Optimization control method and system for double-channel hydrogen production system in multi-power-supply scene

Abstract

The invention discloses a double-channel hydrogen production system optimization control method for a multi-power-supply scene, and the method comprises the steps: constructing a double-channel hydrogen production system, and obtaining corresponding operation data; decomposing and reconstructing based on the operation data to obtain the initial input power of the electrolytic cell; formulating a start-stop rule of the electrolytic cell based on the initial input power; correcting the initial input power based on a start-stop rule to obtain actual hydrogen production power; an electrolytic cell mathematical model is constructed, and the unit hydrogen production cost and the energy conversion efficiency are obtained based on the actual hydrogen production power; establishing a target function based on the unit hydrogen production cost and the energy conversion efficiency; and optimizing the target function based on a multi-target particle swarm algorithm to obtain an optimal filtering reconstruction order and an electrolytic cell retention ratio, and completing power distribution and optimal capacity configuration of the double-channel hydrogen production system. Power division and capacity configuration of the alkaline electrolytic bath and the PEM electrolytic bath are achieved, the hydrogen production cost of the wind-solar coupled system is effectively reduced, and the energy conversion efficiency of the electrolytic bath is improved.

Description

Technical Field

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

[0002] At present, facing the severe environmental pollution and energy crisis, vigorously developing new energy is an important measure to achieve "dual carbon". Due to the random and intermittent fluctuations of new energy, the real-time balance of the power grid has brought great challenges, and the phenomenon of wind and solar power abandonment occurs from time to time. Using wind and solar energy to produce "green hydrogen" will provide a new clean conversion and local consumption method for the development of large-scale wind power and photovoltaic projects, and can meet the huge hydrogen energy market demand of modern industry.

[0003] However, wind and solar power generation have great randomness and volatility, which will cause the electrolyzer to be in a frequent start and stop and non-steady state, reducing the hydrogen production efficiency and the service life of the equipment.

[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 high fluctuation input.

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

[0007] An optimization control method for a dual-channel hydrogen production system in a multi-power scenario, comprising:

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

[0009] Decomposing and reconstructing the operation data to obtain an initial input power of the electrolyzer;

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

[0011] The initial input power is corrected 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 an 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 allocation 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 operation 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 electrolyzer, 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:

[0031] Based on the physical and chemical properties of the electrolytic cell, the lower limit of operation 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 lower limit of the operation of the PEM electrolyzer is Y 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 the normal working mode;

[0035] If the last 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 and light 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, it will switch to the 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, switch to shutdown mode;

[0041] If the last moment was in shutdown mode, then continue to maintain shutdown mode;

[0042] If the last 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, it switches to the 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 the current operating modes of the alkaline electrolyzer and the PEM electrolyzer based on the new state of the system;

[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 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 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 comprises:

[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 electrolyzer, I alk represents the working current of the alkaline electrolytic cell, N1 represents the number of alkaline electrolytic cells connected in series, U ref 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, is 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 operating current density of the PEM electrolyzer, i an and i cat are the anodic and cathodic exchange current densities, α an and α cat denote the anode and cathode charge transfer coefficients respectively, arcsinh denotes the inverse hyperbolic sine function, A2 denotes the effective electrolysis area of ​​the PEM electrolyzer, δ denotes the thickness of the PEM membrane; σ denotes the resistivity of the PEM membrane, and F denotes 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 electrolyzer mathematical model and the PEM electrolyzer mathematical model are respectively introduced to obtain the actual working current I' of the alkaline electrolyzer. alk and the actual working 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 of the PEM electrolyzer n 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 It 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 Represent the unit purchase and civil construction installation costs of alkaline electrolyzer and PEM electrolyzer, E alk and E pem Represent 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 Respectively represent the purchase and installation costs of photovoltaic units and wind turbines per unit capacity, E pv and E wp Respectively represent the installed capacity of photovoltaic units and wind turbine units;

[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 minimum objective function of 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 electrolyzer, 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 unit, 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 allocation 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 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 the PEM electrolyzer is obtained respectively, and the power allocation of the dual-channel hydrogen production system is realized;

[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, thereby achieving the optimal configuration of the electrolyzer capacity of the dual-channel hydrogen production system.

[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 operation data;

[0089] The power acquisition module is used to decompose and reconstruct the operation data to obtain the initial input power of the electrolyzer;

[0090] The rule-making module is used 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, and complete the power allocation and capacity optimal configuration of the dual-channel hydrogen production system.

[0095] It can be seen from the above technical solutions that, 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, which realizes the long-term and efficient operation of the water electrolysis hydrogen production system under high fluctuation input. The present invention makes full use of the differences in the adaptability of different hydrogen production equipment to fluctuating inputs, realizes the power division and capacity configuration of alkaline electrolyzers and PEM electrolyzers, effectively reduces the hydrogen production cost of wind-solar coupling systems, improves the energy conversion efficiency of electrolyzers, and provides a scientific basis and feasible solutions 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 drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0097] Figure 1 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 schematic structural diagram of the dual-channel hydrogen production system provided by the present invention.

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

[0100] Figure 4 A schematic diagram of the structure of an optimization 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 be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[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] The initial input power is corrected based on the start-stop rule to obtain the actual hydrogen production power;

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

[0109] Establishing 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 allocation 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, including:

[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 turbine and photovoltaic units are connected to the AC / DC converter;

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

[0117] Both the alkaline electrolyzer and the PEM electrolyzer are connected to a 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] The operating data of wind turbines and photovoltaic units are obtained 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 operation 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 gth 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, the high-frequency signal and the low-frequency signal 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 the low-frequency signal respectively:

[0133]

[0134]

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

[0136] Preferably, IMF1 to IMF k As a high-frequency signal, the PEM electrolyzer and the second fuel cell bear the positive power and negative power parts respectively; IMF 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 electrolyzer, the lower limit of operation Y of the alkaline electrolyzer 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 the normal working mode;

[0144] If the last 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 and light 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, it will switch to the 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, switch to shutdown mode;

[0150] If the last moment was in shutdown mode, then continue to maintain shutdown mode;

[0151] If the last 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, it switches to the shutdown mode.

[0153] Based on the start-stop rule, 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 is composed 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 digital mark on the directed arc, the default arc weight is 1; the small black dot Token in the place represents 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 input places connected to it are required to contain tokens of corresponding weights, which is called transition enablement. After the transition is ignited, a token is removed from all input places of the transition, and a token is added to all outputs of the transition. When the weight of a directed arc is not 1, the tokens of corresponding weights are removed or added from the places connected to it.

[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 transition 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 corresponding to the column occurs. S is the transition sequence, which represents the number and position of the ignition transitions. If the transition T i Occurs, component S in the sequence i is 1.

[0168] According to the size of the initial input power of the electrolytic cell in the initial identifier M0 and the working mode of the electrolytic cell at the previous moment, the working mode of the electrolytic cell at the current moment can be obtained from the identifier M through the switch control of the Petri net. Finally, the electrolytic cell working mode selection scheme for the full 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 comprises:

[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 electrolyzer, I alk represents the working current of the alkaline electrolytic cell, N1 represents 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, is 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 operating current density of the PEM electrolyzer, i an and i cat are the anodic and cathodic exchange current densities, α an and α cat denote the anode and cathode charge transfer coefficients respectively, arcsinh denotes the inverse hyperbolic sine function, A2 denotes the effective electrolysis area of ​​the PEM electrolyzer, δ denotes the thickness of the PEM membrane; σ denotes the resistivity of the PEM membrane, and F denotes 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 the mathematical model of PEM electrolyzer into the actual working current I' of alkaline electrolyzer. alk and the actual working 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 of the PEM electrolyzer n 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 It represents the Faradaic efficiency of the PEM electrolyzer;

[0187] Based on n alk and n pem Get the mass of hydrogen 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 prepresents the unit purchase and civil construction installation cost of alkaline electrolyzer and PEM electrolyzer respectively (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 Respectively represent 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 of photovoltaic units and wind turbine units (MW), 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 minimum objective function of 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 electrolyzer, E pemIndicates the rated capacity of the PEM electrolyzer. The PEM electrolyzer can operate at up to 120% over the 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 group loads should be lower than the wind and solar power generation power at any time: 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 unit, 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 allocation 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 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 the PEM electrolyzer is obtained respectively, and the power allocation of the dual-channel hydrogen production system is realized;

[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, thereby achieving the optimal configuration of the electrolyzer capacity of the dual-channel hydrogen production system.

[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. Taking the filter reconstruction order k and the PEM electrolyzer capacity retention ratio γ as decision variables, the particle speed 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 the adaptive grid method to update the population's historical optimal position gbest. The individuals in the initial archive set Rep are divided into different grids according to their fitness values; the grid density is calculated, and the smaller the grid density, the greater the probability that the individual will be selected. A grid is selected in a roulette manner, and the individuals in the selected grid are used 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] S4 updates the speed and position of all particles based on the global optimal position, 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 ​​(not dominating each other), it is updated randomly with a certain probability.

[0219] In order to avoid the algorithm from falling into the local optimum, S6 calculates the perturbation operator according to the current number of iterations and the mutation rate, and performs mutation operations on the particles. If the mutated particles are better, the particles are updated. If the updated particles are better than pbest, pbest is also updated.

[0220] S7 sorts all individuals in the entire population by non-dominance, 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 a 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 set matrix: uniformly transform 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 score;

[0227] The comprehensive evaluation scores of all non-inferior solutions are counted, and the only optimal solution is determined 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 operation data;

[0231] A power acquisition module, used for decomposing and reconstructing the operation data to obtain the initial input power of the electrolyzer;

[0232] A rule making module, used to make start and stop rules of the electrolyzer based on the initial input power;

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

[0234] A calculation module is used to construct 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, 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, obtain the optimal filter reconstruction order and electrolyzer retention ratio, and complete the power allocation and capacity optimal configuration of the dual-channel hydrogen production system.

[0237] Those skilled in the art will appreciate that the above modules can be distributed in the device according to the description of the embodiment, or can be changed accordingly and only used in one or more devices different from the embodiment. The modules of the above embodiments can be combined into one module, or further divided into multiple sub-modules.

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

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

[0240] The software product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, a system, device or device 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 data signals propagated in baseband or as part of a carrier wave, wherein readable program codes are carried. Such propagated data signals may take various 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, device, or device. The program codes contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0242] Through the above technical solutions, it can be seen that the present invention provides a dual-channel hydrogen production system optimization control method and system for multiple power supply scenarios, which realizes the long-term and efficient operation of the water electrolysis hydrogen production system under high fluctuation input. The present invention makes full use of the differences in the adaptability of different hydrogen production equipment to fluctuating inputs, realizes the power division and capacity configuration of alkaline electrolyzers and PEM electrolyzers, effectively reduces the hydrogen production cost of wind-solar coupling systems, improves the energy conversion efficiency of electrolyzers, and provides a scientific basis and feasible solutions for the efficient and flexible operation of renewable energy hydrogen production systems.

[0243] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0244] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be 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 will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An optimization control method for a dual-channel hydrogen production system in a multi-power scenario, characterized in that: include: Build a dual-channel hydrogen production system and obtain corresponding operating data; Decomposing and reconstructing the operation data to obtain an initial input power of the electrolyzer; Formulate a start and stop rule for the electrolytic cell based on the initial input power; The initial input power is corrected based on the start-stop rule to obtain actual hydrogen production power; Constructing a mathematical model of the electrolyzer, and obtaining a unit hydrogen production cost and an 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.

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 operation 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: The initial input power of the electrolyzer is obtained, specifically including: Obtaining an original signal time series based on the operating data; Based on the EEMD algorithm, the original time series signal is decomposed into multiple intrinsic mode functions and residual terms: 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; 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 electrolyzer, 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 electrolyzer are specifically as follows: Based on the physical and chemical properties of the electrolytic cell, the lower limit of operation 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 lower limit of the operation of the PEM electrolyzer is Y 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 the normal working mode; If the last 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 and light 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, it will switch to the 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, switch to shutdown mode; If the last moment was in shutdown mode, then continue to maintain shutdown mode; If the last moment was in cold start mode, then continue to maintain cold start mode; If the cold start process is completed at the current moment, it switches to the 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: 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 the current operating modes 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, the actual hydrogen production power is obtained: When the alkaline electrolyzer and the 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 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 electrolyzer, I alk represents the working current of the alkaline electrolytic cell, N1 represents the number of alkaline electrolytic cells connected in series, U ref 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, is 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 operating current density of the PEM electrolyzer, i an and i cat are the anodic and cathodic exchange current densities, α an and α cat denote the anode and cathode charge transfer coefficients respectively, arcsinh denotes the inverse hyperbolic sine function, A2 denotes the effective electrolysis area of ​​the PEM electrolyzer, δ denotes the thickness of the PEM membrane; σ denotes the resistivity of the PEM membrane, and F denotes 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 electrolyzer mathematical model and the PEM electrolyzer mathematical model are respectively introduced to obtain the actual working current I' of the alkaline electrolyzer. alk and the actual working 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 of the PEM electrolyzer n 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 It represents the Faradaic efficiency of the PEM electrolyzer; Based on n alk and n pem Get the mass of hydrogen 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 Represent the unit purchase and civil construction installation costs of alkaline electrolyzer and PEM electrolyzer, E alk and E pem Represent 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 Respectively represent the purchase and installation costs of photovoltaic units and wind turbines per unit capacity, E pv and E wp Respectively represent the installed capacity of photovoltaic units and wind turbine units; 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 minimum objective function of unit hydrogen production cost: The constraints are: Electrolyzer capacity constraints: Among them, E alk Indicates the rated capacity of the alkaline electrolyzer, 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 of the photovoltaic unit, P wp (t) represents the power generation of the wind turbine; P fc (t) represents the load power of the fuel cell.

9. The optimization control method for a dual-channel hydrogen production system in a multi-power scenario according to claim 8 is characterized in that: The power allocation and capacity optimal configuration of the dual-channel hydrogen production system are completed, 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 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 the PEM electrolyzer is obtained respectively, and the power allocation of the dual-channel hydrogen production system is realized; 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, thereby achieving the optimal configuration of the electrolyzer capacity of the dual-channel hydrogen production system.

10. 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 1-9, 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 operation data; The power acquisition module is used to decompose and reconstruct the operation data to obtain the initial input power of the electrolyzer; The rule-making module is used 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, and complete the power allocation and capacity optimal configuration of the dual-channel hydrogen production system.

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