Current ripple suppression method for hydrogen production converter

Abstract

The invention discloses a current ripple suppression method for a hydrogen production converter, which belongs to the technical field of power electronics, and comprises three H-bridge modules, three filter capacitors C1, C2 and C3, three excitation inductors L1, L2 and L3 and a three-winding transformer with the voltage ratio of N1, N2 and N3, a port I is a direct current power supply module, a port II is a battery module, and a port III is an electrolytic cell module. The energy flow direction is double-end input and single-end output, based on the structure, delays t11, t13 and t33 are added to original H-bridge circuits of a first port and a third port, the optimal delay time corresponding to the minimum current peak value of the third load port is obtained by performing differential evolution algorithm optimization, then suppression of current ripples input into an electrolytic cell is achieved, and the current ripple suppression effect is improved. Current can be provided for the electrolytic cell more accurately, effectively and stably, and the practical value is good.

Description

Technical Field

[0001] The invention relates to the technical field of power electronics, and in particular to a method for suppressing current ripple of a hydrogen production converter. Background Art

[0002] The large-scale use of traditional fossil energy has supported the global energy supply system in the past, promoted the rapid development of industry and great progress of society, but it has also brought a series of serious problems. As human demand for energy continues to rise, traditional fossil energy is facing the dilemma of increasing depletion. Building a new generation of clean, low-carbon, safe and efficient energy system has become an inevitable trend in the future development of energy. Among many new energy sources, hydrogen energy, as a clean secondary energy carrier, stands out and shows unique advantages. Hydrogen energy has a wide range of sources. It can be obtained from the electrolysis process of water with abundant water resources, and can also be produced from biomass, natural gas reforming and other methods. Moreover, during the use of hydrogen energy, the product is only water, and no greenhouse gases and pollutants are produced, which realizes green environmental protection in the true sense. At the same time, hydrogen energy can also be efficiently converted into electricity and heat, providing clean power for transportation, industry, construction and other fields, and its application prospects are extremely broad.

[0003] Among the many ways to produce hydrogen, water electrolysis has attracted much attention. It can produce hydrogen without CO2 emissions and is currently a relatively feasible green hydrogen production method. The principle of water electrolysis is to use electricity to decompose water into hydrogen and oxygen. The whole process is clean and pollution-free. However, to achieve efficient water electrolysis hydrogen production, advanced equipment support is indispensable, among which the electrolyzer is one of the key components.

[0004] The electrolyzer requires the switching power supply to have the characteristics of low voltage, high current output, high voltage step-down capability, high reliability, high efficiency and low current ripple. High voltage step-down ratio is the main requirement of the electrolyzer for the converter. This is because the DC-DC converter used in the electrolyzer usually has a high input side voltage, and the rated operating voltage of the electrolyzer is low. At the same time, at the same power level, a high voltage step-down ratio is required so that the converter meets the requirements of low voltage and high current. Low current ripple is another key requirement of the electrolyzer for the converter. Current ripple affects the efficiency of hydrogen production, and larger current ripple will also cause instability in the hydrogen flow rate, affecting the safety and life of the hydrogen storage equipment. Therefore, there is an urgent need for a method that can effectively suppress current ripples in the electrolysis process to improve the efficiency and safety of hydrogen production. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a method for suppressing current ripple of a hydrogen production converter, which can effectively suppress current ripple and reduce output capacity.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: a method for suppressing current ripple of a hydrogen production converter, the hydrogen production converter used comprises three H-bridge modules, each module comprises three groups of switch tubes S1-S4, S5-S8, S9-S 12 , three filter capacitors C1, C2, C3, three excitation inductors L1, L2, L3 and a three-winding transformer with a voltage ratio of N1, N2, N3. The energy flow relationship is double-ended input and single-ended output. Port one is a DC power supply module, which is connected to a DC power supply as the energy input end of port two and port three. Port two is a battery module, which receives energy input from port one and transmits energy to port three at the same time. Port three is an electrolyzer module, which receives energy input from port one and port two and consumes energy as a load port. The specific steps of the current ripple suppression method are as follows:

[0007] Step S1: Sample the voltage of port 3 and the current at the load end, and set the delay time t of port 2. 1_2 And analyze the voltage waveform of port three;

[0008] Step S2: Based on the given time segment, the current in half a cycle is iterated to obtain the peak value of the output current I of the port 3. peak ;

[0009] Step S3: Perform differential evolution algorithm optimization, initialize parameters, and initialize population X i , looking for I peak The optimal solution and the optimal delay time t of port one 1_1 , port three and the optimal internal delay time t of port three 1_3 ,t 3_3 ;

[0010] Step S4, performing parameter adaptation strategy;

[0011] Step S5: Perform mutation and crossover to generate a test solution U i , and retain the winner;

[0012] Step S6, determine whether the G+1 generation mutation satisfies the maximum number of mutations. If not, return to step S5 to perform mutation and crossover again.

[0013] Step S7: If it is satisfied, then the optimal I is obtained. peak , i.e. the minimum current ripple and the optimal delay time t of port 1 1_1 , port three and the optimal internal delay time t of port three 1_3 ,t 3_3 .

[0014] A further improvement of the technical solution of the present invention is that: in step S2, the peak value of the output current I of the third port is peakThe calculation is as follows:

[0015] The time segment relationship after the superposition of the three voltage waveforms at the port is:

[0016] t1=t0+t 1_1

[0017] t2=t0+t 1_2

[0018] t3=t0+t 1_3

[0019] t4=t3+t 3_3

[0020] t5=0.5*T

[0021] The initial time is t0, which corresponds to the underestimation of the load current, t1 to t4 are the time points corresponding to the change of the load current waveform, and t5 is the time corresponding to the peak value of the load current;

[0022] According to the load current sampling result in step S1, the expression of the load current in each time period is analyzed:

[0023]

[0024] Among them, U1 is the input voltage of port 1, U2 is the input voltage of port 2, U3 is the voltage of the load end, L 13 , L 23 are the equivalent inductances between ports 1 and 3 and ports 2 and 3, respectively, and are calculated as follows:

[0025]

[0026] By adopting the iterative solution method and combining the above time segment relationship, the load current peak value corresponding to time t5 is obtained.

[0027]

[0028] The peak current of the load terminal corresponding to time t5 is I peak , then I peak for:

[0029]

[0030] The further improvement of the technical solution of the present invention is that the specific process of optimizing the differential evolution algorithm in step S3 is as follows:

[0031] Define an optimization problem based on differential evolution algorithm, the objective function is the peak value of the output port current I peak Minimum value, the constraints are power balance and constant output current;

[0032] objective=min I peak (t 1-1 ,t 1-3 ,t 3-3 )

[0033]

[0034] Initialize the population and randomly generate a set of control parameter vectors X i =d i1 , d i2 , d i3 , where i=1,2,…,NP, NP represents the population size.

[0035] The further improvement of the technical solution of the present invention is that: Step S4 is specifically: to obtain the optimal scaling factor F i and the crossover probability CR i , a parameter adaptation strategy is proposed. For the power balance constraint of the three-port topology, a dynamic penalty function is proposed to dynamically integrate the constraint violation degree into the objective function:

[0036] P in -P out -P loss =0

[0037] I peak_prime (α)=objective(α)+λ(t)·constraint(α) 2

[0038] Where λ(t) increases with the number of iterations t:

[0039]

[0040] Initial weight λ0 = 10 3 , the final weight λ(T max )=10 6 ,The dynamic adjustment mechanism allows constraint violations in the early stage to explore the ,global situation, and enforces constraint satisfaction in the later stage;

[0041] In the differential evolution algorithm under the adaptive strategy, each individual i in each generation has an independent F i and CR i , for individual i in the tth generation population, the scaling factor is F i , the crossover probability is CR i , NF i and NCR i is the experimental individual U i The scaling factor and crossover probability of the tth generation NF i and NCR i Modify as follows:

[0042]

[0043] Regenerate F with a probability of 10% in the objective function i , ensure that F i Distributed in [0.2, 0.4], enhancing local development capabilities; λ(t) regenerates CR with a probability of 10% i , ensure CR i Distributed in [0.8, 1.0], using modified NF i and NCR i Generate a test individual of the i-th individual in the t-th generation population, and the F of the i-th individual in the t+1-th generation population inext and CR inext The modified values ​​are as follows:

[0044]

[0045] Only when the generated trial solution is better than the original solution, update F i and CR i , retain the successful parameter combination.

[0046] A further improvement of the technical solution of the present invention is that: Step S5 is specifically: for each individual X in the population i Perform mutation operation and randomly select 3 different individuals X r1 , X r2 , X r3 Weighted generation of new individuals V i , for each individual X i and new individual V i Perform a crossover operation and generate a test solution U according to the crossover probability CR i ;

[0047] Finally, the selection operation is performed according to the greedy criterion, and individuals with high fitness are retained to the next generation. The specific relationship is as follows:

[0048]

[0049] Where i≠r1≠r2≠r3, F is the scaling factor, rand() is a uniform random number distributed in the interval [0, 1], CR is the crossover probability in the range [0, 1], randi(1, D) is a random integer distributed in the interval [1, D], fit(X i ) is X i The fitness of .

[0050] A further improvement of the technical solution of the present invention is that: Step S7 is specifically: judging whether G+1 satisfies a maximum number of iterations G max, if satisfied, then after G generations of mutation, crossover and selection operations, the final generation population X is generated G , in X G Filter out the individual X with the minimum value of the objective function best The three components in this individual are the optimal delay time t of port 1. 1_1 , port three and the optimal internal delay time t of port three 1_3 ,t 3_3 At this time, the corresponding port three current peak value I peak , that is, the load end current ripple reaches the minimum value.

[0051] Due to the adoption of the above technical solution, the technical progress achieved by the present invention is: by constructing a setting function, a delay t is added to the original H-bridge circuit of port one and port three. 1_1 ,t 1_3 ,t 3_3 , the three output current peaks of the optimal port can be clearly optimized. By performing differential evolution algorithm optimization, the optimal delay time corresponding to the minimum three current peaks of the load port can be obtained, thereby achieving the suppression of the input electrolytic cell current ripple, and providing current to the electrolytic cell more accurately, effectively and stably, with good practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] 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 some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.

[0053] Figure 1 It is a structural schematic diagram of the hydrogen production converter used in the present invention;

[0054] Figure 2 It is a schematic diagram of the process of the present invention; DETAILED DESCRIPTION

[0055] The present invention is further described in detail below in conjunction with embodiments:

[0056] like Figure 1 The structure diagram of the hydrogen production converter used is shown in FIG. 1 , which includes three H-bridge modules, each of which is composed of three groups of switch tubes S1-S4, S5-S8, and S9-S 12, the diagonal switches in each H-bridge realize coordinated control, and each group of diagonal switches realizes complementary control. It is composed of three filter capacitors C1, C2, and C3, three excitation inductors L1, L2, and L3, and a three-winding transformer with a voltage ratio of N1, N2, and N3. The energy flow relationship of the present invention is double-ended input and single-ended output. Port one is a DC power supply module, which is connected to a DC power supply as the energy input end of port two and port three. Port two is a battery module, which receives energy input from port one and transmits energy to port three at the same time. Port three is an electrolyzer module, which receives energy input from port one and port two, and consumes energy as a load port.

[0057] A method for suppressing current ripple of a hydrogen production converter is implemented by means of the above hydrogen production converter. The specific steps are as follows: Figure 2 As shown, the specific steps are as follows:

[0058] Step S1: Sample the voltage of port 3 and the current at the load end, and set the delay time t of port 2. 1_2 And analyze the voltage waveform of port three; in this embodiment, the delay time t of port two 1_2 Can be set to 12μs.

[0059] Step S2: Based on the given time segment, the current in half a cycle is iterated to obtain the peak value of the output current I of the port 3. peak ;

[0060] Port three output current peak I peak The calculation is as follows:

[0061] The time segment relationship after the superposition of the three voltage waveforms at the port is:

[0062] t1=t0+t 1_1

[0063] t2=t0+t 1_2

[0064] t3=t0+t 1_3

[0065] t4=t3+t 3_3

[0066] t5=0.5*T

[0067] The initial time is t0, which corresponds to the underestimation of the load current, t1 to t4 are the time points corresponding to the change of the load current waveform, and t5 is the time corresponding to the peak value of the load current;

[0068] According to the load current sampling result in step S1, the expression of the load current in each time period is analyzed:

[0069]

[0070] Among them, U1 is the input voltage of port 1, U2 is the input voltage of port 2, U3 is the voltage of the load end, L 13 , L 23 are the equivalent inductances between ports 1 and 3 and ports 2 and 3, respectively, and are calculated as follows:

[0071]

[0072] By adopting the iterative solution method and combining the above time segment relationship, the load current peak value corresponding to time t5 is obtained.

[0073]

[0074] The peak current of the load terminal corresponding to time t5 is I peak , then I peak for:

[0075]

[0076] Step S3: Perform differential evolution algorithm optimization, initialize parameters, and initialize population X i , looking for I peak The optimal solution and the optimal delay time t of port one 1_1 , port three and the optimal internal delay time t of port three 1_3 ,t 3_3 ;

[0077] The specific process of differential evolution algorithm optimization is as follows:

[0078] Define an optimization problem based on differential evolution algorithm, the objective function is the peak value of the output port current I peak Minimum value, the constraints are power balance and constant output current;

[0079] objective=min I peak (t 1-1 ,t 1-3 ,t 3-3 )

[0080]

[0081] Initialize the population and randomly generate a set of control parameter vectors X i =d i1 , d i2 , d i3 , where i=1,2,…,NP, NP represents the population size.

[0082] Step S4, performing parameter adaptation strategy;

[0083] To obtain the optimal scaling factor F i and the crossover probability CR i , a parameter adaptation strategy is proposed. For the power balance constraint of the three-port topology, a dynamic penalty function is proposed to dynamically integrate the constraint violation degree into the objective function:

[0084] P in -P out -P loss =0

[0085] I peak_prime (α)=objective(α)+λ(t)·constraint(α) 2

[0086] Where λ(t) increases with the number of iterations t:

[0087]

[0088] Initial weight λ0 = 10 3 , the final weight λ(T max )=10 6 ,The dynamic adjustment mechanism allows constraint violations in the early stage to explore the ,global situation, and enforces constraint satisfaction in the later stage;

[0089] In the differential evolution algorithm under the adaptive strategy, each individual i in each generation has an independent F i and CR i , for individual i in the tth generation population, the scaling factor is F i , the crossover probability is CR i , NF i and NCR i is the experimental individual U i The scaling factor and crossover probability of the tth generation NF i and NCR i Modify as follows:

[0090]

[0091] Regenerate F with a probability of 10% in the objective function i , ensure that F i Distributed in [0.2, 0.4], enhancing local development capabilities; λ(t) regenerates CR with a probability of 10% i , ensure CR i Distributed in [0.8, 1.0], using modified NF i and NCR i Generate a test individual of the i-th individual in the t-th generation population, and the F of the i-th individual in the t+1-th generation population inext and CR inext The modified values ​​are as follows:

[0092]

[0093] Only when the generated trial solution is better than the original solution, update F i and CR i , retain the successful parameter combination.

[0094] Step S5: Perform mutation and crossover to generate a test solution U i , and retain the winner;

[0095] For each individual X in the population i Perform mutation operation and randomly select 3 different individuals X r1 , X r2 , X r3 Weighted generation of new individuals V i , for each individual X i and new individual V i Perform a crossover operation and generate a test solution U according to the crossover probability CR i ;

[0096] Finally, the selection operation is performed according to the greedy criterion, and individuals with high fitness are retained to the next generation. The specific relationship is as follows:

[0097]

[0098] Where i≠r1≠r2≠r3, F is the scaling factor, rand() is a uniform random number distributed in the interval [0, 1], CR is the crossover probability in the range [0, 1], randi(1, D) is a random integer distributed in the interval [1, D], fit(X i ) is X i The fitness of .

[0099] Step S6, determine whether the G+1 generation mutation satisfies the maximum number of mutations. If not, return to step S5 to perform mutation and crossover again.

[0100] Step S7: If it is satisfied, then the optimal I is obtained. peak , i.e. the minimum current ripple and the optimal delay time t of port 1 1_1 , port three and the optimal internal delay time t of port three 1_3 ,t 3_3 Specifically: determine whether G+1 satisfies the maximum number of iterations G max , if satisfied, then after G generations of mutation, crossover and selection operations, the final generation population X is generated G , in X G Filter out the individual X with the minimum value of the objective function bestThe three components in this individual are the optimal delay time t of port 1. 1_1 , port three and the optimal internal delay time t of port three 1_3 ,t 3_3 At this time, the corresponding port three current peak value I peak , that is, the load-end current ripple reaches the minimum value, and I peak The optimal solution and the optimal delay time t of port one 1_1 , port three and the optimal internal delay time t of port three 1_3 ,t 3_3 , and then the converter topology can be set to suppress the current ripple.

[0101] The embodiments described above are merely descriptions of preferred implementation modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for suppressing current ripple of a hydrogen production converter, characterized in that: The hydrogen production converter used includes three H-bridge modules, each of which consists of three groups of switch tubes S1-S4, S5-S8, S9-S 12 , three filter capacitors C1, C2, C3, three excitation inductors L1, L2, L3 and a three-winding transformer with a voltage ratio of N1, N2, N3. The energy flow relationship is double-ended input and single-ended output. Port one is a DC power supply module, which is connected to a DC power supply as the energy input end of port two and port three. Port two is a battery module, which receives energy input from port one and transmits energy to port three at the same time. Port three is an electrolyzer module, which receives energy input from port one and port two and consumes energy as a load port. The specific steps of the current ripple suppression method are as follows: Step S1: Sample the voltage of port 3 and the current at the load end, and set the delay time t of port 2. 1_2 And analyze the voltage waveform of port three; Step S2: Based on the given time segment, the current in half a cycle is iterated to obtain the peak value of the output current I of the port 3. peak ; Step S3: Perform differential evolution algorithm optimization, initialize parameters, and initialize population X i , looking for I peak The optimal solution and the optimal delay time t of port one 1_1 , port three and the optimal internal delay time t of port three 1_3 ,t 3_3 ; Step S4, performing parameter adaptation strategy; Step S5: Perform mutation and crossover to generate a test solution U i , and retain the winner; Step S6, determine whether the G+1 generation mutation satisfies the maximum number of mutations. If not, return to step S5 to perform mutation and crossover again. Step S7: If it is satisfied, then the optimal I is obtained. peak , i.e. the minimum current ripple and the optimal delay time t of port 1 1_1 , port three and the optimal internal delay time t of port three 1_3 ,t 3_3 .

2. The method for suppressing current ripple of a hydrogen production converter according to claim 1, characterized in that: The peak value of the output current I of port 3 in step S2 is peak The calculation is as follows: The time segment relationship after the superposition of the three voltage waveforms at the port is: t1=t0+t 1_1 t2=t0+t 1_2 t3=t0+t 1_3 t4=t3+t 3_3 t5=0.5*T The initial time is t0, which corresponds to the low estimate of the load current, t1 to t4 are the time points corresponding to the change of the load current waveform, and t5 is the time corresponding to the peak value of the load current; According to the load current sampling result in step S1, the expression of the load current in each time period is analyzed: i0=-i5 Among them, U1 is the input voltage of port 1, U2 is the input voltage of port 2, U3 is the voltage of the load end, L 13 , L 23 are the equivalent inductances between ports 1 and 3 and ports 2 and 3, respectively, and are calculated as follows: By adopting the iterative solution method and combining the above time segment relationship, the load current peak value corresponding to time t5 is obtained. The peak current of the load terminal corresponding to time t5 is I peak , then I peak for:

3. The method for suppressing current ripple of a hydrogen production converter according to claim 1, characterized in that: The specific process of the differential evolution algorithm optimization in step S3 is as follows: Define an optimization problem based on differential evolution algorithm, the objective function is the peak value of the output port current I peak Minimum value, the constraints are power balance and constant output current; objective=min I peak (t 1-1 ,t 1-3 ,t 3-3 ) Initialize the population and randomly generate a set of control parameter vectors X i =d i1 , d i2 , d i3 , where i=1,2,…,NP, NP represents the population size.

4. The method for suppressing current ripple of a hydrogen production converter according to claim 1, characterized in that: Step S4 is specifically as follows: To obtain the optimal scaling factor F i and the crossover probability CR i , a parameter adaptation strategy is proposed. For the power balance constraint of the three-port topology, a dynamic penalty function is proposed to dynamically integrate the constraint violation degree into the objective function: P in -P out -P loss =0 I peak_prime (α)=objective(α)+λ(t)·constraint(α) 2 Where λ(t) increases with the number of iterations t: Initial weight λ0 = 10 3 , the final weight λ(T max )=10 6 ,The dynamic adjustment mechanism allows constraint violations in the early stage to explore the ,global situation, and enforces constraint satisfaction in the later stage; In the differential evolution algorithm under the adaptive strategy, each individual i in each generation has an independent F i and CR i , for individual i in the tth generation population, the scaling factor is F i , the crossover probability is CR i , NF i and NCR i is the experimental individual U i The scaling factor and crossover probability of the tth generation NF i and NCR i Modify as follows: Regenerate F with a probability of 10% in the objective function i , ensure that F i Distributed in [0.2, 0.4], enhancing local development capabilities; λ(t) regenerates CR with a probability of 10% i , ensure CR i Distributed in [0.8, 1.0], using modified NF i and NCR i Generate a test individual of the i-th individual in the t-th generation population, and the F of the i-th individual in the t+1-th generation population inext and CR inext The modified values ​​are as follows: Only when the generated trial solution is better than the original solution, update F i and CR i , retain the successful parameter combination.

5. The method for suppressing current ripple of a hydrogen production converter according to claim 1, characterized in that: Step S5 is as follows: for each individual X in the population i Perform mutation operation and randomly select 3 different individuals X r1 , X r2 , X r3 Weighted generation of new individuals V i , for each individual X i and new individual V i Perform a crossover operation and generate a test solution U according to the crossover probability CR i ; Finally, the selection operation is performed according to the greedy criterion, and individuals with high fitness are retained to the next generation. The specific relationship is as follows: Where i≠r1≠r2≠r3, F is the scaling factor, rand() is a uniform random number distributed in the interval [0, 1], CR is the crossover probability in the range [0, 1], randi(1, D) is a random integer distributed in the interval [1, D], fit(X i ) is X i The fitness of .

6. A method for suppressing current ripple of a hydrogen production converter according to claim 1, characterized in that: Step S7 is specifically: determine whether G+1 satisfies the maximum number of iterations G max , if satisfied, then after G generations of mutation, crossover and selection operations, the final generation population X is generated G , in X G Filter out the individual X with the minimum value of the objective function best The three components in this individual are the optimal delay time t of port 1. 1_1 , port three and the optimal internal delay time t of port three 1_3 ,t 3_3 At this time, the corresponding port three current peak value I peak , that is, the load end current ripple reaches the minimum value.

Images