Optimization control system of multi-class coupling hydrogen production system based on wind-solar complementation

Abstract

The invention discloses an optimal control system of a multi-class coupling hydrogen production system based on wind-solar complementation, and relates to the technical field of industrial hydrogen production, an energy source module of the system monitors external environment data in real time, generates a first data set, provides key wind energy and solar energy information for the system, facilitates energy supply prediction, and improves the energy utilization rate. The wind-solar cooperative control module carries out complementary adjustment according to the first data set, the power output efficiency is maximized, the energy utilization rate is further improved, and therefore the overall performance of the hydrogen production system is improved; the electrolytic hydrogen production data acquisition module monitors electrolytic state data in real time, establishes an energy data set, provides key parameters in the electrolytic hydrogen production process for the system, and is beneficial to comprehensively understanding the state of an electrolyzer. The supply fluctuation analysis module obtains a supply evaluation index Gyzs through feature extraction and machine learning calculation, deep analysis of the supply condition is achieved, and a basis for intelligent decision making is provided for the system.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial hydrogen production, and specifically to an optimization control system for multiple types of coupled hydrogen production systems based on wind-solar complementarity. Background Art

[0002] In the field of energy and environmental protection, hydrogen energy, as a clean and efficient energy carrier, has broad application prospects. Specifically, this technology has a far-reaching impact in the field of industrial hydrogen production. Traditional hydrogen production methods usually rely on fossil fuels, while the multi-type coupled hydrogen production system based on wind and solar complementarity directly converts clean energy into hydrogen by utilizing wind and solar energy, thus achieving clean production of hydrogen. This is of great significance for solving problems such as carbon emissions and resource consumption in the traditional hydrogen production process.

[0003] However, current hydrogen production still has some shortcomings. Traditional hydrogen production methods often rely on the stability of energy supply, and the wind-solar hybrid system is subject to natural factors such as weather, so its energy output is volatile, which leads to the instability of hydrogen production, which may lead to a mismatch between supply and demand, affect production efficiency, and cannot be flexibly adjusted according to the volatility of energy supply, affecting the electrolysis efficiency and even the life of the water electrolyzer. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the deficiencies in the prior art, the present invention provides an optimization control system for multiple types of coupled hydrogen production systems based on wind-solar complementarity, which solves the problems in the above-mentioned background technology.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: an optimization control system for multiple types of coupled hydrogen production systems based on wind-solar complementarity, including an energy source module, a wind-solar coordinated control module, an electrolytic hydrogen production data acquisition module, a supply fluctuation analysis module, and a hydrogen production optimization module;

[0008] The energy source module is used to monitor in real time the impact of external environmental data information on the conversion of wind energy and solar energy into electrical energy, generate a first data set, and integrate the electrical energy generated by wind energy and solar energy into a total power output;

[0009] The wind-solar coordinated control module is used to complementarily adjust the wind turbine and the photovoltaic array according to the first data group to maximize the power output efficiency;

[0010] The electrolysis hydrogen production data acquisition module is used to monitor and record relevant electrolysis state data information in the electrolysis hydrogen production process in real time, and generate a second data group, and establish an energy data set by combining the first data group and the second data group;

[0011] The supply fluctuation analysis module is used to extract features from relevant data information in the energy data set to obtain wind energy output factor Fsyz, light energy output factor Gsyz, current density Dlmd and electrolyte concentration Djnd, and obtain energy availability coefficient Nkxs by associating the wind energy output factor Fsyz with the light energy output factor Gsyz, obtain electrolysis state coefficient Ztxs by associating the current density Dlmd with the electrolyte concentration Djnd, and obtain supply evaluation index Gyzs by fitting and calculating using machine learning analysis;

[0012] The hydrogen production optimization module is used to pre-set the evaluation threshold V, and compare and analyze it with the supply evaluation index Gyzs to obtain a supply level report, and automatically adjust and control the internal parameters of the electrolysis device according to the corresponding level report.

[0013] Preferably, the energy source module includes a wind energy monitoring unit and a solar energy monitoring unit;

[0014] The first data group includes wind energy environment data information and solar energy environment data information;

[0015] The wind energy monitoring unit is used to monitor the wind energy environment data information around the wind farm, including the equipment height Sbgd, wind speed value Fsz, air density Kmd and wind speed change frequency Fbpl;

[0016] The solar energy monitoring unit is used to monitor the solar energy environment data information around the photovoltaic panel in real time, including sunshine hours Rscz, solar altitude angle Gdj, cloud coverage Yfgz and sunshine intensity Rzqd.

[0017] Preferably, the wind-solar coordinated control module includes a wind turbine control unit and a photovoltaic control unit;

[0018] The wind turbine control unit is used to monitor and adjust the speed and blade angle of the wind turbine in real time according to the real-time wind speed changes and wind turbine characteristics, and integrate the electric energy generated by the wind into the total power output;

[0019] The photovoltaic control unit is used to control the working state of the photovoltaic array, adjust the angle of the photovoltaic panel according to the light intensity and temperature, and integrate the electric energy generated by solar energy into the total power output.

[0020] Preferably, the electrolysis hydrogen production data acquisition module includes an extreme state unit and an electrolytic cell internal state unit;

[0021] The extreme state unit is used to monitor the current density Dlmd, electrolyte concentration Djnd, operation time Yscv and electrolyzer operation rate Yxsl at both ends of the water electrolyzer in real time;

[0022] The electrolytic cell internal state unit is used to monitor the liquid level Ywz in the electrolytic cell in real time through a float-type liquid level sensor, and to monitor the electrolyte temperature Dywd through a temperature sensor.

[0023] Preferably, the supply fluctuation analysis module includes an energy supply analysis unit, a water electrolysis analysis unit and a related analysis unit;

[0024] The energy supply analysis unit includes a wind energy subunit and a solar energy subunit;

[0025] The wind energy subunit is used to obtain the wind energy output factor Fsyz according to the wind energy environment data information by associating the wind speed change frequency Fbpl with the air density Kmd and performing dimensionless processing. The wind energy output factor Fsyz is obtained by the following formula:

[0026]

[0027] Wherein, Fsz represents the wind speed value, Sbgd represents the equipment height, a1, a2, a3 and a4 represent the preset proportional coefficients of the wind speed value Fsz, the air density Kmd, the wind speed change frequency Fbpl and the equipment height Sbgd respectively, and A represents the first correction constant;

[0028] The solar energy subunit is used to obtain the light energy output factor Gsyz according to the solar energy environment data information by associating the sunshine intensity Rzqd and the cloud coverage rate Yfgz and performing dimensionless processing. The light energy output factor Gsyz is obtained by the following formula:

[0029]

[0030] Wherein, Gdj represents the solar altitude angle, Rscz represents the sunshine hours, b1, b2, b3 and b4 represent the preset proportional coefficients of cloud coverage Yfgz, sunshine intensity Rzqd, solar altitude angle Gdj and sunshine hours Rscz respectively, and B represents the second correction constant.

[0031] Preferably, the energy availability coefficient Nkxs is obtained by associating the light energy output factor Gsyz with the wind energy output factor Fsyz and performing dimensionless processing. The energy availability coefficient Nkxs is obtained by the following formula:

[0032] Nkxs=Gsyz*α+Fsyz*β;

[0033] Wherein, α and β represent the preset proportional coefficients of the light energy output factor Gsyz and the wind energy output factor Fsyz respectively.

[0034] Preferably, a threshold value E is preset, and the energy availability coefficient Nkxs is compared and analyzed with the threshold value E to determine whether the current total power output is normal;

[0035] If the energy availability coefficient Nkxs ≥ the threshold E, it indicates that the current total power output is in a normal state;

[0036] If the energy availability coefficient Nkxs is less than the threshold value E, it indicates that the current total power output is in an abnormal state.

[0037] Preferably, the water electrolysis analysis unit is used to obtain an electrolysis state coefficient Ztxs based on the second data group by associating the current density Dlmd with the electrolyte concentration Djnd after dimensionless processing, and the electrolysis state coefficient Ztxs is obtained by the following formula:

[0038]

[0039] In the formula, Yscv represents the operating time, Yxsl represents the electrolyzer operating rate, Ywz represents the liquid level, Dywd represents the electrolyte temperature, j, t, y, s, f and k represent the preset proportional coefficients of electrolyte concentration Djnd, current density Dlmd, operating time Yscv, electrolyzer operating rate Yxsl, liquid level Ywz and electrolyte temperature Dywd respectively, and C represents the third correction constant.

[0040] Preferably, the correlation analysis unit is used to correlate the electrolysis state coefficient Ztxs with the energy availability coefficient Nkxs, analyze and fit to obtain the supply evaluation index Gyzs, and the supply evaluation index Gyzs is obtained by the following formula:

[0041]

[0042] Preferably, a supply level report is obtained by comparing and analyzing the supply evaluation index Gyzs with the evaluation threshold V, wherein the specific content of the supply level report is as follows:

[0043] If the supply evaluation index Gyzs is greater than the evaluation threshold V, that is, Gyzs>V, a first supply level is generated, indicating that the total power output generated by the current wind-solar complementarity cannot meet the current demand for water electrolysis hydrogen production. At this time, according to the real-time changes in power supply, the power output of water electrolysis hydrogen production and the operating parameters of the water electrolyzer are dynamically adjusted, including the current density, temperature and continuous operation cycle, to adapt to the real-time power supply conditions;

[0044] If the supply evaluation index Gyzs is equal to the evaluation threshold V, that is, Gyzs=V, a second supply level is generated, indicating that the total power output generated by the current wind-solar complementarity can supply the current demand for water electrolysis hydrogen production. At this time, the wind-solar power supply status and water electrolysis hydrogen production will continue to be monitored;

[0045] If the supply evaluation index Gyzs is less than the evaluation threshold V, that is, Gyzs<V, a third supply level is generated, indicating that the total power output generated by the current wind-solar complementarity can supply the current demand for hydrogen production by water electrolysis. At this time, excess electricity is stored to supply the total power output generated by the wind-solar complementarity in an abnormal state.

[0046] (III) Beneficial effects

[0047] The present invention provides an optimization control system for multiple types of coupled hydrogen production systems based on wind-solar complementarity, which has the following beneficial effects:

[0048] (1) The energy source module of the system monitors the external environment data in real time and generates the first data group, which provides the system with key wind and solar energy information and helps predict energy supply. The wind-solar coordinated control module makes complementary adjustments based on the first data group to maximize the power output efficiency and further improve energy utilization, thereby improving the overall performance of the hydrogen production system; the electrolysis hydrogen production data acquisition module monitors the electrolysis state data in real time and establishes an energy data set, which provides the system with key parameters in the electrolysis hydrogen production process and helps to fully understand the electrolyzer state. The supply fluctuation analysis module obtains the supply evaluation index Gyzs through feature extraction and machine learning calculation, realizes in-depth analysis of the supply situation, and provides a basis for intelligent decision-making for the system. The hydrogen production optimization module compares and analyzes the evaluation threshold V and the supply evaluation index Gyzs to realize automatic adjustment of the internal parameters of the electrolysis device, ensuring stable operation of the system under different energy supply conditions and improving electrolysis efficiency. In short, on the basis of reducing carbon emissions and rationally utilizing renewable energy, this system, through the complementarity of electricity between renewable energy sources, accurately compares the supply and demand of water electrolysis hydrogen production with the current electricity generated by wind and solar complementarity. Under limited electricity, by timely adjusting the various parameters in the water electrolyzer and electrolytic cell, the water electrolysis hydrogen production process can be more adaptable to the fluctuations of wind and solar energy, thereby improving the hydrogen production efficiency.

[0049] (2) Conduct a comprehensive analysis of the electricity generated by wind and solar energy to determine whether the current power output is in a normal state, to prevent the power output from being too low, which would cause startup damage to the water electrolyzer. This step will further consider the service life of the electrolysis equipment.

[0050] (3) The supply level report covers the degree of match between the system power supply status and the demand for water electrolysis hydrogen production. Corresponding strategies are adopted according to different levels to maximize the match between power supply and water electrolysis hydrogen production demand, thereby improving the overall efficiency of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a schematic diagram of the flow chart of the optimization control system of the multi-type coupled hydrogen production system based on wind-solar complementarity in the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] In the field of energy and environmental protection, hydrogen energy, as a clean and efficient energy carrier, has broad application prospects. Specifically, this technology has a far-reaching impact in the field of industrial hydrogen production. Traditional hydrogen production methods usually rely on fossil fuels, while the multi-type coupled hydrogen production system based on wind and solar complementarity directly converts clean energy into hydrogen by utilizing wind and solar energy, thus achieving clean production of hydrogen. This is of great significance for solving problems such as carbon emissions and resource consumption in the traditional hydrogen production process.

[0054] However, current hydrogen production still has some shortcomings. Traditional hydrogen production methods often rely on the stability of energy supply, and the wind-solar hybrid system is subject to natural factors such as weather, so its energy output is volatile, which leads to the instability of hydrogen production, which may lead to a mismatch between supply and demand, affect production efficiency, and cannot be flexibly adjusted according to the volatility of energy supply, affecting the electrolysis efficiency and even the life of the water electrolyzer.

[0055] Example 1

[0056] See also Figure 1 , the present invention provides an optimization control system for multiple types of coupled hydrogen production systems based on wind-solar complementarity, including an energy source module, a wind-solar coordinated control module, an electrolytic hydrogen production data acquisition module, a supply fluctuation analysis module, and a hydrogen production optimization module;

[0057] The energy source module is used to monitor in real time the impact of external environmental data information on the conversion of wind energy and solar energy into electrical energy, generate a first data set, and integrate the electrical energy generated by wind energy and solar energy into a total power output;

[0058] The wind-solar coordinated control module is used to complementarily adjust the wind turbine and the photovoltaic array according to the first data group to maximize the power output efficiency;

[0059] The electrolysis hydrogen production data acquisition module is used to monitor and record relevant electrolysis state data information in the electrolysis hydrogen production process in real time, and generate a second data group, and establish an energy data set by combining the first data group and the second data group;

[0060] The supply fluctuation analysis module is used to extract features from relevant data information in the energy data set to obtain wind energy output factor Fsyz, light energy output factor Gsyz, current density Dlmd and electrolyte concentration Djnd, and obtain energy availability coefficient Nkxs by associating the wind energy output factor Fsyz with the light energy output factor Gsyz, obtain electrolysis state coefficient Ztxs by associating the current density Dlmd with the electrolyte concentration Djnd, and obtain supply evaluation index Gyzs by fitting and calculating using machine learning analysis;

[0061] The hydrogen production optimization module is used to pre-set the evaluation threshold V, and compare and analyze it with the supply evaluation index Gyzs to obtain a supply level report, and automatically adjust and control the internal parameters of the electrolysis device according to the corresponding level report.

[0062] During the operation of this system, through real-time monitoring of external environmental data, the converted electricity from wind and solar energy can be efficiently integrated into the total power output, providing a reliable energy source for the production of clean hydrogen. Among them, the wind-solar collaborative control module realizes the complementary adjustment of wind turbines and photovoltaic arrays according to external data, maximizes the power output efficiency, and further improves the overall performance of the system; the electrolysis hydrogen production data acquisition module monitors and records the key electrolysis state data in the electrolysis hydrogen production process in real time, providing basic data for subsequent optimization. Through the supply fluctuation analysis module, the system can analyze and extract key data such as wind energy output factor Fsyz, light energy output factor Gsyz, current density Dlmd, and electrolyte concentration Djnd. These data are analyzed and calculated through machine learning to obtain the supply evaluation index Gyzs, which provides the system with real-time energy availability evaluation, making the hydrogen production process more intelligent and adaptable. The hydrogen production optimization module automatically adjusts and controls the internal parameters of the electrolysis device by comparing and analyzing the pre-set evaluation threshold V with the supply evaluation index Gyzs. Such an optimization control system can enable the hydrogen production process to run smoothly under different energy supply conditions, maximize electrolysis efficiency, indirectly extend equipment life, and reduce energy waste; by utilizing wind and solar energy, clean production of hydrogen can be achieved, reducing dependence on traditional fossil fuels and reducing carbon emissions. The synergy of the wind-solar collaborative control module and the supply fluctuation analysis module enables the system to flexibly and efficiently utilize renewable energy. The hydrogen production optimization module realizes intelligent adjustment of electrolysis parameters through real-time supply evaluation index analysis, improves the adaptability and intelligence level of the system, and reduces energy waste and improves electrolysis efficiency, making the system not only more economical but also more sustainable.

[0063] Example 2

[0064] Please refer to Figure 1 ,Specifically: the energy source module includes a wind energy monitoring unit and a solar energy monitoring unit, which monitor the wind energy and solar energy conditions of the external environment in real time;

[0065] The first data group includes wind energy environment data information and solar energy environment data information;

[0066] The wind energy monitoring unit is used to monitor the wind energy environment data information around the wind farm, including the equipment height Sbgd, wind speed value Fsz, air density Kmd and wind speed change frequency Fbpl;

[0067] The solar energy monitoring unit is used to monitor the solar energy environment data information around the photovoltaic panel in real time, including sunshine hours Rscz, solar altitude angle Gdj, cloud coverage Yfgz and sunshine intensity Rzqd.

[0068] The wind-solar coordinated control module includes a wind turbine control unit and a photovoltaic control unit to achieve coordinated control of wind power generation and photovoltaic power generation;

[0069] The wind turbine control unit is used to monitor and adjust the speed and blade angle of the wind turbine in real time according to the real-time wind speed changes and wind turbine characteristics, and integrate the electric energy generated by the wind into the total power output;

[0070] The photovoltaic control unit is used to control the working state of the photovoltaic array, adjust the angle of the photovoltaic panel according to the light intensity and temperature, and integrate the electric energy generated by solar energy into the total power output.

[0071] In this embodiment, the wind-solar collaborative control module enables the system to flexibly and efficiently utilize renewable energy under different environmental conditions through real-time wind and solar energy monitoring, thereby further improving the total power output efficiency. The intelligent adjustment of the wind turbine and photovoltaic control unit can automatically optimize the working state of the power generation equipment according to real-time changes in the external environment, making the system more adaptable to energy fluctuations. Through wind-solar collaborative control, the system can further achieve stable total power output, reduce the instability of electric energy, reduce the instability of hydrogen production caused by wind and solar energy fluctuations, and improve production efficiency. Dynamic adjustment of the working state of wind turbines and photovoltaic panels helps to avoid energy waste and ensure that the system can maximize the use of renewable energy under any environmental conditions.

[0072] Example 3

[0073] Please refer to Figure 1 , specifically: the electrolysis hydrogen production data acquisition module includes an extreme state unit and an electrolytic cell state unit;

[0074] The extreme state unit is used to monitor the current density Dlmd, electrolyte concentration Djnd, operation time Yscv and electrolyzer operation rate Yxsl at both ends of the water electrolyzer in real time. The system can obtain important parameters in the electrolysis process in real time.

[0075] Monitoring the current density Dlmd helps to understand the current distribution during the electrolysis process and can be used to adjust the electrolysis parameters to optimize the hydrogen production efficiency;

[0076] Real-time monitoring of electrolyte concentration Djnd can reflect changes in electrolyte concentration and provide information on the electrolyte state during hydrogen production;

[0077] The monitoring of the operating time Yscv and the electrolyzer operating rate Yxsl can be used to evaluate the stability and life of the electrolyzer, as well as the real-time status of hydrogen production capacity;

[0078] The state unit in the electrolytic cell is used to monitor the liquid level Ywz in the electrolytic cell in real time through a float-type liquid level sensor. The system can understand the changes in the liquid level in the electrolytic cell in real time, thereby maintaining the stability of the liquid level in the electrolytic cell. At the same time, the temperature sensor is used to monitor the electrolyte temperature Dywd.

[0079] In this embodiment, through real-time monitoring of the extreme state unit and the state unit in the electrolytic cell, the system can keep track of the key parameters in the electrolysis process at any time, which helps to achieve dynamic adjustment and optimization of the electrolysis process. By monitoring the current density Dlmd and the electrolyte concentration Djnd, the system can adjust the electrolysis parameters according to the real-time situation to maximize the efficiency of hydrogen production by electrolysis. By real-time monitoring of the liquid level Ywz in the electrolytic cell by the liquid level sensor, the system can maintain the stability of the liquid level, prevent the liquid level in the electrolytic cell from fluctuating, and help stabilize the hydrogen production process.

[0080] Example 4

[0081] Please refer to Figure 1 ,Specifically: the supply fluctuation analysis module includes an energy supply analysis unit, a water electrolysis analysis unit and a related analysis unit;

[0082] The energy supply analysis unit includes a wind energy subunit and a solar energy subunit;

[0083] The wind energy subunit is used to obtain the wind energy output factor Fsyz according to the wind energy environment data information by associating the wind speed change frequency Fbpl with the air density Kmd and performing dimensionless processing. The wind energy output factor Fsyz is obtained by the following formula:

[0084]

[0085] Wherein, Fsz represents the wind speed value, Sbgd represents the equipment height, a1, a2, a3 and a4 represent the preset proportional coefficients of the wind speed value Fsz, the air density Kmd, the wind speed change frequency Fbpl and the equipment height Sbgd, respectively, wherein 0.10≤a1≤0.24, 0.12≤a2≤0.17, 0.03≤a3≤0.34, 0.05≤a4≤0.25, and 0.40≤a1+a2+a3+a4≤1.0, and A represents the first correction constant;

[0086] The above wind speed value Fsz is collected and obtained through a wind speed sensor;

[0087] The air density Kmd is collected and obtained through a weather station or an atmospheric density meter;

[0088] The wind speed change frequency Fbpl is monitored and obtained through a wind speed sensor or a frequency meter;

[0089] The equipment height Sbgd is acquired through a laser rangefinder or an altimeter;

[0090] The solar energy subunit is used to obtain the light energy output factor Gsyz according to the solar energy environment data information by associating the sunshine intensity Rzqd and the cloud coverage rate Yfgz and performing dimensionless processing. The light energy output factor Gsyz is obtained by the following formula:

[0091]

[0092] Wherein, Gdj represents the solar altitude angle, Rscz represents the sunshine hours, b1, b2, b3 and b4 represent the preset proportional coefficients of cloud coverage Yfgz, sunshine intensity Rzqd, solar altitude angle Gdj and sunshine hours Rscz, respectively, wherein, 0.16≤b1≤0.42, 0.05≤b2≤0.21, 0.03≤b3≤0.16, 0.06≤b4≤0.21, and 0.35≤b1+b2+b3+b4≤1.0, and B represents the second correction constant.

[0093] The above cloud coverage rate Yfgz is collected and obtained through meteorological satellites;

[0094] The sunshine intensity Rzqd is collected and obtained through a light sensor or a solar radiometer;

[0095] The solar altitude angle Gdj is monitored and obtained through a solar altitude angle meter;

[0096] The sunshine hours Rscz are collected and obtained through a sunshine meter;

[0097] In this embodiment, through the analysis of the wind energy subunit and the solar energy subunit, the system can more accurately predict the fluctuations in wind and solar energy production capacity, and provide more accurate energy supply information for the hydrogen production process; by comprehensively considering the light energy output factor Gsyz and the wind energy output factor Fsyz, the system can better cope with energy fluctuations, further improve the stability of the system, and reduce the mismatch between supply and demand. According to the changes in the energy output factor, the hydrogen production optimization module can flexibly adjust the electrolysis parameters to make the water electrolysis hydrogen production process more adaptable to the fluctuations of wind and solar energy and improve the efficiency of hydrogen production. The supply fluctuation analysis module enables the system to more intelligently cope with the fluctuations of wind and solar energy, improve energy utilization, and ensure the smooth operation of the hydrogen production process.

[0098] Example 5

[0099] Please refer to Figure 1Specifically, by associating the light energy output factor Gsyz with the wind energy output factor Fsyz and performing dimensionless processing, the energy availability coefficient Nkxs is obtained. The energy availability coefficient Nkxs is obtained by the following formula:

[0100] Nkxs=Gsyz*α+Fsyz*β;

[0101] In the formula, α and β represent the preset proportional coefficients of the light energy output factor Gsyz and the wind energy output factor Fsyz, respectively, wherein 0.10≤α≤0.50, 0.12≤β≤0.50.

[0102] A threshold value E is preset, and the energy availability coefficient Nkxs is compared and analyzed with the threshold value E to determine whether the current total power output is normal;

[0103] If the energy availability coefficient Nkxs ≥ the threshold E, it indicates that the current total power output is in a normal state;

[0104] If the energy availability coefficient Nkxs is less than the threshold value E, it indicates that the current total power output is in an abnormal state.

[0105] In this embodiment, the introduction of the energy availability coefficient Nkxs enables the system to monitor the contribution of wind and solar energy to the total power output in real time, and to understand the energy status of the system in a more timely manner; by comparing it with the preset threshold E, the system can quickly determine whether the current total power output is normal, which helps to take timely measures to maintain the stable operation of the system. The calculation of the energy availability coefficient Nkxs takes into account many factors, improves the robustness of the system to complex environmental changes, and makes full preparations for the system to be more adaptable and robust. At the same time, it enables the system to more intelligently evaluate and respond to the fluctuations of wind and solar energy, improve energy utilization efficiency, and ensure the reliability of the system under different environmental conditions.

[0106] Example 6

[0107] Please refer to Figure 1 Specifically: the water electrolysis analysis unit is used to obtain the electrolysis state coefficient Ztxs based on the second data group and by associating the current density Dlmd with the electrolyte concentration Djnd after dimensionless processing. The electrolysis state coefficient Ztxs is obtained by the following formula:

[0108]

[0109] In the formula, Yscv represents the operating time, Yxsl represents the electrolyzer operating rate, Ywz represents the liquid level, Dywd represents the electrolyte temperature, j, t, y, s, f and k represent the preset proportional coefficients of the electrolyte concentration Djnd, the current density Dlmd, the operating time Yscv, the electrolyzer operating rate Yxsl, the liquid level Ywz and the electrolyte temperature Dywd, respectively, wherein 0.04≤j≤0.15, 0.05≤t≤0.12, 0.05≤y≤0.21, 0.07≤s≤0.30, 0.02≤f≤0.10, 0.04≤k≤0.12, and 0.35≤j+t+y+s+f+k≤1.0, and C represents the third correction constant.

[0110] The electrolyte concentration Djnd is monitored and obtained by a concentration sensor or a refractometer;

[0111] The current density Dlmd is monitored and obtained by a current density sensor or an ammeter;

[0112] The running time Yscv is monitored and obtained through a timer or a running time recorder;

[0113] The electrolyzer operation rate Yxsl is collected and obtained through a rate sensor or a tachometer;

[0114] The liquid level Ywz is collected and obtained through a liquid level sensor or a float-type liquid level gauge;

[0115] The electrolyte temperature Dywd is monitored and obtained by a temperature sensor or an infrared thermometer;

[0116] In this embodiment, by introducing the electrolysis state coefficient Ztxs, the system can have a more comprehensive understanding of the operating status of the water electrolyzer, which helps to promptly discover possible problems with the electrolyzer's supply of power to the retaining wall, and improve the electrolysis efficiency by adjusting parameters, thereby ensuring the efficient operation of the water electrolysis hydrogen production process; by monitoring the electrolysis state coefficient Ztxs, the system can realize intelligent adjustment of the internal parameters of the water electrolyzer, improve the system's adaptability and stability, and ensure the reliability of the system during long-term operation.

[0117] Example 7

[0118] Please refer to Figure 1 Specifically: the correlation analysis unit is used to associate the electrolysis state coefficient Ztxs with the energy availability coefficient Nkxs, analyze and fit to obtain the supply evaluation index Gyzs, and the supply evaluation index Gyzs is obtained by the following formula:

[0119]

[0120] A supply level report is obtained by comparing and analyzing the supply evaluation index Gyzs with the evaluation threshold V, wherein the specific content of the supply level report is as follows:

[0121] If the supply evaluation index Gyzs is greater than the evaluation threshold V, that is, Gyzs>V, a first supply level is generated, indicating that the total power output generated by the current wind-solar complementarity cannot meet the current demand for water electrolysis hydrogen production. At this time, according to the real-time changes in power supply, the power output of water electrolysis hydrogen production and the operating parameters of the water electrolyzer are dynamically adjusted, including the current density, temperature and continuous operation cycle, to adapt to the real-time power supply conditions;

[0122] If the supply evaluation index Gyzs is equal to the evaluation threshold V, that is, Gyzs=V, a second supply level is generated, indicating that the total power output generated by the current wind-solar complementarity can supply the current demand for water electrolysis hydrogen production. At this time, the wind-solar power supply status and water electrolysis hydrogen production will continue to be monitored;

[0123] If the supply evaluation index Gyzs is less than the evaluation threshold V, that is, Gyzs<V, a third supply level is generated, indicating that the total power output generated by the current wind-solar complementarity can supply the current demand for hydrogen production by water electrolysis. At this time, excess electricity is stored to supply the total power output generated by the wind-solar complementarity in an abnormal state.

[0124] In this embodiment, through the calculation of the supply evaluation index Gyzs and the generation of the grade report, the system realizes the real-time monitoring and adaptive adjustment of the power supply status and the demand for hydrogen production by water electrolysis, ensuring the efficient operation of the system under different circumstances. The system dynamically adjusts the parameters of hydrogen production by water electrolysis to maximize the matching of power supply and the demand for hydrogen production by water electrolysis, thereby improving the overall efficiency of the system. When there is excess electricity, the system stores it, realizes the optimal use of electricity, and improves the energy efficiency of the system. Through the above content, the introduction of the supply evaluation index Gyzs enables the system to respond to power fluctuations and changes in demand for hydrogen production by water electrolysis more intelligently, thereby ensuring the stable operation of the system and improving the efficiency of hydrogen production.

[0125] Example: A certain hydrogen production plant has introduced an optimization control system based on wind-solar hybrid multi-type coupled hydrogen production systems. The following is an example of a certain hydrogen production plant:

[0126] Data collection: wind speed value Fsz is 12; air density Kmd is 4.5; wind speed change frequency Fbpl is 68%; equipment height Sbgd is 17.56;

[0127] Preset proportional coefficients: a1 is 0.15; a2 is 0.13; a3 is 0.21; a4 is 0.16; the first correction constant A is 0.72;

[0128] The cloud coverage rate Yfgz is 48%; the sunshine intensity Rzqd is 6.41; the solar altitude angle Gdj is 62.1; the sunshine hours Rscz is 7;

[0129] Preset proportional coefficients: b1 is 0.22; b2 is 0.14; b3 is 0.06; b4 is 0.10; the second correction constant B is 0.77;

[0130] Preset proportional coefficient: α is 0.21; β is 0.23;

[0131] The electrolyte concentration Djnd is 2.5; the current density Dlmd is 6.2; the operating time Yscv is 14.2; the electrolyzer operating rate Yxsl is 75%; the liquid level Ywz is 5.4; the electrolyte temperature Dywd is 27;

[0132] Preset proportional coefficients: j is 0.05; t is 0.06; y is 0.15; s is 0.11; f is 0.06; k is 0.05; the third correction constant C is 0.49;

[0133] With the above data, the following calculations can be performed:

[0134] Wind energy output factor

[0135] Light output factor

[0136] Energy availability coefficient Nkxs = 4*0.21+9*0.23 = 2.07+0.84 = 2.91;

[0137] If the threshold value E is 3, the energy availability coefficient Nkxs < the threshold value E, indicating that the current total power output is in an abnormal state;

[0138] Electrolyte concentration

[0139]

[0140] Supply Assessment Index

[0141] If the evaluation threshold V is 7, the supply evaluation index Gyzs is greater than the evaluation threshold V, that is, Gyzs>V, and the first supply level is generated, indicating that the total power output generated by the current wind-solar complementarity cannot meet the current demand for water electrolysis hydrogen production. At this time, according to the real-time changes in power supply, the power output of water electrolysis hydrogen production and the operating parameters of the water electrolyzer are dynamically adjusted, including the current density, temperature and continuous operation cycle, to adapt to the real-time power supply conditions.

[0142] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An optimization control system based on wind-solar hybrid multi-coupled hydrogen production system, characterized by: It includes energy source module, wind-solar coordinated control module, electrolysis hydrogen production data acquisition module, supply fluctuation analysis module, and hydrogen production optimization module; The energy source module is used to monitor in real time the impact of external environmental data information on the conversion of wind energy and solar energy into electrical energy, generate a first data set, and integrate the electrical energy generated by wind energy and solar energy into a total power output; The wind-solar coordinated control module is used to complementarily adjust the wind turbine and the photovoltaic array according to the first data group to maximize the power output efficiency; The electrolysis hydrogen production data acquisition module is used to monitor and record relevant electrolysis state data information in the electrolysis hydrogen production process in real time, and generate a second data group, and establish an energy data set by combining the first data group and the second data group; The supply fluctuation analysis module is used to extract features from relevant data information in the energy data set to obtain wind energy output factor Fsyz, light energy output factor Gsyz, current density Dlmd and electrolyte concentration Djnd, and obtain energy availability coefficient Nkxs by associating the wind energy output factor Fsyz with the light energy output factor Gsyz, obtain electrolysis state coefficient Ztxs by associating the current density Dlmd with the electrolyte concentration Djnd, and obtain supply evaluation index Gyzs by fitting and calculating using machine learning analysis; The hydrogen production optimization module is used to pre-set the evaluation threshold V, and compare and analyze it with the supply evaluation index Gyzs to obtain a supply level report, and automatically adjust and control the internal parameters of the electrolysis device according to the corresponding level report.

2. The optimization control system of the multi-type coupled hydrogen production system based on wind-solar complementarity according to claim 1 is characterized in that: The energy source module includes a wind energy monitoring unit and a solar energy monitoring unit; The first data group includes wind energy environment data information and solar energy environment data information; The wind energy monitoring unit is used to monitor the wind energy environment data information around the wind farm, including the equipment height Sbgd, wind speed value Fsz, air density Kmd and wind speed change frequency Fbpl; The solar energy monitoring unit is used to monitor the solar energy environment data information around the photovoltaic panel in real time, including sunshine hours Rscz, solar altitude angle Gdj, cloud coverage Yfgz and sunshine intensity Rzqd.

3. The optimization control system of the multi-type coupled hydrogen production system based on wind-solar complementarity according to claim 1 is characterized in that: The wind-solar coordinated control module includes a wind turbine control unit and a photovoltaic control unit; The wind turbine control unit is used to monitor and adjust the speed and blade angle of the wind turbine in real time according to the real-time wind speed changes and wind turbine characteristics, and integrate the electric energy generated by the wind into the total power output; The photovoltaic control unit is used to control the working state of the photovoltaic array, adjust the angle of the photovoltaic panel according to the light intensity and temperature, and integrate the electric energy generated by solar energy into the total power output.

4. The optimization control system of the multi-type coupled hydrogen production system based on wind-solar complementarity according to claim 2 is characterized in that: The electrolysis hydrogen production data acquisition module includes an extreme state unit and an electrolytic cell internal state unit; The extreme state unit is used to monitor the current density Dlmd, electrolyte concentration Djnd, operation time Yscv and electrolyzer operation rate Yxsl at both ends of the water electrolyzer in real time; The electrolytic cell internal state unit is used to monitor the liquid level Ywz in the electrolytic cell in real time through a float-type liquid level sensor, and to monitor the electrolyte temperature Dywd through a temperature sensor.

5. The optimization control system of the multi-type coupled hydrogen production system based on wind-solar complementarity according to claim 4 is characterized in that: The supply fluctuation analysis module includes an energy supply analysis unit, a water electrolysis analysis unit and an associated analysis unit; The energy supply analysis unit includes a wind energy subunit and a solar energy subunit; The wind energy subunit is used to obtain the wind energy output factor Fsyz according to the wind energy environment data information by associating the wind speed change frequency Fbpl with the air density Kmd and performing dimensionless processing. The wind energy output factor Fsyz is obtained by the following formula: Wherein, Fsz represents the wind speed value, Sbgd represents the equipment height, a1, a2, a3 and a4 represent the preset proportional coefficients of the wind speed value Fsz, the air density Kmd, the wind speed change frequency Fbpl and the equipment height Sbgd respectively, and A represents the first correction constant; The solar energy subunit is used to obtain the light energy output factor Gsyz according to the solar energy environment data information by associating the sunshine intensity Rzqd and the cloud coverage rate Yfgz and performing dimensionless processing. The light energy output factor Gsyz is obtained by the following formula: Wherein, Gdj represents the solar altitude angle, Rscz represents the sunshine hours, b1, b2, b3 and b4 represent the preset proportional coefficients of cloud coverage Yfgz, sunshine intensity Rzqd, solar altitude angle Gdj and sunshine hours Rscz respectively, and B represents the second correction constant.

6. The optimization control system of the multi-type coupled hydrogen production system based on wind-solar complementarity according to claim 5 is characterized in that: By associating the light energy output factor Gsyz with the wind energy output factor Fsyz and performing dimensionless processing, the energy availability coefficient Nkxs is obtained. The energy availability coefficient Nkxs is obtained by the following formula: Nkxs=Gsyz*α+Fsyz*β; Wherein, α and β represent the preset proportional coefficients of the light energy output factor Gsyz and the wind energy output factor Fsyz respectively.

7. The optimization control system of the multi-type coupled hydrogen production system based on wind-solar complementarity according to claim 6 is characterized by: A threshold value E is preset, and the energy availability coefficient Nkxs is compared and analyzed with the threshold value E to determine whether the current total power output is normal; If the energy availability coefficient Nkxs ≥ the threshold E, it indicates that the current total power output is in a normal state; If the energy availability coefficient Nkxs is less than the threshold value E, it indicates that the current total power output is in an abnormal state.

8. The optimization control system of the multi-type coupled hydrogen production system based on wind-solar complementarity according to claim 5 is characterized in that: The water electrolysis analysis unit is used to obtain the electrolysis state coefficient Ztxs according to the second data group by associating the current density Dlmd with the electrolyte concentration Djnd after dimensionless processing. The electrolysis state coefficient Ztxs is obtained by the following formula: In the formula, Yscv represents the operating time, Yxsl represents the electrolyzer operating rate, Ywz represents the liquid level, Dywd represents the electrolyte temperature, j, t, y, s, f and k represent the preset proportional coefficients of electrolyte concentration Djnd, current density Dlmd, operating time Yscv, electrolyzer operating rate Yxsl, liquid level Ywz and electrolyte temperature Dywd respectively, and C represents the third correction constant.

9. The optimization control system of the multi-type coupled hydrogen production system based on wind-solar complementarity according to claim 1 is characterized in that: The correlation analysis unit is used to correlate the electrolysis state coefficient Ztxs with the energy availability coefficient Nkxs, and obtain the supply evaluation index Gyzs by analysis and fitting. The supply evaluation index Gyzs is obtained by the following formula:

10. The optimization control system of the multi-type coupled hydrogen production system based on wind-solar complementarity according to claim 9 is characterized in that: A supply level report is obtained by comparing and analyzing the supply evaluation index Gyzs with the evaluation threshold V, wherein the specific content of the supply level report is as follows: If the supply evaluation index Gyzs is greater than the evaluation threshold V, that is, Gyzs>V, a first supply level is generated, indicating that the total power output generated by the current wind-solar complementarity cannot meet the current demand for water electrolysis hydrogen production. At this time, according to the real-time changes in power supply, the power output of water electrolysis hydrogen production and the operating parameters of the water electrolyzer are dynamically adjusted, including the current density, temperature and continuous operation cycle, to adapt to the real-time power supply conditions; If the supply evaluation index Gyzs is equal to the evaluation threshold V, that is, Gyzs=V, a second supply level is generated, indicating that the total power output generated by the current wind-solar complementarity can supply the current demand for water electrolysis hydrogen production. At this time, the wind-solar power supply status and water electrolysis hydrogen production will continue to be monitored; If the supply evaluation index Gyzs is less than the evaluation threshold V, that is, Gyzs<V, a third supply level is generated, indicating that the total power output generated by the current wind-solar complementarity can supply the current demand for hydrogen production by water electrolysis. At this time, excess electricity is stored to supply the total power output generated by the wind-solar complementarity in an abnormal state.

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