A power control method and system for subway emergency lighting

Abstract

This invention discloses a power control method and system for subway emergency lighting. The method includes acquiring power status data and load demand data; dynamically analyzing the power status data to obtain dynamically updated results; based on the updated results and combined with the load demand data, performing a tiered assessment of regional power demand to obtain a load demand priority distribution; classifying the severity of emergency scenarios based on the priority distribution to obtain an urgency classification result; performing a matching degree analysis based on the classification result and priority distribution; if the matching degree is lower than a preset threshold, performing power switching to obtain a power supply scheme; dynamically adjusting the power supply lines according to the scheme to obtain a new power supply line configuration, and monitoring the remaining power of the emergency battery in real time; if the battery power is lower than a preset threshold, limiting the power supply ratio of non-critical areas to obtain a power usage strategy. This method can dynamically optimize the power switching strategy and the power supply priority of lighting circuits.

Description

Technical Field

[0001] This invention relates to the field of subway emergency lighting control technology, and in particular to a power control method and system for subway emergency lighting. Background Technology

[0002] Currently, the subway emergency lighting system is one of the core components to ensure the safety of subway operations. In the event of an emergency or power failure, its stable operation is directly related to the efficiency of passenger evacuation and the smooth progress of rescue work, and plays an irreplaceable role in maintaining the order of subway operations.

[0003] In existing technologies, subway emergency lighting power supply control often employs fixed switching logic or a single power management mode. This involves mechanically switching between normal lighting power, backup power, and emergency batteries based on preset trigger conditions, and allocating power to lighting loads in different areas according to fixed priorities. This approach cannot dynamically adjust strategies based on changes in the actual emergency scenario. However, these traditional methods have significant shortcomings when facing complex real-world emergency situations. They cannot dynamically adjust based on the severity of the emergency (such as the pressure of large passenger evacuation during peak hours) and actual load demands (such as the number of lights to be lit and their power consumption). Furthermore, existing technologies lack sufficient accuracy and response speed in monitoring power status (such as backup power capacity and battery health) under complex environments, leading to inaccurate predictions of the duration of the emergency. This lack of predictive capability makes it difficult for the system to achieve smooth and timely seamless switching between normal lighting power, backup power, and emergency batteries, and also prevents flexible dynamic adjustment of power supply priorities for lighting circuits in different areas (such as critical evacuation routes).

[0004] In summary, existing technologies have the problem of being unable to dynamically optimize power switching strategies and lighting circuit power supply priorities. Summary of the Invention

[0005] This invention provides a power control method and system for subway emergency lighting, to solve the problem that existing technologies cannot dynamically optimize power switching strategies and lighting circuit power supply priorities.

[0006] In a first aspect, to solve the above-mentioned technical problems, the present invention provides a power control method for subway emergency lighting, comprising: Real-time acquisition of power status data and load demand data of the subway emergency lighting system; dynamic analysis and processing of the power status data to obtain dynamic update results of the power status. Based on the dynamic update results and combined with the load demand data, the electricity demand in different regions is evaluated in a hierarchical manner to obtain the load demand priority distribution. Based on the load demand priority distribution, the severity of emergency scenarios is classified according to preset urgency classification rules to obtain urgency classification results; Based on the urgency classification results and the load demand priority distribution, a matching degree analysis is performed to obtain the matching degree between the emergency battery availability time and the load demand. If the matching degree is lower than the preset matching degree threshold, a power switching operation is performed to obtain the switched power supply scheme. Based on the power supply scheme, the power supply lines for critical and non-critical areas are dynamically adjusted to obtain the adjusted power supply line configuration. Based on the adjusted power supply line configuration, the remaining power of the emergency battery is monitored in real time. If the remaining power is lower than the preset safe remaining power threshold, the power supply ratio of non-critical areas is restricted to obtain an optimized power usage strategy.

[0007] Preferably, the real-time acquisition of power status data and load demand data of the subway emergency lighting system, and the dynamic analysis and processing of the power status data to obtain dynamic update results of the power status, includes: The voltage, current and temperature data of the subway emergency lighting system are collected in real time and transmitted to the real-time monitoring platform to obtain the raw dataset of operating parameters. Based on the original dataset of the operating parameters, the trend of the operating parameters is analyzed by a linear regression algorithm. If the operating parameters exceed the preset abnormal threshold, a fault detection mechanism is triggered to generate an abnormal state signal. The power switching logic is executed based on the abnormal state signal to obtain a dynamically updated result.

[0008] Preferably, the step of performing a tiered assessment of electricity demand in different regions based on the dynamic update results and the load demand data to obtain a load demand priority distribution includes: The load demand data is cleaned using time series analysis to obtain electricity demand records for each region. Based on the electricity demand records of each region, the priority of load demand in each region is calculated by weighted scoring to obtain the load demand priority distribution.

[0009] Preferably, the step of classifying the severity of emergency scenarios according to the load demand priority distribution and obtaining the urgency classification result by means of a preset urgency classification rule includes: Obtain the zoning data for the subway emergency lighting system; The load demand priority distribution is combined with the preset urgency classification rules to classify the load demand and obtain the initial urgency classification results. Based on the initial urgency classification results and combined with the regional division data, the scene classification of the regions is dynamically adjusted. If the urgency of a certain region exceeds the preset urgency threshold, it is marked as a key region, and the urgency classification results are obtained.

[0010] Preferably, the step of performing a matching degree analysis based on the urgency classification results and the load demand priority distribution to obtain the matching degree between the emergency battery availability time and the load demand includes: Obtain historical load demand data; The urgency classification results and the load demand priority distribution are compared over time to make a preliminary prediction of the power outage duration in each region. Based on the duration of power outage in each area and the area division data, the available time of the emergency battery is calculated to obtain the available time of the emergency battery. Determine the degree of matching between the available time of the emergency battery and the historical load demand data to obtain a preliminary estimate of the matching degree; If the preliminary matching degree estimate is lower than the preset matching degree threshold, the latest fluctuation record data is monitored in real time, and the matching degree of the load demand priority distribution is evaluated to obtain the matching degree between the emergency battery availability time and the load demand.

[0011] Preferably, the step of dynamically adjusting the power supply lines for critical and non-critical areas according to the power supply scheme to obtain the adjusted power supply line configuration includes: According to the power supply scheme, the power supply lines for critical and non-critical areas are initially divided using a lighting circuit distribution method to obtain a preliminary power supply line configuration. If the power supply line allocation ratio of the key area in the initial power supply line configuration is lower than the preset allocation ratio threshold, then the backup power supply resources will be connected first to obtain the adjusted power allocation result. Based on the adjusted power allocation results, the initial power supply line configuration is dynamically adjusted, and the backup power resources are allocated preferentially to key areas to determine the final power supply line configuration.

[0012] Preferably, the step of monitoring the remaining power of the emergency battery in real time according to the adjusted power supply line configuration, and limiting the power supply ratio of non-critical areas if the remaining power is lower than the safe remaining power threshold, to obtain an optimized power usage strategy, includes: The remaining power of the emergency battery and the current load of the power supply line are obtained in real time to obtain a battery status dataset; If the remaining power in the battery status dataset is lower than the preset safe remaining power threshold, the power supply priority of non-critical areas is sorted to determine the power supply ratio that needs to be restricted. Based on the power supply ratio, the output ratio of the power supply line is dynamically adjusted to generate a set of restriction instructions for non-critical areas. Based on the restriction instruction set for the non-critical areas, the power output of the non-critical areas is reduced to obtain an optimized power distribution scheme.

[0013] Secondly, the present invention provides a power control system for subway emergency lighting, comprising: The data acquisition module is used to acquire the power status data and load demand data of the subway emergency lighting system in real time, and to perform dynamic analysis and processing on the power status data to obtain the dynamic update results of the power status. The load analysis module is used to perform hierarchical evaluation of electricity demand in different areas based on the dynamic update results and the load demand data, and obtain the load demand priority distribution. The emergency prediction module is used to classify the severity of emergency scenarios according to the priority distribution of load demand and a preset urgency classification rule to obtain the urgency classification result. The duration assessment module is used to perform a matching degree analysis based on the urgency classification results and the load demand priority distribution to obtain the matching degree between the emergency battery availability duration and the load demand. A switching control module is used to perform a power switching operation if the matching degree is lower than a preset matching degree threshold, so as to obtain a switched power supply scheme. The power supply adjustment module is used to dynamically adjust the power supply lines of critical and non-critical areas according to the power supply scheme to obtain the adjusted power supply line configuration. The power optimization module is used to monitor the remaining power of the emergency battery in real time according to the adjusted power supply line configuration. If the remaining power is lower than the preset safe remaining power threshold, the power supply ratio of non-critical areas is restricted to obtain an optimized power usage strategy.

[0014] Thirdly, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement a power control method for subway emergency lighting as described in any one of the above.

[0015] Fourthly, the present invention also provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform a power control method for subway emergency lighting as described in any one of the above.

[0016] Compared with the prior art, the present invention has the following beneficial effects: (1) This invention acquires power status data in real time and performs dynamic analysis and processing to analyze the trend of operating parameters. It can trigger the fault detection mechanism in a timely manner and generate abnormal status signals, and then execute the power switching logic to obtain dynamic update results. This process can keep track of power status changes in real time, respond quickly to power abnormalities, and ensure that a reaction can be made as soon as possible when power problems occur. It provides an accurate basis for subsequent power control strategy adjustments and improves the timeliness and accuracy of emergency lighting systems in dealing with power failures.

[0017] (2) Based on the dynamic update results and load demand data, this invention performs a tiered assessment of power demand in different areas, calculates the priority distribution of load demand through weighted scoring, and then classifies the severity of emergency scenarios and marks key areas based on preset rules. This breaks through the fixed priority allocation mode in the prior art, and can dynamically determine the power supply priority of each area according to the actual load demand and emergency scenario, so that key areas are given priority protection in emergency situations, improve the pertinence and effectiveness of emergency lighting power supply, and ensure the smooth progress of passenger evacuation and rescue work.

[0018] (3) This invention determines the matching degree between the available time of the emergency battery and the load demand through matching degree analysis. When the matching degree is lower than the threshold, the power supply is switched. It can also dynamically adjust the power supply line configuration according to the power supply plan and limit the power supply ratio of non-critical areas when the remaining power of the emergency battery is lower than the threshold. This series of operations realizes the dynamic optimization of the power switching strategy and the power supply line configuration, solving the problem of inflexible adjustment in the prior art. It can switch the power supply in time when the power is insufficient, and can rationally allocate power resources to ensure that the power of the emergency battery is used efficiently at critical moments, extend the lighting time of critical areas, and further improve the reliability and adaptability of the subway emergency lighting system.

[0019] (4) This invention can quickly respond to changes in power status and fluctuations in load demand through real-time data acquisition and dynamic analysis, and promptly switch power and adjust resources to reduce power switching delays, improve the response efficiency of the emergency lighting system, make the emergency lighting system control more intelligent and flexible, and better adapt to complex and ever-changing emergency scenarios. Attached Figure Description

[0020] Figure 1 This is a schematic flowchart of a power control method for subway emergency lighting provided in the first embodiment of the present invention; Figure 2 This is a schematic diagram of a power control device for subway emergency lighting provided in the second embodiment of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Reference Figure 1 The first embodiment of the present invention provides a power control method for emergency lighting in subways, comprising the following steps: S11, real-time acquisition of power status data and load demand data of the subway emergency lighting system, dynamic analysis and processing of the power status data to obtain dynamic update results of the power status; S12, Based on the dynamic update results and combined with the load demand data, the electricity demand in different regions is evaluated in a hierarchical manner to obtain the load demand priority distribution. S13, Based on the load demand priority distribution, the severity of the emergency scenario is classified according to the preset urgency classification rules to obtain the urgency classification result; S14. Based on the urgency classification results and the load demand priority distribution, a matching degree analysis is performed to obtain the matching degree between the emergency battery availability time and the load demand. S15, If the matching degree is lower than the preset matching degree threshold, a power switching operation is performed to obtain the switched power supply scheme. S16, According to the power supply scheme, the power supply lines of critical areas and non-critical areas are dynamically adjusted to obtain the adjusted power supply line configuration. S17. Based on the adjusted power supply line configuration, monitor the remaining power of the emergency battery in real time. If the remaining power is lower than the preset safe remaining power threshold, limit the power supply ratio of non-critical areas to obtain an optimized power usage strategy.

[0023] In step S11, the power status data of the subway emergency lighting system and the load demand data of the lighting circuit are acquired in real time. The power status data is dynamically analyzed and processed to obtain the dynamic update result of the power status.

[0024] In one feasible approach, the real-time acquisition of power status data and load demand data of the subway emergency lighting system, and the dynamic analysis and processing of the power status data to obtain a dynamic update result of the power status, includes: The voltage, current and temperature data of the subway emergency lighting system are collected in real time and transmitted to the real-time monitoring platform to obtain the raw dataset of operating parameters. Based on the original dataset of the operating parameters, the trend of the operating parameters is analyzed by a linear regression algorithm. If the operating parameters exceed the preset abnormal threshold, a fault detection mechanism is triggered to generate an abnormal state signal. The power switching logic is executed based on the abnormal state signal to obtain a dynamically updated result.

[0025] It should be noted that the power supply includes normal lighting power, backup power, and emergency batteries. The load demand data for lighting circuits is a set of parameters reflecting the power consumption and fluctuation characteristics of lighting equipment in various areas of the subway, including real-time power, load fluctuation trends, and total regional power consumption. Power status data is a set of key parameters reflecting the operating status of various power supplies in the subway emergency lighting system, including operating parameters such as voltage, current, and temperature. It is mainly used to assess the stability, load capacity, and safety of the power supply. Voltage parameters reflect the stability of the power supply's output, current parameters reflect the load condition, and temperature parameters are related to the safe operation of the power equipment; excessively high temperatures may indicate potential equipment malfunctions. By deploying a sensor network at these key power supply nodes—a collaborative acquisition network composed of multiple sensors distributed at different power supply locations—data can be collected continuously. The sensors collect data very frequently, typically once per second, to ensure that every subtle change in the power supply status is captured, providing comprehensive and timely data support for subsequent analysis and processing. These parameters are encrypted using a data transmission protocol and sent to the real-time monitoring platform to form the raw dataset. The platform uses a linear regression algorithm to predict parameter trends from the data and initiates a fault detection mechanism. When the normal lighting power supply voltage drops to 160V, below the threshold of 180V, the system generates an abnormal status signal, marking it as a fault state. This helps to quickly locate the problem and reduce the scope of the fault's impact. After determining the fault location, the system automatically switches to the backup power supply within one second to ensure uninterrupted lighting. After switching, the system collects backup power supply status data; if the voltage stabilizes at 220V, the switch is confirmed as successful. This ensures power supply continuity and improves system reliability.

[0026] In step S12, based on the dynamic update results and combined with the load demand data, the electricity demand in different regions is evaluated in a hierarchical manner to obtain the load demand priority distribution.

[0027] In one feasible approach, the step of performing a tiered assessment of electricity demand in different regions based on the dynamic update results and the load demand data to obtain a load demand priority distribution includes: The load demand data is cleaned using time series analysis to obtain electricity demand records for each region. Based on the electricity demand records of each region, the priority of load demand in each region is calculated by weighted scoring to obtain the load demand priority distribution.

[0028] It should be noted that load demand refers to the amount of electricity consumed by lighting equipment in different areas. Layered assessment divides electricity demand into different levels based on factors such as area importance and passenger flow, ultimately forming a load demand priority distribution, i.e., the arrangement of areas according to their electricity demand priority from high to low. Specifically, time series analysis is first used to clean the load demand data. During the cleaning process, for those sudden increases in current values ​​caused by instantaneous equipment interference, the system will remove these outliers through smoothing and other methods, retaining only data within the normal fluctuation range. This process results in more accurate and reliable electricity demand records for each area. The records are then categorized according to area division (e.g., platforms, passageways, control rooms), and priorities are calculated using weighted scoring methods. The weight for platforms is set at 0.6, control rooms at 0.3, and passageways at 0.1. Platforms have a higher weight and the highest priority due to high passenger flow and passenger safety concerns; while some equipment rooms or secondary passageways have relatively lower priorities. When the load fluctuation in a certain area exceeds the preset threshold, the system will dynamically adjust the power state to optimize the loop load distribution, and at the same time combine historical data to predict future load changes, providing forward-looking support for resource scheduling.

[0029] It should be noted that load demand may change in actual situations. When a secondary channel needs to be used as an evacuation channel due to a temporary situation, its load demand priority will be temporarily increased, and the system will adjust the power allocation accordingly.

[0030] In step S13, the severity of the emergency scenario is classified according to the load demand priority distribution and a preset urgency classification rule to obtain the urgency classification result.

[0031] In one feasible approach, the step of classifying the severity of emergency scenarios according to the load demand priority distribution and using preset urgency classification rules to obtain urgency classification results includes: Obtain the zoning data for the subway emergency lighting system; The load demand priority distribution is combined with the preset urgency classification rules to classify the load demand and obtain the initial urgency classification results. Based on the initial urgency classification results and combined with the regional division data, the scene classification of the regions is dynamically adjusted. If the urgency of a certain region exceeds the preset urgency threshold, it is marked as a key region, and the urgency classification results are obtained.

[0032] Obtaining zoning data for the subway emergency lighting system is a prerequisite for urgency classification. This zoning data defines in detail the scope, function, and boundaries of each area within the subway station, providing clear objects for subsequent classification. After obtaining the load demand priority distribution, the system performs preliminary classification based on preset urgency classification rules, yielding initial urgency classification results. These urgency classification rules are developed based on numerous real-world cases and safety standards, comprehensively considering factors such as peak load, functional attributes, and the number of potentially affected individuals. For example, areas with high peak load, large passenger flow, and critical evacuation routes are assigned higher urgency weights in the classification rules. By comparing and calculating the load demand priority distribution against these rules, the system can preliminarily determine the urgency level of each area, such as high, medium, or low.

[0033] It's important to note that the initial classification results are not static. The system dynamically adjusts the scenario classification of regions based on the initial urgency classification results and regional segmentation data. This is because in actual emergency scenarios, the situation in each region may change over time. For example, a passageway area that was initially classified as having a medium urgency level might experience a sudden equipment failure leading to passenger congestion, causing its urgency level to rise rapidly. The system monitors these changes in real time and dynamically adjusts the scenario classification of regions. When the urgency level of a region exceeds a preset urgency threshold, the system marks it as a critical region. The urgency threshold is set based on the minimum requirements for ensuring personnel safety and emergency response. Once the urgency level of a region exceeds this threshold, it means that the region needs the highest priority for attention and resource support. For example, if the load on a platform area consistently exceeds the set threshold during peak hours and the personnel density is too high, the system will mark it as a critical region and determine the distribution range of high-urgency scenarios, such as the entire waiting area and boarding / alighting passageways of the platform.

[0034] In step S14, a matching degree analysis is performed based on the urgency classification results and the load demand priority distribution to obtain the matching degree between the emergency battery availability time and the load demand.

[0035] In one feasible approach, the matching degree analysis based on the urgency classification results and the load demand priority distribution to obtain the matching degree between the emergency battery availability time and the load demand includes: Obtain historical load demand data; The urgency classification results and the load demand priority distribution are compared over time to make a preliminary prediction of the power outage duration in each region. Based on the duration of power outage in each area and the area division data, the available time of the emergency battery is calculated to obtain the available time of the emergency battery. Determine the degree of matching between the available time of the emergency battery and the historical load demand data to obtain a preliminary estimate of the matching degree; If the preliminary matching degree estimate is lower than the preset matching degree threshold, the latest fluctuation record data is monitored in real time, and the matching degree of the load demand priority distribution is evaluated to obtain the matching degree between the emergency battery availability time and the load demand.

[0036] It should be noted that historical load demand data is extracted from historical datasets. Matching degree refers to the extent to which the available duration of emergency batteries can meet the load demand of a certain area. During the analysis, historical load demand data—that is, the electricity consumption of each area over a past period—is referenced to more accurately predict current demand. After obtaining historical load demand data, the system performs time-series comparison processing on the urgency classification results and load demand priority distribution to initially predict the duration of power outages in each area. The system extracts all load time series data for "off-peak hours + low urgency + level 1 priority" from historical data, finding that the power outage duration for these scenarios is concentrated between 1.2 and 1.5 hours, with an average of 1.35 hours. Comparing the current load demand with historical data: the current station load peak is 5% higher than the historical average, therefore the predicted duration is corrected to 1.35 × 1.05 ≈ 1.42 hours. The final predicted power outage duration for this area is approximately 1.42 hours. If the available duration of the emergency batteries is greater than or equal to the load demand within the predicted power outage duration based on historical load demand data, the matching degree is high; otherwise, the matching degree is low. If the assessment shows that an area needs continuous lighting for 5 hours in an emergency, and the emergency battery in that area has a usable time of 6 hours, then the match is relatively high; if the emergency battery has a usable time of only 3 hours, then the match is relatively low, and the support of other power sources needs to be considered.

[0037] In step S15, if the matching degree is lower than the preset matching degree threshold, a power switching operation is performed to obtain the switched power supply scheme.

[0038] It should be noted that power switching operation refers to seamless power switching, meaning that the lighting will not be interrupted or flickering during the switching process, ensuring continuous illumination. A preset matching threshold is the standard for determining whether a switch is necessary. The threshold may vary in different areas, with higher thresholds for critical areas, and is set based on historical power supply data. Specifically, when the matching degree of a critical area falls below the threshold, the system will automatically activate the backup power supply while simultaneously disconnecting the original power supply. The entire process is completed in a very short time. For example, if the emergency battery matching degree in a platform area falls below the threshold, the system will quickly connect the backup power supply. During the switching process, passengers will not perceive any change in lighting, ensuring that the evacuation process is not affected.

[0039] In step S16, the power supply lines for critical and non-critical areas are dynamically adjusted according to the power supply scheme to obtain the adjusted power supply line configuration.

[0040] In one feasible approach, the dynamic adjustment of power supply lines for critical and non-critical areas according to the power supply scheme to obtain an adjusted power supply line configuration includes: According to the power supply scheme, the power supply lines for critical and non-critical areas are initially divided using a lighting circuit distribution method to obtain a preliminary power supply line configuration. If the power supply line allocation ratio of the key area in the initial power supply line configuration is lower than the preset allocation ratio threshold, then the backup power supply resources will be connected first to obtain the adjusted power allocation result. Based on the adjusted power allocation results, the initial power supply line configuration is dynamically adjusted, and the backup power resources are allocated preferentially to key areas to determine the final power supply line configuration.

[0041] It should be noted that power supply line configuration includes the connection method and quantity of lines. Dynamic adjustment means changing the line configuration in real time according to changes in power supply and load demand. Critical areas, due to their high importance, are allocated more power supply line resources during the initial allocation to ensure sufficient power supply; non-critical areas are allocated relatively fewer line resources. When power supply is tight, the number of power supply lines in non-critical areas will be reduced, and more power will be delivered to critical areas; when power is sufficient, the line configuration of non-critical areas will be restored. If a power supply line in a critical area fails, the system will automatically switch to a backup line to ensure uninterrupted power supply. The backup line is connected to compensate for the insufficient power supply lines in critical areas, ensuring that they receive sufficient power support. When connecting a backup power source, the system will first check the status of the normal lighting power supply. If the normal lighting power supply cannot provide sufficient power due to a failure, the backup power supply will be quickly connected to the power supply line in the critical area. For example, when a fault is detected in the normal lighting power supply, causing the power distribution ratio in the platform area to be only 60%, below the preset threshold of 70%, the system will immediately activate the backup power supply and connect it to the power supply lines in the platform area to increase the power distribution ratio in that area. This results in an adjusted power distribution, ensuring that the power supply lines can meet current needs while dynamically adapting to changes in emergency scenarios, achieving optimal resource allocation. Finally, the power supply line configuration is dynamically optimized based on the adjusted power distribution results: for critical areas of the platform, backup power resources are prioritized to ensure lighting stability (e.g., maintaining support for more than 5 hours); simultaneously, based on real-time load fluctuations (e.g., a sudden increase in load to 40A in the passageway area), the proportion of power supply in non-critical areas is dynamically fine-tuned (e.g., increasing the power supply ratio in the passageway area from 25% to 30%, and decreasing it in the exit area from 10% to 5%). For example, during the evening peak hours, if the system predicts that the platform load will increase to 1000W, more line resources are reserved in advance, ultimately determining a power supply line configuration of 75% for the platform, 20% for the passageway, and 5% for the exit, achieving a balance between power supply assurance for critical areas and basic needs for non-critical areas.

[0042] In step S17, based on the adjusted power supply line configuration, the remaining power of the emergency battery is monitored in real time. If the remaining power is lower than the preset safe remaining power threshold, the power supply ratio of non-critical areas is restricted to obtain an optimized power usage strategy.

[0043] In one feasible approach, the remaining power of the emergency battery is monitored in real time based on the adjusted power supply line configuration. If the remaining power is lower than a safe remaining power threshold, the power supply ratio to non-critical areas is limited to obtain an optimized power usage strategy, including: The remaining power of the emergency battery and the current load of the power supply line are obtained in real time to obtain a battery status dataset; If the remaining power in the battery status dataset is lower than the preset safe remaining power threshold, the power supply priority of non-critical areas is sorted to determine the power supply ratio that needs to be restricted. Based on the power supply ratio, the output ratio of the power supply line is dynamically adjusted to generate a set of restriction instructions for non-critical areas. Based on the restriction instruction set for the non-critical areas, the power output of the non-critical areas is reduced to obtain an optimized power distribution scheme.

[0044] It's important to note that the battery status dataset is generated by integrating and standardizing scattered power and load information. The system verifies and corrects the collected data, removing outliers and interference signals to ensure accuracy and reliability. Simultaneously, a timestamp and region identifier are added to each data entry to facilitate time-series analysis and inter-regional comparisons. In this way, the battery status dataset accurately reflects the operational status of emergency batteries and the load conditions in each region, providing strong support for dynamically adjusting power supply strategies. The safe remaining power threshold is set based on factors such as the minimum requirements for emergency lighting, battery discharge characteristics, and the potential duration of the emergency. Its purpose is to ensure that emergency batteries retain sufficient power to cope with sudden and more severe emergencies. When the remaining power in the battery status dataset falls below the preset safe remaining power threshold, the system activates the corresponding adjustment mechanism. For example, if the safe remaining power threshold is set to 40%, the system's adjustment mechanism will be triggered when the remaining power of the emergency battery drops to 30%. At this point, the system prioritizes the power supply to non-critical areas, taking into account factors such as the functional importance of these areas, current load levels, and their impact on passenger evacuation. Based on this prioritization, the system determines the required power supply ratio to be restricted. In determining the power supply ratio, the system references historical load demand data to analyze the operation of these areas under low power supply ratios, ensuring that the restricted power supply meets their most basic functional needs while maximizing energy savings.

[0045] For example, the generation of the non-critical area restriction instruction set is achieved through the following specific process: First, a weight coefficient is preset based on the area's functional attributes (0.7 for evacuation routes, 0.3 for equipment rooms, and 0.1 for advertising areas), and the restriction ratio is dynamically calculated in conjunction with the real-time battery power shortage. For example, when a power shortage of 5kWh is detected, a 70% restriction ratio is applied to the lowest priority advertising area (calculated as Min(70%, 5 / 6×1.5)), 40% to the medium priority equipment room (Min(40%, 5 / 8×1.2)), and 10% to the higher priority evacuation route (Min(10%, 5 / 12)). Then, the restriction ratio is converted into equipment-level control parameters: the advertising area implements a 18% voltage reduction, shuts down 50% of the lighting circuits, and enables an intermittent power supply mode of 30 seconds on / 90 seconds off; the equipment room voltage is reduced by 10%, shuts down 30% of the circuits, and adopts a 60-second on / 60-second off cycle; the evacuation route only has a 5% voltage adjustment and maintains continuous power supply. After the instruction is generated, a pre-verification mechanism ensures that the expected energy saving reaches more than 90% of the power shortage. If the initial plan saves 4.3 kWh (with a shortage of 5 kWh), then 20% of the decorative lighting in the advertising area will be turned off, increasing the total energy saving to 5.1 kWh. During instruction execution, the slope of the battery discharge curve is monitored every 30 seconds. When the slope exceeds the threshold of -0.5 kWh / min, the restrictions are dynamically upgraded (e.g., the duty cycle of the advertising area is tightened to 15 seconds on / 105 seconds off) until the discharge rate returns to a safe range.

[0046] It should be noted that the restriction command set includes specific adjustment parameters, such as reducing the lighting brightness of a non-critical area by 50% or turning off some unnecessary lighting fixtures. These commands are formatted so that the power supply line controller can accurately identify and execute them. After receiving the restriction command set, the power supply line controller will perform the corresponding operations according to the command requirements, adjusting the power output of non-critical areas. For example, for the exit area, the controller will turn off some lighting fixtures according to the command, reducing the load of that area from 150W to 80W; for the equipment room, it will reduce the lighting brightness to appropriately reduce its load. Through these operations, the power supply to non-critical areas is effectively restricted, and the saved power is redistributed to critical areas, such as the platform area, to ensure that its load remains stable at a normal level and to ensure the safe evacuation of passengers. The optimized power distribution scheme not only extends the use time of emergency batteries but also achieves reasonable distribution of lighting in various areas with limited power. By restricting the power supply to non-critical areas and concentrating more power on critical areas, it ensures that the emergency lighting system can still play its maximum role when the battery power is low.

[0047] To facilitate understanding of the present invention, some preferred embodiments of the present invention will be described in further detail below.

[0048] In this embodiment, the power supply control system for subway emergency lighting involves a comprehensive control method comprising data acquisition, load analysis, emergency prediction, duration assessment, switching control, power supply adjustment, and power optimization. This system aims to monitor the power supply status of lighting in various areas of the subway in real time, dynamically allocate power resources, and ensure stable lighting during emergency scenarios.

[0049] When the subway is operating normally during the morning rush hour and a large-scale power outage suddenly occurs, the system will respond according to the following steps: Step 1: The sensor network distributed across the normal lighting power supply, backup power supply, and emergency batteries immediately detects the power outage signal and transmits the abnormal status to the monitoring platform in real time via an encrypted transmission protocol. The platform quickly displays "Normal power outage, initiate emergency response" and simultaneously updates the real-time status of each power node.

[0050] Step Two: The load analysis module automatically stratifies the power demand of each area. Platforms, due to the large number of waiting passengers, have the highest priority for lighting loads; transfer passages, serving as evacuation routes, have the next highest priority; equipment rooms and warehouses have the lowest priority. Simultaneously, secondary passages temporarily used as evacuation routes are identified, and their load demand priority is temporarily increased.

[0051] Step 3: The emergency prediction module, based on passenger flow density data, determines that the platform is a "high-urgency area" and marks it as a critical area; the transfer passage is classified as "medium-urgency area." The system automatically triggers a resource allocation mechanism, prioritizing 70% of the platform's power supply.

[0052] Step 4: The duration assessment module compares historical power outage data and predicts that the power outage may last 1.5 hours. Calculations show that the platform's emergency battery can be used for 2 hours (matching degree 133%), and the passage can be used for 1 hour (matching degree 67%), triggering the passage's backup power supply replenishment.

[0053] Step 5: Due to insufficient matching in the passage area, the seamless switching control module initiates the "connect first, disconnect later" logic, and completes the backup power connection within 0.5 seconds. During the process, the lighting does not flicker and passengers are unaware of the power switch.

[0054] Step Six: The lighting circuit distribution module detects that the platform's wiring ratio is only 60%, and automatically transfers 20% of the wiring capacity from the equipment room to the platform to ensure that the wiring quota in critical areas meets the standards. At the same time, the backup lines of the temporary evacuation passages are activated to improve their power supply reliability.

[0055] Step 7: After 1 hour, the battery level drops to 35% (safe threshold 40%). The system implements tiered restrictions on non-critical areas: 50% of the lighting in equipment rooms is turned off, and only emergency indicator lights remain in the exit area; the released power is prioritized for the platform and evacuation routes, extending their lighting duration.

[0056] Through the above steps, the entire process from fault occurrence to recovery is fully presented, demonstrating the collaborative capabilities of this invention in complex scenarios: by sensing the power status in real time, dynamically adjusting load priorities, and intelligently allocating power resources, passenger evacuation safety is ensured while avoiding waste of emergency resources, fully verifying the practicality and reliability of the technical solution.

[0057] In summary, this invention, by acquiring and dynamically analyzing power status data in real time, can promptly trigger fault detection and power switching, ensuring rapid response to power anomalies and providing accurate basis for adjusting control strategies. Simultaneously, based on dynamically updated results and load demand data, hierarchical evaluation and weighted scoring are performed to dynamically determine the power supply priority of each area, breaking through fixed allocation patterns and prioritizing critical areas, thus improving the targeting and effectiveness of power supply. Furthermore, through matching degree analysis, power switching strategies and power line configurations are dynamically optimized, restricting power supply to non-critical areas when power is insufficient, ensuring efficient use of emergency batteries and extending critical lighting time. Ultimately, the synergistic effect of the aforementioned real-time data acquisition, dynamic analysis, priority allocation, and resource optimization mechanisms significantly improves system response efficiency, reduces switching lag, and makes emergency lighting control more intelligent and flexible, greatly enhancing the system's reliability, adaptability, and overall performance in complex and changing emergency scenarios.

[0058] Reference Figure 2 The second embodiment of the present invention provides a power control system for subway emergency lighting, comprising: The data acquisition module is used to acquire the power status data and load demand data of the subway emergency lighting system in real time, and to perform dynamic analysis and processing on the power status data to obtain the dynamic update results of the power status. The load analysis module is used to perform hierarchical evaluation of electricity demand in different areas based on the dynamic update results and the load demand data, and obtain the load demand priority distribution. The emergency prediction module is used to classify the severity of emergency scenarios according to the priority distribution of load demand and a preset urgency classification rule to obtain the urgency classification result. The duration assessment module is used to perform a matching degree analysis based on the urgency classification results and the load demand priority distribution to obtain the matching degree between the emergency battery availability duration and the load demand. A switching control module is used to perform a power switching operation if the matching degree is lower than a preset matching degree threshold, so as to obtain a switched power supply scheme. The power supply adjustment module is used to dynamically adjust the power supply lines of critical and non-critical areas according to the power supply scheme to obtain the adjusted power supply line configuration. The power optimization module is used to monitor the remaining power of the emergency battery in real time according to the adjusted power supply line configuration. If the remaining power is lower than the preset safe remaining power threshold, the power supply ratio of non-critical areas is restricted to obtain an optimized power usage strategy.

[0059] It should be noted that the power control system for subway emergency lighting provided in this embodiment of the invention is used to execute all the process steps of the power control method for subway emergency lighting in the above embodiment. The working principle and beneficial effects of the two are one-to-one, so they will not be described again.

[0060] This invention also provides an electronic device. The electronic device includes a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a power control program for subway emergency lighting. When the processor executes the computer program, it implements the steps described in the various embodiments of the power control method for subway emergency lighting, for example... Figure 1 The step S11 shown. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the above-described device embodiments, such as the data acquisition module.

[0061] For example, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device.

[0062] The electronic device may be a desktop computer, laptop, handheld computer, or smart tablet, etc. The electronic device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. It may include more or fewer components than described above, or combine certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0063] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the electronic device, connecting all parts of the electronic device via various interfaces and lines.

[0064] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0065] Wherein, if the modules / units integrated in the electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0066] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0067] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A power supply control method for subway emergency lighting, characterized in that, include: Real-time acquisition of power status data and load demand data of the subway emergency lighting system; dynamic analysis and processing of the power status data to obtain dynamic update results of the power status. Based on the dynamic update results and combined with the load demand data, the electricity demand in different regions is evaluated in a hierarchical manner to obtain the load demand priority distribution. Based on the load demand priority distribution, the severity of emergency scenarios is classified according to preset urgency classification rules to obtain urgency classification results; Based on the urgency classification results and the load demand priority distribution, a matching degree analysis is performed to obtain the matching degree between the emergency battery availability time and the load demand. If the matching degree is lower than the preset matching degree threshold, a power switching operation is performed to obtain the switched power supply scheme. Based on the power supply scheme, the power supply lines for critical and non-critical areas are dynamically adjusted to obtain the adjusted power supply line configuration. Based on the adjusted power supply line configuration, the remaining power of the emergency battery is monitored in real time. If the remaining power is lower than the preset safe remaining power threshold, the power supply ratio of non-critical areas is restricted to obtain an optimized power usage strategy.

2. The power supply control method for subway emergency lighting according to claim 1, characterized in that, The process involves acquiring real-time power status data and load demand data for the subway emergency lighting system, dynamically analyzing and processing the power status data to obtain dynamic update results of the power status, including: The voltage, current and temperature data of the subway emergency lighting system are collected in real time and transmitted to the real-time monitoring platform to obtain the raw dataset of operating parameters. Based on the original dataset of the operating parameters, the trend of the operating parameters is analyzed by a linear regression algorithm. If the operating parameters exceed the preset abnormal threshold, a fault detection mechanism is triggered to generate an abnormal state signal. The power switching logic is executed based on the abnormal state signal to obtain a dynamically updated result.

3. The power supply control method for subway emergency lighting according to claim 1, characterized in that, The step of evaluating electricity demand in different regions in a tiered manner based on the dynamic update results and the load demand data to obtain a load demand priority distribution includes: The load demand data is cleaned using time series analysis to obtain electricity demand records for each region. Based on the electricity demand records of each region, the priority of load demand in each region is calculated by weighted scoring to obtain the load demand priority distribution.

4. The power supply control method for subway emergency lighting according to claim 1, characterized in that, The step of classifying the severity of emergency scenarios according to the load demand priority distribution and using preset urgency classification rules to obtain urgency classification results includes: Obtain the zoning data for the subway emergency lighting system; The load demand priority distribution is combined with the preset urgency classification rules to classify the load demand and obtain the initial urgency classification results. Based on the initial urgency classification results and combined with the regional division data, the scene classification of the regions is dynamically adjusted. If the urgency of a certain region exceeds the preset urgency threshold, it is marked as a key region, and the urgency classification results are obtained.

5. A power control method for subway emergency lighting according to claim 4, characterized in that, The matching degree analysis, based on the urgency classification results and the load demand priority distribution, is performed to obtain the matching degree between the emergency battery availability time and the load demand, including: Obtain historical load demand data; The urgency classification results and the load demand priority distribution are compared over time to make a preliminary prediction of the power outage duration in each region. Based on the duration of power outage in each area and the area division data, the available time of the emergency battery is calculated to obtain the available time of the emergency battery. Determine the degree of matching between the available time of the emergency battery and the historical load demand data to obtain a preliminary estimate of the matching degree; If the preliminary matching degree estimate is lower than the preset matching degree threshold, the latest fluctuation record data is monitored in real time, and the matching degree of the load demand priority distribution is evaluated to obtain the matching degree between the emergency battery availability time and the load demand.

6. A power supply control method for subway emergency lighting according to claim 1, characterized in that, The step of dynamically adjusting the power supply lines for critical and non-critical areas according to the power supply scheme to obtain the adjusted power supply line configuration includes: According to the power supply scheme, the power supply lines for critical and non-critical areas are initially divided using a lighting circuit distribution method to obtain a preliminary power supply line configuration. If the power supply line allocation ratio of the key area in the initial power supply line configuration is lower than the preset allocation ratio threshold, then the backup power supply resources will be connected first to obtain the adjusted power allocation result. Based on the adjusted power allocation results, the initial power supply line configuration is dynamically adjusted, and the backup power resources are allocated preferentially to key areas to determine the final power supply line configuration.

7. A power control method for subway emergency lighting according to claim 1, characterized in that, The process involves real-time monitoring of the remaining emergency battery power based on the adjusted power supply line configuration. If the remaining power falls below a safe remaining power threshold, the power supply ratio to non-critical areas is limited, resulting in an optimized power usage strategy, including: The remaining power of the emergency battery and the current load of the power supply line are obtained in real time to obtain a battery status dataset; If the remaining power in the battery status dataset is lower than the preset safe remaining power threshold, the power supply priority of non-critical areas is sorted to determine the power supply ratio that needs to be restricted. Based on the power supply ratio, the output ratio of the power supply line is dynamically adjusted to generate a set of restriction instructions for non-critical areas. Based on the restriction instruction set for the non-critical areas, the power output of the non-critical areas is reduced to obtain an optimized power distribution scheme.

8. A power control system for subway emergency lighting, characterized in that, include: The data acquisition module is used to acquire the power status data and load demand data of the subway emergency lighting system in real time, and to perform dynamic analysis and processing on the power status data to obtain the dynamic update results of the power status. The load analysis module is used to perform hierarchical evaluation of electricity demand in different areas based on the dynamic update results and the load demand data, and obtain the load demand priority distribution. The emergency prediction module is used to classify the severity of emergency scenarios according to the priority distribution of load demand and a preset urgency classification rule to obtain the urgency classification result. The duration assessment module is used to perform a matching degree analysis based on the urgency classification results and the load demand priority distribution to obtain the matching degree between the emergency battery availability duration and the load demand. A switching control module is used to perform a power switching operation if the matching degree is lower than a preset matching degree threshold, so as to obtain a switched power supply scheme. The power supply adjustment module is used to dynamically adjust the power supply lines of critical and non-critical areas according to the power supply scheme to obtain the adjusted power supply line configuration. The power optimization module is used to monitor the remaining power of the emergency battery in real time according to the adjusted power supply line configuration. If the remaining power is lower than the preset safe remaining power threshold, the power supply ratio of non-critical areas is restricted to obtain an optimized power usage strategy.

9. An electronic device, characterized in that, The device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements a power control method for subway emergency lighting as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform a power control method for subway emergency lighting as described in any one of claims 1 to 7.

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