A subway ventilation and air conditioning optimization adjustment method and system

Abstract

The present application provides a method and system for optimizing and adjusting subway ventilation and air conditioning, which relates to the field of air conditioning adjustment technology. The method includes: performing seasonal time zone division, configuring the subway air conditioning system based on a fixed control mode, activating a scene-adapted target control mode, transmitting back to an intelligent module based on a distributed sensing device, generating air conditioning adjustment data, and then feeding back to the subway air conditioning system for air conditioning adjustment, simultaneously performing dynamic monitoring to determine control feedback information, and determining relay protection response, and finally performing abnormal operation control analysis and feedback decision-making. The present application mainly solves the problem that traditional subway ventilation and air conditioning adopts a fixed operating mode, cannot be dynamically adjusted according to the real-time environment, and cannot detect abnormalities and provide feedback in a timely manner. It realizes dynamic adjustment of ventilation and air conditioning equipment, reduces energy consumption, improves the energy utilization efficiency of the subway system, reduces operating costs, and improves passenger safety.

Description

Technical Field

[0001] The present application relates to the field of air conditioning regulation technology, and in particular to a method and system for optimizing and regulating subway ventilation and air conditioning. Background Art

[0002] Subway systems are a vital component of urban transportation, often located underground. Due to their unique structural and environmental conditions, subway systems have unique ventilation and air conditioning requirements compared to other buildings. To ensure safe, comfortable, and energy-efficient operation of subway systems, optimizing ventilation and air conditioning systems is crucial. Subway trains and equipment generate significant heat, requiring effective ventilation systems to remove this heat and maintain a suitable temperature and air quality within the subway. Furthermore, the subway's air conditioning system requires optimal adjustment to meet cooling or heating needs across different seasons and time periods. However, traditional subway ventilation and air conditioning systems typically operate in a fixed mode, maintaining fixed operating parameters regardless of changes in temperature and humidity within the subway. This mode of operation not only wastes energy but also compromises comfort within the subway due to its inability to adapt to changing environmental conditions.

[0003] However, in the process of implementing the technical solutions of the invention in the embodiments of this application, it was found that the above technology has at least the following technical problems:

[0004] Traditional subway ventilation and air conditioning adopts a fixed operating mode and cannot be dynamically adjusted according to the real-time environment, nor can it detect abnormalities and provide feedback in a timely manner. Summary of the Invention

[0005] This application mainly solves the problem that traditional subway ventilation and air conditioning adopts a fixed operating mode, cannot be dynamically adjusted according to the real-time environment, and cannot detect abnormalities and provide feedback in time.

[0006] In view of the above problems, the present application provides a method and system for optimizing and adjusting subway ventilation and air conditioning. In a first aspect, the present application provides a method for optimizing and adjusting subway ventilation and air conditioning, the method comprising: performing seasonal time zone division and determining a fixed control mode mapped to the periodic division result; configuring the subway air conditioning system based on the fixed control mode and activating a scene-adapted target control mode; transmitting environmental sensor data back to the intelligent module based on a distributed sensing device, determining and making decisions on the necessity of air conditioning adjustment, and generating air conditioning adjustment data, wherein the air conditioning adjustment mode includes a whole control mode and a partition control mode; feeding back the air conditioning adjustment data to the subway air conditioning system to perform subway ventilation and air conditioning control, wherein a connection loop is established between the subway air conditioning system, the intelligent module and the distributed sensing monitoring device; synchronously performing dynamic monitoring of the air conditioning control and the electrical system to determine control feedback information, wherein a relay protection response is synchronously determined; based on the control feedback information and the relay protection response, abnormal operation and control analysis and feedback decision-making are performed in combination with the intelligent module, feedback adjustment data is determined and transmitted to the subway air conditioning system.

[0007] On the second aspect, the present application provides a subway ventilation and air-conditioning optimization and adjustment system, which includes: a time zone division module, which is used to perform seasonal time zone division and determine a fixed control mode mapped to the periodic division result; a control mode activation module, which is based on the fixed control mode to configure the subway air-conditioning system and activate the scene-adapted target control mode; an air-conditioning adjustment data generation module, which is based on the distributed sensor device sending back environmental sensor data to the intelligent module, to determine and make decisions on the necessity of air-conditioning adjustment, and generate air-conditioning adjustment data, wherein the air-conditioning adjustment mode includes the whole control mode and the partition control mode. mode; an air-conditioning control module, the air-conditioning control module is used to feed back the air-conditioning adjustment data to the subway air-conditioning system to perform subway ventilation and air-conditioning control, wherein a connection loop is established between the subway air-conditioning system, the intelligent module and the distributed sensing monitoring device; a feedback information determination module, the feedback information determination module is used to synchronously perform dynamic monitoring of the air-conditioning control and the electrical system, determine the control feedback information, wherein the relay protection response is synchronously determined; an operation control analysis module, the operation control analysis module is based on the control feedback information and the relay protection response, combined with the intelligent module to perform abnormal operation control analysis and feedback decision-making, determine the feedback adjustment data and transmit it to the subway air-conditioning system.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] The present application provides a method and system for optimizing and adjusting ventilation and air conditioning in a subway, which relates to the technical field of air conditioning adjustment. The method includes: performing seasonal time zone division, configuring the subway air conditioning system based on a fixed control mode, activating a scene-adapted target control mode, transmitting back to an intelligent module based on a distributed sensing device, generating air conditioning adjustment data, and then feeding back to the subway air conditioning system for air conditioning adjustment, simultaneously performing dynamic monitoring to determine control feedback information, and determining relay protection response, and finally performing abnormal operation control analysis and feedback decision-making.

[0010] This application mainly solves the problem that traditional subway ventilation and air conditioning adopts a fixed operating mode, cannot be dynamically adjusted according to the real-time environment, and cannot detect abnormalities and provide feedback in time. It realizes dynamic adjustment of ventilation and air conditioning equipment and reduces energy consumption, thereby improving the energy utilization efficiency of the subway system, reducing operating costs and improving passenger safety.

[0011] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in this application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely exemplary, and a person of ordinary skill in the art can obtain other drawings based on the provided drawings without creative work.

[0013] Figure 1 A schematic flow chart of a method for optimizing and adjusting subway ventilation and air conditioning is provided for an embodiment of the present application;

[0014] Figure 2 A schematic flow chart of a method for determining a fixed control mode in a subway ventilation and air conditioning optimization adjustment method is provided for an embodiment of the present application;

[0015] Figure 3 A schematic flow chart of a method for determining overall amplitude modulation in a subway ventilation and air conditioning optimization adjustment method is provided for an embodiment of the present application;

[0016] Figure 4 A structural schematic diagram of a subway ventilation and air-conditioning optimization adjustment system is provided for an embodiment of the present application.

[0017] Description of the accompanying drawings: time zone division module 10, control mode activation module 20, air conditioning adjustment data generation module 30, air conditioning control module 40, feedback information determination module 50, operation control analysis module 60. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0019] This application mainly solves the problem that traditional subway ventilation and air conditioning adopts a fixed operating mode, cannot be dynamically adjusted according to the real-time environment, and cannot detect abnormalities and provide feedback in time. It realizes dynamic adjustment of ventilation and air conditioning equipment and reduces energy consumption, thereby improving the energy utilization efficiency of the subway system, reducing operating costs and improving passenger safety.

[0020] In order to better understand the above technical solution, the following will introduce the above solution in detail with reference to the accompanying drawings and specific implementation methods:

[0021] Example 1

[0022] like Figure 1 A method for optimizing and adjusting subway ventilation and air conditioning is shown, the method comprising:

[0023] Perform seasonal time zone division and determine a fixed control mode mapped to the periodic division results;

[0024] Specifically, seasonal time zone division is carried out and a fixed control mode mapped to the periodic division result is determined. The seasonal time zone division standard is determined: indicators related to local climate conditions and energy demand, such as average temperature, maximum temperature, minimum temperature, humidity, etc., are selected, and the year is divided into different seasons according to these indicators. Periodic division results: The year is divided into different periodic time periods, such as spring, summer, autumn, and winter, or a more detailed division is made according to changes in climate conditions and energy demand. Determine the fixed control mode: According to the climate conditions and energy demand of each season or periodic time period, a corresponding fixed control mode is formulated. These modes can be set for the switching time, operating mode, operating parameters, etc. of the equipment in different time periods.

[0025] Based on the fixed control mode, the subway air conditioning system is configured and the scene-adapted target control mode is activated;

[0026] Specifically, the subway air-conditioning system is configured according to the requirements of the fixed control mode. This includes the selection, installation and commissioning of hardware equipment such as ventilation equipment, air-conditioning equipment, sensors, and the design and commissioning of the control systems related to these equipment. Determine the target control mode for scene adaptation: Select the corresponding target control mode according to different seasons, time periods and operating scenarios. These modes should correspond to the fixed control mode and can be flexibly configured and activated according to actual needs. Activate the target control mode: Activate the target control mode by setting the control system parameters. When the corresponding trigger conditions are met, such as specific time nodes, changes in environmental parameters, etc., the control system will automatically switch to the corresponding target control mode and adjust and control the ventilation and air-conditioning equipment accordingly.

[0027] Based on distributed sensing devices, environmental sensor data is transmitted back to the intelligent module to determine and make decisions on the necessity of air conditioning adjustment and generate air conditioning adjustment data. The air conditioning adjustment mode includes overall control mode and zone control mode.

[0028] Specifically, distributed sensing devices, such as temperature sensors, humidity sensors, and air quality sensors, are installed in key areas and equipment within the subway system. These sensors monitor environmental parameters such as temperature, humidity, and air quality in real time and transmit the data back to the intelligent module. Environmental sensor data transmission: Environmental sensor data is transmitted back to the intelligent module via a communication interface or network connection. The intelligent module can be a standalone hardware device or a software system with integrated data processing and analysis capabilities. Air conditioning adjustment necessity determination: The intelligent module processes and analyzes the transmitted environmental sensor data to determine whether air conditioning adjustment is necessary. This typically involves determining conditions such as temperature exceeding a preset range or humidity being abnormal. Decision generation: Based on the determination results, the intelligent module generates a corresponding decision, determining whether air conditioning adjustment is necessary and which adjustment mode to use. This process involves learning and predicting historical data, as well as dynamically adjusting real-time data. Air conditioning adjustment data generation: Based on the decision results, the intelligent module generates corresponding air conditioning adjustment data, including parameters such as target temperature, humidity, and air quality, as well as the corresponding adjustment mode (whole control mode or zone control mode). It can realize real-time monitoring and intelligent control of the internal environment of the subway, improve energy utilization efficiency, reduce operating costs, and enhance passenger comfort.

[0029] Feeding back the air conditioning adjustment data to the subway air conditioning system to perform subway ventilation and air conditioning control, wherein a connection loop is established between the subway air conditioning system, the intelligent module and the distributed sensing monitoring device;

[0030] Specifically, a connection loop is established between the subway air-conditioning system, the intelligent module and the distributed sensing and monitoring device. This can be achieved through a wired or wireless communication interface or network connection to ensure that data can be transmitted and exchanged between these devices. Air-conditioning adjustment data feedback: the generated air-conditioning adjustment data is fed back from the intelligent module to the subway air-conditioning system through the connection loop. These data include parameters such as the target temperature, humidity, air quality, etc. that need to be adjusted, as well as the corresponding adjustment mode (whole control mode or partition control mode). Subway ventilation and air-conditioning control: After the subway air-conditioning system receives the feedback air-conditioning adjustment data, it performs actual ventilation and air-conditioning control based on these data. This includes the control of ventilation equipment, the adjustment of the switch or working mode of the air-conditioning equipment, etc. By feeding back the air-conditioning adjustment data to the subway air-conditioning system for subway ventilation and air-conditioning control, intelligent ventilation and air-conditioning control can be achieved, thereby improving the energy efficiency of the system and the comfort of passengers.

[0031] Simultaneously conduct dynamic monitoring of air conditioning control and electrical systems to determine control feedback information, including synchronously determining relay protection response;

[0032] Specifically, in the subway system, dynamic monitoring of both the air conditioning control and electrical systems is performed simultaneously. Air conditioning control primarily focuses on environmental parameters such as temperature, humidity, and air quality, while dynamic electrical system monitoring focuses on the operating status of the power system, such as voltage, current, and power. Control feedback information is determined using data collected by sensors and monitoring equipment. For air conditioning control, this may include equipment operating status, indoor and outdoor temperature, and humidity; for the electrical system, this may include current, voltage, and power factor. Relay protection response is synchronously determined based on control feedback information. Relay protection is a critical component of the power system, ensuring rapid disconnection of faulty lines in the event of a fault to prevent further expansion. By monitoring the operating status of the electrical system, potential faults can be promptly detected and the relay protection devices can be triggered to take appropriate action. By simultaneously monitoring the dynamic status of the air conditioning control and electrical systems, determining control feedback information and relay protection responses, efficient control and safe operation of the subway system can be achieved.

[0033] Based on the control feedback information and the relay protection response, abnormal operation and control analysis and feedback decision-making are performed in combination with the intelligent module, and feedback adjustment data is determined and transmitted to the subway air-conditioning system.

[0034] Specifically, after collecting control feedback information and relay protection responses, the intelligent module can perform abnormal operation and control analysis. This involves analyzing the collected data to identify abnormal conditions in the subway system. These abnormal conditions may include air conditioning equipment failures or power system failures. Feedback decisions: Based on the results of the abnormal operation and control analysis, the intelligent module can make appropriate feedback decisions. These may include adjusting the operating mode of the air conditioning equipment or changing the operating parameters of the power system. Furthermore, the intelligent module can generate corresponding alarms as needed to alert operators and prompt them to take appropriate action. Feedback adjustment data determination: Based on the feedback decision results, the intelligent module can determine the appropriate feedback adjustment data. This data may include the required air conditioning equipment operating parameters and the required power system operating status. Data transmission to the subway air conditioning system: The determined feedback adjustment data is transmitted to the subway air conditioning system. This can be achieved through interface connections, network communications, and other methods. The subway air conditioning system will then make appropriate adjustments and optimizations based on the received feedback adjustment data to ensure stable operation of the subway system. Based on the comprehensive analysis of control feedback information, relay protection responses, and the intelligent module, abnormal operation and control analysis and feedback decisions for the subway system can be implemented, ensuring stable and efficient operation of the subway system.

[0035] Furthermore, if Figure 2 As shown, the method of the present application determines a fixed control mode mapped to the periodic division result, and the method includes:

[0036] Perform first-level time zone division based on seasonality and determine the first division result;

[0037] Perform secondary time zone division based on external environmental factors and determine the second division result;

[0038] fusing the first division result and the second division result to determine the periodic division result;

[0039] A basic air-conditioning control standard that matches each periodic division result under conventional control requirements is determined as the fixed control mode, wherein the fixed control mode corresponds to each division period one by one.

[0040] Specifically, a first-level time zone division is performed based on seasonality to determine the first division result. Given the close relationship between the subway system and local climate conditions, the first-level time zone division can be based on seasonal variations. For example, a year can be divided into four first-level time zones: spring, summer, autumn, and winter. Each time zone corresponds to different climate conditions and energy demands. A second-level time zone division is performed based on external environmental factors to determine the second division result. Within each first-level time zone, a second-level time zone division can be further performed based on external environmental factors. These external environmental factors may include daily weather conditions, sunshine duration, wind speed, etc. For example, within the first-level time zone in summer, a second-level time zone division can be performed based on the daily maximum temperature and humidity, such as a high-temperature, humid zone and a low-temperature, dry zone. The first and second division results are then integrated to determine a periodic division result. By integrating the first-level and second-level time zone division results, a periodic or time-dependent division result can be obtained within each season. For example, in summer, different air conditioning control strategies can be set in the morning and evening to meet passenger comfort and energy needs during different time periods. Under conventional control requirements, basic air conditioning control standards that match the results of each periodic division are determined as fixed control modes. Based on the characteristics and requirements of each periodic division, corresponding fixed control modes can be developed. These modes should meet conventional control requirements, such as controlling parameters such as temperature, humidity, and air quality, and be flexibly configured and adjusted according to actual needs. The fixed control modes correspond one-to-one with each division period. To achieve refined air conditioning control, each fixed control mode should correspond one-to-one with the corresponding periodic division result. This allows for the selection of appropriate control modes based on different time periods and environmental conditions, and for real-time monitoring and adjustment. Through these steps, refined control of the subway air conditioning system can be achieved. The time zone division method based on seasonal and external environmental factors can better adapt to climate conditions and energy requirements within different time periods, improving energy efficiency and reducing operating costs. Furthermore, the basic air conditioning control standards that match the results of each periodic division serve as fixed control modes, meeting conventional control requirements and enhancing passenger comfort.

[0041] Furthermore, if Figure 3 As shown, the present application method makes an air conditioning adjustment decision, and the method includes:

[0042] Identifying the environmental sensor data and extracting regional distribution features, wherein the feature dimensions include at least flow distribution, temperature distribution, and air quality distribution;

[0043] In combination with the regional distribution characteristics, determining whether a distribution balance threshold is met;

[0044] If satisfied, an overall adjustment instruction is generated, and the mean value is calculated based on the regional distribution characteristics as the balanced environment data;

[0045] Based on the equalization environment data, an overall amplitude modulation is determined.

[0046] Specifically, environmental sensor data is identified and regional distribution characteristics are extracted. By analyzing environmental sensor data, different regional distribution characteristics can be identified. These characteristics should at least include flow rate distribution, temperature distribution, and air quality distribution. They may also include the distribution of other environmental parameters, such as humidity and CO2 concentration. Regional distribution characteristics are combined to determine whether a distribution balance threshold is met. Based on the extracted regional distribution characteristics, these characteristics can be further combined to determine whether the distribution balance threshold is met. This may involve evaluating the balance of parameters such as flow rate, temperature, and air quality. If the distribution balance threshold is met, the next step is performed; if not, appropriate adjustment measures may be required. Overall adjustment instructions are generated, and a mean is calculated based on the regional distribution characteristics to generate balanced environmental data. When the distribution balance threshold is met, a mean is calculated based on the regional distribution characteristics to generate balanced environmental data. This may involve averaging or weighted averaging parameters such as temperature, humidity, and air quality across different regions. The generated mean data can be used as part of the overall adjustment instruction to guide subsequent air conditioning control operations. Overall amplitude modulation is determined based on the balanced environmental data. Based on the generated balanced environmental data, the overall amplitude modulation can be further determined. This may involve calculating and optimizing the control amplitude of air conditioning equipment to ensure that environmental parameters across the entire subway system achieve the desired equilibrium. Through these steps, intelligent control of the subway air conditioning system can be achieved. Identifying and analyzing regional distribution characteristics in environmental sensor data can better understand the environmental conditions within the subway system. Combined with the determination of distribution equilibrium thresholds, this can guide the generation of overall control instructions. The resulting balanced environmental data and overall modulation amplitude provide an effective control reference for the subway air conditioning system, ensuring that environmental parameters across the entire system achieve the desired equilibrium, improving passenger comfort and energy efficiency.

[0047] Furthermore, the present application method also includes:

[0048] If the regional distribution characteristics do not meet the distribution balance threshold, generating a partition adjustment instruction;

[0049] Upon receipt of the partition adjustment instruction, the subway distribution area is divided based on the distribution balance threshold to determine multiple local areas;

[0050] For the multiple local areas, regional distribution characteristics of each local area are extracted, and partition balance environment data is calculated to determine the partition amplitude modulation, wherein the partition amplitude modulation corresponds one-to-one to the multiple local areas.

[0051] Specifically, when regional distribution characteristics do not meet the distribution balance threshold, zoning adjustment instructions can be generated. These instructions will make corresponding adjustments to different subway distribution areas to ensure that they meet the distribution balance threshold. Subway Distribution Area Division: Following the receipt of the zoning adjustment instructions, the subway distribution area can be divided based on the distribution balance threshold to determine multiple local areas. This allows the entire subway system to be divided into different areas or subsystems, facilitating more specific control operations. Regional Distribution Characteristics of Each Local Area and Calculation of Zoning Balanced Environmental Data: For each of the multiple local areas, regional distribution characteristics can be extracted and zoning balanced environmental data can be calculated. This data reflects the environmental conditions within each local area and serves as a reference for subsequent control operations. Zoning Amplitude Modulation: Based on the calculated zoning balanced environmental data, zoning amplitude modulation can be determined for each local area. These amplitude modulations are mapped to different local areas and guide the control of air conditioning equipment in the corresponding area. Through these steps, more refined air conditioning control can be achieved when regional distribution characteristics do not meet the distribution balance threshold. By dividing the metro's distribution area and generating zone adjustment instructions, specific air conditioning control operations can be implemented for each local area. Extracting the regional distribution characteristics of each local area and calculating zone equilibrium environmental data helps better understand the environmental conditions in each area. The resulting zone amplitude adjustment provides a specific control reference for air conditioning equipment in each local area, ensuring that environmental parameters across the entire metro system are maintained at the desired equilibrium state.

[0052] Furthermore, the method of the present application performs dynamic monitoring of air conditioning control and electrical systems simultaneously, and the method includes:

[0053] Obtain dynamic monitoring information and perform simultaneous integration to determine the time series monitoring information with time series identification;

[0054] For the time series monitoring information, the correlation between heterogeneous data and the time series data is identified, and correlation identification is performed to determine multiple data networks, which are added to the control feedback information.

[0055] Specifically, dynamic monitoring information about the subway system is acquired through sensors or other monitoring equipment. This information may include various environmental parameters (such as temperature, humidity, and air quality) and equipment operating status. This information is then time-series integrated, meaning it is arranged and organized chronologically. The resulting information is labeled with a time series identifier, reflecting how the monitoring data changes over time. Correlation identification is performed on heterogeneous data within the same time series monitoring information: Based on the time series monitoring information, correlation identification is performed on heterogeneous data within the same time series data. This involves performing correlation analysis on data from different sources and types to identify their connections and influences. For example, the interrelationships between parameters such as temperature, humidity, and air quality, as well as their relationship with the subway system's operating status, can be analyzed. Correlation identification is performed to identify multiple data networks: Based on the results of correlation identification, correlation identification is performed to identify multiple data networks. Each data network may represent a specific correlation or influencing factor. For example, one data network may represent the interaction between temperature and humidity, while another may represent the relationship between air quality and the subway system's operating status. The identified data networks are then added to the control feedback information. These data networks serve as a reference for the intelligent module's abnormal operation and control analysis and feedback decision-making. By comprehensively considering information from multiple data networks, a more comprehensive understanding of the subway system's operating conditions and environmental parameters can be achieved, enabling more accurate control decisions. Through these steps, dynamic monitoring information can be acquired and integrated in a time series, identifying correlations between heterogeneous data sources and incorporating them into control feedback. This enables more comprehensive and refined monitoring and control of the subway system, improving system efficiency and passenger comfort.

[0056] Furthermore, the method of the present application performs abnormal operation and control analysis based on the control feedback information and the relay protection response in combination with the intelligent module, and the method includes:

[0057] Identifying the control feedback information and the relay protection response based on the electrical system to determine an electrical abnormality data sequence;

[0058] Read the electrical anomaly data sequence within a predetermined time interval and screen the electrical faults that meet the predetermined frequency;

[0059] The electrical fault is traced and an operation and maintenance decision is made to generate an operation and maintenance instruction, wherein the operation and maintenance instruction is marked with an operation and maintenance plan and an operation and maintenance time node.

[0060] Specifically, electrical system control feedback information and relay protection responses can be identified by analyzing the control feedback information and relay protection responses. This information may include abnormal fluctuations in electrical parameters such as current, voltage, and power factor, as well as faulty operation of relay protection devices. Electrical abnormality data sequences can be determined based on the identified abnormalities. These data sequences may include the time of occurrence, duration, and type of abnormality. By analyzing these data sequences, we can better understand the abnormality's development trend and impact. Electrical abnormality data sequences within a predetermined time interval can be read to screen for electrical faults with a predetermined frequency. After determining the electrical abnormality data sequence, the data sequences within the predetermined time interval can be read to screen for electrical faults with a predetermined frequency. Electrical fault source tracing and maintenance decision-making can be performed, and maintenance instructions can be generated. For the selected electrical faults, source tracing analysis can be performed to identify the root cause. Based on this, appropriate maintenance decisions can be made and maintenance instructions generated. These instructions should include specific maintenance plans and timelines to facilitate subsequent maintenance work. Through the above steps, control feedback information and relay protection responses based on the electrical system can be identified, electrical anomaly data sequences can be determined, and corresponding operation and maintenance instructions can be generated. This facilitates more comprehensive and refined monitoring and control of the electrical components of the subway system, improving system efficiency and passenger comfort. Furthermore, by tracing the source of electrical faults and making operation and maintenance decisions, more targeted and effective operation and maintenance instructions can be generated, providing strong support for the stable operation of the subway system.

[0061] Furthermore, the method of the present application performs abnormal operation and control analysis based on the control feedback information and the relay protection response in combination with the intelligent module, and the method includes:

[0062] Identifying the control feedback information based on air conditioning control, performing a control deviation analysis in combination with the air conditioning adjustment data, and determining a control deviation degree;

[0063] If the control deviation is greater than a predetermined deviation threshold, a control deviation trend determination is performed;

[0064] If the control deviation trend is greater than a predetermined deviation trend, deviation information is measured and a feedback adjustment instruction is generated.

[0065] Specifically, by analyzing the control feedback information from the air conditioning control system, the operating status of the air conditioning equipment and the effectiveness of controlling environmental parameters can be identified. This information may include measured values ​​of environmental parameters such as temperature, humidity, and air quality, as well as the execution status of control commands. Deviation analysis is performed in conjunction with air conditioning control data: The identified control feedback information is combined with the air conditioning control data to perform deviation analysis. This may involve analyzing the deviation between actual environmental parameters and expected target values ​​and evaluating the effectiveness of control command execution. Deviation analysis can determine the control system's deviation. Determining control deviation: Based on the results of the deviation analysis, the control system's deviation can be determined. This deviation reflects the control system's performance and control accuracy. Excessive deviation may indicate poor control effectiveness and require appropriate adjustments. If the control deviation exceeds a predetermined deviation threshold, a control deviation trend assessment is performed: If the control deviation exceeds a predetermined deviation threshold, a control deviation trend assessment is performed. This may involve analyzing historical data to determine whether the deviation is gradually increasing or decreasing, as well as the speed and direction of the change. If the control deviation trend exceeds the predetermined deviation trend, the deviation information is measured and feedback adjustment instructions are generated. Through these steps, control feedback information based on air conditioning control can be identified, deviation control analysis can be performed in conjunction with air conditioning adjustment data, and corresponding feedback adjustment instructions can be generated. This facilitates more comprehensive and refined monitoring and control of the subway system's air conditioning equipment, improving system operational efficiency and passenger comfort. Furthermore, by analyzing and determining the trend of control deviations, potential issues can be promptly identified and resolved, ensuring the stable operation of the entire subway system.

[0066] Example 2

[0067] Based on the same inventive concept as the above-mentioned embodiment of a subway ventilation and air conditioning optimization adjustment method, as Figure 4 As shown, the present application provides a subway ventilation and air conditioning optimization and adjustment system, the system comprising:

[0068] A time zone division module 10 is used to perform seasonal time zone division and determine a fixed control mode mapped to the periodic division result;

[0069] A control mode activation module 20, which configures the subway air conditioning system based on the fixed control mode and activates a scene-adapted target control mode;

[0070] An air conditioning adjustment data generation module 30, which determines and makes decisions on the necessity of air conditioning adjustment based on environmental sensor data transmitted back from the distributed sensing device to the intelligent module, and generates air conditioning adjustment data. The air conditioning adjustment mode includes a whole-control mode and a partitioned control mode;

[0071] An air conditioning control module 40 is configured to feed the air conditioning adjustment data back to the subway air conditioning system to control the subway ventilation and air conditioning, wherein a connection loop is established between the subway air conditioning system, the intelligent module, and the distributed sensing and monitoring device;

[0072] A feedback information determination module 50 is used to synchronously perform dynamic monitoring of air conditioning control and electrical systems, determine control feedback information, and synchronously determine a relay protection response;

[0073] The operation control analysis module 60 performs abnormal operation control analysis and feedback decision-making based on the control feedback information and the relay protection response in combination with the intelligent module, determines feedback adjustment data and transmits it to the subway air-conditioning system.

[0074] Furthermore, the system also includes:

[0075] The fixed control mode acquisition module performs a first-level time zone division based on seasonality to determine a first division result; performs a second-level time zone division based on external environmental factors to determine a second division result; integrates the first division result and the second division result to determine the periodic division result; determines the basic air-conditioning control standard that matches each periodic division result under conventional control requirements as the fixed control mode, wherein the fixed control mode corresponds one-to-one to each division period.

[0076] Furthermore, the system also includes:

[0077] an overall amplitude modulation determination module, configured to identify the environmental sensor data and extract regional distribution features, wherein the feature dimensions include at least flow distribution, temperature distribution, and air quality distribution;

[0078] In combination with the regional distribution characteristics, determining whether a distribution balance threshold is met;

[0079] If satisfied, an overall adjustment instruction is generated, and the mean value is calculated based on the regional distribution characteristics as the balanced environment data;

[0080] Based on the equalization environment data, an overall amplitude modulation is determined.

[0081] Furthermore, the system also includes:

[0082] The zoning amplitude modulation determination module is configured to generate a zoning adjustment instruction if the regional distribution characteristics do not meet the distribution balance threshold; upon receiving the zoning adjustment instruction, the subway distribution area is divided based on the distribution balance threshold to determine multiple local areas; for the multiple local areas, the regional distribution characteristics of each local area are extracted and the zoning balance environment data is calculated to determine the zoning amplitude modulation, wherein the zoning amplitude modulation corresponds one-to-one to the multiple local areas.

[0083] Furthermore, the system also includes:

[0084] Multiple data network determination modules are used to obtain dynamic monitoring information and perform simultaneous integration to determine time series monitoring information with time series identification; for the time series monitoring information, the correlation of heterogeneous data under simultaneous data is identified, and correlation identification is performed to determine multiple data networks and add them into the control feedback information.

[0085] Furthermore, the system also includes:

[0086] An operation and maintenance instruction generation module is used to identify the control feedback information and the relay protection response based on the electrical system, determine the electrical abnormality data sequence; read the electrical abnormality data sequence within a predetermined time interval, and screen electrical faults that meet the predetermined frequency; trace the source and make operation and maintenance decisions on the electrical faults, and generate operation and maintenance instructions, wherein the operation and maintenance instructions are marked with an operation and maintenance plan and an operation and maintenance time node.

[0087] Furthermore, the system also includes:

[0088] A feedback adjustment instruction generation module is used to identify the control feedback information based on air-conditioning control, perform deviation control analysis in combination with the air-conditioning adjustment data, and determine the control deviation; if the control deviation is greater than a predetermined deviation threshold, perform a control deviation trend judgment; if the control deviation trend is greater than the predetermined deviation trend, measure the deviation information and generate a feedback adjustment instruction.

[0089] Through the detailed description of the aforementioned subway ventilation and air-conditioning optimization and adjustment method, those skilled in the art can clearly understand a subway ventilation and air-conditioning optimization and adjustment system in this embodiment. For the system disclosed in the embodiment, since it corresponds to the device disclosed in the embodiment, the description is relatively simple. For relevant matters, please refer to the method part.

[0090] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing and adjusting subway ventilation and air conditioning, characterized in that: The method comprises: Perform seasonal time zone division and determine a fixed control mode mapped to the periodic division results; Based on the fixed control mode, the subway air conditioning system is configured and the scene-adapted target control mode is activated; Based on distributed sensing devices, environmental sensor data is transmitted back to the intelligent module to determine and make decisions on the necessity of air conditioning adjustment and generate air conditioning adjustment data. The air conditioning adjustment mode includes overall control mode and zone control mode. Feeding back the air conditioning adjustment data to the subway air conditioning system to perform subway ventilation and air conditioning control, wherein a connection loop is established between the subway air conditioning system, the intelligent module and the distributed sensing monitoring device; Simultaneously conduct dynamic monitoring of air conditioning control and electrical systems to determine control feedback information, including synchronously determining relay protection response; Based on the control feedback information and the relay protection response, the intelligent module is combined to perform abnormal operation and control analysis and feedback decision-making, determine feedback adjustment data and transmit it to the subway air conditioning system; Making an air conditioning adjustment decision, the method includes: Identifying the environmental sensor data and extracting regional distribution features, wherein the feature dimensions include at least flow distribution, temperature distribution, and air quality distribution; In combination with the regional distribution characteristics, determining whether a distribution balance threshold is met; If satisfied, an overall adjustment instruction is generated, and the mean value is calculated based on the regional distribution characteristics as the balanced environment data; determining an overall amplitude modulation based on the balanced environment data; The method includes: If the regional distribution characteristics do not meet the distribution balance threshold, generating a partition adjustment instruction; Upon receipt of the partition adjustment instruction, the subway distribution area is divided based on the distribution balance threshold to determine multiple local areas; For the multiple local areas, extract regional distribution characteristics of each local area and calculate zone balance environment data to determine zone amplitude modulation, wherein the zone amplitude modulation corresponds to the multiple local areas one by one; Determining a fixed control mode mapped to the periodic partitioning result, the method includes: Perform first-level time zone division based on seasonality and determine the first division result; Perform secondary time zone division based on external environmental factors and determine the second division result; fusing the first division result and the second division result to determine the periodic division result; A basic air-conditioning control standard that matches each periodic division result under conventional control requirements is determined as the fixed control mode, wherein the fixed control mode corresponds to each division period one by one.

2. The method according to claim 1, wherein The method of synchronously performing dynamic monitoring of air conditioning control and electrical systems includes: Obtain dynamic monitoring information and perform simultaneous integration to determine the time series monitoring information with time series identification; For the time series monitoring information, the correlation between heterogeneous data and the time series data is identified, and correlation identification is performed to determine multiple data networks, which are added to the control feedback information.

3. The method according to claim 1, wherein Based on the control feedback information and the relay protection response, and in combination with the intelligent module, abnormal operation and control analysis is performed, the method comprising: Identifying the control feedback information and the relay protection response based on the electrical system to determine an electrical abnormality data sequence; Read the electrical anomaly data sequence within a predetermined time interval and screen the electrical faults that meet the predetermined frequency; The electrical fault is traced and an operation and maintenance decision is made to generate an operation and maintenance instruction, wherein the operation and maintenance instruction is marked with an operation and maintenance plan and an operation and maintenance time node.

4. The method according to claim 3, wherein Based on the control feedback information and the relay protection response, and in combination with the intelligent module, abnormal operation and control analysis is performed, the method comprising: Identifying the control feedback information based on air conditioning control, performing a control deviation analysis in combination with the air conditioning adjustment data, and determining a control deviation degree; If the control deviation is greater than a predetermined deviation threshold, a control deviation trend determination is performed; If the control deviation trend is greater than a predetermined deviation trend, deviation information is measured and a feedback adjustment instruction is generated.

5. A subway ventilation and air conditioning optimization and adjustment system, characterized in that: The system comprises: A time zone division module, which is used to perform seasonal time zone division and determine a fixed control mode mapped to the periodic division result; A control mode activation module, which configures the subway air-conditioning system based on the fixed control mode and activates a target control mode adapted to the scenario; An air conditioning adjustment data generation module, which determines and decides on the necessity of air conditioning adjustment based on environmental sensor data transmitted back from the distributed sensing device to the intelligent module, and generates air conditioning adjustment data. The air conditioning adjustment modes include a whole-control mode and a partitioned control mode; An air conditioning control module, which is used to feed back the air conditioning adjustment data to the subway air conditioning system to perform subway ventilation and air conditioning control, wherein a connection loop is established between the subway air conditioning system, the intelligent module, and the distributed sensing and monitoring device; A feedback information determination module, the feedback information determination module is used to synchronously perform dynamic monitoring of air conditioning control and electrical systems, determine control feedback information, and synchronously determine relay protection response; An operation control analysis module, which performs abnormal operation control analysis and feedback decision-making based on the control feedback information and the relay protection response in combination with the intelligent module, determines feedback adjustment data, and transmits it to the subway air conditioning system; Furthermore, the system also includes: an overall amplitude modulation determination module, configured to identify the environmental sensor data and extract regional distribution features, wherein the feature dimensions include at least flow distribution, temperature distribution, and air quality distribution; In combination with the regional distribution characteristics, determining whether a distribution balance threshold is met; If satisfied, an overall adjustment instruction is generated, and the mean value is calculated based on the regional distribution characteristics as the balanced environment data; determining an overall amplitude modulation based on the balanced environment data; Furthermore, the system also includes: a zone amplitude modulation determination module, configured to generate a zone adjustment instruction if the regional distribution characteristics do not meet a distribution balance threshold; upon receiving the zone adjustment instruction, divide the subway distribution area based on the distribution balance threshold to determine a plurality of local areas; extract the regional distribution characteristics of each local area and calculate zone balance environment data for each of the plurality of local areas to determine a zone amplitude modulation, wherein the zone amplitude modulation corresponds one-to-one to the plurality of local areas; The system also includes: The fixed control mode acquisition module performs a first-level time zone division based on seasonality to determine a first division result; performs a second-level time zone division based on external environmental factors to determine a second division result; integrates the first division result and the second division result to determine the periodic division result; determines the basic air-conditioning control standard that matches each periodic division result under conventional control requirements as the fixed control mode, wherein the fixed control mode corresponds one-to-one to each division period.

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