Multi-pile proton exchange membrane optical hydrogen system power distribution method considering electrolysis device efficiency and hydrogen production amount

Abstract

The invention discloses a multi-stack parallel proton exchange membrane optical hydrogen system power distribution method considering electrolysis device efficiency and hydrogen production amount, and aims to solve the problem of low electrolytic cell efficiency and hydrogen production amount caused by low-power operation of part of electrolytic cells under continuous fluctuation of photovoltaic power in a multi-electrolytic cell parallel optical hydrogen system. In order to improve the efficiency and hydrogen yield of an electrolytic cell of a hydrogen production system under photovoltaic power fluctuation in a light hydrogen system and ensure efficient and stable operation of the system, firstly, a multi-stack parallel proton exchange membrane (PEM) electrolytic cell photovoltaic hydrogen production system model is established through MATLAB / simulink; when the efficiency of the electrolysis device is analyzed, the electrolysis efficiency, the Faraday efficiency, the efficiency of auxiliary equipment of an electrolysis system and the conversion efficiency of a converter are comprehensively considered, and the hydrogen production amount of a multi-stack parallel electrolytic cell system (MPES), the efficiency of the electrolysis device, the operating power state of the electrolytic cell and the like serve as evaluation indexes. The reference power value of each branch is calculated off line through a dung beetle optimization algorithm (DBO), the system output power of each branch proton exchange membrane electrolytic cell (PEMEL) is optimized in real time, the hydrogen production of the MPES is improved, and the constraint power fluctuation rate is considered. And finally, inputting actual photovoltaic fluctuation data in an experimental example, and verifying the effectiveness of the method by comparing with a traditional electrolytic cell power distribution strategy.

Description

Technical Field

[0002] The present invention belongs to a power allocation technology for a multi-stack proton exchange membrane electrolyzer parallel system, and specifically relates to a power allocation method for a multi-stack proton exchange membrane photohydrogen system taking into account the efficiency of the electrolysis device and the amount of hydrogen produced. Background Art

[0004] Photovoltaic hydrogen production systems have become one of the important development directions in the future energy field due to their environmental friendliness, high efficiency, storability and wide applicability. However, photovoltaic power generation is easily affected by natural factors such as sunlight, shadows and ambient temperature. Its power output shows randomness, volatility and stage, which seriously affects its reliability as a stable energy supply. Under the influence of continuous fluctuations in photovoltaic power, the electrode reaction in the electrolyzer system deviates from the steady-state condition, thereby affecting the hydrogen production efficiency, hydrogen production and the life of the electrolyzer. Explore how to study the MEPS power allocation strategy that adapts to the influence of photovoltaic fluctuations under the complex fluctuations of photovoltaic (PV) power generation, and effectively allocate power and switch the state of the electrolyzer array. Maintaining the safe, stable and efficient operation of multiple parallel-operated electrolyzers is one of the key technologies that need to be solved for the scale-up of photovoltaic hydrogen production systems.

[0005] It is particularly worth mentioning that a photovoltaic-multi-stack electrolyzer model that comprehensively considers the efficiency of the hydrogen production device is established, and the relationship between the hydrogen production of the MPES system and the hydrogen production power and efficiency is studied in depth. The proposed optimization method effectively improves the MPES hydrogen production and electrolysis efficiency, which will provide a solid theoretical foundation for the large-scale development of photovoltaic hydrogen production systems and lay a reliable technical support for practical applications. This research is of great significance to promoting the healthy development of the photovoltaic hydrogen production industry. Summary of the invention

[0007] Purpose of the invention: The study of power allocation for multi-stack parallel electrolyzers is crucial. Establishing a photovoltaic-multi-stack electrolyzer hydrogen production model that comprehensively considers the efficiency and hydrogen production of the hydrogen production device, and proposing a power allocation method for a multi-stack proton exchange membrane photohydrogen system that considers the efficiency and hydrogen production of the electrolysis equipment will provide a solid theoretical foundation for the development of photovoltaic hydrogen production and lay a reliable technical support for practical applications.

[0008] Technical solution: A PEMEL power adaptive allocation method considering the efficiency and hydrogen production of the electrolyzer is proposed. This method takes the MEPS system as the research object. By analyzing the efficiency characteristics of the electrolyzer in the MEPS system, the efficiency of the hydrogen production device of the single-stack PEMEL system changes with the electrolyzer power curve is fitted, and the power allocation strategy that takes into account the hydrogen production and the efficiency of the electrolyzer is established based on the DBO algorithm. This method is specifically divided into two links: offline calculation and online control. The offline calculation link includes PEMEL offline data acquisition, efficiency-power curve fitting, and reference power calculation; the online control link includes adaptive power allocation, control quantity calculation, and PWM modulation. First, according to the characteristics of PV power generation output, offline data acquisition is performed on the input current and working voltage of the single-stack electrolyzer under actual working conditions, and the characteristic curve of the efficiency of the hydrogen production device of the PEMEL system changes with the electrolyzer power is calculated. The curve is fitted to obtain the function of the efficiency of the single-stack electrolyzer system changing with the electrolyzer power. The reference power corresponding to each PEMEL starting point in the MPES system is calculated by the power allocation strategy based on the DBO algorithm. Then, the control system distributes the power of each branch according to the reference power, and then obtains the control quantity of each branch. Finally, the PEMEL system pulse control signal is generated by the PWM control quantity to realize the system branch control.

[0009] The main purpose of the power allocation strategy is to optimize the operation status of the electrolyzer, so that each PEMEL can operate within the optimal efficiency range and rated power range as much as possible, in order to achieve the maximum hydrogen production. The voltage efficiency is shown in the following formula. In the past, the efficiency of the PEMEL electrolyzer was usually measured by voltage efficiency. However, the voltage efficiency mainly reflects the conversion efficiency of the internal electrical energy of the PEMEL, which only covers the membrane loss and heat loss.

[0010]

[0011] Where η el is the single stack PEMEL voltage efficiency, V rev is the reversible voltage of the PEMEL stack, V ele is the PEMEL stack voltage.

[0012] Faraday efficiency is an important indicator for optimizing electrolyzer performance and one of the key parameters for measuring the overall energy efficiency of hydrogen electrolysis systems. It is mainly affected by factors such as hydrogen and oxygen gas permeation, membrane mass transfer process, and side reactions. Optimization of Faraday efficiency is a key factor in improving the overall efficiency of PEM electrolyzer systems, especially when considering large-scale applications. The model is as follows.

[0013]

[0014] Where η F is the PEMEL stack Faraday efficiency, Iel Input current for the PEMEL stack.

[0015] The PEMEL system is mainly composed of a PEM electrolyzer, a DC / DC converter and a series of auxiliary equipment. Given that the essential function of the electrolyzer is to convert electrical energy into chemical energy and store it, the efficiency calculation of the PEMEL auxiliary equipment uses the power consumed by water, thermal management auxiliary equipment and the converter. The formula is as follows:

[0016]

[0017] Where η aux is the PEMEL auxiliary system efficiency, P EC is the output power of the PEMEL stack, P aux The power consumed by PEMEL's auxiliary systems.

[0018] In order to effectively evaluate the efficiency of the electrolysis device, the electrolysis efficiency, Faraday efficiency and auxiliary system efficiency are comprehensively considered, which can be expressed as:

[0019]

[0020] In the formula, is the efficiency of the electrolysis device of the ith electrolytic cell.

[0021] When analyzing the characteristics of PEMEL hydrogen production, the mass flow rate of hydrogen generated can be expressed as follows according to Faraday's law of electrolysis:

[0022]

[0023] In the formula, is the mass flow rate of hydrogen in the electrolyzer, and F is the Faraday coefficient.

[0024] The total hydrogen production over a period of time can be calculated by numerical integration using the trapezoidal method and summing at discrete time points:

[0025]

[0026] In the formula, is the cumulative hydrogen production from time 0 to time τ, is the mass flow rate of hydrogen at time τ.

[0027] In order to optimize the efficiency and hydrogen production of the electrolysis device, power allocation is performed based on the DBO algorithm. With the goal of optimizing the efficiency and hydrogen production of the electrolysis device, the algorithm is optimized according to the curve of the electrolysis device efficiency changing with the electrolyzer power to obtain the reference power that needs to be allocated to each electrolyzer. The power allocation strategy aims at optimizing the hydrogen production of MPES and the efficiency of the hydrogen production device, so the objective function expression is:

[0028]

[0029] Where: K c,i , K p,i is the penalty coefficient; M H2,i represents the hydrogen production of the ith PEMEL; f (total),i is the power of the ith PEMEL electrolyzer.

[0030] The hydrogen production system is a parallel multi-stack array consisting of four identically configured 45 kW PEMELs (PEMEL 1 ~ PEMEL 4), and the hydrogen production electricity is provided by a PV power station with an installed capacity of 200 kW. It is based on the measured irradiance data and photovoltaic panel operating temperature data of a PV power station in July and the first three days of November in a certain year. MATLAB / simulink is used for modeling and simulation, and the three strategies of average allocation strategy, chain allocation strategy, and power adaptive strategy based on electrolysis efficiency are compared to verify the effectiveness of the power allocation strategy.

[0031] Beneficial effects: By optimizing the power allocation strategy of the multi-stack PEM solar hydrogen system, taking into account the efficiency of the electrolysis device and the hydrogen production, efficient power utilization and significant reduction in energy loss are achieved. Experimental verification shows that this strategy improves the stability and operating efficiency of the system and avoids the long-term low-load operation of some electrolyzers. It provides reliable support for the large-scale promotion and application of solar hydrogen technology and lays a solid foundation for the development of the clean energy field. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a power distribution structure diagram of a multi-stack PEM light hydrogen system in the present invention;

[0034] Figure 2 is a single-stack electrolyzer system current density-electrolyzer power-electrolysis device efficiency analysis surface in the embodiment;

[0035] Figure 3 It is the analysis surface of electrolysis device efficiency-electrolysis cell power-hydrogen production of the single-stack electrolysis cell system in the embodiment;

[0036] Figure 4 is a fitting curve of the change in efficiency of the single-stack PEM electrolyzer electrolysis device with power in the embodiment;

[0037] Figure 5 is the photovoltaic panel operating temperature and solar irradiance curve for 4500 min in the embodiment;

[0038] Figure 6 It is the polarization characteristic verification curve of the single-stack PEMEL system in the embodiment;

[0039] Figure 7 1 is the power allocation of the electrolyzer of the four power allocation methods in the embodiment (a) strategy 1, (b) strategy 2, (c) strategy 3, (d) strategy 4;

[0040] Figure 8 is the operating time proportion of each electrolyzer under the four power allocation methods in the embodiment (a) strategy 1, (b) strategy 2, (c) strategy 3, (d) strategy 4;

[0041] Fig. 9 It is a comparison of hydrogen production under four power allocation methods in the embodiment;

[0042] Fig.10 is the efficiency variation range of each electrolytic device of the electrolytic cell under the four power allocation methods in the embodiment; DETAILED DESCRIPTION

[0044] In order to explain the technical solution of the present invention in detail, the following is further described in conjunction with the drawings and specific embodiments of the specification. It should be understood that the described embodiments are only used to explain the present invention and are part of the embodiments of the present invention, rather than all of the embodiments.

[0045] In the offline calculation part of the power allocation strategy, in order to describe the characteristic curve of the MPES system hydrogen production device efficiency changing with the electrolyzer power, the least squares polynomial fitting method is used to fit the collected single-stack PEMEL hydrogen production device efficiency and electrolyzer power data to obtain the corresponding function, which is convenient for the analysis and calculation of the multi-stack PEMEL system. The schematic diagram of the fitting curve is shown in the figure Figure 4 As shown in the figure, the fitting function of the hydrogen production efficiency of the single-stack PEMEL system as the electrolyzer power changes is as follows:

[0046]

[0047] Where: f (P) is the curve of the electrolysis device efficiency of the i-th PEMEL changing with the electrolyzer power. Assuming that the internal differences of each PEMEL are not considered, the above formula is used to represent the relationship between the hydrogen production device efficiency of each PEMEL and the electrolyzer power; where A, B, C, and D are fitting parameters.

[0048] Through the relationship between the efficiency of the electrolysis device of the single-stack PEMEL system and the power of the electrolyzer, the overall system efficiency under the multi-stack parallel topology is analyzed, and the constraint relationship between the overall efficiency of the MPES system and the output power of the PV power supply is established as follows:

[0049]

[0050] Where: f (total) is the overall efficiency of the MPES system; P1, P2, …, P n is the power of each electrolytic cell; f(P1), f(P2), …, f(Pn) are the electrolysis device efficiencies corresponding to the real-time power of each electrolytic cell; P PV is the total output power of the photovoltaic power source.

[0051] The power allocation strategy aims to optimize the hydrogen production of MPES and the efficiency of the hydrogen production device, so the objective function expression is:

[0052]

[0053] Where: K c,i , K p,i is the penalty coefficient; M H2,i represents the hydrogen production of the ith PEMEL; f (total),i is the power of the ith PEMEL electrolyzer.

[0054] The position update of the dung beetle rolling dung ball is divided into two types: there is an obstacle in front and there is no obstacle. The position update formula when there is no obstacle is:

[0055]

[0056] In the formula, t represents the current number of iterations, x z represents the position of the zth dung beetle at the tth iteration, α is a natural coefficient, indicating whether it deviates from the original direction, usually assigned a value of -1 or 1, k∈(0,0.2) represents the deflection coefficient, b is a random vector with element values ​​between 0 and 1, k and b are set to 0.1 and 0.3 respectively, X w Indicates the global worst position. When there is no obstacle:

[0057]

[0058] Where θ∈[0, π] represents the deflection angle. When θ is equal to 0, π or π / 2, the position of the dung beetle will not be updated.

[0059] The movement range of the egg-laying dung beetle is limited to the safe zone, which is used to realize local search and development in the safe zone. The location boundary of its egg-laying area is:

[0060]

[0061] In the formula, X* represents the current local optimal position, Lb * and Ub * Respectively represent the lower and upper limits of the spawning area, T maxrepresents the maximum number of iterations, Lb and Ub represent the lower and upper limits of the optimization problem respectively. The dung beetle will look for food in the best foraging area, and its position will be updated as follows:

[0062]

[0063] In the formula, x z (t) is the position of the zth dung beetle at the tth iteration, C1 is a random number following a normal distribution, C2∈(0,1) is a random vector, Lb b and Ub b are the lower and upper limits of the optimal foraging area.

[0064] The Thief Dung Beetle will steal items from other Dung Beetles. Its position is updated to:

[0065]

[0066] Where, X b is the global optimal position, g represents a 1*D dimensional random variable following a normal distribution, and S represents a constant value.

[0067] In the online control of the MPES with a parallel structure, the total input power of the MPES is calculated by collecting the PV output current and bus voltage, and the hydrogen production power of each subsystem is allocated through the power adaptive allocation strategy based on the DBO algorithm. The reference power of each PEMEL is output in real time to obtain the corresponding PWM control quantity. When the required hydrogen production power is constant, the optimal output power value is obtained according to the offline calculation, and then the power is allocated through online control. In the process of online control of each PEMEL branch, PID is used to apply power-current dual closed-loop control to each PEMEL branch, which can achieve higher control accuracy for the PEMEL branch.

[0068] In order to verify the effectiveness of the proposed method, the performance of the proposed strategy is verified by comparing it with the average allocation strategy, the chain allocation strategy, and the power adaptation strategy based on electrolysis efficiency. Figure 5 The actual light intensity and component temperature are input into the photovoltaic end of the multi-stack solar hydrogen system, and the performance of the power allocation strategy is verified through actual fluctuation scenarios. Figure 6 In order to verify the polarization curve of the single-stack PEMEL system model, the corresponding parameters were calibrated according to the established model and experimental test data, and the experimental test data and model simulation results were compared and analyzed. The established model can well reflect the changes in the polarization curve of PEMEL.

[0069] Figure 7The power distribution of the electrolyzers under the four power distribution methods under actual photovoltaic conditions is shown in Figure 2. For the convenience of description, the above three methods are represented by strategies 1-3, and the proposed method is represented by strategy 4. The proposed distribution method comprehensively considers the power of the electrolyzer and the amount of hydrogen produced, and takes the electrolyzer operation status target as the consideration, solving the problem of low utilization of some electrolyzers when the PV power supply is insufficient. At the same time, the full load operation of PEMEL1 and PEMEL2 is reduced, avoiding the problem of voltage degradation of some PEM electrolyzers due to long-term full load.

[0070] Figure 8 The operating time ratio of each electrolyzer under four different working conditions under four power allocation methods. Compared with strategy 3, the proposed method reduces the downtime by 1.1%, reduces the low-power operating time by 3.62%, reduces the full-load operating time by 5.91%, and increases the rated power operating time by 11.57%. Fig. 9 The comparison of hydrogen production under the four power allocation methods after running for 4500 min shows that the proposed strategy is on par with strategy 2. Compared with strategies 1 and 3, the total hydrogen production has been significantly improved. Fig.10 The efficiency variation range of each electrolyzer electrolysis device under different power allocation methods. It can be seen that compared with strategies 1-3, the proposed method maintains high-efficiency hydrogen production in a larger power range, and the efficiency of the electrolysis device is greatly improved.

Claims

1. A power allocation method for a multi-stack parallel proton exchange membrane photohydrogen system considering the efficiency of the electrolysis device and the amount of hydrogen produced, characterized in that: This is accomplished by following these steps: (1) Establish a photovoltaic-multi-PEM electrolyzer hydrogen production system model that comprehensively considers electrolysis efficiency, Faraday efficiency, efficiency of electrolysis system auxiliary equipment, and converter efficiency; (2) In order to describe the characteristic curve of the MPES system hydrogen production device efficiency changing with the electrolyzer power, the least squares polynomial fitting method was used to fit the collected single-stack PEMEL hydrogen production device efficiency and electrolyzer power data to obtain the corresponding electrolyzer overall efficiency function; (3) The power allocation strategy aims to optimize the hydrogen production of MPES and the efficiency of the hydrogen production device. The reference power value is calculated based on the DBO algorithm to optimize the power allocation strategy and improve the hydrogen production and overall efficiency. (4) The proposed power allocation method is added to a photovoltaic hydrogen production system consisting of four identical PEM electrolyzers, and the effect of the power allocation method is verified through simulation.

2. The power allocation method for a multi-stack parallel PEM solar hydrogen system considering the efficiency and hydrogen production of the electrolysis device according to claim 1 is characterized in that: The efficiency function of the electrolysis device is obtained by fitting the efficiency of the single-stack PEMEL electrolysis device with power after comprehensively considering the electrolysis efficiency, Faraday efficiency and the efficiency of the auxiliary equipment of the electrolysis system using the least squares method: Through the relationship between the efficiency of the electrolysis device of the single-stack PEMEL system and the power of the electrolyzer, the constraint relationship between the overall efficiency of the MPES system and the output power of the PV power supply is established as follows: Where: f (total) is the overall efficiency of the MPES system; P1, P2, …, P n is the power of each electrolytic cell; f (P1), f (P2), …, f (Pn) are the electrolysis device efficiencies corresponding to the real-time power of each electrolytic cell; P PV is the total output power of the photovoltaic power source.

3. The power allocation method for a multi-stack parallel PEM solar hydrogen system considering the efficiency and hydrogen production of the electrolysis device according to claim 2 is characterized in that: Taking the efficiency and hydrogen production of the electrolysis device as the target, the offline reference power value is calculated based on the DBO algorithm to optimize the power allocation strategy of the multi-stack electrolyzer system. The objective function expression is: Where: K c,i , K p,i is the penalty coefficient; M H2,i represents the hydrogen production of the ith PEMEL; f (total),i is the power of the ith PEMEL electrolyzer.

Images