Intelligent frequency conversion control system of generator set cooling system

Abstract

The invention discloses an intelligent frequency conversion control system of a generator set cooling system, which relates to the technical field of industrial automation and energy equipment management and comprises a first temperature monitoring module, a satisfaction degree analysis module, a second temperature monitoring module, a frequency conversion analysis module and a frequency conversion control module. Monitoring the temperature states of inlets and outlets of cooling pipelines at heat source parts of each group of generators in the cooling time period so as to analyze the cooling satisfaction degree of a generator set cooling system to the generator set in the current cooling time period, and correspondingly sending a frequency conversion analysis instruction; monitoring the temperature state of the heat source part of each group of generators in real time in the cooling time period to analyze the frequency conversion regulation state required by the generator set cooling system for normally cooling each group of generators, and obtaining the frequency conversion regulation demand index Zcd of each group of generators; and comparing with a preset demand threshold value Y to obtain a grade frequency conversion control instruction of each group of generators and executing the grade frequency conversion control instruction.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial automation and energy equipment management, and in particular to an intelligent frequency conversion control system for a generator set cooling system. Background Art

[0002] With the widespread deployment of multiple parallel generating sets in large thermal, nuclear and backup power systems, the thermal stability of the generator under high load and high heat source density conditions has become a key factor restricting its continuous and safe operation. During the operation of the generator set, a large amount of heat will be generated in the windings, shafts and rectifiers. If it cannot be effectively cooled, it will directly lead to system heat accumulation, insulation aging, electrical performance degradation and even burning. Therefore, higher requirements are placed on the dynamic adaptability, precise adjustment capability and energy efficiency control capability of the cooling system.

[0003] Existing generator cooling systems mostly adopt a constant frequency conversion control mode, lacking the ability to dynamically identify and respond to the cooling needs of different generator heat source parts in a block-based manner. They usually rely on manually set cooling parameters and start and stop cooling devices with fixed temperature difference logic. When faced with complex working conditions such as changes in the operating status of each group of generators, load fluctuations, and interference from ambient temperature differences, it is difficult for such systems to perform differentiated treatment on each group of equipment, and it is also difficult to accurately adjust the flow rate and cooling frequency of the cooling medium, resulting in insufficient cooling and local overheating in some areas, and conversely, excessive cooling causing waste of resources. In addition, traditional cooling control systems lack the ability to integrate real-time data, perform edge computing processing, and build dynamic adjustment indexes, making it difficult to effectively achieve group frequency modulation and global thermal management optimization, resulting in delayed cooling response and low energy efficiency.

[0004] The above-mentioned deficiencies are mainly caused by the static and single nature of the existing cooling system control logic. On the one hand, the lack of multi-point temperature perception and heat exchange state modeling mechanism makes it difficult to accurately quantify the thermal intensity, temperature rise trend and cooling efficiency of each heating block. On the other hand, the cooling control mechanism fails to introduce a dynamic variable frequency adjustment factor, which makes it difficult for the system to adapt to the differences in the operating conditions of multiple groups of generators. When the cooling is insufficient, it may cause the motor winding temperature to continue to rise, the insulation level to decrease, and even the risk of thermal breakdown and power drop failure. Excessive cooling will cause energy waste. Therefore, constructing an intelligent cooling control system with distributed perception, variable frequency adaptive adjustment and cooling demand driving mechanism is of great significance and engineering application value for ensuring the stable operation of the generator set and improving energy utilization efficiency. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides an intelligent variable frequency control system for a cooling system of a generator set, which solves the problems in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent frequency conversion control system for a generator set cooling system, comprising a first temperature monitoring module, a satisfaction analysis module, a second temperature monitoring module, a frequency conversion analysis module and a frequency conversion control module; The first temperature monitoring module is used to monitor the temperature status of the cooling pipe inlet and outlet of each group of generator heat source parts during the cooling period to obtain relevant pipe temperature data information; The satisfaction analysis module analyzes the cooling satisfaction of the generator set cooling system to the generator set in the current cooling period based on the relevant pipeline temperature data information, and issues a frequency conversion analysis instruction accordingly; The second temperature monitoring module monitors the temperature status of the heat source parts of each group of generators in the cooling period in real time based on the received frequency conversion analysis instruction, obtains relevant generator temperature data information, and obtains relevant heat exchange cavity data information in combination with the generator structure parameter design drawing; The frequency conversion analysis module is used to analyze the frequency conversion regulation state required by the cooling system of the generator set for normal cooling of each group of generators, and obtain the frequency conversion regulation demand index Zcd of each group of generators; The frequency conversion control module is used to compare the frequency conversion regulation demand index Zcd of each group of generators with the preset demand threshold Y to obtain and execute the graded frequency conversion control instructions of each group of generators.

[0007] Preferably, the first temperature monitoring module includes a deployment unit and a coolant temperature monitoring unit; The deployment unit is used to arrange multiple groups of thermocouple temperature sensors at the heat source of each group of generators according to the cooling process of each group of generators by the cooling system of the generator set, and to set multiple groups of flow channel temperature sensors at the coolant inlet and outlet of the corresponding cooling pipeline at the heat source of each group of generators, and to wirelessly connect the multiple groups of temperature sensors to the edge computer by combining wireless communication technology. The edge computer pre-processes the data information obtained by the sensor, and then uniformly dispatches and uploads it to the data storage platform; The heat source parts of the generator include the stator winding, rotor shaft and bearing cavity. The data preprocessing of the edge calculator includes: removing noise, filling missing values ​​and data smoothing operations. The data storage platform is used to store the preprocessed data information.

[0008] Preferably, the coolant temperature monitoring unit is used to set multiple groups of flow channel temperature sensors at the coolant inlets and outlets of the corresponding cooling pipelines at the heat source parts of each group of generators according to the deployment unit, monitor the temperature status of the inlets and outlets of the cooling pipelines at the heat source parts of each group of generators during the cooling period, so as to obtain relevant pipeline temperature data information, send the obtained relevant pipeline temperature data information to the edge computer for data preprocessing, and then upload it to the data storage platform for storage, wherein the relevant pipeline temperature data information includes the inlet coolant temperature Trk and the outlet coolant temperature Tck of each group of generators during the cooling period.

[0009] Preferably, the satisfaction analysis module includes a pre-analysis unit and a determination unit; The pre-analysis unit is used to extract features from the relevant pipeline temperature data information in the data storage platform, associate the inlet coolant temperature Trk of each group of generators in the cooling period with the corresponding outlet coolant temperature Tck, and analyze the cooling satisfaction degree of the generator set cooling system to the generator set in the current cooling period after linear normalization processing, so as to obtain the cooling satisfaction coefficient Xry of the generator set cooling system, wherein the cooling satisfaction coefficient Xry is specifically obtained by the following formula: ; In the formula, It is represented as the outlet coolant temperature of the i-th group of generators, It is represented as the inlet coolant temperature of the i-th group of generators, i=1, 2, 3, ..., n, and n represents the number of generators cooled by the generator set cooling system.

[0010] Preferably, the determination unit is used to compare and analyze the cooling satisfaction coefficient Xry of the cooling system of the generator set with a preset satisfaction threshold R to preliminarily determine whether the cooling of the generator set by the cooling system of the generator set is in a suitable state during the current cooling period, and issue a frequency conversion analysis instruction accordingly. The specific comparative analysis content is as follows: If the cooling satisfaction coefficient Xry of the cooling system of the generator set is greater than the satisfaction threshold R, it means that the cooling system of the generator set is not in a satisfactory state for the cooling of the generator set in the current cooling period, indicating that the cooling system of the generator set is overcooling the generator set in the current cooling period, and a frequency conversion analysis instruction is issued externally at this time; If the cooling satisfaction coefficient Xry of the cooling system of the generator set is equal to the satisfaction threshold R, it means that the cooling system of the generator set is in a suitable state for the cooling of the generator set in the current cooling period, which means that the cooling system of the generator set just meets the normal cooling demand of the generator set in the current cooling period, and no additional frequency conversion analysis instruction is issued at this time; If the cooling satisfaction coefficient Xry of the generator set cooling system is less than the satisfaction threshold R, it means that the cooling of the generator set by the cooling system is not in a satisfactory state during the current cooling period, indicating that the cooling of the generator set by the cooling system is insufficient during the current cooling period, and a frequency conversion analysis instruction is issued.

[0011] Preferably, the second temperature monitoring module includes a heat source monitoring unit and a gradient pre-analysis unit; Based on the received frequency conversion analysis instruction and according to the cooling process of each group of generators by the cooling system of the generator set, the heat source monitoring unit monitors the temperature state of the heat source parts of each group of generators in the cooling period in real time, obtains relevant generator temperature data information, and at the same time, in combination with the generator structure parameter design drawing, collects the effective heat exchange cavity volume of each group of generator heat source parts, obtains relevant heat exchange cavity data information, sends the obtained relevant generator temperature data information and relevant heat exchange cavity data information to the edge computer for data preprocessing, and then uploads them to the data storage platform for storage, wherein the relevant generator temperature data information includes the current temperature value Tdq of each group of generators at each monitoring point in the cooling period, and the relevant heat exchange cavity data information includes the effective heat exchange cavity volume Vyx of each group of generators; The gradient pre-analysis unit is based on the relevant generator temperature data information obtained, combined with the statistical averaging algorithm, and after linear normalization processing, pre-analyzes the temperature change gradient of the heat source part of each group of generators in the cooling period to obtain the temperature change gradient coefficient Xbh of each group of generators, which is specifically obtained by the following formula: ; In the formula, It is represented by the current temperature value of the i-th group of generators at the j-th monitoring point during the cooling period, It is represented by the current temperature value of the i-th group of generators at the j-1-th monitoring point in the cooling period, j=1, 2, 3, ..., m, and m represents the number of monitoring points in the cooling period.

[0012] Preferably, the frequency conversion analysis module includes a heat exchange analysis unit, a cooling efficiency analysis unit and a demand analysis unit; The heat exchange analysis unit is used to extract the physical characteristic parameters of the coolant in the cooling system of the generator set according to the instruction manual of the cooling system of the generator set, so as to obtain the coolant characteristic data information, wherein the coolant characteristic data information includes the specific heat capacity Cbr and density Cmd of the coolant; Based on the temperature change gradient coefficient Xbh of each group of generators obtained after pre-analysis by the gradient pre-analysis unit, it is associated with the coolant characteristic data information and the relevant heat exchange cavity data information. After linear normalization processing, the heat exchange conditions of the heat source parts of each group of generators in the cooling period are analyzed to obtain the heat exchange density coefficient Xmd of each group of generators, which is specifically obtained by the following formula: ; In the formula, Expressed as the temperature change gradient coefficient of the i-th group of generators, It is represented as the effective heat exchange cavity volume of the i-th group of generators, Cbr is represented as the specific heat capacity of the coolant, and Cmd is represented as the density of the coolant.

[0013] Preferably, the cooling efficiency analysis unit is used to extract features from the relevant generator temperature data information, calculate the average value of the current temperature value Tdq of each group of generators at each monitoring point during the cooling period, and obtain the current temperature average value of each group of generators during the cooling period. ; By calculating the current average temperature of each group of generators during the cooling period And associated with the relevant pipeline temperature data information, the cooling efficiency of each group of generators in the cooling period is analyzed to obtain the cooling efficiency coefficient Xxv of each group of generators, which is specifically obtained by the following formula: ; In the formula, It is represented as the current mean temperature of the generator in the i-th group, It is represented as the outlet coolant temperature of the i-th group of generators, It is represented as the inlet coolant temperature of the i-th group of generators.

[0014] Preferably, the demand analysis unit associates the acquired relevant pipeline temperature data information, relevant generator temperature data information and relevant heat exchange cavity data information, and after linear normalization processing, analyzes the frequency conversion regulation state required by the generator set cooling system for normal cooling of each group of generators, and obtains the frequency conversion regulation demand index Zcd of each group of generators, which is specifically obtained by the following formula: ; In the formula, Expressed as the heat exchange density coefficient of the i-th group of generators, Expressed as the cooling efficiency coefficient of the i-th group of generators, and Both are expressed as weight values, and A is expressed as a correction constant.

[0015] Preferably, the level control module is used to compare the frequency conversion regulation demand index Zcd of each group of generators with the preset demand threshold Y, determine the frequency conversion regulation state required for normal cooling of the corresponding generator, and obtain and execute the level frequency conversion control instructions of each group of generators. The specific contents are as follows: If the frequency conversion regulation demand index Zcd of the corresponding generator is ≥ the demand threshold Y, it means that the frequency conversion regulation required for normal cooling of the corresponding generator is in the frequency increase state, and a first-level frequency conversion control instruction is generated and executed. The execution content is: dispatching the frequency converter of the corresponding generator cooling circuit to increase its operating frequency to a level higher than the current operating frequency; If the frequency conversion regulation demand index Zcd of the corresponding generator is less than the demand threshold Y, it means that the frequency conversion regulation required for normal cooling of the corresponding generator is in a frequency reduction state, and a secondary frequency conversion control instruction is generated and executed. The execution content is: dispatching the inverter of the corresponding generator cooling circuit to reduce its output frequency to below the current operating frequency.

[0016] The present invention provides an intelligent frequency conversion control system for a generator set cooling system, which has the following beneficial effects: (1) Aiming at the problems of lack of zoning identification, rough regulation, delayed response and imprecise energy efficiency control in the existing cooling system of generator sets, an intelligent control system with multi-source data acquisition, cooling state identification and frequency conversion regulation fusion mechanism is proposed. A dynamic judgment model with cooling satisfaction coefficient Xry and frequency conversion regulation demand index Zcd as the core is constructed, realizing a closed-loop linkage from cooling data monitoring to intelligent judgment and then to graded frequency conversion execution. By dynamically and accurately identifying the cooling state and heat exchange demand of each group of generators, the limitation of insufficient and excessive cooling coexisting in traditional control strategies is effectively overcome, and the response sensitivity, control accuracy and energy efficiency level of the cooling system are significantly improved, thereby ensuring the safety and stability of the generator sets under complex operating conditions.

[0017] (2) The temperature data of the coolant in the cooling system of the generator set at the inlet and outlet of the cooling pipe of the heat source part of each group of generators are correlated and calculated, and the cooling satisfaction coefficient Xry is constructed, so that the system can quantitatively judge whether the cooling system meets the heat release requirements of each group of generators during the current cooling period; when the cooling satisfaction coefficient Xry exceeds or falls below the preset threshold R, the system can immediately judge whether the current cooling behavior is excessive or insufficient, and automatically trigger the frequency conversion analysis instruction, thereby greatly improving the system's ability to recognize and respond to the cold and hot deviation state, realizing the transformation of the cooling process from experience-driven to data-driven, and enhancing the scientific nature of the cooling strategy and the stability of the system operation.

[0018] (3) By constructing a variable frequency analysis module, the coolant characteristic data information, effective heat exchange cavity data information, temperature change gradient coefficient Xbh and cooling efficiency coefficient Xxv of each group of generators are integrated with each other, and finally the variable frequency regulation demand index Zcd of each group of generators is obtained, realizing the intelligent identification and precision control of the variable frequency regulation state of the cooling system; when the variable frequency regulation demand index Zcd is higher or lower than the preset demand threshold Y, the first or second level variable frequency control instruction is automatically generated, and the corresponding frequency increase or frequency decrease operation is executed to ensure that the cooling medium flow rate and the heat exchange intensity are dynamically matched, thereby improving the system operation energy efficiency ratio and suppressing the frequent adjustment and system oscillation caused by hot and cold fluctuations. It has a high engineering applicability and intelligent control level. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a block diagram of an intelligent frequency conversion control system for a generator set cooling system of the present invention; Figure 2 It is a logical thinking diagram of an intelligent frequency conversion control system of a generator set cooling system of the present invention; Figure 3 It is a schematic diagram of the data transmission process of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Example 1 See also Figure 1 and Figure 2 , the present invention provides an intelligent frequency conversion control system for a generator set cooling system, comprising a first temperature monitoring module, a satisfaction analysis module, a second temperature monitoring module, a frequency conversion analysis module and a frequency conversion control module; The first temperature monitoring module is used to monitor the temperature status of the cooling pipe inlet and outlet of each group of generator heat source parts during the cooling period to obtain relevant pipe temperature data information; The satisfaction analysis module analyzes the cooling satisfaction of the generator set cooling system to the generator set in the current cooling period based on the relevant pipeline temperature data information, and issues a frequency conversion analysis instruction accordingly; The second temperature monitoring module monitors the temperature status of the heat source parts of each group of generators in the cooling period in real time based on the received frequency conversion analysis instruction, obtains relevant generator temperature data information, and obtains relevant heat exchange cavity data information in combination with the generator structure parameter design drawing; The frequency conversion analysis module is used to analyze the frequency conversion regulation state required by the cooling system of the generator set for normal cooling of each group of generators, and obtain the frequency conversion regulation demand index Zcd of each group of generators; The frequency conversion control module is used to compare the frequency conversion regulation demand index Zcd of each group of generators with the preset demand threshold Y to obtain and execute the graded frequency conversion control instructions of each group of generators.

[0022] In this embodiment, by constructing a hierarchical perception and linkage control architecture including a first temperature monitoring module, a satisfaction analysis module, a second temperature monitoring module, a frequency conversion analysis module and a frequency conversion control module, intelligent, partitioned and dynamic management of the cooling process of the generator set is achieved; first, the real-time temperature data of the inlet and outlet of the cooling pipeline is obtained through the first temperature monitoring module, and the heat exchange characteristic parameter basis of the cooling medium at each generator heat source is established; then, the satisfaction analysis module performs a preliminary analysis of the cooling state to determine whether the cooling is excessive or insufficient, and accordingly issues a frequency conversion analysis instruction to achieve a control logic transition from temperature difference judgment to thermal satisfaction judgment; then, the second temperature monitoring module further obtains the temperature of the heat source body and the heat exchange cavity information of each group of generators in combination with the structural drawings, for subsequent The regulation model provides more accurate data support; the frequency conversion analysis module establishes a two-way model of cooling demand and efficiency based on the above multi-source data, and calculates the current frequency conversion regulation demand index Zcd of each group of generators, so that the system can accurately evaluate the actual regulation demand of each group of generators in terms of cooling intensity; finally, the frequency conversion control module compares Zcd with the preset threshold and generates a hierarchical frequency conversion control instruction to achieve independent frequency regulation in groups and differentiated cooling execution strategies; the outstanding advantages of this system are: it not only realizes dynamic perception and real-time regulation of the cooling process, but also constructs a closed-loop mechanism of multi-parameter fusion, hierarchical response, and fine control, which significantly improves the thermal safety assurance capability, cooling efficiency and energy utilization level during the operation of the generator set, and has high adaptability, high responsiveness and high intelligence.

[0023] Example 2 Please refer to Figure 1 and Figure 3 ,Specifically: the first temperature monitoring module includes a deployment unit and a coolant temperature monitoring unit; The deployment unit is used to arrange multiple groups of thermocouple temperature sensors at the heat source of each group of generators according to the cooling process of each group of generators by the cooling system of the generator set, and to set multiple groups of flow channel temperature sensors at the coolant inlet and outlet of the corresponding cooling pipeline at the heat source of each group of generators, and to wirelessly connect the multiple groups of temperature sensors to the edge computer by combining wireless communication technology. The edge computer pre-processes the data information obtained by the sensor, and then uniformly dispatches and uploads it to the data storage platform; It should be noted that the edge computer and the data storage platform jointly build a local processing and centralized management framework for temperature monitoring data in this system. The edge computer is mainly responsible for local preprocessing of the raw data collected by multiple groups of wireless temperature sensors, including noise removal, missing value filling and data smoothing, to improve the reliability and real-time performance of the data, and to uniformly schedule and manage the processed data; the data storage platform is used for centralized storage, classification and archiving of high-quality temperature data uploaded by the edge computer, and subsequent analysis and call, to ensure that the system has complete, continuous and traceable temperature information support during the execution of cooling state identification, frequency modulation analysis and intelligent decision-making, thereby realizing the intelligent, data-based and closed-loop control of the system operation.

[0024] The heat source parts of the generator include the stator winding, rotor shaft and bearing cavity. The data preprocessing of the edge calculator includes: removing noise, filling missing values ​​and data smoothing operations. The data storage platform is used to store the preprocessed data information.

[0025] Specifically, the coolant temperature monitoring unit is used to set up multiple groups of flow channel temperature sensors at the coolant inlets and outlets of the corresponding cooling pipelines at the heat source parts of each group of generators according to the deployment unit, and monitor the temperature status of the inlets and outlets of the cooling pipelines at the heat source parts of each group of generators during the cooling period to obtain relevant pipeline temperature data information, and send the obtained relevant pipeline temperature data information to the edge computer for data preprocessing, and then upload it to the data storage platform for storage, wherein the relevant pipeline temperature data information includes the inlet coolant temperature Trk and the outlet coolant temperature Tck of each group of generators during the cooling period.

[0026] It should be noted that the inlet coolant temperature Trk and the outlet coolant temperature Tck respectively represent the entry temperature and exit temperature of the coolant when it flows through the heat source of each group of generators during the cooling period, reflecting the heat exchange effect completed by the coolant in this area; Trk represents the temperature state of the coolant before it initially enters the cooling pipeline, and Tck represents the temperature value of the coolant after the heat absorption process is completed; by arranging flow channel temperature sensors at the inlet and outlet of each group of generator cooling pipelines, these two parameters can be collected in real time, and their data can be transmitted to the edge computer for preprocessing; the temperature difference between the inlet coolant temperature Trk and the outlet coolant temperature Tck can not only be used to calculate the heat exchange efficiency of the cooling process, but also is the data support for the subsequent analysis of cooling satisfaction and frequency modulation requirements, and plays a key role in achieving precise cooling control.

[0027] In this embodiment, a high-precision, high-stability, and low-latency cooling temperature monitoring mechanism is constructed through the collaborative design of the deployment unit and the coolant temperature monitoring unit; by arranging multiple groups of thermocouple temperature sensors at the key heat source parts of the generator (such as stator windings, rotor shafts, and bearing cavities), and configuring multiple groups of flow channel temperature sensors at the inlet and outlet of the corresponding coolant pipelines, the system can achieve two-dimensional perception of the temperature change of the cooling medium and the actual thermal state of the heat source; the edge computer is connected by wireless communication, which effectively reduces the complexity of traditional wiring and communication delay, while improving the flexibility and scalability of system deployment; the edge computer performs multiple preprocessing operations on the original temperature data, including denoising, missing value compensation, and data smoothing, to ensure that the data uploaded to the data storage platform has high availability and high robustness; the coolant temperature monitoring unit focuses on collecting the inlet coolant temperature Trk and outlet coolant temperature Tck of each generator cooling channel, so that the system can accurately analyze the heat exchange efficiency and temperature difference fluctuations during the cooling process, and provide a real-time, reliable, and complete data basis for subsequent cooling satisfaction analysis and frequency conversion regulation.

[0028] Example 3 Please refer to Figure 1 ,Specifically: the satisfaction analysis module includes a pre-analysis unit and a determination unit; The pre-analysis unit is used to extract features from the relevant pipeline temperature data information in the data storage platform, associate the inlet coolant temperature Trk of each group of generators in the cooling period with the corresponding outlet coolant temperature Tck, and analyze the cooling satisfaction degree of the generator set cooling system to the generator set in the current cooling period after linear normalization processing, so as to obtain the cooling satisfaction coefficient Xry of the generator set cooling system, wherein the cooling satisfaction coefficient Xry is specifically obtained by the following formula: ; In the formula, It is represented as the outlet coolant temperature of the i-th group of generators, It is represented by the inlet coolant temperature of the i-th group of generators, i=1, 2, 3, ..., n, n represents the number of generators cooled by the generator set cooling system, When the temperature difference between the coolant inlet and outlet is too small or too large, it means the cooling effect is excessive or insufficient.

[0029] It should be noted that the cooling satisfaction coefficient Xry reflects the overall ability of the cooling system to remove the heat from the generator in the current period; it is highly related to the problems pointed out in the background technology that the traditional system is difficult to accurately identify whether the cooling is excessive or insufficient, and the adjustment basis is single and the control response is delayed; the cooling satisfaction coefficient Xry, as a quantifiable evaluation indicator, realizes a comprehensive judgment on the actual cooling effect of each group of generators. The larger the value, the overcooling; the lower the value, the insufficient cooling; therefore, the introduction of the cooling satisfaction coefficient Xry enables the system to have the ability to dynamically evaluate and judge the cooling status, and provides a clear and quantitative criterion for subsequent frequency conversion adjustment instructions, effectively solving the technical bottleneck of the traditional cooling system adjustment relying on experience and lack of real-time fit analysis.

[0030] Specifically, the determination unit is used to compare and analyze the cooling satisfaction coefficient Xry of the cooling system of the generator set with the preset satisfaction threshold R to preliminarily determine whether the cooling of the generator set by the cooling system of the generator set is in a suitable state during the current cooling period, and issue a frequency conversion analysis instruction accordingly. The specific comparison and analysis contents are as follows: If the cooling satisfaction coefficient Xry of the cooling system of the generator set is greater than the satisfaction threshold R, it means that the cooling system of the generator set is not in a satisfactory state for the cooling of the generator set in the current cooling period, indicating that the cooling system of the generator set is overcooling the generator set in the current cooling period, and a frequency conversion analysis instruction is issued externally at this time; If the cooling satisfaction coefficient Xry of the cooling system of the generator set is equal to the satisfaction threshold R, it means that the cooling system of the generator set is in a suitable state for the cooling of the generator set in the current cooling period, which means that the cooling system of the generator set just meets the normal cooling demand of the generator set in the current cooling period, and no additional frequency conversion analysis instruction is issued at this time; If the cooling satisfaction coefficient Xry of the generator set cooling system is less than the satisfaction threshold R, it means that the cooling of the generator set by the cooling system is not in a satisfactory state during the current cooling period, indicating that the cooling of the generator set by the cooling system is insufficient during the current cooling period, and a frequency conversion analysis instruction is issued.

[0031] In this embodiment, through the coordinated operation of the pre-analysis unit and the judgment unit, a cooling state evaluation mechanism based on heat exchange feature recognition is constructed, which realizes the quantitative judgment of the operation fit of the cooling system of the generator set; after obtaining the relevant pipeline temperature data information, the pre-analysis unit uses linear normalization processing to extract features and standardize calculations, and constructs the cooling satisfaction coefficient Xry as a dynamic indicator to characterize whether the cooling process meets the actual heat exchange demand, which significantly improves the system's adaptability to the cooling effect of different operating stages; by comparing the cooling satisfaction coefficient Xry with the preset satisfaction threshold R, the judgment unit can clearly identify whether the current cooling is overcooling or insufficient cooling. , and trigger the frequency conversion analysis instruction accordingly; the introduction of this mechanism not only makes up for the limitations of the traditional system that relies on absolute temperature difference or human experience judgment, but also establishes a continuous judgment model of "satisfaction-overcooling-insufficient", so that the system has the pre-decision-making ability of self-identification and self-adjustment of cooling status; the advantage is: through a quantifiable cooling satisfaction coefficient Xry, dynamic matching and advance perception of cooling effect are realized, the accuracy and intelligence level of system cooling regulation are improved, and at the same time, a clear logical premise is provided for subsequent frequency conversion analysis and control, which effectively avoids thermal safety hazards and energy waste caused by improper cooling strategies, and is a key link in achieving high reliability and high energy efficiency cooling management.

[0032] Example 4 Please refer to Figure 1 ,Specifically: the second temperature monitoring module includes a heat source monitoring unit and a gradient pre-analysis unit; Based on the received frequency conversion analysis instruction and according to the cooling process of each group of generators by the cooling system of the generator set, the heat source monitoring unit monitors the temperature state of the heat source parts of each group of generators in the cooling period in real time, obtains relevant generator temperature data information, and at the same time, in combination with the generator structure parameter design drawing, collects the effective heat exchange cavity volume of each group of generator heat source parts, obtains relevant heat exchange cavity data information, sends the obtained relevant generator temperature data information and relevant heat exchange cavity data information to the edge computer for data preprocessing, and then uploads them to the data storage platform for storage, wherein the relevant generator temperature data information includes the current temperature value Tdq of each group of generators at each monitoring point in the cooling period, and the relevant heat exchange cavity data information includes the effective heat exchange cavity volume Vyx of each group of generators; It should be noted that the current temperature value Tdq refers to the real-time generator temperature data collected by temperature sensors deployed at the heat source parts of each group of generators (such as stator windings, rotor shafts and bearing cavities) during the cooling period, reflecting the thermal state of the heat source area during the operation of the generator; and the effective heat exchange cavity volume Vyx represents the geometric volume in the corresponding heat source area that is in direct contact with the coolant and participates in heat exchange, which is usually extracted based on the generator structural parameter design drawing or CAD model; the role of these two parameters in the system is to serve as the basic basis for subsequent analysis of the heat change trend and heat exchange requirements within the unit volume of each block. The current temperature value Tdq is used to judge the temperature rise rate and cooling efficiency, and the effective heat exchange cavity volume Vyx is used to evaluate the heat density and heat exchange capacity; the combination of the two can construct the key parameters of temperature gradient changes and heat exchange density, support the quantitative modeling and analysis of cooling regulation requirements, and is the core data support for achieving system fine control and dynamic thermal management.

[0033] The gradient pre-analysis unit is based on the relevant generator temperature data information obtained, combined with the statistical averaging algorithm, and after linear normalization processing, pre-analyzes the temperature change gradient of the heat source part of each group of generators in the cooling period to obtain the temperature change gradient coefficient Xbh of each group of generators, which is specifically obtained by the following formula: ; In the formula, It is represented by the current temperature value of the i-th group of generators at the j-th monitoring point during the cooling period, It is represented by the current temperature value of the i-th group of generators at the j-1-th monitoring point in the cooling period, j=1, 2, 3, ..., m, and m represents the number of monitoring points in the cooling period.

[0034] It should be noted that the temperature change gradient coefficient Xbh is a temperature change rate indicator obtained by taking the absolute value and averaging the differential processing of the generator heat source temperature value Tdq collected from multiple consecutive monitoring points during the cooling period, which is used to reflect the dynamic trend of temperature rise or temperature drop of a certain block of generators during the cooling process; the formula and its parameter design are directly related to the technical deficiencies pointed out in the background technology that the existing cooling system is difficult to identify the temperature change trend in real time and only relies on static temperature values ​​to judge the cooling state, resulting in response lag and passive control strategy; traditional systems often ignore the gradient and feedforward characteristics of temperature changes and are difficult to effectively predict the occurrence of thermal imbalance; and the temperature change gradient coefficient Xbh, as a quantitative indicator reflecting the intensity of temperature fluctuations, has the ability to perceive the trend of heat source heating risks, can realize early triggering and adjustment optimization of cooling response, and provide a dynamic basis for subsequent heat exchange density calculation and variable frequency adjustment strategy formulation, which significantly improves the system's adaptability to complex operating conditions and the forward-looking nature of intelligent control, and is a key supporting parameter for effectively solving the perception lag and adjustment delay problems of traditional cooling systems.

[0035] In this embodiment, by integrating the heat source monitoring unit and the gradient pre-analysis unit, a deep temperature perception and trend assessment mechanism for the dynamic changes of the thermal characteristics of the generator operation is constructed, which realizes the pre-identification and quantitative support of the cooling regulation demand; the heat source monitoring unit not only realizes responsive monitoring of the cooling process based on the variable frequency analysis instruction, but also combines the generator structure parameter design diagram to collect volume data of the effective heat exchange cavity in the heat source area of ​​each group of generators, thereby realizing the synchronous fusion of thermal state data and structural thermal capacity data; the temperature value Tdq of each monitoring point and the volume Vyx of the heat exchange cavity obtained are synchronously uploaded to the edge calculator for data cleaning and structured processing to ensure that the subsequent analysis module has high-quality input; in this On this basis, the gradient pre-analysis unit combines statistical mean calculation and linear normalization method to dynamically identify the temperature changes of the heat source of each group of generators during the cooling period, and constructs the temperature change gradient coefficient Xbh; the temperature change gradient coefficient Xbh not only reflects the temperature rise or temperature drop rate, but also can be used as a basis for determining the urgency of the cooling response; its advantages are: by integrating time series analysis and structural parameters, the system is given the ability to characterize temperature changes, thereby identifying temperature control risks in advance before cooling strategy decisions are made, and predictive prediction and strategy advancement of cooling adjustment are achieved; it improves the foresight and response agility of the system's cooling adjustment under complex operating conditions, and is an indispensable basic layer support for building a refined thermal management system.

[0036] Example 5 Please refer to Figure 1 ,Specifically: the frequency conversion analysis module includes a heat exchange analysis unit, a cooling ,efficiency analysis unit and a demand analysis unit; The heat exchange analysis unit is used to extract the physical characteristic parameters of the coolant in the cooling system of the generator set according to the instruction manual of the cooling system of the generator set, so as to obtain the coolant characteristic data information, wherein the coolant characteristic data information includes the specific heat capacity Cbr and density Cmd of the coolant; Based on the temperature change gradient coefficient Xbh of each group of generators obtained after pre-analysis by the gradient pre-analysis unit, it is associated with the coolant characteristic data information and the relevant heat exchange cavity data information. After linear normalization processing, the heat exchange conditions of the heat source parts of each group of generators in the cooling period are analyzed to obtain the heat exchange density coefficient Xmd of each group of generators, which is specifically obtained by the following formula: ; In the formula, Expressed as the temperature change gradient coefficient of the i-th group of generators, is represented by the effective heat exchange cavity volume of the i-th group of generators, Cbr is represented by the specific heat capacity of the coolant, Cmd is represented by the density of the coolant, It is expressed as the heat exchange demand of the cooling medium under the actual temperature rise and temperature drop rate.

[0037] It should be noted that the heat exchange density coefficient Xmd is a comprehensive heat load intensity index constructed based on the physical property parameters of the coolant (specific heat capacity Cbr and density Cmd), the temperature change gradient coefficient Xbh and the effective heat exchange cavity volume Vyx of the generator, which represents the heat density that the unit volume of the cooling cavity needs to absorb in unit time; this formula is highly related to the problem that the traditional cooling system mentioned in the background technology fails to comprehensively consider the coolant thermal physical parameters, the thermal characteristics of the equipment structure and the temperature change trend, resulting in a single cooling adjustment model and insufficient adjustment accuracy; by introducing the specific heat capacity Cbr and density Cmd of the coolant, the system can quantify the cooling medium The actual heat absorption capacity of the quality; combined with the temperature change gradient coefficient Xbh, it reflects the current thermal change rate of the equipment; combined with the effective heat exchange cavity volume Vyx, the actual heat exchange demand density of each generator cooling system is obtained; the role of the heat exchange density coefficient Xmd is to provide key heat load input for the subsequent frequency conversion regulation demand index, so that the cooling control not only considers whether the temperature rises, but also considers whether the temperature rises quickly, whether the heat absorption is difficult, and whether the structure is under great pressure, thereby realizing a cooling regulation strategy that is more in line with the actual thermal characteristics of the equipment. It is an important parameter to support refined and structured frequency regulation decisions, and significantly improves the system's understanding and response capabilities to complex thermal coupling relationships.

[0038] Specifically, the cooling efficiency analysis unit is used to extract features from the relevant generator temperature data information, calculate the average value of the current temperature value Tdq of each group of generators at each monitoring point during the cooling period, and obtain the current average temperature value of each group of generators during the cooling period. ; By calculating the current average temperature of each group of generators during the cooling period And associated with the relevant pipeline temperature data information, the cooling efficiency of each group of generators in the cooling period is analyzed to obtain the cooling efficiency coefficient Xxv of each group of generators, which is specifically obtained by the following formula: ; In the formula, It is represented as the current mean temperature of the generator in the i-th group, It is represented as the outlet coolant temperature of the i-th group of generators, It is represented as the inlet coolant temperature of the i-th group of generators.

[0039] It should be noted that the cooling efficiency coefficient Xxv is a ratio obtained by comparing the current temperature value Tdq of the generator with the corresponding inlet and outlet temperatures of the coolant, which is used to reflect the actual heat absorption efficiency of the coolant within a unit temperature difference range; the cooling efficiency coefficient Xxv represents the actual degree of heat absorbed by the coolant within the temperature difference range between the current temperature value Tdq of each group of generators and the inlet coolant temperature Trk and the outlet coolant temperature Tck of the coolant; it is not only used to judge the immediate effectiveness of the cooling process, but also serves as an important input indicator for measuring the cooling degree in the frequency conversion regulation strategy, and is one of the key parameters for achieving on-demand frequency regulation, dynamic energy saving and preventing over-cooling; Specifically, the demand analysis unit associates the acquired relevant pipeline temperature data information, relevant generator temperature data information and relevant heat exchange cavity data information, and after linear normalization processing, analyzes the frequency conversion regulation state required by the generator set cooling system for normal cooling of each group of generators, and obtains the frequency conversion regulation demand index Zcd of each group of generators, which is specifically obtained through the following formula: ; In the formula, Expressed as the heat exchange density coefficient of the i-th group of generators, Expressed as the cooling efficiency coefficient of the i-th group of generators, and are all expressed as weight values, and A is expressed as a correction constant, where: Indicates the degree of cooling efficiency deficiency.

[0040] It should be noted that the variable frequency regulation demand index Zcd is a dynamic regulation index calculated by combining the weighted sum of the heat exchange density coefficient Xmd and the cooling efficiency coefficient Xxv of the generator and the correction constant A, and is used to determine whether each group of generators currently needs to increase or decrease the variable frequency operation state of the cooling system; the design of the variable frequency regulation demand index Zcd is closely related to the technical deficiency pointed out in the background technology that the traditional cooling system has a single regulation basis and it is difficult to comprehensively analyze the cold and heat imbalance and the change of system thermal efficiency in real time; by introducing the heat exchange density coefficient Xmd, the actual heat load density is quantified; by introducing the cooling efficiency coefficient Xxv, the current cooling efficiency is evaluated, and the variable frequency regulation demand index Zcd constructed after weighing the two can accurately reflect whether the current cooling intensity matches the heat load demand; its role is to serve as the core control quantity and judgment basis for the cooling system to execute variable frequency regulation, and to improve the energy efficiency ratio, thermal matching and operation intelligence level of the cooling system.

[0041] In this embodiment, through the collaborative construction of the heat exchange analysis unit, the cooling efficiency analysis unit and the demand analysis unit, an intelligent cooling regulation decision-making mechanism for multi-parameter fusion, dynamic response and group adaptation is formed, which realizes the refined judgment of the variable frequency regulation state of the generator set cooling system; the heat exchange analysis unit extracts the physical characteristic parameters of the coolant (including specific heat capacity Cbr and density Cmd) based on the instruction manual of the generator set cooling system, combines the temperature change gradient coefficient Xbh obtained by the previous gradient pre-analysis and the heat exchange cavity volume Vyx corresponding to each group of generators, calculates and generates the heat exchange density coefficient Xmd, and comprehensively quantifies the heat exchange intensity required per unit volume of each generator block per unit time; the cooling efficiency analysis unit obtains the current temperature value Tdq of each monitoring point by counting the current temperature value Tdq and obtaining the current temperature average , and correlated it with the inlet and outlet temperature difference of the coolant to construct the cooling efficiency coefficient Xxv, which accurately describes the actual heat absorption efficiency of the coolant in the heat conduction process; based on the above two core indicators, the demand analysis unit correlates the cooling intensity demand with the actual cooling effect and generates the variable frequency regulation demand index Zcd, which serves as the core quantitative basis for measuring whether frequency increase or frequency decrease is required; the advantage lies in: by introducing the three-dimensional coupling analysis of coolant thermophysical properties, heat exchange geometry and dynamic thermal state data, a comprehensive regulation logic based on physical mechanism, operating status and system feedback is established, which significantly enhances the cooling system's adaptive judgment ability for changes in operating conditions, and provides key intelligent decision-making support for efficient, stable and safe cooling management of generator sets.

[0042] Example 6 Please refer to Figure 1 Specifically, the level control module is used to compare the frequency conversion regulation demand index Zcd of each group of generators with the preset demand threshold Y, determine the frequency conversion regulation state required for normal cooling of the corresponding generator, and obtain and execute the level frequency conversion control instructions of each group of generators. The specific contents are as follows: If the frequency conversion regulation demand index Zcd of the corresponding generator is ≥ the demand threshold Y, it means that the frequency conversion regulation required for normal cooling of the corresponding generator is in the frequency increase state, and a first-level frequency conversion control instruction is generated and executed. The execution content is: dispatching the frequency converter of the corresponding generator cooling circuit to increase its operating frequency to a level higher than the current operating frequency; If the frequency conversion regulation demand index Zcd of the corresponding generator is less than the demand threshold Y, it means that the frequency conversion regulation required for normal cooling of the corresponding generator is in a frequency reduction state, and a secondary frequency conversion control instruction is generated and executed. The execution content is: dispatching the inverter of the corresponding generator cooling circuit to reduce its output frequency to below the current operating frequency.

[0043] In this embodiment, by introducing a comparison mechanism between the frequency conversion regulation demand index Zcd and the preset demand threshold Y, a hierarchical frequency regulation execution system with fast response and precise control is constructed, and intelligent matching and regulation of the cooling status of each group of generators is realized; the system judges the strength of the current cooling demand according to the size of the frequency conversion regulation demand index Zcd. If the frequency conversion regulation demand index Zcd is higher than the demand threshold Y, a first-level frequency increase control instruction is automatically generated to increase the operating frequency of the corresponding cooling circuit inverter to quickly enhance the cooling capacity; if the frequency conversion regulation demand index Zcd is lower than the demand threshold Y, a second-level frequency reduction control instruction is triggered to reduce the inverter frequency output. It effectively suppresses over-cooling and reduces energy consumption. The mechanism no longer relies on unified regulation and artificially set fixed cooling logic, but realizes differentiated and zoned frequency modulation response for the thermal state of each group of generators, ensuring that each cooling circuit achieves energy efficiency optimization while meeting thermal management requirements. Its special advantage is that through the fine control of hierarchical frequency conversion instructions, it has the ability to dynamically allocate cooling resources in real time according to cooling needs, effectively avoiding the traditional contradiction of coexistence of cooling redundancy and cooling lag, and improving the flexible adaptability and regulation efficiency of the generator set cooling system to changes in operating loads. It is the core execution link for realizing the closed-loop mechanism of intelligent control of generator set cooling.

[0044] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent frequency conversion control system for a generator set cooling system, characterized in that: It includes a first temperature monitoring module, a satisfaction analysis module, a second temperature monitoring module, a frequency conversion analysis module and a frequency conversion control module; The first temperature monitoring module is used to monitor the temperature status of the cooling pipe inlet and outlet of each group of generator heat source parts during the cooling period to obtain relevant pipe temperature data information; The satisfaction analysis module analyzes the cooling satisfaction of the generator set cooling system to the generator set in the current cooling period based on the relevant pipeline temperature data information, and issues a frequency conversion analysis instruction accordingly; The second temperature monitoring module monitors the temperature status of the heat source parts of each group of generators in the cooling period in real time based on the received frequency conversion analysis instruction, obtains relevant generator temperature data information, and obtains relevant heat exchange cavity data information in combination with the generator structure parameter design drawing; The frequency conversion analysis module is used to analyze the frequency conversion regulation state required by the cooling system of the generator set for normal cooling of each group of generators, and obtain the frequency conversion regulation demand index Zcd of each group of generators; The frequency conversion control module is used to compare the frequency conversion regulation demand index Zcd of each group of generators with the preset demand threshold Y to obtain and execute the graded frequency conversion control instructions of each group of generators.

2. The intelligent frequency conversion control system of a generator set cooling system according to claim 1, characterized in that: The first temperature monitoring module includes a deployment unit and a coolant temperature monitoring unit; The deployment unit is used to arrange multiple groups of thermocouple temperature sensors at the heat source of each group of generators according to the cooling process of each group of generators by the cooling system of the generator set, and to set multiple groups of flow channel temperature sensors at the coolant inlet and outlet of the corresponding cooling pipeline at the heat source of each group of generators, and to wirelessly connect the multiple groups of temperature sensors to the edge computer by combining wireless communication technology. The edge computer pre-processes the data information obtained by the sensor, and then uniformly dispatches and uploads it to the data storage platform; The heat source parts of the generator include the stator winding, rotor shaft and bearing cavity. The data preprocessing of the edge calculator includes: removing noise, filling missing values ​​and data smoothing operations. The data storage platform is used to store the preprocessed data information.

3. The intelligent frequency conversion control system of a generator set cooling system according to claim 2, characterized in that: The coolant temperature monitoring unit is used to set up multiple groups of flow channel temperature sensors at the coolant inlets and outlets of the corresponding cooling pipelines at the heat source parts of each group of generators according to the deployment unit, monitor the temperature status of the inlets and outlets of the cooling pipelines at the heat source parts of each group of generators during the cooling period, so as to obtain relevant pipeline temperature data information, send the obtained relevant pipeline temperature data information to the edge computer for data preprocessing, and then upload it to the data storage platform for storage, wherein the relevant pipeline temperature data information includes the inlet coolant temperature Trk and the outlet coolant temperature Tck of each group of generators during the cooling period.

4. The intelligent frequency conversion control system of a generator set cooling system according to claim 3 is characterized in that: The satisfaction analysis module includes a pre-analysis unit and a determination unit; The pre-analysis unit is used to extract features from the relevant pipeline temperature data information in the data storage platform, associate the inlet coolant temperature Trk of each group of generators in the cooling period with the corresponding outlet coolant temperature Tck, and analyze the cooling satisfaction degree of the generator set cooling system to the generator set in the current cooling period after linear normalization processing, so as to obtain the cooling satisfaction coefficient Xry of the generator set cooling system, wherein the cooling satisfaction coefficient Xry is specifically obtained by the following formula: ； In the formula, It is represented as the outlet coolant temperature of the i-th group of generators, It is represented as the inlet coolant temperature of the i-th group of generators, i=1, 2, 3, ..., n, and n represents the number of generators cooled by the generator set cooling system.

5. The intelligent frequency conversion control system of a generator set cooling system according to claim 4, characterized in that: The determination unit is used to compare and analyze the cooling satisfaction coefficient Xry of the cooling system of the generator set with the preset satisfaction threshold R to preliminarily determine whether the cooling of the generator set by the cooling system of the generator set is in a suitable state during the current cooling period, and issue a frequency conversion analysis instruction accordingly. The specific comparison and analysis contents are as follows: If the cooling satisfaction coefficient Xry of the cooling system of the generator set is greater than the satisfaction threshold R, it means that the cooling system of the generator set is not in a satisfactory state for the cooling of the generator set in the current cooling period, indicating that the cooling system of the generator set is overcooling the generator set in the current cooling period, and a frequency conversion analysis instruction is issued externally at this time; If the cooling satisfaction coefficient Xry of the cooling system of the generator set is equal to the satisfaction threshold R, it means that the cooling system of the generator set is in a suitable state for the cooling of the generator set in the current cooling period, which means that the cooling system of the generator set just meets the normal cooling demand of the generator set in the current cooling period, and no additional frequency conversion analysis instruction is issued at this time; If the cooling satisfaction coefficient Xry of the generator set cooling system is less than the satisfaction threshold R, it means that the cooling of the generator set by the cooling system is not in a satisfactory state during the current cooling period, indicating that the cooling of the generator set by the cooling system is insufficient during the current cooling period, and a frequency conversion analysis instruction is issued.

6. The intelligent frequency conversion control system of a generator set cooling system according to claim 5, characterized in that: The second temperature monitoring module includes a heat source monitoring unit and a gradient pre-analysis unit; Based on the received frequency conversion analysis instruction and according to the cooling process of each group of generators by the cooling system of the generator set, the heat source monitoring unit monitors the temperature state of the heat source parts of each group of generators in the cooling period in real time, obtains relevant generator temperature data information, and at the same time, in combination with the generator structure parameter design drawing, collects the effective heat exchange cavity volume of each group of generator heat source parts, obtains relevant heat exchange cavity data information, sends the obtained relevant generator temperature data information and relevant heat exchange cavity data information to the edge computer for data preprocessing, and then uploads them to the data storage platform for storage, wherein the relevant generator temperature data information includes the current temperature value Tdq of each group of generators at each monitoring point in the cooling period, and the relevant heat exchange cavity data information includes the effective heat exchange cavity volume Vyx of each group of generators; The gradient pre-analysis unit is based on the relevant generator temperature data information obtained, and combined with the statistical averaging algorithm, after linear normalization processing, pre-analyzes the temperature change gradient of the heat source part of each group of generators during the cooling period to obtain the temperature change gradient coefficient Xbh of each group of generators.

7. The intelligent frequency conversion control system of a generator set cooling system according to claim 6, characterized in that: The frequency conversion analysis module includes a heat exchange analysis unit, a cooling efficiency analysis unit and a demand analysis unit; The heat exchange analysis unit is used to extract the physical characteristic parameters of the coolant in the cooling system of the generator set according to the instruction manual of the cooling system of the generator set, so as to obtain the coolant characteristic data information, wherein the coolant characteristic data information includes the specific heat capacity Cbr and density Cmd of the coolant; Based on the temperature change gradient coefficient Xbh of each group of generators obtained after pre-analysis by the gradient pre-analysis unit, it is associated with the coolant characteristic data information and the relevant heat exchange cavity data information. After linear normalization processing, the heat exchange conditions of the heat source parts of each group of generators in the cooling period are analyzed to obtain the heat exchange density coefficient Xmd of each group of generators, which is specifically obtained by the following formula: ； In the formula, Expressed as the temperature change gradient coefficient of the i-th group of generators, It is represented as the effective heat exchange cavity volume of the i-th group of generators, Cbr is represented as the specific heat capacity of the coolant, and Cmd is represented as the density of the coolant.

8. The intelligent frequency conversion control system of a generator set cooling system according to claim 7, characterized in that: The cooling efficiency analysis unit is used to extract the features of the relevant generator temperature data information, calculate the average value of the current temperature value Tdq of each group of generators at each monitoring point during the cooling period, and obtain the current average temperature value of each group of generators during the cooling period. ; By calculating the current average temperature of each group of generators during the cooling period And it is associated with the relevant pipeline temperature data information, and the cooling efficiency of each group of generators in the cooling period is analyzed to obtain the cooling efficiency coefficient Xxv of each group of generators.

9. The intelligent frequency conversion control system of a generator set cooling system according to claim 8, characterized in that: The demand analysis unit associates the acquired relevant pipeline temperature data information, relevant generator temperature data information and relevant heat exchange cavity data information, and after linear normalization processing, analyzes the frequency conversion regulation state required by the generator set cooling system for normal cooling of each group of generators, and obtains the frequency conversion regulation demand index Zcd of each group of generators, which is specifically obtained through the following formula: ； In the formula, Expressed as the heat exchange density coefficient of the i-th group of generators, Expressed as the cooling efficiency coefficient of the i-th group of generators, and Both are expressed as weight values, and A is expressed as a correction constant.

10. The intelligent frequency conversion control system of a generator set cooling system according to claim 9, characterized in that: The level control module is used to compare the frequency conversion regulation demand index Zcd of each group of generators with the preset demand threshold Y, determine the frequency conversion regulation state required for normal cooling of the corresponding generator, and obtain and execute the level frequency conversion control instructions of each group of generators. The specific contents are as follows: If the frequency conversion regulation demand index Zcd of the corresponding generator is ≥ the demand threshold Y, it means that the frequency conversion regulation required for normal cooling of the corresponding generator is in the frequency increase state, and a first-level frequency conversion control instruction is generated and executed. The execution content is: dispatching the frequency converter of the corresponding generator cooling circuit to increase its operating frequency to a level higher than the current operating frequency; If the frequency conversion regulation demand index Zcd of the corresponding generator is less than the demand threshold Y, it means that the frequency conversion regulation required for normal cooling of the corresponding generator is in a frequency reduction state, and a secondary frequency conversion control instruction is generated and executed. The execution content is: dispatching the inverter of the corresponding generator cooling circuit to reduce its output frequency to below the current operating frequency.

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