Power supply system for power monitoring based on internet of things

Abstract

The application relates to the technical field of power supply systems for power monitoring, in particular to a power supply system for power monitoring based on the Internet of Things. The application takes the power generation end operation evaluation coefficient, the power transmission end operation evaluation coefficient, the power distribution end operation evaluation coefficient and the power consumption end operation evaluation coefficient of each power system in a target area as a discriminant vector, judges whether the power supply stability of the target area meets the standard through a logistic regression model, quantifies the operation indexes of the power generation end, the power transmission end, the power distribution end and the 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 basis for the operation management of the power system, helps to find the power supply stability problems in time, takes corresponding measures to guarantee the stable operation of the power system.

Description

Technical Field

[0001] This invention relates to the field of power supply system technology for power monitoring, specifically to a power supply system for power monitoring based on the Internet of Things. Background Technology

[0002] In today's era of digitalization and intelligentization, electricity, as a key pillar of economic and social development, is of paramount importance in terms of the stability and reliability of its supply. With the intelligent upgrading of industry, the widespread integration of new energy sources, and the deepening dependence of people's lives on electricity, the structure and operating environment of the power system are becoming increasingly complex, placing higher demands on power monitoring and management. Although existing power monitoring systems have partially incorporated Internet of Things (IoT) technology, they still have many limitations and are insufficient to meet the needs of modern power systems.

[0003] Existing systems tend to have a limited range of assessment dimensions, often focusing on a single aspect of the power system, such as monitoring only the generation end. However, the power system is an organic whole encompassing generation, transmission, distribution, and consumption; a problem in any link can impact the overall stability of the power supply. This lack of a comprehensive assessment model across all aspects makes it impossible to fully and systematically grasp the operational status of the power system, hindering the early detection of potential risks and the implementation of effective countermeasures.

[0004] Meanwhile, existing systems have significant shortcomings in decision support. They lack intelligent algorithms for quantitatively assessing power supply stability, making proactive operation and maintenance of the power system difficult. Faced with complex and ever-changing power operating environments, they cannot make quick and accurate decisions, and can only react passively after problems occur. This not only increases operation and maintenance costs but may also lead to power outages, affecting users' normal electricity consumption and reducing the reliability of the power system.

[0005] To address the aforementioned shortcomings, a technical solution is provided. Summary of the Invention

[0006] The purpose of this invention is to provide a power supply system for power monitoring based on the Internet of Things (IoT) to solve the problems mentioned in the background.

[0007] The objective of this invention can be achieved through the following technical solution: a power supply system for power monitoring based on the Internet of Things, comprising:

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

[0009] The generator monitoring module is used to monitor the operating indicators of the generator terminals of various power systems in the target area and analyze the operating evaluation coefficients of the generator terminals of various power systems in the target area.

[0010] The transmission end monitoring module 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.

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

[0012] The power consumption monitoring module is used to monitor the operating indicators of power consumption terminals of various power systems in the target area and analyze the operating evaluation coefficients of power consumption terminals of various power systems in the target area.

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

[0014] The beneficial effects of this invention are:

[0015] This invention monitors and analyzes the equipment operation index, power generation capacity margin, and energy supply stability of each power system generator terminal in the target area during the current monitoring period. It then evaluates and analyzes the operation assessment coefficients of each power system generator terminal in the target area. This comprehensively and accurately reflects the health status and operational performance of the corresponding power generation equipment at the power system generator terminals, facilitating timely detection of potential faults, advance maintenance arrangements, reduction of unplanned equipment downtime, and ensuring continuous power generation. It also clearly understands the relationship between power generation capacity and electricity load demand, providing a scientific basis for power system power generation planning and dispatch, avoiding overcapacity or undercapacity, and improving the utilization efficiency of power resources. Furthermore, it directly reflects the reliability of energy supply at the generator terminals, helping power companies to promptly identify problems in the energy supply chain and improve the stability of energy supply.

[0016] This invention monitors and analyzes the line loss rate and transmission capacity utilization rate index of each power system transmission terminal in the target area during the current monitoring period. It then evaluates and analyzes the operation assessment coefficients of each power system transmission terminal in the target area. This allows for precise understanding of energy loss during transmission, helping power companies identify lines and time periods with high line losses, implement targeted loss reduction measures, lower transmission costs, assess the actual transmission capacity utilization of transmission lines, identify problems of wasted or unevenly distributed transmission capacity, thereby optimizing the operation mode of transmission lines, improving transmission capacity utilization, and ensuring the stability and reliability of power transmission.

[0017] This invention monitors and analyzes the operating status and power quality values ​​of distribution transformers in various power systems within a target area during the current monitoring period. It then evaluates and analyzes the operating assessment coefficients of the distribution terminals of each power system in the target area. This comprehensive assessment of transformer operating health allows for the timely detection of potential problems such as transformer overheating, overload, and insulation damage, enabling early prevention of transformer failures and ensuring power distribution safety. Simultaneously, it provides a direct and comprehensive view of the power quality of distribution lines, helping to identify the distribution and severity of power quality problems and providing a basis for improving power quality.

[0018] This 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. It then evaluates and analyzes the operational assessment coefficients of each power system's consumer end in the target area. This effectively monitors the operational status of distributed power sources after they are connected to the consumer end, assesses their impact on power system stability, facilitates measures to address the volatility and uncertainty of distributed power sources, improves the power system's capacity to accommodate distributed power sources, accurately analyzes the changes in different types of loads over time, and predicts in advance the impact of load fluctuations on power system frequency and voltage. This allows the power system to prepare for adjustments in advance, ensures power supply stability, and provides strong support for power companies to understand user electricity consumption behavior and optimize electricity management.

[0019] This invention uses the operational evaluation coefficients of the power generation, transmission, distribution, and consumption ends of the power system in the target area as discriminant vectors. It employs a Rogersstick regression model to determine whether the power supply stability of the power system in the target area meets the standards. By quantifying the operational indicators of the power system's generation, transmission, distribution, and consumption ends, it can accurately assess each link of the power system in the target area. This makes the assessment of power supply stability more comprehensive and systematic, providing a scientific and objective basis for power system operation and management. It also helps to promptly identify power supply stability problems and take corresponding measures to ensure the stable operation of the power system. Attached Figure Description

[0020] The invention will now be further described with reference to the accompanying drawings.

[0021] Figure 1 This is a schematic diagram of the system module connections of the present invention.

[0022] Figure 2 This is a schematic diagram of the system business flow of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Please see Figure 1 As shown, this invention is a power supply system for power monitoring based on the Internet of Things (IoT), comprising: a power supply information acquisition module, a generator end monitoring module, a transmission end monitoring module, a distribution end monitoring module, a power consumption end monitoring module, a power supply judgment result feedback terminal, and a database. The modules are connected as follows:

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

[0026] It should be noted that the system business flow diagram is as follows: Figure 2 As shown.

[0027] The power supply information acquisition module lists all power systems in the target area and acquires the generation end, transmission end, distribution end, and consumption end of each power system through the Internet of Things. Each power system is numbered 1, 2, ... i ... m, where m is the maximum value of the power system number.

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

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

[0030] 201: Obtain the failure rate, mean time between failures (MTBF), and performance deviation 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, MTBF, and performance deviation into lengths according to a preset ratio. Construct ellipses with the lengths of the failure rate and performance deviation as the major and minor axes, respectively. Construct circles with the length of the MTBF as the radius. Align the centers of the circles with the centers of the ellipses. Identify the areas where the ellipses and circles do not coincide and perform a reciprocal process. Then, statistically obtain the equipment 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 the equipment operation indices of each power generation device during the current monitoring period to obtain the equipment operation index of each power generation end of the power system in the target area during the current monitoring period.

[0031] It should be noted that the statistical process for performance degradation deviation is as follows: The running time and total operating life of each power generation device at the generator end of each power system in the target area are obtained, and the ratio is calculated to obtain the operating life ratio of each power generation device at the generator end of each power system in the target area. The operating life ratio of each power generation device is then matched with the set operating life ratio thresholds corresponding to each operating level to obtain the operating level of each power generation device at the generator end of each power system in the target area. Finally, this level is matched with the set of reference performance indicators and the set of allowable performance indicator differences corresponding to each operating level to obtain the set of reference performance indicators for each power generation device at the generator end of each power system in the target area. and the set of allowable performance index differences The allowable performance index difference set is represented by the f-th reference performance index of the j-th generating equipment at the i-th power system generator terminal in the target area. Let f represent the allowable performance index difference of the j-th generating equipment at the i-th power system generator terminal in the target area, where j represents the generator number (j = 1, 2, ..., n), and n is the maximum value of the generator number. Let f represent the performance index item number (f = 1, 2, ..., g), and g is the maximum value of the performance index item number.

[0032] Obtain the set of performance indicators for 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 deviation of performance indicators 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 performance indicators include, but are not limited to, power generation efficiency, wear and tear, vibration amplitude, noise level, and temperature change rate.

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

[0035] 203: Obtain the number of energy supply interruptions and the duration of each interruption at the power generation terminals of each power system in the target area during the current monitoring period. Sum the durations of each interruption to obtain the total duration of energy supply interruptions at the power generation terminals of each power system in the target area during the current monitoring period. This total duration is used as the total energy supply interruption duration for the power generation terminals of each power system in the target area during the current monitoring period. Simultaneously, extract the duration of the current monitoring period and match it with the allowed number of energy supply interruptions and allowed duration of energy supply interruptions corresponding to each monitoring duration stored in the database. This yields the allowed number of energy supply interruptions and allowed duration of energy supply interruptions for the power generation terminals of each power system in the target area during the current monitoring period. This is then used to assess energy supply stability. The calculation formula yields the energy supply stability of each power system generator in the target area during the current monitoring period.

[0036] 204: Extract the equipment operation index, generation capacity margin, and energy supply stability of each power system generator terminal in the target area during the current monitoring period. Convert them into lengths according to a preset ratio. Construct ellipses with the lengths of the equipment operation index and generation capacity margin as the major and minor axes, respectively. Select the center of the ellipse as the starting point and the length of energy supply stability as the height to construct a cone. Extract the volume of the cone as the operation evaluation coefficient of each power system generator terminal in the target area.

[0037] In one specific embodiment, this invention monitors and analyzes the equipment operation index, power generation capacity margin, and energy supply stability of each power system generator terminal in the target area during the current monitoring period. This allows for the evaluation and analysis of the operation assessment coefficients of each power system generator terminal in the target area. This comprehensively and accurately reflects the health status and operational performance of the corresponding power generation equipment at each generator terminal, facilitating timely detection of potential faults, advance maintenance arrangements, reduction of unplanned equipment downtime, and ensuring continuous power generation. It also clearly understands the relationship between power generation capacity and electricity load demand, providing a scientific basis for power system power generation planning and dispatch, avoiding overcapacity or undercapacity, and improving the utilization efficiency of power resources. Furthermore, it directly reflects the reliability of energy supply at the generator terminals, helping power companies to promptly identify problems in the energy supply chain and improve the stability of energy supply.

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

[0039] Specifically, the execution steps for the operation evaluation coefficients of each power system transmission end in the target analysis area are as follows:

[0040] 301-1: Obtain the input and output electrical energy of each transmission line at each monitoring time point of each power system transmission terminal in the target area during the current monitoring period, and perform difference calculation to obtain the power loss of each transmission line at each monitoring time point of each power system transmission terminal in the target area during the current monitoring period. Calculate the ratio of power loss to input electrical energy to obtain the line loss rate of each transmission line at each monitoring time point of each power system transmission terminal in the target area during the current monitoring period.

[0041] It should be noted that the input and output electrical energy are collected by an energy metering device.

[0042] 301-2: From the line loss rates of each transmission line at each monitoring time point in the current monitoring period of each power system transmission terminal in the target area, the maximum and minimum line loss rates are selected, and then... The changes in line loss rate of each transmission line at each power system transmission terminal in the target area during the current monitoring period are obtained and accumulated to obtain the changes in line loss rate of each power system transmission terminal in the target area during the current monitoring period.

[0043] 301-3: Compare the changes in line loss rate at each power system transmission terminal in the target area during the current monitoring period with the preset threshold for changes in line loss rate, and determine the line loss rate using the formula. Obtain the target area

[0044] Line loss rate S at the transmission end of the power system during the current monitoring period i In the formula This represents the line loss rate of the k-th transmission line at the i-th power system transmission terminal in the target area at the u-th monitoring time point during the current monitoring period. These represent the maximum and minimum line loss rates of the k-th transmission line at the i-th power system transmission terminal in the target area during the current monitoring period, respectively. k represents the transmission line number, k = 1, 2, ..., l, u represents the monitoring time point number, u = 1, 2, ..., v, where u 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 transmission end of each power system in the target area, and match them with the maximum transmission capacity corresponding to each set material property 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 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 transmission end of each power system in the target area.

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

[0047] 303: Detection points are set up for each transmission line at each power system transmission end in the target area to obtain the actual power at each detection point of each transmission line at each power system transmission end in the target area. The average power is then calculated using the power flow distribution uniformity calculation formula. The uniformity of power flow distribution of each transmission line at each power system transmission terminal in the target area is obtained, where ∏ represents the summation symbol.

[0048] 304: The transmission capacity margin and power flow distribution uniformity of each transmission line at each power system transmission end in the target area are accumulated and calculated to obtain the transmission capacity utilization index of each power system transmission end in the target area.

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

[0050] In one specific embodiment, the present invention monitors and analyzes the line loss rate and transmission capacity utilization rate index of each power system transmission terminal in the target area during the current monitoring period, and then evaluates and analyzes the operation evaluation coefficient of each power system transmission terminal in the target area. This allows for accurate understanding of the power loss during the transmission process, helping power companies identify lines and time periods with high line losses, take targeted loss reduction measures, reduce transmission costs, evaluate the actual transmission capacity utilization of transmission lines, identify problems of wasted or unevenly distributed transmission capacity, thereby optimizing the operation mode of transmission lines, improving transmission capacity utilization, and ensuring the stability and reliability of power transmission.

[0051] The distribution terminal monitoring module monitors the operation indicators of the distribution terminals of each power system in the target area (including the operation status value of the distribution transformer and the power quality value), and analyzes the operation evaluation coefficient of the distribution terminals of each power system in the target area.

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

[0053] 401: Obtain the oil temperature, winding temperature, load current, and partial discharge of each distribution transformer at each monitoring time point in the current monitoring period of each power system distribution terminal in the target area, and compare them with the preset oil temperature threshold, winding temperature threshold, load current threshold, and partial discharge threshold. If the oil temperature of each distribution transformer at each monitoring time point in the current monitoring period of each power system distribution terminal in the target area is greater than or equal to the preset oil temperature threshold, then the oil temperature of each distribution transformer at each monitoring time point in the current monitoring period of each power system distribution terminal in the target area is assigned the value S1, otherwise the oil temperature is assigned the value S2, where S1 < S2. Thus, the total assigned oil temperature value of each distribution transformer at each power system distribution terminal in the target area during the current monitoring period is obtained.

[0054] 402: Similarly, the total winding temperature, total load current, and total partial discharge value of each distribution transformer at each power system distribution terminal in the target area during the current monitoring period are obtained. The total oil temperature, total winding temperature, total load current, and total partial discharge value of each distribution transformer during the current monitoring period are then summed to obtain the operating condition value of the distribution transformer at each power system distribution terminal in the target area during the current monitoring period.

[0055] 403: Obtain the voltage deviation, frequency deviation, and harmonic distortion rate of each node of the distribution lines at each distribution end of the power system in the target area at each monitoring time point during the current monitoring period. Accumulate these values ​​to obtain the total voltage deviation, total frequency deviation, and total harmonic distortion rate of each node of the distribution lines at each distribution end of the power system in the target area during the current monitoring period. Construct a three-dimensional power quality assessment space for the distribution line nodes. The three dimensions correspond to the total voltage deviation, total frequency deviation, and total harmonic distortion rate, respectively. The variability is mapped to the corresponding dimensions of the power quality assessment space of the distribution line node according to a preset ratio. Based on the preset allowable total voltage deviation range, allowable total frequency deviation range, and allowable total harmonic distortion rate range, a normal operation area is defined in the three-dimensional power quality assessment space of the distribution line node. The number of nodes corresponding to all transmission line nodes of the power system distribution end in the target area that fall within the normal operation area is counted. The ratio of this number to the number of all transmission line nodes of the power system distribution end in the target area is calculated to obtain the power quality value of the power system distribution end in the target area during the current monitoring period.

[0056] It should be noted that voltage deviation refers to the percentage of the difference between the actual voltage and the rated voltage relative to the rated voltage; frequency deviation refers to the difference between the actual frequency and the rated frequency; and 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: The operating condition value and power quality value of the distribution transformers of each power system distribution terminal in the target area during the current monitoring period are accumulated and calculated to obtain the operating evaluation coefficient of each power system distribution terminal in the target area.

[0058] In one specific embodiment, the present invention monitors and analyzes the operating status 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 operating evaluation coefficients of the distribution terminals of each power system in the target area. This allows for a comprehensive assessment of the operating health of the transformers, timely detection of potential problems such as transformer overheating, overload, and insulation damage, early prevention of transformer failures, and ensuring power distribution safety. At the same time, it provides a direct and comprehensive reflection of the power quality of the distribution lines, helping to identify the distribution and severity of power quality problems and providing a basis for improving power quality.

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

[0060] Specifically, the execution steps for calculating the operational evaluation coefficients of each power system consumer in the target analysis area are as follows:

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

[0062] It should be noted that distributed power sources are affected by natural conditions, and their output fluctuates. The greater the fluctuation in output, the greater the impact on the power balance and voltage stability of the power system, thus reducing the stability of power supply.

[0063] 502: Obtain the power quality indicators of the distributed power generation output terminals of each power system in the target area at each monitoring time point during the current monitoring period, and compare them with the standard range of each power quality indicator stored in the database. If all power quality indicators at a certain monitoring time point are within the standard range, the power quality at that monitoring time point is determined to be compliant; otherwise, the power quality at that monitoring time point is determined to be non-compliant. Count the number of compliant monitoring time points of the distributed power generation output terminals of each power system in the target area during the current monitoring period, and calculate the ratio of this number to the total number of monitoring time points during the current monitoring period to obtain the power quality compliance rate of the distributed power generation output terminals of each power system in the target area during the current monitoring period.

[0064] It should be noted that various power quality indicators include, but are not limited to, voltage, current, and frequency, which are collected by power quality monitoring devices. A high compliance rate of power quality output from distributed power sources means that indicators such as voltage deviation, frequency deviation, and harmonic content meet the requirements. For example, 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 judgment value, communication status judgment value, and control strategy execution status judgment value of each distributed power source at the power consumption end of the target area at each monitoring time point during the current monitoring period. Then, accumulate the grid connection status judgment value, communication status judgment value, and control strategy execution status judgment value to obtain the comprehensive grid connection status value of each distributed power source at the power consumption end of the target area at each monitoring time point during the current monitoring period. Finally, calculate the average value to obtain the average comprehensive grid connection status value of each distributed power source at the power consumption end of the target area during the current monitoring period.

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

[0067] 504: Obtain the load change rate of each type of load at each power system terminal in the target area during the current monitoring period, and calculate the ratio of each load change rate to the set reference load change rate for each type, and then sum them up to obtain the load change coefficient of each power system terminal in the target area during the current monitoring period.

[0068] It should be noted that the various types of loads include industrial loads, commercial loads, and residential loads. The load change rate reflects how quickly the load changes over time. The greater the load change rate, the larger the fluctuations in the frequency and voltage of the power system, affecting the stability of power supply. For example, the start-up or shutdown of large equipment in industrial production processes can cause instantaneous load changes. If the rate of change exceeds the system's regulation capacity, it may lead to power supply instability.

[0069] 505: Extract the output fluctuation coefficient, power quality compliance rate, average comprehensive value of grid connection status, and load change coefficient of each power system consumer in the target area during the current monitoring period. Convert the power quality compliance rate and average comprehensive value of grid connection status into length according to a preset ratio. Convert the sum of the output fluctuation coefficient and load change coefficient into length according to a preset ratio. Construct a truncated cone with the length of the power quality compliance rate as the lower radius, the length of the average comprehensive value of grid connection status as the upper radius, and the converted length of the output fluctuation coefficient and load change coefficient as the height. Extract the volume of the truncated cone as the evaluation coefficient of each power system consumer in the target area.

[0070] In one 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. This allows for the evaluation and analysis of the operational assessment coefficients of each power system's consumer end in the target area. It effectively monitors the operational status of distributed power sources after they are connected to the consumer end, assesses their impact on power system stability, facilitates measures to address the volatility and uncertainty of distributed power sources, improves the power system's capacity to accommodate distributed power sources, accurately analyzes the changes in different types of loads over time, and predicts in advance the impact of load fluctuations on power system frequency and voltage. This enables the power system to prepare for adjustments in advance, ensures power supply stability, and provides strong support for power companies to understand user electricity consumption behavior and optimize electricity management.

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

[0072] Specifically, the constructed power system supply stability discrimination vector for the target area includes: listing the operation evaluation coefficients ω of the power generation terminals of each power system in the target area. i Transmission end operation evaluation coefficient ξ i ψ, the operation evaluation coefficient of the power distribution end i and the power consumption end operation evaluation coefficient ζ i Construct the power system discrimination vector x for the target region i =(ω i ,ξ i ,ψ i ,ζ i ).

[0073] Specifically, the identification of whether the power supply stability of the target area's power system meets the standards includes: using the Rogersstick regression model. To determine whether the power supply stability of the target area meets the standard, the dependent variable y represents whether the power supply stability of the target area meets the standard. It is a binary variable, where y = 1 indicates compliance and y = 0 indicates non-compliance. P(y = 1 | x i ) is the discriminant vector x i The probability that the dependent variable y takes the value 1. It is the set fitting model parameter β u and discriminant vector x i dot product, These are the parameters of the fitting model, where i represents the parameter number of the fitting model, i = 0, 1, 2, 3, 4.

[0074] Specifically,

[0075] If P(y=1|x i If the value is greater than or equal to 0.5, then the power supply stability of the target area's power system is deemed to meet the standard.

[0076] If P(y=1|x i If the value is less than 0.5, then the power supply stability of the target area's power system does not meet the standard.

[0077] In one specific embodiment, the present invention uses the operational evaluation coefficients of the power generation end, transmission end, distribution end, and consumption end of each power system in the target area as discriminant vectors. It then uses a Rogersstick regression model to determine whether the power supply stability of the power system in the target area meets the standards. By quantifying the operational indicators of the power system's generation, transmission, distribution, and consumption ends, the present invention can accurately evaluate each link of the power system in the target area. This makes the evaluation of power supply stability more comprehensive and systematic, providing a scientific and objective basis for power system operation and management. It also helps to promptly identify power supply stability problems and take corresponding measures to ensure the stable operation of the power system.

[0078] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, 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 in the claims, all of which should fall within the protection scope of the present invention.

Claims

1. A power supply system for power monitoring based on Internet of Things, characterized by, The utility model relates to an electric power supply stability evaluation method and system, and relates to the technical field of electric power supply stability evaluation. The utility model discloses a kind of electric power supply stability evaluation method and system, and relates to the technical field of electric power supply stability evaluation. Including: Power supply information acquisition module, for listing each power system of target area, and the power generation end, power transmission end, power distribution end and power consumption end of each power system are obtained; Power generation end monitoring module, for monitoring the power generation end operation index of each power system of target area, analyzes the power generation end operation evaluation coefficient of each power system of target area; Extract the equipment operation index, power generation capacity margin and energy supply stability of each power system power generation end in target area in current monitoring period, according to the length conversion of preset proportion, respectively with the length of equipment operation index and power generation capacity margin as long axis and short axis to build ellipse, select the center of ellipse as starting point, the length of energy supply stability as high to build cone, extract the numerical value of cone volume as the power generation end operation evaluation coefficient of each power system of target area; Power transmission end monitoring module, for monitoring the power transmission end operation index of each power system of target area, analyzes the power transmission end operation evaluation coefficient of each power system of target area; Extract the line loss rate and power transmission capacity utilization index of each power system power transmission end in target area in current monitoring period, length conversion is carried out according to preset proportion, power transmission capacity utilization length is taken as radius to build circle, line loss rate length is taken as arc length to build sector in circle, extract the numerical value of remaining arc area in circle except sector as the power transmission end operation evaluation coefficient of each power system of target area; Power distribution end monitoring module, for monitoring the power distribution end operation index of each power system of target area, analyzes the power distribution end operation evaluation coefficient of each power system of target area; The power distribution transformer operation health value and power quality value of each power system power distribution end in target area in current monitoring period are accumulated and calculated, and the power distribution end operation evaluation coefficient of each power system of target area is obtained; Power consumption end monitoring module, for monitoring the power consumption end operation index of each power system of target area, analyzes the power consumption end operation evaluation coefficient of each power system of target area; Extract the output fluctuation coefficient, power quality compliance rate, grid-connected state average comprehensive value and load change coefficient of each power system power consumption end in target area in current monitoring period, the power quality compliance rate and grid-connected state average comprehensive value are converted into length according to preset proportion, the value obtained by inverting the sum of output fluctuation coefficient and load change coefficient after processing is converted into length according to preset proportion, respectively with the length of power quality compliance rate as lower base radius, with the length of grid-connected state average comprehensive value as upper base radius, with the length converted after processing of output fluctuation coefficient and load change coefficient as high to build circular truncated cone, extract the numerical value of circular truncated cone volume as the power consumption end evaluation coefficient of each power system of target area; Power supply determination result feedback terminal, for building the power system power supply stability discrimination vector of target area, and then identify whether the power system power supply stability of target area meets the standard; List the power generation end operation evaluation coefficient, power transmission end operation evaluation coefficient, power distribution end operation evaluation coefficient and power consumption end operation evaluation coefficient of each power system of target area, and build the power system discrimination vector of target area; Whether the power system power supply stability of target area meets the standard is discriminated through Logistic regression model.

2. The power supply system for power monitoring based on Internet of Things according to claim 1, wherein The power generation end operation index includes a device operation index, a power generation capacity margin and energy supply stability; the power transmission end operation index includes a line loss rate and a power transmission capacity utilization index; and the power distribution end operation index includes a power distribution transformer operation condition value and an electric energy quality value. The power consumption end operation index includes an output fluctuation coefficient, an electric energy quality compliance rate, an average comprehensive value of grid-connected state and a load change coefficient. 3.The power supply system for power monitoring based on Internet of Things according to claim 1, wherein, The execution process of analyzing the power generation end operation evaluation coefficient of each power system in the target area is as follows: The failure rate, the average failure-free operation duration and the performance index deviation degree are converted into lengths according to a preset proportion, and the device operation index of each power system in the target area at the current monitoring period is obtained by analysis; The power generation capacity of each power generation device of each power system in the target area at each monitoring time point in the current monitoring period is obtained, accumulated and calculated, the total power generation capacity of each power system in the target area at the current monitoring period is obtained, the maximum power consumption load of each power consumption end in the target area at the current monitoring period is extracted from the power consumption load curve of each power consumption end in the target area at the current monitoring period, the total power generation capacity is subtracted from the maximum load demand, and the power generation capacity margin of each power system in the target area at the current monitoring period is obtained; The number of energy supply interruptions and the length of each energy supply interruption of each power system in the target area at the current monitoring period are obtained, the length of each energy supply interruption is summed, the total energy supply interruption length of each power system in the target area at the current monitoring period is obtained, and the energy supply interruption length of each power system in the target area at the current monitoring period is obtained as the energy supply interruption length of each power system in the target area at the current monitoring period; the length of the current monitoring period is extracted and matched with the allowed energy supply interruption number and the allowed energy supply interruption length corresponding to each monitoring length stored in the database, the allowed energy supply interruption number and the allowed energy supply interruption length of each power system in the target area at the current monitoring period are obtained, and the energy supply stability of each power system in the target area at the current monitoring period is obtained through the energy supply stability calculation formula. The device operation index, the power generation capacity margin and the energy supply stability of each power system in the target area at the current monitoring period are extracted and analyzed to obtain the power generation end operation evaluation coefficient of each power system in the target area. 4.The power supply system for power monitoring based on Internet of Things according to claim 1, wherein, The execution process of analyzing the power transmission end operation evaluation coefficient of each power system in the target area is as follows: The input end electric energy and the output end electric energy of each power transmission line of each power system in the target area at each monitoring time point in the current monitoring period are obtained, and the difference is calculated to obtain the electric energy loss of each power transmission line of each power system in the target area at each monitoring time point in the current monitoring period; the line loss rate of each power transmission line of each power system in the target area at each monitoring time point in the current monitoring period is obtained by ratio calculation of the electric energy loss and the input end electric energy. The maximum line loss rate and the minimum line loss rate are selected from the line loss rates of each power transmission line at each monitoring time point in the current monitoring period of each power system power transmission end in the target area, the line loss rate variation amplitude of each power transmission line at the current monitoring period of each power system power transmission end in the target area is obtained through a line loss rate variation amplitude calculation formula, and accumulated calculation is performed to obtain the total line loss rate variation amplitude of each power system power transmission end in the target area at the current monitoring period; The total line loss rate variation amplitude of each power system power transmission end in the target area at the current monitoring period is compared with a preset total line loss rate variation amplitude threshold, and the line loss rate of each power system power transmission end in the target area at the current monitoring period is obtained through a line loss rate determination formula; The material performance of each power transmission line of each power system power transmission end in the target area is obtained, and is matched with the maximum power transmission capacity corresponding to each material performance to obtain the maximum power transmission capacity of each power transmission line of each power system power transmission end in the target area. The actual power transmission capacity of each power transmission line of each power system power transmission end in the target area is obtained, and the actual power transmission capacity is subtracted from the maximum power transmission capacity to obtain the power transmission capacity margin of each power transmission line of each power system power transmission end in the target area; The detection points of each power transmission line of each power system power transmission end in the target area are obtained through detection point arrangement, the actual power of each detection point of each power transmission line of each power system power transmission end in the target area is obtained, mean value calculation is performed to obtain the average power of each power transmission line of each power system power transmission end in the target area, and the power flow distribution uniformity of each power transmission line of each power system power transmission end in the target area is obtained through a power flow distribution uniformity calculation formula; The power transmission capacity margin and the power flow distribution uniformity of each power transmission line of each power system power transmission end in the target area are accumulated to obtain the power transmission capacity utilization rate index of each power system power transmission end in the target area; The line loss rate and the power transmission capacity utilization rate index of each power system power transmission end in the target area at the current monitoring period are extracted, length conversion is performed according to a preset proportion, a circle is constructed with the length of the power transmission capacity utilization rate as the radius, a sector is constructed in the circle with the length of the line loss rate as the arc length, and the numerical value of the remaining arc area in the circle except the sector is extracted as the operation evaluation coefficient of each power system power transmission end in the target area. 5.The power supply system for power monitoring based on Internet of Things according to claim 1, wherein, The execution process of analyzing the operation evaluation coefficient of each power distribution transformer of each power system power distribution end in the target area is as follows: The oil temperature, winding temperature, load current and partial discharge quantity of each power distribution transformer of each power system power distribution end in the target area at each monitoring time point in the current monitoring period are obtained, and are compared and analyzed with the preset oil temperature threshold value, winding temperature threshold value, load current threshold value and partial discharge quantity threshold value. If the oil temperature of each power distribution transformer of each power system power distribution end in the target area at each monitoring time point in the current monitoring period is greater than or equal to the preset oil temperature threshold value, the oil temperature of each power distribution transformer of each power system power distribution end in the target area at each monitoring time point in the current monitoring period is assigned as S1, otherwise the oil temperature is assigned as S2. The total oil temperature assignment value of each power distribution transformer of each power system power distribution end in the target area at the current monitoring period is obtained by statistics. Similarly, the total assigned winding temperature, total assigned load current and total assigned partial discharge of each distribution transformer at the power distribution end of each power system in the target region in the current monitoring period are obtained, and the total assigned oil temperature, total assigned winding temperature, total assigned load current and total assigned partial discharge of each distribution transformer in the current monitoring period are accumulated to obtain the operation condition value of the distribution transformer at the power distribution end of each power system in the target region in the current monitoring period; The voltage deviation, frequency deviation and harmonic distortion rate of each node of the power distribution line at the power distribution end of each power system in the target region at each monitoring time point in the current monitoring period are obtained, and accumulated to obtain the total voltage deviation, total frequency deviation and total harmonic distortion rate of each node of the power distribution line at the power distribution end of each power system in the target region in the current monitoring period, and a three-dimensional power distribution line node power quality evaluation space is constructed, and the three-dimensional dimensions correspond to the total voltage deviation, total frequency deviation and total harmonic distortion rate, respectively. The total voltage deviation, total frequency deviation and total harmonic distortion rate of each node of the power distribution line at the power distribution end of each power system in the target region in the current monitoring period are mapped to each dimension of the power distribution line node power quality evaluation space according to a preset proportion, a normal operation region is determined in the three-dimensional power distribution line node power quality evaluation space according to the pre-set allowed total voltage deviation interval, allowed total frequency deviation interval and allowed total harmonic distortion rate interval, and the number of nodes corresponding to all power transmission line nodes in the target region that fall within the normal operation region is counted, and the number of nodes is compared with the number of all power transmission line nodes in the target region to obtain the power quality value of each power system at the power distribution end of the target region in the current monitoring period. The operation condition value and the power quality value of the distribution transformer at the power distribution end of each power system in the target region in the current monitoring period are accumulated to obtain the operation evaluation coefficient of each power system at the power distribution end of the target region. 6.The power supply system for power monitoring based on Internet of Things according to claim 1, wherein, The execution process of analyzing the operation evaluation coefficient of each power system at the power consumption end of the target region is as follows: The actual output of the distributed power supply access at the power consumption end of each power system in the target region at each monitoring time point in the current monitoring period is obtained, and the average output of the distributed power supply access at the power consumption end of each power system in the target region in the current monitoring period is calculated, and the output fluctuation coefficient of the distributed power supply access at the power consumption end of each power system in the target region in the current monitoring period is calculated. The power quality indexes of the distributed power output end of each power system user end in the target area at each monitoring time point in the current monitoring period are obtained, and compared with the standard range of each power quality index stored in the database. If all the power quality indexes of a monitoring time point are within the standard range, it is determined that the power quality of the monitoring time point meets the standard, otherwise it is determined that the power quality of the monitoring time point does not meet the standard. The number of monitoring time points that meet the standard in the current monitoring period is counted, and the ratio of the number of monitoring time points that meet the standard to the total number of monitoring time points in the current monitoring period is calculated to obtain the power quality compliance rate of the distributed power output end of each power system user end in the target area in the current monitoring period. The grid-connected state judgment value, communication state judgment value and control strategy execution condition judgment value of the distributed power of each power system user end in the target area at each monitoring time point in the current monitoring period are obtained, and the grid-connected state judgment value, communication state judgment value and control strategy execution condition judgment value are added to obtain the grid-connected state comprehensive value of the distributed power of each power system user end in the target area at each monitoring time point in the current monitoring period, and then the average value is calculated to obtain the average grid-connected state comprehensive value of the distributed power of each power system user end in the target area in the current monitoring period. The load change rate of each type of power system user end in the target area in the current monitoring period is obtained, and the load change rate of each type is calculated by the ratio of the set reference load change rate of each type, and then the load change coefficient of the power system user end in the target area in the current monitoring period is obtained by adding the load change rate of each type. The output fluctuation coefficient, power quality compliance rate, average grid-connected state comprehensive value and load change coefficient of each power system user end in the target area in the current monitoring period are extracted, the power quality compliance rate and the average grid-connected state comprehensive value are converted into length according to the preset proportion, the output fluctuation coefficient and the load change coefficient are added and then the inverse value is obtained, and the length converted according to the preset proportion is taken as the height of the frustum of a cone with the length of the power quality compliance rate as the lower radius and the length of the average grid-connected state comprehensive value as the upper radius. The numerical value of the volume of the frustum is taken as the evaluation coefficient of each power system user end in the target area. 7.The power supply system for power monitoring based on Internet of Things according to claim 1, wherein, by logistic regression model whether the power system supply stability of the target region meets the standard, wherein the dependent variable represents whether the power supply stability of the target region is qualified, which is a binary variable, =1 represents qualified, =0 represents unqualified, is a discriminant vector the probability of the dependent variable taking the value 1, is a set fitting model parameter and the dot product of the discriminant vector , and is a set fitting model parameter, i represents the number of the fitting model parameter, i=0,1,2,3,4; If , it is determined that the power system supply stability of the target region meets the standard; If then the power system supply stability of the target region is determined to be non-compliant.

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