Wind power hydrogen production control system based on PLC intelligent control

Abstract

The invention discloses a wind power hydrogen production control system based on PLC intelligent control, and relates to the technical field of industrial automation control. During operation of the system, environment states are collected in real time through an environment module, an environment information group is formed, meteorological change information of a fixed period of a wind power generation equipment region is obtained in real time, and a meteorological information group is formed; the method comprises the following steps: acquiring power storage state information of power storage equipment in real time, forming a power storage information group, preprocessing through a processing module, forming a first data set, a second data set and a third data set, acquiring an equipment regulation index Dkzs through an equipment regulation evaluation module, matching the equipment regulation index Dkzs with a preset equipment regulation threshold D, and acquiring an equipment regulation evaluation strategy scheme. The method comprises the following steps of: performing specific execution including hydrogen production equipment adjustment and related personnel notification, thereby achieving the purpose of adaptively adjusting the hydrogen production equipment and the power storage equipment, further prolonging the service life of the storage battery, and effectively protecting the assets of the storage battery.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial automation control, and specifically to a wind power hydrogen production control system based on PLC intelligent control. Background Art

[0002] In recent years, in the field of renewable energy applications, wind power generation has developed rapidly. However, due to the energy supply fluctuations caused by natural conditions and the curtailment of wind power waste caused by grid load, at the same time, hydrogen, as an important industrial raw material and the power generation raw material for fuel cells, has received increasing attention. Using renewable energy to produce hydrogen has become an important way to solve the problem of wind curtailment.

[0003] At present, however, the currently widely used electrolytic water hydrogen production technology has high requirements for power stability, cannot fully match the volatility of renewable energy, and cannot meet the requirement of stable operation within a certain period of time. Moreover, various faults and losses are likely to occur during the frequent shutdown and startup process. Due to the uncertainty of wind speed in traditional wind power generation systems, it is difficult to accurately predict the wind energy output, resulting in reduced efficiency of the system under low wind speed or high volatility wind speed, and the maximum utilization of wind energy cannot be fully realized. At the same time, the traditional charge and discharge mode causes deep charge and discharge cycles of the battery, thereby shortening the service life of the battery and being unable to flexibly cope with the fluctuations of the battery power. In addition, the efficiency of the current water electrolysis reaction is limited by the difficulty of the system to flexibly adjust the power supply, resulting in fluctuations in hydrogen production efficiency under different environmental conditions. Summary of the Invention

[0004] (I) Technical Problems to be Solved

[0005] In view of the deficiencies of the prior art, the present invention provides a wind power hydrogen production control system based on PLC intelligent control, which solves the problems mentioned in the background art.

[0006] (II) Technical Solutions

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions: A wind power hydrogen production control system based on PLC intelligent control includes an environment acquisition module, a meteorological module, a storage device status module, a processing module, a device regulation and evaluation module, and a decision-making module;

[0008] The environment module collects the environmental status of the operation of the wind power generation equipment in real time through the environmental sensor group integrated in the wind power generation equipment to form an environmental information group;

[0009] The meteorological module obtains the meteorological change information of a fixed period in the region of the wind power generation equipment in real time through the Internet to form a meteorological information group;

[0010] The storage device status module collects the storage status information of the storage device in real time to form a storage information group;

[0011] The processing module preprocesses the environmental information group, meteorological information group, and electricity storage information group to form a first data set, a second data set, and a third data set;

[0012] The equipment regulation evaluation module establishes a power generation equipment prediction model for the first data set and the second data set, conducts training and analysis, and correlates with the third data set to obtain: an equipment regulation index Dkzs, and matches it with a preset equipment regulation threshold D to obtain an equipment regulation evaluation strategy plan;

[0013] The equipment regulation index Dkzs is obtained through the following calculation formula:

[0014] ;

[0015] In the formula, Hjxs represents the environmental coefficient of the power generation equipment, Qxxs represents the regional meteorological coefficient of the power generation equipment, Xdxs represents the state coefficient of the electricity storage equipment, d1, d2, and d3 respectively represent the proportionality coefficients of the environmental coefficient Hjxs of the power generation equipment, the regional meteorological coefficient Qxxs of the power generation equipment, and the state coefficient Xdxs of the electricity storage equipment, and C represents the first correction constant;

[0016] The environmental coefficient Hjxs of the power generation equipment is obtained by calculating through the first data set;

[0017] The regional meteorological coefficient Qxxs of the power generation equipment is obtained by calculating through the second data set, and is matched with a preset regional meteorological state threshold Q to obtain a future meteorological change plan for the power generation equipment area;

[0018] The state coefficient Xdxs of the electricity storage equipment is obtained by calculating through the third data set, and is matched with a preset operation state threshold X of the electricity storage equipment to obtain an operation state plan of the electricity storage equipment;

[0019] The decision-making module specifically executes according to the content of the equipment regulation evaluation strategy plan, including adjusting the hydrogen production equipment and notifying relevant personnel.

[0020] Preferably, the environment module includes a collection unit and a transmission unit;

[0021] The collection unit collects environmental data in real time through an environmental sensor group integrated on the wind power generation equipment, including wind speed information, wind direction information, number of wind direction changes, wind speed fluctuation frequency information, temperature information, and air pressure information, and then integrates them to form an environmental information group;

[0022] Among them, the environmental sensor group includes a wind speed sensor, a wind direction sensor, a temperature sensor, and an air pressure sensor;

[0023] The transmission unit transmits the environmental information group to the processing module, and the transmission methods include wireless network transmission, wired network transmission, Bluetooth transmission, and optical fiber transmission.

[0024] Preferably, the meteorological module includes a networking unit;

[0025] The networking unit executes a preset meteorological information acquisition script instruction by connecting to the Internet to obtain meteorological information within a future fixed period in the current power generation equipment area, including meteorological wind speed, meteorological wind direction, meteorological humidity, meteorological temperature, meteorological rainfall, and strong wind warning information, and forms a meteorological information group.

[0026] Preferably, the energy storage device status module includes an extraction unit;

[0027] The extraction unit real-time collects the status information of the energy storage device, including the charging power of the energy storage device, input voltage, output power value, charge and discharge status, battery capacity, and charging status information, and converts it into digital signals to form an energy storage information group.

[0028] Preferably, the processing module includes a normalization unit;

[0029] The normalization unit preprocesses the environmental information group, meteorological information group, and energy storage information group, including normalization processing and null value processing, integrates and statistically analyzes the processed environmental information group to form a first data set, integrates the processed meteorological information group to form a second data set, and integrates the processed energy storage information group to form a third data set;

[0030] The first data set includes: real-time wind speed value Ssfs, real-time wind direction Ssfx, wind speed fluctuation frequency value Fsbd, wind direction fluctuation frequency value Fxbd, maximum wind speed increase value Zjmax, and minimum wind speed decrease value Jdmin;

[0031] The second data set includes: meteorological wind speed value Qxfs, meteorological wind direction Qxfx, meteorological humidity value Qxsd, and altitude value Hbgd.

[0032] The third data set includes: charging power value Cdz, output power value Scz, total battery capacity value Zrl, and battery status value Ztz.

[0033] Preferably, the equipment regulation and evaluation module includes a modeling unit and a matching unit;

[0034] The modeling unit uses machine learning technology to establish a prediction model for the first data set and the second data set. After training and prediction analysis, the first calculation is performed to obtain: the environmental coefficient Hjxs of the power generation equipment and the regional meteorological coefficient Qxxs of the power generation equipment, which reflect the information on the change of the operating state of the wind power generation equipment within a fixed period, and the second calculation is performed on the third data set to obtain: the state coefficient Xdxs of the energy storage equipment. The environmental coefficient Hjxs of the power generation equipment, the regional meteorological coefficient Qxxs of the power generation equipment, and the state coefficient Xdxs of the energy storage equipment are correlated, and the third calculation is performed to obtain: the equipment regulation index Dkzs;

[0035] The matching unit matches the preset relevant information with the comparison value, including matching the preset equipment regulation threshold D with the equipment regulation index Dkzs to obtain the equipment regulation evaluation strategy plan.

[0036] Preferably, the first calculation includes: the calculation of the environmental coefficient Hjxs of the power generation equipment and the calculation of the regional meteorological coefficient Qxxs of the power generation equipment;

[0037] The environmental coefficient Hjxs of the power generation equipment is obtained through the following calculation formula:

[0038] ;

[0039] In the formula, Ssfs represents the real-time wind speed value, Ssfx represents the real-time wind direction, Fsbd represents the wind speed fluctuation frequency value, Fxbd represents the wind direction fluctuation frequency value, Zjmax represents the maximum wind speed increase value, Jdmin represents the minimum wind speed decrease value, h1, h2, h3, and h4 respectively represent the proportionality coefficients of the real-time wind speed value Ssfs, the real-time wind direction Ssfx, the wind speed fluctuation frequency value Fsbd, and the wind direction fluctuation frequency value Fxbd, h5 represents the proportionality coefficient of the difference between the maximum wind speed increase value Zjmax and the minimum wind speed decrease value Jdmin, and D represents the second correction constant;

[0040] Among them, , , , , ,and ;

[0041] The regional meteorological coefficient Qxxs of the power generation equipment is obtained through the following calculation formula:

[0042] ;

[0043] Wherein, Qxfs represents the meteorological wind speed value, Qxfx represents the meteorological wind direction, Qxsd represents the meteorological humidity value, Hbgd represents the altitude value, q1, q2, q3, and q4 respectively represent the proportionality coefficients of the meteorological wind speed value Qxfs, the meteorological wind direction Qxfx, the meteorological humidity value Qxsd, and the altitude value Hbgd, and K represents the third correction constant;

[0044] Among them, , , , , and ;

[0045] And it is matched with the preset regional meteorological state threshold Q to obtain the future meteorological change plan for the power generation equipment area:

[0046] When the meteorological coefficient Qxxs of the power generation equipment area < the regional meteorological state threshold Q, an evaluation plan for no abnormality in the meteorological change of the power generation equipment area is obtained;

[0047] When the meteorological coefficient Qxxs of the power generation equipment area ≥ the regional meteorological state threshold Q, an evaluation plan for abnormal meteorological change of the power generation equipment area is obtained.

[0048] Preferably, the second calculation includes: calculating the state coefficient Xdxs of the energy storage equipment:

[0049] The state coefficient Xdxs of the energy storage equipment is obtained through the following calculation formula:

[0050] ;

[0051] Wherein, Cdz represents the charging power value, Scz represents the output power value, Zrl represents the total battery capacity value, Ztz represents the battery state value. By calculating the charging power value Cdz, the output power value Scz, the total battery capacity value Zrl, and the battery state value Ztz, the real-time charging and discharging change information of the charging power value Cdz and the output power value Scz for the energy storage equipment is reflected, and L represents the fourth correction constant;

[0052] And it is matched with the preset operation state threshold X of the energy storage equipment to obtain the operation state plan of the energy storage equipment:

[0053] When the state coefficient Xdxs of the energy storage equipment < the operation state threshold X of the energy storage equipment, adjust the charging and discharging state of the energy storage equipment, directly supply the energy collected by the wind power generation equipment to the energy storage equipment, and after the energy that meets the maximum charging power of the energy storage equipment is used, supply the remaining energy to the hydrogen production equipment for operation;

[0054] When the state coefficient Xdxs of the energy storage device is ≥ the operating state threshold X of the energy storage device, adjust the charge and discharge state of the energy storage device, directly supply the energy collected by the wind power generation device to the hydrogen production device, and feed back the remaining energy after meeting the energy required for the operation of the hydrogen production device to the energy storage device for charging.

[0055] Preferably, the device regulation evaluation strategy scheme is obtained through the following matching method:

[0056] When the device regulation index Dkzs < the device regulation threshold D, and the future meteorological change plan for the power generation device area is: when obtaining the evaluation plan of no abnormal meteorological change in the power generation device area, no adjustment is made to the hydrogen production device, the energy storage device, and the charge and discharge of the energy storage device. When the future meteorological change plan for the power generation device area is: when obtaining the evaluation plan of abnormal meteorological change in the power generation device area, adjust the charge and discharge state of the energy storage device, including not releasing electric energy in the charging state, releasing electric energy in the charging state, not releasing electric energy in the non-charging state, and releasing electric energy in the non-charging state;

[0057] When the device regulation index Dkzs ≥ the device regulation threshold D, adjust the charge and discharge states of the hydrogen production device, the energy storage device, and the energy storage device, including turning on and off the energy switching of the hydrogen production device, adjusting the charging power of the energy storage device, adjusting the output power of the energy storage device, and adjusting the discharge state of the energy storage device. Among them, the adjustment of the discharge state of the energy storage device includes not releasing electric energy in the charging state, releasing electric energy in the charging state, not releasing electric energy in the non-charging state, and releasing electric energy in the non-charging state.

[0058] Preferably, the decision-making module includes an execution unit and a notification unit;

[0059] The execution unit executes the preset execution instructions according to the content of the device regulation evaluation strategy scheme to achieve adaptive control of devices, including the hydrogen production device, the wind power generation device, and the energy storage device;

[0060] The notification unit executes the preset contact notification method according to the content of the device regulation evaluation strategy scheme to enable relevant personnel to understand the status information of the hydrogen production device, the wind power generation device, and the energy storage device in real time. The notification methods include: text messages, preset call voices, broadcasts, and interactive page prompts.

[0061] (III) Beneficial effects

[0062] The present invention provides a wind power to hydrogen control system based on PLC intelligent control, having the following beneficial effects:

[0063] (1)When the system is running, the environmental module collects the environmental status of the wind power generation equipment in real time to form an environmental information group, obtains the meteorological change information of a fixed period in the region of the wind power generation equipment in real time to form a meteorological information group, collects the power storage status information of the energy storage equipment in real time to form a power storage information group, and performs preprocessing through the processing module to form a first data set, a second data set, and a third data set. The equipment regulation evaluation module establishes a power generation equipment prediction model for the first data set and the second data set, conducts training and analysis, and correlates with the third data set to obtain: the equipment regulation index Dkzs, and matches it with the preset equipment regulation threshold D to obtain an equipment regulation evaluation strategy plan. The decision-making module specifically executes according to the content of the equipment regulation evaluation strategy plan, including adjusting the hydrogen production equipment and notifying relevant personnel, achieving the purpose of adaptively adjusting the hydrogen production equipment and the energy storage equipment, thereby helping to extend the service life of the storage battery, reducing the adverse impact on the storage battery, effectively protecting the storage battery assets, and improving the reliability of the system.

[0064] (2)By calculating the environmental coefficient Hjxs of the power generation equipment, the regional meteorological coefficient Qxxs of the power generation equipment, and the state coefficient Xdxs of the energy storage equipment, and obtaining the future meteorological change plan in the power generation equipment area and the operation status plan of the energy storage equipment, it is possible to predict and dynamically adjust through the environmental status and the meteorological information within a future fixed period, enabling the system to dynamically adjust the charging and discharging modes of the storage battery under different wind speed conditions, improving the energy utilization efficiency, and effectively coping with power fluctuations, thereby increasing the service life of the storage battery.

[0065] (3)By obtaining the equipment regulation evaluation strategy plan and controlling through the decision-making module, when the future meteorological change in the power generation equipment area is abnormal, the system can adjust the charging and discharging status of the energy storage equipment to adapt to environmental changes, which improves the system's response ability to meteorological fluctuations, increases the stability of the system. At the same time, the adaptive control and real-time notification functions help reduce the operation and maintenance costs of the system. By responding and adjusting in a timely manner, the processing cost of sudden problems can be reduced, and the service life of the equipment can be extended. Brief Description of the Drawings

[0066] Figure 1 It is a schematic diagram of the block diagram process of a wind power to hydrogen control system based on PLC intelligent control according to the present invention. Detailed Embodiment

[0067] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0068] In recent years, in the field of renewable energy applications, wind power generation has developed rapidly. However, due to the energy supply fluctuations caused by natural conditions and the curtailment waste caused by grid load, hydrogen, as an important industrial raw material and power generation raw material for fuel cells, has received increasing attention. Using renewable energy to produce hydrogen has become an important way to solve the problem of curtailment of wind power.

[0069] Currently, however, the widely used electrolytic water hydrogen production technology has high requirements for power stability, cannot fully match the volatility of renewable energy, and cannot meet the requirement of stable operation within a certain period of time. Moreover, various faults and losses are likely to occur during frequent shutdown and startup processes. Due to the uncertainty of wind speed in traditional wind power generation systems, it is difficult to accurately predict the wind energy output, resulting in reduced efficiency of the system under low wind speeds or high volatility wind speeds, and the maximum utilization of wind energy cannot be fully achieved. At the same time, the traditional charge and discharge mode causes deep charge and discharge cycles of the storage battery, thereby shortening the service life of the storage battery and being unable to flexibly cope with the fluctuations in the battery power. In addition, the efficiency of the current water electrolysis reaction is limited by the difficulty of the system to flexibly adjust the power supply, resulting in fluctuations in hydrogen production efficiency under different environmental conditions.

[0070] Embodiment 1

[0071] The present invention provides a wind power hydrogen production control system based on PLC intelligent control. Please refer to Figure 1 , which includes an environment acquisition module, a meteorological module, a storage device status module, a processing module, a device regulation evaluation module, and a decision-making module;

[0072] The environment module collects the environmental status of the operation of the wind power generation equipment in real time through the environmental sensor group integrated in the wind power generation equipment to form an environmental information group;

[0073] The meteorological module obtains the fixed-period meteorological change information of the area where the wind power generation equipment is located in real time through the Internet to form a meteorological information group;

[0074] The storage device status module collects the storage status information of the storage device in real time to form a storage information group;

[0075] The processing module preprocesses the environmental information group, the meteorological information group, and the storage information group to form a first data set, a second data set, and a third data set;

[0076] The device regulation evaluation module establishes a power generation equipment prediction model for the first data set and the second data set, conducts training and analysis, and correlates with the third data set to obtain: the device regulation index Dkzs, and matches it with the preset device regulation threshold D to obtain a device regulation evaluation strategy plan;

[0077] The device regulation index Dkzs is obtained through the following calculation formula:

[0078] ;

[0079] In the formula, Hjxs represents the environmental coefficient of the power generation device, Qxxs represents the regional meteorological coefficient of the power generation device, Xdxs represents the state coefficient of the energy storage device, d1, d2, and d3 respectively represent the proportionality coefficients of the environmental coefficient Hjxs of the power generation device, the regional meteorological coefficient Qxxs of the power generation device, and the state coefficient Xdxs of the energy storage device, and C represents the first correction constant;

[0080] Among them, , , , and ;

[0081] The environmental coefficient Hjxs of the power generation device is obtained through calculation using the first data set;

[0082] The regional meteorological coefficient Qxxs of the power generation device is obtained through calculation using the second data set and is matched with the preset regional meteorological state threshold Q to obtain the future meteorological change plan for the power generation device area;

[0083] The state coefficient Xdxs of the energy storage device is obtained through calculation using the third data set and is matched with the preset operation state threshold X of the energy storage device to obtain the operation state plan of the energy storage device;

[0084] The decision-making module performs specific execution based on the content of the device regulation evaluation strategy plan, including the adjustment of the hydrogen production device and the notification of relevant personnel.

[0085] In this embodiment, the environment module forms an environmental information group by collecting the environmental states of the wind power generation device in real time, forms a meteorological information group by obtaining the meteorological change information of a fixed period in the region where the wind power generation device is located in real time, forms a battery energy storage information group by collecting the battery energy storage state information of the energy storage device in real time, performs preprocessing through the processing module to form the first data set, the second data set, and the third data set, establishes a power generation device prediction model for the first data set and the second data set through the device regulation evaluation module, performs training and analysis, and correlates with the third data set to obtain: the device regulation index Dkzs, and matches it with the preset device regulation threshold D to obtain the device regulation evaluation strategy plan. The decision-making module performs specific execution based on the content of the device regulation evaluation strategy plan, including the adjustment of the hydrogen production device and the notification of relevant personnel, achieving the purpose of adaptively adjusting the hydrogen production device and the energy storage device, thereby helping to extend the service life of the battery, reducing the adverse impact on the battery, effectively protecting the battery assets, and improving the reliability of the system.

[0086] Embodiment 2

[0087] This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: The environment module includes a collection unit and a transmission unit;

[0088] The collection unit collects environmental data in real time through an environmental sensor group integrated on the wind power generation equipment, including wind speed information, wind direction information, number of wind direction changes, wind speed fluctuation frequency information, temperature information, and air pressure information, and then integrates them to form an environmental information group;

[0089] Among them, the environmental sensor group includes a wind speed sensor, a wind direction sensor, a temperature sensor, and an air pressure sensor;

[0090] The transmission unit transmits the environmental information group to the processing module, and the transmission methods include wireless network transmission method, wired network transmission method, Bluetooth transmission method, and optical fiber transmission method.

[0091] The meteorological module includes a networking unit;

[0092] The networking unit executes a preset meteorological information acquisition script instruction by connecting to the Internet to obtain meteorological information within a future fixed period in the current power generation equipment area, including meteorological wind speed, meteorological wind direction, meteorological humidity, meteorological temperature, meteorological rainfall, and gale warning information, and forms a meteorological information group.

[0093] The energy storage device status module includes an extraction unit;

[0094] The extraction unit collects the status information of the energy storage device in real time, including the charging power of the energy storage device, input voltage, output power value, charge and discharge status, battery capacity, and charging status information, and converts it into digital signals to form an energy storage information group.

[0095] Embodiment 3

[0096] This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: The processing module includes a normalization unit;

[0097] The normalization unit preprocesses the environmental information group, meteorological information group, and energy storage information group, including normalization processing and null value processing, integrates and statistically analyzes the processed environmental information group to form a first data set, integrates the processed meteorological information group to form a second data set, and integrates the processed energy storage information group to form a third data set;

[0098] The first data set includes: real-time wind speed value Ssfs, real-time wind direction Ssfx, wind speed fluctuation frequency value Fsbd, wind direction fluctuation frequency value Fxbd, maximum wind speed increase Zjmax, and minimum wind speed decrease Jdmin;

[0099] The second data set includes: meteorological wind speed value Qxfs, meteorological wind direction Qxfx, meteorological humidity value Qxsd, and altitude value Hbgd.

[0100] The third data set includes: charging power value Cdz, output power value Scz, total battery capacity value Zrl, and battery status value Ztz.

[0101] The device regulation evaluation module includes a modeling unit and a matching unit;

[0102] The modeling unit uses machine learning technology to establish a power generation equipment prediction model for the first data set and the second data set. After training and prediction analysis, the first calculation is performed to obtain: the power generation equipment environment coefficient Hjxs and the power generation equipment regional meteorological coefficient Qxxs, which reflect the operating state change information of the wind power generation equipment within a fixed period. The second calculation is performed on the third data set to obtain: the energy storage equipment status coefficient Xdxs. The power generation equipment environment coefficient Hjxs, the power generation equipment regional meteorological coefficient Qxxs, and the energy storage equipment status coefficient Xdxs are correlated, and the third calculation is performed to obtain: the device regulation index Dkzs;

[0103] The matching unit matches through preset relevant information and comparison values, including matching the preset device regulation threshold D with the device regulation index Dkzs to obtain a device regulation evaluation strategy plan.

[0104] Embodiment 4

[0105] This embodiment is an explanatory description carried out in Embodiment 1. Please refer to Figure 1 , specifically: the first calculation includes: the calculation of the power generation equipment environment coefficient Hjxs and the calculation of the power generation equipment regional meteorological coefficient Qxxs;

[0106] The power generation equipment environment coefficient Hjxs is obtained through the following calculation formula:

[0107] ;

[0108] In the formula, Ssfs represents the real-time wind speed value, Ssfx represents the real-time wind direction, Fsbd represents the wind speed fluctuation frequency value, Fxbd represents the wind direction fluctuation frequency value, Zjmax represents the maximum wind speed increase value, Jdmin represents the minimum wind speed decrease value, h1, h2, h3, and h4 respectively represent the proportionality coefficients of the real-time wind speed value Ssfs, the real-time wind direction Ssfx, the wind speed fluctuation frequency value Fsbd, and the wind direction fluctuation frequency value Fxbd, h5 represents the proportionality coefficient of the difference between the maximum wind speed increase value Zjmax and the minimum wind speed decrease value Jdmin, and D represents the second correction constant;

[0109] Among them, , , , , , and ;

[0110] The meteorological coefficient Qxxs of the power generation equipment area is obtained through the following calculation formula:

[0111] ;

[0112] In the formula, Qxfs represents the meteorological wind speed value, Qxfx represents the meteorological wind direction, Qxsd represents the meteorological humidity value, Hbgd represents the altitude value, q1, q2, q3, and q4 respectively represent the proportionality coefficients of the meteorological wind speed value Qxfs, the meteorological wind direction Qxfx, the meteorological humidity value Qxsd, and the altitude value Hbgd, and K represents the third correction constant;

[0113] Among them, , , , , and ;

[0114] And it is matched with the preset regional meteorological state threshold Q to obtain the future meteorological change plan for the power generation equipment area:

[0115] When the meteorological coefficient Qxxs of the power generation equipment area < the regional meteorological state threshold Q, obtain the evaluation plan for no abnormality in the meteorological change of the power generation equipment area;

[0116] When the meteorological coefficient Qxxs of the power generation equipment area ≥ the regional meteorological state threshold Q, obtain the evaluation plan for abnormal meteorological change of the power generation equipment area.

[0117] The second calculation includes: calculating the state coefficient Xdxs of the energy storage equipment:

[0118] The state coefficient Xdxs of the energy storage equipment is obtained through the following calculation formula:

[0119] ;

[0120] Wherein, Cdz represents the charging power value, Scz represents the output power value, Zrl represents the total battery capacity value, Ztz represents the battery state value. By calculating the charging power value Cdz, the output power value Scz, the total battery capacity value Zrl, and the battery state value Ztz, the real-time change information of the charging and discharging of the energy storage device by the charging power value Cdz and the output power value Scz is reflected. L represents the fourth correction constant;

[0121] And it is matched with the preset operation state threshold X of the energy storage device to obtain the operation state scheme of the energy storage device:

[0122] When the state coefficient Xdxs of the energy storage device < the operation state threshold X of the energy storage device, adjust the charging and discharging state of the energy storage device, directly supply the energy collected by the wind power generation device to the energy storage device. After using the energy that meets the maximum charging power of the energy storage device, supply the remaining energy to the hydrogen production device for operation;

[0123] When the state coefficient Xdxs of the energy storage device ≥ the operation state threshold X of the energy storage device, adjust the charging and discharging state of the energy storage device, directly supply the energy collected by the wind power generation device to the hydrogen production device, and feedback the remaining energy after meeting the energy required for the operation of the hydrogen production device to the energy storage device for charging.

[0124] In this embodiment, through the calculation of the environmental coefficient Hjxs of the power generation device, the regional meteorological coefficient Qxxs of the power generation device, and the state coefficient Xdxs of the energy storage device, and the acquisition of the future meteorological change scheme of the power generation device area and the operation state scheme of the energy storage device, it is possible to predict and dynamically adjust through the environmental state and the meteorological information within a future fixed period, enabling the system to dynamically adjust the charging and discharging modes of the battery under different wind speed conditions, improving the energy utilization efficiency, effectively coping with power fluctuations, and extending the service life of the battery.

[0125] Embodiment 5

[0126] This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: The device regulation evaluation strategy scheme is obtained through the following matching method:

[0127] When the device regulation index Dkzs < the device regulation threshold D, and the future meteorological change scheme of the power generation device area is: when obtaining the evaluation scheme of no abnormal meteorological change in the power generation device area, no adjustment is made to the hydrogen production device, the energy storage device, and the charging and discharging of the energy storage device. When the future meteorological change scheme of the power generation device area is: when obtaining the evaluation scheme of abnormal meteorological change in the power generation device area, adjust the charging and discharging state of the energy storage device, including not releasing electric energy in the charging state, releasing electric energy in the charging state, not releasing electric energy in the non-charging state, and releasing electric energy in the non-charging state;

[0128] When the device regulation index Dkzs ≥ the device regulation threshold D, the hydrogen production device, the energy storage device, and the charge-discharge state of the energy storage device are adjusted, including turning on and off the energy switch of the hydrogen production device, adjusting the charging power of the energy storage device, adjusting the output power of the energy storage device, and adjusting the discharge state of the energy storage device. Among them, the adjustment of the discharge state of the energy storage device includes not releasing electric energy in the charging state, releasing electric energy in the charging state, not releasing electric energy in the non-charging state, and releasing electric energy in the non-charging state.

[0129] The decision-making module includes an execution unit and a notification unit;

[0130] The execution unit executes the preset execution instructions according to the content of the device regulation evaluation strategy plan to achieve adaptive control of devices, including hydrogen production devices, wind power generation devices, and energy storage devices;

[0131] The notification unit executes the preset contact notification method according to the content of the device regulation evaluation strategy plan to enable relevant personnel to understand the status information of the hydrogen production device, wind power generation device, and energy storage device in real time. The notification methods include: text messages, preset call voices, broadcasts, and interactive page prompts.

[0132] In this embodiment, through the acquisition of the device regulation evaluation strategy plan and the control of the decision-making module, when the future meteorological changes in the power generation device area are abnormal, the system can adjust the charge-discharge state of the energy storage device to adapt to environmental changes. This improves the system's response ability to meteorological fluctuations, increases the stability of the system. At the same time, the adaptive control and real-time notification functions help reduce the operation and maintenance costs of the system. By responding and adjusting in a timely manner, the processing costs of sudden problems can be reduced, and the service life of the equipment can be extended.

[0133] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A wind power hydrogen production control system based on PLC intelligent control, characterized by: It includes environment acquisition module, meteorological module, power storage equipment status module, processing module, equipment control and evaluation module and decision-making module; The environmental module collects the environmental status of the wind power generation equipment in real time through the environmental sensor group integrated in the wind power generation equipment to form an environmental information group; The meteorological module obtains the fixed-period meteorological change information of the wind power generation equipment area in real time through the Internet to form a meteorological information group; The power storage device status module collects power storage status information of the power storage device in real time to form a power storage information group; The processing module pre-processes the environmental information group, the meteorological information group and the power storage information group to form a first data set, a second data set and a third data set; The equipment control evaluation module establishes a power generation equipment prediction model for the first data set and the second data set, performs training and analysis, and associates the model with the third data set to obtain: an equipment control index Dkzs, and matches the model with a preset equipment control threshold D to obtain an equipment control evaluation strategy solution; The equipment control index Dkzs is obtained by the following calculation formula: ； Wherein, Hjxs represents the environmental coefficient of the power generation equipment, Qxxs represents the regional meteorological coefficient of the power generation equipment, Xdxs represents the state coefficient of the power storage equipment, d1, d2 and d3 represent the proportional coefficients of the environmental coefficient Hjxs of the power generation equipment, the regional meteorological coefficient Qxxs of the power generation equipment and the state coefficient Xdxs of the power storage equipment, respectively, and C represents the first correction constant; The power generation equipment environmental coefficient Hjxs is obtained by calculating the first data set; The power generation equipment regional meteorological coefficient Qxxs is obtained by calculating the second data set and matching it with the preset regional meteorological state threshold Q to obtain the future meteorological change plan of the power generation equipment region; The power storage device state coefficient Xdxs is obtained by calculating the third data set, and matched with the preset power storage device operation state threshold value X to obtain the power storage device operation state scheme; The decision module carries out specific execution through the equipment control evaluation strategy plan content, including hydrogen production equipment adjustment and relevant personnel notification.

2. According to the PLC intelligent control system for wind power hydrogen production according to claim 1, it is characterized by: The environmental module includes a collection unit and a transmission unit; The collection unit collects environmental data in real time through an environmental sensor group integrated on the wind power generation equipment, including wind speed information, wind direction information, wind direction change times, wind speed fluctuation frequency information, temperature information and air pressure information, and then integrates them to form an environmental information group; The environmental sensor group includes a wind speed sensor, a wind direction sensor, a temperature sensor and an air pressure sensor; The transmission unit transmits the environment information group to the processing module, and the transmission mode includes wireless network transmission mode, wired network transmission mode, Bluetooth transmission mode and optical fiber transmission mode.

3. According to the PLC intelligent control-based wind power hydrogen production control system of claim 1, it is characterized by: The meteorological module includes a networking unit; The networking unit executes preset meteorological information acquisition script instructions by connecting to the Internet to obtain meteorological information within a future fixed period in the current power generation equipment area, including meteorological wind speed, meteorological wind direction, meteorological humidity, meteorological temperature, meteorological rainfall and strong wind warning information, forming a meteorological information group.

4. According to claim 1, a wind power hydrogen production control system based on PLC intelligent control is characterized in that: The power storage device status module includes an extraction unit; The extraction unit collects the state information of the power storage device in real time, including the charging power, input voltage, output power value, charging and discharging state, battery capacity and charging state information of the power storage device, and converts it into a digital signal to form a power storage information group.

5. A wind power hydrogen production control system based on PLC intelligent control according to claim 4, characterized in that: The processing module includes a normalization unit; The normalization unit pre-processes the environment information group, the weather information group and the power storage information group, including normalization processing and null value processing, integrates and counts the processed environment information group to form a first data set, integrates the processed weather information group to form a second data set, and integrates the processed power storage information group to form a third data set; The first data set includes: real-time wind speed value Ssfs, real-time wind direction Ssfx, wind speed fluctuation frequency value Fsbd, wind direction fluctuation frequency value Fxbd, maximum wind speed increase Zjmax and minimum wind speed decrease Jdmin; The second data set includes: a meteorological wind speed value Qxfs, a meteorological wind direction Qxfx, a meteorological humidity value Qxsd, and an altitude value Hbgd. The third data set includes: a charging power value Cdz, an output power value Scz, a battery total capacity value Zrl, and a battery state value Ztz.

6. A wind power hydrogen production control system based on PLC intelligent control according to claim 1, characterized in that: The equipment control and evaluation module includes a modeling unit and a matching unit; The modeling unit uses machine learning technology to establish a power generation equipment prediction model for the first data set and the second data set, and after training and prediction analysis, performs a first calculation to obtain: the power generation equipment environmental coefficient Hjxs and the power generation equipment regional meteorological coefficient Qxxs, which reflect the operation state change information of the wind power generation equipment within a fixed period, and performs a second calculation to obtain the power storage equipment state coefficient Xdxs on the third data set, associates the power generation equipment environmental coefficient Hjxs, the power generation equipment regional meteorological coefficient Qxxs and the power storage equipment state coefficient Xdxs, and performs a third calculation to obtain: the equipment regulation index Dkzs; The matching unit matches the preset relevant information with the comparison value, including matching the preset device control threshold D with the device control index Dkzs, to obtain the device control evaluation strategy solution.

7. A wind power hydrogen production control system based on PLC intelligent control according to claim 6, characterized in that: The first calculation includes: calculation of the environmental coefficient Hjxs of the power generation equipment and calculation of the regional meteorological coefficient Qxxs of the power generation equipment; The power generation equipment environmental coefficient Hjxs is obtained by the following calculation formula: ； Wherein, Ssfs represents the real-time wind speed value, Ssfx represents the real-time wind direction, Fsbd represents the wind speed fluctuation frequency value, Fxbd represents the wind direction fluctuation frequency value, Zjmax represents the maximum value of wind speed increase, Jdmin represents the minimum value of wind speed decrease, h1, h2, h3 and h4 represent the proportional coefficients of the real-time wind speed value Ssfs, the real-time wind direction Ssfx, the wind speed fluctuation frequency value Fsbd and the wind direction fluctuation frequency value Fxbd respectively, h5 represents the proportional coefficient of the difference between the maximum value of wind speed increase Zjmax and the minimum value of wind speed decrease Jdmin, and D represents the second correction constant; in, , , , , ,and ; The regional meteorological coefficient Qxxs of the power generation equipment is obtained by the following calculation formula: ； Wherein, Qxfs represents the meteorological wind speed value, Qxfx represents the meteorological wind direction, Qxsd represents the meteorological humidity value, Hbgd ​​represents the altitude value, q1, q2, q3 and q4 represent the proportional coefficients of the meteorological wind speed value Qxfs, the meteorological wind direction Qxfx, the meteorological humidity value Qxsd and the altitude value Hbgd ​​respectively, and K represents the third correction constant; in, , , , ,and ; And match it with the preset regional meteorological state threshold Q to obtain the future meteorological change plan of the power generation equipment area: The meteorological coefficient Qxxs of the power generation equipment area is less than the regional meteorological state threshold Q, and an evaluation plan for abnormal meteorological changes in the power generation equipment area is obtained; The regional meteorological coefficient Qxxs of the power generation equipment is ≥ the regional meteorological state threshold Q, and the abnormal meteorological change assessment plan of the power generation equipment area is obtained.

8. A wind power hydrogen production control system based on PLC intelligent control according to claim 6, characterized in that: The second calculation includes: calculation of the state coefficient Xdxs of the electric storage device: The power storage device state coefficient Xdxs is obtained by the following calculation formula: ； Wherein, Cdz represents the charging power value, Scz represents the output power value, Zrl represents the total battery capacity value, and Ztz represents the battery state value. By calculating the charging power value Cdz, the output power value Scz, the total battery capacity value Zrl and the battery state value Ztz, the real-time change information of the charging and discharging of the power storage device by the charging power value Cdz and the output power value Scz is reflected, and L represents the fourth correction constant; And match it with the preset power storage device operating state threshold X to obtain the power storage device operating state solution: The state coefficient of the electric storage device Xdxs is less than the operating state threshold value X of the electric storage device. The charging and discharging state of the electric storage device is adjusted, and the energy collected by the wind power generation equipment is directly supplied to the electric storage device. After the energy used to charge the electric storage device at the maximum power is used, the remaining energy is supplied to the hydrogen production equipment for operation. The state coefficient of the power storage device Xdxs ≥ the operating state threshold X of the power storage device, adjust the charging and discharging state of the power storage device, directly supply the energy collected by the wind power generation equipment to the hydrogen production equipment, and feed back the remaining energy after satisfying the energy used by the hydrogen production equipment to the power storage device for charging.

9. A wind power hydrogen production control system based on PLC intelligent control according to claim 7, characterized in that: The device control evaluation strategy solution is obtained through the following matching method: The equipment control index Dkzs is less than the equipment control threshold D, and the future meteorological change plan of the power generation equipment area is: when the meteorological change in the power generation equipment area is obtained without abnormal assessment plan, the hydrogen production equipment, the power storage equipment and the charging and discharging of the power storage equipment are not adjusted. When the future meteorological change plan of the power generation equipment area is: when the meteorological change abnormal assessment plan of the power generation equipment area is obtained, the charging and discharging state of the power storage equipment is adjusted, including not releasing electric energy in the charging state, releasing electric energy in the charging state, not releasing electric energy in the non-charging state and releasing electric energy in the non-charging state; The equipment control index Dkzs ≥ equipment control threshold D, and the hydrogen production equipment, the power storage equipment and the charging and discharging status of the power storage equipment are adjusted, including turning on and off the energy switching of the hydrogen production equipment, adjusting the charging power of the power storage equipment, adjusting the output power of the power storage equipment and adjusting the discharge state of the power storage equipment. Among them, the discharge state adjustment of the power storage equipment includes not releasing electric energy in the charging state, releasing electric energy in the charging state, not releasing electric energy in the non-charging state and releasing electric energy in the non-charging state.

10. A wind power hydrogen production control system based on PLC intelligent control according to claim 9, characterized in that: The decision module includes an execution unit and a notification unit; The execution unit executes preset execution instructions according to the content of the equipment control evaluation strategy plan to achieve adaptive control of equipment, including hydrogen production equipment, wind power generation equipment and power storage equipment; The notification unit executes a preset contact notification method according to the content of the equipment control evaluation strategy plan, so that relevant personnel can understand the status information of the hydrogen production equipment, wind power generation equipment and power storage equipment in real time. The notification methods include: text messages, preset call voices, broadcasts and interactive page prompts.

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