Intelligent control method and system for hydrogen generator set

Abstract

The invention relates to the field of electric power early warning, in particular to an intelligent control method and system for a hydrogen generator set. A data analysis module calculates a power grid structure integrity index and an electric energy quality stability index based on a power transmission line switch trip number, a relay protection action signal number, a system active power deviation value and a key node voltage out-of-limit value, and further weighting is carried out to obtain a comprehensive characterization value; the operation condition division module divides stable or disturbance operation conditions; the strategy scheduling module adjusts the acquisition interval of the next time period according to the operation condition; and the alarm module judges whether to give out early warning or not according to the comparison of the comprehensive characterization value and an alarm threshold value. According to the method, the monitoring frequency is reduced under the stable working condition to save resources, the monitoring density is improved under the disturbance working condition to enhance the sensing capability, and the intelligent operation and maintenance level and the early warning accuracy of the dispatching service of the power system are improved.

Description

Technical Field

[0001] This invention relates to the field of power early warning, and in particular to an intelligent control method and system for hydrogen generator sets. Background Technology

[0002] With the rapid development of hydrogen energy technology, hydrogen generator sets, as clean and efficient distributed power sources, are gradually being integrated into the traditional power grid system. While improving the greening level of energy, this integration also brings new challenges to the safe and stable operation of the power grid. The output power of hydrogen power generation is constrained by the hydrogen supply, the state of the fuel cell, and the performance of the power electronic converter, exhibiting significant fluctuations and intermittent characteristics. This characteristic can easily lead to voltage overruns at local nodes of the power grid, frequency deviations, and abrupt changes in power flow distribution, potentially affecting power quality and even threatening the reliability of regional power grid supply.

[0003] Traditional power grid monitoring systems are mainly designed for conventional power sources and loads, and lack sufficient perception and early warning capabilities for new distributed power sources with high proportions and diverse characteristics.

[0004] Chinese Patent Publication No. CN111126810A discloses a method for evaluating the operational safety of source-side generator sets. This invention establishes an operational status perception model based on historical operational data of different operating equipment and systems of the source-side generator set. Principal component analysis is used to convert the status of all protection parameters into operational evaluation status coefficients. These operational evaluation status coefficients are then weighted according to their impact on the safe operation of the corresponding systems to obtain the operational evaluation status value of the system. This invention can provide early warnings of equipment fault changes, alerting staff to monitoring parameters that may trigger alarms in equipment, systems, and generator sets. This helps staff detect generator set equipment deterioration as early as possible, improving the operational safety and stability of the generator set. Furthermore, this method can reduce the impact and damage caused by generator set failures and unplanned outages on the safe and stable operation of power plants and the power grid.

[0005] However, the following problems still exist in the existing technology: 1. In existing technologies, relying on a single or limited number of parameters for status assessment results in an incomplete perception of the system's operational status, making it difficult to identify potential risks and provide timely and accurate early warnings. 2. Existing technologies lack adaptive monitoring mechanisms based on real-time operating conditions, making it difficult to provide more accurate early warning support when the system is disturbed; Summary of the Invention

[0006] To address this, the present invention provides an intelligent control method and system for hydrogen generator sets, which overcomes the problems in the prior art that rely on a single or a small number of parameters for state assessment, resulting in incomplete perception of the system's operating status, difficulty in timely and accurate identification of potential risks for early warning, lack of an adaptive monitoring mechanism based on real-time operating conditions, and difficulty in providing more accurate early warning support when the system is disturbed.

[0007] To achieve the above objectives, in one aspect, the present invention provides an intelligent control system for a hydrogen generator set, comprising: The data acquisition module is used to acquire key operating parameters of the power system connected to the hydrogen generator set within a time period according to the acquisition interval. The key operating parameters include the number of transmission line switches tripped, the number of relay protection action signals, the system active power deviation value, and the voltage over-limit value of key nodes. The data analysis module, which is connected to the data acquisition module, is used to calculate the power grid structure integrity index and the power quality stability index based on the key operating parameters, and to determine the weighted sum of the power grid structure integrity index and the power quality stability index as the comprehensive characterization value corresponding to the time period. The operating condition division module is connected to the data analysis module and is used to divide the operating conditions corresponding to the time period based on the comprehensive characterization value corresponding to the time period and the preset operating condition threshold. The strategy scheduling module is connected to the operating condition division module and is used to adjust the collection interval of the next time period based on the operating condition corresponding to the time period. The alarm module is connected to the data analysis module to compare the comprehensive characterization value corresponding to the time period with the preset alarm threshold to determine whether to issue an alarm.

[0008] Furthermore, the data acquisition module is used to acquire key operating parameters of the power system connected to the hydrogen generator set within a time period according to the acquisition interval, including: The acquisition interval is determined by the product of the basic standard acquisition interval and the dynamic detection coefficient; The basic standard collection interval is predetermined.

[0009] Furthermore, the data analysis module calculates the power grid structural integrity index and power quality stability index based on the key operating parameters, including: The power grid structural integrity index is determined based on the number of power transmission line switch trips and the number of relay protection action signals. The power quality stability index is determined based on the system active power deviation value and the voltage over-limit value of the key node.

[0010] Furthermore, the data analysis module determines the following power grid structural integrity indicators: Based on the number of power transmission line switches that have tripped and the number of relay protection action signals, determine the power transmission line switch tripping frequency and the relay protection action signal frequency. The ratio of the tripping frequency of the transmission line switch to the tripping standard value is determined as the tripping parameter; The ratio of the relay protection action signal frequency to the protection standard value is determined as the protection parameter; The weighted sum of the tripping parameters and the protection parameters is determined as the power grid structure integrity index; The tripping standard value and the protection standard value are predetermined.

[0011] Furthermore, the data analysis module determines the power quality stability indicators, including: The ratio of the system's active power deviation value to the standard power deviation value is determined as the deviation parameter; The ratio of the voltage over-limit value of the key node to the voltage over-limit standard value is determined as the over-limit parameter; The weighted sum of the deviation parameter and the over-limit parameter is determined as the power quality stability index; The power deviation standard value and the voltage over-limit standard value are predetermined.

[0012] Furthermore, the operating condition division module divides the operating conditions corresponding to the time period based on the comprehensive characteristic value corresponding to the time period and the preset operating condition threshold, including: The comprehensive characterization value corresponding to the time period is compared with the preset working condition threshold. If the comprehensive characterization value corresponding to the time period is greater than or equal to the preset operating condition threshold, then the time period is determined to be in a disturbed operating condition. If the comprehensive characteristic value corresponding to the time period is less than the preset operating condition threshold, then the time period is determined to be in a stable operating condition.

[0013] Furthermore, the strategy scheduling module adjusts the data collection interval for the next time period based on the operating conditions corresponding to the time period, including: If the time period is under a disturbance operation condition, the ratio of the preset operation condition threshold to the comprehensive characterization value corresponding to the time period is used as the dynamic detection coefficient for the next time period. The product of the basic standard acquisition interval and the dynamic detection coefficient is used to determine the acquisition interval for the next time period.

[0014] Furthermore, the strategy scheduling module's adjustment of the data collection interval for the next time period based on the operating conditions corresponding to the time period also includes: If the time period is under stable operating conditions, the dynamic detection coefficient corresponding to the next time period will be set to 1; The product of the basic standard acquisition interval and the dynamic detection coefficient is used to determine the acquisition interval for the next time period.

[0015] Furthermore, the alarm module is used to compare the comprehensive characteristic value corresponding to the time period with a preset alarm threshold to determine whether to issue an alarm, including... If the comprehensive characterization value corresponding to the time period is greater than or equal to the preset alarm threshold, an early warning will be issued. If the comprehensive characterization value corresponding to the time period is less than the preset alarm threshold, no warning will be issued; Wherein, the preset alarm threshold is greater than the preset operating condition threshold.

[0016] On the other hand, the present invention provides a method for an intelligent control system applied to a hydrogen generator set, comprising: The key operating parameters of the power system connected to the hydrogen generator set within a time period are obtained according to the collection interval; the key operating parameters are: Based on the key operating parameters, the power grid structural integrity index and the power quality stability index are calculated, and the weighted sum of the power grid structural integrity index and the power quality stability index is determined as the comprehensive characterization value corresponding to the time period. The operating conditions corresponding to the time period are divided based on the comprehensive characterization value corresponding to the time period and the preset operating condition threshold. The data collection interval for the next time period is adjusted based on the operating conditions corresponding to the aforementioned time period. The comprehensive characterization value corresponding to the time period is compared with the preset alarm threshold to determine whether to issue an alarm.

[0017] Compared with existing technologies, this invention acquires key operating parameters at intervals through a data acquisition module. A data analysis module calculates power grid structural integrity and power quality stability indicators based on the number of transmission line switch trips, the number of relay protection action signals, system active power deviation, and voltage exceedance values ​​at key nodes. These are then weighted to obtain a comprehensive characteristic value. An operating condition classification module categorizes the operating conditions as stable or disturbed. A strategy scheduling module adjusts the acquisition interval for the next time period based on the operating condition. An alarm module determines whether to issue a warning by comparing the comprehensive characteristic value with an alarm threshold. This invention achieves resource conservation by reducing monitoring frequency under stable conditions and enhancing perception capabilities under disturbed conditions, thereby improving the intelligent operation and maintenance level and early warning accuracy of power system dispatching.

[0018] In particular, this invention comprehensively considers the synergistic effect of power grid structural integrity indicators and power quality stability indicators. In practice, transmission line switch tripping and relay protection actions jointly reflect the changing trends of the power grid topology, while system active power deviation and node voltage exceedances reflect the stability of power transmission. By weighted summing of these two types of indicators to obtain a comprehensive characterization value, a comprehensive quantitative assessment of the power grid's operating status is achieved.

[0019] In particular, this invention establishes a linkage mechanism between operating conditions and data acquisition intervals. In practice, when the system is under disturbance conditions, various operating parameters change drastically. If conventional acquisition intervals are still used, it is easy to miss or delay critical status information, affecting the accurate judgment of the system's operating status. To address this, this invention uses a dynamic detection coefficient adjustment mechanism to immediately shorten the acquisition interval upon identifying a disturbance condition, significantly increasing the monitoring frequency and ensuring that rapidly changing operating parameters can be captured, providing sufficient data support for accurate early warning. This linkage mechanism ensures both resource conservation during stable system operation and monitoring accuracy under abnormal conditions.

[0020] In particular, this invention constructs a complete closed-loop early warning and control system. In practice, the system acquires operating parameters through a data acquisition module, calculates comprehensive characteristic values ​​through a data analysis module, identifies the current state through an operating condition classification module, adjusts the monitoring strategy through a strategy scheduling module, and finally outputs early warning information through an alarm module, forming a complete closed loop from state perception to control execution. This improves the intelligence level and efficiency of power system dispatching operations. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the structural connection of the intelligent control method and system for a hydrogen generator set according to an embodiment of the invention. Figure 2 A logic block diagram for determining the operating conditions during the time period in an embodiment of the invention; Figure 3 A logic block diagram for determining the dynamic detection coefficient corresponding to the next time period in an embodiment of the invention; Figure 4 This is a logic block diagram illustrating how to determine whether to issue a warning according to an embodiment of the invention. Detailed Implementation

[0022] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0023] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0024] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0025] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0026] Please see Figure 1 As shown, Figure 1 This is a schematic diagram of the structural connection of an intelligent control method and system for a hydrogen generator set according to an embodiment of the invention. The intelligent control method and system for a hydrogen generator set of the present invention includes: The data acquisition module is used to acquire key operating parameters of the power system connected to the hydrogen generator set within a time period according to the acquisition interval. The key operating parameters include the number of transmission line switches tripped, the number of relay protection action signals, the system active power deviation value, and the voltage over-limit value of key nodes. The data analysis module, which is connected to the data acquisition module, is used to calculate the power grid structure integrity index and the power quality stability index based on the key operating parameters, and to determine the weighted sum of the power grid structure integrity index and the power quality stability index as the comprehensive characterization value corresponding to the time period. The operating condition division module is connected to the data analysis module and is used to divide the operating conditions corresponding to the time period based on the comprehensive characterization value corresponding to the time period and the preset operating condition threshold. The strategy scheduling module is connected to the operating condition division module and is used to adjust the collection interval of the next time period based on the operating condition corresponding to the time period. The alarm module is connected to the data analysis module to compare the comprehensive characterization value corresponding to the time period with the preset alarm threshold to determine whether to issue an alarm.

[0027] Specifically, there are no restrictions on the specific structure of the data acquisition module, data analysis module, operating condition division module, strategy scheduling module, and alarm module. They can be composed of logic components or combinations of logic components, including field-programmable processors, computers, or microprocessors in computers.

[0028] Specifically, the data acquisition module is used to acquire key operating parameters of the power system connected to the hydrogen generator set within a time period, according to acquisition intervals. The acquisition interval is determined by the product of the basic standard acquisition interval and the dynamic detection coefficient; The basic standard collection interval is predetermined.

[0029] Specifically, the basic standard data collection interval is predetermined by those skilled in the art, and in this embodiment, the value range is [30 seconds, 60 seconds]. The interval setting can meet the needs of tracking the system operation trend under steady-state operating conditions, while avoiding the waste of system communication resources caused by excessively frequent data collection.

[0030] Specifically, the data analysis module calculates the power grid structural integrity index and power quality stability index based on the key operating parameters, including: The power grid structural integrity index is determined based on the number of power transmission line switch trips and the number of relay protection action signals. The power quality stability index is determined based on the system active power deviation value and the voltage over-limit value of the key node.

[0031] Specifically, the number of transmission line switches tripping directly reflects changes in the physical connectivity of the power grid's main structure, and an abnormal increase in this number indicates that the power grid may be experiencing fault propagation; the number of relay protection action signals reflects the response strength of the power system's secondary protection system, and its changes can effectively reflect the severity and scope of system faults.

[0032] Specifically, the active power deviation of the system reflects the real-time balance between power generation and load demand, and reflects the frequency stability of the power system; the voltage over-limit value of key nodes reflects the strength of the power grid's reactive power balance and voltage support capability, and is an important indicator for evaluating the power grid's power supply quality and stability level.

[0033] Specifically, the data analysis module determines the power grid structural integrity indicators, including: Based on the number of power transmission line switches that have tripped and the number of relay protection action signals, determine the power transmission line switch tripping frequency and the relay protection action signal frequency. The ratio of the tripping frequency of the transmission line switch to the tripping standard value is determined as the tripping parameter; The ratio of the relay protection action signal frequency to the protection standard value is determined as the protection parameter; The weighted sum of the tripping parameters and the protection parameters is determined as the power grid structure integrity index; The tripping standard value and the protection standard value are predetermined.

[0034] Specifically, the tripping standard value is determined by those skilled in the art based on the statistical characteristics of the tripping frequency of transmission line switches in historical power system operation data. In this embodiment, the value is taken as 1.25 times the average tripping frequency of the system under normal operating conditions. Specifically, the protection standard value is determined by those skilled in the art based on the statistical characteristics of the historical operating frequency of the relay protection system. In this embodiment, the value is taken as 1.25 times the average protection operating frequency of the system under normal operating conditions.

[0035] To comprehensively consider the influence of the tripping parameters and the protection parameters, the weighting coefficient for the weighted summation is 0.5.

[0036] Specifically, the data analysis module determines the power quality stability indicators, including: The ratio of the system's active power deviation value to the standard power deviation value is determined as the deviation parameter; The ratio of the voltage over-limit value of the key node to the voltage over-limit standard value is determined as the over-limit parameter; The weighted sum of the deviation parameter and the over-limit parameter is determined as the power quality stability index; The power deviation standard value and the voltage over-limit standard value are predetermined.

[0037] Specifically, the power deviation standard value can be determined according to the power control requirements specified in the "Guidelines for the Safety and Stability of Power Systems". In this embodiment, the value is taken as 2% of the rated active power of the system.

[0038] Specifically, the voltage over-limit standard value can be determined according to the voltage qualified range specified in the "Technical Guidelines for Voltage and Reactive Power of Power Systems". In this embodiment, the value is taken as 0.8 times the voltage standard limit.

[0039] Specifically, both the deviation parameter and the over-limit parameter can reflect the stability of power quality, and the weight of each parameter in the weighted summation is 0.5.

[0040] Please see Figure 2 As shown, Figure 2 This is a logic block diagram illustrating the determination of the operating conditions during a time period according to an embodiment of the invention. The operating condition division module divides the operating conditions corresponding to the time period based on the comprehensive characteristic value corresponding to the time period and a preset operating condition threshold, including: The comprehensive characterization value corresponding to the time period is compared with the preset working condition threshold. If the comprehensive characterization value corresponding to the time period is greater than or equal to the preset operating condition threshold, then the time period is determined to be in a disturbed operating condition. If the comprehensive characteristic value corresponding to the time period is less than the preset operating condition threshold, then the time period is determined to be in a stable operating condition.

[0041] Specifically, the operating condition threshold is determined by those skilled in the art based on the historical comprehensive characterization values ​​of the power grid system. Several typical historical disturbance operating condition periods can be manually selected, the corresponding historical comprehensive characterization values ​​can be calculated, and the product of the average value of the historical comprehensive characterization values ​​and the reduction factor can be determined as the operating condition threshold.

[0042] Specifically, the value range of the reduction factor is [0.85, 0.95].

[0043] Please see Figure 3 As shown, Figure 3 The following is a logic block diagram illustrating the determination of the dynamic detection coefficients for the next time period according to an embodiment of the invention. The strategy scheduling module adjusts the collection interval for the next time period based on the operating conditions corresponding to the time period. If the time period is under a disturbance operation condition, the ratio of the preset operation condition threshold to the comprehensive characterization value corresponding to the time period is used as the dynamic detection coefficient for the next time period. The product of the basic standard acquisition interval and the dynamic detection coefficient is used to determine the acquisition interval for the next time period.

[0044] Specifically, the strategy scheduling module's adjustment of the data collection interval for the next time period based on the operating conditions corresponding to the time period also includes: If the time period is under stable operating conditions, the dynamic detection coefficient corresponding to the next time period will be set to 1; The product of the basic standard acquisition interval and the dynamic detection coefficient is used to determine the acquisition interval for the next time period.

[0045] Please see Figure 4 As shown, Figure 4 The diagram below illustrates the logic block diagram for determining whether to issue a warning according to an embodiment of the invention. The alarm module is used to compare the comprehensive characteristic value corresponding to the time period with a preset alarm threshold to determine whether to issue a warning. If the comprehensive characterization value corresponding to the time period is greater than or equal to the preset alarm threshold, an early warning will be issued. If the comprehensive characterization value corresponding to the time period is less than the preset alarm threshold, no warning will be issued; Wherein, the preset alarm threshold is greater than the preset operating condition threshold.

[0046] Specifically, the alarm threshold in this embodiment is 1.2 times the operating condition threshold.

[0047] Understandably, during continuous operation, the data acquisition module, data analysis module, operating condition classification module, and alarm module will generate and process a series of key data in time intervals, including the acquisition interval for each time interval, key operating parameters, calculated power grid structural integrity indicators and power quality stability indicators, comprehensive characterization values, operating condition judgment results, and early warning trigger records. This structured data, generated chronologically and with clear causal relationships, can be synchronously stored in the system's historical database. Through long-term accumulation, a complete and traceable system operation archive is formed. This archive can not only be used for post-event retrospective analysis and fault analysis, locating the precursors and evolution of specific disturbance events, but also provides a solid data foundation for evaluating and optimizing key parameters such as operating condition thresholds, alarm thresholds, indicator calculation weights, and dynamic detection coefficients. This supports continuous improvement of system operation strategies and further enhances the accuracy and adaptability of early warnings.

[0048] Based on this, the system can also structurally associate and store historical early warning records with their corresponding comprehensive characteristic values, operating conditions, key operating parameters and handling feedback, forming a searchable and analyzable structured historical data, providing a reference for subsequent handling decisions.

[0049] Understandably, the structured historical data generated by this system, besides being used to optimize internal system parameters, can also support more advanced power grid security analysis applications. For example, combined with a power grid geographic information system, historical early warning events can be correlated and mapped with their location, time, and corresponding comprehensive characteristic values ​​to form a sequence dataset with spatiotemporal attributes. Based on this, the density-based spatial clustering algorithm DBSCAN can be used to perform density analysis on the early warning events in the spatial dimension, identifying high-risk areas with dense event distribution, and thus generating an alarm heatmap. This heatmap can intuitively and dynamically display the abnormal activity levels and vulnerability distribution in different areas of the power grid, providing a visual basis for the key deployment of operation and maintenance resources and the optimization of inspection routes.

[0050] Furthermore, for the identified high-frequency alarm areas, their historical comprehensive characteristic value time series can be extracted to construct a Long Short-Term Memory (LSTM) network model suitable for time series prediction. This model, by capturing and learning long-term dependencies in the sequence data, can effectively predict the evolution trend of the comprehensive characteristic value of the area over a future period. Based on this prediction result, the system can achieve early assessment and trend warning of local risks in the power grid, thereby supporting dispatching and operation personnel to take proactive intervention measures and improve the initiative and accuracy of power grid security defense.

[0051] In practice, a method for an intelligent control system applied to a hydrogen generator set is also provided, including: The key operating parameters of the power system connected to the hydrogen generator set within a time period are obtained according to the collection interval; the key operating parameters are: Based on the key operating parameters, the power grid structural integrity index and the power quality stability index are calculated, and the weighted sum of the power grid structural integrity index and the power quality stability index is determined as the comprehensive characterization value corresponding to the time period. The operating conditions corresponding to the time period are divided based on the comprehensive characterization value corresponding to the time period and the preset operating condition threshold. The data collection interval for the next time period is adjusted based on the operating conditions corresponding to the aforementioned time period. The comprehensive characterization value corresponding to the time period is compared with the preset alarm threshold to determine whether to issue an alarm.

[0052] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A smart control method and system for a hydrogen generator set, characterized in that, include: The data acquisition module is used to acquire key operating parameters of the power system connected to the hydrogen generator set within a time period according to the acquisition interval. The key operating parameters include the number of transmission line switches tripped, the number of relay protection action signals, the system active power deviation value, and the voltage over-limit value of key nodes. The data analysis module, which is connected to the data acquisition module, is used to calculate the power grid structure integrity index and the power quality stability index based on the key operating parameters, and to determine the weighted sum of the power grid structure integrity index and the power quality stability index as the comprehensive characterization value corresponding to the time period. The operating condition division module is connected to the data analysis module and is used to divide the operating conditions corresponding to the time period based on the comprehensive characterization value corresponding to the time period and the preset operating condition threshold. The strategy scheduling module is connected to the operating condition division module and is used to adjust the collection interval of the next time period based on the operating condition corresponding to the time period. The alarm module is connected to the data analysis module to compare the comprehensive characterization value corresponding to the time period with the preset alarm threshold to determine whether to issue an alarm.

2. The intelligent control method and system for a hydrogen generator set according to claim 1, characterized in that, The data acquisition module is used to acquire key operating parameters of the power system connected to the hydrogen generator set within a time period, according to acquisition intervals. The acquisition interval is determined by the product of the basic standard acquisition interval and the dynamic detection coefficient; The basic standard collection interval is predetermined.

3. The intelligent control method and system for a hydrogen generator set according to claim 1, characterized in that, The data analysis module calculates power grid structural integrity indicators and power quality stability indicators based on the key operating parameters, including... The power grid structural integrity index is determined based on the number of power transmission line switch trips and the number of relay protection action signals. The power quality stability index is determined based on the system active power deviation value and the voltage over-limit value of the key node.

4. The intelligent control method and system for a hydrogen generator set according to claim 3, characterized in that, The data analysis module determines the following indicators of power grid structural integrity: Based on the number of power line switch trips and the number of relay protection action signals, determine the power line switch trip frequency and the relay protection action signal frequency. The ratio of the tripping frequency of the transmission line switch to the tripping standard value is determined as the tripping parameter; The ratio of the relay protection action signal frequency to the protection standard value is determined as the protection parameter; The weighted sum of the tripping parameters and the protection parameters is determined as the power grid structure integrity index; The tripping standard value and the protection standard value are predetermined.

5. The intelligent control method and system for a hydrogen generator set according to claim 3, characterized in that, The data analysis module determines the power quality stability indicators, including: The ratio of the system's active power deviation value to the standard power deviation value is determined as the deviation parameter; The ratio of the voltage over-limit value of the key node to the voltage over-limit standard value is determined as the over-limit parameter; The weighted sum of the deviation parameter and the over-limit parameter is determined as the power quality stability index; The power deviation standard value and the voltage over-limit standard value are predetermined.

6. The intelligent control method and system for a hydrogen generator set according to claim 1, characterized in that, The operating condition division module divides the operating conditions corresponding to the time period into the following categories based on the comprehensive characteristic value corresponding to the time period and the preset operating condition threshold: The comprehensive characterization value corresponding to the time period is compared with the preset working condition threshold. If the comprehensive characterization value corresponding to the time period is greater than or equal to the preset operating condition threshold, then the time period is determined to be in a disturbed operating condition. If the comprehensive characteristic value corresponding to the time period is less than the preset operating condition threshold, then the time period is determined to be in a stable operating condition.

7. The intelligent control method and system for a hydrogen generator set according to claim 1, characterized in that, The strategy scheduling module adjusts the data collection interval for the next time period based on the operating conditions corresponding to the time period, including... If the time period is under a disturbance operation condition, the ratio of the preset operation condition threshold to the comprehensive characterization value corresponding to the time period is used as the dynamic detection coefficient for the next time period. The product of the basic standard acquisition interval and the dynamic detection coefficient is used to determine the acquisition interval for the next time period.

8. The intelligent control method and system for a hydrogen generator set according to claim 1, characterized in that, The strategy scheduling module also includes adjusting the collection interval for the next time period based on the operating conditions corresponding to the time period. If the time period is under stable operating conditions, the dynamic detection coefficient corresponding to the next time period will be set to 1; The product of the basic standard acquisition interval and the dynamic detection coefficient is used to determine the acquisition interval for the next time period.

9. The intelligent control method and system for a hydrogen generator set according to claim 1, characterized in that, The alarm module is used to compare the comprehensive characteristic value corresponding to the time period with a preset alarm threshold to determine whether to issue an alarm. If the comprehensive characterization value corresponding to the time period is greater than or equal to the preset alarm threshold, an early warning will be issued. If the comprehensive characterization value corresponding to the time period is less than the preset alarm threshold, no warning will be issued; Wherein, the preset alarm threshold is greater than the preset operating condition threshold.

10. A method for applying to an intelligent control system of a hydrogen generator set according to any one of claims 1-9, characterized in that, include: The key operating parameters of the power system connected to the hydrogen generator set within a time period are obtained according to the collection interval; the key operating parameters are: Based on the key operating parameters, the power grid structural integrity index and the power quality stability index are calculated, and the weighted sum of the power grid structural integrity index and the power quality stability index is determined as the comprehensive characterization value corresponding to the time period. The operating conditions corresponding to the time period are divided based on the comprehensive characterization value corresponding to the time period and the preset operating condition threshold. The data collection interval for the next time period is adjusted based on the operating conditions corresponding to the aforementioned time period. The comprehensive characterization value corresponding to the time period is compared with the preset alarm threshold to determine whether to issue an alarm.

Images