A method and system for intelligent control of intelligent low-voltage systems

Abstract

This invention discloses an intelligent control method and system for intelligent low-voltage systems, relating to the field of low-voltage system control technology. It integrates various low-voltage electronic systems within a designated building's low-voltage system, analyzes the comprehensive impact index of conflicting control objectives for each system, including constructing a conflict matrix, determining conflict severity coefficients and weighted importance indicators, and then calculating a comprehensive conflict impact coefficient to assess the conflict situation. For severely conflicting low-voltage electronic systems, intelligent agent deep learning optimization is used to calculate the coordination optimization effectiveness coefficient using optimization coordination parameters, determining whether the low-voltage system optimization requirements are met. If not, by monitoring environmental information and system operation data, an environmental information adaptability index and a coordination enhancement optimization index are calculated to evaluate the optimization strategy, enabling the low-voltage system to effectively resolve conflicts among various low-voltage electronic systems, improve overall performance and stability, and ensure efficient operation.

Description

Technical Field

[0001] This invention relates to the field of low-voltage system control technology, and specifically to an intelligent control method and system for intelligent low-voltage systems. Background Technology

[0002] With the development of intelligent buildings, low-voltage systems are becoming increasingly complex. Due to differences in communication protocols and data formats, various low-voltage systems often experience control objective conflicts during integration, affecting the overall performance and operational stability of the system. Against this backdrop, research on intelligent control methods and systems for intelligent low-voltage systems is becoming increasingly important.

[0003] Existing technology, such as the invention patent application with publication number CN113838563B, discloses a hospital intelligent building low-voltage system, control method, terminal, and storage medium. It belongs to the field of low-voltage systems. The key technical points include an elevator control module, several low-voltage servers, and several terminal devices. Each floor is equipped with an environmental monitoring module and an alarm module. Each low-voltage server controls the environmental monitoring module and alarm module of one floor. Several low-voltage servers are connected to a central server. The central server selects a low-voltage server to operate based on the needs of the terminal devices. All low-voltage servers are communicatively connected to the elevator control module, and all terminal devices are communicatively connected to the central server. The central server receives the location information of the terminal devices in real time. Based on the demand information, the central server controls the corresponding low-voltage server to plan the travel route, effectively selecting the floor corridor with the highest accessibility as the optimal travel route, reducing the time it takes for doctors to reach designated locations.

[0004] The above solution has at least the following technical problems: 1. In the actual operation of the intelligent building low-voltage system in the hospital, due to the lack of analysis of the control target conflicts of each low-voltage electronic system, when there are inconsistencies in communication protocols and data formats between elevator control module, environmental monitoring module, alarm module and various servers, problems such as information transmission errors and chaotic command execution will frequently occur, such as incorrect elevator stops and ineffective monitoring of the floor environment. In severe cases, this will endanger the safety of medical staff and patients and the smooth progress of medical work.

[0005] 2. The above solution lacks a coordination and optimization strategy for subsystem conflicts, which means that the low-voltage system cannot reasonably adjust the resource allocation and operating status of each subsystem according to the actual situation. For example, during peak electricity consumption periods in hospitals, if there is a lack of effective conflict coordination between low-voltage systems such as lighting systems, medical equipment power supply systems, and air conditioning systems, there will be situations where each system competes for power resources, causing some equipment to malfunction and resulting in energy waste. At the same time, medical staff will encounter waiting due to the lack of coordination between low-voltage systems when performing tasks, such as going to wards or operating rooms, which reduces work efficiency and affects the timeliness and quality of medical services.

[0006] 3. The above solution lacks an analysis process for optimizing and adjusting the low-voltage system based on environmental information. The hospital environment is complex and ever-changing. For example, different departments have different requirements for environmental conditions such as temperature, humidity, and air quality. In addition, the flow of people and the operation of equipment are constantly changing. Without a coordination mechanism between environmental factors and the operation of the low-voltage system, the environmental monitoring module may be able to detect environmental changes, but it may not be able to effectively coordinate with other subsystems to make corresponding adjustments. As a result, the hospital environment may not always be kept in a suitable state, which will affect the recovery of patients and the working comfort of medical staff. Summary of the Invention

[0007] The purpose of this invention is to provide an intelligent control method and system for intelligent low-voltage systems, which solves the problems existing in the background art.

[0008] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The present invention provides an intelligent control method for intelligent low-voltage systems, including: Step 1, collaborative control process evaluation: In the low-voltage system corresponding to a specified building, the various low-voltage electronic systems are integrated, and then the comprehensive impact index of the control target conflict of each low-voltage electronic system during the integration process is analyzed.

[0009] Step 2: Impact Assessment of Conflicts in Weak Electronic Systems: Based on the comprehensive impact index of control objective conflicts of each weak electronic system during the fusion process, the control objective conflicts of each weak electronic system during the fusion process are assessed.

[0010] Step 3: Preliminary analysis of coordination and optimization: Based on the system conflict situation of each weak electronic system during the fusion process, coordination and optimization are carried out on each weak electronic system with serious conflict of control objectives.

[0011] Step 4: Evaluation of conflict optimization strategies: If the results of coordinated optimization of severely conflicting weak electronic systems do not meet the requirements of weak electronic system optimization, then the optimization strategies of severely conflicting weak electronic systems shall be evaluated.

[0012] In a second aspect, the present invention provides an intelligent control system for a low-voltage system, comprising: a collaborative control process evaluation module, used to integrate various low-voltage electronic systems in a specified building, and then analyze the comprehensive impact index of control target conflict corresponding to each low-voltage electronic system during the integration process.

[0013] The weak electronic system conflict impact assessment module is used to assess the control objective conflict situation of each weak electronic system during the fusion process based on the comprehensive impact index of the control objective conflict of each weak electronic system during the fusion process.

[0014] The preliminary analysis module for coordination and optimization is used to coordinate and optimize weak electronic systems with severe conflicting control objectives based on the system conflict situation of each weak electronic system during the fusion process.

[0015] The conflict optimization strategy evaluation module is used to evaluate the optimization strategies for each severely conflicting weak electronic system when the results of coordinated optimization of each system do not meet the requirements of weak electronic system optimization.

[0016] The beneficial effects of the present invention are as follows: 1. The intelligent control method and system for a low-voltage system provided by the embodiments of the present invention, in the process of integrating various subsystems of the low-voltage system, clearly defines whether there is a conflict of control objectives between various low-voltage systems by constructing a conflict matrix, such as between a lighting system and a fire alarm system. Through clear matrix judgment rules, potential conflict situations are accurately identified. At the same time, based on the preset conflict severity coefficient scoring standard, the degree of conflict is quantified into a specific value, which is conducive to intuitively and accurately grasping the severity of the conflict between various subsystems, ensuring the overall stability and security of the low-voltage system, and avoiding system failures or functional failures caused by conflicts.

[0017] 2. This invention utilizes parameters such as weighted importance indicators and conflict severity coefficients to calculate the comprehensive impact coefficient of control target conflict. It fully considers the differences in spatial impact factors and importance scores among various low-voltage electronic systems, which is beneficial for comprehensively measuring the actual impact of conflicts in each subsystem on the entire low-voltage system. In a certain building, there is a certain conflict between the security system and the air conditioning and ventilation system. Through this assessment method, not only can the existence of the conflict be determined, but also the comprehensive impact of the conflict on the comfort of people in the building, asset security, and energy consumption can be accurately assessed based on its importance and spatial impact range in the overall operation of the building. This provides a scientific basis for formulating reasonable coordination strategies.

[0018] 3. In this embodiment of the invention, for various low-voltage electronic systems with severe conflicts, a smart agent is used for deep learning optimization. By monitoring the operating status of each low-voltage electronic system in real time, the effectiveness coefficient of coordination optimization is calculated. This is beneficial for automatically and dynamically adjusting the operating parameters and cooperation methods of each subsystem in complex low-voltage system environments, so as to realize the self-optimization and upgrading of the system. For example, in the daily operation of a low-voltage system in a building, the load and operating requirements of each low-voltage device also change. The smart agent optimizes the working mode of each subsystem based on real-time monitoring data, improves the system response speed, reduces energy consumption and enhances operational stability, so that the low-voltage system always maintains a high-efficiency and stable operating state.

[0019] 4. In this embodiment of the invention, when it is found that the optimization and adjustment effect of the intelligent coordination strategy is not good, the environmental information of the environment in which each of the severely conflicting weak electronic systems is located is monitored, the environmental information adaptability index is calculated, and the coordination enhancement optimization index is calculated by combining indicators such as interactive data traffic, synchronization event success rate and collaborative task completion efficiency. The effectiveness of the optimization strategy is further evaluated, and the optimization strategy is continuously improved based on the evaluation results. This is conducive to the weak electronic system continuously adapting to changes in the internal and external environment during long-term operation and continuously improving system performance. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the implementation steps of the present invention.

[0022] Figure 2 This is a schematic diagram of the system structure connection of the present invention. Detailed Implementation

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0024] Please see Figure 1As shown, the present invention provides an intelligent control method for a low-voltage system. The method includes: Step 1, evaluation of the collaborative control process: In the low-voltage system corresponding to a specified building, the various low-voltage electronic systems are integrated, and then the comprehensive impact index of the control target conflict of each low-voltage electronic system during the integration process is analyzed.

[0025] In a specific embodiment, the analysis of the comprehensive impact index of conflict corresponding to each low-voltage electronic system during the fusion process is as follows: When applied to the low-voltage electronic system corresponding to a specified building, if the communication protocols and data formats of each low-voltage electronic system are not uniform, the low-voltage electronic systems are fused. By obtaining the comprehensive impact index of control target conflict corresponding to each fused low-voltage electronic system, which includes a conflict matrix, a conflict severity coefficient, and a weighted importance index, the comprehensive impact coefficient of control target conflict corresponding to each fused low-voltage electronic system is calculated to evaluate the control target conflict situation corresponding to each low-voltage electronic system during the fusion process.

[0026] When weak electronic systems and weak electronic systems When fusion is performed, and If we represent two weak electronic systems with different communication protocols and data formats, then we set up a collision matrix. ,when When this occurs, it indicates a weak electronic system. and weak electronic systems There is a conflict of control objectives, when When this occurs, it indicates a weak electronic system. and weak electronic systems There is no conflict of control objectives. Based on the preset conflict severity coefficient scoring standard, combined with the weak electronic system... and weak electronic systems The severity of the conflict when control objectives conflict, and thus the weak electronic system. and weak electronic systems Corresponding conflict severity coefficient .

[0027] Calculate the weak electron system separately and weak electronic systems Corresponding spatial influence factor and And based on the preset importance scoring criteria, the weak electronic system is obtained. and weak electronic systems The corresponding importance scores and The weak electronic system and weak electronic systems The corresponding spatial influence factor and importance score are multiplied together to obtain the weak electron system. Weighted importance index and weak electronic systems Weighted importance index .

[0028] It should be noted that the conflict severity coefficient For weak electronic systems and weak electronic systems The quantification of the severity of the conflict is based on the degree of impact of the conflict on personnel safety and system function, with a score range of 0-10. The higher the score, the more severe the conflict. For example, the severity coefficient of the conflict between the lighting system and the fire alarm system is 8 points, which indicates that the conflict between the lighting system and the fire alarm system has a significant impact on personnel safety and the normal functioning of the building.

[0029] Step 2: Impact Assessment of Conflicts in Weak Electronic Systems: Based on the comprehensive impact index of control objective conflicts of each weak electronic system during the fusion process, the control objective conflicts of each weak electronic system during the fusion process are assessed.

[0030] In a specific embodiment, the calculation of the comprehensive influence coefficient of the control target conflict corresponding to each weak electronic system being fused is carried out as follows: based on the weak electronic system and weak electronic systems Corresponding conflict matrix and the severity coefficient of conflict and weak electronic systems Weighted importance index and weak electronic systems Weighted importance index Then, through the calculation formula: To obtain a weak electronic system and weak electronic systems Corresponding control objective conflict comprehensive impact coefficient Based on this, the comprehensive influence coefficient of the control objective conflict corresponding to each weak electronic system being integrated is calculated.

[0031] In a specific embodiment, the process of evaluating the control objective conflict of each weak electronic system during the fusion process is as follows: The weak electronic systems... and weak electronic systems The corresponding comprehensive impact coefficient of control target conflict is compared with the preset threshold of the comprehensive impact coefficient of standard control target conflict. If the weak electronic system and weak electronic systems If the corresponding comprehensive influence coefficient of control target conflict is greater than the preset threshold of the comprehensive influence coefficient of standard control target conflict, it indicates that the weak electronic system... and weak electronic systems The corresponding control objective conflict is a severe conflict; conversely, it indicates a weak electronic system. and weak electronic systems The corresponding control objective conflict is considered to be a non-severe conflict, and this is used to assess the control objective conflict situation of each weak electronic system during the fusion process.

[0032] It should be noted that, for example, in the low-voltage system of a smart building, the smart lighting system and the fire alarm system are two low-voltage electronic systems that need to be integrated. In order to achieve energy saving, the smart lighting system is equipped with timed shutdown and automatic dimming functions. However, when the fire alarm is triggered, due to the priority setting of the energy-saving mode, it fails to switch to the emergency lighting full brightness state in time, resulting in insufficient light in some areas of the evacuation route, which affects the evacuation of personnel. At the same time, the fire alarm system is also interfered with by the delayed response of the lighting system, causing the alarm sound to not propagate smoothly in some areas. In this case, the comprehensive impact coefficient of the control target conflict between the two low-voltage electronic systems far exceeds the preset threshold, which manifests as a serious conflict state.

[0033] This invention utilizes parameters such as weighted importance indices and conflict severity coefficients to calculate the comprehensive impact coefficient of control target conflict. It fully considers the differences in spatial impact factors and importance scores among various low-voltage electronic systems, facilitating a comprehensive assessment of the actual impact of conflicts in each subsystem on the entire low-voltage system. In a building where the security system and air conditioning / ventilation system have certain conflicts, this assessment method not only confirms the existence of the conflict but also accurately assesses its comprehensive impact on occupants' comfort, asset security, and energy consumption based on its importance and spatial impact range within the building's overall operation. This provides a scientific basis for developing reasonable coordination strategies.

[0034] Step 3: Preliminary analysis of coordination and optimization: Based on the system conflict situation of each weak electronic system during the fusion process, coordination and optimization are carried out on each weak electronic system with serious conflict of control objectives.

[0035] In a specific embodiment, the coordinated optimization of each weak electronic system with a severe conflict in control objectives is carried out as follows: Intelligent agents are set up in each weak electronic system with a severe conflict in control objectives to perform deep learning optimization. The intelligent agents monitor the real-time status of each weak electronic system in real time, thereby obtaining the optimization coordination parameters of each weak electronic system after a set time period. The optimization coordination parameters include the proportion of optimized response time, the proportion of energy consumption reduction, and the degree of improvement in operational stability. The coordination optimization effectiveness coefficient of the total weak electronic system after optimization of each weak electronic system over the set time period is then calculated.

[0036] The effectiveness coefficient of the coordination strategy of the total weak current system after optimization of each weak current system over a set time period is compared with the preset coordination optimization effectiveness coefficient threshold. When the effectiveness coefficient of the coordination strategy is greater than the preset coordination optimization effectiveness coefficient threshold, it indicates that the optimization effect of each weak current system with serious conflict within the set time period meets the requirements of weak current system optimization. Otherwise, it indicates that the requirements of weak current system optimization are not met. This achieves the purpose of coordinating and optimizing each weak current system with serious conflict of control objectives.

[0037] It should be noted that, taking the two highly conflicting low-voltage electronic systems of smart lighting and fire alarm as an example, the smart agent collects real-time status data such as the brightness changes and working status of the lighting system, and the smoke concentration perception and alarm triggering frequency of the fire alarm system. It then uses deep learning algorithms to continuously analyze the best coordination mode under different environments and event scenarios. The specific learning and optimization process is existing technology and will not be elaborated on here.

[0038] It should also be noted that the process of obtaining the optimized response time ratio is as follows: after the fire alarm is triggered, the actual time it takes for the lighting system to switch from the current state to the emergency lighting full-on state is recorded. Compared with the average response time before optimization after a set time period, the optimized response time ratio is calculated. Previously, it took an average of 8 seconds, and now it takes an average of 3 seconds. The optimized response time ratio is (8-3)÷8. The process of obtaining the energy consumption reduction ratio and the degree of improvement in operational stability is the same as the process of obtaining the optimized response time ratio, and will not be elaborated on here.

[0039] In a specific embodiment, the calculation of the coordination optimization effectiveness coefficient of each weak electronic system corresponding to the total weak electronic system after optimization over a set time period is carried out as follows: Based on the optimization coordination parameters of each weak electronic system corresponding to the total weak electronic system after the set time period, the calculation is performed using the following formula: The coordination optimization effectiveness coefficients of each weak electronic system and the corresponding total weak electronic system after optimization are obtained. ,in , , Represented as the first The percentage of optimized response time, percentage of energy consumption reduction, and degree of improvement in operational stability for each low-voltage electronic system after a set time period. The designation of the weak electronic systems involved in the severe conflict. , The total number of weak electronic systems with severe conflicts. It is a positive integer. , , These are the weighting factors for the optimized response time ratio, the energy consumption reduction ratio, and the operational stability improvement, respectively.

[0040] It should be noted that, , , The values ​​of are all greater than 0 and less than 1. , , The setup process is as follows: For example, in a building's low-voltage electrical system, there is a serious conflict between the intelligent lighting and security monitoring systems. When determining... , , Firstly, based on the building's core needs, if the building frequently hosts important events and places great emphasis on personnel safety and emergency response, then the weighting factor for improving operational stability should be set high, such as 0.5. This is because instability in the low-voltage system can lead to security monitoring failures or lighting malfunctions, causing safety issues. Regarding the weighting factor for reducing energy consumption, if the building is in a period of energy conservation and emission reduction, and energy costs constitute a large portion of operating costs (e.g., energy expenditure accounts for 30% of total operating costs), then it should be set to 0.3. If the building has emergency response time requirements, such as stipulating that the lighting and security systems must complete key actions within 5 seconds after an emergency occurs, then the weighting factor for optimizing response time should be set to 0.2. This means that while response time is important in calculating the effectiveness coefficient of coordinated optimization, its priority is lower than that of energy consumption reduction and operational stability improvement.

[0041] This invention addresses severely conflicting low-voltage electronic systems by employing intelligent agents for deep learning optimization. By monitoring the operational status of each system in real time, it calculates the effectiveness coefficient of coordinated optimization. This facilitates the automatic and dynamic adjustment of operating parameters and collaboration methods of each subsystem in complex low-voltage system environments, enabling system self-optimization and upgrades. For example, in the daily operation of a building's low-voltage system, the load and operational requirements of each device change accordingly. Based on real-time monitoring data, the intelligent agent optimizes the operating modes of each subsystem, improving system response speed, reducing energy consumption, and enhancing operational stability, ensuring the low-voltage system always maintains a highly efficient and stable operating state.

[0042] Step 4: Evaluation of conflict optimization strategies: If the results of coordinated optimization of severely conflicting weak electronic systems do not meet the requirements of weak electronic system optimization, then the optimization strategies of severely conflicting weak electronic systems shall be evaluated.

[0043] In a specific embodiment, the optimization strategy for evaluating each severely conflicting weak electronic system is implemented as follows: By monitoring the environmental information of the environment corresponding to each severely conflicting weak electronic system, the environmental parameters contained in the environmental information are recorded as follows. , Number each environmental parameter. , This represents the total number of environmental parameters included in the environmental information. For positive integers, use the calculation formula: , obtained the An environmental information adaptability index corresponding to the environment in which a weak electronic system with serious conflicts exists. ,in and The first The first seriously conflicting electronically weak system corresponds to the first The minimum and maximum boundary values ​​of each environmental parameter. For setting The first seriously conflicting electronically weak system corresponds to the first... Weighting factors for each environmental parameter.

[0044] like If the environmental information adaptability index falls below the preset minimum standard threshold, the intelligent coordination strategy is optimized and adjusted. This is achieved by monitoring the interactive data traffic, synchronization event success rate, and collaborative task completion efficiency of the severely conflicting weak electronic systems during operation, which are then recorded as follows: , and Then, the synergistic enhancement optimization index of the total weak electronic system corresponding to each severely conflicting weak electronic system is calculated. After the intelligent coordination strategy is executed and the optimization time period is set, the environmental information adaptability optimization index and synergistic enhancement optimization index of each severely conflicting weak electronic system are calculated respectively.

[0045] If both the environmental information adaptability optimization index and the collaborative enhancement optimization index are greater than 0, it indicates that the optimization and adjustment of the intelligent coordination strategy meets the requirements of low-voltage system optimization; otherwise, it indicates that the optimization and adjustment of the intelligent coordination strategy does not meet the requirements of low-voltage system optimization.

[0046] It should be noted that, The values ​​of are all greater than 0 and less than 1. The setup process and , , The setup process is the same, so I won't go into too much detail here.

[0047] It should also be noted that, taking the low-voltage electrical system of a smart warehouse as an example, it includes two conflicting low-voltage electrical systems: an inventory monitoring system and a temperature and humidity control system. The instruction manual for the electronic products requires that the storage temperature must be between 18℃ and 27℃. Therefore, the minimum boundary value for temperature can be set to 18℃ and the maximum boundary value can be set to 27℃.

[0048] It should also be noted that, taking the intelligent lighting system and fire alarm system in a building as an example, if there is a serious conflict between the lighting system and the fire alarm system, the activation of the intelligent coordination strategy optimization means that: the intelligent agent will reconfigure the communication protocols and priority rules of the two low-voltage electronic systems; for interactive data traffic, it will increase the data transmission frequency and bandwidth of key control signals between the lighting system and the fire alarm system, for example, from 10 key signals per second to 20 per second; regarding the success rate of synchronization events, the optimization will recalibrate the time synchronization mechanism and event response logic of the two low-voltage electronic systems, for example, after the fire alarm is triggered, the success rate of the lighting system switching to emergency lighting within 1 second will increase from the original 70% to over 90%; regarding the efficiency of completing collaborative tasks, the optimization will re-plan the entire emergency process. For example, the total time from the start of the fire alarm to the completion of emergency lighting deployment and related ventilation, evacuation instructions, and other collaborative tasks will be reduced from the original 10 seconds to 6 seconds.

[0049] In a specific embodiment, the calculation of the synergistic enhancement optimization index of the total weak electronic system corresponding to each severely conflicting weak electronic system is carried out through the following process: The calculation formula is as follows: The synergistic enhancement optimization index of the total weak electronic system corresponding to each severely conflicting weak electronic system is obtained. ,in and These are the initial interactive data traffic and the maximum tolerable interactive data traffic, respectively. , , These are the weighting factors corresponding to the set interactive data traffic, the weighting factor corresponding to the synchronization event success rate, and the weighting factor corresponding to the collaborative task completion efficiency.

[0050] It should be noted that, , , The values ​​of are all greater than 0 and less than 1. , , The setup process and , , The setup process is the same, so I won't go into too much detail here.

[0051] In a specific embodiment, the calculation of the environmental information adaptability optimization index and the synergistic enhancement optimization index corresponding to each severely conflicting weak electronic system is carried out as follows: The calculation formula is as follows: , obtained the Environmental information adaptability optimization index corresponding to a weak electronic system with serious conflicts ,in This indicates the number of optimization periods after setting the optimization time period. A severely conflicting weak electronic system corresponds to an environmental information adaptability index of its environment. This represents the set optimization time period, which is used to calculate the synergistic enhancement optimization index of the total weak electronic system corresponding to each severely conflicting weak electronic system.

[0052] It should be noted that the calculation process of the synergistic enhancement optimization index of each severely conflicting weak electronic system corresponding to the total weak electronic system is different from that of the environmental information adaptability optimization index. The calculation process is the same, so I will not go into details here.

[0053] In this embodiment of the invention, when the optimization and adjustment effect of the intelligent coordination strategy is found to be unsatisfactory, the environmental information of the environment in which each of the severely conflicting weak electronic systems is located is monitored, the environmental information adaptability index is calculated, and the coordination enhancement optimization index is calculated by combining indicators such as interactive data traffic, synchronization event success rate and collaborative task completion efficiency. The effectiveness of the optimization strategy is further evaluated, and the optimization strategy is continuously improved based on the evaluation results. This is conducive to the weak electronic system continuously adapting to changes in the internal and external environment during long-term operation and continuously improving system performance.

[0054] Please see Figure 2 As shown, an intelligent control system for a low-voltage system includes the following modules: a collaborative control process evaluation module, a low-voltage system conflict impact evaluation module, a preliminary analysis module for coordination optimization, and a conflict optimization strategy evaluation module.

[0055] The collaborative control process evaluation module is connected to the weak electronic system conflict impact evaluation module, the weak electronic system conflict impact evaluation module is connected to the coordination optimization preliminary analysis module, and the coordination optimization preliminary analysis module is connected to the conflict optimization strategy evaluation module.

[0056] The collaborative control process evaluation module is used to integrate the various low-voltage electronic systems in a specified building, and then analyze the comprehensive impact index of the control target conflict of each low-voltage electronic system during the integration process.

[0057] The weak electronic system conflict impact assessment module is used to assess the control objective conflict situation of each weak electronic system during the fusion process based on the comprehensive impact index of the control objective conflict of each weak electronic system during the fusion process.

[0058] The preliminary analysis module for coordination and optimization is used to coordinate and optimize weak electronic systems with severe conflicting control objectives based on the system conflict situation of each weak electronic system during the fusion process.

[0059] The conflict optimization strategy evaluation module is used to evaluate the optimization strategies for severely conflicting weak electronic systems when the results of coordinated optimization of these systems do not meet the requirements for weak electronic system optimization.

[0060] This invention provides an intelligent control method and system for a low-voltage system. During the integration of various subsystems of the low-voltage system, a conflict matrix is ​​constructed to clearly define whether there are control target conflicts between the various low-voltage systems, such as between a lighting system and a fire alarm system. Through clear matrix judgment rules, potential conflict situations are accurately identified. At the same time, based on a preset conflict severity coefficient scoring standard, the degree of conflict is quantified into a specific value, which is conducive to intuitively and accurately grasping the severity of conflicts between subsystems, ensuring the overall stability and security of the low-voltage system, and avoiding system failures or functional malfunctions caused by conflicts.

[0061] The above content is merely an example and explanation of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present invention.

Claims

1. An intelligent control method for an intelligent low-voltage system, characterized in that, include: Step 1: Evaluation of Collaborative Control Process: In the low-voltage electrical system corresponding to the specified building, the various low-voltage electrical systems are integrated, and then the comprehensive impact index of the control target conflict corresponding to each low-voltage electrical system during the integration process is analyzed. Step 2, Impact Assessment of Conflicts in Weak Electronic Systems: Based on the comprehensive impact index of control target conflicts corresponding to each weak electronic system during the fusion process, the conflict situation of control targets corresponding to each weak electronic system during the fusion process is then assessed. When applied to the low-voltage electrical system of a specified building, if the communication protocols and data formats of the various low-voltage electrical systems are not uniform, the various low-voltage electrical systems are merged. By obtaining the comprehensive impact index of control target conflict corresponding to each low-voltage electrical system being merged, which includes the conflict matrix, conflict severity coefficient and weighted importance index, the comprehensive impact coefficient of control target conflict corresponding to each low-voltage electrical system being merged is calculated, thereby assessing the control target conflict situation of each low-voltage electrical system during the merging process. Step 3: Preliminary analysis of coordination and optimization: Based on the system conflict situation of each weak electronic system during the fusion process, coordination and optimization are carried out on each weak electronic system with serious conflict of control objectives. Intelligent agents are set up for deep learning optimization in each weak electronic system where the control target conflict is severe. The intelligent agents monitor the real-time status of each weak electronic system in real time, and then obtain the optimization coordination parameters of each weak electronic system after a set time period. The optimization coordination parameters include the optimization response time ratio, energy consumption reduction ratio, and operational stability improvement. Then, the coordination optimization effectiveness coefficient of the total weak electronic system after optimization of each weak electronic system after a set time period is calculated. The effectiveness coefficient of the coordination strategy of the total weak current system after optimization of each weak current system over a set time period is compared with the preset coordination optimization effectiveness coefficient threshold. When the effectiveness coefficient of the coordination strategy is greater than the preset coordination optimization effectiveness coefficient threshold, it indicates that the optimization effect of each weak current system with serious conflict within the set time period meets the requirements of weak current system optimization. Otherwise, it indicates that the requirements of weak current system optimization are not met. This achieves the purpose of coordinating and optimizing each weak current system with serious conflict of control objectives. Step 4: Evaluation of conflict optimization strategies: If the results of coordinated optimization of severely conflicting weak electronic systems do not meet the requirements of weak electronic system optimization, then the optimization strategies of severely conflicting weak electronic systems shall be evaluated.

2. The intelligent control method for an intelligent low-voltage system according to claim 1, characterized in that, The analysis of the comprehensive impact indicators of conflict among various weak electronic systems during the fusion process is as follows: When weak electronic systems i and j are merged, i and j represent two weak electronic systems with different communication protocols and data formats, respectively. Then, a conflict matrix Q is set. ij When Q ij When Q = 1, it indicates that there is a conflict in control objectives between the weak electronic system i and the weak electronic system j. ij When the value is 0, it indicates that there is no control objective conflict between weak electronic system i and weak electronic system j. Based on the preset conflict severity coefficient scoring standard, and combined with the conflict severity corresponding to the control objective conflict between weak electronic system i and weak electronic system j, the conflict severity coefficient YZ corresponding to weak electronic system i and weak electronic system j is obtained. ij ; Calculate the spatial influence factor F for weak electronic system i and weak electronic system j respectively. i and F j Based on the preset importance scoring criteria, the importance scores Z corresponding to weak electronic system i and weak electronic system j are obtained respectively. i and Z j The spatial influence factor and importance score corresponding to weak electronic system i and weak electronic system j are multiplied respectively to obtain the weighted importance index of weak electronic system i. Weighted importance index of weak electronic system j 3. The intelligent control method for an intelligent low-voltage system according to claim 2, characterized in that, The calculation of the comprehensive influence coefficient of the control objective conflict for each fused weak electronic system is as follows: Based on the conflict matrix Q corresponding to weak electronic system i and weak electronic system j ij And the conflict severity coefficient YZ ij And the weighted importance index of weak electronic system i Weighted importance index of weak electronic system j Then, through the calculation formula: The comprehensive influence coefficient α of the control objective conflict for weak electronic system i and weak electronic system j is obtained. ij Based on this, the comprehensive influence coefficient of the control objective conflict corresponding to each weak electronic system being integrated is calculated.

4. The intelligent control method for an intelligent low-voltage system according to claim 3, characterized in that, The specific process for evaluating the control objective conflicts among the various weak electronic systems during the fusion process is as follows: The comprehensive impact coefficients of control target conflicts corresponding to weak electronic systems i and j are compared with the preset threshold values ​​of the comprehensive impact coefficients of standard control target conflicts. If the comprehensive impact coefficients of control target conflicts corresponding to weak electronic systems i and j are greater than the preset threshold values, it indicates that the control target conflicts corresponding to weak electronic systems i and j are serious conflicts; otherwise, it indicates that the control target conflicts corresponding to weak electronic systems i and j are not serious conflicts. This is used to evaluate the control target conflict situation of each weak electronic system during the fusion process.

5. The intelligent control method for an intelligent low-voltage system according to claim 1, characterized in that, The calculation yields the coordination optimization effectiveness coefficient of the overall weak current system after each weak current system has been optimized over a set time period. The specific calculation process is as follows: Based on the optimized coordination parameters of each low-voltage electronic system corresponding to the overall low-voltage electronic system after a set time period, the following calculation formula is used: The coordination optimization effectiveness coefficient β of each weak electronic system after optimization is obtained, where ZT1 q , These represent the optimized response time ratio, energy consumption reduction ratio, and operational stability improvement degree of the q-th weak electronic system after a set time period, respectively. q is the number of each severely conflicting weak electronic system, p = 1, 2, ..., p, p is the total number of severely conflicting weak electronic systems, and p is a positive integer. μ1, μ2, and μ3 are the set weight factors for the optimized response time ratio, energy consumption reduction ratio, and operational stability improvement degree, respectively.

6. The intelligent control method for an intelligent low-voltage system according to claim 5, characterized in that, The specific process for evaluating the optimization strategies of each severely conflicting electronically weak system is as follows: By monitoring the environmental information of each weak electronic system in a severely conflicting environment, the environmental parameters contained in the environmental information are denoted as EN. x Let x be the number of each environmental parameter, x = 1, 2, ..., y, and y be the total number of environmental parameters included in the environmental information. y is a positive integer, calculated using the formula: The environmental information adaptability index χ of the q-th weak electron system with severe conflict is obtained. q ,in and Let κ be the lowest and highest boundary values ​​of the x-th environmental parameter corresponding to the q-th severely conflicting electron-weak system. qx The weighting factor for the x-th environmental parameter corresponding to the q severely conflicting electronically weak systems; If χ q If the environmental information adaptability index falls below the preset minimum standard threshold, the intelligent coordination strategy is optimized and adjusted. This is achieved by monitoring the interactive data flow, synchronization event success rate, and collaborative task completion efficiency of each severely conflicting weak electronic system during operation, denoted as a. x b x and c x Then, the synergistic enhancement optimization index of the total weak electronic system corresponding to each severely conflicting weak electronic system is calculated. After the optimization time period is set according to the intelligent coordination strategy, the environmental information adaptability optimization index and the synergistic enhancement optimization index of each severely conflicting weak electronic system are calculated respectively. If both the environmental information adaptability optimization index and the collaborative enhancement optimization index are greater than 0, it indicates that the optimization and adjustment of the intelligent coordination strategy meets the requirements of low-voltage system optimization; otherwise, it indicates that the optimization and adjustment of the intelligent coordination strategy does not meet the requirements of low-voltage system optimization.

7. The intelligent control method for an intelligent low-voltage system according to claim 6, characterized in that, The calculation yields the synergistic enhancement optimization index of the total weak electronic system for each severely conflicting weak electronic system. The specific process is as follows: Calculation formula: The collaborative enhancement optimization index ξ of the total weak current system corresponding to each severely conflicting weak current system is obtained, where a′ and a″ are the initial interactive data flow and the maximum tolerable interactive data flow, respectively, and π1, π2, and π3 are the weight factors corresponding to the set interactive data flow, the weight factor corresponding to the synchronization event success rate, and the weight factor corresponding to the collaborative task completion efficiency, respectively.

8. The intelligent control method for an intelligent low-voltage system according to claim 7, characterized in that, The specific process for calculating the environmental information adaptive optimization index and the synergistic enhancement optimization index corresponding to each severely conflicting weak electronic system is as follows: Calculation formula: Obtain the environmental information adaptive optimization index Kχ corresponding to the q-th weak electronic system with severe conflict. q , where χ′ q Let T represent the environmental information adaptability index of the q-th severely conflicting weak electronic system after setting the optimization time period, and let T represent the set optimization time period. Based on this, the synergistic enhancement optimization index of the total weak electronic system corresponding to each severely conflicting weak electronic system is calculated.

9. An intelligent control system for a low-voltage system implementing the intelligent control method for an intelligent low-voltage system according to any one of claims 1-8, characterized in that, Includes the following modules: The collaborative control process evaluation module is used to integrate the various low-voltage electronic systems in the corresponding low-voltage electronic systems of a specified building, and then analyze the comprehensive impact index of the control target conflict of each low-voltage electronic system during the integration process. The weak electronic system conflict impact assessment module is used to assess the control objective conflict situation of each weak electronic system during the fusion process based on the comprehensive impact index of the control objective conflict of each weak electronic system during the fusion process. The preliminary analysis module for coordination and optimization is used to coordinate and optimize weak electronic systems with severe conflict of control objectives based on the system conflict situation of each weak electronic system during the fusion process. The conflict optimization strategy evaluation module is used to evaluate the optimization strategies for each severely conflicting weak electronic system when the results of coordinated optimization of each system do not meet the requirements of weak electronic system optimization.

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