrolysis efficiency and reducing electrolysis costs. Attached Figure Description

[0015] Figure 1 This is a flowchart of a method for optimizing the operating range parameters of an electrolytic cell according to an embodiment of the present invention; Figure 2 This is a structural diagram of the device for optimizing the operating range parameters of an electrolytic cell provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of the computing device provided in an embodiment of the present invention. Detailed Implementation

[0016] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0017] like Figure 1 As shown, an embodiment of the present invention proposes a method for optimizing the parameters of an electrolyzer operating range, including: Step 11: Obtain real-time operating status data of the electrolytic cell and external power system data; Step 12: Based on the real-time operating status data, obtain the electrolytic cell voltage and current efficiency; Step 13: Obtain the hydrogen production energy consumption based on the electrolyzer voltage and the current efficiency; Step 14: Based on the hydrogen production energy consumption, divide the operating range of the electrolyzer into multiple operating ranges; Step 15: Based on the external power system data, perform rolling optimization to solve the multi-objective optimization function, and dynamically determine the optimal operating range of the electrolyzer in multiple operating ranges; Step 16: Control the electrolytic cell to operate within the optimal operating range.

[0018] In this embodiment, in step 11, real-time operating status data is collected by sensors deployed in the electrolyzer system, including electrolyte temperature and input current; real-time electricity price, wind power output forecast, and photovoltaic power output forecast are obtained through the energy management system or grid data interface.

[0019] In step 12, based on the obtained electrolyte temperature and input current, the corresponding electrolytic cell voltage and current efficiency are obtained through the voltage model and current efficiency model.

[0020] In step 13, the hydrogen production energy consumption is the energy consumption for producing one unit of hydrogen. The unit is This indicator reflects the electrical energy consumed in producing each standard cubic meter of hydrogen and is the most direct indicator for measuring operational energy efficiency.

[0021] In step 14, the different hydrogen production energy consumption can divide the operating power range into three functionally oriented zones: the efficiency zone, the economic zone, and the safety zone. The efficiency zone has the lowest unit hydrogen production energy consumption. Although the power consumption is high, the efficiency is high and the unit hydrogen production power consumption is the lowest. The economic zone is suitable for high electricity prices or grid peak shaving needs. By sacrificing some efficiency, the operating cost is reduced. If the electrolyzer maintains the efficiency zone, although the efficiency is high, it requires a large amount of high-priced electricity, resulting in the increase in electricity price cost exceeding the energy savings brought by the efficiency improvement. The safety zone is used for emergency equipment protection and to deal with power shortages.

[0022] In step 15, the multi-objective optimization function simultaneously minimizes energy consumption, power fluctuations (affecting lifetime), and operating costs, combining external market and environmental signals, internal equipment characteristics, and multiple conflicting objectives through "prediction." optimization The "rolling" mechanism makes forward-looking and intelligent optimal decisions, dynamically providing the answer to which range of operation of the electrolyzer yields the highest overall benefit. The rolling optimization solution process starts from the current state, predicts the system behavior at multiple future time points based on a multi-objective optimization function, solves the above multi-objective function under constraints (such as power change ΔP≤M, where M is the power change gradient constraint), outputs the optimal control sequence for a future period, and implements the optimal operating range command at the current time.

[0023] In step 16, the optimal operating range represents a target power range, which can be converted into a specific input current control signal and sent to the electrolytic cell's regulation system. Through closed-loop control, the input current is precisely adjusted so that the actual operating power is stabilized within the optimal operating range.

[0024] This technical solution maximizes the overall operational benefits of the electrolyzer, solves the problem of balancing multiple objectives in the hydrogen production process, significantly reduces the unit hydrogen production energy consumption while improving energy utilization efficiency, thereby effectively extending the service life of the equipment and reducing the cost of hydrogen production.

[0025] In an optional embodiment of the present invention, step 11, obtaining real-time operating status data of the electrolytic cell and external power system data, may include: Step 111: Obtain at least one of the real-time operating status data of the electrolyte temperature and input current of the electrolytic cell; Step 112: Obtain at least two types of external power system data from real-time electricity prices, wind power output forecasts, and photovoltaic power output forecasts.

[0026] In this embodiment, in step 111, real-time operating status data is collected by sensors deployed in the electrolytic cell system. The real-time operating status data includes electrolyte temperature and input current. In step 112, real-time electricity price, wind power output forecast, and photovoltaic power output forecast are obtained through the energy management system or grid data interface. Since this scheme focuses on comprehensive operational benefits, it is necessary to obtain at least two of the real-time electricity price, wind power output forecast, and photovoltaic power output forecast. Different data from the external power system can affect the multi-objective weights of the multi-objective optimization function.

[0027] In an optional embodiment of the present invention, step 12, obtaining the electrolytic cell voltage and current efficiency based on the real-time operating status data, may include: Step 121: Obtain the electrolytic cell voltage based on the electrolyte temperature and input current; Step 122, based on the input current, through The current efficiency is obtained; where, Indicates current efficiency; These are the first fitted parameters; These are the second fitting parameters; For input current; This represents the effective area of ​​the electrolytic cell.

[0028] In this embodiment, in step 121, the electrolytic cell voltage mainly comprises three components, namely, the electrolytic cell voltage. ; wherein, the It is a reversible voltage; the The polarity voltage is ohmic; This is the activation polarity voltage. The reversible voltage is obtained through... Obtain; the ohmic polarity voltage is obtained through The activation polarity voltage is obtained through... Obtain; among which, It is a reversible voltage; It is the ohmic polarity voltage; Activation polarity voltage; and The ohmic resistance parameter of the electrolyte; The effective area of ​​the electrolytic cell; The electrolyte temperature; For input current; denoted as Gibbs free energy of the electrolysis reaction, with a value of 237.1 kJ / mol; z represents the number of electrons transferred during hydrogen production via water electrolysis, with a value of 2. The coefficient is Faraday's constant, taken as 96485 C / mol; s, , and This represents the overvoltage coefficient of the alkaline electrolytic cell.

[0029] In step 122, based on the input current, through To obtain the current efficiency, the temperature was set to T℃, the pressure to nMPa, and the input current of the electrolyzer was set within the range of [a, b]A. The electrolyzer was run at a constant rate of 5A for 10 minutes. The current efficiency under the current input current was calculated by comparing the actual hydrogen production with the theoretical value. The first fitting parameter was then obtained. The second fitting parameter is That is, current efficiency through We obtain; where, Indicates current efficiency; These are the first fitted parameters; These are the second fitting parameters; For input current; This represents the effective area of ​​the electrolytic cell.

[0030] In an optional embodiment of the present invention, step 13, obtaining the hydrogen production energy consumption based on the electrolyzer voltage and the current efficiency, may include: Step 131, according to The hydrogen production rate was obtained. Step 132, according to This gives the instantaneous power at the current moment; Step 133: Obtain the hydrogen production energy consumption based on the hydrogen production rate and the instantaneous power. Where V represents the hydrogen production rate; Indicates current efficiency; This represents the gas volume under standard conditions (taken as 2 ÷ 89 to reduce error), with units of L / mol. The input current is z; z is the number of electrons transferred during hydrogen production via water electrolysis. The coefficient is Faraday's constant, taken as 96485 C / mol; represents the voltage of the electrolytic cell; P represents the instantaneous power.

[0031] In this embodiment, in step 131, based on the input current and the current efficiency, by... The hydrogen production rate is obtained; the hydrogen production efficiency can also be obtained. .

[0032] In step 132, based on the input current and the electrolytic cell voltage, by... This gives the instantaneous power at the current moment; In step 133, based on the hydrogen production rate and the instantaneous power, by... The energy consumption for hydrogen production was obtained; according to the above ,available In this way, the relationship between current efficiency and hydrogen production energy consumption is established; Where V represents the hydrogen production rate; Indicates current efficiency; This represents the gas volume under standard conditions (taken as 2 ÷ 89 to reduce error), with units of L / mol. The input current is z; z is the number of electrons transferred during hydrogen production via water electrolysis. The coefficient is Faraday's constant, taken as 96485 C / mol; P represents the voltage of the electrolytic cell; P represents the instantaneous power. This indicates the energy consumption for hydrogen production.

[0033] In an optional embodiment of the present invention, step 14, dividing the operating range of the electrolyzer according to the hydrogen production energy consumption to obtain multiple operating ranges, may include: Step 141, when the hydrogen production energy consumption < The operating range of the electrolytic cell is a safe zone; Step 142, when <The energy consumption for hydrogen production< The operating range of the electrolytic cell is the economic zone; Step 143, when <The energy consumption for hydrogen production< The operating range of the electrolytic cell is the efficiency range.

[0034] In this embodiment, the operating range of the electrolyzer is divided into a safe zone, an economic zone, and an efficiency zone based on the hydrogen production energy consumption being within a preset threshold range; , and That is, the first threshold range, the second threshold range, and the third threshold range.

[0035] In an optional embodiment of the present invention, step 15, which involves performing rolling optimization on a multi-objective optimization function based on the external power system data to dynamically determine the optimal operating range of the electrolyzer within multiple operating ranges, may include: Step 151: Based on the external power system data, dynamically adjust the multi-objective weights to obtain the updated multi-objective optimization function; Step 152: Determine the optimal operating range at the current moment based on the updated multi-objective optimization function.

[0036] In this embodiment, the process of constructing the multi-objective optimization function includes: (1) Integrate the instantaneous power to obtain the cumulative energy consumption; specifically including: according to This yields the cumulative energy consumption within the current scrolling window; where, This is the set time for the scrolling window; It represents the cumulative energy consumption within the current scrolling window; It is the voltage of the electrolytic cell; This is the input current.

[0037] (2) According to The changing power is obtained; Specifically, It is the difference between the instantaneous power in the new cycle (new rolling window) and the instantaneous power in the previous cycle, which is the change in power between the two cycles; It is the instantaneous power within the current new cycle; It is the instantaneous power within the previous cycle.

[0038] (3) According to The overall operating cost is obtained; Specifically, the comprehensive operating cost is the combined value of electricity price and maintenance cost. Indicates the overall operating cost; Indicates real-time electricity price cost; This indicates the maintenance cost during the electrolytic cell's rolling cycle; This indicates cumulative energy consumption.

[0039] (4) Based on the cumulative energy consumption, the variable power, and the comprehensive operating cost, construct a multi-objective optimization function; the multi-objective optimization function is as follows: ; in, , , This represents the weights of the first objective, the second objective, and the third objective in a multi-objective weighting system. This represents the lowest energy consumption for hydrogen production in the efficiency zone; Indicates the rated power of the electrolytic cell; This indicates the lowest cost per unit of hydrogen production in the efficiency zone.

[0040] In step 151, based on the three scenario characteristics of wind and solar power output status, electricity price period, and equipment operating condition, following... Based on the principle of dynamically adjusting multi-objective weights according to the external power system data, when wind and solar power output is sufficient and electricity prices are low: [the following applies:] [Increase / reduce] The weighting of the parameters ensures the electrolyzer operates within its efficiency range, aiming for the lowest energy consumption per unit of hydrogen production; however, wind and solar power output fluctuates significantly, necessitating improvements. Prioritize power stability; during peak electricity price periods, wind and solar power output is low: increase... We assign weights to prioritize cost control; and update the multi-objective weights accordingly to obtain the updated multi-objective optimization function.

[0041] In step 152, the process needs to satisfy preset constraints, such as power variation ΔP ≤ M, where M is the power variation gradient constraint. Similarly, safety constraints such as input current and electrolyte temperature must also be satisfied to prevent a physically infeasible final result during the optimization process. Afterward, possible future control sequences are attempted. For each attempt, the future state of the system (power, energy consumption, cost, etc.) under that control sequence is deduced, and the function value is calculated based on the deduced state. The final value obtained is the optimal control sequence for the current moment. By implementing this value, the optimal operating range for the current moment is determined. Only the first element of the future control sequence is taken; in the next cycle, data is re-acquired, the function is updated, and the corresponding future control sequence is calculated.

[0042] In an optional embodiment of the present invention, step 16, controlling the electrolytic cell to operate within the optimal operating range, may include: Step 161: Control the electrolytic cell to operate according to the input current corresponding to the optimal operating range, thereby operating within the optimal operating range.

[0043] In this embodiment, the range of input current corresponding to the current optimal operating range can be deduced from the current optimal operating range obtained by the multi-objective function. By controlling the input current within this range, the electrolyzer is kept in the optimal operating range, thereby achieving a balance between multiple objectives such as cost and electrolyzer life.

[0044] The proposed method for optimizing the operating parameters of an electrolyzer in this invention dynamically solves and tracks the global optimal balance point between energy consumption, equipment lifespan, and operating economy. This method can move from passive, coarse-grained control to intelligent operation with forward-looking decision-making, thereby reducing hydrogen production costs and extending equipment lifespan.

[0045] like Figure 2As shown, this embodiment of the invention also provides an optimization device 20 for the operating range parameters of an electrolytic cell, comprising: The acquisition module 21 is used to acquire real-time operating status data of the electrolytic cell and external power system data; The processing module 22 is used to obtain the electrolyzer voltage and current efficiency based on the real-time operating status data; obtain the hydrogen production energy consumption based on the electrolyzer voltage and current efficiency; divide the electrolyzer into multiple operating ranges based on the hydrogen production energy consumption; perform rolling optimization of the multi-objective optimization function based on the external power system data; dynamically determine the optimal operating range of the electrolyzer among the multiple operating ranges; and control the electrolyzer to operate in the optimal operating range.

[0046] Optionally, module 21 is specifically used for: Acquire at least one of the following real-time operating status data of the electrolyzer: electrolyte temperature and input current; Obtain at least two types of external power system data from real-time electricity prices, wind power output forecasts, and photovoltaic power output forecasts.

[0047] Optionally, processing module 22 is specifically used for: The electrolytic cell voltage is obtained based on the electrolyte temperature and the input current. Based on the input current, through The current efficiency is obtained; where, Indicates current efficiency; These are the first fitted parameters; These are the second fitting parameters; For input current; This represents the effective area of ​​the electrolytic cell.

[0048] Optionally, processing module 22 is specifically used for: according to The hydrogen production rate was obtained. according to This gives the instantaneous power at the current moment; The hydrogen production energy consumption is obtained based on the hydrogen production rate and the instantaneous power. Where V represents the hydrogen production rate; Indicates current efficiency; This represents the gas volume under standard conditions (taken as 2 ÷ 89 to reduce error), with units of L / mol. The input current is z; z is the number of electrons transferred during hydrogen production via water electrolysis. The coefficient is Faraday's constant, taken as 96485 C / mol; represents the voltage of the electrolytic cell; P represents the instantaneous power.

[0049] Optionally, the process of constructing the multi-objective optimization function includes: Integrating the instantaneous power yields the cumulative energy consumption; according to The changing power is obtained; according to The overall operating cost is obtained; Based on the cumulative energy consumption, the varying power, and the comprehensive operating cost, a multi-objective optimization function is constructed; the multi-objective optimization function is... ; in, Indicates varying power; This represents the instantaneous power within the new cycle; This indicates the instantaneous power of the previous cycle; Indicates the overall operating cost; Indicates real-time electricity price cost; This indicates the maintenance cost during the electrolytic cell's rolling cycle; Indicates cumulative energy consumption; , , This represents the weights of the first objective, the second objective, and the third objective in a multi-objective weighting system. This represents the lowest energy consumption for hydrogen production in the efficiency zone; Indicates the rated power of the electrolytic cell; This indicates the lowest cost per unit of hydrogen production in the efficiency zone.

[0050] Optionally, the processing module 22 is also specifically used for: Based on the external power system data, the multi-objective weights are dynamically adjusted to obtain the updated multi-objective optimization function. Based on the updated multi-objective optimization function, the optimal operating range at the current moment is determined.

[0051] Optionally, the processing module 22 is also specifically used for: The electrolytic cell is controlled to operate according to the input current corresponding to the optimal operating range, thereby operating within the optimal operating range.

[0052] It should be noted that this device is a device corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0053] like Figure 3As shown, this embodiment of the invention also provides a computing device 30, including a processor 31, a memory 32, and a program or instructions stored in the memory 32 and executable on the processor 31. When the program or instructions are executed by the processor 31, they implement the various processes of the above-described method embodiment for optimizing the operating range parameters of the electrolytic cell, and achieve the same technical effect. To avoid repetition, they will not be described again here. It should be noted that the computing device in this embodiment of the invention includes the aforementioned mobile electronic devices and non-mobile electronic devices.

[0054] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0055] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0056] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0057] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0058] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0059] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0060] Furthermore, it should be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of the present invention. Moreover, the steps performing the above series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof. This is something that those skilled in the art can achieve by using their basic programming skills after reading the description of the present invention.

[0061] Therefore, the object of the present invention can also be achieved by running a program or a set of programs on any computing device. The computing device can be a known general-purpose device. Therefore, the object of the present invention can also be achieved simply by providing a program product containing program code for implementing the method or apparatus. That is, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any known storage medium or any storage medium developed in the future. It should also be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent to the present invention. Furthermore, the steps for performing the above series of processes can naturally be performed in the order described, but are not necessarily required to be performed in chronological order. Some steps can be performed in parallel or independently of each other.

[0062] The above are preferred embodiments of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for optimizing parameters of an electrolysis cell operating range, characterized in that, The method comprises the following steps: obtaining real-time running state data of the electrolytic cell and external power system data; obtaining electrolytic cell voltage and current efficiency according to the real-time running state data; obtaining hydrogen production energy consumption according to the electrolytic cell voltage and the current efficiency; dividing the running interval of the electrolytic cell according to the hydrogen production energy consumption to obtain a plurality of running intervals; dynamically determining the optimal running interval of the electrolytic cell in the plurality of running intervals by rolling optimization solution of the multi-objective optimization function according to the external power system data; controlling the electrolytic cell to run in the optimal running interval.

2. The method of optimizing parameters of an electrolysis cell operating range according to claim 1, characterized in that, The method comprises the following steps: obtaining at least one of the real-time running state data of the electrolytic cell, including electrolyte temperature and input current; obtaining at least two types of external power system data, including real-time electricity price, wind power output prediction value and photovoltaic output prediction value.

3. The method of optimizing parameters of an electrolysis cell operating range according to claim 2, characterized in that, obtaining electrolytic cell voltage and current efficiency according to the real-time running state data, comprising: obtaining electrolytic cell voltage according to the electrolyte temperature and input current; According to the input current, by a current efficiency is obtained; wherein, represents the current efficiency; is a first fitting parameter; is a second fitting parameter; is the input current; is the effective area of the electrolytic cell.

4. The method of optimizing operating range parameters of an electrolytic cell of claim 2, wherein, obtaining hydrogen production energy consumption according to the electrolytic cell voltage and the current efficiency, comprising: According to , the hydrogen production rate is obtained; According to , the instantaneous power at the current moment is obtained; obtaining hydrogen production energy consumption according to the hydrogen production rate and the instantaneous power; wherein V represents the hydrogen production rate; represents the current efficiency; represents the gas volume at standard conditions, taken as 2÷89 to reduce errors, in L / mol; is the input current; z is the number of electrons transferred in the production of hydrogen from water electrolysis; is the Faraday constant, taken as 96485 C / mol; represents the electrolyser voltage; P represents the instantaneous power.

5. The method of optimizing parameters of an electrolysis cell operating range according to claim 4, characterized in that, The construction process of the multi-objective optimization function comprises: integrating the instantaneous power to obtain cumulative energy consumption; According to , the varying power is obtained; According to , a comprehensive operating cost is obtained; According to the cumulative energy consumption, the change power and the comprehensive operation cost, a multi-objective optimization function is constructed; the multi-objective optimization function is ; wherein, represents the varying power; represents the instantaneous power in the new cycle; represents the instantaneous power in the previous cycle; represents the overall operating cost; represents the real-time electricity price cost; represents the maintenance cost in the rolling cycle of the electrolytic cell; represents the cumulative energy consumption; , , represents the first target weight, the second target weight, and the third target weight in the multi-target weight; represents the lowest value of the energy consumption of hydrogen production in the efficiency zone; represents the rated power of the electrolytic cell; represents the lowest cost of unit hydrogen production in the efficiency zone.

6. The method of optimizing parameters of an operating range of an electrolytic cell according to claim 1, wherein dynamically determining the optimal running interval of the electrolytic cell in the plurality of running intervals by rolling optimization solution of the multi-objective optimization function according to the external power system data, comprising: dynamically adjusting the multi-objective weight according to the external power system data to obtain an updated multi-objective optimization function; determining the optimal running interval at the current time according to the updated multi-objective optimization function.

7. The method of optimizing parameters of an operating range of an electrolytic cell according to claim 1, wherein controlling the electrolytic cell to run in the optimal running interval, comprising: controlling the electrolytic cell to run according to the input current corresponding to the optimal running interval, so as to run in the optimal running interval.

8. An apparatus for optimizing parameters of an electrolysis cell operating range, characterized by, The method comprises the following steps: an acquisition module for obtaining real-time running state data of the electrolytic cell and external power system data; a processing module for obtaining electrolytic cell voltage and current efficiency according to the real-time running state data; obtaining hydrogen production energy consumption according to the electrolytic cell voltage and the current efficiency; dividing the running interval of the electrolytic cell according to the hydrogen production energy consumption to obtain a plurality of running intervals; dynamically determining the optimal running interval of the electrolytic cell in the plurality of running intervals by rolling optimization solution of the multi-objective optimization function according to the external power system data; controlling the electrolytic cell to run in the optimal running interval.

9. A computing device, comprising: The method comprises the following steps: a processor and a memory storing a computer program, wherein the computer program is executed by the processor to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, instructions stored in a computer, when the instructions are executed on the computer, the computer executes the method according to any one of claims 1 to 7.

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