A dual-channel hydrogen production system optimization control method and system for multiple power supply scenarios

Abstract

The present invention discloses a dual-channel hydrogen production system optimization control method for a multi-power scenario, comprising: constructing a dual-channel hydrogen production system and obtaining corresponding operating data; decomposing and reconstructing the operating data to obtain the initial input power of the electrolyzer; formulating start-stop rules for the electrolyzer based on the initial input power; correcting the initial input power based on the start-stop rules to obtain the actual hydrogen production power; constructing a mathematical model of the electrolyzer and obtaining the unit hydrogen production cost and energy conversion efficiency based on the actual hydrogen production power; establishing an objective function based on the unit hydrogen production cost and energy conversion efficiency; optimizing the objective function based on a multi-objective particle swarm algorithm to obtain the optimal filter reconstruction order and electrolyzer retention ratio, thereby completing the power allocation and capacity optimization configuration of the dual-channel hydrogen production system. This method achieves power division and capacity configuration for the alkaline electrolyzer and PEM electrolyzer, effectively reducing the hydrogen production cost of the wind-solar coupling system and improving the energy conversion efficiency of the electrolyzer.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrogen production system optimization, and more particularly to an optimization control method and system for a dual-channel hydrogen production system in a multi-power scenario. Background Art

[0002] Currently, facing severe environmental pollution and energy crises, vigorously developing new energy is a key measure for achieving "dual carbon" goals. The random and intermittent fluctuations in the operation of new energy sources pose significant challenges to real-time grid balancing, leading to frequent wind and solar curtailment. Harnessing wind and solar energy to produce "green hydrogen" will provide a new, clean conversion and localized consumption pathway for large-scale wind and photovoltaic projects, and can meet the vast hydrogen energy market demand of modern industry.

[0003] However, wind and solar power generation are highly random and volatile, causing the electrolyzer to be in a state of frequent start and stop and non-steady state, reducing hydrogen production efficiency and equipment service life.

[0004] Therefore, how to achieve long-term and efficient operation of the water electrolysis hydrogen production system under high fluctuation input is an urgent problem that technicians in this field need to solve. Summary of the Invention

[0005] In view of this, the present invention provides an optimization control method and system for a dual-channel hydrogen production system in a multi-power scenario, which realizes the long-term and efficient operation of the water electrolysis hydrogen production system under highly fluctuating input.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A dual-channel hydrogen production system optimization control method for multiple power supply scenarios includes:

[0008] Build a dual-channel hydrogen production system and obtain corresponding operating data;

[0009] Decomposing and reconstructing the operating data to obtain an initial input power of the electrolytic cell;

[0010] formulating a start and stop rule for the electrolytic cell based on the initial input power;

[0011] Correcting the initial input power based on the start-stop rule to obtain actual hydrogen production power;

[0012] Constructing a mathematical model of the electrolyzer and obtaining a unit hydrogen production cost and energy conversion efficiency based on the actual hydrogen production power;

[0013] Establishing an objective function based on the unit hydrogen production cost and the energy conversion efficiency;

[0014] The objective function is optimized based on a multi-objective particle swarm algorithm to obtain the optimal filter reconstruction order and electrolyzer retention ratio, thereby completing the power distribution and capacity optimal configuration of the dual-channel hydrogen production system.

[0015] Preferably, the dual-channel hydrogen production system comprises: a wind turbine, a photovoltaic unit, an alkaline electrolyzer, a PEM electrolyzer, a hydrogen storage tank, a first fuel cell, a second fuel cell and an AC / DC converter;

[0016] The operating data of the wind turbine generator set and the photovoltaic generator set are respectively obtained.

[0017] Preferably, obtaining the initial input power of the electrolyzer specifically includes:

[0018] Obtaining an original signal time series based on the operating data;

[0019] Based on the EEMD algorithm, the original time series signal is decomposed into multiple intrinsic mode functions and residual terms:

[0020]

[0021] Among them, X(t) represents the original time series signal, r n (t) represents the residual term, n represents the number of intrinsic mode functions, IMF g (t) represents the g-th eigenmode function;

[0022] A high-frequency signal and a low-frequency signal are obtained based on the intrinsic mode function and the residual term:

[0023]

[0024]

[0025] Among them, x high (t) represents the high-frequency signal, x low (t) represents the low-frequency signal, k represents the filter reconstruction order;

[0026] The initial input powers of the alkaline electrolyzer and the PEM electrolyzer are obtained based on the high-frequency signal and the low-frequency signal, respectively:

[0027]

[0028]

[0029] Among them, P alk0 (t) represents the initial input power of the alkaline electrolytic cell, P pem0 (t) represents the initial input power of the PEM electrolyzer.

[0030] Preferably, the start and stop rules of the electrolytic cell are specifically as follows:

[0031] Based on the physical and chemical properties of the electrolytic cell, the lower operating limit Y of the alkaline electrolytic cell is alk The alkaline electrolyzer is set to 20% of its rated capacity, the cold start time is 2 hours, and the operating lower limit Y of the PEM electrolyzer is pem Set to 5% of the rated capacity of the PEM electrolyzer, with a cold start time of 0.5 hours;

[0032] When P alk0 (t)≥Y alk When the alkaline electrolytic cell is in the first state, P pem0 (t)≥Y pem When , the PEM electrolyzer is in the first state;

[0033] The start and stop rules of the electrolyzer in the first state are:

[0034] If the previous moment was in normal working mode, then continue to maintain normal working mode;

[0035] If the previous moment was in shutdown mode, switch to cold start mode and maintain the corresponding cold start time;

[0036] If the previous moment was in cold start mode, the power required for cold start is preset to be provided externally, and the state is not affected by the wind or solar input power, then the cold start mode will continue;

[0037] If the cold start process is completed at the current moment and all startup preparations are completed, the machine will switch to normal working mode;

[0038] When P alk0 (t)<Y alk When the alkaline electrolytic cell is in the second state, P pem0 (t)<Y pem When , the PEM electrolyzer is in the second state;

[0039] The start and stop rules of the electrolyzer in the second state are:

[0040] If the previous moment was in normal working mode, it will switch to shutdown mode;

[0041] If the previous moment was in shutdown mode, it will continue to remain in shutdown mode;

[0042] If the previous moment was in cold start mode, then continue to maintain cold start mode;

[0043] If the cold start process is completed at the current moment, the system switches to shutdown mode.

[0044] Preferably, obtaining the actual hydrogen production power specifically includes:

[0045] Based on the start-stop rules and the switch control of the Petri net, the new state M of the system after the transition is obtained:

[0046] M=M0+A T S

[0047] Among them, M0 represents the initial state of the system, A T represents the correlation matrix, S represents the transition sequence;

[0048] Obtaining current operating modes of the alkaline electrolyzer and the PEM electrolyzer based on the new system state;

[0049] Based on the working mode and the input power, the actual hydrogen production power is obtained:

[0050] When the alkaline electrolyzer and the PEM electrolyzer are in the shutdown mode and the cold start mode, the actual hydrogen production power P' of the alkaline electrolyzer is alk and the actual hydrogen production power P' of the PEM electrolyzer pem Both are 0, no hydrogen is produced;

[0051] When the alkaline electrolyzer and the PEM electrolyzer are in normal working mode, P' alk =P alk0 , P' pem =P pem0 , both produce hydrogen.

[0052] Preferably, the electrolytic cell mathematical model includes:

[0053] Alkaline electrolyzer mathematical model:

[0054]

[0055] Among them, P alk Indicates the hydrogen production power of alkaline electrolyzer, U alk Indicates the working voltage of the alkaline electrolytic cell, I alk Indicates the working current of the alkaline electrolytic cell, N1 indicates the number of alkaline electrolytic cells connected in series, U ref Represents the reversible voltage, U act Indicates activation overvoltage, U ohm represents the ohmic overvoltage, s1, s3 and s3 represent the electrode overvoltage coefficient, t1, t2 and t3 represent the electrolyte overvoltage coefficient, r1 and r2 represent the ohmic resistance of the alkaline electrolytic cell, T el Indicates the working temperature of the alkaline electrolytic cell; A1 indicates the effective electrolysis area of ​​the alkaline electrolytic cell;

[0056] PEM electrolyzer mathematical model:

[0057] P pem =Upem I pem

[0058]

[0059] Among them, P pem Indicates the hydrogen production power of PEM electrolyzer, U pem Indicates the operating voltage of the PEM electrolyzer, I pem represents the working current of the PEM electrolyzer, N2 represents the number of PEM electrolyzers connected in series, U ocv represents the open circuit voltage, represents the hydrogen partial pressure, represents the oxygen partial pressure, represents the water activity between the electrode and the membrane, R represents the gas constant, i represents the working current density of the PEM electrolyzer, i an and i cat denote the anodic and cathodic exchange current densities, α an and α cat are the anode and cathode charge transfer coefficients, arcsinh is the inverse hyperbolic sine function, A2 is the effective electrolysis area of ​​the PEM electrolyzer, δ is the thickness of the PEM membrane, σ is the resistivity of the PEM membrane, and F is the Faraday constant.

[0060] Preferably, the unit hydrogen production cost and energy conversion efficiency are obtained, specifically including:

[0061] Based on P' alk and P' pem The alkaline electrolytic cell mathematical model and the PEM electrolytic cell mathematical model are respectively introduced to obtain the actual working current I' of the alkaline electrolytic cell. alk and the actual operating current I' of the PEM electrolyzer pem ;

[0062] Based on I' alk and I' pem The hydrogen production rate n of the alkaline electrolyzer is obtained respectively alk and the hydrogen production rate n of the PEM electrolyzer pem :

[0063]

[0064]

[0065] Among them, η f1 represents the Faraday efficiency of the alkaline electrolyzer, z represents the number of electrons transferred during the electrolysis of water, and η f2 represents the Faradaic efficiency of the PEM electrolyzer;

[0066] Based on n alk and npem Get the hydrogen mass in the hydrogen storage tank based on The unit hydrogen production cost C of the dual-channel hydrogen production system is obtained H2 :

[0067]

[0068] Among them, C a and C p are the unit purchase and civil construction installation costs of alkaline electrolyzer and PEM electrolyzer, respectively. alk and E pem Represents the rated capacity of alkaline electrolyzer and PEM electrolyzer, C w represents the cost of raw water consumed to produce unit mass of hydrogen, γ represents the capacity retention ratio of the PEM electrolyzer, b represents the depreciation period or the entire life cycle of the system, V el represents the annual maintenance cost and labor cost, C pv and C wp Represent the purchase and installation costs of photovoltaic units and wind turbines per unit capacity, E pv and E wp Represent the installed capacity of photovoltaic units and wind turbine units respectively;

[0069] Based on n alk and n pem The energy conversion efficiency η is obtained:

[0070]

[0071] Where ΔG represents the Gibbs free energy, P pv (t) and P wp (t) represents the instantaneous output power of the photovoltaic unit and the wind turbine unit respectively, and t represents the working time period of the hydrogen production system.

[0072] Preferably, establishing the objective function specifically includes:

[0073] Based on the energy conversion efficiency η, the maximum objective function of wind power and photovoltaic energy conversion efficiency is established:

[0074] minf1=1-η;

[0075] And based on the unit hydrogen production cost C H2 Establish the objective function of minimizing the unit hydrogen production cost:

[0076]

[0077] The constraints are:

[0078] Electrolyzer capacity constraints:

[0079] Among them, E alk Indicates the rated capacity of the alkaline electrolytic cell, E pem Indicates the rated capacity of the PEM electrolyzer;

[0080] Power balance constraint: 0≤P alk '+P pem '≤P pv (t)+P wp (t)+P fc (t)

[0081] Among them, P pv (t) represents the power generation power of the photovoltaic system, P wp (t) represents the power generation of the wind turbine; P fc (t) represents the load power of the fuel cell.

[0082] Preferably, completing the power distribution and capacity optimal configuration of the dual-channel hydrogen production system specifically includes:

[0083] The filter reconstruction order k and the PEM electrolyzer capacity retention ratio γ are used as decision variables, and the multi-objective particle swarm optimization algorithm is used to optimize the objective function to obtain a non-inferior solution set.

[0084] The TOPSIS method is used to comprehensively evaluate the non-inferior solution set to determine the optimal filter reconstruction order and the optimal PEM electrolyzer capacity retention ratio;

[0085] Based on the optimal filter reconstruction order, the optimal input power of the alkaline electrolyzer and PEM electrolyzer is obtained respectively, realizing the power allocation of the dual-channel hydrogen production system;

[0086] Based on the optimal PEM electrolyzer capacity retention ratio, the optimal capacity of the PEM electrolyzer and the optimal capacity of the alkaline electrolyzer are obtained, and the optimal configuration of the electrolyzer capacity of the dual-channel hydrogen production system is achieved.

[0087] An optimization control system for a dual-channel hydrogen production system in a multi-power scenario, comprising: a data acquisition module, a power acquisition module, a rule formulation module, a correction module, a calculation module, an objective function establishment module, and an optimization configuration module;

[0088] The data acquisition module is used to construct a dual-channel hydrogen production system and obtain corresponding operating data;

[0089] The power acquisition module is configured to obtain the initial input power of the electrolyzer by decomposing and reconstructing the operating data;

[0090] The rule-making module is configured to make a start-stop rule for the electrolyzer based on the initial input power;

[0091] The correction module is used to correct the initial input power based on the start-stop rule to obtain the actual hydrogen production power;

[0092] The calculation module is used to construct a mathematical model of the electrolyzer and obtain a unit hydrogen production cost and energy conversion efficiency based on the actual hydrogen production power;

[0093] The objective function establishment module is used to establish an objective function based on the unit hydrogen production cost and the energy conversion efficiency;

[0094] The optimization configuration module is used to optimize the objective function based on a multi-objective particle swarm algorithm to obtain the optimal filter reconstruction order and electrolyzer retention ratio, thereby completing the power distribution and capacity optimal configuration of the dual-channel hydrogen production system.

[0095] As can be seen from the above technical solutions, compared with the prior art, the present invention provides a dual-channel hydrogen production system optimization control method and system for multiple power supply scenarios, achieving long-term and efficient operation of the water electrolysis hydrogen production system under highly fluctuating inputs. This invention fully utilizes the differences in the adaptability of different hydrogen production equipment to fluctuating inputs to achieve power division and capacity configuration between alkaline electrolyzers and PEM electrolyzers, effectively reducing the hydrogen production cost of wind-solar coupled systems and improving the energy conversion efficiency of electrolyzers, providing a scientific basis and feasible solution for the efficient and flexible operation of renewable energy hydrogen production systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0097] Figure 1 This is a flow chart of an optimization control method for a dual-channel hydrogen production system in a multi-power scenario provided by the present invention.

[0098] Figure 2 This is a structural schematic diagram of the dual-channel hydrogen production system provided by the present invention.

[0099] Figure 3 The present invention provides a flow chart of the electrolytic cell switch control based on Petri net.

[0100] Figure 4 This is a schematic diagram of the structure of an optimized control system for a dual-channel hydrogen production system in a multi-power scenario provided by the present invention. DETAILED DESCRIPTION

[0101] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0102] Example 1

[0103] like Figure 1 As shown, an embodiment of the present invention discloses an optimization control method for a dual-channel hydrogen production system in a multi-power scenario, including:

[0104] Build a dual-channel hydrogen production system and obtain corresponding operating data;

[0105] The initial input power of the electrolyzer is obtained by decomposing and reconstructing the operating data;

[0106] Formulate start and stop rules for the electrolyzer based on the initial input power;

[0107] Based on the start-stop rules, the initial input power is corrected to obtain the actual hydrogen production power;

[0108] Construct a mathematical model of the electrolyzer and derive the unit hydrogen production cost and energy conversion efficiency based on the actual hydrogen production power;

[0109] Establish an objective function based on unit hydrogen production cost and energy conversion efficiency;

[0110] The objective function is optimized based on the multi-objective particle swarm algorithm to obtain the optimal filter reconstruction order and electrolyzer retention ratio, and complete the power distribution and capacity optimal configuration of the dual-channel hydrogen production system.

[0111] Example 2

[0112] The embodiment of the present invention discloses an optimization control method for a dual-channel hydrogen production system in a multi-power scenario, comprising:

[0113] Build a dual-channel hydrogen production system and obtain corresponding operating data:

[0114] Preferably, Figure 2 As shown, the dual-channel hydrogen production system includes: a wind turbine, a photovoltaic unit, an alkaline electrolyzer, a PEM electrolyzer (proton exchange membrane electrolyzer), a hydrogen storage tank, a first fuel cell, a second fuel cell and an AC / DC converter;

[0115] The wind turbines and photovoltaic units are connected to the AC / DC converter;

[0116] The AC / DC converters are connected to the alkaline electrolyzer and the PEM electrolyzer respectively;

[0117] Both the alkaline electrolyzer and the PEM electrolyzer are connected to the hydrogen storage tank;

[0118] The first fuel cell is connected to the alkaline electrolyzer and the hydrogen storage tank respectively;

[0119] The second fuel cell is connected to the PEM electrolyzer and the hydrogen storage tank respectively;

[0120] Obtain the operating data of wind turbines and photovoltaic units respectively.

[0121] The initial input power of the electrolyzer is obtained by decomposition and reconstruction based on the operating data:

[0122] Preferably, obtaining the initial input power of the electrolyzer specifically includes:

[0123] Obtaining the original wind power output power and the original photovoltaic output power based on the operating data;

[0124] The original signal time series is obtained based on the original wind power output power and the original photovoltaic output power;

[0125] Based on the EEMD algorithm, the original time series signal is decomposed into multiple intrinsic mode functions and residual terms:

[0126]

[0127] Among them, X(t) represents the original time series signal, r n (t) represents the residual term, n represents the number of intrinsic mode functions, IMF g (t) represents the g-th intrinsic mode function; each order IMF can reflect the mode of the original signal at a corresponding characteristic scale parameter;

[0128] Based on the intrinsic mode function and the residual term, high-frequency and low-frequency signals are obtained:

[0129]

[0130]

[0131] Among them, x high (t) represents the high-frequency signal, x low (t) represents the low-frequency signal, k represents the filter reconstruction order;

[0132] The initial input power of the alkaline electrolyzer and PEM electrolyzer is obtained based on the high-frequency signal and low-frequency signal respectively:

[0133]

[0134]

[0135] Among them, P alk0(t) represents the initial input power of the alkaline electrolytic cell, P pem0 (t) represents the initial input power of the PEM electrolyzer.

[0136] Preferably, IMF1~IMF k As a high-frequency signal, the PEM electrolyzer and the second fuel cell bear the positive power and negative power parts respectively; k+1 ~IMF n and the residual term r n (t) As a low-frequency signal, the alkaline electrolyzer and the first fuel cell bear the positive power and negative power parts respectively.

[0137] Formulate start and stop rules for the electrolyzer based on the initial input power:

[0138] Preferably, the start and stop rules of the electrolytic cell are specifically as follows:

[0139] Based on the physical and chemical properties of the electrolytic cell, the lower operating limit Y of the alkaline electrolytic cell is alk Set to 20% of the rated capacity of the alkaline electrolyzer, the cold start time is 2 hours, and the operating lower limit Y of the PEM electrolyzer pem Set to 5% of the rated capacity of the PEM electrolyzer, with a cold start time of 0.5 hours;

[0140] The working modes of the electrolyzer include: normal working mode, shutdown mode and cold start mode;

[0141] When P alk0 (t)≥Y alk When the alkaline electrolytic cell is in the first state, P pem0 (t)≥Y pem When , the PEM electrolyzer is in the first state;

[0142] The start and stop rules of the electrolyzer in the first state are:

[0143] If the previous moment was in normal working mode, then continue to maintain normal working mode;

[0144] If the previous moment was in shutdown mode, switch to cold start mode and maintain the corresponding cold start time;

[0145] If the previous moment was in cold start mode, the power required for cold start is preset to be provided externally, and the state is not affected by the wind or solar input power, then the cold start mode will continue;

[0146] If the cold start process is completed at the current moment and all startup preparations are completed, the machine will switch to normal working mode;

[0147] When P alk0 (t)<Y alk When the alkaline electrolytic cell is in the second state, Ppem0 (t)<Y pem When , the PEM electrolyzer is in the second state;

[0148] The start and stop rules of the electrolyzer in the second state are:

[0149] If the previous moment was in normal working mode, it will switch to shutdown mode;

[0150] If the previous moment was in shutdown mode, it will continue to remain in shutdown mode;

[0151] If the previous moment was in cold start mode, then continue to maintain cold start mode;

[0152] If the cold start process is completed at the current moment, the system switches to shutdown mode.

[0153] Based on the start-stop rules, the initial input power is corrected to obtain the actual hydrogen production power:

[0154] The actual hydrogen production power is obtained, including:

[0155] Preferably, based on the start-stop rules and the switch control of the Petri net, the new state M of the system after the transition is obtained:

[0156] M=M0+A T S

[0157]

[0158] Among them, M0 represents the initial state of the system, A T represents the correlation matrix, S represents the transition sequence;

[0159] Based on the new state of the system, the current working mode of the alkaline electrolyzer and the PEM electrolyzer is obtained;

[0160] Based on the working mode and input power, the actual hydrogen production power is obtained:

[0161] When the alkaline electrolyzer and PEM electrolyzer are in shutdown mode and cold start mode, the actual hydrogen production power P' of the alkaline electrolyzer is alk and the actual hydrogen production power P' of the PEM electrolyzer pem are all 0, that is, P' alk =0, P' pem =0, both electrolyzers do not produce hydrogen;

[0162] When the alkaline electrolyzer and PEM electrolyzer are in normal working mode, P' alk =P alk0 , P' pem =P pem0 , both electrolyzers produce hydrogen.

[0163] Preferably, the Petri net consists of a four-tuple (P, T, C, M0), where P (place) represents a place; T (Transition) represents a transition; places and transitions are connected by directed arcs C (Connection), and when there is no number mark on the directed arc, the default arc weight is 1; the small black dots in the place (Token) represent the number of resources in the place, and the vector M0 composed of the number of tokens in all places is called the initial identifier, which represents the initial state of the system.

[0164] Preferably, the electrolyzer switch control based on Petri net is as follows Figure 3 As shown in the figure, places are used to represent events, transitions are used to represent "If...Then" rules, and the causal relationship between events and rules is represented by directed arcs. If the event is true, the token is marked in the place.

[0165] The place set is set to P = [P1, P2, ..., P7], where P1 - input power P alk0 ≥20% E alk ,P pem0 ≥20% E pem , in line with safety requirements; P2-input power P alk0 <20%E alk ,P pem0 <20%E pem , which does not meet the safety requirements; P3-P5 represent the shutdown mode, normal working mode and cold start mode respectively; P6 represents the counting library; P7 represents the cold start completion mark, indicating that it can be put into use.

[0166] The transition ignition condition is defined as: if the transition T i All input places of a transition contain at least one token. When the weight of a directed arc is not 1, the connected input places are required to contain tokens of the corresponding weight. This is called transition enablement. After a transition is triggered, a token is removed from all input places of the transition and a token is added to all output places of the transition. When the weight of a directed arc is not 1, tokens of the corresponding weight are removed or added from the connected places.

[0167] After a round of Petri net switch control, the initial mark M0 can be transformed into M=M0+A T S calculation, where M represents the new state of the system after the change occurs; A T is an association matrix, whose rows are related to places and columns are related to transitions. Each column represents the modification of the number of tokens in each place when the transition in the column occurs. S is the transition sequence, which represents the number and position of the ignition transitions. If the transition T i Occurrence, component S in the sequence i is 1.

[0168] Based on the initial input power of the electrolytic cell in the initial identifier M0 and the electrolytic cell's operating mode at the previous moment, the current operating mode of the electrolytic cell can be obtained from the identifier M through switch control of the Petri net. Ultimately, a solution for selecting the electrolytic cell's operating mode for the entire time period can be obtained.

[0169] A mathematical model of the electrolyzer was constructed, and the unit hydrogen production cost and energy conversion efficiency were obtained based on the actual hydrogen production power:

[0170] Preferably, the electrolytic cell mathematical model includes:

[0171] Alkaline electrolyzer mathematical model:

[0172] P alk =U alk I alk

[0173]

[0174] Among them, P alk Indicates the hydrogen production power of alkaline electrolyzer, U alk Indicates the working voltage of the alkaline electrolytic cell, I alk Indicates the working current of the alkaline electrolytic cell, N1 indicates the number of alkaline electrolytic cells connected in series, U ref Represents the reversible voltage, U act Indicates activation overvoltage, U ohm represents the ohmic overvoltage, s1, s3 and s3 represent the electrode overvoltage coefficient, t1, t2 and t3 represent the electrolyte overvoltage coefficient, r1 and r2 represent the ohmic resistance of the alkaline electrolytic cell, T el Indicates the working temperature of the alkaline electrolytic cell; A1 indicates the effective electrolysis area of ​​the alkaline electrolytic cell;

[0175] PEM electrolyzer mathematical model:

[0176] P pem =U pem I pem

[0177]

[0178] Among them, P pem Indicates the hydrogen production power of PEM electrolyzer, U pem Indicates the operating voltage of the PEM electrolyzer, I pem represents the working current of the PEM electrolyzer, N2 represents the number of PEM electrolyzers connected in series, U ocv represents the open circuit voltage, represents the hydrogen partial pressure, represents the oxygen partial pressure, represents the water activity between the electrode and the membrane, R represents the gas constant, i represents the working current density of the PEM electrolyzer, i an and i cat denote the anodic and cathodic exchange current densities, α an and α cat are the anode and cathode charge transfer coefficients, arcsinh is the inverse hyperbolic sine function, A2 is the effective electrolysis area of ​​the PEM electrolyzer, δ is the thickness of the PEM membrane, σ is the resistivity of the PEM membrane, and F is the Faraday constant.

[0179] Preferably, the unit hydrogen production cost and energy conversion efficiency are obtained, specifically including:

[0180] Based on P' alk and P' pem Substitute the mathematical model of alkaline electrolyzer and PEM electrolyzer into the mathematical model respectively, and the actual working current I' of the alkaline electrolyzer is obtained. alk and the actual operating current I' of the PEM electrolyzer pem ;

[0181] Based on I' alk and I' pem The hydrogen production rate n of the alkaline electrolyzer is obtained respectively alk and the hydrogen production rate n of the PEM electrolyzer pem :

[0182]

[0183]

[0184]

[0185]

[0186] Among them, η f1 represents the Faraday efficiency of the alkaline electrolyzer, z represents the number of electrons transferred during the electrolysis of water, and η f2 represents the Faradaic efficiency of the PEM electrolyzer;

[0187] Based on n alk and n pem Get the hydrogen mass in the hydrogen storage tank based on The unit hydrogen production cost C of the dual-channel hydrogen production system is obtained H2 :

[0188]

[0189] Among them, C a and C pare the unit purchase and civil construction installation costs of alkaline electrolyzer and PEM electrolyzer (yuan / W), E alk and E pem Represent the rated capacity (MW) of alkaline electrolyzer and PEM electrolyzer, C w represents the cost of raw water consumed to produce unit mass of hydrogen (yuan / kg), γ represents the capacity retention ratio of the PEM electrolyzer, b represents the depreciation period or the entire life cycle of the system (years), V el represents the annual maintenance cost and labor cost (10,000 yuan / year), C pv and C wp are the purchase and installation costs of photovoltaic units and wind turbines per unit capacity (yuan / W), E pv and E wp represent the installed capacity (MW) of photovoltaic units and wind turbines respectively;

[0190] Based on n alk and n pem The energy conversion efficiency η is obtained:

[0191]

[0192] Where ΔG represents the Gibbs free energy, P pv (t) and P wp (t) represents the instantaneous output power of the photovoltaic unit and the wind turbine unit respectively, and t represents the working time period of the hydrogen production system.

[0193] The objective function is established based on the unit hydrogen production cost and energy conversion efficiency:

[0194] Preferably, establishing the objective function specifically includes:

[0195] Based on the energy conversion efficiency η, the maximum objective function of wind power and photovoltaic energy conversion efficiency is established:

[0196]

[0197] And based on the unit hydrogen production cost C H2 Establish the objective function of minimizing the unit hydrogen production cost:

[0198]

[0199] The constraints are:

[0200] Electrolyzer capacity constraints:

[0201] Among them, E alk Indicates the rated capacity of the alkaline electrolytic cell, E pemIndicates the rated capacity of the PEM electrolyzer. The PEM electrolyzer can operate at up to 120% of its rated capacity, maximizing the utilization rate of hydrogen production from renewable energy.

[0202] Power balance constraint: the total power of the two types of electrolyzers and fuel cell stack loads at any time should be lower than the wind and solar power generation power: 0≤P alk '+P pem '≤P pv (t)+P wp (t)+P fc (t)

[0203] Among them, P pv (t) represents the power generation power of the photovoltaic system, P wp (t) represents the power generation of the wind turbine; P fc (t) represents the load power of the fuel cell.

[0204] The objective function is optimized based on the multi-objective particle swarm algorithm to obtain the optimal filter reconstruction order and electrolyzer retention ratio, and complete the power distribution and capacity optimal configuration of the dual-channel hydrogen production system.

[0205] Preferably, the power distribution and capacity optimal configuration of the dual-channel hydrogen production system are completed, specifically including:

[0206] The filter reconstruction order k and the PEM electrolyzer capacity retention ratio γ are used as decision variables, and the multi-objective particle swarm optimization algorithm is used to optimize the objective function to obtain a non-inferior solution set.

[0207] The TOPSIS method is used to comprehensively evaluate the non-inferior solution set to determine the optimal filter reconstruction order and the optimal PEM electrolyzer capacity retention ratio;

[0208] Based on the optimal filter reconstruction order, the optimal input power of the alkaline electrolyzer and PEM electrolyzer is obtained respectively, realizing the power allocation of the dual-channel hydrogen production system;

[0209] Based on the optimal PEM electrolyzer capacity retention ratio, the optimal capacity of the PEM electrolyzer and the optimal capacity of the alkaline electrolyzer are obtained, and the optimal configuration of the electrolyzer capacity of the dual-channel hydrogen production system is achieved.

[0210] Preferably, the PEM electrolyzer capacity retention ratio γ is defined as follows:

[0211]

[0212] That is, according to the PEM electrolyzer capacity retention ratio γ, the initial input power P pem0 The peak power exceeding this ratio is discarded to obtain a new initial input power P pem0 .

[0213] Preferably, the objective function is optimized using a multi-objective particle swarm algorithm, and the specific process is as follows:

[0214] S1 input basic parameters: maximum number of iterations It max , population size n pop , archive set threshold n rep , inertia weight w, learning factors c1 and c2. Using the filter reconstruction order k and the PEM electrolyzer capacity retention ratio γ as decision variables, the particle velocity and position are initialized, and the initial archive set Rep (non-dominated solution set) is calculated;

[0215] S2 initializes the adaptive grid;

[0216] S3 uses an adaptive grid method to update the population's historical optimal position, gbest. Individuals in the initial archive set, Rep, are divided into different grids based on their fitness values. The grid density is calculated; the smaller the grid density, the greater the probability that an individual will be selected. A grid is selected using a roulette wheel. The individuals in the selected grid serve as the candidate set for the population's historical optimal position, gbest. One individual is randomly selected from the candidate set as the global optimal position.

[0217] Based on the global optimal position, S4 updates the speed and position of all particles and calculates the particle fitness value, that is, the objective function value: wind and solar energy loss rate f1 and unit hydrogen production cost f2;

[0218] S5 updates the individual's historical optimal position pbest based on the dominance relationship. If the new individual is superior to pbest only in some objective function values ​​(they do not dominate each other), it is updated randomly according to a certain probability.

[0219] To prevent the algorithm from falling into a local optimum, S6 calculates the perturbation operator based on the current number of iterations and the mutation rate, and performs a mutation operation on the particle. If the particle is better after mutation, the particle is updated. If the updated particle is better than pbest, pbest is also updated at the same time.

[0220] S7 performs non-dominated sorting on all individuals in the entire population, selects non-dominated solutions and adds them to the initial archive set Rep. If the archive set threshold is exceeded, the adaptive grid method is also used to filter and delete them until the threshold limit is reached, and the grid is re-divided;

[0221] S8 determines whether the maximum number of iterations has been reached. If so, the archive set is output as the non-inferior solution set. Otherwise, go to S3.

[0222] S9 comprehensively evaluates the obtained non-inferior solution set based on the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) to determine the only optimal solution, that is, the only optimal filter reconstruction order k and the optimal PEM electrolyzer capacity retention ratio γ.

[0223] Preferably, a comprehensive evaluation of the obtained non-inferior solution set is performed based on the TOPSIS method, specifically including:

[0224] Forwarding the original solution matrix: uniformly transforming the actual multi-objective problem matrix into a very large indicator matrix;

[0225] Forward matrix normalization: convert all original objective function values ​​in the matrix into dimensionless normalized values;

[0226] Calculate the score: define the maximum and minimum values, calculate the distance between each non-inferior solution and the maximum and minimum values, and normalize the evaluation scores;

[0227] Count the comprehensive evaluation scores of all non-inferior solutions and determine the only optimal solution by sorting.

[0228] Example 3

[0229] like Figure 4 As shown, an optimization control system for a dual-channel hydrogen production system in a multi-power scenario includes: a data acquisition module, a power acquisition module, a rule formulation module, a correction module, a calculation module, an objective function establishment module and an optimization configuration module;

[0230] Data acquisition module, used to build a dual-channel hydrogen production system and obtain corresponding operating data;

[0231] A power acquisition module is used to decompose and reconstruct the operating data to obtain the initial input power of the electrolyzer;

[0232] A rule-making module for formulating start-stop rules for the electrolyzer based on the initial input power;

[0233] A correction module is used to correct the initial input power based on the start-stop rules to obtain the actual hydrogen production power;

[0234] A calculation module is used to build a mathematical model of the electrolyzer and obtain the unit hydrogen production cost and energy conversion efficiency based on the actual hydrogen production power;

[0235] An objective function establishment module is used to establish an objective function based on unit hydrogen production cost and energy conversion efficiency;

[0236] The optimization configuration module is used to optimize the objective function based on the multi-objective particle swarm algorithm to obtain the optimal filter reconstruction order and electrolyzer retention ratio, and complete the power distribution and capacity optimal configuration of the dual-channel hydrogen production system.

[0237] Those skilled in the art will appreciate that the modules described above can be distributed in the device according to the description of the embodiment, or can be modified accordingly to be used in one or more devices that are different from the embodiment. The modules of the above embodiment can be combined into one module or further divided into multiple submodules.

[0238] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software, or by combining software with necessary hardware.

[0239] Therefore, according to a fourth embodiment of the present invention, the present invention provides a computer-readable medium. The technical solution according to the embodiments of the present invention can be embodied in the form of a software product, which can be stored on a non-volatile storage medium (such as a CD-ROM, USB flash drive, or mobile hard drive) or on a network and includes instructions for causing a computing device (such as a personal computer, server, or network device) to execute the above-described method according to the embodiments of the present invention.

[0240] The software product can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0241] Computer-readable storage media may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0242] As can be seen from the above technical solutions, the present invention provides a dual-channel hydrogen production system optimization control method and system for multiple power supply scenarios, achieving long-term and efficient operation of the water electrolysis hydrogen production system under highly fluctuating inputs. This invention fully utilizes the differences in the adaptability of different hydrogen production equipment to fluctuating inputs to achieve power division and capacity configuration between alkaline electrolyzers and PEM electrolyzers, effectively reducing the hydrogen production cost of wind-solar coupled systems and improving the energy conversion efficiency of electrolyzers, providing a scientific basis and feasible solution for the efficient and flexible operation of renewable energy hydrogen production systems.

[0243] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0244] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A dual-channel hydrogen production system optimization control method for a multi-power scenario, characterized in that: include: Build a dual-channel hydrogen production system and obtain corresponding operating data; Decomposing and reconstructing the operating data to obtain an initial input power of the electrolytic cell; Obtain the initial input power of the electrolytic cell, specifically including: Obtaining an original signal time series based on the operating data; Based on the EEMD algorithm, the original signal time series is decomposed into multiple intrinsic mode functions and residual terms: Among them, X(t) represents the original signal time series, r n (t) represents the residual term, n represents the number of intrinsic mode functions, IMF g (t) represents the g-th eigenmode function; Obtaining a high-frequency signal and a low-frequency signal based on the intrinsic mode function and the residual term; Obtaining initial input powers of the alkaline electrolyzer and the PEM electrolyzer respectively based on the high-frequency signal and the low-frequency signal; formulating a start and stop rule for the electrolytic cell based on the initial input power; Correcting the initial input power based on the start-stop rule to obtain actual hydrogen production power; The actual hydrogen production power is obtained, including: Based on the start-stop rules and the switch control of the Petri net, the new state M of the system after the transition is obtained: M=M0+A T S Among them, M0 represents the initial state of the system, A T represents the correlation matrix, S represents the transition sequence; Obtaining a current operating mode of the alkaline electrolyzer and the PEM electrolyzer based on the new state of the system; Based on the working mode and the input power, an actual hydrogen production power is obtained; Constructing a mathematical model of the electrolyzer and obtaining a unit hydrogen production cost and energy conversion efficiency based on the actual hydrogen production power; Establishing an objective function based on the unit hydrogen production cost and the energy conversion efficiency; The objective function is optimized based on a multi-objective particle swarm algorithm to obtain the optimal filter reconstruction order and electrolyzer retention ratio, thereby completing the power allocation and capacity optimal configuration of the dual-channel hydrogen production system; Complete the power distribution and capacity optimization configuration of the dual-channel hydrogen production system, specifically including: The filter reconstruction order k and the PEM electrolyzer capacity retention ratio γ are used as decision variables, and the multi-objective particle swarm optimization algorithm is used to optimize the objective function to obtain a non-inferior solution set. The TOPSIS method is used to comprehensively evaluate the non-inferior solution set to determine the optimal filter reconstruction order and the optimal PEM electrolyzer capacity retention ratio; Based on the optimal filter reconstruction order, the optimal input power of the alkaline electrolyzer and PEM electrolyzer is obtained respectively, realizing the power allocation of the dual-channel hydrogen production system; Based on the optimal PEM electrolyzer capacity retention ratio, the optimal capacity of the PEM electrolyzer and the optimal capacity of the alkaline electrolyzer are obtained, achieving the optimal configuration of the electrolyzer capacity of the dual-channel hydrogen production system; According to the capacity retention ratio of the PEM electrolyzer, the peak power portion of the initial input power that exceeds the ratio is discarded to obtain a new initial input power.

2. The optimization control method for a dual-channel hydrogen production system in a multi-power scenario according to claim 1 is characterized in that: The dual-channel hydrogen production system includes: a wind turbine, a photovoltaic unit, an alkaline electrolyzer, a PEM electrolyzer, a hydrogen storage tank, a first fuel cell, a second fuel cell and an AC / DC converter; The operating data of the wind turbine generator set and the photovoltaic generator set are respectively obtained.

3. The optimization control method for a dual-channel hydrogen production system in a multi-power scenario according to claim 2 is characterized in that: A high-frequency signal and a low-frequency signal are obtained based on the intrinsic mode function and the residual term: Among them, x high (t) represents the high-frequency signal, x low (t) represents the low-frequency signal, k represents the filter reconstruction order; The initial input powers of the alkaline electrolyzer and the PEM electrolyzer are obtained based on the high-frequency signal and the low-frequency signal, respectively: Among them, P alk0 (t) represents the initial input power of the alkaline electrolytic cell, P pem0 (t) represents the initial input power of the PEM electrolyzer.

4. The optimization control method for a dual-channel hydrogen production system in a multi-power scenario according to claim 3 is characterized in that: The start and stop rules of the electrolytic cell are specifically as follows: Based on the physical and chemical properties of the electrolytic cell, the lower operating limit Y of the alkaline electrolytic cell is alk The alkaline electrolyzer is set to 20% of its rated capacity, the cold start time is 2 hours, and the operating lower limit Y of the PEM electrolyzer is pem Set to 5% of the rated capacity of the PEM electrolyzer, with a cold start time of 0.5 hours; When P alk0 (t)≥Y alk When the alkaline electrolytic cell is in the first state, P pem0 (t)≥Y pem When , the PEM electrolyzer is in the first state; The start and stop rules of the electrolyzer in the first state are: If the previous moment was in normal working mode, then continue to maintain normal working mode; If the previous moment was in shutdown mode, switch to cold start mode and maintain the corresponding cold start time; If the previous moment was in cold start mode, the power required for cold start is preset to be provided externally, and the state is not affected by the wind or solar input power, then the cold start mode will continue; If the cold start process is completed at the current moment and all startup preparations are completed, the machine will switch to normal working mode; When P alk0 (t)<Y alk When the alkaline electrolytic cell is in the second state, P pem0 (t)<Y pem When , the PEM electrolyzer is in the second state; The start and stop rules of the electrolyzer in the second state are: If the previous moment was in normal working mode, it will switch to shutdown mode; If the previous moment was in shutdown mode, it will continue to remain in shutdown mode; If the previous moment was in cold start mode, then continue to maintain cold start mode; If the cold start process is completed at the current moment, the system switches to shutdown mode.

5. The optimization control method for a dual-channel hydrogen production system in a multi-power scenario according to claim 4 is characterized in that: Based on the working mode and the input power, the actual hydrogen production power is obtained: When the alkaline electrolyzer and the PEM electrolyzer are in the shutdown mode and the cold start mode, the actual hydrogen production power P' of the alkaline electrolyzer is alk and the actual hydrogen production power P' of the PEM electrolyzer pem Both are 0, no hydrogen is produced; When the alkaline electrolyzer and the PEM electrolyzer are in normal working mode, P' alk =P alk0 , P' pem =P pem0 , both produce hydrogen.

6. The optimization control method for a dual-channel hydrogen production system in a multi-power scenario according to claim 5 is characterized in that: The electrolytic cell mathematical model includes: Alkaline electrolyzer mathematical model: P alk =U alk AND alk Among them, P alk Indicates the hydrogen production power of alkaline electrolyzer, U alk Indicates the working voltage of the alkaline electrolytic cell, I alk Indicates the working current of the alkaline electrolytic cell, N1 indicates the number of alkaline electrolytic cells connected in series, U ref Represents the reversible voltage, U act Indicates activation overvoltage, U ohm represents the ohmic overvoltage, s1, s3 and s3 represent the electrode overvoltage coefficient, t1, t2 and t3 represent the electrolyte overvoltage coefficient, r1 and r2 represent the ohmic resistance of the alkaline electrolytic cell, T el Indicates the working temperature of the alkaline electrolytic cell; A1 indicates the effective electrolysis area of ​​the alkaline electrolytic cell; PEM electrolyzer mathematical model: P pem =U pem AND pem Among them, P pem Indicates the hydrogen production power of PEM electrolyzer, U pem Indicates the operating voltage of the PEM electrolyzer, I pem represents the working current of the PEM electrolyzer, N2 represents the number of PEM electrolyzers connected in series, U ocv represents the open circuit voltage, represents the hydrogen partial pressure, represents the oxygen partial pressure, represents the water activity between the electrode and the membrane, R represents the gas constant, i represents the working current density of the PEM electrolyzer, i an and i cat denote the anodic and cathodic exchange current densities, α an and α cat are the anode and cathode charge transfer coefficients, arcsinh is the inverse hyperbolic sine function, A2 is the effective electrolysis area of ​​the PEM electrolyzer, δ is the thickness of the PEM membrane, σ is the resistivity of the PEM membrane, and F is the Faraday constant.

7. The optimization control method for a dual-channel hydrogen production system in a multi-power scenario according to claim 6 is characterized in that: The unit hydrogen production cost and energy conversion efficiency are obtained, including: Based on P' alk and P' pem The alkaline electrolytic cell mathematical model and the PEM electrolytic cell mathematical model are respectively introduced to obtain the actual working current I' of the alkaline electrolytic cell. alk and the actual operating current I' of the PEM electrolyzer pem ; Based on I' alk and I' pem The hydrogen production rate n of the alkaline electrolyzer is obtained respectively alk and the hydrogen production rate n of the PEM electrolyzer pem : Among them, η f1 represents the Faraday efficiency of the alkaline electrolyzer, z represents the number of electrons transferred during the electrolysis of water, and η f2 represents the Faradaic efficiency of the PEM electrolyzer; Based on η alk and n pem Get the hydrogen mass in the hydrogen storage tank based on The unit hydrogen production cost C of the dual-channel hydrogen production system is obtained H2 : Among them, C a and C p are the unit purchase and civil construction installation costs of alkaline electrolyzer and PEM electrolyzer, respectively. alk and E pem Represents the rated capacity of alkaline electrolyzer and PEM electrolyzer, C w represents the cost of raw water consumed to produce unit mass of hydrogen, γ represents the capacity retention ratio of the PEM electrolyzer, b represents the depreciation period or the entire life cycle of the system, V el represents the annual maintenance cost and labor cost, C pv and C wp Represent the purchase and installation costs of photovoltaic units and wind turbines per unit capacity, E pv and E wp Represent the installed capacity of photovoltaic units and wind turbine units respectively; Based on n alk and n pem The energy conversion efficiency η is obtained: Where ΔG represents the Gibbs free energy, P pv (t) and P wp (t) represents the instantaneous output power of the photovoltaic unit and the wind turbine unit respectively, and t represents the working time period of the hydrogen production system.

8. The optimization control method for a dual-channel hydrogen production system in a multi-power scenario according to claim 7 is characterized in that: Establishing the objective function specifically includes: Based on the energy conversion efficiency η, the maximum objective function of wind power and photovoltaic energy conversion efficiency is established: minf1=1-η; And based on the unit hydrogen production cost C H2 Establish the objective function of minimizing the unit hydrogen production cost: The constraints are: Electrolyzer capacity constraints: Among them, E alk Indicates the rated capacity of the alkaline electrolytic cell, E pem Indicates the rated capacity of the PEM electrolyzer; Power balance constraint: 0≤P' alk +P' pem ≤P pv (t)+P wp (t)+P fc (t) Among them, P pv (t) represents the power generation power of the photovoltaic system, P wp (t) represents the power generation of the wind turbine; P fc (t) represents the load power of the fuel cell.

9. An optimization control system for a dual-channel hydrogen production system in a multi-power scenario, characterized in that: A dual-channel hydrogen production system optimization control method for a multi-power scenario based on any one of claims 1-8, comprising: a data acquisition module, a power acquisition module, a rule formulation module, a correction module, a calculation module, an objective function establishment module, and an optimization configuration module; The data acquisition module is used to construct a dual-channel hydrogen production system and obtain corresponding operating data; The power acquisition module is configured to obtain the initial input power of the electrolyzer by decomposing and reconstructing the operating data; The rule-making module is configured to make a start-stop rule for the electrolyzer based on the initial input power; The correction module is used to correct the initial input power based on the start-stop rule to obtain the actual hydrogen production power; The calculation module is used to construct a mathematical model of the electrolyzer and obtain a unit hydrogen production cost and energy conversion efficiency based on the actual hydrogen production power; The objective function establishment module is used to establish an objective function based on the unit hydrogen production cost and the energy conversion efficiency; The optimization configuration module is used to optimize the objective function based on a multi-objective particle swarm algorithm to obtain the optimal filter reconstruction order and electrolyzer retention ratio, thereby completing the power distribution and capacity optimal configuration of the dual-channel hydrogen production system.

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