Wind power hydrogen production system based on multiple electrolysis technologies and power distribution constant volume method

Abstract

The invention discloses a wind power hydrogen production system based on multiple electrolysis technologies and a power distribution constant volume method, and belongs to the technical field of hydrogen energy production and utilization, the system comprises a wind power generation module, a wind power distribution module and an electrolysis hydrogen production module, the wind power distribution module decomposes wind power into grid-connected electric power and hydrogen production electric power meeting the power grid fluctuation standard; the electrolytic hydrogen production module comprises an AEL electrolytic cell and a PEMEL electrolytic cell, and cooperative operation is achieved through the electrolytic cell power distribution strategy module. The method comprises the following steps: decomposing wind power into a low-frequency component meeting a grid-connected standard and a high-frequency component for hydrogen production by adopting self-adaptive wavelet packet decomposition; dynamically distributing power to AEL and PEMEL based on an electrolytic cell capacity comparison mechanism; and with the annual unit hydrogen production cost and the energy loss efficiency as objective functions, the capacity configuration of the electrolytic cell is optimized through a multi-objective particle swarm algorithm. According to the scheme, the system hydrogen production cost can be reduced, the energy efficiency is improved, the annual hydrogen production amount is increased, the system load fluctuation rate is greatly reduced, and the service life of equipment is effectively prolonged.

Description

Technical Field

[0001] This invention belongs to the field of hydrogen energy production and utilization technology, and in particular relates to a wind power hydrogen production system based on multiple electrolysis technologies and a power distribution and stabilization method. Background Technology

[0002] In recent years, the installed capacity of new energy sources, with wind power as an important component, has been continuously increasing. However, the randomness and volatility of wind power output pose significant challenges to the safe and stable operation of the power system and the quality of power supply. How to effectively mitigate wind power grid connection fluctuations and improve wind power absorption has become an urgent problem to be solved. The development and application of hydrogen energy storage technology provides technical support for this. Utilizing wind power to electrolyze water to produce hydrogen not only improves the output characteristics of wind power but also solves problems such as high hydrogen production costs. It can convert fluctuating electricity into high-quality hydrogen energy, thereby improving the reliability and economy of renewable energy utilization. Currently, the main water electrolysis equipment includes alkaline electrolyzers (AEL) and proton exchange membrane electrolyzers (PEMEL). AEL has lower cost and mature technology, but its response speed is lower and the current density of the electrolyzer is lower, resulting in poor compatibility with fluctuating power sources. PEMEL has a faster response speed and good start-stop characteristics, showing superior matching characteristics when using fluctuating power sources for hydrogen production, but its higher cost limits its large-scale application in the field of wind power hydrogen production.

[0003] Furthermore, wind power generation is characterized by randomness and volatility, making its output power difficult to predict in real time. Direct grid connection can lead to voltage and frequency fluctuations, negatively impacting grid stability and power quality. Existing research primarily focuses on off-grid wind-to-hydrogen systems, directly using wind power output as the power source for hydrogen storage. This not only results in wind curtailment but also affects the lifespan of the electrolysis unit. Against this backdrop, developing a wind-to-hydrogen system based on the synergistic application of multiple electrolysis technologies has become an urgent technological need. Summary of the Invention

[0004] To overcome the above-mentioned technical defects, the present invention provides a wind power hydrogen production system based on multiple electrolysis technologies and a wind power hydrogen production power allocation and calibration method based on multiple electrolysis technologies, so as to solve at least one technical problem existing in the above-mentioned background technology.

[0005] A wind-powered hydrogen production system based on multiple electrolysis technologies includes a public grid module, a wind power generation module, and an electrolysis hydrogen production module. The wind power generation module includes a wind turbine generator set that converts wind energy into electrical energy. The wind power generation module is electrically connected to a wind power distribution module. The wind power distribution module decomposes electrical energy into grid-connected power less than a preset active power variation limit and hydrogen production power greater than or equal to the preset active power variation limit. The wind power distribution module transmits the grid-connected power to the public grid module and the hydrogen production power to the electrolysis hydrogen production module. The electrolysis hydrogen production module includes an electrolyzer power distribution strategy module and an electrolyzer module. The electrolyzer module includes AEL and PEMEL electrolyzers. The electrolyzer power distribution strategy module is electrically connected to the AEL and PEMEL electrolyzers respectively. The electrolyzer power distribution strategy module is used to realize the joint operation of the AEL and PEMEL electrolyzers. The hydrogen produced by the AEL and PEMEL electrolyzers is stored through a hydrogen storage facility module.

[0006] Furthermore, the hydrogen storage module supplies hydrogen to the hydrogen consumption module and the fuel cell module respectively. Users can directly use hydrogen through the hydrogen consumption module, while the fuel cell module is used to convert hydrogen into electrical energy and transmit it to the public power grid module.

[0007] A method for allocating and controlling the capacity of wind power hydrogen production based on multiple electrolysis technologies includes the following steps, which are performed sequentially.

[0008] Step 1: Set a preset active power variation limit and use adaptive wavelet packet decomposition to decompose the power output of the wind turbine generator into low-frequency components that are less than the preset active power variation limit and high-frequency components that are greater than or equal to the preset active power variation limit.

[0009] Step 2: The high-frequency components are distributed to the AEL and PEMEL electrolytic cells via the electrolytic cell power distribution strategy module. The distribution strategy of the electrolytic cell power distribution strategy module is as follows: compare the capacity E of AEL. AEL PEMEL's capacity E PEMEL and the power P input to the electrolytic cell e Size, P e ≥E AEL >E PEMEL AEL then operates at maximum capacity, while PEMEL consumes the remaining power input to the electrolyzer; P e ≥E PEMEL >E AEL PEMEL then operates at maximum capacity, while AEL consumes the remaining power input to the electrolyzer; E AEL ≤P e <E PEMEL The power input to the electrolyzer in equal capacity to AEL is then allocated to PEMEL, and AEL consumes the remaining power input to the electrolyzer; P e<E PEMEL <E AEL or P e <E PEMEL <E AEL Power is then allocated based on the proportion of capacity occupied by AEL and PEMEL.

[0010] Step 3: Construct the annual unit comprehensive hydrogen production cost based on the wind power hydrogen production system With system annual energy loss efficiency η loss The objective function for capacity optimization configuration is the capacity E of the hybrid electrolyzer. AEL and E PEMEL Let P be the decision variable, and let 0 ≤ P be the constraint. AEL +P PEMEL ≤P e ;

[0011] Step 4: Solve the objective function described in Step 3 using a multi-objective particle swarm optimization algorithm to obtain the electrolyzer capacity E. AEL and E PEMEL .

[0012] Furthermore, before setting the active power variation limit in step one, the system first inputs the installed capacity of the wind turbine generator set, then inputs the limiting relationship between the installed wind power capacity of the wind turbine generator set's location and the active power variation limit, and outputs the preset active power variation limit.

[0013] Furthermore, the adaptive wavelet packet decomposition method in step one includes: S represents the original signal, which can be decomposed into low-frequency components S n,0 and high frequency component S n,i (i = 1…2) n -1), where i is the initial number of decomposition layers, and the frequency range f0 of each component is expressed as equation (13):

[0014]

[0015] In the formula: n is the wavelet packet decomposition level; f s The initial sampling frequency of the signal;

[0016] The basic decomposition algorithm of wavelet packet decomposition is specifically expressed as equation (14):

[0017]

[0018] In the formula: and These represent the low-frequency and high-frequency subbands obtained from the decomposition, respectively, where l is the position index of the subband in the sequence; a n-2l and b n-2l Represents the wavelet packet decomposition coefficients; j and i are wavelet packet nodes; n represents the wavelet packet decomposition level;

[0019] The wavelet packet reconstruction algorithm is given by equation (15):

[0020]

[0021] In the formula: The coefficients corresponding to node i in the (j+1)th layer after reconstruction are given. These are the target coefficients to be reconstructed, where l is their position index in the sequence; h l-2n and g l-2n represents the wavelet packet decomposition coefficients; j and i are wavelet packet nodes; n represents the wavelet packet decomposition level.

[0022] Furthermore, the steps of the adaptive wavelet packet decomposition method in step one include: first, if the original wind power is less than the preset active power variation limit, then the original wind power is directly connected to the grid; otherwise, proceed to the next step.

[0023] Secondly, the wind power signal is decomposed into n (n=1) layers of wavelet packets based on the db6 fundamental wavelet;

[0024] Next, the decomposed layer wavelet coefficients are reconstructed to obtain low-frequency and high-frequency components;

[0025] Finally, if the low-frequency component after n-level decomposition is less than the preset active power variation limit, the decomposition terminates; otherwise, proceed to the second step and continue with n+1-level decomposition until the low-frequency component is less than the preset active power variation limit, obtaining a wavelet packet decomposition level of value n, then terminating the loop. The grid-connected power P0 after decomposition and reconstruction is the low-frequency component S. n,0 The input power P of a wind power hydrogen production system based on the synergy of multiple electrolysis technologies e The sum of the high-frequency components is given by equations (17) and (18):

[0026] P0 = S n,0 (17)

[0028] P e =∑S n,i i = 1, 2, ..., 2 n-1 (18)

[0030] In the formula: S n,i Let be the high-frequency components after decomposition and reconstruction, where n is the number of wavelet packet decomposition layers and i is the number of wavelet packet nodes.

[0031] Furthermore, the power allocation method in step two, which allocates power based on the capacity ratio of AEL and PEMEL, is given by equations (19) and (20):

[0032] P AEL =Pe E AEL / (E AEL +E PEMEL ) (19)

[0034] P PEMEL =P e E PEMEL / (E AEL +E PEMEL ) (20)

[0036] In the formula: P e For input power, P AEL To allocate the electrolysis hydrogen production power to AEL, P PEMEL To allocate the electrolysis hydrogen production power to PEMEL, E AEL For the capacity of AEL, E PEMEL This refers to the capacity of the PEMEL.

[0037] Furthermore, the objective function of step three is the annual unit comprehensive hydrogen production cost. The construction method is as shown in equation (21):

[0038]

[0039] In the formula: C inv For investment costs, C op S represents the annual revenue from hydrogen production, where S is the operating and maintenance cost. This refers to the annual hydrogen production capacity.

[0040] Furthermore, the objective function of step three is the system's annual energy loss efficiency η. loss The construction method is as shown in equation (25):

[0041]

[0042] In the formula η sys For the energy efficiency of the electrolyzer, η AEL η PEMEL t represents the electrolysis hydrogen production efficiency of AEL and PEMEL, respectively, and t represents the operating time of the hydrogen production system.

[0043] Furthermore, the objective function constraint in step three also includes equation (28):

[0044]

[0045] In the formula: P AEL,rate and P PEMEL,rate The rated power of AEL and PEMEL are respectively, P w,max This is the upper limit of the power generation capacity of wind turbine units.

[0046] This invention utilizes adaptive wavelet packet decomposition technology to decompose wind power into low-frequency components that meet grid connection standards and high-frequency components for hydrogen production. It employs a collaborative operation mechanism between an alkaline electrolyzer (AEL) and a proton exchange membrane electrolyzer (PEMEL): the dynamically responsive PEMEL absorbs fluctuating power, while the low-cost AEL handles stable power. Through multi-objective optimization, this scheme reduces system hydrogen production costs, improves energy efficiency, increases annual hydrogen production, significantly reduces system load volatility, and effectively extends equipment lifespan. Attached Figure Description

[0047] Figure 1 This invention provides a framework for a wind power hydrogen production system based on the synergy of multiple electrolysis technologies.

[0048] Figure 2 This is a schematic diagram of the principle of adaptive wavelet packet decomposition.

[0049] Figure 3 This is a schematic diagram of a wind power allocation strategy based on adaptive wavelet packet decomposition.

[0050] Figure 4 This is a schematic diagram illustrating the characteristic analysis of the AEL and PEMEL hydrogen production systems.

[0051] Figure 5 Flowchart of power allocation strategy for hybrid electrolyzers.

[0052] Figure 6 This is a map showing the measured wind speed data for the wind farm location throughout the year.

[0053] Figure 7 This is a dynamic characteristic diagram of wind power output during typical periods throughout the year at the location of the wind farm.

[0054] Figure 8 (a) is a schematic diagram of the AEL cold start process.

[0055] Figure 8 (b) is a schematic diagram of the PEMEL cold start process.

[0056] Figure 9 (a) is a schematic diagram of the original wind power and the grid-connected power during a typical period in January.

[0057] Figure 9 (b) is a schematic diagram of the original wind power and the grid-connected power during a typical period in July.

[0058] Figure 10 (a) is a schematic diagram of the power output of the wind-to-hydrogen system based on multiple electrolysis technologies during a typical period in January.

[0059] Figure 10(b) is a schematic diagram of the power output of the wind-to-hydrogen system based on multiple electrolysis technologies during a typical period in July, which is used to smooth grid-connected power.

[0060] Figure 11 Schematic diagram of the characteristics of different types of electrolyzer hydrogen production systems.

[0061] Figure 12 (a) is a schematic diagram of AEL volatility in a wind power hydrogen production system based on the synergy of multiple electrolysis technologies.

[0062] Figure 12 (b) is a schematic diagram of PEMEL volatility in a wind power hydrogen production system based on the synergy of multiple electrolysis technologies.

[0063] Figure 13 (a) is a schematic diagram of the AEL hydrogen production efficiency in a wind power hydrogen production system based on the synergy of multiple electrolysis technologies.

[0064] Figure 13 (b) is a schematic diagram of the PEMEL hydrogen production efficiency in a wind power hydrogen production system based on the synergy of multiple electrolysis technologies. Detailed Implementation

[0065] To better understand the purpose, system, and function of this invention, the following description is provided in conjunction with the appendix. Figure 1-13 The embodiments further illustrate the wind power hydrogen production system and power distribution and calibration method based on various electrolysis technologies of the present invention.

[0066] like Figure 1 As shown, the wind power hydrogen production system based on multiple electrolysis technologies includes a public grid module, a wind power generation module, and an electrolysis hydrogen production module. The wind power generation module includes a wind turbine generator set that realizes the conversion of wind energy into electrical energy. The wind power generation module is electrically connected to a wind power distribution module. The wind power distribution module decomposes electrical energy into grid-connected power and hydrogen production power that meet the grid fluctuation standards. The wind power distribution module is electrically connected to both the public grid module and the electrolysis hydrogen production module. The wind power distribution module transmits grid-connected power to the public grid module and hydrogen production power to the electrolysis hydrogen production module.

[0067] The electrolysis hydrogen production module includes an electrolyzer power allocation strategy module and an electrolyzer module. The electrolyzer power allocation strategy module is electrically connected to the electrolyzer module. The electrolyzer module includes an AEL (Alkaline Electrolyzer) and a PEMEL (Proton Exchange Membrane Electrolyzer). The electrolyzer power allocation strategy module achieves joint operation of the two electrolyzers through a power coordination mechanism, utilizing clean wind power to produce high-purity hydrogen. The hydrogen produced by the AEL and PEMEL is stored through a hydrogen storage facility module. The hydrogen storage facility module supplies hydrogen to both the hydrogen consumption module and the fuel cell module. The hydrogen consumption module is used for direct user consumption of hydrogen, while the fuel cell module converts hydrogen into electrical energy and transmits it to the public power grid, achieving the goal of long-term storage and wide-area distribution of renewable energy.

[0068] The wind power hydrogen production capacity allocation and stabilization method based on multiple electrolysis technologies of the present invention is as follows:

[0069] The wind power hydrogen production capacity allocation method based on multiple electrolysis technologies involves the coupling between wind turbines and various electrolysis technologies. Therefore, modeling and analysis are performed on wind power generation modules and two types of electrolyzers. When the wind turbine area is S, the wind turbine generator's power output P... W The expression is:

[0070] P W =0.5ρν 3 SC p (1)

[0071] In the formula: ρ and ν are the real-time air density and wind speed, respectively; C p This represents the power factor of the wind turbine.

[0072] The relationship between the power factor of wind power generation and the aerodynamic parameters of the wind turbine is shown in equations (2), (3), and (4):

[0073]

[0074] In the formula: λ is the tip speed ratio; ω is the angular velocity of the wind turbine in rad / s; β is the blade pitch angle in rad; and λ' is the corrected tip speed ratio.

[0075] The electrolytic cell module includes AEL and / or PEMEL, used to mix and use multiple types of electrolytic cells. AEL has poor compatibility with fluctuating power sources, so it operates in the low power fluctuation range; PEMEL has better compatibility with fluctuations, so it is used to improve the system's ability to absorb fluctuating power sources. The power of the electrolytic cell is mainly affected by its volt-ampere characteristics and response rate. The power model of AEL is shown in equation (5):

[0076] P AEL=U AEL I AEL

[0077] (5) Where: P AEL For AEL electrolysis hydrogen production power; I AEL The current input to the electrolytic cell; U AEL This is the input voltage of the electrolytic cell. Where U... AEL It can also be expressed as:

[0078]

[0079] Where: U0 is the output voltage of the electrolytic cell; A is the effective electrolytic area of ​​the electrolytic cell; s is the overvoltage coefficient; T AEL R1 represents the temperature of the electrolytic cell; R1, R2, K1, K2, and K3 are empirical coefficients of the electrolytic cell power model.

[0080] The PEMEL characteristics are affected by activation overvoltage, thermal neutral voltage, ohmic overvoltage, and diffusion overvoltage. Its electrolytic hydrogen production power P PEMEL It can be represented as:

[0081] P PEMEL =I PEMEL [U ocv +U act +U diff +U ohm ] (7)

[0083] In the formula: I PEMEL This refers to the PEMEL operating current; U ocv U is the thermal neutral voltage of the PEMEL electrolytic cell circuit; act U is the activation voltage for the PEMEL circuit. diff For the PEMEL circuit diffusion voltage; U ohm This refers to the ohmic overvoltage generated by the internal resistance of the PEM electrolytic cell. The specific expressions for the above four voltages are equations (8), (9), and (10):

[0084]

[0085] In the formula: R is the ideal gas constant, which is 8.3144 J / (mol·K); The pressure of hydrogen, oxygen, and water; T PEMEL is the temperature of the electrolytic cell; F is the Faraday constant. an0 i cn0 The exchange current density at the anode and cathode; α a α c T represents the charge transfer coefficient between the anode and cathode. a T c These are the anode and cathode reaction temperatures, respectively. The oxygen and hydrogen concentrations between the membrane and the electrode; ρ represents the oxygen and hydrogen concentrations at the anode and cathode electrodes, respectively. i represents the PEMEL circuit current; δ represents the thickness of the membrane electrode; σ represents the ionic conductivity; ρ represents the resistivity of the electronic material; l represents the electron path length; and S represents the conductor cross-sectional area.

[0086] Hydrogen production efficiency η of AEL and PEMEL EL and hydrogen production rate The expression is:

[0087]

[0088] In the formula: ΔG EL For Gibbs free energy; P EL N represents the power of the electrolytic cell. EL The number of electrolytic cells; I EL η is the electrolytic current of the electrolytic cell. F denoted as Faraday efficiency of the electrolyzer; z represents the number of electrons in the reaction.

[0089] The wind power allocation strategy based on adaptive wavelet packet decomposition applied in this invention has the following main principles and strategies:

[0090] Adaptive wavelet packet decomposition, an improvement upon wavelet transform, allows for finer resolution settings, decomposing the signal into a series of non-overlapping frequency bands and reducing the difference in analytical capabilities between high and low frequency bands. The principle of adaptive wavelet packet decomposition is as follows: Figure 2 As shown.

[0091] S represents the original signal, which can be decomposed into a low-frequency component S0. n,0 and high frequency component S n,i (i = 1…2) n -1), where i is the number of wavelet packet nodes, and the frequency range f0 of each component can be expressed as:

[0092]

[0093] In the formula: n is the wavelet packet decomposition level; f s is the initial sampling frequency of the signal.

[0094] The basic decomposition algorithm for wavelet packet decomposition is expressed as follows:

[0095]

[0096] In the formula: and These represent the low-frequency and high-frequency subbands obtained from the decomposition, respectively, where l is the position index of the subband in the sequence; a n-2l and bn-2l represents the wavelet packet decomposition coefficients; j and i are wavelet packet nodes; n represents the decomposition level.

[0097] The wavelet packet reconstruction algorithm is as follows:

[0098]

[0099] In the formula: The coefficients corresponding to node i in the (j+1)th layer after reconstruction are given. These are the target coefficients to be reconstructed, where l is their position index in the sequence; h l-2n and g l-2n represents the wavelet packet decomposition coefficients; j and i are wavelet packet nodes; n represents the decomposition level.

[0100] like Figure 3 As shown, the steps of the wind power allocation strategy based on adaptive wavelet packet decomposition are as follows:

[0101] The first step involves checking if the initial wind power output is less than the active power variation limits for 1 minute and 10 minutes. These active power variation limits are selected based on the maximum active power variation limits for wind farms in Table 1. If so, the initial wind power output is directly connected to the grid; otherwise, proceed to the next step. If the initial wind power output is directly connected to the grid, then the grid-connected power P0 of the wind farm is equal to the output power P of the wind farm. w,orig :

[0102] P0 = P w,orig (16)

[0104] Table 1 Maximum Variation Limits of Active Power in Wind Farms

[0105]

[0106] The second step is to perform n (n=1) layer wavelet packet decomposition on the wind power signal based on the db6 small fundamental wavelet;

[0107] The third step is to reconstruct the decomposed layer wavelet coefficients to obtain the low-frequency and high-frequency components.

[0108] In the fourth step, if the low-frequency component after n-level decomposition is less than the active power change limits of 1 minute and 10 minutes, the decomposition is terminated; otherwise, return to the second step and continue with n+1-level decomposition until the low-frequency component is less than the active power change limits of 1 minute and 10 minutes, obtaining the wavelet packet decomposition level with a value of n, and then terminate the loop. The grid-connected power P0 after decomposition and reconstruction is the low-frequency component S. n,0 The input power P of a wind power hydrogen production system based on the synergy of multiple electrolysis technologies e It is the sum of the high-frequency components, that is:

[0109] P0 = S n,0 (17)

[0111] P e =∑S n,i i = 1, 2, ..., 2 n-1 (18)

[0113] Figure 4 The diagram illustrates the characteristic analysis of AEL and PEMEL hydrogen production systems. AEL boasts higher technological maturity and lower cost, while PEMEL, although more expensive, offers superior responsiveness to rapid fluctuations. Eight different indicators are compared: electrolyzer load range, response speed, equipment cost, energy consumption, start-up time, technological maturity, hydrogen production capacity, and hydrogen production efficiency. To visually compare the differences in characteristics between the two electrolyzers, each indicator parameter is normalized; values ​​closer to 1 indicate a wider electrolyzer load range, faster response speed, higher equipment cost, higher energy consumption, faster start-up time, higher technological maturity, and greater hydrogen production capacity and efficiency.

[0114] PEMEL electrolyzers offer significant advantages in load range, start-up time, and response speed, making them better suited for fluctuating wind power-to-hydrogen production. However, their high equipment cost limits their economic efficiency. AEL and PEMEL electrolyzers are not significantly different in terms of hydrogen production capacity and efficiency. While AEL has a lower cost, its start-up speed and dynamic response characteristics are inferior to PEMEL. Combining AEL and PEMEL electrolyzers can improve the dynamic response characteristics of the hydrogen production system while simultaneously enhancing its economic efficiency.

[0115] This invention proposes an electrolyzer power allocation strategy to enable coordinated operation of AEL and PEMEL, as detailed below:

[0116] Considering the economic advantages of AEL and the adaptability of PEMEL to fluctuating power, and taking into account the poor performance of electrolysis equipment operating at low power for extended periods and the impact of frequent start-ups and shutdowns on equipment lifespan, in wind power-to-hydrogen production, power is prioritized for electrolysis equipment with a larger capacity. Furthermore, the coordinated operation of multiple types of electrolyzers is maximized to reduce frequent start-ups and shutdowns and no-load operation issues. Therefore, a power allocation strategy considering electrolyzer capacity is adopted: the capacity of AEL and PEMEL is expressed as E. AEL and E PEMEL P e This refers to the power input to the electrolytic cell. First, compare the capacities of the two electrolytic cells; AEL's capacity is greater than PEMEL's. Then compare E... AEL With input power P e Size, P e ≥E AELAEL then operates at maximum power, i.e., maximum capacity, while PEMEL consumes the remaining power; P e <E PEMEL Power is then allocated according to the proportion of capacity occupied by AEL and PEMEL, that is:

[0117] P AEL =P e E AEL / (E AEL +E PEMEL ) (19)

[0119] P PEMEL =P e E PEMEL / (E AEL +E PEMEL ) (20)

[0121] In the formula: E AEL For the capacity of AEL, E PEMEL For the capacity of PEMEL, P AEL To allocate the electrolysis hydrogen production power to AEL, P PEMEL The electrolysis hydrogen production power allocated to PEMEL.

[0122] E PEMEL ≤P e <E AEL Then, an equal share of the power of PEMEL's capacity is allocated to AEL, and the remaining power is allocated to PEMEL to produce hydrogen.

[0123] If the capacity of PEMEL is greater than the capacity of AEL, then compare E. PEMEL With input power P e Size, P e ≥E PEMEL Then PEMEL operates at maximum power, i.e., maximum capacity, while AEL consumes the remaining power; if P e <E AEL Then, power is allocated according to the proportion of capacity occupied by AEL and PEMEL (the calculation formula is the same as formulas (19) and (20)), that is:

[0124] P AEL =P e E AEL / (E AEL +E PEMEL ) (19)

[0126] P PEMEL =P e E PEMEL / (E AEL +EPEMEL ) (20)

[0128] In the formula, E AEL For the capacity of AEL, E PEMEL For the capacity of PEMEL, P AEL To allocate the electrolysis hydrogen production power to AEL, P PEMEL The electrolysis hydrogen production power allocated to PEMEL.

[0129] If E AEL ≤P e <E PEMEL Then, an equal amount of power from the AEL capacity will be allocated to the PEMEL, and the remaining power will be allocated to the AEL for hydrogen production.

[0130] Construct the objective function and decision variables to determine the annual comprehensive hydrogen production cost per unit of a wind power-to-hydrogen system based on the synergy of multiple electrolysis technologies. With system annual energy loss efficiency η loss The objective function for capacity optimization configuration is the capacity E of the hybrid electrolyzer. AEL and E PEMEL These are decision variables.

[0131] The system's annual unit comprehensive hydrogen production cost Investment cost C inv Operation and maintenance costs C op Annual revenue from hydrogen production (S) and annual hydrogen production volume The decision is made jointly, and the specific expression is as shown in equation (21):

[0132]

[0133] In the wind power hydrogen production system based on the synergy of multiple electrolysis technologies, the investment costs of AEL and PEMEL are positively correlated with the capacity configuration of the electrolyzer. The system investment cost can be expressed as:

[0134]

[0135] In the formula C el C as These represent the investment cost of the electrolyzer and the investment cost of auxiliary equipment in the hydrogen production system, respectively. To simplify the calculation, C... as Calculated at 10% of the investment cost of the electrolytic cell; C el,AEL With C el,PEMEL This indicates the price per unit power for the two types of electrolytic cells.

[0136] Electrolytic cell system operation and maintenance cost C op The rated power of the two electrolytic cells and their respective unit power operation and maintenance costs C op,AEL C op,PEMEL The product is composed of the following, which is given by equation (23):

[0137] C op =P AEL C op,AEL +P PEMEL C op,PEMEL (twenty three)

[0139] Hydrogen produced by wind power hydrogen production systems based on various electrolysis technologies can be sold, thus offsetting some of the costs. The produced hydrogen can be used in power systems, industry, transportation, and other fields. Its revenue model is Equation (24):

[0140]

[0141] In the formula, S represents the system's hydrogen production revenue, and C... H (t) represents the unit price of hydrogen at that moment, H H (t) represents the amount of hydrogen sold at time t, which is estimated using the energy consumed by the electrolyzer at time t, where T is the operating cycle.

[0142] Using system energy loss efficiency η loss As another objective function for capacity configuration to evaluate the benefits of wind power-to-hydrogen systems based on the synergy of multiple electrolysis technologies, the collective expression is as follows:

[0143]

[0144] In the formula η sys η represents the energy efficiency of the electrolyzer. AEL η PEMEL t represents the electrolysis hydrogen production efficiency of AEL and PEMEL, respectively, and t represents the operating time of the hydrogen production system.

[0145] A wind-powered hydrogen production system based on the synergy of multiple electrolysis technologies must meet an energy balance constraint during operation, meaning the total power of the hydrogen production equipment should not exceed the power input to the electrolyzer. The power balance relationship is as follows:

[0146] 0≤P AEL +P PEMEL ≤P e (26)

[0148] The output of the wind turbine is less than or equal to the upper limit of the unit's power generation capacity.

[0149] 0≤P w ≤P w,max

[0150] (27) Where: P w,max This is the upper limit of the power generation capacity of wind turbine units.

[0151] The total capacity of the electrolyzers is lower than the peak output of the wind power.

[0152]

[0153] In the formula: P AEL,rate and P PEMEL,rate These represent the rated power of AEL and PEMEL, respectively.

[0154] The relevant parameter settings involved in the model are shown in Table 2:

[0155] Table 2 Model-related parameters

[0156]

[0157]

[0158] The capacity optimization of a wind power-to-hydrogen system employing multiple electrolysis technologies is treated as a multi-variable, multi-constraint, multi-objective optimization problem, and solved using the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. MOPSO possesses global search capabilities, fast convergence speed, and high flexibility, making it a highly efficient algorithm. The specific algorithm steps are as follows:

[0159] Step 1: Initialize the particle swarm. Set the number of particles, randomly generate the initial position and velocity of each particle, set the maximum number of iterations and inertia weight, input the cognitive acceleration constant and social acceleration constant, and set the velocity clamping and position boundaries of the particles.

[0160] Step 2: Calculate the objective function. Based on the wind farm output data, a simulated hydrogen production process is performed under the constraints of the electrolyzer formulas (26), (27) and (28), and the fitness function is defined and evaluated.

[0161] Step 3: Selection of Non-Dominated Solutions and Pareto Front Update. Dominance relations are used to determine the relative merits of particles, and a set of non-dominated solutions is found, forming the current Pareto front. An external archive is used to store the current Pareto front; this repository stores the current non-dominated solutions and is continuously updated during the iteration process.

[0162] Step 4: Update particle velocity and position. Based on the individual extreme value p best Social extreme value (global optimal position g) best (Or non-dominated solutions in the repository) Update the particle's velocity, adjust the particle's position according to the updated velocity, and ensure that the particle is within the search space.

[0163] Step 5: If the maximum number of iterations is reached, output the global optimal solution, i.e., output the Pareto front, and complete the multi-objective optimization solution. Finally, determine the entropy weight of each objective function in different non-dominated solutions using the entropy weight method, further calculate the comprehensive optimization degree, and select the optimal solution.

[0164] This paper presents a calculation and analysis of a wind power hydrogen production system based on multiple electrolysis technologies and a power distribution and saturation method. Wind speed data from the wind farm is shown below. Figure 6 As shown, the dynamic characteristics of wind power output during typical periods throughout the year are as follows: Figure 7 As shown.

[0165] When using fluctuating power sources for hydrogen production, the water electrolyzer needs to adjust its load according to actual operating conditions. Frequent start-ups and shutdowns are common during dynamic operation, and the cold start process of the electrolyzer directly impacts the energy efficiency of wind power-based hydrogen production systems using multiple electrolysis technologies. AEL (Alternating Electrolyte) exhibits a certain lag during cold start-up; it takes approximately 60 minutes for an AEL to go from cooling to operating at its rated power, including about 50 minutes of start-up time and about 10 minutes of electrolyzer heating time. This leads to a significant increase in energy loss for the AEL. In contrast, PEMEL (Polymerized Electrolyte) has superior start-up characteristics, with a start-up lag time of less than 10 minutes and higher energy efficiency than AEL. In summary, combining the start-up characteristics of AEL and PEMEL in a hydrogen production system, and allocating power to both types of electrolyzers through a reasonable power distribution strategy, helps improve the hydrogen production system's resilience to complex wind power fluctuations. Figure 8 (a) and (b) are schematic diagrams of the cold start process of AEL and PEMEL, respectively.

[0166] Using China's "Technical Regulations for Wind Farm Connection to Power Systems" as a reference standard, the selected 50MW wind farm falls within the 30-150MW installed capacity range. Therefore, its 1-minute maximum power change rate limit is 5MW, and its 10-minute maximum power change limit is 16.67MW. The 1-minute maximum power change during typical periods in January and July was 23.01MW and 12.12MW, respectively, both exceeding the limits set by the reference standard. After adaptive wavelet packet decomposition, the 1-minute fluctuations were reduced to 2.29MW and 2.75MW, respectively. The 10-minute active power changes during the two typical periods in January and July were 26.88MW and 23.27MW, respectively, not meeting the 16.67MW fluctuation limit. After wavelet packet decomposition, the 10-minute maximum power change was reduced to 15.91MW and 12.20MW, respectively. The original output power of the wind farm, the grid-connected power smoothed after wavelet packet decomposition, and the input power of the wind power-to-hydrogen system based on multiple electrolysis technologies are shown below. Figure 9 (a), (b) and Figure 10 As shown in (a) and (b), the comparison of the suppression effect during typical time periods is shown in Table 3.

[0167] Table 3 Comparison of Suppression Effects During Typical Time Periods

[0168]

[0169] Adaptive wavelet packet decomposition has a good effect on smoothing the random and fluctuating power output of wind power generation. The maximum power changes in the two typical time periods of 1 minute and 10 minutes after decomposition both meet the requirements of wind power grid connection standards. Therefore, the smoothed low-frequency component power can be connected to the grid, and the remaining high-frequency component can be used as the input power of a wind power hydrogen production system based on multiple electrolysis technologies.

[0170] To improve the energy efficiency of the wind power hydrogen production system based on multiple electrolysis technologies and reduce the number of start-ups and shutdowns of the electrolysis equipment, and to fully utilize the excellent dynamic response and start-up / shutdown characteristics of PEMEL and the low cost of AEL, a 15MW electrolysis hydrogen production equipment is configured for the wind farm. In conjunction with the electrolyzer power allocation method, a multi-objective particle swarm optimization algorithm is used to configure the capacity of the two types of electrolyzers.

[0171] Table 4 compares wind power hydrogen production systems based on multiple electrolysis technologies with single AEL or single PEMEL systems. While a single AEL system has the lowest hydrogen production cost, the power input to the hydrogen production system fluctuates significantly due to wavelet packet decomposition of the original wind power signal. AEL systems have poor response to fluctuating power, long start-up lag, and are not suitable for frequent start-ups and shutdowns, resulting in substantial energy losses and reduced annual hydrogen production. The energy efficiency of a single AEL system is only 30.6%, with an annual hydrogen production of 462 tons. PEMEL systems, with their superior fluctuating resource response and start-up / shutdown characteristics, significantly reduce energy losses compared to single AEL systems, increasing energy efficiency to 49.7% and achieving a hydrogen production of 574 tons. However, their hydrogen production cost is 26% higher than that of a single AEL system. This higher cost reduces internal system revenue and negatively impacts the overall economic viability. Therefore, while single PEMEL systems offer advantages in wind power hydrogen production efficiency and output, they are not suitable for standalone configuration in hydrogen production systems considering economic benefits.

[0172] After capacity optimization, the wind power-to-hydrogen system based on multiple electrolysis technologies achieves an AEL (Automatic Electrolysis Electrolysis) capacity ratio of 26.87% and a PEMEL (Penetrating Electrolysis ...

[0173] Table 4 Optimization results of wind power hydrogen production system based on synergy of multiple electrolysis technologies

[0174]

[0175] Analysis of a typical period in January revealed that when only an AEL (Alternating Electrolysis Unit) was used, the power curve of the hydrogen production system fluctuated significantly. Prolonged operation under this scenario not only negatively impacted the electrolysis equipment but also failed to adapt well to fluctuating power sources. When only a PEMEL (Polymer Electrolysis Unit) was used, the system power curve was the smoothest due to the PEMEL's rapid dynamic response; however, economic considerations prevented the use of a single PEMEL as a hydrogen production device. When both AEL and PEMEL were configured according to the optimization results described above, the power curve of the wind power hydrogen production system based on the synergy of multiple electrolysis technologies showed significant improvement compared to the single AEL system. This effectively reduced the power output fluctuation of the hydrogen production system while meeting the system's economic requirements. The peak fluctuation rate of the hydrogen production load with a single AEL was 87.99%, which decreased to 79.87% during the same period after adding a PEMEL. The average fluctuation rate of a single AEL was 43.58%, while the optimized average fluctuation rate was only 10.23%, a reduction of 33.35%. During certain extreme periods, PEMEL can adjust its output to reduce the volatility of AEL load, effectively avoiding the shortcomings of AEL's poor dynamic response capability.

[0176] After optimization, the electrolysis efficiency of AEL stabilized at around 67%, while that of PEMEL fluctuated around 63%. By optimizing the capacity of the wind power-to-hydrogen system based on the synergy of multiple electrolysis technologies, the system's coupling capability with fluctuating resources was improved, enabling the system to operate stably and efficiently while also being economical.

[0177] The simulation results above demonstrate that the hybrid electrolyzer power allocation and capacity configuration method based on adaptive wavelet packet transform of the present invention, coupled with the multi-electrolysis technology synergistic control mechanism, improves the effect of hydrogen energy storage system on wind power fluctuations, while enabling the wind power hydrogen production system based on multiple electrolysis technologies to effectively adapt to the intermittent and fluctuating output characteristics of wind power, and significantly improves the dynamic response performance of the system.

[0178] The calculation conditions, illustrations, etc. in the embodiments of this invention are only used to further illustrate the invention and are not exhaustive. They do not constitute a limitation on the scope of protection of the claims. Those skilled in the art, based on the inspiration gained from the examples of this invention, can conceive of other substantially equivalent alternatives without inventive effort, all of which are within the scope of protection of this invention.

Claims

1. A wind power hydrogen production system based on multiple electrolysis technologies, characterized in that, The system includes a public grid module, a wind power generation module, and an electrolysis hydrogen production module. The wind power generation module includes wind turbine generators that convert wind energy into electrical energy. The wind power generation module is electrically connected to a wind power distribution module. The wind power distribution module decomposes electrical energy into grid-connected power (below a preset active power variation limit) and hydrogen production power (greater than or equal to the preset active power variation limit). The wind power distribution module transmits the grid-connected power to the public grid module and the hydrogen production power to the electrolysis hydrogen production module. The electrolysis hydrogen production module includes an electrolyzer power distribution strategy module and an electrolyzer module. The electrolyzer module includes AEL and PEMEL electrolyzers. The electrolyzer power distribution strategy module is electrically connected to the AEL and PEMEL electrolyzers respectively. The electrolyzer power distribution strategy module is used to enable the joint operation of the AEL and PEMEL electrolyzers. The hydrogen produced by the AEL and PEMEL electrolyzers is stored through a hydrogen storage facility module.

2. The wind power hydrogen production system based on multiple electrolysis technologies according to claim 1, characterized in that, The hydrogen storage module supplies hydrogen to the hydrogen consumption module and the fuel cell module respectively. Users can directly use hydrogen through the hydrogen consumption module, while the fuel cell module is used to convert hydrogen into electrical energy and transmit it to the public power grid module.

3. A method for allocating and controlling the power output of wind-powered hydrogen production based on multiple electrolysis technologies, characterized in that... It includes the following steps, and the following steps are performed in sequence. Step 1: Set a preset active power variation limit and use adaptive wavelet packet decomposition to decompose the power output of the wind turbine generator into low-frequency components that are less than the preset active power variation limit and high-frequency components that are greater than or equal to the preset active power variation limit. Step 2: The high-frequency components are distributed to the AEL and PEMEL electrolytic cells via the electrolytic cell power distribution strategy module. The distribution strategy of the electrolytic cell power distribution strategy module is as follows: compare the capacity E of AEL. AEL PEMEL's capacity E PEMEL and the power P input to the electrolytic cell e Size, P e ≥E AEL >E PEMEL AEL then operates at maximum capacity, while PEMEL consumes the remaining power input to the electrolyzer; P e ≥E PEMEL >E AEL PEMEL then operates at maximum capacity, while AEL consumes the remaining power input to the electrolyzer; E AEL ≤P e <E PEMEL The power input to the electrolyzer in equal capacity to AEL is then allocated to PEMEL, and AEL consumes the remaining power input to the electrolyzer; P e <E PEMEL <E AEL or P e <E PEMEL <E AEL Power is then allocated based on the proportion of capacity occupied by AEL and PEMEL. Step 3: Construct the annual unit comprehensive hydrogen production cost based on the wind power hydrogen production system With system annual energy loss efficiency η loss The objective function for capacity optimization configuration is the capacity E of the hybrid electrolyzer. AEL and E PEMEL Let P be the decision variable, and let 0 ≤ P be the constraint. AEL +P PEMEL ≤P e ; Step 4: Solve the objective function described in Step 3 using a multi-objective particle swarm optimization algorithm to obtain the electrolyzer capacity E. AEL and E PEMEL .

4. The method for allocating and controlling the power output of wind power hydrogen production based on multiple electrolysis technologies according to claim 3, characterized in that, Before setting the active power variation limit in step one, the method further includes first inputting the installed capacity of the wind turbine generator set, then inputting the limiting relationship between the installed wind power capacity of the wind turbine generator set's location and the active power variation limit of the wind power, and outputting the preset active power variation limit.

5. The method for allocating and controlling the power output of wind power hydrogen production based on multiple electrolysis technologies according to claim 3, characterized in that, The first step, the adaptive wavelet packet decomposition method, includes: S represents the original signal, which can be decomposed into low-frequency components S0. n,0 and high frequency component S n,i (i = 1…2) n -1), where i is the initial number of decomposition layers, and the frequency range f0 of each component is expressed as equation (13): In the formula: n is the number of wavelet packet decomposition layers; f s The initial sampling frequency of the signal; The basic decomposition algorithm of wavelet packet decomposition is specifically expressed as equation (14): In the formula: and These represent the low-frequency and high-frequency subbands obtained from the decomposition, respectively, where l is the position index of the subband in the sequence; a n-2l and b n-2l Represents the wavelet packet decomposition coefficients; j and i are wavelet packet nodes; n represents the wavelet packet decomposition level; The wavelet packet reconstruction algorithm is given by equation (15): In the formula: The coefficients corresponding to node i in the (j+1)th layer after reconstruction are given. These are the target coefficients to be reconstructed, where l is their position index in the sequence; h l-2n and g l-2n represents the wavelet packet decomposition coefficients; j and i are wavelet packet nodes; n represents the wavelet packet decomposition level.

6. The method for allocating and controlling the power output of wind power hydrogen production based on multiple electrolysis technologies according to claim 3, characterized in that, The steps of the adaptive wavelet packet decomposition method in step one include: First, if the original wind power is less than the preset active power variation limit, the original wind power is directly connected to the grid; otherwise, proceed to the next step. Secondly, the wind power signal is decomposed into n (n=1) layers of wavelet packets based on the db6 fundamental wavelet; Next, the decomposed layer wavelet coefficients are reconstructed to obtain low-frequency and high-frequency components; Finally, if the low-frequency component after n-level decomposition is less than the preset active power variation limit, the decomposition terminates; otherwise, proceed to the second step and continue with n+1-level decomposition until the low-frequency component is less than the preset active power variation limit, obtaining a wavelet packet decomposition level of value n, then terminating the loop. The grid-connected power P0 after decomposition and reconstruction is the low-frequency component S. n,0 The input power P of a wind power hydrogen production system based on the synergy of multiple electrolysis technologies e The sum of the high-frequency components is given by equations (17) and (18): P0=S n,0 (17) P e =∑S n,i ,i=1,2,…,2 n-1 (18) In the formula: S n,i Let be the high-frequency components after decomposition and reconstruction, where n is the number of wavelet packet decomposition layers and i is the number of wavelet packet nodes.

7. The method for allocating and controlling the power output of wind power hydrogen production based on multiple electrolysis technologies according to claim 3, characterized in that, The power allocation method in step two, which is based on the capacity ratio of AEL and PEMEL, is expressed by equations (19) and (20): P AEL =P e AND AEL / (AND AEL +E PEMEL ) (19) P PEMEL =P e AND PEMEL / (AND AEL +E PEMEL ) (20) In the formula: P e For input power, P AEL To allocate the electrolysis hydrogen production power to AEL, P PEMEL To allocate the electrolysis hydrogen production power to PEMEL, E AEL For the capacity of AEL, E PEMEL This refers to the capacity of the PEMEL.

8. The method for allocating and controlling the power output of wind power hydrogen production based on multiple electrolysis technologies according to claim 3, characterized in that, The objective function of step three is the annual unit comprehensive hydrogen production cost. The construction method is as shown in equation (21): In the formula: C inv For investment costs, C op S represents the annual revenue from hydrogen production, where S is the operating and maintenance cost. This refers to the annual hydrogen production capacity.

9. A method for allocating and controlling the power output of wind power hydrogen production based on multiple electrolysis technologies according to claim 3, characterized in that, The objective function of step three is the system's annual energy loss efficiency η. loss The construction method is as shown in equation (25): In the formula η sys For the energy efficiency of the electrolyzer, η AEL η PEMEL t represents the electrolytic hydrogen production efficiency of AEL and PEMEL, respectively, and t represents the operating time of the hydrogen production system.

10. A method for allocating and controlling the power output of wind power hydrogen production based on multiple electrolysis technologies according to claim 3, characterized in that, The objective function constraint in step three also includes equation (28): In the formula: P AEL,rate and P PEMEL,rate The rated power of AEL and PEMEL are respectively, P w,max This is the upper limit of the power generation capacity of wind turbine units.

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