A communication master control system based on intelligent power supply

Abstract

This invention provides a communication master control system based on intelligent power supply, relating to the field of communication technology. It includes: a power supply monitoring module for monitoring the mains power supply status of the communication base station; when a mains power interruption is detected, it automatically controls the power switching circuit to switch the power supply mode to backup battery power supply mode; a status acquisition module for real-time acquisition of the backup battery's state of charge, discharge efficiency, and health status data in backup battery power supply mode, obtaining the battery's remaining capacity, actual discharge capacity, and lifespan indicators; and a load receiving module for uploading the battery's remaining capacity, actual discharge capacity, and lifespan indicators to the communication master control unit, while simultaneously receiving load data from the current communication network. This invention achieves intelligent power scheduling, improving the reliability and stability of the communication system's power supply.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a communication master control system based on intelligent power supply. Background Technology

[0002] In the communication control of smart power supply, traditional technologies have some areas for improvement. Taking a large commercial complex as an example, it is equipped with a large number of smart electrical devices, such as smart meters, lighting systems, and air conditioning systems. These devices rely on communication control technology to achieve efficient collaboration and intelligent management. Traditional technologies have some shortcomings in data transmission reliability. For example, during peak electricity consumption periods, a large number of devices transmit data simultaneously, which can easily lead to network congestion. Real-time electricity consumption data collected by smart meters may not be uploaded to the control center in a timely and accurate manner due to transmission delays. This prevents managers from making reasonable electricity control decisions based on the latest data, affecting the efficient allocation and utilization of energy.

[0003] In addition, traditional communication control technology is not flexible enough when dealing with multiple devices and complex communication needs. Different manufacturers' equipment uses different communication protocols, and traditional technology is difficult to quickly and easily convert and adapt to the protocols. It requires a lot of time and manpower to debug and modify the protocols, which affects the use of smart power supply. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a communication master control system based on intelligent power supply, so as to realize intelligent management and control of the power supply status of the communication system.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: Firstly, a communication master control system based on intelligent power supply includes: The power supply monitoring module is used to monitor the mains power supply status of the communication base station. When a mains power interruption is detected, the power switching circuit is automatically controlled to switch the power supply mode to the backup battery power supply mode. The status acquisition module is used to collect real-time data on the state of charge, discharge efficiency, and health status of the backup battery in backup battery power supply mode, and to obtain the battery's remaining capacity, actual discharge capacity, and lifespan indicators. The load receiving module is used to upload the battery's remaining capacity, actual discharge capacity, and lifespan indicators to the communication main control unit, while also receiving load data from the current communication network. The power supply assessment module is used to perform dynamic correlation analysis between battery status data and communication network load data. By constructing multi-source data sequences and calculating relative relationships, it generates dynamic assessment parameters that reflect power supply reliability. The power consumption strategy module is used to identify core communication function units and non-core power consumption equipment based on dynamic evaluation parameters and preset strategies, and form a power consumption scheduling strategy table. The instruction generation module is used to generate power outage scheduling instructions for non-core power-consuming equipment based on the power consumption scheduling strategy table when the communication load changes and exceeds a preset threshold. The power supply execution module is used to send power outage dispatch commands to the power supply management component, which then executes the commands and actively cuts off the power supply to non-core electrical equipment to ensure the continuous operation of the core communication function unit.

[0006] Furthermore, the mains power supply status of the communication base station is monitored. When a mains power outage is detected, the automatic power switching circuit switches the power supply mode to backup battery power mode, including: The electrical parameters at the mains input terminal are collected in real time by voltage and current sensors to obtain monitoring data including voltage values; The system judges based on the voltage value in the monitoring data. If it is found that the mains voltage is continuously lower than the rated value, the timing is started and the duration of low voltage is accumulated. When the duration of low pressure reaches the first preset time threshold, a switching trigger signal is generated; Based on the switching trigger signal, the relay in the power switching circuit is controlled to perform a switching operation, switching the power supply mode from mains power supply to backup battery power supply mode.

[0007] Furthermore, in backup battery power mode, the state of charge, discharge efficiency, and health status data of the backup battery are collected in real time to obtain the battery's remaining capacity, actual discharge capacity, and lifespan indicators, including: By using a monitoring device configured on the backup battery pack, the voltage, current and temperature parameters of the backup battery pack are collected in real time to obtain the raw data of battery operation; Based on the current parameters in the original battery operation data, the current value is integrated with time to calculate the real-time remaining capacity of the battery. Based on the real-time remaining capacity, and combined with the currently collected discharge rate and ambient temperature parameters, the actual discharge capacity of the battery under the current operating conditions is calculated. Based on the voltage parameters and cumulative cycle count in the original battery operation data, a comprehensive evaluation is conducted by comparing them with the preset battery capacity change pattern to obtain the battery health status index.

[0008] Furthermore, the remaining battery capacity, actual discharge capacity, and lifespan indicators are uploaded to the communication main control unit, while simultaneously receiving load data from the current communication network, including: The real-time remaining battery capacity, actual discharge capacity, and battery health status indicators are formatted and structured to generate a standardized battery status dataset. The battery status dataset is encapsulated using a serial communication interface to generate data frames that conform to the communication protocol, and the encapsulated data frames are sent to the communication master control unit according to a preset period. The communication master control unit receives and analyzes data frames, and at the same time obtains real-time power consumption data of each functional unit from the base station master equipment. It then merges the analyzed battery status data with the received load data to generate a network load status dataset. Time synchronization and correlation analysis are performed on the battery status dataset and the network load status dataset to generate complete status information for power supply capacity assessment and load demand analysis.

[0009] Furthermore, dynamic correlation analysis is performed on battery status data and communication network load data. By constructing multi-source data sequences and calculating relative relationships, dynamic evaluation parameters reflecting power supply reliability are generated, including: Analyze battery status data and communication load demand data to establish a power supply capacity time series and a load demand time series based on the time axis; The power supply capacity time series and the load demand time series are aligned on the time axis to establish the correspondence between power supply capacity and load demand at the same time, forming a dynamic matching relationship table between power supply and load. Based on the dynamic matching table of power supply and load, the estimated remaining power supply time of the battery under the current load demand conditions is calculated. At the same time, the trend of load demand change is predicted and analyzed to generate load demand change trend data. The estimated remaining power supply duration is matched with the load demand change trend data to calculate the power supply sustainability index. Based on the numerical range of the power supply sustainability index, power supply reliability is divided into multiple levels according to preset standards, generating dynamic evaluation parameters for power supply reliability.

[0010] Furthermore, based on dynamic evaluation parameters and pre-defined strategies, core communication functional units and non-core power-consuming equipment are identified, forming a power dispatching strategy table, including: Based on dynamic evaluation parameters, a preset evaluation strategy is used to evaluate all electrical equipment in the base station to obtain evaluation results; Based on the assessment results and the importance level of the equipment in the communication network, the transmission equipment and baseband processing unit are classified as core communication functional units; the environmental control equipment and auxiliary heat dissipation equipment are classified as non-core electrical equipment. Based on the equipment classification results, the equipment is sorted according to its key functional parameters to generate a ranking table of equipment importance. Based on the equipment importance priority list, the interruptible power supply characteristics of non-core power-consuming equipment are analyzed, and equipment with interruptible power supply is screened out to generate a list of interruptible power supply equipment. The device priority sequence list and the list of interruptible power supply devices are integrated to form a power dispatching strategy table.

[0011] Furthermore, based on the power consumption scheduling strategy table, when the communication load changes and exceeds a preset threshold, a power outage scheduling instruction is generated for non-core power-consuming equipment, including: Based on the power consumption dispatch strategy table, the load changes of the communication network are monitored in real time to obtain dynamic load change data. The dynamic load change data is compared and analyzed with the preset safety threshold. When the load change causes the power supply reliability index to be less than the safety threshold, the power dispatching process is triggered. Based on the trigger-based power dispatching process, the scheduling algorithm is invoked to process the list of interruptible power supply equipment in the power dispatching strategy table, generating dispatching instructions that include the power outage sequence and power outage time arrangement for non-core power consumption equipment.

[0012] Furthermore, the power outage dispatch command is sent to the power management component, which executes the command and actively cuts off the power supply to non-core electrical equipment to ensure the continuous operation of the core communication function unit, including: The power outage dispatch command is analyzed to extract the identification information of non-core power-consuming equipment and the power outage time parameter. Based on the equipment identification information and the power outage time parameter, a power outage dispatch command data packet conforming to the communication protocol is generated. The power outage dispatch command data packet is sent to the intelligent power distribution unit through the communication interface. The intelligent power distribution unit receives and parses the command content, and controls the corresponding contactor to perform the power outage operation according to the command content, disconnecting the power supply circuit of non-core electrical equipment. After the power outage operation is performed, the power supply status of the core communication function unit is monitored in real time, voltage and current parameters are collected, the real-time power supply is calculated, and the real-time power supply is compared and analyzed with the preset safety threshold. When the real-time power supply is detected to be less than the safe operating threshold, the protection mechanism is activated and the power supply strategy is adjusted to ensure the continuous operation of the core communication function unit.

[0013] In a second aspect, a computing device includes: One or more processors; A storage device for storing one or more programs that, when executed by one or more processors, cause the one or more processors to implement the method.

[0014] Thirdly, a computer-readable storage medium storing a program that, when executed by a processor, implements the method.

[0015] The above-described solution of the present invention has at least the following beneficial effects: The system monitors the mains power status in real time. When the mains voltage remains below the rated value and reaches a preset threshold, it automatically switches to backup battery power. Once the mains power is restored, it switches back to backup power promptly to prevent power outages for core communication units. This ensures stable operation of the communication network during mains power fluctuations or interruptions, enhancing the power supply's resilience. It also collects real-time data on battery state of charge, discharge efficiency, and health status, and dynamically calculates remaining power supply time and sustainability index based on load conditions. This prevents damage such as over-discharge and high-rate discharge, and only schedules power outages for non-core equipment when necessary, reducing ineffective battery consumption, extending cycle life, and lowering base station battery replacement costs. Furthermore, it acquires load data in real time and integrates it with battery status analysis. Based on load fluctuations, it adjusts power consumption strategies to achieve precise matching between power supply and load, reducing overall base station energy consumption. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of a communication master control system based on intelligent power supply provided by an embodiment of the present invention.

[0017] Figure 2 This is a flowchart illustrating the process of dynamically correlating battery status data and communication network load data through an embodiment of the present invention. By constructing multi-source data sequences and calculating relative relationships, dynamic evaluation parameters reflecting power supply reliability are generated. Detailed Implementation

[0018] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0019] like Figure 1 As shown, an embodiment of the present invention proposes a communication master control system based on intelligent power supply, comprising: The power supply monitoring module is used to monitor the mains power supply status of the communication base station. When a mains power interruption is detected, the power switching circuit is automatically controlled to switch the power supply mode to the backup battery power supply mode. The status acquisition module is used to collect real-time data on the state of charge, discharge efficiency, and health status of the backup battery in backup battery power supply mode, and to obtain the battery's remaining capacity, actual discharge capacity, and lifespan indicators. The load receiving module is used to upload the battery's remaining capacity, actual discharge capacity, and lifespan indicators to the communication main control unit, while also receiving load data from the current communication network. The power supply assessment module is used to perform dynamic correlation analysis between battery status data and communication network load data. By constructing multi-source data sequences and calculating relative relationships, it generates dynamic assessment parameters that reflect power supply reliability. The power consumption strategy module is used to identify core communication function units and non-core power consumption equipment based on dynamic evaluation parameters and preset strategies, and form a power consumption scheduling strategy table. The instruction generation module is used to generate power outage scheduling instructions for non-core power-consuming equipment based on the power consumption scheduling strategy table when the communication load changes and exceeds a preset threshold. The power supply execution module is used to send power outage dispatch commands to the power supply management component, which then executes the commands and actively cuts off the power supply to non-core electrical equipment to ensure the continuous operation of the core communication function unit.

[0020] In this embodiment of the invention, the mains power status is monitored in real time. When the mains voltage is continuously lower than the rated value and reaches a preset threshold, the system automatically switches to backup battery power. After the mains power is restored, the system switches back to backup power in a timely manner to avoid power outages in core communication units. This ensures that the communication network can still operate stably when the mains power fluctuates or is interrupted, improving the power supply's resilience. Data such as battery state of charge, discharge efficiency, and health status are collected in real time. Combined with load dynamics, the remaining power supply time and sustainability index are calculated to avoid damage conditions such as battery over-discharge and high-rate discharge. Power outages for non-core equipment are only scheduled when necessary to reduce ineffective battery consumption, extend cycle life, and reduce base station battery replacement costs. Load data is acquired in real time and integrated with battery status for analysis. Power consumption strategies are adjusted according to load fluctuations to achieve precise matching between power supply and load, reducing the overall energy consumption of the base station.

[0021] In a preferred embodiment of the present invention, monitoring the mains power supply status of the communication base station and automatically controlling the power switching circuit to switch the power supply mode to the backup battery power supply mode when a mains power interruption is detected may include: In this embodiment of the invention, electrical parameters at the mains power input terminal are collected in real time using voltage and current sensors to obtain monitoring data including voltage values. Specifically, high-precision voltage and current sensors are installed at the input terminal of the mains power supply to the mains distribution room of the commercial complex. The voltage sensor uses the principle of electromagnetic induction, capturing the voltage signal generated by the alternating electric field in the cable in real time through an induction coil wound on the mains power input cable. The weak induction signal is then amplified by an internal signal amplification circuit, and the analog voltage signal is converted into digital voltage data that the system can recognize by a digital-to-analog converter chip, with a data accuracy of 0.1V. The current sensor uses the Hall effect. Based on this principle, the sensor is placed on the outside of the mains input cable. By detecting the magnetic field strength generated by the current in the cable, it is converted into a corresponding current signal. After amplification and digital-to-analog conversion, digital current data with an accuracy of 0.01A is generated. These two sensors continuously collect data at a frequency of once every 0.2 seconds. After each collection, the data is immediately transmitted to the system's signal processing unit through a shielded cable. This ensures that at least 5 complete sets of voltage and current values ​​can be obtained within 1 second, providing high-density and high-precision raw data for judging the mains power status. This avoids misjudgment of the mains power status due to excessively long collection intervals or insufficient data accuracy, thereby preventing any impact on the transmission stability of the smart meter's real-time power consumption data.

[0022] Based on the voltage values ​​in the monitoring data, if the mains voltage is consistently lower than the rated value, a timer is started to accumulate the duration of low voltage. Specifically, the signal processing unit performs specialized analysis on the received voltage data. First, it pre-stores the rated voltage standard of the mains for the commercial complex, which is 220V. This standard is determined according to the State Grid's regulations on commercial electricity use and the rated voltage requirements of the equipment inside the complex. The signal processing unit compares each collected real-time voltage value with 220V. If a voltage value is lower than 220V, it is marked as a low voltage occurrence. If the number of consecutive low voltage occurrences reaches a certain threshold... Five tests, each 0.2 seconds apart, totaling 1 second, are required. Only if all five voltage values ​​are below 220V will the mains voltage be considered to be continuously below the rated value. At this point, the internal timing mode is immediately activated, accumulating the low voltage duration in milliseconds. The accumulated value is updated every 0.1 seconds and stored in a temporary cache. This continuous multi-testing method can effectively distinguish between short-term voltage fluctuations, such as a voltage drop of 0.3 seconds caused by the temporary start-up of a large device, and genuine continuous low mains voltage. This avoids erroneous triggering of subsequent operations due to momentary fluctuations, ensures the accuracy of power supply mode switching, and maintains the continuity of data transmission for smart devices.

[0023] When the low-pressure duration reaches the first preset time threshold, a switching trigger signal is generated. Specifically, the timing analysis unit reads the cumulative low-pressure duration stored in the timing mode in real time and continuously compares it with the preset first time threshold. The setting of the first preset time threshold needs to comprehensively consider multiple factors, referencing the minimum tolerable low-pressure duration of key equipment in the commercial complex, such as smart meter data transmission and the core air conditioning control system, combined with the longest self-recovery duration after a brief low-pressure period in historical mains power failure data, and is finally determined to be 5 seconds. Every 0.1 seconds, the timing analysis unit will compare the currently accumulated low-pressure duration with 5 seconds. A comparison is performed. If the cumulative time is less than 5 seconds, monitoring continues. If the cumulative time reaches or exceeds 5 seconds, the timing analysis unit will immediately generate a switching trigger signal. This signal contains information such as the trigger time, current voltage value, and cumulative low voltage duration. It is transmitted to the system's control center via the internal bus to ensure that a switching command is issued only when there is a genuine risk of continuous power outage. This avoids premature switching, such as switching after only 3 seconds of low voltage, which would cause unnecessary power consumption of the backup battery. It also prevents delayed switching, such as switching after 7 seconds of low voltage, which would cause the smart meter to interrupt data upload due to insufficient power supply, affecting the real-time monitoring of the power load by management personnel.

[0024] Based on the switching trigger signal, the relays in the power switching circuit execute a switching operation to switch the power supply mode from mains power to backup battery power. Specifically, after receiving the switching trigger signal, the system control center verifies the signal within 0.1 seconds to confirm that the signal source is legitimate and that the cumulative low-voltage duration is true and valid. After successful verification, the control center sends a switching command to the relay controller in the power switching circuit. The command clearly specifies the sequence of actions: disconnecting the mains power line and closing the backup battery line. Upon receiving the command, the relay controller first sends a power-off signal to the relay controlling the mains power input. The electromagnetic coil of this relay is energized, generating magnetic force that attracts the armature to disconnect the contact connected to the mains power line. The entire disconnection process is completed within 0.05 seconds. Immediately afterwards, the relay controller sends a power-off signal to the relay controlling the backup battery line. When an energizing signal is sent, the relay's electromagnetic coil is energized, attracting the armature and closing the contact connected to the backup battery line. This closing process is also completed within 0.05 seconds, ensuring that the switching interval between the two lines does not exceed 0.1 seconds to avoid power interruption. During the switching process, the status of the main contacts is monitored in real time through the relay's built-in auxiliary contacts. If the feedback from the auxiliary contacts of the mains line relay is open and the feedback from the auxiliary contacts of the backup battery line relay is closed, the switching is considered successful. If any contact status is abnormal, an alarm signal is immediately issued, and the switching command is repeatedly sent until the switching is confirmed to be complete. This process effectively avoids short circuits or open circuits, ensuring the continuity of power supply for smart meters, lighting systems, air conditioning systems, and other equipment, ensuring normal data transmission, and providing a stable power supply foundation for managers to adjust power consumption strategies based on real-time data.

[0025] By collecting mains power parameters at high frequency using high-precision sensors and combining this with a continuous multi-judgment mechanism to identify persistent low-voltage conditions, the system can accurately distinguish between brief fluctuations and genuine mains power faults, avoiding false switching. By comprehensively considering multiple factors and setting a first preset time threshold, switching is only triggered when the mains power is persistently low. This ensures timely switching to the backup battery when a genuine persistent mains power fault occurs, preventing equipment shutdown due to power outages, while also preventing premature switching that would lead to ineffective battery consumption, thus extending the effective power supply time of the backup battery. Through a clear relay action sequence and real-time status monitoring, the system ensures rapid and safe switching of power supply modes, avoiding power supply accidents caused by line faults and improving the operating efficiency of the intelligent power supply system.

[0026] In a preferred embodiment of the present invention, in the backup battery power supply mode, real-time acquisition of the backup battery's state of charge, discharge efficiency, and health status data to obtain the battery's remaining capacity, actual discharge capacity, and lifespan indicators may include: In this embodiment of the invention, a monitoring device configured on the backup battery pack collects the voltage, current, and temperature parameters of the backup battery pack in real time to obtain the raw data of battery operation. Specifically, this includes: for backup battery packs with multiple cells connected in series in commercial complexes, typically 12 12V cells connected in series to form a 144V system, a miniature voltage sensor is installed on the positive and negative terminals of each cell via copper terminals. The positive and negative terminals of the sensor are securely connected to the positive and negative terminals of the battery, ensuring that the contact resistance is less than 0.01 ohms to avoid voltage detection errors caused by poor contact. A Hall effect current sensor is installed in series on the copper busbar at the positive output terminal of the battery pack. The sensor is fixed to the copper busbar with bolts, and its detection window completely covers the copper busbar to ensure that it can completely capture the magnetic field generated by all currents in the copper busbar, avoiding current data deviations caused by missed detections. A patch-type temperature sensor is attached to the side of the outer casing of each of the first, middle, and last cells of the battery pack. The sensor is connected via a conductive... The thermal silicone sealant adheres tightly to the battery casing, with a thermal conductivity greater than 0.8 W / (m·K), ensuring rapid response to changes in the battery's internal temperature. All three types of sensors employ 16-bit digital-to-analog converters to convert acquired analog signals into digital data. Voltage data accuracy reaches 0.001V, current data accuracy reaches 0.0001A, and temperature data accuracy reaches 0.01℃. The sensors continuously acquire data every 0.05 seconds. After each acquisition, the data is transmitted to the system's data acquisition box via a twisted-pair cable with a metal shield and a grounding resistance of less than 1 ohm. The signal filtering circuit within the acquisition box filters out 50Hz power frequency interference from the distribution room and electromagnetic noise from other equipment. The filtered raw data is then stored in a 10GB circular buffer on the local hard drive, ensuring at least 24 hours of data storage. This forms continuous, uninterrupted raw battery operation data, providing high-density, low-noise foundational data for performance calculations.

[0027] Based on the current parameters in the original battery operation data, the current value is integrated with time to calculate the real-time remaining capacity of the battery. Specifically, the system's data processing unit reads current data frame by frame from the circular buffer to calculate the real-time remaining capacity of the battery. First, it pre-stores the initial calibration capacity of the backup battery pack. This capacity is not the nominal capacity of the battery, but the actual capacity obtained during the system installation by performing a complete charge and discharge test on the battery pack using a dedicated charging and discharging device. For example, the initial calibration capacity obtained from the test is 105 amp-hours, and the 20-hour rate discharge capacity is the capacity obtained by continuously discharging at a current of 5.25 amps for 20 hours. The data processing unit records the initial remaining capacity at the moment the system switches to backup battery mode. This initial value is calculated by comparing the voltage data collected last before the switch with the battery's standard discharge curve. For example, if the voltage at the time of switch is 138V, the remaining capacity in the standard curve is 90 amp-hours. Afterward, the data processing unit extracts current data frame by frame at 0.05-second intervals. If the current value is positive... A positive current value indicates that the battery is in a discharging state. Multiplying this current value by 0.05 seconds gives the amount of electricity discharged by the battery during that time interval. A negative current value indicates that the battery is in a charging state, such as float charging during a brief restoration of mains power. Multiplying this current value by 0.05 seconds gives the amount of electricity charged by the battery during that time interval. The data processing unit continuously accumulates the charge and discharge amounts for each time interval, starting from the initial remaining capacity. During discharging, the amount of electricity discharged in that interval is subtracted from the current remaining capacity; during charging, the amount of electricity discharged in that interval is subtracted from the current remaining capacity. The real-time remaining capacity is obtained by adding the amount of electricity charged during that interval to the initial remaining capacity. For example, if the initial remaining capacity is 90 amp-hours, the discharge current in the first 0.05 seconds is 12 amps, and the amount of electricity discharged is 12 amps × 0.05 seconds = 0.6 amp-hours. At this time, the real-time remaining capacity is 90 amp-hours minus 0.6 amp-hours, which equals 89.4 amp-hours. The discharge current in the second 0.05 seconds is 11.8 amps, and the amount of electricity discharged is 11.8 amps × 0.05 seconds = 0.59 amp-hours. The real-time remaining capacity is then 89.4 amp-hours minus 0.59 amp-hours, which equals 88.81 amp-hours. The current in the third 0.05 seconds is -3 amps (float charging state), and the amount of electricity charged is -3 amps × 0.05 seconds = -0.15 amp-hours. The real-time remaining capacity is then 88.81 amp-hours plus 0.15 amp-hours, which equals 88.96 amp-hours. This process continues, updating the real-time remaining capacity every 0.05 seconds to ensure accurate reflection of the battery's current available capacity.

[0028] Based on the real-time remaining capacity and combined with the currently collected discharge rate and ambient temperature parameters, the actual discharge capacity of the battery under the current operating conditions is calculated. Specifically, this includes: First, calculating the discharge rate, expressed in C, where C is equal to the reciprocal of the battery's nominal capacity (100 Ah, 20-hour rate), i.e., 1C corresponds to 100 Ah of discharge current. The data processing unit uses the currently collected current value, taking the average of the last 10 current measurements to avoid the influence of instantaneous current fluctuations, and dividing by 100. The system calculates the current discharge rate. For example, if the average current over the last 10 discharges is 25 amps, the discharge rate is 25 amps ÷ 100 amps = 0.25C. The system pre-stores a discharge rate-capacity correction factor table, which is generated by fitting 500 sets of measured data at different discharge rates provided by the battery manufacturer. For example, the correction factor is 1.02 at 0.1C. The lower the discharge rate, the closer the actual discharged capacity is to the nominal capacity, and sometimes even slightly higher. For example, it is 1.0 at 0.2C, 0.98 at 0.3C, 0.95 at 0.5C, and 0.95 at 1C. The value is 0.9 at 2C and 0.85 at 2C. Next, the ambient temperature correction factor is calculated. The data processing unit takes the average value of the temperature sensors of the first, middle and last battery cells of the battery pack as the current ambient temperature. Because there is a temperature gradient inside the battery pack, the temperature of a single cell cannot represent the whole. For example, if the temperatures of the three cells are 24.5℃, 25.2℃ and 24.8℃ respectively, the average value is 24.8℃. The temperature-capacity correction factor table pre-stored by the system is also based on the manufacturer's actual measured data. For example, the correction factor is 1 when the temperature is between 23℃ and 27℃. 0 (Battery final operating temperature range): 0.98 at 20℃-22℃, 0.96 at 15℃-19℃, 0.93 at 10℃-14℃, 0.9 at 5℃-9℃, 0.85 at 0℃-4℃, and 0.8 below 0℃. To calculate the actual discharge capacity, first multiply the real-time remaining capacity by the discharge rate correction factor to obtain the capacity corrected for the discharge rate; then multiply this corrected capacity by the temperature correction factor to finally obtain the actual discharge capacity. For example, if the real-time remaining capacity is 75 amp-hours... With a discharge rate of 0.25C (correction factor 0.99) and an ambient temperature of 24.8℃ (correction factor 1.0), the capacity after discharge rate correction is 75 amp-hours multiplied by 0.99 equals 74.25 amp-hours. Multiplying this by the temperature correction factor of 1.0, the actual discharge capacity is 74.25 amp-hours. If the ambient temperature drops to 8℃ (correction factor 0.9), the actual discharge capacity is 75 amp-hours × 0.99 × 0.9 = 66.825 amp-hours, accurately reflecting the effective amount of electricity the battery can actually discharge under the current operating conditions.

[0029] Based on the voltage parameters and cumulative cycle count in the original battery operation data, a comprehensive evaluation is performed against a preset battery capacity change pattern to obtain the battery's health status index. Specifically, this includes: First, recording the cumulative cycle count; the system monitors the battery's charging and discharging process in real time. When the battery's remaining capacity continuously charges from below 20% (e.g., 19.8%) to above 90% (e.g., 90.5%), and the highest voltage during charging reaches the battery's nominal maximum voltage (158.4V for a 144V system), it is considered a complete cycle. The cumulative cycle count is then recorded. The number of cycles is incremented by 1. If the battery is only charged from 30% to 80%, it is not counted as one cycle to avoid incorrect cycle counting due to mid-charge. For example, if the battery pack is charged from 18% to 92% with a peak charging voltage of 158.6V, the cumulative cycle count is updated from 280 to 281. Next, voltage comparison data is extracted. The data processing unit records the current actual voltage value at five key nodes: 100%, 80%, 60%, 40%, and 20% of the remaining battery capacity. This value is compared with the pre-stored standard voltage trend, which is obtained from factory testing under standard conditions (25℃, 0.2C discharge). For example, the standard voltage is 158.4V at 100% remaining capacity and 152.1V at 80% remaining capacity. At 60% capacity, the voltage is 147.6V; at 40% capacity, it is 143.4V; and at 20% capacity, it is 139.2V. If the actual voltage at a certain node is more than 0.5V lower than the standard voltage, for example, the actual voltage at 60% capacity is 146.9V (lower than the standard 147.6V), it is marked as voltage decay. Then, refer to the preset capacity change table, which is based on accelerated aging test data of the same type of battery. For example, the capacity retention rate is 96% after 100 cycles, 92% after 200 cycles, 88% after 300 cycles, 84% after 400 cycles, and 80% after 500 cycles. During evaluation, the actual dischargeable capacity is first divided by the battery's initial calibration capacity (105 Ah) to obtain the current capacity retention rate. For example, if the actual dischargeable capacity is 88 Ah... 0.2 amp-hours, the current capacity retention rate is 88.2 amp-hours divided by 105 amp-hours equals 84%. Then, based on the cumulative number of cycles (281 times), find the corresponding standard capacity retention rate from the capacity change pattern table. After 280 cycles, the standard capacity retention rate is approximately 89%, and after 281 cycles, it is approximately 88.98%. If the current capacity retention rate (84%) is lower than the standard capacity retention rate (88.98%), and there is a voltage decay indicator, then multiply the current capacity retention rate by a correction factor of 0.95. If there is no voltage decay, multiply by 1.0 to obtain the health status index. For example, 84% × 0.95 = 79.8%, that is, the battery health status index is 79.8%, which comprehensively reflects the aging degree of the battery and its actual power supply capacity.

[0030] By installing high-precision sensors at multiple locations within the battery pack and employing high-frequency acquisition and noise filtering technologies, the continuity and accuracy of raw battery operation data are ensured. This avoids misjudgments of battery status due to data loss or interference, thereby guaranteeing stable transmission of real-time power consumption data from smart meters and control signals from air conditioning systems. Real-time remaining capacity is calculated using current-time integration based on the actual calibrated capacity, combined with dual corrections for discharge rate and temperature to obtain the actual dischargeable capacity. This accurately reflects the battery's true usable power under current operating conditions, preventing sudden power outages in smart devices due to incorrect power estimation. This enhances the system's flexibility in handling complex power supply scenarios. By accurately counting cycle counts and comparing standard voltage curves with capacity change patterns, the battery health status is comprehensively assessed, enabling early identification of battery aging trends. This facilitates timely battery maintenance or replacement by management personnel, preventing power outages due to sudden battery failure.

[0031] In a preferred embodiment of the present invention, uploading the battery's remaining capacity, actual discharge capacity, and lifespan indicators to the communication master control unit, while simultaneously receiving load data from the current communication network, may include: In this embodiment of the invention, the real-time remaining battery capacity, actual dischargeable capacity, and battery health status indicators are formatted and structured to generate a standardized battery status dataset. Specifically, this includes: formatting and structuring the real-time remaining battery capacity, actual dischargeable capacity, and battery health status indicators; firstly, determining a unified data format; all values ​​are rounded to two decimal places; unit labels use fixed abbreviations; the unit for real-time remaining capacity and actual dischargeable capacity is Ah; and the unit for health status indicators is %; field names use all uppercase English letters and are semantically clear, namely REAL_TIME_REMAINING_CAPACITY, ACTUAL_DISCHARGE_CAPACITY, and BATTERY_HEALTH_STATE; timestamps use year-month-day hour:minute:second:millisecond format, such as 2024-05-20. 14:30:25.123, accurate to the millisecond level, ensuring data time traceability; then, structured processing is performed, organizing information into data blocks. Each data block contains three parts: a header identifier, data fields, and a tail checksum. The header identifier is fixed as BAT_STATUS, used for quick identification of data type during communication; the data fields are arranged in the order of timestamp + real-time remaining capacity + actual dischargeable capacity + health status indicators, with each field separated by commas; the tail checksum is calculated by adding the integer parts of each value and taking the remainder of 100. Generate a checksum. For example, if the real-time remaining capacity is 88.25Ah (integer part 88), the actual dischargeable capacity is 74.50Ah (integer part 74), and the health status indicator is 79.80% (integer part 79), the integer parts of these three values ​​are added together to get 88 + 74 + 79 = 241. Taking the remainder of 100 gives the checksum 41, and the checksum field at the end is CHK:41. Through this process, a standardized battery status dataset with a fixed length and uniform format is generated, avoiding subsequent transmission and parsing errors caused by inconsistent formats.

[0032] The battery status dataset is encapsulated using a serial communication interface to generate data frames conforming to the communication protocol. These encapsulated data frames are then sent to the communication control unit according to a preset cycle. Specifically, the process includes: First, selecting the serial communication interface and parameters. An RS485 serial communication interface is used, employing differential signal transmission. Two signal lines transmit positive and negative signals respectively, canceling out interference signals on the two lines. This provides strong anti-electromagnetic interference capability and is suitable for the strong electromagnetic environment generated by frequency converters and large air conditioning compressors in commercial complex power distribution rooms. The interface parameters are specifically set as follows: a baud rate of 9600bps, balancing transmission speed and stability to avoid packet loss during long-distance transmission at high baud rates; 8 data bits to meet the transmission requirements of ASCII codes and numerical data; 1 stop bit to ensure identification at the end of the data frame; and even parity, using an even number of 1s to detect single-bit errors during transmission. The interface uses shielded twisted-pair cable connections, with one end of the shield grounded and a grounding resistance of less than 1 ohm to further reduce external interference.

[0033] The second step involves encapsulating the data using the industry-standard Modbus-RTU protocol. The data frame structure is fixed in bytes as follows: slave address (1 byte) + function code (1 byte) + data length (1 byte) + data content (N bytes) + CRC checksum (2 bytes). The slave address is fixed at 0x01, representing the device responsible for battery status monitoring in the commercial complex, facilitating the main control unit's differentiation of different data sources. The function code is fixed at 0x03, representing the reading of holding register data, conforming to the Modbus protocol's specifications for transmitting device status data. The data length is the number of bytes in the data content; the standardized battery status dataset is 64 bytes, hence the data length field is 0x40. The data content is the 64 bytes of the standardized battery status dataset, with the header identifier, data fields, and tail checksum fully preserved, converted to a hexadecimal byte stream (e.g., the character B is converted to 0). x42 and the number 8 are converted to 0x38. The CRC checksum is calculated using a byte-by-byte XOR + two's complement method. First, the slave address (0x01), function code (0x03), data length (0x40), and 64 bytes of data content are arranged in order to obtain 67 bytes of original data. Then, starting from the first byte, XOR operations are performed with the next byte in sequence (0x01 XOR 0x03 to get 0x02, 0x02 XOR 0x40 to get 0x42, and so on, until all 67 bytes are processed to obtain a 1-byte intermediate result. Finally, the intermediate result is XORed with 0xFF (i.e., inverted) to obtain the high byte of the CRC checksum. The intermediate result is then shifted left by 8 bits and XORed with 0xFF to obtain the low byte of the CRC checksum. For example, if the intermediate result is 0x12, then the high byte of the CRC checksum is 0xED, the low byte is 0x21, and the final CRC checksum is 0xED21.

[0034] The third step involves sending data at a preset cycle. This cycle is determined based on the data requirements of the equipment in the commercial complex. Smart meters need to upload real-time electricity consumption data every 10 seconds to support load regulation; therefore, the battery status data transmission cycle is also set to 10 seconds to ensure time matching. Before each transmission, the system first checks the bus status of the RS485 interface (by reading the busy pin level; high level indicates busy, low level indicates idle). If idle is detected, the encapsulated data frame is sent immediately; if busy is detected, the system waits, checking the bus status every 0.5 seconds, for a maximum wait of 3 seconds to avoid data backlog caused by indefinite waiting. After transmission, the system starts a 5-second timer to wait for confirmation from the communication master control unit. The reply frame is a 1-byte 0x06, representing confirmation of reception. If 0x06 is received within 5 seconds, the transmission is considered successful. If not received, the data frame is repackaged, the CRC checksum is recalculated to prevent the original checksum from becoming invalid, and the transmission is retried. A maximum of 3 retries are made, with a 2-second interval between each retrieval. Too short an interval can exacerbate bus congestion, while too long an interval can cause data delay. If all 3 retries fail, a data transmission failure log is recorded, and a local audible and visual alarm is triggered to remind maintenance personnel to check the communication line to ensure that battery status data is not missed due to bus congestion or line faults.

[0035] The communication control unit receives and analyzes data frames, and simultaneously acquires real-time power consumption data from various functional units of the base station main equipment. It then merges the analyzed battery status data with the received load data to generate a network load status dataset. Specifically, after receiving a data frame, the communication control unit first performs frame parsing. The first step is to verify the CRC checksum. The checksum is recalculated according to the CRC generation rules for the bytes from the station address to the data content in the received data frame and compared with the CRC checksum carried in the frame. If they match, the verification passes; otherwise, the frame is discarded and a retransmission request is sent to the battery monitoring device. The second step is to extract the data content. The hexadecimal bytes are converted into the original standardized battery status dataset. The header identifier is checked to see if it is BAT_STATUS. If not, it is considered invalid data and discarded; if it is, the timestamp, various capacity indicators, and health status indicators are extracted and stored in a temporary database. Next, the real-time power consumption data of the base station main equipment is acquired. For smart meters, the real-time current and voltage values ​​are read from their communication port. The real-time current value is multiplied by the real-time voltage value to obtain the real-time power consumption data of the corresponding circuit of the smart meter, for example, current 10A, voltage 220V. The power consumption is 10A × 220V = 2200W. For the air conditioning system, the operating power of the compressor and fan is read from the air conditioning controller, and the two power values ​​are added together to obtain the real-time power consumption data of the air conditioning system. For example, if the compressor power is 1500W and the fan power is 300W, the total power consumption is 1500W + 300W = 1800W. For the lighting system, the rated power and switch status of each circuit are read from the lighting control module. When the switch is closed, the power consumption is counted as the rated power, and when it is open, it is counted as 0. The rated power of all closed circuits is added together to obtain the real-time power consumption of the lighting system. Finally, the data is fused. The system uses timestamps as a reference to associate battery status data with an error of no more than 500 milliseconds at the same timestamp with the real-time power consumption data of each device to generate a network load status dataset. The dataset includes fields such as fused timestamp, real-time remaining battery capacity, actual battery discharge capacity, battery health status, total power consumption of smart meters, total power consumption of air conditioning system, total power consumption of lighting system, and total power consumption of other devices. The total power consumption of other devices is the sum of the power consumption of devices other than the above three categories in the base station main equipment, such as surveillance cameras and emergency indicator lights, which is obtained by reading the power consumption data of each device controller and adding them together.

[0036] Time synchronization and correlation analysis are performed on the battery status dataset and the network load status dataset to generate complete status information for power supply capacity assessment and load demand analysis. Specifically, this includes: first, time synchronization is performed using the Network Time Protocol (NTP) to synchronize the system time of the communication master control unit with the central clock server of the commercial complex at a frequency of once per minute, ensuring that the time error of the master control unit does not exceed 10%. Milliseconds; simultaneously, it is required that the battery monitoring equipment and all load devices (smart meters, air conditioner controllers, etc.) calibrate their time through the same central clock server, so that the timestamps of all data generated by all devices are based on a unified time reference; for the collected dataset, if the timestamp difference between the battery status data and the network load data exceeds 500 milliseconds, it is determined to be out of sync, the data set is marked as to be synchronized, and data at the same time point is re-requested from the corresponding device; if the difference is within 500 milliseconds, it is determined to be synchronized, and the data set is retained for subsequent analysis; then, correlation analysis is performed. First, the matching relationship between the total load power consumption and the actual discharge capacity of the battery is analyzed. The real-time power consumption of smart meters, air conditioners, lighting, and other devices is added to obtain the total load power consumption. The total load power consumption is compared with the maximum power supply corresponding to the actual discharge capacity of the battery (the actual discharge capacity of the battery is divided by the expected power supply duration to obtain the maximum power supply, for example, the actual discharge capacity is 74.5Ah, the expected power supply is 8 hours, and the maximum power supply is 74.5Ah multiplied by the battery nominal voltage 1). 44V divided by 8 hours equals 1341W, used to determine if the current load exceeds the battery's power supply capacity. Secondly, the impact of single device power consumption changes on the remaining battery capacity is analyzed. For example, when the total power consumption of the smart meter increases from 2200W to 3000W, the power consumption increment is calculated (3000W-2200W=800W), and the current increment is calculated based on the battery voltage (800W÷144V≈5.56A). Then, the rate of change in the remaining battery capacity is estimated based on the current increment (the larger the current increment, the faster the remaining capacity is consumed). Thirdly, the load-bearing capacity is analyzed based on battery health status indicators. If the health status indicator is below 80%, it indicates battery performance degradation, requiring appropriate reduction of power consumption in non-core devices (such as some lighting circuits) to avoid excessive battery discharge. Through these correlation analyses, complete status information is generated, including power supply capacity assessment (currently supported load range and estimated power supply duration) and load demand analysis (power consumption percentage of each device and list of high-power devices). This information is stored in the main control unit's historical database for management personnel to view and control.

[0037] By standardizing the format and structuring the data, battery status data is presented in a standardized format, avoiding parsing errors caused by chaotic data formats in traditional technologies. This ensures accurate data identification during transmission. Simultaneously, the structured verification mechanism reduces the impact of data loss or tampering, guaranteeing the reliability of data required for the control of devices such as smart meters and air conditioning systems. A mature serial communication interface and transmission protocol are used to encapsulate the data, combined with a retransmission mechanism, improving the stability of battery status data transmission. This adapts to the complex electromagnetic environment of commercial complexes, reducing manpower costs for equipment debugging and maintenance. Preset periodic transmission meets the real-time data requirements of different devices, supporting rapid power control. By acquiring load data from multiple dimensions and integrating it with battery status data, managers can intuitively grasp the matching between battery power supply capacity and load demand. The complete status information generated by time synchronization and correlation analysis comprehensively reflects the dynamic relationship between power supply capacity and load demand, helping managers to identify risks of insufficient battery power or overload in advance, adjust the operating status of non-core equipment in a timely manner, ensure the continuous operation of core equipment, and improve the control efficiency of the smart power supply system.

[0038] like Figure 2 As shown, in a preferred embodiment of the present invention, dynamic correlation analysis is performed on battery status data and communication network load data. By constructing multi-source data sequences and calculating relative relationships, dynamic evaluation parameters reflecting power supply reliability are generated, which may include: In this embodiment of the invention, battery status data and communication load demand data are analyzed to establish a power supply capacity time series and a load demand time series based on a time axis. Specifically, this includes: extracting battery status data and load demand data for the past 30 minutes from the historical database of the communication master control unit, with a strict collection interval of 10 seconds. The data is displayed in seconds, as smart meters in commercial complexes upload electricity consumption data every 10 seconds. This interval ensures data matching, resulting in 180 sets of data. For the power supply capacity time sequence, the horizontal axis is the timestamp, starting from the first data time 30 minutes ago (e.g., 14:00:00), with each time mark spaced 10 seconds apart (14:00:00, 14:00:10...14:30:00). The vertical axis contains three core parameters: real-time remaining battery capacity (unit: Ah), actual dischargeable capacity (unit: Ah), and battery health status index (unit: %). When extracting data, outliers must be removed first. If the real-time remaining capacity in a data set is greater than the actual dischargeable capacity (logical error) or the health status index is greater than 100% (physically impossible), then the average of the previous and next data sets is used to replace it (e.g., if the data at 14:00:20 is abnormal, use the average of 14:00:10 and 14:00:30). (The data is averaged and then padded). The processed data is arranged in ascending order of timestamps to form a two-dimensional table. Each time point corresponds to a complete set of parameters. For example, 14:00:00 corresponds to a real-time remaining capacity of 88.25Ah, an actual dischargeable capacity of 74.50Ah, and a health status of 79.80%; 14:00:10 corresponds to 87.50Ah, 73.80Ah, and 79.80%; 14:00:20 corresponds to 86.80Ah, 73.10Ah, and 79.80%, and so on, to ensure that the sequence is continuous without any breaks.

[0039] For the load demand time series, the horizontal axis is also set to 10-second intervals within 30 minutes (exactly the same as the horizontal axis of the power supply capacity time series), and the vertical axis is the total power consumption of the network load (in W). This total power consumption is calculated as follows: extract the total power consumption of smart meters, air conditioning system, lighting system, and other devices at each time point from the complete status information, and add these four values ​​together (e.g., 14:00:00). At that time, the total power consumption is 136700W (smart meter 79800W + air conditioner 53600W + lighting 2000W + other 1300W). If the power consumption data of a certain type of device is missing at a certain point in time, such as due to communication interruption of the air conditioner controller, the average power consumption of that device in the previous 5 times is used to fill the gap. For example, the average power consumption of the air conditioner in the previous 5 times is 53500W. This value is used when the gap is missing. The filled data is arranged by timestamp to form a load demand time sequence. Each time point corresponds to a unique total power consumption value. For example, 14:00:00 corresponds to 136700W, 14:00:10 corresponds to 135800W, and 14:00:20 corresponds to 136900W, ensuring that there is a one-to-one correspondence between the power supply capacity time sequence and the power supply capacity time sequence on the time axis.

[0040] The power supply capacity time series and load demand time series are aligned along the time axis to establish a correspondence between power supply capacity and load demand at the same time, forming a dynamic matching table of power supply and load. Specifically, although both sets of sequences are collected at 10-second intervals, there may be a ±2-second error in the actual collection time. For example, battery data might be collected at 14:00:00.123, and load data at 14:00:01.876. Alignment is required using the timestamp of the power supply capacity time series as the reference time point (rounded to the nearest 10 seconds, such as 14:00:00, 14:00:10, etc.). The timestamps of each data point in the load demand time series are checked one by one. If the difference between the load data timestamp and the reference time point is ≤2 seconds (e.g., the difference between 14:00:00.123 and 14:00:00 is 0.123), the data is aligned. If the difference is greater than 2 seconds and less than 8 seconds, for example, if the load data is taken at 14:00:03 and the reference point is 14:00:00, with a difference of 3 seconds, then linear interpolation is used to calculate the load data at the reference time point. For example, if the load data at 14:00:00 is 136700W and the load data at 14:00:10 is 135800W, then the interpolation at the 14:00:00 reference point needs to be calculated. Since the actual load is taken at 14:00:03, first calculate the time percentage: 3 seconds ÷ 10 seconds = 0.3. Then calculate the power consumption change: 135800W - 136700W = -900W. Finally, add the power consumption at the previous time point to the change and multiply by the percentage: 136700W + (-900W)×0.3=136700W-270W=136430W, which is used as the load data for the 14:00:00 reference point; if the difference is ≥8 seconds, it is considered as abnormal data, and the load data of the previous reference point is used to fill it.

[0041] After alignment, each reference time point corresponds to a set of power supply capacity data and a set of load demand data. These data are organized into a dynamic power supply-load matching table, which contains six fields: reference time point, real-time remaining capacity, actual dischargeable capacity, health status, total load power consumption, and data status. For example, the data for the 14:00:00 row is: 14:00:00, 88.25Ah, 74.50Ah, 79.80%, 136430W, interpolated; the data for the 14:00:10 row is: 14:00:10, 87.50Ah, 73.80Ah, 79.80%, 135800W, original. This ensures that the power supply and load data at the same time accurately correspond, eliminating the impact of time deviation for subsequent analysis.

[0042] Based on the dynamic matching table of power supply and load, the estimated remaining power supply time of the battery under the current load demand conditions is calculated. Simultaneously, the changing trend of load demand is predicted and analyzed to generate load demand trend data. Specifically, when calculating the estimated remaining power supply time, the actual dischargeable capacity and total load power consumption at the current reference time point (e.g., 14:00:30) are used as the basis. First, the actual dischargeable capacity (e.g., 72.30Ah) is multiplied by the battery's nominal voltage (144V) to obtain the total electrical energy currently available from the battery (72.30Ah × 144V). =10411.2Wh); then divide the total power consumption by the current total load power consumption (e.g., 136500W, converted to 136.5kW) to obtain the estimated remaining power supply duration (10411.2Wh ÷ 136.5W ≈ 76.27 hours). If the current total load power consumption is 0 (equipment not running), the estimated duration is recorded as infinite; when predicting the trend of load demand changes, select the total load power consumption data at the most recent 5 reference time points, such as 136700W at 14:00:00, 136080W at 14:00:10, 136900W at 14:00:20, 136900W at 14:00:1 ... Calculate the power consumption change between adjacent time points: 14:00:10 and 14:00:00: 136080W - 136700W = -620W; 14:00:20 and 14:00:10: 136900W - 136080W = 820W; 14:00:30 and 14:00:20: 136500W - 136900W = -400W; 14:00:40 and 14:00:30: 137100W - 136500W = 600W. Then calculate the average of these four changes (-620W + 820W + -400W + 600W = 400W, 400W ÷ 4 = 100W, meaning the load increases by an average of 100W every 10 seconds). Based on the average change, predict the load trend for the next three time points (within 30 seconds). If the average change is positive, the load is considered to be on an upward trend; if it is negative, the load is considered to be on a downward trend; if it is close to 0, the load is considered to be stabilizing. At the same time, calculate the trend strength by dividing the absolute value of the average change by the average load of the last five time points (e.g., if the average load is 136656W, 100W ÷ 136656W ≈ 0.00073). The larger the value, the more obvious the trend. Generate load demand change trend data that includes trend direction, average change, and trend strength.

[0043] The estimated remaining power supply duration is matched with the load demand trend data to calculate the matching degree and generate a power supply sustainability index. Specifically, the matching degree calculation is performed from three dimensions: First, the basic matching degree, which is obtained by dividing the estimated remaining power supply duration (e.g., 76.27 hours) by the preset minimum guarantee duration (4 hours for commercial complexes to ensure power supply to core equipment in case of emergencies), resulting in a basic value (76.27 hours ÷ 4 hours = 19.0675); Second, the trend influence coefficient, which is (1 minus the trend strength) if the load shows an upward trend. For example, if the trend strength is 0.00073, the coefficient is 1 - 0.00073 = 0.99927; if the load shows a downward trend, the coefficient is (1 - 0.00073 = 0.99927). (Add trend strength); if stable, the coefficient is 1; third, the health status correction coefficient, which is the battery health status index (e.g., 79.80%) divided by 100, yields 0.798; the power supply sustainability index is the base matching degree multiplied by the trend influence coefficient and then multiplied by the health status correction coefficient. For example, 19.0675×0.99927×0.798≈19.0675×0.797≈15.2. If the estimated remaining power supply time is less than the minimum guaranteed time, the base value is negative, and the final index is also negative, indicating that the power supply is unsustainable; if the index is positive, the larger the value, the stronger the power supply sustainability. Through this multi-dimensional weighted calculation, the degree of matching between the estimated power supply capacity and the load change trend is comprehensively reflected.

[0044] Based on the numerical range of the power supply sustainability index, power supply reliability is divided into multiple levels according to preset standards, generating dynamic evaluation parameters for power supply reliability. Specifically, the preset standards are formulated based on the power supply needs of the commercial complex and are divided into five levels: A level greater than 10 indicates Level 1 (extremely high reliability), meaning the battery power supply capacity far exceeds the current and future load demand, and core equipment can operate stably; a level between 5 and 10 indicates Level 2 (high reliability), meaning the power supply capacity meets the load demand and no adjustment is needed; a level between 0 and 5 indicates Level 3 (medium reliability), meaning the power supply capacity basically meets the demand, but load changes need to be monitored; a level between -5 and 0 indicates Level 4 (low reliability), meaning the power supply capacity may be insufficient in the short term, and non-core loads, such as some lighting circuits, need to be reduced; a level less than -5 indicates a lower reliability. When the power supply is at level 5 (extremely low reliability), it indicates a severe shortage of power supply capacity, requiring the activation of emergency plans, such as using a backup generator. The system determines the power supply sustainability index (e.g., 15.2) to level 1 (extremely high reliability) based on the preset standard, and integrates this level with the corresponding index value and evaluation timestamp to generate dynamic evaluation parameters for power supply reliability. These parameters are stored in the historical database and displayed in real time on the main control unit interface, allowing managers to intuitively understand the current power supply reliability status.

[0045] By establishing a time-series data set, scattered battery and load data are transformed into continuous time-related data, enabling managers to clearly understand the changing patterns of power supply capacity and load demand over time. This provides time-series data support for the precise control of smart meters, air conditioners, and other equipment. Time axis alignment ensures that power supply capacity and load demand correspond precisely at the same time, avoiding analysis errors caused by time deviations, improving the accuracy of correlation analysis, ensuring more reliable judgment of the power supply status of smart devices, and reducing control decision errors caused by data asynchrony.

[0046] In a preferred embodiment of the present invention, based on dynamic evaluation parameters and combined with preset strategies, core communication functional units and non-core power-consuming equipment are identified to form a power dispatching strategy table, which may include: In this embodiment of the invention, based on dynamic evaluation parameters, a preset evaluation strategy is used to evaluate all electrical equipment within the base station to obtain evaluation results. Specifically, the dynamic evaluation parameters include power supply reliability level, such as Level 2 high reliability, and power supply sustainability index (e.g., 1.063). The preset evaluation strategy evaluates each device from three dimensions, each dimension being tailored to the operational needs of equipment in a commercial complex. The first dimension is the matching degree of power supply reliability requirements. If the power supply reliability level is Level 1 or Level 2, and the power supply is sufficient, the evaluation standard for this dimension is whether the device needs continuous power supply to maintain basic functions. If it is Level 3 or below, and the power supply is tight, the standard is upgraded to whether the device needs continuous power supply to avoid loss of core data. For example, when evaluating the data transmission of smart meters, regardless of the power supply level, continuous power supply is required to avoid loss of power consumption data, and this dimension scores high. When evaluating the corridor lights of the lighting system, continuous power supply is required when the power supply is sufficient, and power supply can be paused when the power supply is tight. This dimension scores medium under Level 2 reliability.

[0047] The second dimension is the necessity of equipment functionality. This involves counting the number of downstream smart devices affected by the equipment shutdown. The more devices affected, the higher the necessity. For example, if a transmission device, such as a fiber optic transmitter, shuts down, 100 smart meters and 8 air conditioner controllers will be unable to communicate with the main control unit, affecting 108 devices. This dimension scores high. If a humidifier in the environmental control equipment shuts down, it only affects the humidity in the computer room and does not directly affect other equipment, affecting 0 devices. This dimension scores low.

[0048] The third dimension is data transmission priority. Core data, such as real-time electricity consumption data from smart meters and operating parameters of air conditioner compressors, has high priority for the corresponding transmission devices. Non-core data, such as the status of lighting switches and equipment inspection logs, has low priority for the corresponding devices. For example, the baseband processing unit, which is responsible for signal demodulation and transmission of core electricity consumption data from smart meters, scores high in this dimension; while the status monitoring of auxiliary heat dissipation equipment transmits fan speed data, which scores low in this dimension.

[0049] During the evaluation, each dimension is divided into three levels: high, medium, and low. They are quantified as 3 points for high, 2 points for medium, and 1 point for low. The scores of the three dimensions are added together to obtain the total score of the device. For example, for the transmission device, 3 + 3 + 3 = 9 points, and for the humidifier, 1 + 1 + 1 = 3 points. The higher the total score, the more urgent the device's need for continuous power supply. Finally, an evaluation result table including the device name, the scores of the three dimensions, and the total score is formed.

[0050] According to the evaluation results and the importance level of the device in the communication network, the transmission device and the baseband processing unit are classified as core communication function units; the environmental control device and the auxiliary heat dissipation device are classified as non-core power-consuming devices, specifically including: first, determine the importance level of the device in the communication network. This level is set based on the role of the device in the data transmission link. Devices at key data transmission nodes, such as transmission and demodulation devices, have an importance level of first; devices at data auxiliary processing nodes, such as data storage and status monitoring devices, are second; devices at environmental support nodes, such as temperature control and heat dissipation devices, are third.

[0051] Combined with the total score of the evaluation results, it is set that a total score ≥ 7 is a high demand, and < 7 is a low demand for classification: For transmission devices, such as fiber optic transmitters and 5G signal transmitters, their importance level is first, the evaluation total score is 9 points, and after停运, it will directly interrupt the core data transmission of smart meters and air conditioner controllers. For example, after the fiber optic transmitter is停运, the smart meters on each floor of the commercial complex cannot upload real-time electricity consumption data to the main control unit, resulting in managers being unable to regulate the electricity load, which meets the definition of a core communication function unit, so it is classified as a core communication function unit; for the baseband processing unit, the importance level is first, the evaluation total score is 8 points with high demand. It is responsible for converting the analog signals transmitted by smart meters into digital signals. If it is停运, the main control unit cannot identify the electricity consumption data, which belongs to the core data processing link and is classified as a core communication function unit.

[0052] For environmental control devices, such as computer room air conditioners, humidifiers, and dehumidifiers, the importance level is third, and the evaluation total score is 3 - 4 points with low demand. Although the computer room air conditioner affects the device operation environment, if it is停运 for a short time, such as within 30 minutes, the temperature of the core devices is still within the safe range of 20 - 28 °C and will not interrupt data transmission; the停运 of the humidifier only causes a change in humidity and does not affect the functions of the core devices, so it is classified as a non-core power-consuming device; for auxiliary heat dissipation devices, such as散热 fans, heat sink power supply modules, and temperature inspection instruments, the importance level is third, and the evaluation total score is 2 - 3 points with low demand. After the散热 fan is停运, the core devices can maintain normal operation for 15 - 20 minutes through their own heat dissipation, and the temperature inspection instrument only monitors the temperature and does not participate in data transmission, so it is classified as a non-core power-consuming device. After classification, a corresponding table of device name - device type (core / non-core) is formed to ensure that the attribution of each device is clear.

[0053] Based on the equipment classification results, the equipment is sorted according to its key functional parameters to generate a priority list. Specifically, the key functional parameters include three specific indicators, all set for the operational characteristics of equipment in commercial complexes. The first indicator is the scope of impact of data transmission interruption, which counts the number of smart devices that cannot transmit data normally after equipment shutdown. The higher the number, the more critical the device. For example, if the main transmission equipment in the core communication functional unit shuts down, it affects 100 smart meters + 8 air conditioners = 108 devices; if the backup transmission equipment shuts down, it only affects 20 smart meters. Therefore, the main transmission equipment is more critical than the backup transmission equipment in this indicator. The second indicator is the severity of the consequences of equipment shutdown, divided into core data loss, such as historical electricity consumption data of smart meters, and data loss in functional parts. The system is categorized into three levels of severity: (e.g., partial air conditioning malfunction, no direct impact), with higher levels indicating greater criticality. For example, a baseband processing unit outage would result in core data loss, a severe consequence. A data backup unit outage in core equipment would only cause backup functionality failure without data loss, a moderate consequence. Therefore, the baseband processing unit is superior to the data backup unit in this regard. The third indicator is the time required for equipment recovery. Shorter recovery times indicate lower criticality. Equipment that can be quickly restored can be temporarily de-energized. Longer recovery times indicate higher criticality and require priority to avoid prolonged interruptions. For example, a signal amplifier outage in core equipment requires 5 minutes to recover, while a main transmission equipment outage requires 30 minutes. Therefore, the main transmission equipment is superior to the signal amplifier in this regard.

[0054] During the sorting process, core communication functional units are first sorted according to the following order: the scope of impact of data transmission interruption from largest to smallest, the severity of equipment downtime consequences from highest to lowest, and the recovery time from longest to shortest. For example, the sorted result is: main transmission equipment, baseband processing unit, backup transmission equipment, signal amplifier, and data backup unit. Then, non-core power-consuming equipment is sorted according to the same three indicators, but the indicator weights are adjusted so that the indirect impact of equipment downtime on core equipment is from lowest to highest. The lower the indirect impact, the higher the priority for power supply. For example, in environmental control equipment, the downtime of a humidifier has no indirect impact on core equipment, but the downtime of the computer room air conditioner for 30 minutes will indirectly cause the temperature of core equipment to rise. In auxiliary heat dissipation equipment, the downtime of a cooling fan for 20 minutes will indirectly affect the temperature of core equipment. Therefore, the non-core sorted result is: humidifier, dehumidifier, cooling fan, and computer room air conditioner. The sorting results of core and non-core equipment are integrated to generate an order table of equipment importance that includes equipment name, equipment type, functional key parameter score, and ranking, ensuring that the importance of each piece of equipment is clearly ranked.

[0055] Based on a priority list of equipment, an interruptible power supply characteristic analysis was conducted on non-core electrical equipment to identify interruptible power supply devices and generate an interruptible power supply device list. Specifically, the interruptible power supply characteristic analysis revolves around three actual operating scenarios to avoid impacting core equipment due to the interruption of non-core equipment. The first analysis dimension is the indirect impact on core equipment after an interruption. This involves monitoring changes in key operating parameters of core equipment, such as temperature, voltage, and data transmission rate, after the interruption of non-core equipment. For example, if the humidifier is interrupted, the humidity in the computer room drops from 50% to 40%, while the safe humidity range for core equipment is 30%-70%, and the core equipment parameters show no abnormalities, resulting in no indirect impact. If the computer room air conditioner is interrupted, the computer room temperature rises from 25℃ to 28℃ within 30 minutes, while the safe temperature limit for core equipment is 30℃, resulting in a slight indirect impact. If the cooling fan is interrupted, the core equipment temperature rises from 25℃ to 27℃ within 20 minutes, also resulting in a slight indirect impact.

[0056] The second dimension of analysis is the allowable interruption duration. Through experimental testing, the maximum interruption time for non-core equipment is determined to ensure that restarting after an interruption does not affect its own functions or indirectly affect core equipment. For example, a humidifier can be interrupted for up to 4 hours, after which the humidity will still be within a safe range. A dehumidifier can be interrupted for up to 3 hours, a cooling fan can be interrupted for up to 20 minutes, after which the temperature of core equipment will exceed the safe range. A server room air conditioner can be interrupted for up to 30 minutes, after which the temperature will exceed the safe range.

[0057] The third analytical dimension is the ease of power restoration, categorized into those that can be restored with a single click (e.g., humidifiers and cooling fans, requiring on-site manual adjustments), and those requiring coordination with other equipment (e.g., some dehumidifiers, requiring coordination with other devices, such as server room air conditioners, which need to be linked with temperature controllers). The easier the restoration, the more suitable it is as an interruptible device. The selection criteria are: no or minimal indirect impact on core equipment after interruption; an allowable interruption duration of ≥10 minutes; and ease of power restoration (one-click restart or simple adjustments). According to these criteria, among non-core equipment, humidifiers (no indirect impact, 4-hour allowable interruption, one-click restart), dehumidifiers (no indirect impact, 3-hour allowable interruption, simple adjustments), and cooling fans (minor indirect impact, 20-minute allowable interruption, one-click restart) all meet the selection criteria. Although server room air conditioners have a minor indirect impact and a 30-minute allowable interruption, restoration requires coordination with the temperature controller, which is more difficult, and they need to be restarted immediately after a 30-minute interruption; therefore, they are not currently listed as interruptible devices. A list of interruptible power supply devices is generated after screening, including the device name, the maximum allowable interruption duration, the restoration method, and post-interruption precautions (e.g., cooling fans should not be interrupted for more than 20 minutes). Minutes are required to ensure that there is a clear basis for interrupting the operation.

[0058] The device priority sequence table and the list of interruptible power supply devices are integrated to form a power dispatching strategy table. Specifically, the integration process revolves around the control logic in case of power shortage, ensuring the strategy table can be directly used for actual dispatching. The first step involves extracting the device name, device type, and ranking from the device priority sequence table, and extracting the maximum allowed interruption duration, recovery method, and post-interruption precautions from the list of interruptible power supply devices. These two sets of information are then linked by device name to form a basic information table. The second step involves supplementing the dispatching rule fields. For core communication function units, the dispatching rule is unified as prioritizing power supply, ensuring no interruption under any circumstances, and prioritizing reducing power supply to non-core devices when power is insufficient. For interruptible devices among the non-core devices, the dispatching rule is to interrupt them from the back of the ranking list, meaning the later the device is in the ranking, the higher the priority for interruption, with the interruption duration not exceeding the maximum allowed interruption duration. Upon power restoration... The system is restored from top to bottom according to the order of priority. For non-core, uninterruptible equipment, such as server room air conditioners, the scheduling rule is that they can only be briefly interrupted when the power supply reliability level is level 5 (extremely low reliability), not exceeding 10 minutes, and backup cooling measures must be activated simultaneously. The third step is to add an interruption priority field. Only non-core interruptible equipment is included. The system is sorted by non-core equipment order, with higher priority and earlier interruption occurring later. For example, if the non-core order is humidifier, dehumidifier, cooling fan, and server room air conditioner, and the first three are interruptible, the interruption priority would be cooling fan (level 1, interrupted first), dehumidifier (level 2), and humidifier (level 3). The final power scheduling strategy table includes nine fields: equipment name, equipment type, order of priority, interruptibility, maximum allowed interruption duration, recovery method, interruption priority, scheduling rules, and post-interruption precautions. For example: Main transmission equipment: Core, 1, No, None, None, None, Priority guarantee, None; Humidifier: Non-core, 1 (non-core sorting), Yes, 4 hours, one-key restart, 3 levels, interrupt by priority, monitor humidity after interruption; Cooling fan: Non-core, 3 (non-core sorting), Yes, 20 minutes, One-click restart, Level 1, Interrupt by priority, Interruption not exceeding 20 minutes; This strategy table can be directly imported into the main control system for automatic or manual scheduling when power supply is insufficient, ensuring that control is carried out in a systematic manner.

[0059] By combining multi-dimensional evaluation parameters with preset strategies, core and non-core equipment are accurately distinguished, ensuring that core functions such as smart meter data transmission and air conditioning control signal transmission receive priority power supply. This avoids data transmission interruptions caused by erroneous disconnection of core equipment, aligning with the data reliability requirements of commercial complexes. Equipment is prioritized according to its functional critical parameters and its interruptibility characteristics are clearly defined, making power control more targeted when power is insufficient. Among non-core equipment, those with the least interruptibility and impact are given priority power supply, reducing equipment malfunctions caused by blind power outages. At the same time, the continuous and stable operation of core equipment is ensured, improving the rationality of power supply control.

[0060] In a preferred embodiment of the present invention, based on the power consumption scheduling strategy table, when the communication load changes and exceeds a preset threshold, a power outage scheduling instruction for non-core power-consuming equipment is generated, which may include: In this embodiment of the invention, based on the power consumption scheduling strategy table, the load changes of the communication network are monitored in real time to obtain dynamic load change data. Specifically, the monitoring objects are the real-time power consumption of all devices in the power consumption scheduling strategy table, including core communication functional units such as the main transmission equipment and baseband processing units, and non-core power consumption equipment such as humidifiers and cooling fans. The monitoring frequency is consistent with the previous data acquisition interval, that is, the real-time power consumption of each device is collected once every 10 seconds. Core devices directly read the power consumption through their built-in power consumption monitoring. For example, the power consumption monitoring port of the main transmission equipment returns the current power value once every 10 seconds. The device reads data through a connected smart controller. For example, the KNX controller of a humidifier uploads its operating power every 10 seconds. After acquiring the data, it first performs a validity check. If a device returns a power consumption value exceeding 120% of its rated power for three consecutive times, such as a 100W cooling fan returning 130W, 140W, and 150W consecutively, it is determined to be abnormal data. The average power consumption of the device in the previous five times is then used to replace it. If the average of the previous five times is 95W, then this time it is recorded as 95W. If there is only a single abnormality, the average of the previous and subsequent times is used to fill the gap. For example, if the data is abnormal in the 10th second, the average of the 0th and 20th seconds is used for calculation.

[0061] The processed real-time power consumption data is used to calculate dynamic load change data, including three elements: the current total power consumption, which is the sum of the real-time power consumption of all devices, such as the total power consumption of core devices (5000W) plus the total power consumption of non-core devices (3000W) equals 8000W; the load change amount, which is the current total power consumption minus the total power consumption 10 seconds ago, such as 8000W minus 7500W equals 500W; and the load change rate, which is the change amount divided by the total power consumption 10 seconds ago, such as 500W divided by 7500W approximately 0.067, or 6.7%. This data is stored in real-time in the dynamic database of the main control unit and updated every 10 seconds, providing real-time basis for subsequent comparative analysis.

[0062] The dynamic load change data is compared and analyzed with preset safety thresholds. When the load change causes the power supply reliability index to fall below the safety threshold, the power dispatching process is triggered. Specifically, the preset safety thresholds are set based on the power supply safety requirements of the commercial complex and include two related thresholds: the load change rate safety threshold and the power supply reliability index safety threshold. The load change rate safety threshold is set to 10%, meaning that a load change rate exceeding 10% within 10 seconds is considered a significant fluctuation. The power supply reliability index safety threshold is set to 0.3, corresponding to the previous level three medium reliability; a value below this indicates insufficient power supply capacity. It may not be able to meet the load demand; the comparative analysis is carried out according to the following process: First, determine whether the load change rate exceeds 10%. If it does not exceed 10%, such as 6.7%, continue monitoring without triggering any process; if it exceeds 10%, such as the load increasing from 7500W to 8500W within 10 seconds, a change of 1000W, a change rate of 13.3%, then proceed to the second step; Second, recalculate the power supply reliability index based on the current total load power consumption. For example, if the current actual discharge capacity corresponds to a total energy of 10000Wh, and the current load is 8500W, the estimated remaining time is 10000 ÷ 8500 ≈ 1.176. The first step is to divide the minimum guaranteed duration of 0.5 hours by the hour to obtain the basic matching degree of 2.352. After combining the trend coefficient and health coefficient, the index is 1.2. The third step is to compare the recalculated power supply reliability index with the safety threshold of 0.3. If the index is ≥0.3, such as 1.2, only the load fluctuation is recorded and no dispatch is triggered. If the index is <0.3, such as the load continuing to rise to 12000W, the recalculated index is 0.2. Then it is determined that the power supply reliability is insufficient and the power dispatch process is immediately triggered. After the trigger, the system first issues an audible and visual warning. The yellow indicator light on the main control unit panel flashes and the buzzer sounds once every 3 seconds. At the same time, the trigger time, current load data, and power supply reliability index are recorded to provide traceability information for subsequent dispatch.

[0063] Based on the trigger-based power dispatching process, the dispatching algorithm is invoked to process the list of interruptible power supply equipment in the power dispatching strategy table, generating dispatching instructions that include the power outage sequence and timing of non-core power supply equipment. Specifically, the core logic of the dispatching algorithm is to meet power supply demand with minimal interruption cost. The specific processing steps are as follows: First, calculate the power consumption to be reduced by subtracting the total power consumption of the safe load from the total power consumption of the current load. The total power consumption of the safe load is the load value corresponding to a power supply reliability index of 0.3. For example, if the calculated safe load is 10000W and the current load is 12000W, then 2000W needs to be reduced. Second, extract the equipment and its parameters from the list of interruptible power supply equipment, including the equipment name. The steps are as follows: 1. Current power consumption, interrupt priority (level 1 is the highest), and maximum allowed interrupt duration (e.g., cooling fan level 1, current power consumption 500W, allowed 20 minutes; dehumidifier level 2, current power consumption 800W, allowed 3 hours; humidifier level 3, current power consumption 600W, allowed 4 hours). 2. Select devices according to interrupt priority from high to low, and accumulate their current power consumption until the required power reduction value is reached. First, select the level 1 cooling fan (500W), the accumulated power consumption is 500W, which is less than 2000W. Then select the level 2 dehumidifier (800W), the accumulated power consumption is 500 + 800 = 1300W, still not reaching the required level. Finally, select the level 3 humidifier (600W), the accumulated power consumption is 1300 + 600 = 1900W. When the power consumption approaches 2000W (a difference of 100W, within the allowable error range), stop selecting. Fourth, determine the power-off sequence, prioritizing from highest to lowest interruption priority: first, power off the cooling fan; then the dehumidifier; finally, power off the humidifier. Fifth, schedule the power-off times. Based on the maximum allowable interruption duration and the estimated time to maintain a safe load, and considering load trend predictions (e.g., if the load is expected to remain high for 30 minutes), allocate power-off time for each device. The cooling fan is allowed a maximum of 20 minutes, so allocate 20 minutes; it must be restarted after 20 minutes to avoid affecting core equipment. The dehumidifier is allowed 3 hours, so allocate 30 minutes; just enough to meet the needs, no need to reach the maximum duration. The humidifier is allowed... The process involves allocating 30 minutes to each of the 4 hours, and setting the restart sequence to be the reverse of the power outage sequence: first restarting the humidifier, then the dehumidifier, and finally the cooling fan, ensuring a gradual increase in load during power restoration to avoid overload. The sixth step involves generating scheduling instructions. Each instruction includes the device name, power outage start time, current time plus 10 seconds, preparation time, power outage duration, restart time, and execution priority (urgent). For example, the instruction for the cooling fan would be: Cooling Fan, 14:30:10, 20 minutes, 14:30:30, Urgent. After generation, the instructions are sent to the target device via the device's corresponding communication interface, such as the KNX interface or RS485 interface, and the instruction execution status (pending execution, executing, completed) is displayed on the main control unit interface.

[0064] Real-time monitoring of load changes and acquisition of dynamic data ensures that the system can promptly detect load fluctuations in the communication network, providing real-time load data for the stable operation of devices such as smart meters and air conditioner controllers. This avoids power overload caused by undetected load changes. By triggering the scheduling process through dual threshold comparison, it ensures that processing is only initiated when real control is needed, improving the accuracy of triggering conditions and meeting the high requirements of commercial complexes for power supply stability. Based on the scheduling algorithm, it generates orderly power-off commands and rationally selects non-core devices according to priority and power consumption requirements, ensuring that power supply needs are met with minimal interruption and guaranteeing continuous power supply to core communication functional units.

[0065] In a preferred embodiment of the present invention, a power outage scheduling command is sent to a power supply management component, which executes the command and actively cuts off the power supply to non-core electrical equipment to ensure the continuous operation of the core communication function unit. This may include: The power outage dispatch command is analyzed to extract the identification information of non-core electrical equipment and the power outage time parameter. Based on the equipment identification information and the power outage time parameter, a power outage dispatch command data packet conforming to the communication protocol is generated. Specifically, the power outage dispatch command includes information such as equipment name, power outage start time, power outage duration, and restart time, such as cooling fan, 14:30:10, 20 minutes, 14:30:30. When analyzing the command, the unique identification information of non-core electrical equipment is first extracted. Each device has a unique code preset in the system, such as NC-001 for cooling fan, NC-002 for dehumidifier, and NC-003 for humidifier. This code is bound to the device's communication address, such as NC-001 corresponding to RS485 address 0x0A. Then, the power outage time parameter is extracted, including the power outage start time, accurate to the second, such as 14:30:10, and the power outage duration converted to seconds, such as 20 minutes = 1200 seconds. When generating the command data packet, it must conform to the device's communication protocol. For devices connected via RS485 interface, such as cooling fans and dehumidifiers, the Modbus-RTU protocol is used for encapsulation. The data packet structure is slave address (1 byte, such as 0x0A) + function code (0x05, representing forced single coil) + register address (0x0001, representing power-off control) + data (0xFF00, representing power-off execution) + CRC checksum (2 bytes). For devices connected via KNX bus, the KNX protocol is used for encapsulation. The data packet contains source address (master unit address) + destination address (device address) + control command (0x01, representing power-off) + time parameters (binary encoding of start time and duration). Each data packet also needs to add a command priority field, set as urgent and check bits. The device identifier and time parameters are converted to ASCII code and then summed and modulo 256 to ensure that the data is not tampered with during transmission. After generation, the data packet is temporarily stored in the command buffer, waiting to be sent.

[0066] The power outage dispatch command data packet is sent to the intelligent power distribution unit via the communication interface. The intelligent power distribution unit receives and parses the command content, and controls the corresponding contactor to perform the power outage operation according to the command content, disconnecting the power supply circuit of non-core electrical equipment. Specifically, the communication interface is selected according to the equipment type. Data packets of RS485 devices are sent through the RS485 interface of the main control unit, with a baud rate of 9600bps and even parity. Data packets of KNX devices are forwarded through the KNX gateway. When sending, the system first checks the status of the communication link, such as whether the RS485 bus is idle and whether the KNX gateway is online. If the link is normal, it sends immediately. If there is an abnormality, it waits for 1 second and retryes, with a maximum of 3 retries. The intelligent power distribution unit is installed in the power distribution room of the commercial complex and is responsible for the power supply switching of each device. After receiving the data packet, it first verifies the check bit. If the verification is successful, it parses the content and extracts the contactor number corresponding to the equipment identifier. For example, NC-001 corresponds to contactor K10, NC-002 corresponds to K11, and NC-003 corresponds to K12. It confirms whether the power outage start time has arrived. If not, it enters a waiting state and executes the operation when the time arrives.

[0067] When performing a power-off operation, the intelligent power distribution unit sends a trip signal to the target contactor, a DC 24V voltage signal, lasting for 100 milliseconds. After the contactor coil is energized, the moving contact separates from the stationary contact, cutting off the power supply circuit of the corresponding non-core equipment. For example, after K10 trips, the 380V power supply circuit of the cooling fan is disconnected. After the operation is completed, the contactor sends back a trip success signal, the passive contact closes, and the intelligent power distribution unit returns the execution result (success / failure) to the main control unit through the original communication interface. The main control unit updates the instruction status to executed or failed. If it fails, a retry mechanism is triggered.

[0068] After a power outage, the power supply status of the core communication functional units is monitored in real time. Voltage and current parameters are collected, and the real-time power supply is calculated. The real-time power supply is then compared with a preset safety threshold. Specifically, the monitoring targets are the power supply circuits of core communication functional units, such as the main transmission equipment and baseband processing unit. The monitoring frequency is increased to once every 2 seconds, higher than the normal monitoring frequency, to ensure timely detection of anomalies. When collecting voltage parameters, a voltage sensor installed at the power supply input terminal of the core equipment is used to obtain the line voltage value, such as 380V, with a range of 0-500V and an accuracy of ±0.5%. Current parameters are also collected. In this case, the phase current value is obtained by a current sensor connected in series in the power supply circuit, with a range of 0-50A and an accuracy of ±0.5%, such as 10A. When calculating the real-time power supply, for core equipment with three-phase power supply, such as the main transmission equipment, the average value of the three-phase voltage and the average value of the three-phase current are taken, multiplied by the two, and then multiplied by 1.732 (three-phase power calculation coefficient) to obtain the real-time power (such as average voltage 380V × average current 10A × 1.732 = 6581.6W). For core equipment with single-phase power supply, such as the baseband processing unit, the voltage parameter is directly multiplied by the current parameter, such as 220V × 5A = 1100W.

[0069] The preset safety thresholds are set based on the rated power of the core equipment. The normal operating power threshold is 80%-120% of the rated power. For example, for a device with a rated power of 5000W, the safety threshold is 4000W-6000W. The minimum safe operating threshold is 50% of the rated power. For example, for a 5000W device, the minimum threshold is 2500W. If it is lower than this value, it indicates insufficient power supply. During comparison and analysis, if the real-time power is within the normal threshold range, it is determined that the power supply is normal; if it is lower than the minimum safe operating threshold, it is determined that the power supply is abnormal; if it is between the minimum threshold and the lower limit of the normal threshold, it is determined that the power supply is in warning.

[0070] When the real-time power supply is detected to be less than the safe operating threshold, a protection mechanism is activated to adjust the power supply strategy to ensure the continuous operation of the core communication function unit. Specifically, this includes: the safe operating threshold, i.e., the minimum safe operating threshold, such as 2500W. When the real-time power is lower than this value, such as 2000W for the main transmission equipment, the system immediately activates a three-level protection mechanism. The first level involves rapid switching to the backup power supply. The dual-power transfer switch (with mechanical interlock) in the intelligent power distribution unit receives the switching command and switches from the current main power supply (battery pack) to the backup power supply (diesel generator emergency output) within 0.5 seconds. During the switching process, the core equipment is powered by an uninterruptible power supply (UPS) (ensuring uninterrupted switching). After the switching is completed, the voltage and current of the backup power supply are monitored to confirm stable power supply, such as voltage 380V±5% and current 10A±10%. The second level involves reducing unnecessary functions of the core equipment and sending a power reduction signal to the core communication function unit. The power consumption instructions include, for example, the baseband processing unit suspending the demodulation function of non-real-time data, retaining only the demodulation of real-time power consumption data from smart meters, and reducing its own power consumption, such as from 1100W to 800W; the main transmission equipment reduces the forwarding of redundant data, retaining only the core control signals, and reducing power consumption from 6581.6W to 5000W; the third level initiates load redistribution. If the backup power capacity is limited, according to the priority list of core equipment, such as the main transmission equipment taking priority over the backup transmission equipment, the lower-ranked core equipment is suspended, such as the backup transmission equipment, and its power resources are allocated to the higher-ranked equipment to ensure that the most critical functions, such as smart meter data transmission, are not affected. After adjustment, the real-time power of the core equipment is continuously monitored until it rises above the safe operating threshold. At this time, the protection mechanism is gradually exited, non-essential functions are restored first, then the main power is switched back, and finally the suspended core equipment is restarted to ensure the continuous operation of the core communication function units.

[0071] By standardizing instruction parsing and data packet encapsulation, it ensures that power outage dispatch instructions can be accurately recognized by devices with different communication protocols, improving the accuracy of power outage operations for non-core devices and laying the foundation for power supply assurance for core devices. Adapting to the scenario of multi-protocol device collaborative operation in commercial complexes, the coordinated execution of the intelligent power distribution unit and contactors enables precise disconnection of power supply circuits for non-core devices, reducing power supply chaos caused by improper power outage operations, improving the reliability of dispatch execution, and enabling real-time monitoring of the power supply status of core devices and comparison with safety thresholds to promptly detect power supply anomalies. This avoids problems such as interruption of smart meter data transmission and air conditioning control failure caused by power outages of core devices, ensuring the continuity of core functions.

[0072] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0073] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0074] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A communication master system based on intelligent power supply, characterized in that, include: The power supply monitoring module is used to monitor the mains power supply status of the communication base station. When a mains power interruption is detected, the power switching circuit is automatically controlled to switch the power supply mode to the backup battery power supply mode. The status acquisition module is used to collect real-time data on the state of charge, discharge efficiency, and health status of the backup battery in backup battery power supply mode, and to obtain the battery's remaining capacity, actual discharge capacity, and lifespan indicators. The load receiving module is used to upload the battery's remaining capacity, actual discharge capacity, and lifespan indicators to the communication main control unit, while also receiving load data from the current communication network. The power supply assessment module is used to perform dynamic correlation analysis on battery status data and communication network load data. By constructing multi-source data sequences and calculating relative relationships, it generates dynamic assessment parameters reflecting power supply reliability. This includes analyzing battery status data and communication load demand data to establish a power supply capacity time series and a load demand time series based on a time axis. The power supply capacity time series and the load demand time series are then aligned on the time axis to establish the correspondence between power supply capacity and load demand at the same time, forming a dynamic power supply-load matching relationship table. Based on the dynamic matching table of power supply and load, the estimated remaining power supply time of the battery under the current load demand conditions is calculated. At the same time, the trend of load demand change is predicted and analyzed to generate load demand change trend data. The estimated remaining power supply duration is matched with the load demand change trend data to calculate the power supply sustainability index; based on the numerical range of the power supply sustainability index, the power supply reliability is divided into multiple levels according to preset standards to generate dynamic evaluation parameters for power supply reliability. The power consumption strategy module is used to identify core communication function units and non-core power consumption equipment based on dynamic evaluation parameters and preset strategies, and form a power consumption scheduling strategy table. The instruction generation module is used to generate power outage scheduling instructions for non-core power-consuming equipment based on the power consumption scheduling strategy table when the communication load changes and exceeds a preset threshold. The power supply execution module is used to send power outage dispatch commands to the power supply management component, which then executes the commands and actively cuts off the power supply to non-core electrical equipment to ensure the continuous operation of the core communication function unit.

2. The communication master control system based on intelligent power supply according to claim 1, characterized in that, The system monitors the mains power supply status of the communication base station. When a mains power outage is detected, the automatic power switching circuit switches the power supply mode to backup battery power mode, including: The electrical parameters at the mains input terminal are collected in real time by voltage and current sensors to obtain monitoring data including voltage values; The system judges based on the voltage value in the monitoring data. If it is found that the mains voltage is continuously lower than the rated value, the timing is started and the duration of low voltage is accumulated. When the duration of low pressure reaches the first preset time threshold, a switching trigger signal is generated; Based on the switching trigger signal, the relay in the power switching circuit is controlled to perform a switching operation, switching the power supply mode from mains power supply to backup battery power supply mode.

3. The communication master control system based on intelligent power supply according to claim 2, characterized in that, In backup battery power mode, the system collects real-time data on the backup battery's state of charge, discharge efficiency, and health status to obtain the battery's remaining capacity, actual discharge capacity, and lifespan indicators, including: By using a monitoring device configured on the backup battery pack, the voltage, current and temperature parameters of the backup battery pack are collected in real time to obtain the raw data of battery operation; Based on the current parameters in the original battery operation data, the current value is integrated with time to calculate the real-time remaining capacity of the battery. Based on the real-time remaining capacity, and combined with the currently collected discharge rate and ambient temperature parameters, the actual discharge capacity of the battery under the current operating conditions is calculated. Based on the voltage parameters and cumulative cycle count in the original battery operation data, a comprehensive evaluation is conducted by comparing them with the preset battery capacity change pattern to obtain the battery health status index.

4. The communication master control system based on intelligent power supply according to claim 3, characterized in that, The remaining battery capacity, actual discharge capacity, and lifespan indicators are uploaded to the communication main control unit, while simultaneously receiving load data from the current communication network, including: The real-time remaining battery capacity, actual discharge capacity, and battery health status indicators are formatted and structured to generate a standardized battery status dataset. The battery status dataset is encapsulated using a serial communication interface to generate data frames that conform to the communication protocol, and the encapsulated data frames are sent to the communication master control unit according to a preset period. The communication master control unit receives and analyzes data frames, and at the same time obtains real-time power consumption data of each functional unit from the base station master equipment. It then merges the analyzed battery status data with the received load data to generate a network load status dataset. Time synchronization and correlation analysis are performed on the battery status dataset and the network load status dataset to generate complete status information for power supply capacity assessment and load demand analysis.

5. The communication master control system based on intelligent power supply according to claim 4, characterized in that, Based on dynamic evaluation parameters and pre-set strategies, core communication functional units and non-core power-consuming equipment are identified, forming a power dispatching strategy table, including: Based on dynamic evaluation parameters, a preset evaluation strategy is used to evaluate all electrical equipment in the base station to obtain evaluation results; Based on the assessment results and the importance level of the equipment in the communication network, the transmission equipment and baseband processing unit are classified as core communication functional units; the environmental control equipment and auxiliary heat dissipation equipment are classified as non-core electrical equipment. Based on the equipment classification results, the equipment is sorted according to its key functional parameters to generate a ranking table of equipment importance. Based on the equipment importance priority list, the interruptible power supply characteristics of non-core power-consuming equipment are analyzed, and equipment with interruptible power supply is screened out to generate a list of interruptible power supply equipment. The device priority sequence list and the list of interruptible power supply devices are integrated to form a power dispatching strategy table.

6. The communication master control system based on intelligent power supply according to claim 5, characterized in that, Based on the power consumption scheduling strategy table, when the communication load changes and exceeds a preset threshold, a power outage scheduling instruction is generated for non-core power-consuming equipment, including: Based on the power consumption dispatch strategy table, the load changes of the communication network are monitored in real time to obtain dynamic load change data. The dynamic load change data is compared and analyzed with the preset safety threshold. When the load change causes the power supply reliability index to be less than the safety threshold, the power dispatching process is triggered. Based on the trigger-based power dispatching process, the scheduling algorithm is invoked to process the list of interruptible power supply equipment in the power dispatching strategy table, generating dispatching instructions that include the power outage sequence and power outage time arrangement for non-core power consumption equipment.

7. The communication master control system based on intelligent power supply according to claim 6, characterized in that, The power outage dispatch command is sent to the power management component, which executes the command and actively cuts off the power supply to non-core electrical equipment to ensure the continuous operation of the core communication function unit, including: The power outage dispatch command is analyzed to extract the identification information of non-core power-consuming equipment and the power outage time parameter. Based on the equipment identification information and the power outage time parameter, a power outage dispatch command data packet conforming to the communication protocol is generated. The power outage dispatch command data packet is sent to the intelligent power distribution unit through the communication interface. The intelligent power distribution unit receives and parses the command content, and controls the corresponding contactor to perform the power outage operation according to the command content, disconnecting the power supply circuit of non-core electrical equipment. After the power outage operation is performed, the power supply status of the core communication function unit is monitored in real time, voltage and current parameters are collected, the real-time power supply is calculated, and the real-time power supply is compared and analyzed with the preset safety threshold. When the real-time power supply is detected to be less than the safe operating threshold, the protection mechanism is activated and the power supply strategy is adjusted to ensure the continuous operation of the core communication function unit.

8. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the system as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that, when executed by a processor, implements the system as described in any one of claims 1 to 7.

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