Power supply system for power monitoring based on Internet of Things

Abstract

The invention relates to the technical field of power supply systems for power monitoring, and particularly discloses a power supply system for power monitoring based on the Internet of Things. According to the method, a power generation end operation evaluation coefficient, a power transmission end operation evaluation coefficient, a power distribution end operation evaluation coefficient and a power utilization end operation evaluation coefficient of each power system in a target area serve as discrimination vectors, and whether the power supply stability of the power systems in the target area meets the standard or not is judged through a Rogowski regression model; the operation indexes of the power generation end, the power transmission end, the power distribution end and the power utilization end of the power system are quantified, each link of the power system in a target area can be accurately evaluated, the evaluation of the power supply stability of the power system is more comprehensive and systematic, a scientific and objective decision basis is provided for the operation management of the power system, the power supply stability problem can be found in time, and the power supply efficiency is improved. And corresponding measures are taken to guarantee stable operation of the power system.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply systems for power monitoring, and particularly to a power supply system for power monitoring based on the Internet of Things. Background Technique

[0002] In the current wave of digitalization and intelligentization, electricity, as a key support for economic and social development, the stability and reliability of its supply are of crucial importance. With the intelligent upgrading of industries, the widespread access of new energy, and the increasing dependence of people's lives on electricity, the structure and operating environment of the power system have become increasingly complex, posing higher requirements for power monitoring and management. Although some existing power monitoring systems have introduced Internet of Things technology, there are still many limitations and it is difficult to meet the needs of modern power systems.

[0003] The existing systems are relatively single in the evaluation dimension, mostly focusing on a single link of the power system, such as only emphasizing the monitoring of the power generation end. However, the power system is an organic whole from power generation, transmission, distribution to power consumption. Any problem in any link will affect the power supply stability of the entire system. This lack of a comprehensive evaluation model for the whole link makes it impossible to comprehensively and systematically master the operating state of the power system, and it is difficult to discover potential risks in advance and take effective measures.

[0004] At the same time, there are obvious deficiencies in the decision-making support of the existing systems. The lack of intelligent algorithms for quantitatively evaluating power supply stability makes it difficult to achieve proactive operation and maintenance of the power system. In the face of a complex and changeable power operation environment, it is impossible to make decisions quickly and accurately, and can only passively handle problems after they occur. This not only increases the operation and maintenance costs, but also may lead to power outages, affecting the normal power consumption of users and reducing the reliability of the power system.

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

[0006] The purpose of the present invention is to provide a power supply system for power monitoring based on the Internet of Things to solve the problems raised in the above background.

[0007] The purpose of the present invention can be achieved through the following technical solutions: A power supply system for power monitoring based on the Internet of Things, including:

[0008] A power supply information acquisition module, used to list each power system in the target area and obtain the power generation end, transmission end, distribution end, and power consumption end of each power system through the Internet of Things. Each power system is numbered 1, 2,... i... m, and m is the maximum value of the power system numbers.

[0009] The power generation end monitoring module is used to monitor the operation indicators of the power generation ends of each power system in the target area and analyze the operation evaluation coefficients of the power generation ends of each power system in the target area.

[0010] The power transmission end monitoring module is used to monitor the operation indicators of the power transmission ends of each power system in the target area and analyze the operation evaluation coefficients of the power transmission ends of each power system in the target area.

[0011] The power distribution end monitoring module is used to monitor the operation indicators of the power distribution ends of each power system in the target area and analyze the operation evaluation coefficients of the power distribution ends of each power system in the target area.

[0012] The power consumption end monitoring module is used to monitor the operation indicators of the power consumption ends of each power system in the target area and analyze the operation evaluation coefficients of the power consumption ends of each power system in the target area.

[0013] The power supply determination result feedback terminal is used to construct the power supply stability discrimination vector of the power system in the target area, and then identify whether the power supply stability of the power system in the target area meets the standard.

[0014] Advantages of the present invention:

[0015] By monitoring and analyzing the equipment operation index, power generation capacity margin, and energy supply stability of the power generation ends of each power system in the target area during the current monitoring period, and then evaluating and analyzing the operation evaluation coefficients of the power generation ends of each power system in the target area, the present invention can comprehensively and accurately reflect the health status and operation performance of the corresponding power generation equipment at the power generation end of the power system, facilitating the timely discovery of potential faults, arranging maintenance in advance, reducing unplanned equipment outages, and ensuring the continuity of power generation; clearly understanding the relationship between the power generation capacity and the power consumption load demand, providing a scientific basis for the power generation planning and dispatching of the power system, avoiding overcapacity or insufficient power generation capacity, and improving the utilization efficiency of power resources; being able to intuitively reflect the reliability of the energy supply at the power generation end, helping power enterprises to promptly investigate problems in the energy supply link and improve the stability of the energy supply.

[0016] By monitoring and analyzing the line loss rate and power transmission capacity utilization index of the power transmission ends of each power system in the target area during the current monitoring period, and then evaluating and analyzing the operation evaluation coefficients of the power transmission ends of each power system in the target area, the present invention can accurately master the power loss situation during the power transmission process, help power enterprises identify the lines and time periods with high line losses, and take targeted loss reduction measures to reduce the power transmission cost, evaluate the actual utilization of the power transmission capacity of the power transmission lines, discover problems of power transmission capacity waste or uneven distribution, so as to optimize the operation mode of the power transmission lines, improve the power transmission capacity utilization rate, and ensure the stability and reliability of power transmission.

[0017] The present invention monitors and analyzes the operation condition values and power quality values of distribution transformers in each power system of the target area during the current monitoring period, and then evaluates and analyzes the operation evaluation coefficients at the distribution end of each power system in the target area. It can comprehensively evaluate the operation health status of transformers, timely detect potential problems such as overheating, overload, and insulation damage of transformers, prevent transformer failures in advance, ensure distribution safety, and at the same time intuitively and comprehensively reflect the power quality of distribution lines, which helps to discover the distribution and severity of power quality problems and provides a basis for improving power quality.

[0018] The present invention monitors and analyzes the output fluctuation coefficient, power quality compliance rate, average comprehensive value of grid connection status, and load change coefficient of each power system in the target area during the current monitoring period, and then evaluates and analyzes the operation evaluation coefficients at the power consumption end of each power system in the target area. It can effectively monitor the operation status of distributed power sources after being connected to the power consumption end, evaluate their impact on the stability of the power system, facilitate taking measures to cope with the volatility and uncertainty of distributed power sources, improve the acceptance ability of the power system to distributed power sources, can accurately analyze the variation of different types of loads over time, predict in advance the impact of load fluctuations on the frequency and voltage of the power system, enable the power system to make adjustment preparations in advance, ensure power supply stability, and provide strong support for power enterprises to understand user power consumption behaviors and optimize power consumption management.

[0019] The present invention takes the operation evaluation coefficients at the power generation end, transmission end, distribution end, and power consumption end of each power system in the target area as discriminant vectors, and judges whether the power supply stability of the power system in the target area meets the standards through a logistic regression model. It quantifies the operation indicators at the power generation end, transmission end, distribution end, and power consumption end of the power system, can accurately evaluate each link of the power system in the target area, makes the evaluation of the power supply stability of the power system more comprehensive and systematic, provides a scientific and objective decision-making basis for the operation management of the power system, helps to timely discover power supply stability problems, and takes corresponding measures to ensure the stable operation of the power system. Brief Description of the Drawings

[0020] The following further describes the present invention with reference to the drawings.

[0021] Figure 1 It is a schematic diagram of the connection of system modules of the present invention.

[0022] Figure 2 It is a schematic diagram of the business process flow of the system of the present invention. Detailed Embodiments

[0023] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0024] Please refer to Figure 1 as shown in the figure, the present invention is a power supply system for power monitoring based on the Internet of Things, including: a power supply information acquisition module, a power generation end monitoring module, a power transmission end monitoring module, a power distribution end monitoring module, a power consumption end monitoring module, a power supply determination result feedback terminal, and a database. Among them, the connection method between the modules is as follows:

[0025] The power supply information acquisition module is respectively connected to the power generation end monitoring module, the power transmission end monitoring module, the power distribution end monitoring module, and the power consumption end monitoring module. The power generation end monitoring module, the power transmission end monitoring module, the power distribution end monitoring module, and the power consumption end monitoring module are respectively connected to the power supply determination result feedback module. The database is respectively connected to the power generation end monitoring module and the power consumption end monitoring module.

[0026] It should be noted that the system service flow diagram is as Figure 2 shown.

[0027] The power supply information acquisition module lists each power system in the target area and obtains the power generation end, power transmission end, power distribution end, and power consumption end of each power system through the Internet of Things. The numbers of each power system are 1, 2,... i... m, and m is the maximum value of the power system numbers.

[0028] The power generation end monitoring module monitors the operation indicators of the power generation ends of each power system in the target area (including equipment operation index, power generation capacity margin, and energy supply stability), and analyzes the operation evaluation coefficients of the power generation ends of each power system in the target area.

[0029] Specifically, the execution steps for analyzing the operation evaluation coefficients of the power generation ends of each power system in the target area are as follows:

[0030] 201: Obtain the failure rate, average failure-free operation duration, and performance index deviation degree of each power generation device at the power generation end of each power system in the target area during the current monitoring period. Convert the failure rate, average failure-free operation duration, and performance index deviation degree into lengths according to a preset ratio. Construct an ellipse with the lengths of the failure rate and performance index deviation degree as the major axis and minor axis respectively, and then construct a circle with the length of the average failure-free operation duration as the radius. Coincide the centers of the circle and the ellipse. After identifying the non-coincident area between the ellipse and the circle, perform a reciprocal process, and then statistically obtain the device operation index of each power generation device at the power generation end of each power system in the target area during the current monitoring period. Sum up the device operation indices of each power generation device during the current monitoring period to obtain the device operation index of the power generation end of each power system in the target area during the current monitoring period.

[0031] It should be noted that the statistical process of the performance degradation deviation degree is as follows: Obtain the already-operated duration and total operation life duration of each power generation device at the power generation end of each power system in the target area, perform a ratio calculation to obtain the operation life ratio of each power generation device at the power generation end of each power system in the target area. Match the operation life ratio of each power generation device with the operation life ratio thresholds corresponding to each set operation level to obtain the operation level of each power generation device at the power generation end of each power system in the target area, and then match it with the reference performance index set and the allowable performance index difference set corresponding to each set operation level to obtain the reference performance index set and the allowable performance index difference set The allowable performance index difference set is expressed as the f-th reference performance index of the j-th power generation device at the power generation end of the i-th power system in the target area, denoted as the f-th allowable performance index difference of the j-th power generation device at the power generation end of the i-th power system in the target area. j represents the number of the power generation device, j = 1, 2,...., n, where n is the maximum value of the power generation device numbers, and f represents the number of the performance index item, f = 1, 2,...., g, where g is the maximum value of the performance index item numbers.

[0032] Obtain the performance index set of each power generation device at the power generation end of each power system in the target area during the current monitoring period According to the formula Calculate the performance index deviation degree of each power generation device at the power generation end of each power system in the target area during the current monitoring period.

[0033] It should be noted that the performance indices include but are not limited to power generation efficiency, wear degree, vibration amplitude, noise level, and temperature change rate.

[0034] 202: Obtain the power generation capacity of each power generation device at each power generation end of each power system in the target area at each monitoring time point during the current monitoring period, perform cumulative calculation to obtain the total power generation capacity of each power generation end of each power system in the target area during the current monitoring period, obtain the power consumption load curve of each power consumption end of each power system in the target area during the current monitoring period, and extract the maximum power consumption load therefrom as the maximum load demand of each power consumption end of each power system in the target area during the current monitoring period. Subtract the maximum load demand from the total power generation capacity to obtain the power generation capacity margin of each power generation end of each power system in the target area during the current monitoring period.

[0035] 203: Obtain the number of times of energy supply interruption and the duration of each energy supply interruption of each power generation end of each power system in the target area during the current monitoring period. Sum up the durations of each energy supply interruption to obtain the total duration of energy supply interruption of each power generation end of each power system in the target area during the current monitoring period, which is used as the duration of energy supply interruption of each power generation end of each power system in the target area during the current monitoring period. At the same time, extract the duration of the current monitoring period, and match it with the allowable number of times of energy supply interruption and the allowable duration of energy supply interruption corresponding to each monitoring duration stored in the database to obtain the allowable number of times of energy supply interruption and the allowable duration of energy supply interruption of each power generation end of each power system in the target area during the current monitoring period. Through the energy supply stability calculation formula, obtain the energy supply stability of each power generation end of each power system in the target area during the current monitoring period.

[0036] 204: Extract the equipment operation index, power generation capacity margin and energy supply stability of each power generation end of each power system in the target area during the current monitoring period, convert them into lengths according to a preset ratio, construct an ellipse with the lengths of the equipment operation index and the power generation capacity margin as the major axis and the minor axis respectively, select the center of the ellipse as the starting point, and construct a cone with the length of the energy supply stability as the height. Extract the numerical value of the cone volume as the operation evaluation coefficient of each power generation end of each power system in the target area.

[0037] In a specific embodiment, the present invention monitors and analyzes the equipment operation index, power generation capacity margin and energy supply stability of each power generation end of each power system in the target area during the current monitoring period, and then evaluates and analyzes the operation evaluation coefficient of each power generation end of each power system in the target area. It can comprehensively and accurately reflect the health status and operation performance of the corresponding power generation equipment at the power generation end of the power system, facilitate timely discovery of potential faults, arrange maintenance in advance, reduce unplanned downtime of equipment, and ensure the continuity of power generation; clearly master the relationship between power generation capacity and power consumption load demand, provide a scientific basis for power generation planning and dispatching of the power system, avoid over - surplus or insufficient power generation capacity, and improve the utilization efficiency of power resources; can intuitively reflect the reliability of energy supply at the power generation end, help power enterprises timely detect problems in the energy supply link, and improve the stability of energy supply.

[0038] The power transmission end monitoring module monitors the operation indexes of the power transmission ends of each power system in the target area (including the line loss rate and the power transmission capacity utilization index), and analyzes the operation evaluation coefficient of the power transmission ends of each power system in the target area.

[0039] Specifically, the execution steps for analyzing the operation evaluation coefficient of the power transmission ends of each power system in the target area are as follows:

[0040] 301-1: Obtain the input power and output power of each transmission line at each monitoring time point in the current monitoring period for the power transmission ends of each power system in the target area, perform a subtraction calculation to obtain the power loss of each transmission line at each monitoring time point in the current monitoring period for the power transmission ends of each power system in the target area, and calculate the ratio of the power loss to the input power to obtain the line loss rate of each transmission line at each monitoring time point in the current monitoring period for the power transmission ends of each power system in the target area.

[0041] It should be noted that the input power and output power are collected through an electric energy metering device.

[0042] 301-2: Screen out the maximum line loss rate and the minimum line loss rate from the line loss rates of each transmission line at each monitoring time point in the current monitoring period for the power transmission ends of each power system in the target area, and through Obtain the change range of the line loss rate of each transmission line at each monitoring time point in the current monitoring period for the power transmission ends of each power system in the target area, and perform an accumulation calculation to obtain the total change range of the line loss rate of the power transmission ends of each power system in the target area in the current monitoring period.

[0043] The total change range of the line loss rate of the power transmission ends of each power system in the target area in the current monitoring period is compared with a preset threshold of the total change range of the line loss rate, and through the line loss rate determination formula Obtain each in the target area

[0044] The line loss rate S of the power transmission ends of each power system in the current monitoring period i , where represents the line loss rate of the kth transmission line at the u-th monitoring time point in the current monitoring period for the power transmission end of the i-th power system in the target area, respectively represent the maximum line loss rate and the minimum line loss rate of the kth transmission line at the u-th monitoring time point in the current monitoring period for the power transmission end of the i-th power system in the target area, k represents the number of the transmission line, k = 1, 2,...., l, u represents the number of the monitoring time point, u = 1, 2,...., v, is the maximum value of the transmission line number, and v is the maximum value of the monitoring time point number.

[0045] 302: Obtain the material properties of each transmission line at the power transmission end of each power system in the target area, match them with the maximum transmission capacity corresponding to each set of material properties to obtain the maximum transmission capacity of each transmission line at the power transmission end of each power system in the target area. At the same time, obtain the actual transmission capacity of each transmission line at the power transmission end of each power system in the target area, calculate the difference between the actual transmission capacity and the maximum transmission capacity to obtain the transmission capacity margin of each transmission line at the power transmission end of each power system in the target area.

[0046] It should be noted that the material properties include but are not limited to wire cross-sectional area, line length, transmission voltage level, and line insulation level.

[0047] 303: Arrange detection points for each transmission line at the power transmission end of each power system in the target area to obtain each detection point of each transmission line at the power transmission end of each power system in the target area. Obtain the actual power of each detection point of each transmission line at the power transmission end of each power system in the target area, perform mean calculation to obtain the average power of each transmission line at the power transmission end of each power system in the target area. Through the power flow distribution uniformity calculation formula Obtain the power flow distribution uniformity of each transmission line at the power transmission end of each power system in the target area, where ∏ represents the summation symbol.

[0048] 304: Perform cumulative calculation on the transmission capacity margin and power flow distribution uniformity of each transmission line at the power transmission end of each power system in the target area to obtain the transmission capacity utilization index of the power transmission end of each power system in the target area.

[0049] 305: Extract the line loss rate and transmission capacity utilization index of the power transmission end of each power system in the target area during the current monitoring period, perform length conversion according to a preset ratio. Construct a circle with the length of the transmission capacity utilization as the radius, construct a sector in the circle with the length of the line loss rate as the arc length, and extract the numerical value of the remaining segment area in the circle except the sector as the operation evaluation coefficient of the power transmission end of each power system in the target area.

[0050] In a specific embodiment, the present invention monitors and analyzes the line loss rate and transmission capacity utilization index of the power transmission end of each power system in the target area during the current monitoring period, and then evaluates and analyzes the operation evaluation coefficient of the power transmission end of each power system in the target area, so as to accurately grasp the power loss situation during the power transmission process, help power enterprises find out the lines and time periods with high line losses, take targeted loss reduction measures, reduce the power transmission cost, evaluate the actual power transmission capacity utilization situation of the transmission lines, discover problems of waste or uneven distribution of transmission capacity, and thus optimize the operation mode of the transmission lines, improve the transmission capacity utilization rate, and ensure the stability and reliability of power transmission.

[0051] The power distribution end monitoring module monitors the operation indicators of the power distribution ends of each power system in the target area (including the operation condition values of distribution transformers and power quality values), and analyzes the operation evaluation coefficients of the power distribution ends of each power system in the target area.

[0052] Specifically, the execution steps for analyzing the operation evaluation coefficients of the power distribution ends of each power system in the target area are as follows:

[0053] 401: Obtain the oil temperature, winding temperature, load current, and partial discharge amount of each distribution transformer at each monitoring time point in the current monitoring period for the power distribution ends of each power system in the target area, and compare and analyze them with the preset oil temperature threshold, winding temperature threshold, load current threshold, and partial discharge amount threshold. If the oil temperature of each distribution transformer at each monitoring time point in the current monitoring period for the power distribution ends of each power system in the target area is greater than or equal to the preset oil temperature threshold, assign the oil temperature of each distribution transformer at each monitoring time point in the current monitoring period for the power distribution ends of each power system in the target area as S1, otherwise assign the oil temperature as S2, where S1 < S2. Thus, the total oil temperature assignment of each distribution transformer at the power distribution ends of each power system in the target area in the current monitoring period is statistically obtained.

[0054] 402: Similarly, obtain the total winding temperature assignment, total load current assignment, and total partial discharge amount assignment of each distribution transformer at the power distribution ends of each power system in the current monitoring period, and perform an accumulative calculation on the total oil temperature assignment, total winding temperature assignment, total load current assignment, and total partial discharge amount assignment of each distribution transformer in the current monitoring period to obtain the operation condition value of the distribution transformers at the power distribution ends of each power system in the target area in the current monitoring period.

[0055] 403: Obtain the voltage deviation, frequency deviation, and harmonic distortion rate of each node of the distribution lines at the distribution end of each power system in the target area at each monitoring time point during the current monitoring period, perform cumulative calculations to obtain the total voltage deviation, total frequency deviation, and total harmonic distortion rate of each node of the distribution lines at the distribution end of each power system in the target area during the current monitoring period, construct a three-dimensional power quality evaluation space for the distribution line nodes, with the three dimensions corresponding to the total voltage deviation, total frequency deviation, and total harmonic distortion rate respectively. Map the total voltage deviation, total frequency deviation, and total harmonic distortion rate of each node of the distribution lines at the distribution end of each power system in the target area during the current monitoring period onto the corresponding dimensions of the power quality evaluation space for the distribution line nodes according to a preset ratio. According to the preset allowable total voltage deviation range, allowable total frequency deviation range, and allowable total harmonic distortion rate range, delimit a normal operation area in the three-dimensional power quality evaluation space for the distribution line nodes, and thereby count the number of nodes corresponding to all transmission line nodes at the distribution end of each power system in the target area that fall within the normal operation area, and calculate the ratio of this number to the number of all transmission line nodes at the distribution end of each power system in the target area to obtain the power quality value of each power system distribution end in the target area during the current monitoring period.

[0056] It should be noted that the voltage deviation refers to the percentage of the difference between the actual voltage and the rated voltage to the rated voltage, the frequency deviation refers to the difference between the actual frequency and the rated frequency, and the harmonic distortion rate refers to the percentage of the square root of the sum of the squares of the effective values of each harmonic voltage (or current) to the effective value of the fundamental voltage (or current).

[0057] 404: Perform cumulative calculations on the operation condition values and power quality values of the distribution transformers at the distribution end of each power system in the target area during the current monitoring period to obtain the operation evaluation coefficients of the distribution ends of each power system in the target area.

[0058] In a specific embodiment, the present invention monitors and analyzes the operation condition values and power quality values of the distribution transformers of each power system in the target area during the current monitoring period, and then evaluates and analyzes the operation evaluation coefficients of the distribution ends of each power system in the target area, which can comprehensively evaluate the operation health status of the transformers, timely discover potential problems such as overheating, overload, and insulation damage of the transformers, prevent transformer failures in advance, ensure distribution safety, and at the same time intuitively and comprehensively reflect the power quality situation of the distribution lines, which helps to discover the distribution and severity of power quality problems and provides a basis for improving power quality.

[0059] The power consumption end monitoring module monitors the operation indicators of the power consumption ends of each power system in the target area (including the output fluctuation coefficient, power quality compliance rate, average comprehensive value of the grid connection status, and load change coefficient), and analyzes the operation evaluation coefficients of the power consumption ends of each power system in the target area.

[0060] Specifically, the execution steps of the operation evaluation coefficients of each power system's power consumption end in the analysis target area are as follows:

[0061] 501: Obtain the actual output of each distributed power source connected to the power consumption end of each power system in the target area at each monitoring time point during the current monitoring period, calculate the mean value, obtain the average output of each distributed power source connected to the power consumption end of each power system in the target area during the current monitoring period, and then calculate the standard deviation to obtain the output fluctuation coefficient of each distributed power source connected to the power consumption end of each power system in the target area during the current monitoring period.

[0062] It should be noted that the output of distributed power sources is affected by natural conditions and has volatility. The greater the output fluctuation range, the greater the impact on the power balance and voltage stability of the power system, reducing the power supply stability.

[0063] 502: Obtain each power quality index of the output end of each distributed power source connected to the power consumption end of each power system in the target area at each monitoring time point during the current monitoring period, and compare it with the standard range of each power quality index stored in the database. If all power quality indexes at a certain monitoring time point are within the standard range, it is determined that the power quality at this monitoring time point meets the standard; otherwise, it is determined that the power quality at this monitoring time point does not meet the standard. Thus, count the number of monitoring time points with qualified power quality at the output end of each distributed power source connected to the power consumption end of each power system in the target area during the current monitoring period, and calculate the ratio with the number of all monitoring time points during the current monitoring period to obtain the power quality compliance rate of the output end of each distributed power source connected to the power consumption end of each power system in the target area during the current monitoring period.

[0064] It should be noted that each power quality index includes but is not limited to voltage, current, and frequency, which are collected by a power quality monitoring device; a high power quality compliance rate of the distributed power source output means that indicators such as voltage deviation, frequency deviation, and harmonic content generated by it meet the requirements. For example, a low harmonic content can reduce pollution to the power grid, reduce equipment losses and failure risks, and ensure the stable operation of the power system. The higher the compliance rate, the greater the positive effect on power supply stability.

[0065] 503: Obtain the grid connection status determination value, communication status determination value, and control strategy execution status determination value of each distributed power source connected to the power consumption end of each power system in the target area at each monitoring time point during the current monitoring period, and perform cumulative calculation on the grid connection status determination value, communication status determination value, and control strategy execution status determination value to obtain the grid connection status comprehensive value of each distributed power source connected to the power consumption end of each power system in the target area at each monitoring time point during the current monitoring period, and then calculate the mean value to obtain the average grid connection status comprehensive value of each distributed power source connected to the power consumption end of each power system in the target area during the current monitoring period.

[0066] It should be noted that the process of obtaining the grid connection status determination value, communication status determination value, and control strategy execution status determination value is as follows: If the grid connection status is normal connection, the grid connection status determination value is assigned 1; if the grid connection status is abnormal connection, the grid connection status determination value is assigned 0; if the communication status is normal communication, the communication status determination value is assigned 1; if the communication status is abnormal communication, the communication status determination value is assigned 0; if the control strategy execution status is executed in place, the control strategy execution status determination value is assigned 1; if the control strategy execution status is not executed in place, the control strategy execution status determination value is assigned 0.

[0067] 504: Obtain the change rates of various types of loads at the power consumption ends of each power system in the target area during the current monitoring period, calculate the ratios of them to the set reference change rates of various types respectively, and then accumulate the results to obtain the load change coefficient of the power consumption ends of each power system in the target area during the current monitoring period.

[0068] It should be noted that various types of loads include industrial loads, commercial loads, and residential loads. The load change rate reflects the speed of load change over time. The larger the load change rate, the greater the fluctuations in the frequency and voltage of the power system, affecting power supply stability. For example, the start or stop of large equipment during industrial production will cause an instantaneous change in the load. If the change rate exceeds the system's adjustment ability, it may trigger power supply instability problems.

[0069] 505: Extract the output fluctuation coefficient, power quality compliance rate, average integrated grid connection status value, and load change coefficient of the power consumption ends of each power system in the target area during the current monitoring period. Convert the power quality compliance rate and the average integrated grid connection status value into lengths according to a preset ratio. Convert the value obtained by adding the output fluctuation coefficient and the load change coefficient and then taking the reciprocal into a length according to a preset ratio. Construct a frustum of a cone with the length of the power quality compliance rate as the bottom radius, the length of the average integrated grid connection status value as the upper radius, and the length obtained by processing the output fluctuation coefficient and the load change coefficient as the height, and extract the numerical value of the volume of the frustum of the cone as the evaluation coefficient of the power consumption ends of each power system in the target area.

[0070] In a specific embodiment, the present invention monitors and analyzes the output fluctuation coefficient, power quality compliance rate, average comprehensive value of grid connection status, and load change coefficient of each power system in the target area during the current monitoring period, and then evaluates and analyzes the operation evaluation coefficient of the power consumption end of each power system in the target area, which can effectively monitor the operation status of the distributed power source after accessing the power consumption end, evaluate its impact on the stability of the power system, facilitate taking measures to cope with the volatility and uncertainty of the distributed power source, improve the acceptance capacity of the power system for the distributed power source, accurately analyze the variation of different types of loads over time, predict in advance the impact of load fluctuations on the frequency and voltage of the power system, enable the power system to make adjustment preparations in advance, ensure power supply stability, and provide strong support for power enterprises to understand user power consumption behaviors and optimize power consumption management.

[0071] The power supply determination result feedback terminal is used to construct a discrimination vector for the power supply stability of the power system in the target area, and then identify whether the power supply stability of the power system in the target area meets the standard.

[0072] Specifically, the construction of the discrimination vector for the power supply stability of the power system in the target area includes: listing the operation evaluation coefficient ω of the power generation end of each power system in the target area i , the operation evaluation coefficient ξ of the power transmission end i , the operation evaluation coefficient ψ of the power distribution end i and the operation evaluation coefficient ζ of the power consumption end i , and constructing a discrimination vector x i =(ω i ,ξ i ,ψ i ,ζ i ) of the power system in the target area.

[0073] Specifically, the identification of whether the power supply stability of the power system in the target area meets the standard includes: using the Logistic regression model to determine whether the power supply stability of the power system in the target area meets the standard. In the formula, the dependent variable y represents whether the power supply stability of the target area meets the standard, which is a binary variable. y = 1 indicates qualified, and y = 0 indicates unqualified. P(y = 1|x i ) is the probability that the dependent variable y takes the value of 1 under the discrimination vector x i , is the set fitting model parameter β u and the dot product of the discrimination vector x i , is the set fitting model parameter, i represents the number of the fitting model parameter, and i = 0, 1, 2, 3, 4.

[0074] Specifically,

[0075] If P(y = 1|x i ) ≥ 0.5, it is determined that the power supply stability of the power system in the target area meets the standard.

[0076] If P(y = 1|x i ) < 0.5, it is determined that the power supply stability of the power system in the target area does not meet the standard.

[0077] In a specific embodiment, the present invention uses the operation evaluation coefficients of the power generation end, transmission end, distribution end, and power consumption end of each power system in the target area as discriminant vectors, and determines whether the power supply stability of the power system in the target area meets the standard through a logistic regression model, quantifying the operation indicators of the power generation end, transmission end, distribution end, and power consumption end of the power system, and can accurately evaluate each link of the power system in the target area, making the evaluation of the power supply stability of the power system more comprehensive and systematic, providing a scientific and objective decision-making basis for the operation management of the power system, and helping to timely discover power supply stability problems and take corresponding measures to ensure the stable operation of the power system.

[0078] The above content is only an example and explanation of the structure of the present invention. Those skilled in the art of this technology make various modifications or supplements to the described specific embodiments or use similar methods to replace them. As long as they do not deviate from the structure of the invention or exceed the scope defined by this claims, they should fall within the protection scope of the present invention.

Claims

1. A power supply system for power monitoring based on the Internet of Things, characterized in that, Including: A power supply information acquisition module, which is used to list each power system in the target area and obtain the power generation end, transmission end, distribution end, and power consumption end of each power system; A power generation end monitoring module, which is used to monitor the operation indicators of the power generation ends of each power system in the target area and analyze the operation evaluation coefficients of the power generation ends of each power system in the target area; A transmission end monitoring module, which is used to monitor the operation indicators of the transmission ends of each power system in the target area and analyze the operation evaluation coefficients of the transmission ends of each power system in the target area; A distribution end monitoring module, which is used to monitor the operation indicators of the distribution ends of each power system in the target area and analyze the operation evaluation coefficients of the distribution ends of each power system in the target area; A power consumption end monitoring module, which is used to monitor the operation indicators of the power consumption ends of each power system in the target area and analyze the operation evaluation coefficients of the power consumption ends of each power system in the target area; A power supply determination result feedback terminal, which is used to construct a power supply stability discrimination vector for the power system in the target area, and then identify whether the power supply stability of the power system in the target area meets the standard.

2. The power supply system for power monitoring based on the Internet of Things according to claim 1, wherein The operation indicators of the power generation end include the equipment operation index, power generation capacity margin, and energy supply stability; the operation indicators of the transmission end include the line loss rate and the transmission capacity utilization index; the operation indicators of the distribution end include the operation condition value of the distribution transformer and the power quality value; The operation indicators of the power consumption end include the output fluctuation coefficient, the power quality compliance rate, the average comprehensive value of the grid connection status, and the load change coefficient.

3. The power supply system for power monitoring based on the Internet of Things according to claim 1, wherein The execution process of analyzing the operation evaluation coefficients of the power generation ends of each power system in the target area is as follows: Convert the failure rate, the average trouble-free operation duration, and the performance index deviation degree into lengths according to a preset ratio and analyze to obtain the equipment operation index of the power generation ends of each power system in the target area during the current monitoring period; Obtain the power generation capacity of each power generation device at each monitoring time point during the current monitoring period for each power generation end of each power system in the target area, perform cumulative calculation to obtain the total power generation capacity of the power generation ends of each power system in the target area during the current monitoring period, obtain the power consumption load curve of the power consumption ends of each power system in the target area during the current monitoring period, and extract the maximum power consumption load therefrom as the maximum load demand of the power consumption ends of each power system in the target area during the current monitoring period. Subtract the total power generation capacity from the maximum load demand to obtain the power generation capacity margin of the power generation ends of each power system in the target area during the current monitoring period; Obtain the number of energy supply interruptions and the duration of each energy supply interruption of the power generation ends of each power system in the target area during the current monitoring period, sum up the duration of each energy supply interruption to obtain the total energy supply interruption duration of the power generation ends of each power system in the target area during the current monitoring period, which is used as the energy supply interruption duration of the power generation ends of each power system in the target area during the current monitoring period. At the same time, extract the duration of the current monitoring period, and match it with the allowed number of energy supply interruptions and the allowed energy supply interruption duration corresponding to each monitoring duration stored in the database to obtain the allowed number of energy supply interruptions and the allowed energy supply interruption duration of the power generation ends of each power system in the target area during the current monitoring period. Calculate the energy supply stability of the power generation ends of each power system in the target area during the current monitoring period through the energy supply stability calculation formula; Extract the equipment operation index, power generation capacity margin, and energy supply stability of each power system in the target area during the current monitoring period, and analyze to obtain the operation evaluation coefficient of the power generation end of each power system in the target area.

4. The power supply system for power monitoring based on the Internet of Things according to claim 1, characterized in that, The execution process of analyzing the operation evaluation coefficient of the transmission end of each power system in the target area is as follows: Obtain the input power and output power of each transmission line at each monitoring time point during the current monitoring period for the transmission end of each power system in the target area, and perform a subtraction calculation to obtain the power loss of each transmission line at each monitoring time point during the current monitoring period for the transmission end of each power system in the target area. Calculate the ratio of the power loss to the input power to obtain the line loss rate of each transmission line at each monitoring time point during the current monitoring period for the transmission end of each power system in the target area; Screen out the maximum line loss rate and the minimum line loss rate from the line loss rates of each transmission line at each monitoring time point during the current monitoring period for the transmission end of each power system in the target area. Obtain the line loss rate change range of each transmission line at each monitoring time point during the current monitoring period for the transmission end of each power system in the target area through the line loss rate change range calculation formula, and perform an accumulation calculation to obtain the total line loss rate change range of the transmission end of each power system in the target area during the current monitoring period; Compare the total line loss rate change range of the transmission end of each power system in the target area during the current monitoring period with the preset total line loss rate change range threshold, and obtain the line loss rate of the transmission end of each power system in the target area during the current monitoring period through the line loss rate determination formula; Obtain the material properties of each transmission line at the transmission end of each power system in the target area, and match them with the maximum transmission capacity corresponding to each set of material properties to obtain the maximum transmission capacity of each transmission line at the transmission end of each power system in the target area. At the same time, obtain the actual transmission capacity of each transmission line at the transmission end of each power system in the target area, and perform a subtraction calculation of the actual transmission capacity from the maximum transmission capacity to obtain the transmission capacity margin of each transmission line at the transmission end of each power system in the target area; Arrange detection points for each transmission line at the transmission end of each power system in the target area to obtain each detection point of each transmission line at the transmission end of each power system in the target area. Obtain the actual power of each detection point of each transmission line at the transmission end of each power system in the target area, and perform an average calculation to obtain the average power of each transmission line at the transmission end of each power system in the target area. Obtain the power flow distribution uniformity of each transmission line at the transmission end of each power system in the target area through the power flow distribution uniformity calculation formula; Perform an accumulation calculation on the transmission capacity margin and the power flow distribution uniformity of each transmission line at the transmission end of each power system in the target area to obtain the transmission capacity utilization index of the transmission end of each power system in the target area; Extract the line loss rate and the transmission capacity utilization index of the transmission end of each power system in the target area during the current monitoring period, perform a length conversion according to the preset ratio, construct a circle with the length of the transmission capacity utilization as the radius, construct a sector in the circle with the length of the line loss rate as the arc length, and extract the numerical value of the remaining segment area in the circle except the sector as the operation evaluation coefficient of the transmission end of each power system in the target area.

5. The power supply system for power monitoring based on the Internet of Things according to claim 1, characterized in that, The execution process of analyzing the operation evaluation coefficient of the distribution end of each power system in the target area is as follows: Obtain the oil temperature, winding temperature, load current, and partial discharge amount of each distribution transformer at each distribution end of each power system in the target area at each monitoring time point during the current monitoring period, and compare and analyze them with the preset oil temperature threshold, winding temperature threshold, load current threshold, and partial discharge amount threshold. If the oil temperature of each distribution transformer at each distribution end of each power system in the target area at each monitoring time point during the current monitoring period is greater than or equal to the preset oil temperature threshold, assign the oil temperature of each distribution transformer at each distribution end of each power system in the target area at each monitoring time point during the current monitoring period to S1, otherwise assign the oil temperature to S2. Thus, the total oil temperature assignment of each distribution transformer at each distribution end of each power system in the target area during the current monitoring period is statistically obtained; Similarly, obtain the total winding temperature assignment, total load current assignment, and total partial discharge amount assignment of each distribution transformer at each distribution end of each power system in the target area during the current monitoring period, and perform cumulative calculation on the total oil temperature assignment, total winding temperature assignment, total load current assignment, and total partial discharge amount assignment of each distribution transformer during the current monitoring period to obtain the operation condition value of the distribution transformer at each distribution end of each power system in the target area during the current monitoring period; Obtain the voltage deviation, frequency deviation, and harmonic distortion rate of each node of the distribution line at each distribution end of each power system in the target area at each monitoring time point during the current monitoring period, and perform cumulative calculation to obtain the total voltage deviation, total frequency deviation, and total harmonic distortion rate of each node of the distribution line at each distribution end of each power system in the target area during the current monitoring period. Construct a three-dimensional power quality evaluation space for distribution line nodes, where the three dimensions correspond to the total voltage deviation, total frequency deviation, and total harmonic distortion rate respectively. Map the total voltage deviation, total frequency deviation, and total harmonic distortion rate of each node of the distribution line at each distribution end of each power system in the target area during the current monitoring period to the corresponding dimensions of the power quality evaluation space for distribution line nodes according to the preset ratio. According to the preset allowable total voltage deviation range, allowable total frequency deviation range, and allowable total harmonic distortion rate range, delimit a normal operation area in the three-dimensional power quality evaluation space for distribution line nodes, and thus statistically obtain the number of nodes corresponding to all transmission line nodes at each distribution end of each power system in the target area that fall within the normal operation area. Calculate the ratio of it to the number of all transmission line nodes at each distribution end of each power system in the target area to obtain the power quality value of each distribution end of each power system in the target area during the current monitoring period; Perform cumulative calculation on the operation condition value of the distribution transformer and the power quality value at each distribution end of each power system in the target area during the current monitoring period to obtain the operation evaluation coefficient of each distribution end of each power system in the target area.

6. The power supply system for power monitoring based on the Internet of Things according to claim 1, characterized in that, The execution process of analyzing the operation evaluation coefficient of each power consumption end of each power system in the target area is as follows: Obtain the actual output of the distributed power sources connected to the power consumption ends of each power system in the target area at each monitoring time point during the current monitoring period, calculate the mean value, obtain the average output of the distributed power sources connected to the power consumption ends of each power system in the target area during the current monitoring period, and then calculate the standard deviation to obtain the output fluctuation coefficient of the distributed power sources connected to the power consumption ends of each power system in the target area during the current monitoring period; Obtain each power quality index of the output ends of the distributed power sources connected to the power consumption ends of each power system in the target area at each monitoring time point during the current monitoring period, and compare it with the standard range of each power quality index stored in the database. If all power quality indexes at a certain monitoring time point are within the standard range, it is determined that the power quality at this monitoring time point meets the standard; otherwise, it is determined that the power quality at this monitoring time point does not meet the standard. Thus, count the number of monitoring time points with qualified power quality at the output ends of the distributed power sources connected to the power consumption ends of each power system in the target area during the current monitoring period, and calculate the ratio with the number of all monitoring time points during the current monitoring period to obtain the power quality compliance rate of the output ends of the distributed power sources connected to the power consumption ends of each power system in the target area during the current monitoring period; Obtain the grid connection status determination value, communication status determination value, and control strategy execution status determination value of the distributed power sources connected to the power consumption ends of each power system in the target area at each monitoring time point during the current monitoring period, and perform cumulative calculation on the grid connection status determination value, communication status determination value, and control strategy execution status determination value to obtain the grid connection status comprehensive value of the distributed power sources connected to the power consumption ends of each power system in the target area at each monitoring time point during the current monitoring period, and then calculate the mean value to obtain the average comprehensive grid connection status value of the distributed power sources connected to the power consumption ends of each power system in the target area during the current monitoring period; Obtain the change rates of various types of loads at the power consumption ends of each power system in the target area during the current monitoring period, and perform a cumulative process after calculating the ratio of each change rate of various types of loads to the set reference change rates of various types of loads to obtain the load change coefficient of the power consumption ends of each power system in the target area during the current monitoring period; Extract the output fluctuation coefficient, power quality compliance rate, average comprehensive grid connection status value, and load change coefficient of the power consumption ends of each power system in the target area during the current monitoring period. Convert the power quality compliance rate and average comprehensive grid connection status value into lengths according to a preset ratio. Convert the value obtained by taking the reciprocal of the sum of the output fluctuation coefficient and load change coefficient into a length according to a preset ratio. Construct a frustum of a cone with the length of the power quality compliance rate as the lower base radius, the length of the average comprehensive grid connection status value as the upper base radius, and the length obtained by processing the output fluctuation coefficient and load change coefficient as the height, and extract the numerical value of the volume of the frustum of the cone as the evaluation coefficient of the power consumption ends of each power system in the target area.

7. The power supply system for power monitoring based on the Internet of Things according to claim 1, characterized in that, The discriminant vector for the power supply stability of the constructed target area includes: listing the operation evaluation coefficients ω of each power generation end of the power systems in the target area i , the operation evaluation coefficient ξ of the transmission end i , the operation evaluation coefficient ψ of the distribution end i , and the operation evaluation coefficient ζ of the power consumption end i , and constructing the discriminant vector x of the power system in the target area i = (ω i , ξ i , ψ i , ζ i ).

8. The power supply system for power monitoring based on the Internet of Things according to claim 1, characterized in that, Determine whether the power supply stability of the identified target area meets the standard, including: through the Logistic regression model Determine whether the power supply stability of the power system in the target area meets the standard. In the formula, the dependent variable y represents whether the power supply stability in the target area is qualified, which is a binary variable. y = 1 indicates qualified, and y = 0 indicates unqualified. P(y = 1|x i ) is the probability that the dependent variable y takes the value of 1 under the discriminant vector x i , is the set fitting model parameter β u and the dot product of the discriminant vector x i , is the set fitting model parameter. i represents the number of the fitting model parameter, and i = 0, 1, 2, 3, 4; If P(y = 1|x i ) ≥ 0.5, it is determined that the power supply stability of the target area meets the standard; If P(y = 1|x i ) < 0.5, it is determined that the power supply stability of the target area does not meet the standard.

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