Energy data management system and method based on Internet of Things platform

Abstract

The present invention discloses an energy data management system and method based on an Internet of Things platform. The system includes: an equipment monitoring module, an intelligent communication module, a cloud analysis module, a risk handling module and a maintenance notification module. The equipment detection module is used to detect data of power equipment, the intelligent communication module is used to upload data to the data cloud, the cloud analysis module is used to analyze data, make data charts and mark risk components, the risk handling module is used to detect equipment containing risk components and slowly reduce its voltage, and the maintenance notification module is used to send maintenance notifications to user terminals. The present invention can perform real-time detection of power equipment and components therein to avoid safety accidents, realize thermal maintenance of risk components without power outages, and at the same time reduce the impact of equipment self-inductance current on the power system, thereby ensuring the safety of the power system.

Description

Technical Field

[0001] The present invention relates to the field of energy management technology, and in particular to an energy data management system and method based on an Internet of Things platform. Background Art

[0002] With the development of power technology, high-quality and reliable electricity has become a fundamental requirement for business production, especially with the implementation of large-scale power distribution systems, which enable users to control and manage power supply. However, due to the erratic nature of business electricity consumption and the constant switching of distribution system operating conditions, not only is electricity usage data difficult to compile, but distribution equipment that frequently switches operating conditions, such as filter cabinets and compensation cabinets, is also more susceptible to component aging. When component aging reaches a certain level, its temperature rises rapidly, potentially causing fires in distribution equipment and posing a safety hazard to businesses.

[0003] Existing energy data management solutions focus on real-time monitoring of power distribution equipment. When problems such as overheating or abnormal power data are detected, the power supply to the equipment is disconnected, and an alert is issued to operations and maintenance personnel, prompting them to replace the component, thereby troubleshooting potential safety hazards in the power equipment. However, when operations and maintenance personnel receive the alert, the company's production line is often still in operation. Even if only a single component of a single device is damaged, replacing the component requires shutting down the entire power system. During this period, production is suspended due to power shortages, resulting in unnecessary losses.

[0004] In addition, under AC voltage, a single device, especially one containing a large number of capacitors and inductors, will generate a certain amount of self-inductance current in the power system when the power is suddenly cut off, which can easily damage other normally operating power equipment, causing property losses and safety hazards to the enterprise. Summary of the Invention

[0005] The purpose of the present invention is to provide an energy data management system and method based on the Internet of Things platform to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: an energy data management system based on the Internet of Things platform, comprising: an equipment monitoring module, an intelligent communication module, a cloud analysis module, a risk management module and a maintenance notification module;

[0007] The equipment monitoring module is used to collect voltage and current data collected by the power sensor, calculate the load value of the power system and the power information of the equipment, collect component data collected by the component sensor, and store the data in the database;

[0008] The intelligent communication module is used to read various types of collected data from the database, upload the data to the cloud platform through the wireless network card, and receive commands sent by the cloud platform and transmit the command information to each electrical device;

[0009] The cloud analysis module is used to visualize the uploaded data and organize it into charts for reference by operation and maintenance personnel; based on the data of the components in the cloud platform, it calculates the risk factor of each component, screens out components with risk factors higher than the safety parameter value, marks these components as risk components, marks the equipment containing risk components as risk equipment, calculates the safety voltage of the risk equipment, and calculates the voltage reduction gradient per second based on the power system parameters;

[0010] The risk management module is used to send a maintenance waiting instruction to the intelligent communication module when detecting a device marked as risky by the system, so that maintenance personnel can prepare to replace components in advance; send a transfer command to the power system through the cloud platform, gradually reducing the voltage supply to the risky device according to the calculated voltage reduction gradient per second until the voltage of the risky device is reduced to a safe voltage; after the device stops working, the maintenance personnel are notified to replace the device components;

[0011] The maintenance notification module is used to receive instructions from the intelligent communication module and provide power data and visual charts to the user terminal. When receiving a risk equipment notification, it notifies the operation and maintenance personnel of the number of the risk equipment and risk components, so that they can prepare to replace the components in advance. When the risk equipment stops working, the operation and maintenance personnel are notified to go and replace the risk components. After the maintenance is completed, the maintenance completion information is sent to the Internet of Things. The system reconnects the repaired equipment to the power system and removes its risk mark.

[0012] Furthermore, the equipment monitoring module includes: a load detection unit, a power detection unit, a component detection unit and a database unit;

[0013] The load detection unit is used to measure the total voltage and total current of the entire power system, calculate the total load of the power system based on the measured voltage and current data, and store the data in the database module;

[0014] The power detection unit is used to detect the current and voltage data of a single device, calculate the power of the device based on the measured voltage and current data, and store the device number, device type, device self-inductance coefficient, and the voltage, current, and power data of the device at each time point in the database;

[0015] The component detection unit is used to detect the capacitance of the capacitor element, the resistance of the resistor element and the opening and closing data of the circuit breaker, calculate the capacitance value of the capacitor element and the resistance value of the resistor element based on the obtained data, and store the collected data in the database;

[0016] The database unit is used to store various collected data;

[0017] Furthermore, the cloud analysis module includes: a visualization processing unit, an equipment status determination unit, a component risk calculation unit, and a voltage gradient calculation unit;

[0018] The visualization processing unit is used to receive information uploaded to the cloud platform, draw a line graph of the current, voltage, and power of each device with time as the horizontal axis and the current, voltage, and power of each device as the vertical axis, and feed the graph back to the user terminal; draw a graph of the capacitance change over time for each capacitor element of each device, and draw a graph of the resistance change over time for each resistor element of each device, and feed the graph back to the user terminal;

[0019] The component risk calculation unit is used to detect changes in the capacitance and resistance values of a component at preset intervals, subtract the two detected capacitance and resistance values, and take the absolute value to calculate its risk factor. The component risk factor is compared with the safety parameter value preset by the system. If the component risk factor is greater than the safety parameter value, it is marked as a risk component. The total number of opening and closing times of the circuit breaker is detected. When the total number of opening and closing times of the circuit breaker reaches its service life, the circuit breaker is marked as a risk component, and the equipment containing the risk component is marked as risk equipment.

[0020] The device status identification unit is used to mark the device containing risk components as risky devices and calculate the safe voltage of the device based on the number and type of risk components contained in the device;

[0021] The voltage gradient calculation unit is used to read the real-time voltage and current values of the risk equipment, calculate the voltage gradient of the equipment per second based on the maximum current of the equipment, the load of the power system and the self-inductance coefficient of the equipment, and feed the calculated data back to the cloud platform;

[0022] The risk handling unit includes: a risk equipment monitoring unit, a circuit switching unit and a power restoration unit;

[0023] The risk equipment monitoring unit is used to detect risk equipment containing risk components, record the equipment number, equipment name, risk component number and risk component name data, and send the data to the intelligent communication module, which transmits the data and detects the operating status of the risk equipment. When the risk equipment stops working, a notification is sent to the intelligent communication module;

[0024] The circuit switching unit is used to read the safety voltage of the risk equipment. When the voltage of the equipment is higher than the safety voltage value of the risk equipment, the voltage of the risk equipment is gradually reduced according to the calculated voltage reduction rate per second until it is reduced to the safety voltage.

[0025] The power restoration unit is used to reconnect the repaired risk equipment to the power system after receiving the maintenance completion information, remove its risk equipment mark, and restore the normal operation of the system.

[0026] The maintenance notification module includes: a user terminal unit and a user control unit;

[0027] The user terminal unit is used to receive charts and equipment data provided by the cloud platform, display them on the user terminal through the software application, issue a warning to the user terminal when a risky device is found, provide the number and name of the risky device, the number and name of the risky component, notify maintenance personnel to prepare maintenance materials in advance, and send a maintenance reminder to the user when receiving a notification that the risky device has stopped working;

[0028] The user control unit is used to receive the maintenance end instruction from the user, feedback the re-power supply information to the user terminal, and transmit the power supply restoration instruction to the Internet of Things cloud platform.

[0029] The energy data management method based on the Internet of Things includes the following steps:

[0030] S100. Sensors are embedded in devices and components. After the power system is working, the sensors record device data and component data at preset intervals. At the same time, the actual power is calculated based on the voltage and current values of each device, and the load value of the power system is calculated based on the overall current and voltage values of the power system.

[0031] S200. The data recorded by the sensor in step S100, the power system power, the power system load value, the device number and the type of the device are uploaded to the cloud platform in real time for analysis in step S300;

[0032] S300. After the cloud platform receives the data from step S200, it draws a line graph of the current, voltage, and power of each device, and draws a curve graph of the capacitance and resistance change of each component;

[0033] S400. Monitor the capacitance value of the capacitor and the resistance value of the resistor. Subtract the two uploaded capacitance or resistance values and take the absolute value to calculate the risk factor. When the risk factor of a component is greater than the system's preset safety parameter value, the component is marked as a risk component. Detect the number of times a circuit breaker is opened and closed. When the total number of times a circuit breaker is opened and closed reaches its service life, the circuit breaker is marked as a risk component, and the equipment containing the risk component is marked as a risk device.

[0034] S500. Read the real-time voltage and current values of the risk device in step S400, calculate the voltage gradient of the device per second based on the maximum current of the device, the load of the power system and the self-inductance of the device; calculate the safe voltage of the risk device based on the number and type of risk elements contained;

[0035] S600. Based on the safety voltage calculated in step S500, if the voltage of the risky device exceeds its safety voltage, gradually reduce the voltage on the risky device by a voltage gradient per second calculated in step S500, until the voltage of the risky device is reduced to the safety voltage. A maintenance notice is then issued to maintenance personnel via the cloud platform, along with the name and number of the risky device and risky component. After the maintenance is complete, the device is reconnected and its flag is removed.

[0036] Furthermore, step S100 includes:

[0037] Step S101. At predetermined intervals T0, record the total voltage V0 and total current I0 of the power system, the voltage V1 and current I1 of the equipment, the capacitance C of the capacitor, the resistance R of the resistor, and the circuit breaker open / close state S, where S = 1 indicates that the circuit breaker is open, and S = 0 indicates that the circuit breaker is open.

[0038] Step S102. Calculate the actual power P1 of each device, where P1 = V1 * I1, and calculate the load R0 of the power system, where R0 = V0 / I0;

[0039] In step S300, a line graph of the current, voltage, and power of each device is drawn with time as the horizontal axis and the current, voltage, and power of each device as the vertical axis. A graph of the capacitance versus time is drawn for each capacitor element of each device, and a graph of the resistance versus time is drawn for each resistor element of each device.

[0040] Furthermore, step S400 includes:

[0041] Step S401: Monitor the capacitor element. The capacitance value of a capacitor element measured at time T0 is recorded as C1, and the capacitance value measured at the next time 2T0 is recorded as C2. Calculate the capacitor risk coefficient E1, where E1 = |C1-C2|. When E1>EC0, where EC0 represents the safety parameter of the capacitor element, the capacitor element is marked as a risk element.

[0042] Step S402 monitors the resistor element. The resistance value of a resistor element measured at time T0 is recorded as R1, and the resistance value measured at the next time 2T0 is recorded as R2. The risk factor E2 is calculated, where E2 = |R1-R2|. When E2>ER0, where ER0 represents the safety parameter of the resistor element, the resistor element is marked as a risk element.

[0043] Step S403: Count the total number of opening and closing times of the circuit breaker as S1, and the life of the circuit breaker as S0. When S1>S0 of a circuit breaker, mark the circuit breaker as a risk element;

[0044] Step S404: Mark the device containing risky components as risky device;

[0045] Furthermore, in step S500, based on the data obtained from the cloud platform, the system obtains the historical maximum current collected from the risk device, records it as Imax, and calculates the voltage gradient △U of the device per second according to the following formula:

[0046]

[0047] Among them, the equipment current is I1, the total load of the power system is R0, and the self-inductance coefficient of the equipment is L;

[0048] Calculate the safety voltage U of the risk equipment according to the following formula:

[0049] U=V1-(a*U1+b*U2+c*U3)

[0050] Wherein, the equipment voltage is V1, the number of risk capacitor elements is a, the number of risk resistor elements is b, the number of risk circuit breaker elements is c, U1 represents the safety voltage of the risk capacitor element, U2 represents the safety voltage of the risk resistor element, and U3 represents the safety voltage of the risk circuit breaker element. U1, U2, and U3 are preset in the system;

[0051] Furthermore, step S600 includes:

[0052] Step S601: gradually reduce the voltage on the risky device, with the voltage reduction value per second equal to ∆U. ∆U is updated in real time as the device current I1 changes, until the voltage on the risky device is reduced to a safe voltage.

[0053] Step S602: Detect the status of risky equipment and issue a reminder when the risky equipment stops working;

[0054] Step S603: After receiving the reminder, a maintenance notice is issued to the maintenance personnel through the cloud platform. The maintenance notice includes: the device number, device type, component number and component type to be repaired; after the maintenance is completed, the risk device is reconnected and its mark is cancelled.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] 1. Based on the Internet of Things technology, this invention uploads real-time monitoring data of equipment data to the cloud platform, enabling operation and maintenance personnel to understand the operating status of power equipment at any time and make corresponding adjustments to the power equipment;

[0057] 2. This invention can establish a power system working model to uniformly manage every power device within the enterprise. When a device risk is detected, the cloud platform automatically notifies the operation and maintenance personnel, intelligently analyzes the working status of the risk device, and gradually reduces the power of the risk device until it can operate safely. This ensures that the self-inductance current does not exceed the maximum current of the device during normal operation. This prevents the induced current generated by a sudden power outage during component replacement from damaging other power devices, thus achieving self-inductance protection for the device and avoiding safety accidents.

[0058] 3. The present invention can monitor the parameters of each component in real time, evaluate the risk factor of each component, and inform the operation and maintenance personnel; maintain the risk equipment at low power to ensure safety, and when the risk equipment stops working, notify the maintenance personnel to replace the components with high risk factors, realizing hot maintenance and preventive maintenance, and avoiding the situation where enterprises need to shut down the power supply and stop production during the operation of production equipment to wait for the completion of power system maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0060] Figure 1 It is a structural diagram of the energy data management system based on the Internet of Things platform of the present invention;

[0061] Figure 2 Schematic diagram of the steps of the energy data management method based on the Internet of Things platform of the present invention; DETAILED DESCRIPTION

[0062] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0063] See also Figure 1, the present invention provides a technical solution: an energy data management system based on the Internet of Things platform, including: an equipment monitoring module, an intelligent communication module, a cloud analysis module, a risk management module and a maintenance notification module;

[0064] The equipment monitoring module is used to collect voltage and current data collected by the power sensor, calculate the load value of the power system and the power information of the equipment, collect component data collected by the component sensor, and store the data in the database;

[0065] The equipment monitoring module includes: a load detection unit, a power detection unit, a component detection unit and a database unit;

[0066] The load detection unit is used to measure the total voltage and total current of the entire power system, calculate the total load of the power system based on the measured voltage and current data, and store the data in the database module;

[0067] The power detection unit is used to detect the current and voltage data of a single device, calculate the power of the device based on the measured voltage and current data, and store the device number, device type, device self-inductance coefficient, and the voltage, current, and power data of the device at each time point in the database;

[0068] The component detection unit is used to detect the capacitance of the capacitor element, the resistance of the resistor element and the opening and closing data of the circuit breaker, calculate the capacitance value of the capacitor element and the resistance value of the resistor element based on the obtained data, and store the collected data in the database;

[0069] The database unit is used to store various collected data;

[0070] The intelligent communication module is used to read various types of collected data from the database, upload the data to the cloud platform through the wireless network card, and receive commands sent by the cloud platform and transmit the command information to each electrical device;

[0071] The cloud analysis module is used to visualize the uploaded data and organize it into charts for reference by operation and maintenance personnel; based on the data of the components in the cloud platform, it calculates the risk factor of each component, screens out components with risk factors higher than the safety parameter value, marks these components as risk components, marks the equipment containing risk components as risk equipment, calculates the safety voltage of the risk equipment, and calculates the voltage reduction gradient per second based on the power system parameters;

[0072] The cloud analysis module includes: a visualization processing unit, an equipment status determination unit, a component risk calculation unit, and a voltage gradient calculation unit;

[0073] The visualization processing unit is used to receive information uploaded to the cloud platform, draw a line graph of the current, voltage, and power of each device with time as the horizontal axis and the current, voltage, and power of each device as the vertical axis, and feed the graph back to the user terminal; draw a graph of the capacitance change over time for each capacitor element of each device, and draw a graph of the resistance change over time for each resistor element of each device, and feed the graph back to the user terminal;

[0074] The component risk calculation unit is used to detect changes in the capacitance and resistance values of a component at preset intervals, subtract the two detected capacitance and resistance values, and take the absolute value to calculate its risk factor. The component risk factor is compared with the safety parameter value preset by the system. If the component risk factor is greater than the safety parameter value, it is marked as a risk component. The total number of opening and closing times of the circuit breaker is detected. When the total number of opening and closing times of the circuit breaker reaches its service life, the circuit breaker is marked as a risk component, and the equipment containing the risk component is marked as risk equipment.

[0075] The device status identification unit is used to mark the device containing risk components as risky devices and calculate the safe voltage of the device based on the number and type of risk components contained in the device;

[0076] The voltage gradient calculation unit is used to read the real-time voltage and current values of the risk equipment, calculate the voltage gradient of the equipment per second based on the maximum current of the equipment, the load of the power system and the self-inductance coefficient of the equipment, and feed the calculated data back to the cloud platform;

[0077] The risk management module is used to send a maintenance waiting instruction to the intelligent communication module when detecting a device marked as risky by the system, so that maintenance personnel can prepare to replace components in advance; send a transfer command to the power system through the cloud platform, gradually reducing the voltage supply to the risky device according to the calculated voltage reduction gradient per second until the voltage of the risky device is reduced to a safe voltage; after the device stops working, the maintenance personnel are notified to replace the device components;

[0078] The risk handling unit includes: a risk equipment monitoring unit, a circuit switching unit and a power restoration unit;

[0079] The risk equipment monitoring unit is used to detect risk equipment containing risk components, record the equipment number, equipment name, risk component number and risk component name data, and send the data to the intelligent communication module, which transmits the data and detects the operating status of the risk equipment. When the risk equipment stops working, a notification is sent to the intelligent communication module;

[0080] The circuit switching unit is used to read the safety voltage of the risk equipment. When the voltage of the equipment is higher than the safety voltage value of the risk equipment, the voltage of the risk equipment is gradually reduced according to the calculated voltage reduction rate per second until it is reduced to the safety voltage.

[0081] The power restoration unit is used to reconnect the repaired risk equipment to the power system after receiving the maintenance completion information, remove its risk equipment mark, and restore the normal operation of the system.

[0082] The maintenance notification module is used to receive instructions from the intelligent communication module and provide power data and visual charts to the user terminal. When receiving a risk equipment notification, it notifies the operation and maintenance personnel of the number of the risk equipment and risk components, so that they can prepare to replace the components in advance. When the risk equipment stops working, the operation and maintenance personnel are notified to go and replace the risk components. After the maintenance is completed, the maintenance completion information is sent to the Internet of Things. The system reconnects the repaired equipment to the power system and removes its risk mark.

[0083] The maintenance notification module includes: a user terminal unit and a user control unit;

[0084] The user terminal unit is used to receive charts and equipment data provided by the cloud platform, display them on the user terminal through the software application, issue a warning to the user terminal when a risky device is found, provide the number and name of the risky device, the number and name of the risky component, notify maintenance personnel to prepare maintenance materials in advance, and send a maintenance reminder to the user when receiving a notification that the risky device has stopped working;

[0085] The user control unit is used to receive the maintenance end instruction from the user, feedback the re-power supply information to the user terminal, and transmit the power supply restoration instruction to the Internet of Things cloud platform.

[0086] The energy data management method based on the Internet of Things includes the following steps:

[0087] S100. Sensors are embedded in devices and components. After the power system is working, the sensors record device data and component data at preset intervals. At the same time, the actual power is calculated based on the voltage and current values of each device, and the load value of the power system is calculated based on the overall current and voltage values of the power system.

[0088] Step S100 includes:

[0089] Step S101. At predetermined intervals T0, record the total voltage V0 and total current I0 of the power system, the voltage V1 and current I1 of the equipment, the capacitance C of the capacitor, the resistance R of the resistor, and the circuit breaker open / close state S, where S = 1 indicates that the circuit breaker is open, and S = 0 indicates that the circuit breaker is open.

[0090] Step S102. Calculate the actual power P1 of each device, where P1 = V1 * I1, and calculate the load R0 of the power system, where R0 = V0 / I0;

[0091] S200. The data recorded by the sensor in step S100, the power system power, the power system load value, the device number and the type of the device are uploaded to the cloud platform in real time for analysis in step S300;

[0092] S300. After the cloud platform receives the data from step S200, it draws a line graph of the current, voltage, and power of each device, and draws a curve graph of the capacitance and resistance change of each component;

[0093] In step S300, a line graph of the current, voltage, and power of each device is drawn with time as the horizontal axis and the current, voltage, and power of each device as the vertical axis. A graph of the capacitance versus time is drawn for each capacitor element of each device, and a graph of the resistance versus time is drawn for each resistor element of each device.

[0094] S400. Monitor the capacitance value of the capacitor and the resistance value of the resistor. Subtract the two uploaded capacitance or resistance values and take the absolute value to calculate the risk factor. When the risk factor of a component is greater than the system's preset safety parameter value, the component is marked as a risk component. Detect the number of times a circuit breaker is opened and closed. When the total number of times a circuit breaker is opened and closed reaches its service life, the circuit breaker is marked as a risk component, and the equipment containing the risk component is marked as a risk device.

[0095] Step S400 includes:

[0096] Step S401: Monitor the capacitor element. The capacitance value of a capacitor element measured at time T0 is recorded as C1, and the capacitance value measured at the next time 2T0 is recorded as C2. Calculate the capacitor risk coefficient E1, where E1 = |C1-C2|. When E1>EC0, where EC0 represents the safety parameter of the capacitor element, the capacitor element is marked as a risk element.

[0097] Step S402 monitors the resistor element. The resistance value of a resistor element measured at time T0 is recorded as R1, and the resistance value measured at the next time 2T0 is recorded as R2. The risk factor E2 is calculated, where E2 = |R1-R2|. When E2>ER0, where ER0 represents the safety parameter of the resistor element, the resistor element is marked as a risk element.

[0098] Step S403: Count the total number of opening and closing times of the circuit breaker as S1, and the life of the circuit breaker as S0. When S1>S0 of a circuit breaker, mark the circuit breaker as a risk element;

[0099] Step S404: Mark the device containing risky components as risky device;

[0100] S500. Read the real-time voltage and current values of the risk device in step S400, calculate the voltage gradient of the device per second based on the maximum current of the device, the load of the power system and the self-inductance of the device; calculate the safe voltage of the risk device based on the number and type of risk elements contained;

[0101] In step S500, based on the data obtained from the cloud platform, the system obtains the historical maximum current collected from the risk device, records it as Imax, and calculates the voltage gradient △U of the device per second according to the following formula:

[0102] ;

[0103] Among them, the equipment current is I1, the total load of the power system is R0, and the self-inductance coefficient of the equipment is L;

[0104] Calculate the safety voltage U of the risk equipment according to the following formula:

[0105] U=V1-(a*U1+b*U2+c*U3)

[0106] Wherein, the equipment voltage is V1, the number of risk capacitor elements is a, the number of risk resistor elements is b, the number of risk circuit breaker elements is c, U1 represents the safety voltage of the risk capacitor element, U2 represents the safety voltage of the risk resistor element, and U3 represents the safety voltage of the risk circuit breaker element. U1, U2, and U3 are preset in the system;

[0107] S600. Based on the safety voltage calculated in step S500, if the voltage of the risky device exceeds its safety voltage, gradually reduce the voltage on the risky device by a voltage gradient per second calculated in step S500, until the voltage of the risky device is reduced to the safety voltage. A maintenance notice is then issued to maintenance personnel via the cloud platform, along with the name and number of the risky device and risky component. After the maintenance is complete, the device is reconnected and its flag is removed.

[0108] Step S600 includes:

[0109] Step S601: gradually reducing the voltage on the risky device, with the voltage reduction value per second being equal to ∆U, until the voltage on the risky device is reduced to a safe voltage;

[0110] Step S602: Detect the status of risk devices and issue a reminder when a risk device stops working;

[0111] Step S603: After receiving the reminder, send a maintenance notice to the maintenance personnel through the cloud platform. The maintenance notice includes: the device number to be maintained, device type, component number, and component type; after the maintenance is completed, reconnect the risk device and cancel its mark. Embodiment

[0112] There are 4 devices of the same type in a power system, with device numbers 1, 2, 3, and 4 respectively. The device parameters are as follows: the rated power of the device P0 = 1100W, the inductance coefficient of the device L = 2, the safety factor of the capacitor element EC0 = 0.1F, the safety factor of the resistor element ER0 = 1Ω, the sampling interval T0 = 30 seconds, the breaker life S0 = 1000 times, the power system is connected to a 220V constant voltage alternating current, and the system presets U1 = 10, U2 = 5, U3 = 50;

[0113] After the power system starts working, the system device detection module detects that the voltage of device 1 is 220v and the current is 5A, the voltage of device 2 is 220V and the current is 2A, the voltage of device 3 is 220V and the current is 1A, the voltage of device 4 is 220V and the current is 3A, the total voltage of the power system is 220V, and the current is 11A. Calculate the total load R0 = 20Ω;

[0114] For the first time, the capacitance values of 8 capacitor elements in device 1 are 1F, and the resistance values of 2 resistor elements are 100Ω. The breaker has been opened and closed 500 times. For the second time, it is detected that the capacitance values of 8 capacitor elements are 1.2F, and the resistance values of 2 resistor elements are 101Ω. The system uploads all the collected data to the Internet of Things cloud platform through the intelligent communication module;

[0115] The cloud platform receives the data, calculates that the power of device 1 is 1100W, the power of device 2 is 440W, the power of device 3 is 220W, and the power of device 4 is 660W. Records the current, voltage, and power data of each device in the database, makes a line chart together with the previously received data, and sends the chart to the user terminal;

[0116] The cloud platform changes the capacitance and resistance of all detection components, and draws them into a chart and sends it to the user terminal; it is detected that the risk coefficient E1 of the capacitor in device 1 = 0.2F, exceeding the safety factor of the capacitor element. The system marks 8 capacitor elements as risk components and records their numbers. The risk coefficient E2 of the resistor = 1Ω, not greater than the safety factor of the resistor element. The number of breaker openings and closings S1 < S0, not within the risk range. Since there are risk components, device 1 is marked as a risk device;

[0117] The system records the number of the risky device and the number of the risky component and feeds them back to the user terminal; it calculates the historical maximum current of device 1, Imax = 6A, and the voltage gradient of device 1 per second, ∆U = 2*20*(6-5) = 40V, and the safety voltage, U = 140V. It then reduces the voltage across device 1 by 40V per second until it reaches 140V; it sends a maintenance notice to the user terminal, and after the maintenance is completed, it reconnects device 1 to the power system and removes its mark.

[0118] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0119] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. Energy data management system based on the Internet of Things platform, characterized by: The system includes: an equipment monitoring module, an intelligent communication module, a cloud analysis module, a risk management module and a maintenance notification module; The equipment monitoring module is used to collect voltage and current data collected by the power sensor, calculate the load value of the power system and the power information of the equipment, collect component data collected by the component sensor, and store the data in the database; The intelligent communication module is used to read various types of collected data from the database, upload the data to the cloud platform through the wireless network card, and receive commands sent by the cloud platform and transmit the command information to each electrical device; The cloud analysis module is used to visualize the uploaded data and organize it into charts for reference by operation and maintenance personnel; based on the data of the components in the cloud platform, it calculates the risk factor of each component, screens out components with risk factors higher than the safety parameter value, marks these components as risk components, marks the equipment containing risk components as risk equipment, calculates the safety voltage of the risk equipment, and calculates the voltage reduction gradient per second based on the power system parameters; The risk management module is used to send a maintenance waiting instruction to the intelligent communication module when detecting a device marked as risky by the system, so that maintenance personnel can prepare to replace components in advance; send a transfer command to the power system through the cloud platform, gradually reducing the voltage supply to the risky device according to the calculated voltage reduction gradient per second until the voltage of the risky device is reduced to a safe voltage; after the device stops working, the maintenance personnel are notified to replace the device components; The maintenance notification module is used to receive instructions from the intelligent communication module and provide power data and visual charts to the user terminal. When receiving a risk equipment notification, it notifies the operation and maintenance personnel of the number of the risk equipment and risk components, so that they can prepare to replace the components in advance. When the risk equipment stops working, the operation and maintenance personnel are notified to go and replace the risky components. After the maintenance is completed, the maintenance completion information is sent to the Internet of Things, and the system reconnects the repaired equipment to the power system and removes its risk mark.

2. The energy data management system based on the Internet of Things platform according to claim 1 is characterized in that: The equipment monitoring module includes: a load detection unit, a power detection unit, a component detection unit and a database unit; The load detection unit is used to measure the total voltage and total current of the entire power system, calculate the total load of the power system based on the measured voltage and current data, and store the data in the database module; The power detection unit is used to detect the current and voltage data of a single device, calculate the power of the device based on the measured voltage and current data, and store the device number, device type, device self-inductance coefficient, and the voltage, current, and power data of the device at each time point in the database; The component detection unit is used to detect the capacitance of the capacitor element, the resistance of the resistor element and the opening and closing data of the circuit breaker, calculate the capacitance value of the capacitor element and the resistance value of the resistor element based on the obtained data, and store the collected data in the database; The database unit is used to store various collected data.

3. The energy data management system based on the Internet of Things platform according to claim 1 is characterized in that: The cloud analysis module includes: a visualization processing unit, a component risk calculation unit, an equipment status determination unit and a voltage gradient calculation unit; The visualization processing unit is used to receive information uploaded to the cloud platform, draw a line graph of the current, voltage, and power of each device with time as the horizontal axis and the current, voltage, and power of each device as the vertical axis, and feed the graph back to the user terminal; draw a graph of the capacitance change over time for each capacitor element of each device, and draw a graph of the resistance change over time for each resistor element of each device, and feed the graph back to the user terminal; The component risk calculation unit is used to detect changes in the capacitance and resistance values of a component at preset intervals, subtract the two detected capacitance and resistance values, and take the absolute value to calculate its risk factor. The component risk factor is compared with the safety parameter value preset by the system. If the component risk factor is greater than the safety parameter value, it is marked as a risk component. The total number of opening and closing times of the circuit breaker is detected. When the total number of opening and closing times of the circuit breaker reaches its service life, the circuit breaker is marked as a risk component, and the equipment containing the risk component is marked as risk equipment. The device status identification unit is used to mark the device containing risk components as risky devices and calculate the safe voltage of the device based on the number and type of risk components contained in the device; The voltage gradient calculation unit is used to read the real-time voltage and current values of the risk equipment, calculate the voltage gradient of the equipment per second based on the maximum current of the equipment, the load of the power system and the self-inductance coefficient of the equipment, and feed the calculated data back to the cloud platform.

4. The energy data management system based on the Internet of Things platform according to claim 1 is characterized in that: The risk handling module includes: a risk equipment monitoring unit, a circuit switching unit and a power restoration unit; The risk equipment monitoring unit is used to detect risk equipment containing risk components, record the equipment number, equipment name, risk component number and risk component name data, and send the data to the intelligent communication module, which transmits the data and detects the operating status of the risk equipment. When the risk equipment stops working, a notification is sent to the intelligent communication module; The circuit switching unit is used to read the safety voltage of the risk equipment. When the voltage of the risk equipment is higher than the safety voltage value of the risk equipment, the voltage of the risk equipment is gradually reduced according to the calculated voltage reduction rate per second until it is reduced to the safety voltage. The power restoration unit is used to reconnect the repaired risk equipment to the power system after receiving the maintenance completion information, remove its risk equipment mark, and restore the normal operation of the system.

5. The energy data management system based on the Internet of Things platform according to claim 1 is characterized in that: The maintenance notification module includes: a user terminal unit and a user control unit; The user terminal unit is used to receive charts and equipment data provided by the cloud platform, display them on the user terminal through the software application, issue a warning to the user terminal when a risky device is found, provide the number and name of the risky device, the number and name of the risky component, notify maintenance personnel to prepare maintenance materials in advance, and send a maintenance reminder to the user when receiving a notification that the risky device has stopped working; The user control unit is used to receive the maintenance end instruction from the user, feedback the re-power supply information to the user terminal, and transmit the power supply restoration instruction to the Internet of Things cloud platform.

6. An energy data management method based on the Internet of Things platform is characterized by: The following steps are involved: S100. Sensors are embedded in devices and components. After the power system is working, the sensors record device data and component data at preset intervals. At the same time, the actual power is calculated based on the voltage and current values of each device, and the load value of the power system is calculated based on the overall current and voltage values of the power system. S200. The data recorded by the sensor in step S100, the power system power, the power system load value, the device number and the type of the device are uploaded to the cloud platform in real time for analysis in step S300; S300. After the cloud platform receives the data from step S200, it draws a line graph of the current, voltage, and power of each device, and draws a curve graph of the capacitance and resistance change of each component; S400. Monitor the capacitance value of the capacitor and the resistance value of the resistor. Subtract the two uploaded capacitance or resistance values and take the absolute value to calculate the risk factor. When the risk factor of a component is greater than the system's preset safety parameter value, the component is marked as a risk component. Detect the number of times a circuit breaker is opened and closed. When the total number of times a circuit breaker is opened and closed reaches its service life, the circuit breaker is marked as a risk component, and the equipment containing the risk component is marked as a risk device. S500. Read the real-time voltage and current values of the risk device in step S400, calculate the voltage gradient of the device per second based on the maximum current of the device, the load of the power system and the self-inductance of the device; calculate the safe voltage of the risk device based on the number and type of risk elements contained; S600. According to the safety voltage calculated in step S500, when the voltage of the risk device is greater than its safety voltage, the voltage on the risk device is gradually reduced, and the voltage reduction value per second is equal to the voltage gradient value per second calculated in step S500, until the voltage of the risk device is reduced to the safety voltage. A maintenance notice is issued to the maintenance personnel through the cloud platform, and the name and number information of the risk device and risk component are provided. After the maintenance is completed, the device is reconnected and its mark is canceled.

7. The energy data management method based on the Internet of Things platform according to claim 6 is characterized in that: Step S100 includes: Step S101. At predetermined intervals T0, record the total voltage V0 and total current I0 of the power system, the voltage V1 and current I1 of the equipment, the capacitance C of the capacitor, the resistance R of the resistor, and the circuit breaker open / close state S, where S = 1 indicates that the circuit breaker is open, and S = 0 indicates that the circuit breaker is open. Step S102. Calculate the actual power P1 of each device, where P1 = V1 * I1, and calculate the load R0 of the power system, where R0 = V0 / I0; In step S300, a line graph of the current, voltage, and power of each device is drawn with time as the horizontal axis and the current, voltage, and power of each device as the vertical axis. A curve graph of the capacitance change over time is drawn for each capacitor element of each device, and a curve graph of the resistance change over time is drawn for each resistor element of each device.

8. The energy data management method based on the Internet of Things platform according to claim 6 is characterized in that: Step S400 includes: Step S401: Monitor the capacitor element. The capacitance value of a capacitor element measured at time T0 is recorded as C1, and the capacitance value measured at the next time 2T0 is recorded as C2. Calculate the capacitor risk coefficient E1, where E1 = |C1-C2|. When E1>EC0, where EC0 represents the safety parameter of the capacitor element, the capacitor element is marked as a risk element. Step S402 monitors the resistor element. The resistance value of a resistor element measured at time T0 is recorded as R1, and the resistance value measured at the next time 2T0 is recorded as R2. The risk factor E2 is calculated, where E2 = |R1-R2|. When E2>ER0, where ER0 represents the safety parameter of the resistor element, the resistor element is marked as a risk element. Step S403: Count the total number of opening and closing times of the circuit breaker as S1, and the life of the circuit breaker as S0. When S1>S0 of a circuit breaker, mark the circuit breaker as a risk element; Step S404: Mark the device containing risky components as risky device; In step S500, based on the data obtained from the cloud platform, the system obtains the historical maximum current collected from the risk device, records it as Imax, and calculates the voltage gradient △U of the device per second according to the following formula: ； Among them, the equipment current is I1, the total load of the power system is R0, and the self-inductance coefficient of the equipment is L; Calculate the safety voltage U of the risk equipment according to the following formula: U=V1-(a*U1+b*U2+c*U3) Among them, the equipment voltage is V1, the number of risk capacitor elements is a, the number of risk resistor elements is b, the number of risk circuit breaker elements is c, U1 represents the safety voltage of the risk capacitor element, U2 represents the safety voltage of the risk resistor element, and U3 represents the safety voltage of the risk circuit breaker element. U1, U2 and U3 are preset in the system.

9. The energy data management method based on the Internet of Things platform according to claim 6, characterized in that: Step S600 includes: Step S601: gradually reducing the voltage on the risky device, with the voltage reduction value per second being equal to ∆U, until the voltage on the risky device is reduced to a safe voltage; Step S602: Detect the status of risky equipment and issue a reminder when the risky equipment stops working; Step S603: After receiving the reminder, a maintenance notice is issued to the maintenance personnel through the cloud platform. The maintenance notice includes: the device number, device type, component number and component type to be repaired; after the maintenance is completed, the risk device is reconnected and its mark is cancelled.

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