An intelligent variable frequency control system for a generator set cooling system

Abstract

The present invention discloses an intelligent variable-frequency control system for a generator set cooling system, which relates to the technical fields of industrial automation and energy equipment management. The system includes a first temperature monitoring module, a satisfaction analysis module, a second temperature monitoring module, a variable-frequency analysis module, and a variable-frequency control module. It monitors the temperature states at the inlets and outlets of the cooling pipelines of the heat source parts of each group of generators during the cooling period to analyze the cooling satisfaction degree of the generator set cooling system for the generator set during the current cooling period, and accordingly issues a variable-frequency analysis instruction. Then, it monitors the temperature states of the heat source parts of each group of generators in real time during the cooling period to analyze the variable-frequency adjustment state required for the normal cooling of each group of generators by the generator set cooling system, and obtains the variable-frequency adjustment demand index Zcd of each group of generators. And it compares them with the preset demand threshold Y respectively to obtain the hierarchical variable-frequency control instructions for each group of generators and execute them.

Description

Technical Field

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

[0002] With the wide deployment of multiple parallel generator sets in large-scale thermal power, nuclear power, and standby power systems, the thermal stability of generators under high load and high heat source density conditions has become a key factor restricting their continuous and safe operation. During the operation of generator sets, a large amount of heat is generated in the winding, shaft, and rectifier parts. If effective cooling cannot be achieved, it will directly lead to system heat accumulation, insulation aging, degradation of electrical performance, and even burnout. Therefore, higher requirements are put forward for the dynamic adaptability, precise regulation ability, and energy efficiency control ability of the cooling system.

[0003] Most existing generator set cooling systems adopt a constant variable frequency control mode, lacking the ability of dynamic identification and zonal response to the cooling requirements of different heat source parts of generators. Usually, cooling parameters are set manually and the cooling device is started and stopped based on a fixed temperature difference logic. When facing complex working conditions such as changes in the operating state of each group of generators, load fluctuations, and environmental temperature difference interference, it is difficult to perform differential processing on each group of equipment, and it is also difficult to precisely adjust the flow rate and cooling frequency of the cooling medium, resulting in insufficient cooling in some areas and local overheating, and conversely, excessive cooling causing waste of resources. In addition, traditional cooling control systems lack the ability of real-time data integration, edge computing processing, and construction of dynamic adjustment indexes, making it difficult to effectively achieve grouped frequency modulation and global thermal management optimization, with a lag in cooling response and a low energy efficiency ratio.

[0004] The above deficiencies are mainly due to the static and single nature of the control logic of existing cooling systems; on the one hand, there is a lack of a multi-point temperature sensing and heat transfer state modeling mechanism, making it difficult to accurately quantify the heat 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, resulting in the system's difficulty in adapting to the differential changes in the operating states of multiple groups of generators; when the cooling is insufficient, it may cause the temperature of the motor winding to continue to rise, the insulation level to decline, and even the risk of thermal breakdown and power sudden drop faults; while excessive cooling will cause energy waste; therefore, constructing an intelligent cooling control system with distributed sensing, variable frequency adaptive adjustment, and cooling demand-driven mechanisms is of great significance and engineering application value for ensuring the stable operation of generator sets and improving energy utilization efficiency. Summary of the Invention

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

[0006] To achieve the above object, the present invention is realized through the following technical solutions: An intelligent variable frequency control system for a generator set cooling system, comprising a first temperature monitoring module, a satisfaction analysis module, a second temperature monitoring module, a variable frequency analysis module, and a variable frequency control module;

[0007] The first temperature monitoring module is used to monitor the temperature states 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;

[0008] The satisfaction analysis module analyzes the cooling satisfaction degree of the generator set cooling system for the generator set during the current cooling period based on the relevant pipeline temperature data information, and issues a variable frequency analysis instruction accordingly;

[0009] Based on the received variable frequency analysis instruction, the second temperature monitoring module monitors the temperature states of the heat source parts of each group of generators in real time during the cooling period, obtains relevant generator temperature data information, and combines with the generator structure parameter design drawing to obtain relevant heat exchange cavity data information;

[0010] The variable frequency analysis module is used to analyze the variable frequency adjustment state required for the normal cooling of each group of generators by the generator set cooling system, and obtain the variable frequency adjustment demand index Zcd of each group of generators;

[0011] The variable frequency control module is used to compare the variable frequency adjustment demand index Zcd of each group of generators with a preset demand threshold Y respectively, so as to obtain the hierarchical variable frequency control instructions for each group of generators and execute them.

[0012] Preferably, the first temperature monitoring module includes a deployment unit and a coolant temperature monitoring unit;

[0013] The deployment unit is used to arrange multiple groups of thermocouple type temperature sensors at the heat source parts of each group of generators according to the cooling process of the generator set cooling system for each group of generators, and set multiple groups of flow channel temperature sensors at the inlets and outlets of the coolant of the corresponding cooling pipelines at the heat source parts of each group of generators. Combining with wireless communication technology, the multiple groups of temperature sensors are wirelessly connected to the edge calculator. After preprocessing the data information obtained by the sensors, the edge calculator uniformly schedules and uploads it to the data storage platform;

[0014] The heat source parts of the generator include the stator winding, the rotor shaft, and the bearing cavity. The data preprocessing content 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.

[0015] Preferably, the coolant temperature monitoring unit is used to set multiple sets 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 states 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, send the obtained relevant pipeline temperature data information to the edge calculator for data preprocessing, and then upload it to the data storage platform for storage. Among them, 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.

[0016] Preferably, the satisfaction analysis module includes a pre-analysis unit and a determination unit;

[0017] 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 with the corresponding outlet coolant temperature Tck during the cooling period, and after linear normalization processing, analyze the cooling satisfaction degree of the generator set cooling system for the generator set during the current cooling period to obtain the cooling satisfaction coefficient Xry of the generator set cooling system. Among them, the cooling satisfaction coefficient Xry is specifically obtained through the following formula:

[0018] ;

[0019] In the formula, represents the outlet coolant temperature of the i-th group of generators, represents 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.

[0020] Preferably, the determination unit is used to compare and analyze the cooling satisfaction coefficient Xry of the generator set cooling system with the preset satisfaction threshold R, and then preliminarily determine whether the cooling of the generator set cooling system for the generator set is in a fitting state during the current cooling period, and issue a frequency conversion analysis instruction accordingly. The specific content of the comparison and analysis is as follows:

[0021] If the cooling satisfaction coefficient Xry of the generator set cooling system > the satisfaction threshold R, it means that the cooling of the generator set cooling system for the generator set is not in a fitting state during the current cooling period, indicating that the generator set cooling system cools the generator set excessively during the current cooling period. At this time, a frequency conversion analysis instruction is issued outward;

[0022] If the cooling satisfaction coefficient Xry of the generator set cooling system is equal to the satisfaction threshold R, it indicates that the cooling of the generator set by the generator set cooling system is in a fitting state during the current cooling period, which means that the generator set cooling system exactly meets the normal cooling requirements of the generator set during the current cooling period. At this time, no additional variable frequency analysis instruction is issued;

[0023] If the cooling satisfaction coefficient Xry of the generator set cooling system is less than the satisfaction threshold R, it indicates that the cooling of the generator set by the generator set cooling system is not in a fitting state during the current cooling period, which means that the generator set cooling system is insufficient for cooling the generator set during the current cooling period. At this time, a variable frequency analysis instruction is sent outwards.

[0024] Preferably, the second temperature monitoring module includes a heat source monitoring unit and a gradient pre-analysis unit;

[0025] Based on the received variable frequency analysis instruction and according to the cooling process of the generator set cooling system for each group of generators, the heat source monitoring unit monitors the temperature state of the heat source parts of each group of generators during the cooling period in real time, obtains relevant generator temperature data information. At the same time, in combination with the generator structure parameter design drawing, it collects the effective heat exchange cavity volume of the heat source parts of each group of generators, obtains relevant heat exchange cavity data information, and sends the obtained relevant generator temperature data information and relevant heat exchange cavity data information to the edge calculator for data preprocessing and then uploads them to the data storage platform for storage. Among them, the relevant generator temperature data information includes the current temperature value Tdq of each group of generators at each monitoring point during the cooling period, and the relevant heat exchange cavity data information includes the effective heat exchange cavity volume Vyx of each group of generators;

[0026] Based on the obtained relevant generator temperature data information and combined with the statistical mean algorithm, after linear normalization processing, the gradient pre-analysis unit pre-analyzes the temperature change gradient of the heat source parts of each group of generators during the cooling period to obtain the temperature change gradient coefficient Xbh of each group of generators, which is specifically obtained through the following formula:

[0027] ;

[0028] In the formula, represents the current temperature value of the i-th group of generators at the j-th monitoring point during the cooling period, represents the current temperature value of the i-th group of generators at the (j - 1)-th monitoring point during the cooling period, j = 1, 2, 3,..., m, and m represents the number of monitoring points during the cooling period.

[0029] Preferably, the variable frequency analysis module includes a heat exchange analysis unit, a cooling efficiency analysis unit and a demand analysis unit;

[0030] The heat exchange analysis unit is used to extract the physical characteristic parameters of the coolant in the generator set cooling system according to the content of the operation manual of the generator set cooling system, so as to obtain the coolant characteristic data information. Among them, the coolant characteristic data information includes the specific heat capacity Cbr and density Cmd of the coolant;

[0031] 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 relevant heat exchange cavity data information. After linear normalization processing, the heat exchange situation of the heat source parts of each group of generators during the cooling period is analyzed to obtain the heat exchange density coefficient Xmd of each group of generators, which is specifically obtained through the following formula:

[0032] ;

[0033] In the formula, represents the temperature change gradient coefficient of the i-th group of generators, represents the effective heat exchange cavity volume of the i-th group of generators, Cbr represents the specific heat capacity of the coolant, and Cmd represents the density of the coolant.

[0034] Preferably, the cooling efficiency analysis unit is used to extract the characteristics of the relevant generator temperature data information, calculate the average value of the current temperature values 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 ;

[0035] By associating the current temperature average value of each group of generators during the cooling period with the relevant pipeline temperature data information, the cooling efficiency of each group of generators during the cooling period is analyzed to obtain the cooling efficiency coefficient Xxv of each group of generators, which is specifically obtained through the following formula:

[0036] ;

[0037] In the formula, represents the current temperature average value of the i-th group of generators, represents the outlet coolant temperature of the i-th group of generators, represents the inlet coolant temperature of the i-th group of generators.

[0038] Preferably, the demand analysis unit associates the obtained relevant pipeline temperature data information, relevant generator temperature data information and relevant heat exchange cavity data information. After linear normalization processing, it analyzes the frequency conversion adjustment state required for the normal cooling of each group of generators in the generator set cooling system, and obtains the frequency conversion adjustment demand index Zcd of each group of generators, which is specifically obtained through the following formula:

[0039] ;

[0040] In the formula, is expressed as the heat exchange density coefficient of the i-th group of generators, is expressed as the cooling efficiency coefficient of the i-th group of generators, and are both expressed as weight values, and A is expressed as a correction constant.

[0041] Preferably, the level control module is used to compare the frequency conversion adjustment demand index Zcd of each group of generators with a preset demand threshold Y respectively, determine the frequency conversion adjustment state required for the normal cooling of the corresponding generator, so as to obtain the level frequency conversion control instructions for each group of generators and execute them. The specific content is as follows:

[0042] If the frequency conversion adjustment demand index Zcd of the corresponding generator ≥ the demand threshold Y, it means that the frequency conversion adjustment required for the normal cooling of the corresponding generator is in the frequency increasing state, generate a first-level frequency conversion control instruction and execute it. The execution content is: dispatch the frequency converter of the cooling circuit of the corresponding generator to increase its operating frequency to be higher than the current operating frequency;

[0043] If the frequency conversion adjustment demand index Zcd of the corresponding generator < the demand threshold Y, it means that the frequency conversion adjustment required for the normal cooling of the corresponding generator is in the frequency decreasing state, generate a second-level frequency conversion control instruction and execute it. The execution content is: dispatch the frequency converter of the cooling circuit of the corresponding generator to reduce its output frequency to be lower than the current operating frequency.

[0044] The present invention provides an intelligent frequency conversion control system for a generator set cooling system, which has the following beneficial effects:

[0045] (1) Aiming at the problems of the existing generator set cooling system, such as lack of partition recognition, rough regulation, response lag and inaccurate energy efficiency control, an intelligent control system with a multi-source data acquisition, cooling state recognition and frequency conversion regulation fusion mechanism is proposed. A dynamic decision-making model with the cooling satisfaction coefficient Xry and the frequency conversion adjustment demand index Zcd as the core is constructed, realizing a closed-loop linkage from cooling data monitoring to intelligent decision-making and then to hierarchical frequency conversion execution; through the dynamic and accurate recognition of the cooling state and heat exchange demand of each group of generators, the limitation of coexistence of insufficient cooling and overcooling in the traditional control strategy is effectively overcome, and the response sensitivity, control accuracy and energy efficiency level of the cooling system are significantly improved, thus ensuring the safety and stability of the generator set under complex operating conditions.

[0046] (2) By performing correlation calculations on the temperature data at the inlets and outlets of the cooling pipelines at the heat source parts of each generator in the generator set cooling system, and constructing a cooling satisfaction coefficient Xry, the system can quantitatively determine whether the cooling system meets the heat release requirements of each generator during the current cooling period; when the cooling satisfaction coefficient Xry exceeds or is lower than the preset threshold R, the system can immediately determine that the current cooling behavior is excessive or insufficient, and automatically trigger a frequency conversion analysis instruction, thereby greatly improving the system's recognition ability and response timeliness for the hot and cold 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 system operation.

[0047] (3) By constructing a frequency conversion analysis module, fusing the coolant characteristic data information, the effective heat exchange cavity data information, the temperature change gradient coefficient Xbh and the cooling efficiency coefficient Xxv of each generator, and finally obtaining the frequency conversion adjustment demand index Zcd of each generator, realizing the intelligent recognition and precision control of the frequency conversion adjustment state of the cooling system; when the frequency conversion adjustment demand index Zcd is higher or lower than the preset demand threshold Y, automatically generate a first-level or second-level frequency conversion control instruction, and execute the corresponding frequency increase or decrease operation 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 phenomena caused by hot and cold fluctuations, and having high engineering applicability and regulation intelligence level. Description of the Drawings

[0048] Figure 1 It is a block diagram of an intelligent frequency conversion control system for a generator set cooling system of the present invention;

[0049] Figure 2 It is a logical thinking diagram of an intelligent frequency conversion control system for a generator set cooling system of the present invention;

[0050] Figure 3 It is a schematic diagram of the data transmission process of the present invention. Specific Embodiments

[0051] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0052] Embodiment 1

[0053] Please refer to Figure 1 and Figure 2, the present invention provides an intelligent variable frequency control system for a generator set cooling system, including a first temperature monitoring module, a satisfaction analysis module, a second temperature monitoring module, a variable frequency analysis module, and a variable frequency control module;

[0054] The first temperature monitoring module is used to monitor the temperature states 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;

[0055] The satisfaction analysis module analyzes the cooling satisfaction degree of the generator set cooling system for the generator set during the current cooling period based on the relevant pipeline temperature data information, and issues a variable frequency analysis instruction accordingly;

[0056] The second temperature monitoring module, based on the received variable frequency analysis instruction, monitors the temperature states of the heat source parts of each group of generators during the cooling period in real time, obtains relevant generator temperature data information, and combines with the generator structure parameter design drawing to obtain relevant heat exchange cavity data information;

[0057] The variable frequency analysis module is used to analyze the variable frequency adjustment state required for the normal cooling of each group of generators by the generator set cooling system, and obtain the variable frequency adjustment demand index Zcd of each group of generators;

[0058] The variable frequency control module is used to compare the variable frequency adjustment demand index Zcd of each group of generators with the preset demand threshold Y respectively to obtain the hierarchical variable frequency control instructions for each group of generators and execute them.

[0059] In this embodiment, 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 is constructed to achieve intelligent, zonal, and dynamic management of the cooling process of the generator set. First, the first temperature monitoring module obtains the real-time temperature data at the inlet and outlet of the cooling pipeline to establish the basis of the heat exchange characteristic parameters of the cooling medium at each heat source part of the generator. Subsequently, the satisfaction analysis module conducts a preliminary analysis of the cooling state to determine whether the cooling is excessive or insufficient, and issues a frequency conversion analysis instruction accordingly to achieve the control logic transition from temperature difference judgment to heat satisfaction judgment. Then, the second temperature monitoring module further obtains the temperature of the heat source body of each group of generators and the heat exchange cavity information in combination with the structure drawings to provide more accurate data support for the subsequent adjustment model. The frequency conversion analysis module establishes a two-way model of cooling demand and efficiency based on the above multi-source data, calculates the current frequency conversion adjustment demand index Zcd of each group of generators, enabling the system to accurately evaluate the actual adjustment demand of each group of generators in terms of cooling intensity. Finally, the frequency conversion control module generates a hierarchical frequency conversion control instruction after comparing Zcd with the preset threshold to achieve the grouping independent frequency modulation and differential cooling execution strategy. The outstanding advantage of this system is that it not only realizes the dynamic perception and real-time control of the cooling process, but also constructs a closed-loop mechanism of multi-parameter fusion, hierarchical response, and fine control, significantly improving the thermal safety guarantee ability, cooling efficiency, and energy utilization level during the operation of the generator set, with high self-adaptability, high responsiveness, and high intelligence level.

[0060] Embodiment 2

[0061] Please refer to Figure 1 and Figure 3 , specifically: The first temperature monitoring module includes a deployment unit and a coolant temperature monitoring unit;

[0062] The deployment unit is used to arrange multiple groups of thermocouple-type temperature sensors at the heat source parts of each group of generators according to the cooling process of each group of generators in the generator set cooling system, and set multiple groups of flow channel temperature sensors at the coolant inlet and outlet of the corresponding cooling pipelines at the heat source parts of each group of generators. Combining with wireless communication technology, the multiple groups of temperature sensors are wirelessly connected to the edge calculator. After preprocessing the data information obtained by the sensors, the edge calculator uniformly schedules and uploads it to the data storage platform;

[0063] It should be noted that the edge calculator and the data storage platform jointly construct a local processing and centralized management framework for temperature monitoring data in this system. The edge calculator is mainly responsible for locally preprocessing the raw data collected by multiple groups of wireless temperature sensors, including removing noise, filling missing values, and data smoothing, to improve the reliability and real-time performance of the data, and uniformly scheduling and managing the processed data. The data storage platform is used for centrally storing, classifying and archiving, and subsequent analysis and calling of the high-quality temperature data uploaded by the edge calculator, ensuring that the system has complete, continuous, and traceable temperature information support during the processes of cooling state recognition, frequency modulation analysis, and intelligent decision-making, so as to achieve the intelligentization, digitalization, and closed-loop control of the system operation.

[0064] The heat source parts of the generator include the stator winding, the rotor shaft, and the bearing cavity. The data preprocessing content of the edge calculator includes: removing noise, filling missing values, and data smoothing operations. The data storage platform is used for storing the data information after preprocessing.

[0065] Specifically, 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 of each group of generator heat source parts according to the deployment unit, monitor the temperature states of the inlets and outlets of the cooling pipelines of each group of generator heat source parts during the cooling period to obtain the relevant pipeline temperature data information, and send the obtained relevant pipeline temperature data information to the edge calculator for data preprocessing and then upload it to the data storage platform for storage. Among them, 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.

[0066] It should be noted that the inlet coolant temperature Trk and the outlet coolant temperature Tck respectively represent the entering temperature and the leaving temperature when the coolant flows through each group of generator heat source parts 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 entering the cooling pipeline, and Tck represents the temperature value of the coolant after completing the heat absorption process. By arranging flow channel temperature sensors at the inlets and outlets of the cooling pipelines of each group of generators, these two parameters can be collected in real time and their data can be transmitted to the edge calculator 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 be the data support for subsequent analysis of the cooling satisfaction degree and frequency modulation control requirements, and plays a key role in achieving precise cooling control.

[0067] In this embodiment, through the collaborative design of the deployment unit and the coolant temperature monitoring unit, a cooling temperature monitoring mechanism with high precision, high stability, and low latency is constructed. By arranging multiple groups of thermocouple-type temperature sensors at the key heat source parts of the generator (such as the stator winding, rotor shaft, and bearing cavity), and respectively configuring multiple groups of flow channel temperature sensors at the inlet and outlet of the corresponding coolant pipeline, the system can achieve two-dimensional perception of the temperature change of the cooling medium and the true thermal state of the heat source. The wireless communication method is used to connect the edge calculator, effectively reducing the complexity of traditional wiring and communication latency, while improving the flexibility and scalability of system deployment. The edge calculator performs a number of 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 the outlet coolant temperature Tck of each generator cooling path, enabling the system to accurately analyze the heat exchange efficiency and temperature difference fluctuation during the cooling process, providing a real-time, reliable, and complete data basis for subsequent cooling satisfaction analysis and frequency conversion adjustment.

[0068] Embodiment 3

[0069] Please refer to Figure 1 , specifically: The satisfaction analysis module includes a pre-analysis unit and a determination unit;

[0070] The pre-analysis unit is used to extract the characteristics of the relevant pipeline temperature data information in the data storage platform, associate the inlet coolant temperature Trk and the corresponding outlet coolant temperature Tck of each group of generators during the cooling period, and after linear normalization processing, analyze the cooling satisfaction degree of the generator set cooling system for the generator set during the current cooling period to obtain the cooling satisfaction coefficient Xry of the generator set cooling system. Among them, the cooling satisfaction coefficient Xry is specifically obtained through the following formula:

[0071] ;

[0072] In the formula, represents the outlet coolant temperature of the i-th group of generators, represents 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, represents that when the temperature difference between the coolant inlet and outlet is too small or too large, it represents the over-cooling and under-cooling of the cooling effect.

[0073] It should be noted that the cooling satisfaction coefficient Xry reflects the overall ability of the cooling system to remove the heat of the generator set during the current period; it is highly correlated with the problems pointed out in the background technology that the traditional system is difficult to accurately identify whether the cooling is excessive or insufficient, has a single adjustment basis, and has a lagging regulation response; as a quantifiable evaluation index, the cooling satisfaction coefficient Xry realizes the comprehensive judgment of the actual cooling effect of each group of generator sets. The larger its value, the more overcooling exists; if the value is too low, the cooling is insufficient; therefore, the introduction of the cooling satisfaction coefficient Xry enables the system to have the ability to dynamically evaluate and judge the cooling state and trigger, providing a clear and quantifiable criterion for the subsequent variable-frequency adjustment command, effectively solving the technical bottleneck that the traditional cooling system depends on experience and lacks real-time fit analysis.

[0074] Specifically, the determination unit is used to compare and analyze the cooling satisfaction coefficient Xry of the generator set cooling system with the preset satisfaction threshold R, so as to preliminarily determine whether the cooling of the generator set by the generator set cooling system is in a fitting state during the current cooling period, and accordingly issue a variable-frequency analysis command. The specific content of the comparison and analysis is as follows:

[0075] If the cooling satisfaction coefficient Xry of the generator set cooling system > the satisfaction threshold R, it means that the cooling of the generator set by the generator set cooling system is not in a fitting state during the current cooling period, indicating that the generator set cooling system overcools the generator set during the current cooling period. At this time, a variable-frequency analysis command is issued outward;

[0076] If the cooling satisfaction coefficient Xry of the generator set cooling system = the satisfaction threshold R, it means that the cooling of the generator set by the generator set cooling system is in a fitting state during the current cooling period, indicating that the generator set cooling system just meets the normal cooling requirements of the generator set during the current cooling period. At this time, no additional variable-frequency analysis command is issued;

[0077] If the cooling satisfaction coefficient Xry of the generator set cooling system < the satisfaction threshold R, it means that the cooling of the generator set by the generator set cooling system is not in a fitting state during the current cooling period, indicating that the generator set cooling system undercools the generator set during the current cooling period. At this time, a variable-frequency analysis command is issued outward.

[0078] In this embodiment, through the collaborative operation of the pre-analysis unit and the determination unit, an evaluation mechanism for the cooling state based on heat exchange feature recognition is constructed, realizing the quantitative judgment of the operation compliance of the generator set cooling system; after obtaining the relevant pipeline temperature data information, the pre-analysis unit uses linear normalization processing means for feature extraction and standardization calculation, constructs the cooling satisfaction coefficient Xry, as a dynamic index representing whether the cooling process meets the actual heat exchange requirements, significantly improving the adaptability of the system to the cooling effect in different operation stages; by comparing the cooling satisfaction coefficient Xry with the preset satisfaction threshold R, the determination unit can clearly identify whether there is overcooling or insufficient cooling in the current cooling, and trigger the frequency conversion analysis instruction accordingly; the introduction of this mechanism not only makes up for the limitations of traditional systems relying on absolute temperature difference or manual experience judgment, but also enables the system to have the pre-decision ability of self-identifying and self-regulating the cooling state by establishing a continuous judgment model of "satisfaction - overcooling - insufficiency"; the advantages are as follows: through a quantifiable cooling satisfaction coefficient Xry, the dynamic matching and advanced perception of the cooling effect are realized, improving the accuracy and intelligent level of the system cooling regulation, and at the same time providing a clear logical premise for subsequent frequency conversion analysis and control, effectively avoiding the thermal safety hazards and energy waste problems caused by improper cooling strategies, which is the key link to achieve high-reliability and high-energy-efficiency cooling management.

[0079] Embodiment 4

[0080] Please refer to Figure 1 , specifically: the second temperature monitoring module includes a heat source monitoring unit and a gradient pre-analysis unit;

[0081] Based on the received frequency conversion analysis instruction and according to the cooling process of each group of generators in the generator set cooling system, the heat source monitoring unit monitors the temperature state of the heat source parts of each group of generators during the cooling period in real time, obtains the relevant generator temperature data information, and at the same time combines the generator structure parameter design drawing to collect the effective heat exchange cavity volume of the heat source parts of each group of generators, obtains the relevant heat exchange cavity data information, and sends the obtained relevant generator temperature data information and relevant heat exchange cavity data information to the edge calculator for data preprocessing and then uploads them to the data storage platform for storage. Among them, the relevant generator temperature data information includes the current temperature value Tdq of each group of generators at each monitoring point during the cooling period, and the relevant heat exchange cavity data information includes the effective heat exchange cavity volume Vyx of each group of generators.

[0082] 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, which reflects the thermal state of the heat source area during the operation of the generator; while 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, and is usually extracted according to the generator structure parameter design drawing or CAD model; the roles of these two parameters in the system are the basic basis for subsequent analysis of the heat change trend and heat exchange requirements per unit volume in 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; combined, they can construct the key parameters of temperature gradient change and heat exchange density, support the quantitative modeling and analysis of cooling adjustment requirements, and are the core data support for realizing the fine regulation and dynamic thermal management of the system.

[0083] Based on the obtained relevant generator temperature data information and combined with the statistical mean algorithm, after linear normalization processing, the gradient pre-analysis unit pre-analyzes the temperature change gradient of the heat source parts of each group of generators during the cooling period to obtain the temperature change gradient coefficient Xbh of each group of generators, which is specifically obtained through the following formula:

[0084] ;

[0085] In the formula, represents the current temperature value of the i-th group of generators at the j-th monitoring point during the cooling period, represents the current temperature value of the i-th group of generators at the (j - 1)-th monitoring point during the cooling period, where j = 1, 2, 3,..., m, and m represents the number of monitoring points during the cooling period.

[0086] It should be noted that the temperature change gradient coefficient Xbh is a temperature change rate index obtained by taking the absolute value and averaging the differential processing of the generator heat source temperature values Tdq collected at multiple consecutive monitoring points during the cooling period, which is used to reflect the temperature rise or fall dynamic trend of the generator in a certain block during the cooling process; the design of this formula and its parameters 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 strategies; traditional systems often ignore the gradient and feed-forward characteristics of temperature changes and are difficult to effectively predict the occurrence of thermal imbalance; as a quantitative index reflecting the intensity of temperature fluctuations, the temperature change gradient coefficient Xbh has the ability to sense the trend of the heat source temperature rise risk, can realize the early triggering and adjustment optimization of cooling response, provide a dynamic basis for subsequent heat exchange density calculation and variable frequency adjustment strategy formulation, significantly improve the adaptability of the system to complex operating conditions and the forward-looking nature of intelligent control, and is a key support parameter for effectively solving the perception lag and adjustment delay problems of traditional cooling systems.

[0087] In this embodiment, by integrating the heat source monitoring unit and the gradient pre-analysis unit, a deep temperature perception and trend evaluation mechanism for the dynamic changes of the thermal characteristics of the generator during operation is constructed, realizing the pre-identification and quantitative support of the cooling adjustment requirements; the heat source monitoring unit not only realizes the responsive monitoring of the cooling process based on the variable frequency analysis instruction, but also combines with the generator structure parameter design drawing to collect the volume data of the effective heat exchange cavities in the heat source areas of each group of generators, thus realizing the synchronous fusion of the thermal state data and the structural heat capacity data; the temperature values Tdq of each monitoring point and the heat exchange cavity volume Vyx 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; on this basis, the gradient pre-analysis unit combines the statistical mean calculation and the linear normalization method to identify the dynamic trend of the heat source temperature change 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 fall speed, but can also be used as the basis for judging the urgency of the cooling response; its advantages are: by integrating time series analysis and structural parameters, it endows the system with the ability to depict temperature changes, thus identifying temperature control risks in advance before making cooling strategy decisions, realizing predictive pre-judgment and strategy forward movement of cooling adjustment; improving the forward-looking nature and response agility of the cooling adjustment of the system under complex operating conditions, and is an indispensable basic layer support for constructing a refined thermal management system.

[0088] Embodiment 5

[0089] Please refer to Figure 1 , specifically: the variable frequency analysis module includes a heat exchange analysis unit, a cooling efficiency analysis unit and a demand analysis unit;

[0090] The heat exchange analysis unit is used to extract the physical property parameters of the coolant in the generator set cooling system according to the content of the operation manual of the generator set cooling system, so as to obtain the coolant characteristic data information. Among them, the coolant characteristic data information includes the specific heat capacity Cbr and density Cmd of the coolant;

[0091] 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 relevant heat exchange cavity data information. After linear normalization processing, the heat exchange situation of the heat source parts of each group of generators during the cooling period is analyzed to obtain the heat exchange density coefficient Xmd of each group of generators, which is specifically obtained through the following formula:

[0092] ;

[0093] In the formula, represents the temperature change gradient coefficient of the i-th group of generators, represents the effective heat exchange cavity volume of the i-th group of generators, Cbr represents the specific heat capacity of the coolant, and Cmd represents the density of the coolant, represents the heat exchange demand of the cooling medium under the actual temperature rise and fall rate.

[0094] 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), temperature change gradient coefficient Xbh, and the effective heat exchange cavity volume Vyx of the generator. It represents the heat density that needs to be absorbed per unit volume of the cooling cavity per unit time; this formula is highly relevant to the problems of the traditional cooling system mentioned in the background technology, such as the failure to comprehensively consider the thermophysical parameters of the coolant, 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 true heat absorption capacity of the cooling medium; combined with the temperature change gradient coefficient Xbh, it reflects the current heat change rate of the equipment; and then combined with the effective heat exchange cavity volume Vyx, the true heat exchange demand density of the cooling system of each group of generators is obtained; the role of the heat exchange density coefficient Xmd is to provide a key heat load input for the subsequent variable frequency adjustment demand index, enabling the cooling control to not only consider whether there is a temperature rise, but also consider how fast the temperature rises, how difficult it is to absorb heat, and how large the structural pressure is, so as to achieve a cooling adjustment strategy that more conforms to the actual thermal characteristics of the equipment. It is an important parameter to support refined and structured frequency modulation decision-making, and significantly improves the system's understanding and response ability to complex thermal coupling relationships.

[0095] Specifically, the cooling efficiency analysis unit is used to extract features from relevant generator temperature data information, calculate the average value of the current temperature values 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. ;

[0096] By correlating the current temperature average value of each group of generators during the cooling period and associating it with relevant pipeline temperature data information, analyze the cooling efficiency of each group of generators during the cooling period to obtain the cooling efficiency coefficient Xxv of each group of generators, which is specifically obtained through the following formula:

[0097] ;

[0098] In the formula, represents the current temperature average value of the i-th group of generators, represents the outlet coolant temperature of the i-th group of generators, represents the inlet coolant temperature of the i-th group of generators.

[0099] It should be noted that the cooling efficiency coefficient Xxv is the ratio obtained by comparing the current temperature value Tdq of the generator with the corresponding coolant inlet and outlet temperatures, which is used to reflect the actual heat absorption efficiency of the coolant within the unit temperature difference range; the cooling efficiency coefficient Xxv represents the degree of heat actually 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 an important input index for measuring the cooling degree in the variable frequency regulation strategy, and is one of the key parameters for realizing frequency modulation on demand, dynamic energy saving and preventing over-cooling;

[0100] Specifically, the demand analysis unit correlates the obtained relevant pipeline temperature data information, relevant generator temperature data information and relevant heat exchange cavity data information, and after linear normalization processing, analyzes the variable frequency regulation state required for the normal cooling of each group of generators by the generator set cooling system, and obtains the variable frequency regulation demand index Zcd of each group of generators, which is specifically obtained through the following formula:

[0101] ;

[0102] In the formula, represents the heat exchange density coefficient of the i-th group of generators, represents the cooling efficiency coefficient of the i-th group of generators, and both represent weight values, A represents a correction constant, where represents the degree of insufficient cooling efficiency.

[0103] It should be noted that the variable-frequency adjustment demand index Zcd is a dynamic adjustment index calculated by comprehensively weighting the heat exchange density coefficient Xmd and the cooling efficiency coefficient Xxv of the generator and combining the correction constant A. It is used to judge whether each group of generators currently needs to improve or reduce the variable-frequency operation state of the cooling system. The design of the variable-frequency adjustment demand index Zcd is closely related to the technical deficiency in the background technology that the traditional cooling system has a single adjustment basis and is difficult to comprehensively analyze the heat and cold imbalance situation 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. The variable-frequency adjustment demand index Zcd constructed after weighing the two can accurately reflect whether the current cooling intensity matches the heat load demand. Its function is to serve as the core control quantity and judgment basis for the cooling system to perform variable-frequency adjustment, improving the energy efficiency ratio, heat matching degree and operation intelligence level of the cooling system.

[0104] 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 decision-making mechanism for cooling adjustment oriented to multi-parameter fusion, dynamic response and group adaptation is formed, realizing the refined determination of the variable-frequency adjustment state of the generator set cooling system. The heat exchange analysis unit extracts the physical property parameters of the coolant (including specific heat capacity Cbr and density Cmd) based on the operation manual of the generator set cooling system, and combines the temperature change gradient coefficient Xbh obtained from the previous gradient pre-analysis and the heat exchange cavity volume Vyx corresponding to each group of generators to calculate and generate the heat exchange density coefficient Xmd, comprehensively quantifying the heat exchange intensity required per unit volume per unit time in each generator block. The cooling efficiency analysis unit constructs the cooling efficiency coefficient Xxv by statistically analyzing the current temperature values Tdq at each monitoring point and obtaining the current temperature average value, and correlating it with the temperature difference between the inlet and outlet of the coolant, accurately depicting the actual heat absorption efficiency of the coolant during the heat conduction process. Based on the above two core indicators, the demand analysis unit conducts an associated modeling of the cooling intensity demand and the actual cooling effect, generating the variable-frequency adjustment demand index Zcd as the core quantitative basis for measuring whether frequency increase or decrease control is required. The advantages are as follows: By introducing the three-dimensional coupling analysis of the thermal physical properties of the coolant, the heat exchange geometric structure and the dynamic thermal state data, a comprehensive adjustment logic based on physical mechanism, operation state and system feedback is established, significantly enhancing the adaptive judgment ability of the cooling system to working condition changes, and providing key intelligent decision-making support for the efficient, stable and safe cooling management of the generator set.

[0105] Embodiment 6

[0106] Please refer to Figure 1, specifically: The level control module is used to compare the frequency conversion adjustment demand index Zcd of each group of generators with a preset demand threshold Y respectively, determine the frequency conversion adjustment state required for the normal cooling of the corresponding generator, so as to obtain the level frequency conversion control instructions for each group of generators and execute them. The specific content is as follows:

[0107] If the frequency conversion adjustment demand index Zcd of the corresponding generator is ≥ the demand threshold Y, it means that the frequency conversion adjustment required for the normal cooling of the corresponding generator is in the frequency increase state, generate a first-level frequency conversion control instruction and execute it. The execution content is: dispatch the frequency converter of the cooling circuit of the corresponding generator to increase its operating frequency to be higher than the current operating frequency;

[0108] If the frequency conversion adjustment demand index Zcd of the corresponding generator < the demand threshold Y, it means that the frequency conversion adjustment required for the normal cooling of the corresponding generator is in the frequency decrease state, generate a second-level frequency conversion control instruction and execute it. The execution content is: dispatch the frequency converter of the cooling circuit of the corresponding generator to reduce its output frequency to be lower than the current operating frequency.

[0109] In this embodiment, by introducing a comparison mechanism between the frequency conversion adjustment demand index Zcd and the preset demand threshold Y, a hierarchical frequency modulation execution system with fast response and precise control is constructed, realizing intelligent matching control of the cooling states of each group of generators; the system judges the strength of the current cooling demand according to the size of the frequency conversion adjustment demand index Zcd. If the frequency conversion adjustment 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 frequency converter of the corresponding cooling circuit to quickly enhance the cooling capacity; if the frequency conversion adjustment demand index Zcd is lower than the demand threshold Y, a second-level frequency decrease control instruction is triggered to reduce the frequency output of the frequency converter, effectively suppressing the phenomenon of excessive cooling and reducing energy consumption; this mechanism no longer relies on unified adjustment and fixed cooling logic set by humans, but realizes differential and zonal frequency modulation responses for the thermal states of each group of generators, ensuring energy efficiency optimization while meeting the thermal management requirements for each cooling circuit; its special advantage lies in: through the fine control of hierarchical frequency conversion instructions, it has the ability to dynamically allocate cooling resources in real time according to the cooling demand, effectively avoiding the traditional contradiction of coexistence of cooling redundancy and cooling lag, improving the flexible adaptability and adjustment efficiency of the generator set cooling system to changes in operating load, and is the core execution link for realizing the intelligent control closed-loop mechanism of the generator set cooling.

[0110] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent variable frequency 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 states 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; The satisfaction analysis module analyzes the cooling satisfaction degree of the generator set cooling system for the generator set during the current cooling period based on the relevant pipeline temperature data information, and issues a frequency conversion analysis instruction accordingly; Based on the received frequency conversion analysis instruction, the second temperature monitoring module monitors the temperature states of the heat source parts of each group of generators during the cooling period in real time, obtains relevant generator temperature data information, and combines with the generator structure parameter design drawing to obtain relevant heat exchange cavity data information; 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 the generator set cooling system for each group of generators, the heat source monitoring unit monitors the temperature states of the heat source parts of each group of generators during the cooling period in real time, obtains relevant generator temperature data information, and at the same time combines with the generator structure parameter design drawing to collect the effective heat exchange cavity volume of the heat source parts of each group of generators to obtain relevant heat exchange cavity data information. After the obtained relevant generator temperature data information and relevant heat exchange cavity data information are sent to the edge calculator for data preprocessing, they are uploaded to the data storage platform for storage. Among them, the relevant generator temperature data information includes the current temperature value Tdq of each group of generators at each monitoring point during the cooling period, and the relevant heat exchange cavity data information includes the effective heat exchange cavity volume Vyx of each group of generators; Based on the obtained relevant generator temperature data information and combined with the statistical mean algorithm, after linear normalization processing, the gradient pre-analysis unit pre-analyzes the temperature change gradient of the heat source parts of each group of generators during the cooling period to obtain the temperature change gradient coefficient Xbh of each group of generators; The frequency conversion analysis module is used to analyze the frequency conversion adjustment state required for the normal cooling of each group of generators by the generator set cooling system and obtain the frequency conversion adjustment demand index Zcd of each group of generators; 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 generator set cooling system according to the content of the operation manual of the generator set cooling system to obtain coolant characteristic data information. Among them, 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 the 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 situation of the heat source parts of each group of generators during the cooling period is analyzed to obtain the heat exchange density coefficient Xmd of each group of generators, which is specifically obtained through the following formula: ； In the formula, represents the temperature change gradient coefficient of the i-th group of generators, represents the volume of the effective heat exchange cavity of the i-th group of generators, Cbr represents the specific heat capacity of the coolant, and Cmd represents the density of the coolant; The variable-frequency control module is used to compare the variable-frequency adjustment demand index Zcd of each group of generators with a preset demand threshold Y respectively, so as to obtain the hierarchical variable-frequency control instructions for each group of generators and execute them.

2. The intelligent variable frequency 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-type temperature sensors at the heat source parts of each group of generators according to the cooling process of the generator set cooling system for each group of generators, and 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. Combining with wireless communication technology, the multiple groups of temperature sensors are wirelessly connected to the edge calculator. After preprocessing the data information obtained by the sensors, the edge calculator uniformly schedules and uploads it to the data storage platform; The heat source parts of the generator include the stator winding, the rotor shaft and the bearing cavity. The data preprocessing content of the edge calculator includes: removing noise, filling in missing values and data smoothing operations. The data storage platform is used to store the preprocessed data information.

3. The intelligent variable frequency control system of a generator set cooling system according to claim 2, characterized in that: The coolant temperature monitoring unit is used to monitor the temperature states at the inlets and outlets of the cooling pipelines at the heat source parts of each group of generators during the cooling period by arranging 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, so as to obtain the relevant pipeline temperature data information. After sending the obtained relevant pipeline temperature data information to the edge calculator for data preprocessing, it is uploaded to the data storage platform for storage. Among them, 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 variable-frequency control system of a generator set cooling system according to claim 3, wherein: The satisfaction analysis module includes a pre-analysis unit and a determination unit; The pre-analysis unit is used to extract the characteristics of the relevant pipeline temperature data information in the data storage platform, associate the inlet coolant temperature Trk of each group of generators with the corresponding outlet coolant temperature Tck during the cooling period, and after linear normalization processing, analyze the cooling satisfaction degree of the generator set cooling system for the generator set during the current cooling period, so as to obtain the cooling satisfaction coefficient Xry of the generator set cooling system. Among them, the cooling satisfaction coefficient Xry is specifically obtained through the following formula: ； In the formula, represents the outlet coolant temperature of the i-th group of generators, represents the inlet coolant temperature of the i-th group of generators, where i = 1, 2, 3,..., n, and n represents the number of generators cooled by the generator set cooling system.

5. The intelligent variable-frequency 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 generator set cooling system with a preset satisfaction threshold R, so as to preliminarily determine whether the cooling of the generator set cooling system for the generator set is in a fitting state during the current cooling period, and issue a variable-frequency analysis instruction accordingly. The specific comparison and analysis content is as follows: If the cooling satisfaction coefficient Xry of the generator set cooling system > the satisfaction threshold R, it means that the cooling of the generator set cooling system for the generator set is not in a fitting state during the current cooling period, indicating that the generator set cooling system overcools the generator set during the current cooling period. At this time, a variable-frequency analysis instruction is sent outwards; If the cooling satisfaction coefficient Xry of the generator set cooling system is equal to the satisfaction threshold R, it indicates that the cooling of the generator set by the generator set cooling system is in a matching state during the current cooling period, which means that the generator set cooling system just meets the normal cooling requirements of the generator set during the current cooling period. At this time, no additional variable frequency analysis instruction is issued. If the cooling satisfaction coefficient Xry of the generator set cooling system is less than the satisfaction threshold R, it indicates that the cooling of the generator set by the generator set cooling system is not in a matching state during the current cooling period, which means that the generator set cooling system is insufficient for cooling the generator set during the current cooling period. At this time, a variable frequency analysis instruction is issued outward.

6. The intelligent variable frequency control system of a generator set cooling system according to claim 1, wherein: The cooling efficiency analysis unit is used to extract features from the relevant generator temperature data information, calculate the mean value of the current temperature values Tdq of each group of generators at each monitoring point during the cooling period, and obtain the current temperature mean value of each group of generators during the cooling period ; By taking the average of the current temperatures of each group of generators during the cooling period and associating it with the temperature data information of the relevant pipelines, the cooling efficiency of each group of generators during the cooling period is analyzed to obtain the cooling efficiency coefficient Xxv of each group of generators.

7. The intelligent variable frequency control system of a generator set cooling system according to claim 1, wherein: The demand analysis unit correlates the obtained relevant pipeline temperature data information, relevant generator temperature data information, and relevant heat exchange cavity data information. After linear normalization processing, it analyzes the variable frequency adjustment state required for the normal cooling of each group of generators by the generator set cooling system, and obtains the variable frequency adjustment demand index Zcd of each group of generators. The specific formula for obtaining it is as follows: ； wherein, represents the heat exchange density coefficient of the i-th group of generators, represents the cooling efficiency coefficient of the i-th group of generators, and both represent weight values, and A represents a correction constant.

8. The intelligent variable frequency control system of a generator set cooling system according to claim 1, wherein: The level control module is used to compare the variable frequency adjustment demand index Zcd of each group of generators with the preset demand threshold Y respectively, determine the variable frequency adjustment state required for the normal cooling of the corresponding generator, so as to obtain the level variable frequency control instruction of each group of generators and execute it. The specific content is as follows: If the variable frequency adjustment demand index Zcd of the corresponding generator is greater than or equal to the demand threshold Y, it indicates that the variable frequency adjustment required for the normal cooling of the corresponding generator is in an up - frequency state, generate a first - level variable frequency control instruction and execute it. The execution content is: dispatch the frequency converter of the cooling circuit of the corresponding generator to increase its operating frequency to be higher than the current operating frequency; If the variable frequency adjustment demand index Zcd of the corresponding generator is less than the demand threshold Y, it indicates that the variable frequency adjustment required for the normal cooling of the corresponding generator is in a down - frequency state, generate a second - level variable frequency control instruction and execute it. The execution content is: dispatch the frequency converter of the cooling circuit of the corresponding generator to reduce its output frequency to be lower than the current operating frequency.

Images