High-voltage power distribution cabinet remote supervision system based on Internet of Things

Abstract

The invention relates to the field of high-voltage power distribution cabinet remote supervision, in particular to a high-voltage power distribution cabinet remote supervision system based on the Internet of Things, which comprises a sensing acquisition module, a power distribution cabinet electric energy optimization module, a temperature and smoke combined monitoring module, a remote control module and the like. The sensing acquisition module adjusts sensor information and acquires electric energy and internal state data; the power distribution cabinet electric energy optimization module obtains an electric energy operation early warning value, divides a load area, marks risk equipment, and optimizes electric energy according to the priority of the equipment; the temperature and smoke combined monitoring module monitors faults through smoke and temperature parameters, the smoke detection unit calculates a smoke hazard value, and the temperature detection unit locates a dangerous part; the remote control module receives the maintenance signal and then obtains the equipment position and distributes a maintenance instruction; according to the invention, accurate optimization of electric power and early warning and accurate positioning of faults are realized, the operation safety of the high-voltage power distribution cabinet is improved, and the method has important significance in the field of operation management of an electric power system.

Description

Technical Field

[0001] The present invention relates to the field of remote supervision of high-voltage distribution cabinets, and specifically to a remote supervision system for high-voltage distribution cabinets based on the Internet of Things. Background Technique

[0002] In modern power systems, high-voltage distribution cabinets, as key nodes for power distribution, their stable operation is crucial for ensuring the reliability and safety of the entire power supply network;

[0003] Currently, high-voltage distribution cabinets face many challenges in power optimization and fault monitoring. In terms of power optimization, traditional distribution cabinets lack the ability to finely analyze and dynamically adjust the power consumption of each load area. With the complexity of the power consumption scenarios of electrical equipment, the power consumption demands in different regions vary significantly. Traditional supervision methods are difficult to obtain these detailed information in real time and cannot perform accurate power optimization scheduling according to the actual situation;

[0004] In terms of fault monitoring, temperature and smoke are important indicators reflecting the internal operating state of high-voltage distribution cabinets, but traditional monitoring means have obvious limitations and are difficult to quickly and accurately locate the specific fault location. It is impossible to know in time whether it is a bus connection point, a switch contact, a transformer winding or other components that have problems. This makes maintenance personnel spend a lot of time and energy in troubleshooting, delaying the fault handling time;

[0005] To solve the above defects, a technical solution is provided now. Summary of the Invention

[0006] To solve the technical problems raised in the above background technique, the present invention provides a remote supervision system for high-voltage distribution cabinets based on the Internet of Things.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The present invention is a remote supervision system for high-voltage distribution cabinets based on the Internet of Things, including a sensing and acquisition module, a power optimization module for distribution cabinets, a combined temperature and smoke monitoring module, a remote control module, an equipment server, and a database.

[0009] The sensing and acquisition module adjusts the information of the connected sensor devices, sets the sensor acquisition frequency to collect the power energy and internal state data of the corresponding load areas of each distribution equipment, and the specific process is as follows:

[0010] A sensing adjustment unit and an acquisition unit are provided in the sensing and acquisition module;

[0011] The sensing adjustment unit is used to adjust the operating states of various types of sensors. The various types of sensors include smoke sensors, temperature sensors, and power sensors. Specifically: obtain the adjusted times YI of various types of sensors, then obtain the installation time points of various types of sensors, calculate the time difference between the installation time point and the current time point to obtain the used duration YQ of various types of sensors, obtain the most recent adjustment time point of various types of sensors, and calculate the unadjusted duration YE by taking the difference between the most recent adjustment time point and the current time point;

[0012] Normalize the adjusted times, used duration, and unadjusted duration and substitute them into the formula for calculation Obtain the sensing adjustment value YD. Among them, P1, P2, and P3 are preset proportionality coefficients, g represents the sensor number, and m represents the total number of sensors. Take the difference between the actual sensing adjustment value of each type of sensor and the preset sensor adjustment value to obtain the adjustment compensation value. If each type of sensor performs self-checking based on the adjustment compensation value, send the self-checking information to the device server for storage;

[0013] The acquisition unit is specifically: set the sensor acquisition frequency to 3 seconds, collect the smoke data of each power distribution device in real time through the smoke sensor, and obtain the smoke parameter values of each power distribution device in real time. Collect the temperature data of each part of each power distribution device in real time through the temperature sensor, and obtain the temperature parameter values of each part of each power distribution device in real time. Collect the power consumption of each power distribution device in real time through the power sensor, and obtain the power consumption of each power distribution device in real time.

[0014] The power distribution cabinet power optimization module obtains the power operation warning value of the corresponding load area of each power distribution device. When the power operation warning value of the corresponding load area of a certain power distribution device is higher than the preset power operation warning range, optimize the power of each load area according to the device priority. The specific process is as follows:

[0015] Obtain the real-time power data of the corresponding load area of each power distribution device, and divide each load area according to the real-time data. The real-time data of the load area includes: total regional power usage duration, total regional power consumption, regional load fluctuation amplitude, load fluctuation frequency, and three-phase unbalance degree;

[0016] Mark the total regional power usage duration, total regional power consumption, regional load fluctuation amplitude, load fluctuation frequency, and three-phase unbalance degree as FY, FI, FR, FG, and FQ respectively, normalize them and substitute them into the formula for calculation Obtain the power operation warning value FCA corresponding to each power distribution device. Among them, Q1, Q2, Q3, and Q4 are the weight factors corresponding to the total regional power usage duration, total regional power consumption, regional load fluctuation amplitude, load fluctuation frequency, and three-phase unbalance degree;

[0017] Extract the preset power operation warning range in the database. When the power operation warning value is lower than the minimum value in the preset power operation warning range, mark the power distribution equipment corresponding to the power operation warning value as a risk-free device; and so on. When the power operation warning value is within the preset power operation warning range, mark the corresponding power distribution equipment as a low-risk device. When the power operation warning value is greater than the maximum value in the preset power operation warning range, mark the corresponding device as a high-risk device;

[0018] Subtract the power operation warning value of each high-risk device from the maximum value in the preset power operation warning range to obtain the power operation difference value of each high-risk device. Arrange the power operation difference values in descending order to obtain a power operation difference value sequence;

[0019] Sort the priority values of each electrical equipment in the load area. Each electrical equipment includes life safety equipment, life support equipment, communication equipment, and entertainment equipment. Specifically: Life safety equipment includes medical equipment, fire-fighting equipment, and emergency equipment, and mark the priority value of life safety equipment as 1; Life support equipment includes refrigerators and cooking equipment, and mark the priority value of life support equipment as 2; and so on. Communication equipment includes mobile phone chargers and computers without working purposes, and mark the priority value of communication equipment as 3; Entertainment equipment includes air conditioners, TVs, and washing machines, and mark the priority value of entertainment equipment as 4. Send each priority value to the equipment server;

[0020] Optimize the load area corresponding to the power operation difference value ranked first. Adjust the equipment power of priority value 4, priority value 3, priority value 2, and priority value 1 in sequence. Specifically: After adjusting the equipment power of priority value 4 in the corresponding load area, collect the power operation warning value in real time and determine whether it exceeds the preset power operation warning range. If it does not exceed, stop adjusting the equipment of priority value 3. If it has exceeded, continue to adjust the equipment power of priority value 3; and so on. If it does not exceed, stop adjusting the equipment of priority value 2. If it has exceeded, continue to adjust the equipment power of priority value 2 until the power operation warning value is less than the maximum value of the preset power operation warning range; Optimize the load area corresponding to the second-ranked power operation difference value in sequence until the power operation warning values of the load areas corresponding to all high-risk devices are less than the maximum value of the preset power operation warning range.

[0021] The temperature-smoke combined monitoring module sets up a dual warning mechanism to monitor the faults of power distribution equipment through smoke parameter values and temperature parameter values. The specific process is as follows:

[0022] Install a video monitoring device inside the power distribution equipment. Inside the combined temperature and smoke monitoring module, there is a smoke detection unit and a temperature detection unit. The smoke detection unit is used to automatically identify the smoke parameter value of the power distribution equipment. If there is smoke, it will trigger a dual warning mechanism, specifically: obtain the duration of the smoke parameter value of each power distribution equipment, mark the moment when the smoke sensor detects smoke as the first time point, and calculate the difference between the first time point and the current time point to obtain the smoke duration HLt;

[0023] Obtain the smoke dispersion image according to the video monitoring device, divide the smoke dispersion image proportionally into several image grids, count the number of smoke image grids in the smoke dispersion image, and obtain the total smoke diffusion area HEm based on the number of smoke image grids;

[0024] Identify the smoke concentration value within the current smoke parameter value, extract the preset smoke concentration value in the database, calculate the difference between the actual smoke concentration value and the preset smoke concentration value to obtain the smoke concentration difference HGn;

[0025] Normalize the smoke duration, the total smoke diffusion area, and the smoke concentration difference, and then substitute them into the formula for calculation Obtain the smoke hazard value HQx of the power distribution equipment, where W1, W2, and W3, i represents the number of the power distribution equipment, and n represents the total number of power distribution equipment; extract the preset smoke hazard threshold of the data center, compare the smoke hazard value with the preset smoke hazard threshold. If the smoke hazard value is greater than the preset smoke hazard value, mark the corresponding power distribution equipment as the equipment to be detected.

[0026] The temperature detection unit is used to analyze the temperature parameter value of the equipment to be detected and determine the dangerous parts of the equipment to be detected, specifically:

[0027] Extract the temperature parameter values of each part of the equipment to be detected. Each part includes the bus connection point, switch contact, fuse, and transformer winding. Set a preset detection period for each part of the equipment to be detected, divide the preset detection period proportionally into several preset detection sub-periods, match the temperature parameter values of each part with each preset detection sub-period to obtain the temperature parameter values corresponding to each preset detection sub-period, obtain the maximum temperature value corresponding to each part and each preset detection sub-period, extract the standard temperature value in the database, calculate the difference between the maximum temperature value of each part of the equipment to be detected and the standard temperature value to obtain each temperature difference value. If the temperature difference value of a certain part is positive, mark the corresponding part as a dangerous part, obtain the dangerous parts of the equipment to be detected, and intelligently generate a maintenance signal and send it to the remote control module.

[0028] The remote control module obtains the location information of the corresponding equipment to be detected according to the received maintenance signal, and remotely allocates maintenance instructions according to the location. The specific process is as follows:

[0029] The remote control module consists of a display screen and a remote operation interface. When receiving a maintenance signal, it sends the maintenance signal to the display screen. The display screen receives the maintenance signal and intelligently obtains the positioning points and numbers of the corresponding devices to be detected through a positioning sensor, and then sends the positioning points and numbers of the devices to be detected to the remote operation interface. The remote operation interface filters the mobile terminal positions of maintenance personnel within the radius according to the positioning points of the devices to be detected, connects the positioning points of the devices to be detected with the mobile terminal positions of each maintenance personnel, marks the maintenance personnel with the shortest straight-line distance as high-quality personnel, and the remote operation interface sends the dangerous parts, positioning points and numbers of the devices to be detected to the high-quality personnel.

[0030] Compared with the prior art, the beneficial effects of the present invention are as follows: by obtaining the total power consumption duration, total power consumption, load fluctuation amplitude, fluctuation frequency and three-phase unbalance degree of the corresponding load areas of each power distribution device to calculate the power operation warning value, it can accurately monitor the power operation status of each load area; when the warning value is higher than the preset range, potential power problems can be detected in time, and measures can be taken in advance to avoid equipment damage or power outage accidents caused by problems such as power overload or imbalance, ensuring the stable operation of the power system. Optimize the electric energy of the load area according to the equipment priority, give priority to ensuring the power supply of life safety equipment, ensure that these key equipment can operate normally in case of emergency, and reasonably distribute power to life support equipment, communication equipment and entertainment equipment, improving the utilization efficiency of power resources;

[0031] The smoke detection unit and temperature detection unit in the temperature-smoke combined monitoring module can real-time monitor the smoke parameter values and temperature parameter values of the power distribution equipment. By comprehensively grasping the equipment operation status through the smoke duration, diffusion total area, concentration difference and the temperature changes in different parts and time periods, abnormal situations can be detected in time, effectively preventing the occurrence of accidents such as fires and equipment overheating damage.

[0032] Intelligent dual warning and equipment marking: When the dual warning mechanism detects smoke, it can accurately calculate the smoke hazard value and compare it with the preset threshold, and mark the equipment exceeding the threshold as the equipment to be detected. At the same time, the temperature detection unit can further analyze the equipment to be detected, determine the dangerous parts, provide a clear direction for subsequent maintenance work, shorten the troubleshooting time and improve the maintenance efficiency. Brief Description of the Drawings

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. The following drawings are not deliberately drawn to scale in actual size, and the focus is on showing the gist of the present invention.

[0034] Figure 1 It is the principle block diagram of the present invention. Detailed Embodiments

[0035] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only partial embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts also belong to the scope of protection of the present invention.

[0036] Please refer to Figure 1 As shown, the present invention is a remote monitoring system for high-voltage distribution cabinets based on the Internet of Things, including a sensing and acquisition module, a power optimization module for distribution cabinets, a combined temperature and smoke monitoring module, a remote control module, a device server, and a database.

[0037] The sensing and acquisition module adjusts the information of the connected sensor devices, sets the sensor acquisition frequency, and acquires the power and internal state data of the corresponding load areas of each distribution device. The specific process is as follows:

[0038] A sensing adjustment unit and an acquisition unit are provided in the sensing and acquisition module;

[0039] The sensing adjustment unit is used to adjust the operating states of various types of sensors. The various types of sensors include smoke sensors, temperature sensors, and power sensors. Specifically: obtain the adjusted times YI of various types of sensors, then obtain the installation time points of various types of sensors, calculate the time difference between the installation time point and the current time point to obtain the used duration YQ of various types of sensors, obtain the most recent adjustment time point of various types of sensors, and calculate the difference between the most recent adjustment time point and the current time point to obtain the unadjusted duration YE;

[0040] Normalize the adjusted times, used duration, and unadjusted duration and substitute them into the formula for calculation Obtain the sensing adjustment value YD. Among them, P1, P2, and P3 are preset proportional coefficients, g represents the sensor number, and m represents the total number of sensors. Calculate the difference between the actual sensing adjustment values of various types of sensors and the preset sensor adjustment values to obtain the adjustment compensation value. If various types of sensors perform self-checking based on the adjustment compensation value and send the self-checking information to the device server for storage;

[0041] The acquisition unit is specifically: set the sensor acquisition frequency to 3 seconds, collect the smoke data of each distribution device in real time through the smoke sensor, obtain the smoke parameter values of each distribution device in real time, collect the temperature data of each part of each distribution device in real time through the temperature sensor, obtain the temperature parameter values of each part of each distribution device in real time, collect the power consumption of each distribution device in real time through the power sensor, and obtain the power consumption of each distribution device in real time.

[0042] The power optimization module of the distribution cabinet obtains the power operation warning values of the load areas corresponding to each distribution device. When the power operation warning value of the load area corresponding to a certain distribution device is higher than the preset power operation warning range, the power of each load area is optimized according to the device priority. The specific process is as follows:

[0043] Obtain the real-time power data of the load areas corresponding to each distribution device, and divide each load area according to the real-time data. The real-time data of the load area includes: total regional power consumption duration, total regional power consumption, regional load fluctuation range, load fluctuation frequency, and three-phase unbalance degree;

[0044] Mark the total regional power consumption duration, total regional power consumption, regional load fluctuation range, load fluctuation frequency, and three-phase unbalance degree as FY, FI, FR, FG, and FQ respectively, perform normalization processing and substitute them into the formula for calculation Obtain the power operation warning value FCA corresponding to each distribution device, where Q1, Q2, Q3, and Q4 are the weight factors corresponding to the total regional power consumption duration, total regional power consumption, regional load fluctuation range, load fluctuation frequency, and three-phase unbalance degree;

[0045] Extract the preset power operation warning range in the database. When the power operation warning value is lower than the minimum value in the preset power operation warning range, mark the distribution device corresponding to the power operation warning value as a risk-free device; and so on. When the power operation warning value is within the preset power operation warning range, mark the corresponding distribution device as a low-risk device. When the power operation warning value is greater than the maximum value in the preset power operation warning range, mark the corresponding device as a high-risk device;

[0046] Calculate the difference between the power operation warning value of each high-risk device and the maximum value in the preset power operation warning range to obtain the power operation difference value of each high-risk device. Arrange the power operation difference values from largest to smallest to obtain a power operation difference value sequence;

[0047] Sort the priority values of each electrical equipment in the load area. Each electrical equipment includes life safety equipment, life support equipment, communication equipment, and entertainment equipment. Specifically: life safety equipment includes medical equipment, fire-fighting equipment, and emergency equipment, and mark the priority value of life safety equipment as 1; life support equipment includes refrigerators and cooking equipment, and mark the priority value of life support equipment as 2; and so on. Communication equipment includes mobile phone chargers and computers without working purposes, and mark the priority value of communication equipment as 3; entertainment equipment includes air conditioners, TVs, and washing machines, and mark the priority value of entertainment equipment as 4. Send each priority value to the device server;

[0048] Optimize the load area corresponding to the first-ranked power operation difference, and adjust the device power from priority value 4, priority value 3, priority value 2, and priority value 1 in sequence. Specifically: after adjusting the device power with priority value 4 in the corresponding load area, collect the power operation warning value in real time and determine whether it exceeds the preset power operation warning range. If it does not exceed, stop adjusting the device with priority value 3. If it has exceeded, continue to adjust the device power with priority value 3; and so on. If it does not exceed, stop adjusting the device with priority value 2. If it has exceeded, continue to adjust the device power with priority value 2 until the power operation warning value is less than the maximum value of the preset power operation warning range; optimize the load area corresponding to the second-ranked power operation difference in sequence until the power operation warning values of the load areas corresponding to all high-risk devices are less than the maximum value of the preset power operation warning range.

[0049] The temperature and smoke combined monitoring module sets up a dual warning mechanism to monitor the faults of power distribution equipment through the smoke parameter value and the temperature parameter value. The specific process is as follows:

[0050] Install video monitoring equipment inside the power distribution equipment. The temperature and smoke combined monitoring module is internally provided with a smoke detection unit and a temperature detection unit. The smoke detection unit is used to automatically identify the smoke parameter value of the power distribution equipment. If there is smoke, the dual warning mechanism is triggered. Specifically: obtain the duration of the smoke parameter value of each power distribution equipment, mark the moment when the smoke sensor contacts the smoke as the first time point, and calculate the smoke duration HLt by subtracting the first time point from the current time point;

[0051] Obtain the smoke divergence image according to the video monitoring equipment, equally divide the smoke divergence image into several image grids, count the number of smoke image grids in the smoke divergence image, and obtain the total smoke diffusion area HEm based on the number of smoke image grids;

[0052] Identify the smoke concentration value within the current smoke parameter value, extract the preset smoke concentration value in the database, and calculate the difference between the actual smoke concentration value and the preset smoke concentration value to obtain the smoke concentration difference HGn;

[0053] Normalize the smoke duration, the total smoke diffusion area, and the smoke concentration difference and substitute them into the formula for calculation Obtain the smoke hazard value HQx of the power distribution equipment, where W1, W2, and W3, i represents the number of the power distribution equipment, and n represents the total number of power distribution equipment; extract the preset smoke hazard threshold of the data center, compare the smoke hazard value with the preset smoke hazard threshold. If the smoke hazard value is greater than the preset smoke hazard value, mark the corresponding power distribution equipment as the equipment to be detected.

[0054] The temperature detection unit is used to analyze the temperature parameter values of the device to be detected and determine the dangerous parts of the device to be detected. Specifically:

[0055] Extract the temperature parameter values of each part of the device to be detected. Each part includes bus connection points, switch contacts, fuses, and transformer windings. Set a preset detection period for each part of the device to be detected, and divide the preset detection period into several preset detection sub-periods in a geometric progression. Match the temperature parameter values of each part with each preset detection sub-period to obtain the temperature parameter values corresponding to each preset detection sub-period. Obtain the maximum temperature values corresponding to each preset detection sub-period of each part, extract the standard temperature values in the database, subtract the standard temperature values from the maximum temperature values of each part of the device to be detected to obtain the temperature difference values. If the temperature difference value of a certain part is positive, mark the corresponding part as a dangerous part, obtain the dangerous parts of the device to be detected, and intelligently generate a maintenance signal and send it to the remote control module.

[0056] The remote control module obtains the location information of the corresponding device to be detected according to the received maintenance signal, and remotely allocates maintenance instructions according to the location. The specific process is as follows:

[0057] The remote control module consists of a display screen and a remote operation interface. After receiving the maintenance signal, it sends the maintenance signal to the display screen. The display screen receives the maintenance signal and intelligently obtains the positioning point and number of the corresponding device to be detected through a positioning sensor, and sends the positioning point and number of the device to be detected to the remote operation interface. The remote operation interface screens the mobile terminal positions of maintenance personnel within the radius according to the positioning point of the device to be detected, connects the positioning point of the device to be detected with the mobile terminal positions of each maintenance personnel, marks the maintenance personnel with the shortest straight-line distance as high-quality personnel, and the remote operation interface sends the dangerous parts, positioning point, and number of the device to be detected to the high-quality personnel.

[0058] The above is the description of the present invention and should not be considered as a limitation thereof. Although several exemplary embodiments of the present invention have been described, those skilled in the art will easily understand that many modifications can be made to the exemplary embodiments without departing from the novel teachings and advantages of the present invention. Therefore, all such modifications are intended to be included within the scope of the present invention as defined by the claims. It should be understood that the above is the description of the present invention and should not be considered as limited to the specific embodiments disclosed, and the modifications to the disclosed embodiments and other embodiments are intended to be included within the scope of the appended claims. The present invention is defined by the claims and their equivalents.

Claims

1. A remote monitoring system for high-voltage distribution cabinets based on the Internet of Things, including a sensor acquisition module, a temperature and smoke joint monitoring module, a remote control module, a device server and a database, characterized in that: It also includes a power distribution cabinet power optimization module; The sensor acquisition module is equipped with a sensor adjustment unit and an acquisition unit to adjust the information of the connected sensor equipment, and set the sensor acquisition frequency to collect the power and internal status data of the corresponding load area of ​​each distribution equipment; the temperature and smoke joint monitoring module is equipped with a smoke detection unit and a temperature detection unit, and a dual early warning mechanism is set to monitor the fault of the distribution equipment through the smoke parameter value and the temperature parameter value; The power optimization module of the power distribution cabinet obtains the power operation warning value of the load area corresponding to each distribution equipment, specifically: The real-time data of electric energy in the load area corresponding to each power distribution device is obtained, and each load area is divided according to the real-time data. The real-time data of the load area includes: total power consumption time of the area, total power consumption of the area, regional load fluctuation amplitude, load fluctuation frequency and three-phase imbalance; The total power consumption time, total power consumption, load fluctuation amplitude, load fluctuation frequency and three-phase imbalance degree of the region are marked as FY, FI, FR, FG and FQ respectively, and then normalized and substituted into the formula for calculation The electric energy operation warning value FCA corresponding to each distribution equipment is obtained, where Q1, Q2, Q3 and Q4 are the weight factors corresponding to the total power consumption time of the region, the total power consumption of the region, the regional load fluctuation amplitude, the load fluctuation frequency and the three-phase imbalance.

2. According to the Internet of Things-based high-voltage distribution cabinet remote monitoring system of claim 1, it is characterized in that: In the power distribution cabinet power optimization module, when the power operation warning value of a certain power distribution equipment corresponding to the load area is higher than the preset power operation warning range, the corresponding equipment is marked and the power operation difference sequence is obtained. The specific process is as follows: Extract the preset power operation warning range in the database. When the power operation warning value is lower than the minimum value in the preset power operation warning range, mark the distribution equipment corresponding to the power operation warning value as risk-free equipment. By analogy, when the power operation warning value is within the preset power operation warning range, the corresponding power distribution equipment is marked as low-risk equipment; when the power operation warning value is greater than the maximum value in the preset power operation warning range, the corresponding equipment is marked as high-risk equipment; The electric energy operation warning value of each high-risk equipment is subtracted from the maximum value in the preset electric energy operation warning range to obtain the electric energy operation difference of each high-risk equipment. The electric energy operation difference is arranged from large to small to obtain the electric energy operation difference sequence.

3. The high-voltage distribution cabinet remote monitoring system based on the Internet of Things according to claim 1 is characterized in that: The power distribution cabinet power optimization module optimizes the power of each load area according to the equipment priority. The specific optimization process is as follows: Priority values ​​are sorted for each electrical equipment in the load area. Each electrical equipment includes life safety equipment, life support equipment, communication equipment and entertainment equipment. Specifically, life safety equipment includes medical equipment, fire fighting equipment and emergency equipment, and the priority value of life safety equipment is marked as 1; life support equipment includes refrigerators and cooking equipment, and the priority value of life support equipment is marked as 2; and so on, communication equipment includes mobile phone chargers and computers without work purposes, and the priority value of communication equipment is marked as 3; entertainment equipment includes air conditioners, televisions and washing machines, and the priority value of entertainment equipment is marked as 4. Each priority value is sent to the device server; The load area corresponding to the first-ranked electric operation difference is optimized, and the power of the equipment with priority value 4, priority value 3, priority value 2 and priority value 1 are adjusted in turn. Specifically, after adjusting the power of the equipment with priority value 4 in the corresponding load area, the electric energy operation warning value is collected in real time, and it is determined whether it exceeds the preset electric energy operation warning range. If it does not exceed, stop adjusting the equipment with priority value 3; if it has exceeded, continue to adjust the power of the equipment with priority value 3; and so on. If it does not exceed, stop adjusting the equipment with priority value 2; if it has exceeded, continue to adjust the power of the equipment with priority value 2 until the electric energy operation warning value is less than the maximum value of the preset electric energy operation warning range; optimize the load area corresponding to the second-ranked electric operation difference in turn until the electric energy operation warning value of the load area corresponding to all high-risk equipment is less than the maximum value of the preset electric energy operation warning range.

4. The high-voltage distribution cabinet remote monitoring system based on the Internet of Things according to claim 1 is characterized in that: The temperature and smoke joint monitoring module sets up a dual early warning mechanism to monitor the faults of the power distribution equipment through the smoke parameter value and the temperature parameter value. The specific process is as follows: Video surveillance equipment is installed inside the power distribution equipment to automatically identify the smoke parameter values ​​of the power distribution equipment. If there is smoke, a dual warning mechanism is triggered. Specifically, the duration of the smoke parameter values ​​of each power distribution equipment is obtained, the moment when the smoke sensor contacts the smoke is marked as the first time point, and the first time point is subtracted from the current time point to obtain the smoke duration HLt; Obtain a smoke diffusion image according to a video surveillance device, divide the smoke diffusion image into a number of image squares in equal proportion, count the number of smoke image squares in the smoke diffusion image, and obtain the total smoke diffusion area HEm based on the number of smoke image squares; Identify the smoke concentration value within the current smoke parameter value, extract the preset smoke concentration value in the database, and subtract the actual smoke concentration value from the preset smoke concentration value to obtain the smoke concentration difference value HGn; The smoke duration, total smoke diffusion area and smoke concentration difference are normalized and entered into the formula for calculation Obtain the smoke hazard value HQx of the distribution equipment, where W1, W2 and W3, i represents the number of the distribution equipment, and n represents the total number of distribution equipment; extract the preset smoke hazard threshold of the data center, compare the smoke hazard value with the preset smoke hazard threshold, and if the smoke hazard value is greater than the preset smoke hazard value, mark the corresponding distribution equipment as a device to be detected.

5. The high-voltage power distribution cabinet remote monitoring system based on the Internet of Things according to claim 4 is characterized in that: The temperature detection unit is used to analyze the temperature parameter value of the device to be detected and determine the dangerous parts of the device to be detected, specifically: Extract the temperature parameter values ​​of each part of the equipment to be detected, and each part includes the busbar connection point, switch contact, fuse and transformer winding. Set a preset detection period for each part of the equipment to be detected, divide the preset detection period into a number of preset detection sub-time periods in equal proportion, match the temperature parameter values ​​of each part with each preset detection sub-time period, obtain the temperature parameter value corresponding to each preset detection sub-time period, obtain the maximum temperature corresponding to each preset detection sub-time period of each part, extract the standard temperature value of the database, and subtract the maximum temperature value and the standard temperature value of each part of the equipment to be detected to obtain each temperature difference value. If the temperature difference value of a part is a positive number, the corresponding part is marked as a dangerous part, and the dangerous part of the equipment to be detected is obtained, and a maintenance signal is intelligently generated and sent to the remote control module.

6. The high-voltage power distribution cabinet remote monitoring system based on the Internet of Things according to claim 1 is characterized in that: The remote control module obtains the location information of the corresponding device to be detected according to the received maintenance signal, and remotely distributes maintenance instructions according to the location. The specific process is as follows: The remote control module consists of a display screen and a remote operation interface. When a maintenance signal is received, the maintenance signal is sent to the display screen. The display screen receives the maintenance signal and intelligently obtains the positioning point and number of the corresponding equipment to be detected through the positioning sensor, and sends the positioning point and number of the equipment to be detected to the remote operation interface. The remote operation interface filters the mobile terminal positions of maintenance personnel within the radius according to the positioning point of the equipment to be detected, connects the positioning point of the equipment to be detected and the mobile terminal positions of each maintenance personnel, marks the maintenance personnel with the closest straight-line distance as high-quality personnel, and the remote operation interface sends the dangerous parts, positioning points and numbers of the equipment to be detected to the high-quality personnel.

7. The high-voltage power distribution cabinet remote monitoring system based on the Internet of Things according to claim 1 is characterized in that: The sensor adjustment unit is used to adjust the operating status of various types of sensors, including smoke sensors, temperature sensors and electric energy sensors, specifically: Get the number of times each type of sensor has been adjusted YI, then get the installation time of each type of sensor, calculate the time difference between the installation time and the current time to get the usage time YQ of each type of sensor, get the most recent adjustment time of each type of sensor, and calculate the difference between the most recent adjustment time and the current time to get the unadjusted time YE; Normalize the adjusted times, used duration, and unadjusted duration and substitute them into the formula for calculation The sensor adjustment value YD is obtained, where P1, P2 and P3 are preset proportional coefficients, g represents the sensor number, and m represents the total number of sensors. The actual sensor adjustment value of each type of sensor is subtracted from the preset sensor adjustment value to obtain the adjustment compensation value. If each type of sensor performs self-test according to the adjustment compensation value, the self-test information is sent to the device server for storage.

8. The high-voltage distribution cabinet remote monitoring system based on the Internet of Things according to claim 7 is characterized in that: The acquisition unit is specifically: Set the sensor collection frequency to 3 seconds. Use the smoke sensor to collect the smoke data of each distribution equipment in real time, and obtain the smoke parameter value of each distribution equipment in real time. Use the temperature sensor to collect the temperature data of each part of each distribution equipment in real time, and obtain the temperature parameter value of each part of each distribution equipment in real time. Use the electric energy sensor to collect the power consumption of each distribution equipment in real time, and obtain the power consumption of each distribution equipment in real time.

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