An intelligent distribution box management system based on the Internet of Things

Abstract

The present invention discloses an intelligent distribution box management system based on the Internet of Things, which relates to the technical field of distribution boxes. The intelligent distribution box management system includes: a data acquisition component, an optimization model component, a monitoring component and a main control module; the main control module is connected to the data acquisition component by signal, and the data acquisition component is used to obtain the power consumption data of several load devices, and send the power consumption data to the main control module; the optimization model component is connected to the monitoring component by signal, and the monitoring component is used to obtain the internal operation data of the intelligent distribution box; the main control module generates a first distribution instruction according to the power consumption data fed back by the data acquisition component, and sends the first distribution instruction to the optimization model component; the optimization model component simulates the operation of the intelligent distribution box based on the internal operation data and the first distribution instruction, and outputs a second distribution instruction. The distribution instructions of the distribution box are simulated and optimized by the optimization model component, and the distribution instructions are adjusted to improve the reliability and safety of the distribution management of the distribution box.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent distribution boxes, and in particular to an intelligent distribution box management system based on the Internet of Things. Background Art

[0002] The distribution box is one of the main equipment in the power system. It can meet the voltage conversion requirements of the high-voltage current of the high-voltage power grid and the low-voltage power consumption of the load equipment. When multiple load devices are connected to the distribution system network, the distribution box is required to have an automatic adjustment function, which can adjust the distribution output of the distribution box according to the power consumption demand of the load equipment to meet the normal operation of the load equipment.

[0003] The existing intelligent distribution box mainly adjusts the power distribution by adjusting its own working output stability and cooperating with the remote adjustment of the staff. Due to the power changes of multiple load devices, the internal working voltage, working current, working temperature of the transformer equipment and other parameters of the distribution box fluctuate greatly. During the power distribution process, the distribution box is prone to high load operation, affecting the power distribution safety and reliability of the distribution box. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides an intelligent distribution box management system based on the Internet of Things, which adjusts the simulated operation strategy of the distribution system according to the changes in the load working electrical data, realizes the intelligent distribution adjustment of the distribution box, and enables the distribution box to adjust the distribution strategy according to the load to improve the accuracy of distribution. The distribution instructions of the distribution box are simulated by optimizing the model components, and optimized according to the distribution simulation of the distribution box, so as to improve the reliability and safety of the distribution management of the distribution box.

[0005] The present invention provides an intelligent distribution box management system based on the Internet of Things, the intelligent distribution box management system comprising: a data acquisition component, an optimization model component, a monitoring component and a main control module;

[0006] The main control module is connected to the data acquisition component by signal, and the data acquisition component is used to obtain power consumption data of several load devices and send the power consumption data to the main control module;

[0007] The optimization model component is connected to the monitoring component by signal, and the monitoring component is used to obtain internal operation data of the intelligent distribution box;

[0008] The main control module generates a first power distribution instruction according to the power consumption data fed back by the data acquisition component, and sends the first power distribution instruction to the optimization model component;

[0009] The optimization model component performs intelligent distribution box simulation operation based on the internal operation data and the first power distribution instruction, and outputs a second power distribution instruction.

[0010] Furthermore, the data acquisition component includes sensing elements arranged on a plurality of load devices, and acquires power consumption data of the plurality of load devices based on the sensing elements.

[0011] Furthermore, the monitoring component includes a plurality of detection elements arranged in the intelligent distribution box, and internal operation data of the intelligent distribution box is obtained based on the detection elements.

[0012] Furthermore, the intelligent distribution box is provided with a high-voltage input component, a transformer component and a low-voltage distribution component;

[0013] The high-voltage input component is connected to the high-voltage power grid and is used to receive the high-voltage current input from the high-voltage power grid to the intelligent distribution box;

[0014] The transformer assembly is used to perform a voltage reduction operation on the high voltage current, so that the high voltage current can adapt to the power distribution work of the low voltage power distribution assembly after the voltage reduction operation of the transformer assembly;

[0015] The low-voltage power distribution component is connected to the load device, so that the low-voltage power distribution component can distribute the corresponding working voltage to the load device according to the power demand of the load device.

[0016] Furthermore, the monitoring component obtains the input voltage of the high-voltage input component and the output voltage of the low-voltage distribution component based on the detection of the high-voltage input component, the transformer component and the low-voltage distribution component by a plurality of the detection elements, and simultaneously obtains the temperature data of the transformer component.

[0017] Furthermore, the optimization model component obtains the correlation function relationship between the temperature data and the voltage data of the transformer component inside the intelligent distribution box according to the internal operation data of the intelligent distribution box obtained by the detection element;

[0018] Obtain the correlation function between the low voltage change rate of the low voltage power distribution component and the temperature change of the transformer component:

[0019] ;

[0020] in, is the rate of change of the operating temperature of the transformer component, is the low voltage data change rate of the low voltage distribution component, is the correlation coefficient, and μ is the correction coefficient.

[0021] Furthermore, the calculation formula of the correlation coefficient r is:

[0022] ;

[0023] Among them, r is the correlation coefficient, N is the number of extracted samples of the operating temperature data of the transformer component obtained in unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer component per unit time, is the i-th low-voltage voltage sample data of the low-voltage power distribution component in unit time, i is a constant, i≤N, It is the average low voltage data of the low voltage distribution component in unit time.

[0024] Furthermore, when the low-voltage power distribution component is set to a constant voltage and constant current state, the correlation coefficient of the temperature change rate of the high-voltage input component and the transformer component is calculated to obtain a correction coefficient μ. The calculation formula of the correction coefficient μ is:

[0025] ;

[0026] Wherein, μ is the correction coefficient, N is the number of samples of the working temperature data of the transformer component obtained per unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer component per unit time, is the i-th high voltage voltage sample data of the high voltage input component in unit time, i is a constant, i≤N, It is the average high voltage voltage data of the high voltage input component per unit time.

[0027] Furthermore, the optimization model component obtains the operating voltage of the low-voltage distribution component after power distribution according to the received first power distribution instruction;

[0028] The operating voltage after power distribution is input into the correlation function between the low voltage change rate of the low voltage power distribution component and the temperature change of the transformer component to perform power distribution simulation and obtain the temperature change of the transformer component.

[0029] Furthermore, the optimization model component compares the simulated operating temperature data with the operating temperature data threshold of the transformer component. If the simulated operating temperature data is greater than the operating temperature data threshold of the transformer component, the optimization model component adjusts the output mode of the intelligent distribution box so that the energy storage unit of the intelligent distribution box transmits current to the load device through the low-voltage distribution component.

[0030] The optimization model component compares the temperature variation amplitude of the simulated operating temperature data with the standard temperature variation amplitude range of the transformer component. If the temperature variation amplitude of the simulated operating temperature data exceeds the standard temperature variation amplitude range, the transformer component of the intelligent distribution box is subjected to on-load voltage regulation.

[0031] Beneficial effects of the present invention:

[0032] The present invention provides an intelligent distribution box management system based on the Internet of Things, which adjusts the simulated operation strategy of the distribution system according to the changes in the load working electrical data, realizes the intelligent distribution adjustment of the distribution box, and enables the distribution box to adjust the distribution strategy according to the load, thereby improving the accuracy of distribution.

[0033] By setting the optimization model component, the simulated operating temperature of the voltage component of the intelligent distribution box is calculated based on the voltage data and current data, which can improve the calculation accuracy and reliability of the optimization model component. Based on the optimization model component, the simulation data and the operating temperature of the distribution box transformer component are optimized to achieve the optimization adjustment of the distribution box distribution strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a structural diagram of an intelligent distribution box management system based on the Internet of Things in an embodiment of the present invention;

[0035] Figure 2 It is a structural schematic diagram of an intelligent distribution box in an embodiment of the present invention;

[0036] Figure 3 It is a flow chart of an intelligent distribution box management method based on the Internet of Things in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Embodiment 1:

[0039] Figure 1A structural schematic diagram of an intelligent distribution box 50 management system based on the Internet of Things in an embodiment of the present invention is shown. The intelligent distribution box 50 management system includes: a data acquisition component 40, an optimization model component 20, a monitoring component 30 and a main control module 10. The data acquisition component 40 is used to collect power consumption data of the load device, and send the power consumption data of the load device to the main control module 10 through the Internet of Things. The main control module 10 adjusts the operating status of the intelligent distribution box 50 according to the power consumption data.

[0040] The monitoring component 30 is used to detect and obtain the internal operation data of the intelligent distribution box 50 during operation. The optimization model component 20 is provided with an operation model of the intelligent distribution box 50. The optimization model component 20 can simulate the distribution operation of the intelligent distribution box 50 according to the distribution adjustment instruction of the main control module 10 and the internal operation data collected by the monitoring component 30. By obtaining the parameter change data of the simulated operation of the intelligent distribution box 50, the parameter change data of the simulated operation of the optimization model component 20 is compared with the standard operation data of the intelligent distribution box 50, and the operation parameter setting of the intelligent distribution box 50 is adjusted, thereby correcting the distribution adjustment instruction of the main control module 10 and improving the reliability of the distribution management of the intelligent distribution box 50.

[0041] The data acquisition component 40 includes sensing elements arranged in a plurality of load devices, and obtains power consumption data of the plurality of load devices based on the sensing elements. By setting a plurality of sensing elements in the load devices, when the load devices are in working state, the sensing elements are started and connected to the Internet of Things system where the intelligent distribution box 50 is located, and the working voltage and working current of the load devices are uploaded based on the sensing elements, so that the main control module 10 can obtain the operating power of the load devices, and adjust the output strategy of the intelligent distribution box 50 according to the operating power of the load devices.

[0042] The monitoring component 30 includes a plurality of detection elements arranged in the intelligent distribution box 50, and the internal operation data of the intelligent distribution box 50 is obtained based on the detection elements. The plurality of detection elements include: a voltmeter, an ammeter, a temperature detector and other elements. The internal operation data of the intelligent distribution box 50 when working is obtained through the plurality of detection elements, so that the optimization model component 20 can simulate the power distribution operation state of the intelligent distribution box 50 according to the internal operation data of the intelligent distribution box 50 combined with the power distribution instructions of the main control module 10, and adjust the power distribution instructions of the intelligent distribution box 50.

[0043] Specifically, the main control module 10 is connected to the data acquisition component 40 by signal. The main control module 10 generates a first power distribution instruction according to the power consumption data fed back by the data acquisition component 40, and sends the first power distribution instruction to the optimization model component 20. The main control module 10 can adjust the output power of the intelligent distribution box 50 based on the power consumption change data at the load end.

[0044] The optimization model component 20 is connected to the monitoring component 30 by signal. The optimization model component 20 simulates the operation of the intelligent distribution box 50 based on the internal operation data and the first power distribution instruction, and outputs a second power distribution instruction. The optimization model component 20 is based on the internal operation data fed back by the monitoring component 30, so that the optimization module component can simulate the operation of the intelligent distribution box 50 according to the internal operation data combined with the first power distribution instruction, so as to obtain the change of the working operation state of the intelligent distribution box 50, so that the optimization model component 20 can optimize the operation deployment strategy of the intelligent distribution box 50 according to the change of the operation parameters of the intelligent distribution box 50 obtained by the simulation operation, thereby outputting the second power distribution instruction, improving the safety and reliability of the power distribution adjustment of the intelligent distribution box 50, and thus improving the service life of the intelligent distribution box 50.

[0045] Embodiment 2:

[0046] Figure 2 A structural schematic diagram of an intelligent distribution box 50 in an embodiment of the present invention is shown, wherein the intelligent distribution box 50 is provided with a high-voltage input component 51, a transformer component 52 and a low-voltage distribution component 53. The high-voltage input component 51 is connected to the high-voltage power grid and is used to receive the high-voltage current input from the high-voltage power grid to the intelligent distribution box 50. The transformer component 52 is used to step down the high-voltage current so that the high-voltage current can adapt to the power distribution work of the low-voltage distribution component 53 after the step-down operation of the transformer component 52. The low-voltage distribution component 53 is connected to the load device so that the low-voltage distribution component 53 can distribute the corresponding working voltage to the load device according to the power demand of the load device.

[0047] Specifically, the low-voltage power distribution component 53 is provided with an output circuit, and the low-voltage power distribution component 53 is electrically connected to a plurality of load devices based on the output circuit, and the low-voltage power distribution component 53 can realize working drive of a plurality of load devices.

[0048] Several detection elements of the monitoring component 30 are arranged inside the intelligent distribution box 50. Based on the detection of the high-voltage input component 51, the transformer component 52 and the low-voltage distribution component 53 by the several detection elements, the input voltage of the high-voltage input component 51 and the output voltage of the low-voltage distribution component 53 can be obtained, and the temperature data of the transformer component 52 can be obtained at the same time. The monitoring component 30 can send the internal operating data of the intelligent distribution box 50 to the optimization model component 20. The operating data of the intelligent distribution box 50 is monitored by the monitoring component 30, and the distribution strategy of the intelligent distribution box 50 is adjusted in cooperation with the optimization model component 20, which can improve the reliability of the distribution strategy adjustment of the intelligent distribution box 50.

[0049] Specifically, the optimization model component 20 obtains the correlation function relationship between the temperature data and the voltage data of the transformer component 52 inside the smart distribution box 50 according to the internal operation data of the smart distribution box 50 obtained by the detection element.

[0050] The optimization model component 20 obtains the temperature variation of the transformer component 52 within a unit time, and the voltage variation of the intelligent distribution box 50 within a unit time.

[0051] According to the temperature detection of the transformer component 52 inside the intelligent distribution box 50 by the monitoring component 30, the operating temperature change rate of the transformer component 52 in unit time is calculated:

[0052] ;

[0053] in, is the rate of change of the operating temperature, N is the number of samples of the operating temperature data of the transformer assembly 52 obtained per unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer assembly 52 per unit time, , As unit time.

[0054] According to the voltage data detection of the high-voltage input component 51 inside the intelligent distribution box 50 by the monitoring component 30, the high-voltage voltage change rate of the high-voltage input component 51 of the intelligent distribution box 50 in unit time is calculated:

[0055] ;

[0056] in, is the high voltage data change rate, N is the number of extracted samples of the high voltage data of the high voltage input component 51 obtained per unit time, is the i-th high voltage voltage sample data of the high voltage input component 51 in unit time, i is a constant, i≤N, is the average high voltage voltage data of the high voltage input component 51 in unit time, As unit time.

[0057] According to the voltage data detection of the low-voltage distribution component 53 inside the intelligent distribution box 50 by the monitoring component 30, the low-voltage voltage change rate of the low-voltage distribution component 53 of the intelligent distribution box 50 in unit time is calculated:

[0058] ;

[0059] in, is the low voltage data change rate, N is the number of extracted samples of the low voltage data of the low voltage distribution component 53 obtained in unit time, is the i-th low voltage sample data of the low voltage distribution component 53 in unit time, i is a constant, i≤N, is the average low voltage data of the low voltage distribution component 53 in unit time, As unit time.

[0060] According to the current data detection of the low-voltage distribution component 53 inside the intelligent distribution box 50 by the monitoring component 30, the low-voltage current change rate of the low-voltage distribution component 53 of the intelligent distribution box 50 in unit time is calculated:

[0061] ;

[0062] in, is the rate of change of low-voltage current data, N is the number of extracted samples of low-voltage current data of the low-voltage power distribution component 53 obtained in unit time, is the i-th low-voltage current sample data of the low-voltage power distribution component 53 in unit time, i is a constant, i≤N, is the average low voltage current data of the low voltage power distribution component 53 in unit time, As unit time.

[0063] Specifically, the correlation function between the temperature change of the transformer component 52 of the intelligent distribution box 50 and the high voltage voltage is analyzed according to the high voltage voltage change rate of the high voltage input component 51 of the intelligent distribution box 50 and the operating temperature change rate of the transformer component 52.

[0064] Obtain the correlation function between the low voltage change rate of the low voltage power distribution component 53 and the temperature change of the transformer component 52:

[0065] ;

[0066] in, is the operating temperature change rate of the transformer assembly 52, is the low voltage data change rate of the low voltage distribution component 53, is the correlation coefficient, and μ is the correction coefficient.

[0067] The calculation formula of the correlation coefficient r is:

[0068] ;

[0069] Wherein, r is the correlation coefficient, N is the number of extracted samples of the operating temperature data of the transformer assembly 52 obtained in a unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer assembly 52 per unit time, is the i-th low voltage sample data of the low voltage distribution component 53 in unit time, i is a constant, i≤N, It is the average low voltage data of the low voltage distribution component 53 in unit time.

[0070] Furthermore, the optimization model component 20 is configured as a correction coefficient based on the correlation coefficient analysis between the high-voltage data change rate of the high-voltage input component 51 of the intelligent distribution box 50 and the temperature change rate of the transformer component 52 .

[0071] Specifically, when the low-voltage power distribution component 53 is set to a constant voltage and constant current state, the correlation coefficient of the temperature change rate of the high-voltage input component 51 and the transformer component 52 is calculated to obtain a correction coefficient μ. The calculation formula of the correction coefficient μ is:

[0072] ;

[0073] Wherein, μ is the correction coefficient, N is the number of extracted samples of the working temperature data of the transformer assembly 52 obtained in a unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer assembly 52 per unit time, is the i-th high voltage voltage sample data of the high voltage input component 51 in unit time, i is a constant, i≤N, is the average high voltage voltage data of the high voltage input component 51 in unit time.

[0074] Specifically, the correlation function between the current change rate of the low voltage power distribution component 53 and the temperature change of the transformer component 52 is obtained:

[0075] ;

[0076] in, is the rate of change of the operating temperature of the transformer assembly 52, is the low voltage current data change rate of the low voltage power distribution component 53, is the correlation coefficient, and μ is the correction coefficient.

[0077] The correlation coefficient The calculation formula is:

[0078] ;

[0079] in, is the correlation coefficient, N is the number of extracted samples of the operating temperature data of the transformer assembly 52 obtained in a unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer assembly 52 per unit time, is the i-th low-voltage current sample data of the low-voltage power distribution component 53 in unit time, i is a constant, i≤N, It is the average low voltage current data of the low voltage power distribution component 53 per unit time.

[0080] Furthermore, the optimization model component 20 is configured as a correction coefficient based on the correlation coefficient analysis between the high-voltage data change rate of the high-voltage input component 51 of the intelligent distribution box 50 and the temperature change rate of the transformer component 52 .

[0081] Specifically, the optimization model component 20 obtains the operating voltage of the low-voltage distribution component after power distribution according to the first power distribution instruction of the main control module 10, and inputs the operating voltage after power distribution into the correlation function between the low-voltage change rate of the low-voltage distribution component 53 and the temperature change of the transformer component 52 to perform power distribution simulation, and obtain the temperature change of the transformer component 52.

[0082] Specifically, the optimization model component 20 obtains simulated operating temperature data of the transformer component 52 according to the simulated operation, and compares the simulated operating temperature data with the operating temperature data of the transformer component 52 before the power distribution work to obtain the temperature change amplitude of the simulated operating temperature data.

[0083] Furthermore, the optimization model component 20 compares the simulated operating temperature data with the operating temperature data threshold of the transformer component 52. If the simulated operating temperature data is greater than the operating temperature data threshold of the transformer component 52, the optimization model component 20 adjusts the output mode of the intelligent distribution box 50 so that the energy storage unit of the intelligent distribution box 50 transmits current to the load equipment through the low-voltage distribution component 53, thereby reducing the workload of the transformer component 52 of the intelligent distribution box 50.

[0084] Furthermore, the optimization model component 20 compares the temperature variation amplitude of the simulated operating temperature data with the standard temperature variation amplitude range of the transformer component 52. If the temperature variation amplitude of the simulated operating temperature data exceeds the standard temperature variation amplitude range, the transformer component 52 of the intelligent distribution box 50 is subjected to on-load voltage regulation so that the transformer regulation of the transformer component 52 meets the working requirements of the load equipment.

[0085] Specifically, the optimization model component 20 can calculate the simulated operating temperature data of the transformer component 52 based on the simulated operating current of the low-voltage distribution component 53, so as to adjust the distribution instructions of the intelligent distribution box 50 in combination with the simulated operating temperature data of the transformer component 52.

[0086] Furthermore, the optimization model component 20 calculates the simulated operating temperature of the voltage component of the intelligent distribution box 50 based on the voltage data and the current data, which can improve the calculation accuracy and reliability of the optimization model component 20.

[0087] Specifically, the optimization model component 20 adjusts the power distribution instruction regulation of the intelligent distribution box 50 according to the temperature data of the transformer component 52 during operation simulation, thereby ensuring that the power distribution regulation of the intelligent distribution box 50 can meet the power distribution demand.

[0088] An embodiment of the present invention provides an Internet of Things-based smart distribution box 50 management system, which, by setting an optimization model component 20, performs operation simulation on the smart distribution box 50 according to the power consumption data of the load equipment, obtains the simulated operating temperature data of the transformer component 52 of the load equipment, compares the simulated operating temperature data of the transformer component 52 of the smart distribution box 50 with the standard threshold of the normal operating temperature data of the transformer component 52 of the smart distribution box 50, and optimizes and adjusts the power distribution adjustment strategy of the smart distribution box 50 according to the comparison result, thereby improving the reliability and stability of the management of the smart distribution box 50.

[0089] Embodiment three:

[0090] Figure 3 A schematic flow chart of a management method for an intelligent distribution box 50 based on the Internet of Things in an embodiment of the present invention is shown. The management method is adapted to the management system of the intelligent distribution box 50. The management method includes:

[0091] S11: Obtain power consumption data of the load device.

[0092] The data collection component 40 collects electrical data of a plurality of load devices to obtain power consumption data of the plurality of load devices.

[0093] The data acquisition component 40 includes sensing elements arranged in a plurality of load devices, and obtains power consumption data of the plurality of load devices based on the sensing elements. By setting a plurality of sensing elements in the load devices, when the load devices are in working state, the sensing elements are started and connected to the Internet of Things system where the intelligent distribution box 50 is located, and the working voltage and working current of the load devices are uploaded based on the sensing elements, so that the main control module 10 can obtain the operating power of the load devices, and adjust the output strategy of the intelligent distribution box 50 according to the operating power of the load devices.

[0094] S12: Generate a first power distribution instruction according to the power consumption data.

[0095] Specifically, the main control module 10 is connected to the data acquisition component 40 by signal. The main control module 10 generates a first power distribution instruction according to the power consumption data fed back by the data acquisition component 40, and sends the first power distribution instruction to the optimization model component 20. The main control module 10 can adjust the output power of the intelligent distribution box 50 based on the power consumption change data at the load end.

[0096] S13: Obtaining the operating data of the intelligent distribution box 50.

[0097] The monitoring component 30 includes a plurality of detection elements arranged in the intelligent distribution box 50, and the internal operation data of the intelligent distribution box 50 is obtained based on the detection elements. The plurality of detection elements include: a voltmeter, an ammeter, a temperature detector and other elements. The internal operation data of the intelligent distribution box 50 when working is obtained through the plurality of detection elements, so that the optimization model component 20 can simulate the power distribution operation state of the intelligent distribution box 50 according to the internal operation data of the intelligent distribution box 50 combined with the power distribution instructions of the main control module 10, and adjust the power distribution instructions of the intelligent distribution box 50.

[0098] S14: Perform power distribution operation simulation on the intelligent distribution box 50.

[0099] Specifically, the optimization model component 20 obtains the correlation function relationship between the temperature data and the voltage data of the transformer component 52 inside the smart distribution box 50 according to the internal operation data of the smart distribution box 50 obtained by the detection element.

[0100] The optimization model component 20 obtains the temperature variation of the transformer component 52 within a unit time, and the voltage variation of the intelligent distribution box 50 within a unit time.

[0101] According to the temperature detection of the transformer component 52 inside the intelligent distribution box 50 by the monitoring component 30, the operating temperature change rate of the transformer component 52 in unit time is calculated:

[0102] ;

[0103] in, is the rate of change of the operating temperature, N is the number of extracted samples of the operating temperature data of the transformer assembly 52 obtained in a unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer assembly 52 per unit time, , As unit time.

[0104] According to the voltage data detection of the high-voltage input component 51 inside the intelligent distribution box 50 by the monitoring component 30, the high-voltage voltage change rate of the high-voltage input component 51 of the intelligent distribution box 50 in unit time is calculated:

[0105] ;

[0106] in, is the high voltage data change rate, N is the number of extracted samples of the high voltage data of the high voltage input component 51 obtained in unit time, is the i-th high voltage voltage sample data of the high voltage input component 51 in unit time, i is a constant, i≤N, is the average high voltage voltage data of the high voltage input component 51 in unit time, As unit time.

[0107] According to the voltage data detection of the low-voltage distribution component 53 inside the intelligent distribution box 50 by the monitoring component 30, the low-voltage voltage change rate of the low-voltage distribution component 53 of the intelligent distribution box 50 in unit time is calculated:

[0108] ;

[0109] in, is the low voltage data change rate, N is the number of extracted samples of the low voltage data of the low voltage distribution component 53 obtained in unit time, is the i-th low voltage sample data of the low voltage distribution component 53 in unit time, i is a constant, i≤N, is the average low voltage data of the low voltage distribution component 53 in unit time, As unit time.

[0110] According to the current data detection of the low-voltage distribution component 53 inside the intelligent distribution box 50 by the monitoring component 30, the low-voltage current change rate of the low-voltage distribution component 53 of the intelligent distribution box 50 in unit time is calculated:

[0111] ;

[0112] in, is the rate of change of low-voltage current data, N is the number of extracted samples of low-voltage current data of the low-voltage power distribution component 53 obtained in unit time, is the i-th low-voltage current sample data of the low-voltage power distribution component 53 in unit time, i is a constant, i≤N, is the average low voltage current data of the low voltage power distribution component 53 in unit time, As unit time.

[0113] S15: Adjust the first power distribution instruction according to the simulation result.

[0114] Specifically, the optimization model component obtains the correlation function relationship between the temperature data and the voltage data of the transformer component inside the intelligent distribution box according to the internal operation data of the intelligent distribution box obtained by the detection element.

[0115] The optimization model component obtains the temperature variation range of the transformer component within a unit time, and the voltage variation range of the intelligent distribution box within a unit time.

[0116] According to the temperature detection of the transformer component inside the intelligent distribution box by the monitoring component, the operating temperature change rate of the transformer component in unit time is calculated:

[0117] ;

[0118] in, is the rate of change of the operating temperature, N is the number of samples of the operating temperature data of the transformer component obtained per unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer component per unit time, , As unit time.

[0119] According to the voltage data detection of the high-voltage input component inside the intelligent distribution box by the monitoring component, the high-voltage voltage change rate of the high-voltage input component of the intelligent distribution box in unit time is calculated:

[0120] ;

[0121] in, is the high voltage data change rate, N is the number of extracted samples of the high voltage data of the high voltage input component obtained per unit time, is the i-th high voltage voltage sample data of the high voltage input component in unit time, i is a constant, i≤N, is the average high voltage voltage data of the high voltage input component per unit time, As unit time.

[0122] According to the voltage data detection of the low-voltage distribution component inside the intelligent distribution box by the monitoring component, the low-voltage voltage change rate of the low-voltage distribution component of the intelligent distribution box in unit time is calculated:

[0123] ;

[0124] in, is the rate of change of low voltage data, N is the number of extracted samples of low voltage data of low voltage distribution components obtained in unit time, is the i-th low-voltage voltage sample data of the low-voltage power distribution component in unit time, i is a constant, i≤N, is the average low voltage data of the low voltage distribution component in unit time, As unit time.

[0125] According to the current data detection of the low-voltage power distribution component inside the intelligent power distribution box by the monitoring component, the low-voltage current change rate of the low-voltage power distribution component of the intelligent power distribution box in unit time is calculated:

[0126] ;

[0127] in, is the rate of change of low-voltage current data, N is the number of extracted samples of low-voltage current data of low-voltage power distribution components obtained per unit time, is the i-th low-voltage current sample data of the low-voltage distribution component in unit time, i is a constant, i≤N, is the average low-voltage current data of the low-voltage power distribution component per unit time, As unit time.

[0128] Specifically, the correlation function between the temperature change of the transformer component of the intelligent distribution box and the high voltage voltage is analyzed according to the high voltage voltage change rate of the high voltage input component of the intelligent distribution box and the operating temperature change rate of the transformer component.

[0129] Obtain the correlation function between the low voltage change rate of the low voltage power distribution component and the temperature change of the transformer component:

[0130] ;

[0131] in, is the rate of change of the operating temperature of the transformer component, is the low voltage data change rate of the low voltage distribution component, is the correlation coefficient, and μ is the correction coefficient.

[0132] The calculation formula of the correlation coefficient r is:

[0133] ;

[0134] Among them, r is the correlation coefficient, N is the number of extracted samples of the operating temperature data of the transformer component obtained in unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer component per unit time, is the i-th low-voltage voltage sample data of the low-voltage power distribution component in unit time, i is a constant, i≤N, It is the average low voltage data of the low voltage distribution component in unit time.

[0135] Furthermore, the optimization model component is configured as a correction coefficient based on a correlation coefficient analysis between the high-voltage data change rate of the high-voltage input component of the intelligent distribution box and the temperature change rate of the transformer component.

[0136] Specifically, when the low-voltage power distribution component is set to a constant voltage and constant current state, the correlation coefficient of the temperature change rate of the high-voltage input component and the transformer component is calculated to obtain a correction coefficient μ. The calculation formula of the correction coefficient μ is:

[0137] ;

[0138] Wherein, μ is the correction coefficient, N is the number of samples of the working temperature data of the transformer component obtained per unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer component per unit time, is the i-th high voltage voltage sample data of the high voltage input component in unit time, i is a constant, i≤N, It is the average high voltage voltage data of the high voltage input component per unit time.

[0139] Specifically, the correlation function between the current change rate of the low-voltage power distribution component and the temperature change of the transformer component is obtained:

[0140] ;

[0141] in, is the rate of change of the operating temperature of the transformer component, is the low voltage current data change rate of the low voltage power distribution component, is the correlation coefficient, and μ is the correction coefficient.

[0142] The correlation coefficient The calculation formula is:

[0143] ;

[0144] in, is the correlation coefficient, N is the number of samples of the working temperature data of the transformer component obtained in unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer component per unit time, is the i-th low-voltage current sample data of the low-voltage distribution component in unit time, i is a constant, i≤N, It is the average low-voltage current data of the low-voltage power distribution component per unit time.

[0145] S16: Output a second power distribution instruction.

[0146] Specifically, the optimization model component obtains the operating voltage of the low-voltage distribution component after power distribution according to the first power distribution instruction of the main control module, and inputs the operating voltage after power distribution into the correlation function between the low-voltage change rate of the low-voltage distribution component and the temperature change of the transformer component to perform power distribution simulation to obtain the temperature change of the transformer component.

[0147] Specifically, the optimization model component obtains simulated operating temperature data of the transformer component according to the simulated operation, and compares the simulated operating temperature data with the operating temperature data of the transformer component before the power distribution work to obtain the temperature change amplitude of the simulated operating temperature data.

[0148] Furthermore, the optimization model component compares the simulated operating temperature data with the operating temperature data threshold of the transformer component. If the simulated operating temperature data is greater than the operating temperature data threshold of the transformer component, the optimization model component adjusts the output mode of the intelligent distribution box so that the energy storage unit of the intelligent distribution box transmits current to the load equipment through the low-voltage distribution component, thereby reducing the workload of the transformer component of the intelligent distribution box.

[0149] Furthermore, the optimization model component compares the temperature variation amplitude of the simulated operating temperature data with the standard temperature variation amplitude range of the transformer component. If the temperature variation amplitude of the simulated operating temperature data exceeds the standard temperature variation amplitude range, the transformer component of the intelligent distribution box is subjected to on-load voltage regulation so that the transformer regulation of the transformer component meets the working requirements of the load equipment.

[0150] Specifically, the optimization model component can calculate the simulated operating temperature data of the transformer component based on the simulated operating current of the low-voltage distribution component, so as to adjust the distribution instructions of the intelligent distribution box in combination with the simulated operating temperature data of the transformer component.

[0151] Furthermore, the optimization model component calculates the simulated operating temperature of the voltage component of the intelligent distribution box based on the voltage data and the current data, which can improve the calculation accuracy and reliability of the optimization model component.

[0152] Specifically, the optimization model component adjusts the power distribution instruction regulation of the intelligent distribution box according to the temperature data of the transformer component in the running simulation, so as to ensure that the power distribution regulation of the intelligent distribution box can meet the power distribution demand.

[0153] An embodiment of the present invention provides an intelligent distribution box management method based on the Internet of Things, which obtains power consumption data of several load devices, generates a first distribution instruction according to the power consumption data of the load devices, performs operation simulation by optimizing a model component in combination with the first distribution instruction and internal working data of the distribution box, obtains the temperature change of the transformer component, and adjusts the first distribution instruction according to the simulated temperature change of the transformer component to obtain a second distribution instruction, and simulates and optimizes the distribution instruction by optimizing the model component to improve the safety and reliability of the distribution management of the distribution box.

[0154] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the storage medium may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0155] In addition, the embodiments of the present invention are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. An intelligent distribution box management system based on the Internet of Things, characterized in that: The intelligent distribution box management system includes: a data acquisition component, an optimization model component, a monitoring component and a main control module; The main control module is connected to the data acquisition component by signal, and the data acquisition component is used to obtain power consumption data of several load devices and send the power consumption data to the main control module; The optimization model component is connected to the monitoring component by signal, and the monitoring component is used to obtain internal operation data of the intelligent distribution box; The main control module generates a first power distribution instruction according to the power consumption data fed back by the data acquisition component, and sends the first power distribution instruction to the optimization model component; The optimization model component performs intelligent distribution box simulation operation based on the internal operation data and the first power distribution instruction, and outputs a second power distribution instruction; The intelligent distribution box is provided with a transformer component, a low-voltage distribution component and a high-voltage input component. The optimization model component obtains the correlation function relationship between the temperature data and the voltage data of the transformer component inside the intelligent distribution box according to the internal operation data of the intelligent distribution box obtained by the monitoring component; Obtain the correlation function between the low voltage change rate of the low voltage power distribution component and the temperature change of the transformer component: ； in, is the rate of change of the operating temperature of the transformer component, is the low voltage data change rate of the low voltage distribution component, is the correlation coefficient, μ is the correction coefficient; The calculation formula of the correlation coefficient r is: ； Among them, r is the correlation coefficient, N is the number of extracted samples of the operating temperature data of the transformer component obtained in unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer component per unit time, is the i-th low-voltage voltage sample data of the low-voltage power distribution component in unit time, i is a constant, i≤N, It is the average low voltage data of the low voltage distribution component in unit time; When the low-voltage power distribution component is set to a constant voltage and constant current state, the correlation coefficient of the temperature change rate of the high-voltage input component and the transformer component is calculated to obtain a correction coefficient μ. The calculation formula of the correction coefficient μ is: ； Wherein, μ is the correction coefficient, N is the number of samples of the operating temperature data of the transformer component obtained per unit time, is the i-th working temperature data sample in unit time, i is a constant, i≤N, is the average operating temperature of the transformer component per unit time, is the i-th high voltage voltage sample data of the high voltage input component in unit time, i is a constant, i≤N, It is the average high voltage voltage data of the high voltage input component in unit time; The optimization model component obtains the operating voltage of the low-voltage distribution component after power distribution according to the received first power distribution instruction; Inputting the operating voltage after power distribution into the correlation function between the low voltage change rate of the low voltage power distribution component and the temperature change of the transformer component to perform power distribution simulation, and obtaining the temperature change of the transformer component; The optimization model component compares the simulated operating temperature data with the operating temperature data threshold of the transformer component. If the simulated operating temperature data is greater than the operating temperature data threshold of the transformer component, the optimization model component adjusts the output mode of the intelligent distribution box so that the energy storage unit of the intelligent distribution box transmits current to the load device through the low-voltage distribution component; The optimization model component compares the temperature variation amplitude of the simulated operating temperature data with the standard temperature variation amplitude range of the transformer component. If the temperature variation amplitude of the simulated operating temperature data exceeds the standard temperature variation amplitude range, the transformer component of the intelligent distribution box is subjected to on-load voltage regulation.

2. The intelligent distribution box management system based on the Internet of Things according to claim 1, characterized in that: The data acquisition component includes sensing elements arranged on a plurality of load devices, and acquires power consumption data of the plurality of load devices based on the sensing elements.

3. The intelligent distribution box management system based on the Internet of Things as claimed in claim 1, characterized in that: The monitoring component includes a plurality of detection elements arranged in the intelligent distribution box, and the internal operation data of the intelligent distribution box is obtained based on the detection elements.

4. The intelligent distribution box management system based on the Internet of Things as claimed in claim 3 is characterized in that: The high-voltage input component is connected to the high-voltage power grid and is used to receive the high-voltage current input from the high-voltage power grid to the intelligent distribution box; The transformer assembly is used to perform a voltage reduction operation on the high voltage current, so that the high voltage current can adapt to the power distribution work of the low voltage power distribution assembly after the voltage reduction operation of the transformer assembly; The low-voltage power distribution component is connected to the load device, so that the low-voltage power distribution component can distribute the corresponding working voltage to the load device according to the power demand of the load device.

5. The intelligent distribution box management system based on the Internet of Things as claimed in claim 4 is characterized in that: The monitoring component obtains the input voltage of the high-voltage input component and the output voltage of the low-voltage distribution component based on the detection of the high-voltage input component, the transformer component and the low-voltage distribution component by a plurality of the detection elements, and simultaneously obtains the temperature data of the transformer component.

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