Intelligent state management and control system and method for indoor distribution power supply

Abstract

The invention discloses an intelligent state management and control system and method for an indoor distribution power supply, relates to the technical field of intelligent state analysis, and solves the problems that in equipment state analysis, equipment is managed and controlled only according to the current heating condition, the heating condition is difficult to analyze in advance, and the equipment is difficult to manage and control in advance. And the technical problem that the heating influence caused by environmental factors cannot act on the equipment immediately is neglected. According to the method, the reference output power of each time period is obtained by analyzing the historical output power, the standard output power of the next time period is obtained by analyzing the target data, and the environmental influence factor is obtained by analyzing the environmental information; performing influence analysis on the equipment temperature based on the environmental influence factor and the standard output power to obtain the equipment temperature of the next time period, and managing and controlling the equipment based on the equipment temperature of the next time period; according to the invention, fault risks and potential safety hazards caused by heating of equipment can be reduced through predictive management and control.

Description

Technical Field

[0001] The present invention belongs to the field of equipment management, and relates to a state intelligent analysis technology, and specifically to a state intelligent control system and method for indoor power supply. Background Art

[0002] With the development of communication technology, indoor distributed systems have been widely used in various buildings. Indoor distributed systems are mainly used to solve the problem of weak mobile phone signals in closed environments such as large buildings and underground spaces. By evenly distributing the base station signals to each area that needs to be covered, the communication quality and service level are improved. Indoor distributed power supply equipment is responsible for supplying power to signal amplifiers, combiners, antennas and other equipment distributed in different locations to ensure the normal operation of the entire system.

[0003] At present, most of the intelligent status control systems for indoor power supplies, in the equipment status analysis, only control the equipment according to the current heating conditions. It is difficult to analyze the heating conditions in advance and control the equipment in advance. Failure to control in advance may result in untimely control, which further leads to untimely cooling of the equipment, bringing certain safety hazards to the operation of the indoor power supply equipment. At the same time, most of the intelligent status control systems for indoor power supplies, in the equipment status analysis, ignore the heating effects caused by environmental factors and cannot act immediately on the equipment, resulting in inaccurate data analysis, which may cause the system to incorrectly judge the equipment status and increase the risk of fire or equipment damage.

[0004] Therefore, the present invention discloses an intelligent state control system and method for indoor power supply, which are used to solve the above technical problems. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an intelligent state control system and method for indoor power supply, which is used to solve the technical problems that in the equipment state analysis, the equipment is only controlled according to the current heating condition, it is difficult to analyze the heating condition in advance and control the equipment in advance, and the heating effect caused by environmental factors is ignored and cannot act on the equipment immediately. The present invention solves the above problems by analyzing the historical output power to obtain the reference output power of each time period, analyzing the target data to obtain the standard output power of the next time period, analyzing the environmental information to obtain the environmental impact factor, analyzing the impact of the environmental impact factor and the standard output power on the equipment temperature to obtain the equipment temperature of the next time period, and controlling the equipment based on the equipment temperature of the next time period.

[0006] To achieve the above-mentioned object, the first aspect of the present invention provides an intelligent state control system for indoor power supply, comprising: an intelligent analysis module, and an information acquisition module, a state control module and a database connected thereto; The information acquisition module is used to plan a day into several time periods and obtain basic information and environmental information of the indoor power supply equipment in the current time period; wherein the basic information includes equipment temperature and output power; the environmental information includes characteristic values ​​of ambient temperature, ambient humidity and ambient wind speed; The intelligent analysis module is used to analyze the historical output power to obtain the reference output power of each time period; mark the reference output power of the next time period and the output power and reference output power of the current time period as target data, analyze the target data to obtain the standard output power of the next time period; analyze the environmental information to obtain the environmental impact factor, and analyze the impact of the environmental impact factor and the standard output power on the device temperature to obtain the device temperature of the next time period; The state control module is used to control the device based on the device temperature in the next time period.

[0007] Preferably, the planning of a day into several time periods includes: Extract the area where the current indoor power supply equipment is located, and the area type of the area; extract the peak time period of use of the indoor power supply equipment corresponding to the area type; wherein the area types include residential areas, office areas, commercial areas, transportation hub areas and public facilities areas; the peak time period is obtained by manual setting; Extracting the initial time length CH of the time period from the database, extracting the non-peak time period in sequence, and judging whether the extracted non-peak time period can be evenly divided into a number of time periods based on the initial time length CH; if yes, evenly dividing the extracted non-peak time period into a number of time periods based on the initial time length CH; if no, obtaining the maximum number of complete time periods that can be divided in the extracted non-peak time period, and evenly dividing the non-peak time period into a number of time periods based on the maximum number; wherein the initial time length CH is obtained by manual setting; Extract peak time periods in sequence, obtain the dynamic time length DH based on the formula DH=α×CH, and determine whether the extracted peak time period can be evenly divided into several time periods based on the dynamic time length DH; if yes, evenly divide the extracted peak time period into several time periods based on the dynamic time length DH; if no, obtain the maximum number of complete time periods that can be divided in the extracted peak time period, and evenly divide the peak time period into several time periods based on the maximum number; wherein α is the proportional adjustment coefficient, and the value range of α is (0,1]; The time periods are arranged from the beginning to the end according to the time, and a day is divided into several time periods.

[0008] It is worth noting that the time period planned in the present invention is planned according to the area type, because the number of people in different types of areas at the same time is different, and thus the network usage is also different, which will further cause the output power of the indoor power supply equipment to be different; planning the time period according to the area type is conducive to more detailed acquisition of the output power of the indoor power supply equipment at different locations, providing data support for subsequent analysis.

[0009] Preferably, the obtaining of basic information and environmental information of the indoor power supply equipment in the current time period includes: Extract the time period in which the current time is located, and mark the time period as the current time period; obtain the temperature of the indoor power supply equipment at the current time through a temperature sensor, and mark the temperature as the equipment temperature; obtain the real-time output power of the indoor power supply equipment in the current time period through a power monitor, calculate the average value of the real-time output power to obtain the average power, and mark the average power as the output power; in the current time period, obtain several ambient temperatures through a temperature sensor, obtain several ambient humidity through a humidity sensor, obtain several ambient wind speeds through an anemometer, and calculate the ambient temperature, ambient humidity and ambient wind speed to obtain characteristic values.

[0010] Preferably, the calculating of the ambient temperature, ambient humidity and ambient wind speed to obtain the characteristic value includes: The environmental humidity is divided into the H1 group, and the environmental wind speed is divided into the H2 group; the maximum value ZDi, percentile BSi, and mode ZSi of each group of data are extracted; the characteristic value TZi of each group is obtained based on the formula TZi=(B1i×ZDi+B2i×BSi+ZSi) / 2; wherein, i represents the sequence number of each group, when i is 1, it represents the relevant data of the H1 group, and when i is 2, it represents the relevant data of the H2 group; the percentile of the percentile BSi is obtained by manual setting; B1i and B2i are both proportional adjustment coefficients greater than 0, and B1i+B2i=1, B1i>B2i; The ambient temperatures are sorted according to the acquisition time, and the ambient temperatures are extracted at fixed intervals. The extracted ambient temperatures are marked as detection temperatures CWj. Among two adjacent detection temperatures CWj, the adjacent temperature difference LCj is obtained by subtracting the next detection temperature CWj+1 from the previous detection temperature CWj. The proportion BL of the number of adjacent temperature differences LCj less than 0 to the total number of adjacent temperature differences LCj is counted, and the maximum value ZD3, percentile BS3, and mode ZS3 of the ambient temperatures are extracted. When i is 3, the characteristic value TZ3 of the ambient temperature is obtained based on the formula TZ3=exp(ρ×BL)×(B13×ZD3+B23×BS3+ZS3) / 2. Among them, j is the order of extraction. ρ is a proportional adjustment coefficient greater than 0, and the value range of ρ is (0,1).

[0011] It is worth noting that the present invention uses percentiles when calculating eigenvalues. This value is added because: the system can set different percentiles according to the needs of the device, so that the acquired eigenvalues ​​can adapt to different devices, increasing the flexibility of the system.

[0012] Preferably, the analyzing the historical output power to obtain the reference output power in each time period includes: Extract the historical output power of each time period, and divide the historical output power into several data sets according to the time period; obtain the variance of the output power in each data set, and judge whether the variance is less than the corresponding definition threshold; if yes, retain the output power of the data set; if no, remove the output power with the largest difference from the mode in the data set, and re-judge the variance until the variance of the data set is less than the corresponding definition threshold, and retain the remaining output power; wherein the definition threshold is obtained through experience; The output powers retained in each data set are averaged to obtain an average output power, and the average output power is marked as a reference output power for the corresponding time period.

[0013] It is worth noting that the present invention uses a threshold judgment method when obtaining the reference output power of each time period. In the threshold judgment, the data with large fluctuations in the data set is removed, which increases the accuracy of the calculated reference output power and provides data support for the subsequent calculation of the standard output power.

[0014] Preferably, analyzing the target data to obtain the standard output power for the next time period includes: Extract the reference output power NCL of the next time period, as well as the output power SL and reference output power DCL of the current time period; obtain the standard output power BSL of the next time period based on the formula BSL=β×NCL×SL / DCL; where β is a proportional adjustment coefficient greater than 0, and the value range of β is (0,2].

[0015] It is worth noting that the present invention does not take the reference output power of the next time period as the standard value, but analyzes the relationship between the output power of the current time period and the reference output power to further obtain the standard output power of the next time period; this is because, in the present invention, the time distance between two adjacent time periods is not large, and when the number of people in the area where the equipment is located fluctuates drastically in a short period of time due to special events, this will cause the reference output power to be inaccurate. Using the output power of the current time period and the reference output power as references to adjust the reference output power of the next time period can effectively avoid the abnormal situation of inaccurate standard output power obtained from the analysis caused by such drastic fluctuations in the number of people.

[0016] Preferably, the environmental information is analyzed to obtain environmental impact factors, including: A1: extract the characteristic value TZ1 of the ambient humidity, and determine whether the characteristic value TZ1 exceeds the standard ambient humidity BHS; if yes, issue a message that the characteristic value TZ1 of the ambient humidity exceeds the standard; if no, do not perform a reminder operation; A2: extract the characteristic value TZ2 of the ambient wind speed, and determine whether the characteristic value TZ2 exceeds the standard ambient wind speed BFS; if yes, issue a message that the characteristic value TZ2 of the ambient wind speed exceeds the standard; if no, do not perform a reminder operation; A3: extract the characteristic value TZ3 of the ambient temperature, and determine whether the characteristic value TZ3 exceeds the standard ambient temperature BHW; if yes, issue a message indicating that the characteristic value TZ3 exceeds the standard; if no, do not perform any reminder operation; wherein the standard ambient humidity BHS, the standard ambient wind speed BFS and the standard ambient temperature BHW are all obtained through experience; A4: The environmental impact factor HYZ for the current time period is obtained based on the formula HYZ=δ / exp((TZ2-BFS) / BFS)×(μ1×(TZ1-BHS) / BHS+μ2×(TZ3-BHW) / BHW); wherein δ is an amplitude adjustment coefficient greater than 0; μ1 and μ2 are both proportional adjustment coefficients greater than 0, and μ1+μ2=1, μ1<μ2.

[0017] It is worth noting that the effects of ambient temperature, ambient humidity and ambient wind speed on device heating are delayed, that is, environmental factors do not immediately affect the device, but the effects require a certain amount of time to accumulate before they act on the device; and because the time period set by the present invention is relatively short, the environmental impact factors obtained by the present invention will not affect the device heating in this time period, but will be superimposed on the subsequent time periods. The present invention takes into account the delayed effect of environmental factors on device heating, and can increase the accuracy of result analysis.

[0018] It is worth noting that when analyzing the environmental factors that have an impact on the heating of the device, the present invention not only takes into account the impact of ambient temperature and ambient humidity on the heating of the device, but also takes into account the impact of ambient wind speed on the heating of the device. This is because: when there is a certain wind speed around the device, the wind will drive the circulation of air, so that the temperature and humidity around the device are reduced. Therefore, the impact of ambient wind speed on the heating of the device is a weakening effect. That is to say, when the wind speed does not exceed normal conditions, the greater the wind speed, the more beneficial it is to the heat dissipation of the device. The present invention uses the δ / exp((TZ2-BFS) / BFS) function to express the weakening effect of wind speed on the heating of the device, which increases the adaptability and practicality of the system.

[0019] Preferably, the performing an impact analysis on the device temperature based on the environmental impact factor and the standard output power to obtain the device temperature in the next time period includes: Extract the environmental impact factor HYZ and the output power SL of the equipment in the current time period, as well as the standard output power BSL in the next time period; The device temperature SWn+1 of the next time period is obtained based on the formula SWn+1=(BSL-SL)×LR+(HYZ-SHYZ)×HR+SWn; wherein SHYZ is the environmental impact factor of the previous time period, SW is the device temperature; LR is the temperature change caused by the manually set unit output power change, and HR is the temperature change caused by the manually set unit environmental impact factor change.

[0020] Preferably, the controlling of the device based on the device temperature in the next time period includes: E1: extract the device temperature SWn+1 of the next time period, and determine whether the device temperature SWn+1 exceeds the temperature threshold 1; if yes, issue an alarm and cut off the power supply to the current room power supply device for protection; if no, jump to E2; E2: Determine whether the device temperature SWn+1 is lower than temperature threshold 2; if yes, do nothing; if no, reduce the output power of the current indoor power supply device to a fixed power; wherein the fixed power is obtained through experience; temperature threshold 1 and temperature threshold 2 are obtained through manual setting, and temperature threshold 1 is greater than temperature threshold 2.

[0021] A second aspect of the present invention provides a method for intelligently controlling the state of a room power supply, comprising the following steps: S1: Plan a day into several time periods, and obtain basic information and environmental information of the indoor power supply equipment in the current time period; S2: Analyze the historical output power to obtain the reference output power of each time period; mark the reference output power of the next time period and the output power and reference output power of the current time period as target data, analyze the target data to obtain the standard output power of the next time period; analyze the environmental information to obtain the environmental impact factor, and analyze the impact of the environmental impact factor and the standard output power on the device temperature to obtain the device temperature of the next time period; S3: Control the device based on the device temperature in the next time period.

[0022] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention obtains the reference output power of each time period by analyzing the historical output power, obtains the standard output power of the next time period by analyzing the target data, obtains the standard output power of the next time period by analyzing the environmental information, obtains the environmental impact factor, performs an impact analysis on the device temperature based on the environmental impact factor and the standard output power to obtain the device temperature of the next time period, and manages the device based on the device temperature of the next time period, thereby solving the technical problems that in the device status analysis, the device is only managed based on the current heating condition, it is difficult to analyze the heating condition in advance and manage the device in advance, and the heating effect caused by environmental factors is ignored and cannot act on the device immediately; the present invention can reduce the failure risk and safety hazards caused by equipment heating through predictive management and control.

[0023] 2. The present invention does not take the reference output power of the next time period as the standard value, but analyzes the relationship between the output power of the current time period and the reference output power to further obtain the standard output power of the next time period; this is because, in the present invention, the time distance between two adjacent time periods is not large, and when the number of people in the area where the equipment is located fluctuates dramatically in a short period of time due to special events, this will cause the reference output power to be inaccurate. By taking the output power of the current time period and the reference output power as references to adjust the reference output power of the next time period, it can effectively avoid the abnormal situation of inaccurate standard output power obtained by analysis caused by such drastic fluctuations in the number of people.

[0024] 3. When analyzing the environmental factors that have an impact on the heating of the equipment, the present invention not only takes into account the impact of ambient temperature and ambient humidity on the heating of the equipment, but also takes into account the impact of ambient wind speed on the heating of the equipment. This is because: when there is a certain wind speed around the equipment, the wind will drive the circulation of air, so that the temperature and humidity around the equipment are reduced. Therefore, the impact of ambient wind speed on the heating of the equipment is a weakening effect. That is to say, when the wind speed does not exceed normal conditions, the greater the wind speed, the more beneficial it is to the heat dissipation of the equipment. The present invention uses the δ / exp((TZ2-BFS) / BFS) function to express the weakening effect of wind speed on the heating of the equipment, thereby increasing the adaptability and practicality of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 It is a schematic diagram of the operation steps of the present invention; Figure 2 It is a schematic diagram of the system module of the present invention; Figure 3 A schematic diagram of the operation steps for obtaining characteristic values ​​according to the present invention; Figure 4 The figure is a schematic diagram of the operation steps for obtaining the environmental impact factors of the present invention. DETAILED DESCRIPTION

[0027] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] See also Figure 1-Figure 2 , the first aspect of the present invention provides an intelligent state control system for indoor power supply, including: an intelligent analysis module, and an information acquisition module, a state control module and a database connected thereto; Information acquisition module: used to plan a day into several time periods and obtain basic information and environmental information of the indoor power supply equipment in the current time period; the basic information includes equipment temperature and output power; the environmental information includes characteristic values ​​of ambient temperature, ambient humidity and ambient wind speed; Intelligent analysis module: used to analyze historical output power to obtain reference output power for each time period; mark the reference output power for the next time period and the output power and reference output power for the current time period as target data, analyze the target data to obtain standard output power for the next time period; analyze environmental information to obtain environmental impact factors, and analyze the impact of environmental impact factors and standard output power on device temperature to obtain device temperature for the next time period; Status control module: used to control the device based on the device temperature in the next time period.

[0029] For example, in this embodiment, the area where the current indoor power supply equipment is located is a residential area, and the current time is 19:00:59; The peak time periods for the use of indoor power equipment corresponding to the residential area are extracted as follows: 7:00-8:00, 18:00-22:00; therefore, 0:00-7:00, 8:00-18:00, and 22:00-0:00 are marked as non-peak time periods; Divide the non-peak time period into time periods based on the initial time length CH; For example, the non-peak time period of 8:00-18:00 is divided. Since the initial time length CH = 2 minutes, the non-peak time period of 8:00-18:00 can be evenly divided. Therefore, the non-peak time period of 8:00-18:00 is divided into 300 time periods, and the length of each time period is 2 minutes. Based on the formula DH=α×CH=0.5×2=1 minute, the dynamic time length DH=1 minute is obtained; the peak time period is divided into time periods based on the dynamic time length DH; wherein, in this embodiment, the proportional adjustment coefficient α is set to 0.5; For example, the peak time period of 7:00-8:00 is divided. Since the dynamic time length DH = 1 minute, the peak time period of 7:00-8:00 can be evenly divided. Therefore, the peak time period of 7:00-8:00 is divided into 60 time periods, and the length of each time period is 1 minute. Arrange the time periods from the beginning to the end and divide a day into several time periods; The current time is 19:00:59, and the time period is 19:00-19:01, so 19:00-19:01 is recorded as the current time period; The temperature of the indoor power supply device at the current time is obtained through the temperature sensor, and the temperature is marked as the device temperature; the real-time output power of the indoor power supply device in the current time period is obtained through the power monitor, the average value of the real-time output power is calculated to obtain the average power, and the average power is marked as the output power; in the current time period, several ambient temperatures are obtained through the temperature sensor, several ambient humidity values ​​are obtained through the humidity sensor, and several ambient wind speed values ​​are obtained through the anemometer; The ambient humidity is divided into the H1 group, and the ambient wind speed is divided into the H2 group; Extract the maximum value ZD1=47%RH, percentile BS1=45%RH, and mode ZS1=46%RH of the H1 group data; based on the formula TZ1=(B11×ZD1+B21×BZ1+ZS1) / 2=(0.6×47+0.4×45+46) / 2=46.1%RH, obtain the characteristic value TZ1=46.1%RH of the H1 group; wherein, in this embodiment, the percentile where the percentile is located is 60%, the proportional adjustment coefficient B11 is 0.6, and the proportional adjustment coefficient B21 is 0.4; Extract the maximum value ZD2=0.25m / s, percentile BS2=0.21m / s, and mode ZS2=0.2m / s of the H2 group data; based on the formula TZ2=(B12×ZD2+B22×BS2+ZS2) / 2=(0.65×0.25+0.35×0.21+0.2) / 2=0.218m / s, obtain the characteristic value TZ2=0.218m / s of each group; wherein, in this embodiment, the proportional adjustment coefficient B12 takes a value of 0.65, and the proportional adjustment coefficient B22 takes a value of 0.35; The ambient temperatures are sorted according to the acquisition time, the ambient temperatures are extracted at fixed intervals, and the extracted ambient temperatures are marked as detection temperatures CWj. Among two adjacent detection temperatures CWj, the adjacent temperature difference LCj is obtained by subtracting the latter detection temperature CWj from the former detection temperature CWj. The proportion of the number of adjacent temperature differences LCj less than 0 to the total number of adjacent temperature differences LCj is calculated as BL=2%; wherein the fixed interval is a fixed interval of the sequence number, and in this embodiment, the fixed interval is 2; The maximum value ZD3=26℃, the percentile BS3=25℃, and the mode ZS3=25.5℃ of the ambient temperature are extracted; when i is 3, based on the formula TZ3=exp(ρ×BL)×(B13×ZD3+B23×BS3+ZS3) / 2=exp(0.02×2%)×(0.7×26+0.3×25+25.5) / 2=25.6℃, the characteristic value TZ3=25.7℃ of the ambient temperature is obtained; wherein, in this embodiment, the proportional adjustment coefficient B13 is 0.7, the proportional adjustment coefficient B23 is 0.3, and the proportional adjustment coefficient ρ is 0.02; Extract the historical output power of each time period, and divide the historical output power into several data sets according to the time period; obtain the variance of the output power in each data set, and judge whether the variance is less than the corresponding definition threshold; if yes, retain the output power of the data set; if no, remove the output power with the largest difference from the mode in the data set, and re-judge the variance until the variance of the data set is less than the corresponding definition threshold, and retain the remaining output power; The output powers retained in each data set are averaged to obtain an average output power, and the average output power is marked as a reference output power for the corresponding time period; Extract the reference output power NCL=500W from 19:01 to 19:02, the output power SL=495W from 19:01 to 19:01, and the reference output power DCL=490W; based on the formula BSL=β×NCL×SL / DCL=0.99×500×495 / 490=500.05W, obtain the standard output power BSL=500.05W from 19:01 to 19:02; wherein, in this embodiment, the proportional adjustment coefficient β is taken as 0.99; Since the characteristic value TZ1 of the ambient humidity, the characteristic value TZ2 of the ambient wind speed, and the characteristic value TZ3 of the ambient temperature do not exceed the corresponding standard values, no reminder operation is performed; Based on the formula HYZ=δ / exp((TZ2-BFS) / BFS)×(μ1×(TZ1-BHS) / BHS+μ2×(TZ3-BHW) / BHW)=0.9 / exp((0.218m / s-0.20m / s) / 0.20m / s)×(0.2×(46.1%RH-50%RH) / 50%RH+0.8×(25.7℃-28℃) / 28℃)=-0.0668, the environmental impact factor HYZ=-0.0668 is obtained from 19:00 to 19:01; wherein, in this embodiment, the standard ambient humidity BHS is 50%RH, the standard ambient wind speed BFS is 0.20m / s, the standard ambient temperature BHW is 28℃, the amplitude adjustment coefficient δ is 0.9, the proportional adjustment coefficient μ1 is 0.2, and the proportional adjustment coefficient μ2 is 0.8; Extract the environmental impact factor HYZ=-0.0668 and the output power SL=495W of the equipment from 19:00 to 19:01, and the standard output power BSL=500.05W from 19:01 to 19:02; Based on the formula SWn+1=(BSL-SL)×LR+(HYZ-SHYZ)×HR+SWn=(500.05W-495W)×0.1℃+(-0.0668+0.06)×1℃+38℃=38.5℃, the device temperature SWn+1=38.5℃ from 19:01 to 19:02 is obtained; wherein, in this embodiment, the environmental impact factor SHYZ of the previous time period is -0.06, and the device temperature SW is 38℃; the temperature change LR caused by the unit output power change is 0.1℃, and the temperature change HR caused by the unit environmental impact factor change is 1℃; The device temperature SWn+1 is lower than the temperature threshold 2, so no operation is performed; wherein, in this embodiment, the temperature threshold 2 is 60° C.

[0030] In this application, a day is divided into several time periods, including: Extract the area where the current indoor power supply equipment is located and the area type of the area; extract the peak time period of indoor power supply equipment corresponding to the area type; where the area types include residential areas, office areas, commercial areas, transportation hub areas and public facilities areas; the peak time period is obtained by manual setting; Extracting the initial time length CH of the time period from the database, extracting the non-peak time period in sequence, and judging whether the extracted non-peak time period can be evenly divided into a number of time periods based on the initial time length CH; if yes, evenly dividing the extracted non-peak time period into a number of time periods based on the initial time length CH; if no, obtaining the maximum number of complete time periods that can be divided in the extracted non-peak time period, and evenly dividing the non-peak time period into a number of time periods based on the maximum number; wherein the initial time length CH is obtained by manual setting; Extract peak time periods in sequence, obtain the dynamic time length DH based on the formula DH=α×CH, and determine whether the extracted peak time period can be evenly divided into several time periods based on the dynamic time length DH; if yes, evenly divide the extracted peak time period into several time periods based on the dynamic time length DH; if no, obtain the maximum number of complete time periods that can be divided in the extracted peak time period, and evenly divide the peak time period into several time periods based on the maximum number; wherein α is the proportional adjustment coefficient, and the value range of α is (0,1]; The time periods are arranged from the beginning to the end according to the time, and a day is divided into several time periods.

[0031] It should be noted that dividing the extracted non-peak time period evenly into several time periods based on the initial time length CH is: dividing the non-peak time period into several time periods according to the initial time length CH; dividing the non-peak time period evenly into several time periods based on the maximum number is: dividing the non-peak time period into several time periods according to the maximum number.

[0032] It should be noted that, in the maximum number of complete time periods that can be divided in the extracted non-peak time period, the value of the complete time period is an initial time length CH.

[0033] It should be noted that the maximum number of complete time periods that can be divided in the extracted non-peak time period is obtained, and the non-peak time period is evenly divided into several time periods based on the maximum number. An example is as follows: if a non-peak time period is one hour and one minute, and the initial time length CH is 2 minutes, then one hour and one minute cannot be evenly divided into complete time periods according to 2 minutes, and can only be divided into 30 complete time periods at most, and one minute more cannot be divided. At this time, the maximum number of complete time periods extracted is 30, and one hour and one minute is evenly divided into 30 time periods, and one time period is 2 minutes and 2 seconds.

[0034] It should be noted that the peak time periods are manually set, such as the peak time periods in residential areas are: 7:00-8:00, 18:00-22:00; the peak time periods in office areas are: 9:00-11:00, 14:00-17:30.

[0035] This application obtains basic information and environmental information of the indoor power supply equipment in the current time period, including: Extract the time period in which the current time is located, and mark the time period as the current time period; obtain the temperature of the indoor power supply equipment at the current time through the temperature sensor, and mark the temperature as the equipment temperature; obtain the real-time output power of the indoor power supply equipment in the current time period through the power monitor, calculate the average value of the real-time output power to obtain the average power, and mark the average power as the output power; obtain several ambient temperatures through the temperature sensor in the current time period, obtain several ambient humidity through the humidity sensor, obtain several ambient wind speeds through the anemometer, and calculate the ambient temperature, ambient humidity and ambient wind speed to obtain the characteristic value.

[0036] See also Figure 3 In this application, the ambient temperature, ambient humidity and ambient wind speed are calculated to obtain characteristic values, including: The environmental humidity is divided into the H1 group, and the environmental wind speed is divided into the H2 group; the maximum value ZDi, percentile BSi, and mode ZSi of each group of data are extracted; the characteristic value TZi of each group is obtained based on the formula TZi=(B1i×ZDi+B2i×BSi+ZSi) / 2; wherein, i represents the sequence number of each group, when i is 1, it represents the relevant data of the H1 group, and when i is 2, it represents the relevant data of the H2 group; the percentile of the percentile BSi is obtained by manual setting; B1i and B2i are both proportional adjustment coefficients greater than 0, and B1i+B2i=1, B1i>B2i; The ambient temperatures are sorted according to the acquisition time, and the ambient temperatures are extracted at fixed intervals. The ambient temperatures are marked as detection temperatures CWj. Among two adjacent detection temperatures CWj, the adjacent temperature difference LCj is obtained by subtracting the next detection temperature CWj+1 from the previous detection temperature CWj. The proportion BL of the number of adjacent temperature differences LCj less than 0 to the total number of adjacent temperature differences LCj is counted, and the maximum value ZD3, percentile BS3, and mode ZS3 of the ambient temperatures are extracted. When i is 3, the characteristic value TZ3 of the ambient temperature is obtained based on the formula TZ3=exp(ρ×BL)×(B13×ZD3+B23×BS3+ZS3) / 2. Among them, j is the order of extraction. ρ is a proportional adjustment coefficient greater than 0, and the value range of ρ is (0,1).

[0037] It should be noted that when i is 1, it represents the relevant data of group H1, when i is 2, it represents the relevant data of group H2, and when i is 3, it represents the relevant data of ambient temperature; the proportional adjustment coefficients B13 and B23 are the proportional adjustment coefficients B1i and B2i when i is 3, and the value ranges of B13 and B23 are the same as those of B1i and B2i, that is, B13 and B23 are both proportional adjustment coefficients greater than 0, and B13+B23=1, B13>B23.

[0038] It should be noted that in the present invention, the percentile BSi is the value at a specific percentile in each group; for example, if the data of each group is sorted in order of size, if the manually set percentile is 60%, then the data at the 60% position of each group is the percentile BSi of the group.

[0039] It should be noted that an adjacent temperature difference LCj less than 0 between adjacent temperatures can be understood as a temperature increase.

[0040] It should be noted that the effects of ambient humidity and ambient wind speed on device heating are only indirect, but ambient temperature directly affects the device; for example, changes in ambient humidity and ambient wind speed cause changes in device heating due to heat dissipation, and changes in ambient temperature are directly superimposed on the device to cause changes in device heating. An increase in temperature will directly lead to an increase in device temperature, and this effect is more significant. The present invention takes into account the potential impact of the ambient temperature change trend on device heating in the characteristic value analysis of ambient temperature, thereby improving the accuracy of system analysis.

[0041] In this application, the historical output power is analyzed to obtain the reference output power for each time period, including: Extract the historical output power of each time period, and divide the historical output power into several data sets according to the time period; obtain the variance of the output power in each data set, and judge whether the variance is less than the corresponding definition threshold; if yes, retain the output power of the data set; if no, remove the output power with the largest difference from the mode in the data set, and re-judge the variance until the variance of the data set is less than the corresponding definition threshold, and retain the remaining output power; wherein the definition threshold is obtained through experience; The output powers retained in each data set are averaged to obtain an average output power, and the average output power is marked as a reference output power for the corresponding time period.

[0042] In this application, the target data is analyzed to obtain the standard output power for the next time period, including: Extract the reference output power NCL of the next time period, as well as the output power SL and reference output power DCL of the current time period; obtain the standard output power BSL of the next time period based on the formula BSL=β×NCL×SL / DCL; where β is a proportional adjustment coefficient greater than 0, and the value range of β is (0,2].

[0043] See also Figure 4 In this application, environmental information is analyzed to obtain environmental impact factors, including: A1: Extract the characteristic value TZ1 of the ambient humidity and determine whether the characteristic value TZ1 exceeds the standard ambient humidity BHS; if yes, issue a message that the characteristic value TZ1 of the ambient humidity exceeds the standard; if no, do not perform any reminder operation; A2: Extract the characteristic value TZ2 of the ambient wind speed and determine whether the characteristic value TZ2 exceeds the standard ambient wind speed BFS; if yes, issue a message that the characteristic value TZ2 of the ambient wind speed exceeds the standard; if no, do not perform any reminder operation; A3: Extract the characteristic value TZ3 of the ambient temperature and determine whether the characteristic value TZ3 exceeds the standard ambient temperature BHW; if yes, issue a message that the characteristic value TZ3 exceeds the standard; if no, do not perform any reminder operation; among them, the standard ambient humidity BHS, the standard ambient wind speed BFS and the standard ambient temperature BHW are all obtained through experience; A4: The environmental impact factor HYZ for the current time period is obtained based on the formula HYZ=δ / exp((TZ2-BFS) / BFS)×(μ1×(TZ1-BHS) / BHS+μ2×(TZ3-BHW) / BHW); wherein δ is an amplitude adjustment coefficient greater than 0; μ1 and μ2 are both proportional adjustment coefficients greater than 0, and μ1+μ2=1, μ1<μ2.

[0044] It should be noted that a high humidity environment may affect the heat dissipation efficiency of the device, causing the temperature of the device to rise during operation, increasing the risk of overheating. For example, in a high humidity environment, the moisture content in the air is high, which will reduce the heat conduction efficiency of the air, causing the heat dissipation of the device to slow down, thereby increasing the temperature of the device.

[0045] In this application, the impact analysis of the device temperature based on the environmental impact factor and the standard output power is performed to obtain the device temperature in the next time period, including: Extract the environmental impact factor HYZ and the output power SL of the equipment in the current time period, as well as the standard output power BSL in the next time period; The device temperature SWn+1 of the next time period is obtained based on the formula SWn+1=(BSL-SL)×LR+(HYZ-SHYZ)×HR+SWn; wherein SHYZ is the environmental impact factor of the previous time period, SW is the device temperature; LR is the temperature change caused by the manually set unit output power change, and HR is the temperature change caused by the manually set unit environmental impact factor change.

[0046] It should be noted that the impact of environmental factors on equipment heating is delayed, while the equipment heating caused by output power is time-sensitive. Therefore, when calculating the equipment temperature in the next time period, the present invention uses the environmental impact factor data of the previous time period and the current time period, and the output power data used is the current time period and the next time.

[0047] It should be noted that the temperature change amount caused by the unit output power change and the temperature change amount caused by the unit environmental impact factor change are both set manually based on experience.

[0048] In this application, the device is controlled based on the device temperature in the next time period, including: E1: Extract the device temperature SWn+1 of the next time period and determine whether the device temperature SWn+1 exceeds the temperature threshold 1; if yes, issue an alarm and cut off the power supply to the current room power supply device for protection; if no, jump to E2; E2: Determine whether the device temperature SWn+1 is lower than the temperature threshold 2; if yes, do nothing; if no, reduce the output power of the current indoor power supply device to a fixed power; the fixed power is obtained through experience; the temperature threshold 1 and the temperature threshold 2 are obtained through manual setting, and the temperature threshold 1 is greater than the temperature threshold 2.

[0049] The second aspect of the present invention provides a method for intelligently controlling the state of a room power supply, comprising the following steps: S1: Plan a day into several time periods, and obtain basic information and environmental information of the indoor power supply equipment in the current time period; S2: Analyze the historical output power to obtain the reference output power of each time period; mark the reference output power of the next time period and the output power and reference output power of the current time period as target data, analyze the target data to obtain the standard output power of the next time period; analyze the environmental information to obtain the environmental impact factor, and analyze the impact of the environmental impact factor and the standard output power on the device temperature to obtain the device temperature of the next time period; S3: Control the device based on the device temperature in the next time period.

[0050] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0051] Working principle of the present invention: A day is planned into several time periods, and the basic information and environmental information of the indoor power supply equipment in the current time period are obtained. This step increases the acquisition of characteristic values ​​and increases the accuracy of system analysis information; the historical output power is analyzed to obtain the reference output power of each time period. In this step, the data with large fluctuations in the data set is removed in the threshold judgment, which increases the accuracy of the calculated reference output power and provides data support for the subsequent calculation of the standard output power; the reference output power of the next time period and the output power and reference output power of the current time period are marked as target data, and the target data is analyzed to obtain the standard output power of the next time period. This step can effectively avoid the abnormal situation of inaccurate standard output power obtained by analysis due to drastic fluctuations in the number of people; the environmental information is analyzed to obtain the environmental impact factor. This step takes into account the delay of the impact of environmental factors on equipment heating, which can increase the accuracy of the result analysis; the impact of the environmental impact factor and the standard output power on the equipment temperature is analyzed to obtain the equipment temperature of the next time period; the equipment is controlled based on the equipment temperature of the next time period.

[0052] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An intelligent control system for indoor power supply status, characterized in that: include: Intelligent analysis module, and the information acquisition module, status control module and database connected to it; The information acquisition module is used to plan a day into several time periods and obtain basic information and environmental information of the indoor power supply equipment in the current time period; wherein the basic information includes equipment temperature and output power; the environmental information includes characteristic values ​​of ambient temperature, ambient humidity and ambient wind speed; The intelligent analysis module is used to analyze the historical output power to obtain the reference output power of each time period; mark the reference output power of the next time period and the output power and reference output power of the current time period as target data, analyze the target data to obtain the standard output power of the next time period; analyze the environmental information to obtain the environmental impact factor, and analyze the impact of the environmental impact factor and the standard output power on the device temperature to obtain the device temperature of the next time period; The state control module is used to control the device based on the device temperature in the next time period.

2. According to claim 1, the intelligent state control system for indoor power supply is characterized in that: The day is planned into several time periods, including: Extract the area where the current indoor power supply equipment is located, and the area type of the area; extract the peak time period of use of the indoor power supply equipment corresponding to the area type; wherein the area types include residential areas, office areas, commercial areas, transportation hub areas and public facilities areas; Extracting the initial time length CH of the time period from the database, extracting the non-peak time period in sequence, and judging whether the extracted non-peak time period can be evenly divided into a plurality of time periods based on the initial time length CH; if yes, evenly dividing the extracted non-peak time period into a plurality of time periods based on the initial time length CH; if no, obtaining the maximum number of complete time periods that can be divided in the extracted non-peak time period, and evenly dividing the non-peak time period into a plurality of time periods based on the maximum number; Extract peak time periods in sequence, obtain the dynamic time length DH based on the formula DH=α×CH, and determine whether the extracted peak time period can be evenly divided into several time periods based on the dynamic time length DH; if yes, evenly divide the extracted peak time period into several time periods based on the dynamic time length DH; if no, obtain the maximum number of complete time periods that can be divided in the extracted peak time period, and evenly divide the peak time period into several time periods based on the maximum number; wherein α is the proportional adjustment coefficient, and the value range of α is (0,1]; The time periods are arranged from the beginning to the end according to the time, and a day is divided into several time periods.

3. According to claim 1, the intelligent state control system for indoor power supply is characterized in that: The obtaining of basic information and environmental information of the indoor power supply equipment in the current time period includes: Extract the time period in which the current time is located, and mark the time period as the current time period; obtain the temperature of the indoor power supply equipment at the current time through a temperature sensor, and mark the temperature as the equipment temperature; obtain the real-time output power of the indoor power supply equipment in the current time period through a power monitor, calculate the average value of the real-time output power to obtain the average power, and mark the average power as the output power; in the current time period, obtain several ambient temperatures through a temperature sensor, obtain several ambient humidity through a humidity sensor, obtain several ambient wind speeds through an anemometer, and calculate the ambient temperature, ambient humidity and ambient wind speed to obtain characteristic values.

4. The intelligent state control system for indoor power supply according to claim 3 is characterized in that: The characteristic values ​​obtained by calculating the ambient temperature, ambient humidity and ambient wind speed include: The ambient humidity is divided into the H1 group, and the ambient wind speed is divided into the H2 group; the maximum value ZDi, percentile BSi, and mode ZSi of each group of data are extracted; the characteristic value TZi of each group is obtained based on the formula TZi=(B1i×ZDi+B2i×BSi+ZSi) / 2; wherein i represents the sequence number of each group, when i is 1, it represents the relevant data of the H1 group, and when i is 2, it represents the relevant data of the H2 group; B1i and B2i are both proportional adjustment coefficients greater than 0, and B1i+B2i=1, B1i>B2i; The ambient temperatures are sorted according to the acquisition time, and the ambient temperatures are extracted at fixed intervals. The extracted ambient temperatures are marked as detection temperatures CWj. Among two adjacent detection temperatures CWj, the adjacent temperature difference LCj is obtained by subtracting the next detection temperature CWj+1 from the previous detection temperature CWj. The proportion BL of the number of adjacent temperature differences LCj less than 0 to the total number of adjacent temperature differences LCj is counted, and the maximum value ZD3, percentile BS3, and mode ZS3 of the ambient temperatures are extracted. When i is 3, the characteristic value TZ3 of the ambient temperature is obtained based on the formula TZ3=exp(ρ×BL)×(B13×ZD3+B23×BS3+ZS3) / 2. Among them, j is the order of extraction. ρ is a proportional adjustment coefficient greater than 0, and the value range of ρ is (0,1).

5. The intelligent state control system for indoor power supply according to claim 1 is characterized in that: The analyzing the historical output power to obtain the reference output power in each time period includes: Extract the historical output power of each time period, and divide the historical output power into several data sets according to the time period; obtain the variance of the output power in each data set, and judge whether the variance is less than the corresponding definition threshold; if yes, retain the output power of the data set; if no, remove the output power with the largest difference from the mode in the data set, and re-judge the variance until the variance of the data set is less than the corresponding definition threshold, and retain the remaining output power; The output powers retained in each data set are averaged to obtain an average output power, and the average output power is marked as a reference output power for the corresponding time period.

6. The intelligent state control system for indoor power supply according to claim 1 is characterized in that: The step of analyzing the target data to obtain the standard output power for the next time period includes: Extract the reference output power NCL of the next time period, as well as the output power SL and reference output power DCL of the current time period; obtain the standard output power BSL of the next time period based on the formula BSL=β×NCL×SL / DCL; where β is a proportional adjustment coefficient greater than 0, and the value range of β is (0,2].

7. The intelligent state control system for indoor power supply according to claim 6 is characterized in that: The environmental information is analyzed to obtain environmental impact factors, including: A1: extract the characteristic value TZ1 of the ambient humidity, and determine whether the characteristic value TZ1 exceeds the standard ambient humidity BHS; if yes, issue a message that the characteristic value TZ1 of the ambient humidity exceeds the standard; if no, do not perform a reminder operation; A2: extract the characteristic value TZ2 of the ambient wind speed, and determine whether the characteristic value TZ2 exceeds the standard ambient wind speed BFS; if yes, issue a message that the characteristic value TZ2 of the ambient wind speed exceeds the standard; if no, do not perform a reminder operation; A3: extract the characteristic value TZ3 of the ambient temperature, and determine whether the characteristic value TZ3 exceeds the standard ambient temperature BHW; if yes, issue a message that the characteristic value TZ3 of the ambient temperature exceeds the standard; if no, do not perform a reminder operation; A4: The environmental impact factor HYZ for the current time period is obtained based on the formula HYZ=δ / exp((TZ2-BFS) / BFS)×(μ1×(TZ1-BHS) / BHS+μ2×(TZ3-BHW) / BHW); wherein δ is an amplitude adjustment coefficient greater than 0; μ1 and μ2 are both proportional adjustment coefficients greater than 0, and μ1+μ2=1, μ1<μ2.

8. The intelligent state control system for indoor power supply according to claim 7 is characterized in that: The performing of an impact analysis on the device temperature based on the environmental impact factor and the standard output power to obtain the device temperature in the next time period includes: Extract the environmental impact factor HYZ and the output power SL of the equipment in the current time period, as well as the standard output power BSL in the next time period; The device temperature SWn+1 of the next time period is obtained based on the formula SWn+1=(BSL-SL)×LR+(HYZ-SHYZ)×HR+SWn; wherein SHYZ is the environmental impact factor of the previous time period, SW is the device temperature; LR is the temperature change caused by the unit output power change, and HR is the temperature change caused by the unit environmental impact factor change.

9. The intelligent state control system for indoor power supply according to claim 8 is characterized in that: The controlling of the device based on the device temperature in the next time period includes: E1: extract the device temperature SWn+1 of the next time period, and determine whether the device temperature SWn+1 exceeds the temperature threshold 1; if yes, issue an alarm and cut off the power supply to the current room power supply device for protection; if no, jump to E2; E2: Determine whether the device temperature SWn+1 is lower than temperature threshold 2; if yes, do nothing; if no, reduce the output power of the current indoor power supply device to a fixed power; wherein temperature threshold 1 is greater than temperature threshold 2.

10. A method for intelligent state control of indoor power supply, based on the operation of an intelligent state control system for indoor power supply according to any one of claims 1 to 9, characterized in that: S1: Plan a day into several time periods, and obtain basic information and environmental information of the indoor power supply equipment in the current time period; S2: Analyze the historical output power to obtain the reference output power of each time period; mark the reference output power of the next time period and the output power and reference output power of the current time period as target data, analyze the target data to obtain the standard output power of the next time period; analyze the environmental information to obtain the environmental impact factor, and analyze the impact of the environmental impact factor and the standard output power on the device temperature to obtain the device temperature of the next time period; S3: Control the device based on the device temperature in the next time period.

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