Intelligent monitoring method and system for line loss of power distribution network

Abstract

The invention discloses a power distribution network line loss intelligent monitoring method and system, and belongs to the technical field of power distribution network monitoring, and the method comprises the steps: obtaining the line segment length, reference resistance, head end active power, load point active power and feed line segment temperature of a feed line in a power distribution network; according to the line segment length and the reference resistance of the feeder line in the power distribution network, establishing a theoretical analysis model, and generating line segment theoretical line loss of the feeder line in the power distribution network; establishing a theoretical correction model according to the line segment theoretical line loss of the feeder line in the power distribution network and the feeder line segment temperature, and generating power distribution network feeder line theoretical correction line loss; generating actual line loss of the power distribution network according to the head end active power and the load point active power; generating a line loss abnormal coefficient according to the actual line loss of the power distribution network and the theoretical correction line loss of the feeder line of the power distribution network, and monitoring the line loss of the power distribution network; the method solves the problems that a traditional method is insufficient in precision and cannot achieve dynamic correction, and has the advantages that the line loss calculation precision is improved, dynamic temperature correction is achieved, and line loss abnormity is recognized in time.

Description

Technical Field

[0001] This invention belongs to the field of power distribution network monitoring technology, and in particular relates to an intelligent monitoring method and system for power distribution network line losses. Background Technology

[0002] As a crucial component of the power system, the distribution network's line loss level directly impacts the grid's operational economy and power supply quality. Distribution network line losses mainly include technical line losses and management line losses, with technical line losses influenced by various factors such as line parameters, load distribution, and ambient temperature.

[0003] Traditional line loss monitoring methods typically employ statistical methods based on historical data or simplified theoretical calculation models, which have significant limitations. On the one hand, existing technologies often use fixed-coefficient methods to estimate theoretical line losses or perform line loss analysis based on typical daily load curves, failing to fully consider the segmented characteristics of the distribution network and actual operating conditions. On the other hand, existing systems often neglect the impact of temperature changes on line resistance when calculating theoretical line losses, or only use simple ambient temperature correction methods, leading to significant deviations between the calculated results and actual line losses. These problems severely restrict the accuracy of distribution network line loss management. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an intelligent monitoring method and system for distribution network line losses, solving the aforementioned problems.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an intelligent monitoring method for line losses in a distribution network, specifically comprising the following steps:

[0006] Obtain the line segment length, reference resistance, active power at the beginning, active power at the load point, and feeder line segment temperature of the feeder in the distribution network; where the reference resistance refers to the resistance value per unit feeder at standard temperature;

[0007] Based on the line segment length and reference resistance of the feeder in the distribution network, a theoretical analysis model is established to generate the theoretical line loss of the feeder segment in the distribution network.

[0008] A theoretical correction model is established based on the theoretical line loss and temperature of feeder segments in the distribution network to generate the theoretical correction line loss of the distribution network feeder.

[0009] The actual line loss of the distribution network is generated based on the active power at the head end and the active power at the load point.

[0010] Line loss is corrected based on the actual line loss of the distribution network and the theoretical distribution network feeder, and a line loss anomaly coefficient is generated.

[0011] The line loss of the distribution network is monitored based on the line loss anomaly coefficient.

[0012] Based on the above technical solutions, the present invention also provides the following optional technical solutions:

[0013] Further technical solutions: The specific methods for generating the theoretical line loss of the distribution network include:

[0014] Based on the line segment length and reference resistance of the feeder in the distribution network, generate the total reference resistance of the feeder line segment in the distribution network.

[0015] A theoretical analysis model is established based on the total reference resistance loss of the feeder segment to generate the theoretical line loss of the feeder segment in the distribution network.

[0016] Further technical solutions: The specific methods for generating the theoretical line loss of the feeder segment include:

[0017] Through the formula: ;

[0018] Generate total reference resistance for line segments ;

[0019] In the formula, This represents the reference resistance of line segment i in the feeder. This represents the length of line segment i in the feeder.

[0020] Further technical solution: The expression of the theoretical analysis model is specifically as follows: ;

[0021] In the expression, This represents the theoretical line loss of feeder segment i in the distribution network. This represents the current flowing through segment i in the feeder. This represents the total reference resistance of segment i in the feeder.

[0022] Further technical solutions: The specific methods for generating the theoretically corrected line loss of the distribution network include:

[0023] A temperature correction factor is generated based on the temperature of the feeder segment.

[0024] A theoretical correction model is established based on the temperature correction factor and the theoretical line loss of feeder segments in the distribution network, and the theoretical correction line loss of the distribution network feeder is generated.

[0025] Further technical solution: The method for generating the feeder resistance correction value specifically includes:

[0026] Through the formula: ;

[0027] Generating temperature correction factor ;

[0028] In the formula, This represents the temperature coefficient of resistance of line segment i in the distribution network feeder. This represents the temperature of feeder segment i in the distribution network feeder. This indicates the standard temperature in the reference resistor. This represents the reference resistance of line segment i in the feeder.

[0029] Further technical solution: The expression of the theoretical correction model is specifically as follows: ;

[0030] In the expression, This refers to the theoretical correction for line loss in the distribution network feeder. This represents the theoretical line loss of feeder segment i. This represents the temperature correction factor. This represents the total number of line segments in the feeder. This represents the total loss of the distribution transformer.

[0031] Further technical solutions: The specific methods for generating the actual line loss of the distribution network include:

[0032] Through the formula: ;

[0033] Generate actual line losses in the distribution network ;

[0034] In the formula, This represents the active power at the beginning of the distribution network. This represents the active power at load point j, and M represents the total number of load points.

[0035] Further technical solution: The method for generating the line loss anomaly coefficient specifically includes:

[0036] Through the formula: ;

[0037] Generate the line loss anomaly coefficient K;

[0038] In the formula, This represents the actual line loss of the distribution network. This refers to the theoretical correction of line loss in the distribution network feeder.

[0039] A distribution network line loss intelligent monitoring system, the system being used to execute the above-mentioned distribution network line loss intelligent monitoring method, specifically including:

[0040] The data acquisition unit is used to obtain the line segment length, reference resistance, active power at the head end, active power at the load point, and feeder line segment temperature of the feeder in the distribution network; wherein, the reference resistance refers to the resistance value per unit feeder at standard temperature.

[0041] The line segment theoretical line loss analysis unit is used to establish a theoretical analysis model based on the line segment length and reference resistance of the feeder in the distribution network, and generate the theoretical line loss of the feeder in the distribution network.

[0042] The theoretical correction unit is used to establish a theoretical correction model based on the theoretical line loss and temperature of feeder segments in the distribution network, and generate the theoretical correction line loss of the distribution network feeder.

[0043] The actual line loss analysis unit is used to generate the actual line loss of the distribution network based on the active power at the head end and the active power at the load point.

[0044] The line loss anomaly analysis unit is used to correct line loss based on the actual line loss of the distribution network and the theoretical distribution network feeder, and to generate the line loss anomaly coefficient.

[0045] The monitoring unit is used to monitor the line loss of the distribution network based on the line loss anomaly coefficient.

[0046] This invention provides an intelligent monitoring method and system for distribution network line losses, which has the following advantages compared with the prior art:

[0047] This invention solves the problems of insufficient accuracy and inability to dynamically correct for the effects of temperature by calculating theoretical line loss in segments and comparing the difference between actual and theoretical line loss. It has the advantages of improving the accuracy of line loss calculation, realizing dynamic temperature correction, and timely identification of line loss anomalies. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating an intelligent monitoring method for power distribution network line losses provided by the present invention.

[0049] Figure 2 This is a flowchart illustrating step S20 of the present invention.

[0050] Figure 3 This is a flowchart illustrating step S30 of the present invention.

[0051] Figure 4 This is a flowchart illustrating step S60 of the present invention.

[0052] Figure 5 This is a schematic diagram of the structure of an intelligent monitoring system for power distribution network line losses provided by the present invention.

[0053] Figure 6 This is a schematic diagram of the line loss analysis unit for line segment theory provided by the present invention.

[0054] Figure 7 A schematic diagram of the structure of the theoretical correction unit provided by the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0056] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0057] Please see Figure 1 and Figure 4 The present invention provides an intelligent monitoring method for line losses in a power distribution network, comprising the following steps:

[0058] Step S10: Obtain the line segment length, reference resistance, active power at the beginning, active power at the load point, and feeder line segment temperature of the feeder in the distribution network;

[0059] Step S20: Based on the line segment length and reference resistance of the feeder in the distribution network, establish a theoretical analysis model and generate the theoretical line loss of the feeder in the distribution network.

[0060] Step S30: Establish a theoretical correction model based on the theoretical line loss of feeder segments and the temperature of feeder segments in the distribution network, and generate the theoretical correction line loss of the distribution network feeder;

[0061] Step S40: Generate the actual line loss of the distribution network based on the active power at the head end and the active power at the load point;

[0062] Step S50: Correct the line loss based on the actual line loss of the distribution network and the theoretical line loss of the distribution network feeders, and generate the line loss anomaly coefficient;

[0063] Step S60: Monitor the distribution network line loss according to the line loss anomaly coefficient; specifically, this includes: comparing the line loss anomaly coefficient with a preset benchmark value; if the line loss anomaly coefficient is greater than the preset benchmark value, it indicates that the distribution network line loss is abnormal; if the line loss anomaly coefficient is less than or equal to the preset benchmark value, it indicates that the distribution network line loss is in a normal state.

[0064] Among them, the line segment length refers to the actual extension distance of the conductor between two adjacent nodes in the distribution network topology. Specifically, it can be obtained by measuring through a geographic information system or parsing topology data, and is used to calculate the total resistance value of each line segment.

[0065] The reference resistance refers to the resistance value per unit length of wire at standard temperature. Specifically, it can be determined by combining the standard resistivity parameter of the conductor material with the temperature coefficient, and serves as the basic parameter for calculating theoretical line loss.

[0066] Feeder segment temperature refers to the real-time temperature of the conductor during operation, which can be collected by an infrared temperature measuring device or a distributed temperature sensor to dynamically correct the resistance value.

[0067] The active power at the beginning of the distribution network feeder refers to the input power at the beginning of the feeder, which can be monitored in real time through smart meters or power acquisition devices.

[0068] The active power at the load point refers to the power consumed at each power consumption node. It can be obtained through a metering device installed on the load side and is used to calculate the actual line loss difference.

[0069] The line loss anomaly coefficient is the ratio of actual line loss to corrected theoretical line loss. It is generated through numerical calculation and is used to quantitatively assess the degree to which line loss deviates from the normal range.

[0070] Specifically, each feeder in the distribution network is divided into multiple independent segments, and the length and reference resistance of each segment are obtained separately. The total reference resistance value of each segment is calculated by multiplying the segment length by the reference resistance. Based on the product of the square of the current and the resistance, a power loss model for each segment is established to generate theoretical line loss. Subsequently, based on real-time collected segment temperature data, a temperature correction factor is calculated to dynamically adjust the theoretical line loss, eliminating resistance deviations caused by temperature changes. Actual line loss is calculated as the difference between the input power at the head end and the sum of the power at each load point. An anomaly coefficient is generated by comparing the actual line loss with the corrected theoretical line loss in real time. When the anomaly coefficient exceeds a preset threshold, a monitoring mechanism is triggered to locate the abnormal segment. For example, if a segment experiences an increase in theoretically corrected line loss due to increased resistance in a high-temperature environment, and the actual line loss increases synchronously but does not exceed the theoretical range, it is considered normal loss; if the actual line loss is significantly higher than the corrected theoretical value, it is identified as abnormal and an investigation is initiated.

[0071] Compared to existing technologies, traditional methods use the equivalent resistance method to treat the entire feeder as a single resistor, failing to reflect the loss differences between different segments. This solution, however, significantly improves the accuracy of theoretical line loss calculation by segmenting the model and independently calculating the resistance and current of each segment. Existing technologies often use ambient temperature to approximate conductor temperature for temperature correction, leading to correction errors. This solution directly measures conductor temperature and establishes a correction factor to achieve dynamic calibration of resistance values. Furthermore, existing systems lack a dynamic comparison mechanism between theoretical and actual line loss, while this solution uses anomaly coefficients to assess line loss status in real time, shifting from passive statistics to active monitoring.

[0072] Through the above technical solution, this application achieves segmented and refined calculation of distribution network line losses, solving the estimation deviation problem caused by neglecting the segmented characteristics of the line in traditional methods. By introducing a dynamic temperature correction model, the impact of temperature changes on line loss calculation is effectively eliminated, improving the accuracy of theoretical line losses. Based on a dynamic comparison mechanism of anomaly coefficients, abnormal line losses can be identified in a timely manner and problematic line segments can be located, overcoming the lag and uncertainty of manual experience judgment. For example, in areas with significant diurnal temperature differences, this solution can automatically adjust the theoretical line loss value, avoiding false alarms caused by temperature fluctuations, while accurately capturing abnormal losses caused by insulation aging or electricity theft.

[0073] For preferred options, please refer to [link / reference]. Figure 2 The present invention further proposes a method for generating the theoretical line loss of the distribution network, specifically including:

[0074] Step S21: Generate the total reference resistance of the feeder segments in the distribution network based on the segment length and reference resistance of the feeder in the distribution network;

[0075] Step S22: Establish a theoretical analysis model based on the total reference resistance loss of the feeder segment to generate the theoretical line loss of the feeder segment in the distribution network;

[0076] The total reference resistance of the line segment refers to the total resistance value of each line segment in the feeder at the reference temperature. Specifically, it can be achieved by multiplying the line segment length by the reference resistance per unit length. This feature allows the resistance parameter of each line segment to be characterized independently, avoiding the defect of the overall estimation method ignoring the segment characteristics of the line.

[0077] The theoretical analysis model refers to a mathematical model that calculates theoretical line loss based on the total reference resistance of the line segment. Specifically, it can be implemented by using the product relationship between the square of the current and the total reference resistance.

[0078] Specifically, the feeder is decomposed into multiple independent segments with uniform electrical parameters, and the length and reference resistance of each segment are extracted separately. By calculating the total reference resistance of the segments, a theoretical line loss model based on the relationship between current and resistance is established, and the power loss of each segment is calculated independently. For example, for a feeder containing three segments, the total reference resistance of each segment is calculated separately, and then the theoretical line loss is calculated separately based on the actual current value of each segment. This segmented calculation method can accurately reflect the line loss distribution characteristics caused by differences in length and current of different segments.

[0079] Compared to existing technologies, traditional methods use the equivalent resistance method to calculate the entire feeder as a single resistor, ignoring the differences in segment lengths and current distributions. For example, when the feeder contains long-distance lightly loaded segments and short-distance heavily loaded segments, the overall equivalent resistance method averages the losses of both, causing the calculated results to deviate from reality. This solution, however, uses segmented independent modeling to accurately capture the interaction between the resistance parameters and current distribution of each segment. For instance, in heavily loaded segments, the higher current value, combined with its corresponding total reference resistance, can be accurately calculated as a higher theoretical line loss value.

[0080] Through the above technical solution, this application achieves refined segmented calculation of distribution network line losses, solving the problem of insufficient accuracy caused by neglecting the segmented characteristics of traditional methods. By independently calculating the resistance and line loss of each line segment, the differences in loss contribution of different line segments can be accurately reflected. For example, in scenarios with branch lines or uneven load distribution, the differences in line loss between main line segments and branch line segments can be effectively distinguished, providing high-precision benchmark data for subsequent temperature correction and anomaly detection.

[0081] Preferably, the present invention further proposes a method for generating the theoretical line loss of the feeder segment, specifically including:

[0082] Through the formula: ;

[0083] Generate total reference resistance for line segments ;

[0084] In the formula, This represents the reference resistance of line segment i in the feeder. This represents the length of segment i in the feeder;

[0085] The reference resistance refers to the DC resistance value of a unit length of feeder conductor under standard temperature conditions. Specifically, it can be calculated by combining the standard resistivity of the conductor material with the temperature coefficient, and is used to characterize the inherent electrical characteristics of the conductor under a reference environment.

[0086] Line segment length refers to the actual physical extension of the conductor between two adjacent nodes in the distribution network topology. It can be obtained by measuring with a geographic information system or by obtaining line design parameters, and is used to quantify the spatial distribution characteristics of the line.

[0087] Specifically, a resistance calculation model based on the segmented characteristics of the line is constructed by multiplying the reference resistance of each independent line segment with its corresponding length. The total reference resistance of each line segment is accurately calculated using a formula, allowing line segments of different materials, cross-sectional areas, or installation methods to independently characterize their resistance parameters. This calculation method takes into account the actual segmented differences in distribution network lines, avoiding the parameter distortion problem caused by treating the entire feeder as a homogeneous conductor in traditional methods. By establishing resistance benchmark values ​​at the line segment level, accurate input parameters are provided for subsequent segmented calculations of theoretical line losses.

[0088] Compared with existing technologies, traditional methods for monitoring line losses in distribution networks typically use the equivalent resistance calculation model for the entire feeder, ignoring the differences in resistance parameters caused by line segmentation. This solution establishes a segmented resistance calculation model, achieving accurate quantification of conductor characteristics and length differences in different sections of the line, thus solving the resistance calculation error problem caused by the homogenization assumption of the line in traditional methods.

[0089] Through the above technical solution, this application effectively solves the problem of inaccurate total reference resistance caused by ignoring the segment characteristics of the line in the theoretical line loss calculation of the distribution network. By establishing a resistance calculation mechanism based on line segment units, it ensures the accurate characterization of the resistance parameters of each independent line segment, laying an accurate parameter foundation for the refined calculation of subsequent line loss analysis and improving the accuracy of distribution network line loss monitoring.

[0090] Preferably, the present invention further proposes the following expression for the theoretical analysis model: ;

[0091] In the expression, This represents the theoretical line loss of feeder segment i in the distribution network. This represents the current flowing through segment i in the feeder. This represents the total reference resistance of segment i in the feeder;

[0092] Among them, line segment theoretical line loss This refers to the power loss of feeder segment i at standard temperature. Specifically, it can be calculated by multiplying the square of the current by the total reference resistance, and is used to quantify the baseline value of the line loss of segment i.

[0093] Current It refers to the real-time current value flowing through line segment i. Specifically, it can be calculated by combining the difference between the active power at the beginning and the active power at the load point with the line topology, and is used to reflect the current distribution under actual operating conditions.

[0094] Specifically, the theoretical line loss of a line segment is calculated using the line loss theoretical calculation formula (i.e., the square of the current combined with the total reference resistance of the line segment). This line loss theoretical calculation formula is an existing formula and will not be elaborated here.

[0095] Compared with existing technologies, this solution achieves refined processing of line loss calculation by independently modeling each line segment and combining the actual current and resistance parameters of each line segment, providing high-precision basic data for subsequent temperature correction and anomaly detection.

[0096] Through the above technical solution, this application solves the problem of insufficient accuracy in the traditional theoretical line loss calculation of distribution networks due to the lack of consideration for line segment characteristics and actual operating parameters. By calculating the line loss independently by segment and correlating the dynamic current parameters, the calculation accuracy of theoretical line loss is significantly improved, providing a reliable theoretical basis for subsequent temperature correction models and line loss anomaly detection.

[0097] For preferred options, please refer to [link / reference]. Figure 3 The present invention further proposes a method for generating the theoretically corrected line loss of the distribution network, specifically including:

[0098] Step S31: Generate a temperature correction factor based on the temperature of the feeder segment;

[0099] Step S32: Establish a theoretical correction model based on the temperature correction factor and the theoretical line loss of the feeder segments in the distribution network, and generate the theoretical corrected line loss of the distribution network feeder;

[0100] Among them, the temperature correction factor is a coefficient used to quantify the impact of temperature changes on line resistance. Specifically, it can be calculated using the temperature coefficient of resistance of the conductor material and the difference between the actual temperature of the line segment and the reference temperature. Real-time calibration of the resistance value is achieved through the dynamic coupling of temperature parameters and theoretical line loss values.

[0101] The theoretical correction model refers to a calculation framework that combines temperature correction factors with theoretical line losses. Specifically, a weighted superposition method can be used to integrate the corrected theoretical line losses of each line segment with the total losses of the distribution transformer, and to reflect the actual changes in line resistance at different temperatures through mathematical correlation.

[0102] Specifically, the temperature correction factor establishes a linear relationship between temperature and resistance based on the temperature-resistance characteristics of the conductor material, converting real-time collected line segment temperature data into a resistance change proportionality coefficient. The theoretical correction model applies the temperature correction factor to the corresponding theoretical line loss value for each line segment, accumulating the corrected line segment losses plus the distribution transformer losses to form a complete theoretically corrected line loss for the distribution network. During operation, the temperature correction factor dynamically adjusts the resistance component in the theoretical line loss according to the line segment temperature, eliminating resistance calculation deviations caused by a fixed reference temperature, ensuring that the corrected theoretical line loss matches the line operating conditions under actual operating temperatures.

[0103] Compared to existing technologies, traditional methods use a reference resistor at a fixed temperature to calculate line loss, ignoring the impact of actual operating temperature fluctuations on the resistance value, leading to a systematic deviation between the theoretical line loss and the actual value. Existing simple temperature correction methods do not consider the differences in temperature distribution across different line segments, failing to achieve accurate segmented correction. This solution introduces a temperature correction factor to achieve independent dynamic adjustment of the resistance value of each line segment, establishing a segmented temperature correction mechanism that ensures the theoretical line loss calculation results accurately reflect the actual operating state of the line.

[0104] Through the above technical solution, this application effectively solves the problem of insufficient accuracy caused by the failure of traditional theoretical line loss calculation to consider the actual operating temperature changes of the line, and realizes accurate line loss calculation based on dynamic temperature correction. By collecting line segment temperature data in real time and generating a temperature correction factor, the resistance calculation value of each line segment is dynamically adjusted to eliminate the influence of temperature fluctuations on line loss calculation. The theoretical correction model, through a combination of segmented correction and overall superposition, ensures that the corrected theoretical line loss value can accurately reflect the actual loss of different line segments at different temperatures, providing a reliable theoretical benchmark for line loss anomaly monitoring.

[0105] Preferably, the present invention further proposes a method for generating the feeder resistance correction value, specifically including:

[0106] Through the formula: ;

[0107] Generating temperature correction factor ;

[0108] In the formula, This represents the temperature coefficient of resistance of line segment i in the distribution network feeder (i.e., the change in resistance of line segment i when the temperature rises by one unit). This represents the temperature of feeder segment i in the distribution network feeder. This indicates the standard temperature in the reference resistor. This represents the reference resistance of line segment i in the feeder;

[0109] The temperature correction factor is a proportional coefficient used to dynamically adjust the theoretical line loss calculation value. Specifically, it can be calculated by real-time acquisition of line temperature data by temperature sensor and combined with the material resistance temperature coefficient, which reflects the influence of actual operating temperature on line resistance.

[0110] The temperature coefficient of resistance refers to the rate at which the resistance of a conductor material changes with temperature. The specific parameters can be obtained by consulting the technical manual of wire materials, which is used to quantify the differences in temperature sensitivity of different wires.

[0111] Feeder segment temperature refers to the actual temperature of the conductor during operation. It can be monitored in real time using distributed fiber optic temperature measurement devices or infrared thermal imagers to capture the temperature distribution characteristics of each segment of the line.

[0112] The standard temperature refers to the standard temperature corresponding to the reference resistor. For example, it can be set to 20°C or determined according to local climate conditions, and is used to establish a benchmark comparison value for resistance changes.

[0113] Specifically, the temperature correction factor achieves dynamic correction through physical mechanism modeling. The temperature coefficient of resistance is incorporated into the formula, directly relating to the inherent properties of the conductor material. The difference between the real-time acquired feeder segment temperature and the standard temperature is calculated to quantify the degree of temperature deviation from standard operating conditions. This difference is then combined with the temperature coefficient of resistance to convert the temperature difference into a change in resistance. The reference resistance is then used as the denominator in the calculation, normalizing the temperature correction to a percentage change in unit resistance. This formula, by organically combining material properties, measured temperature, and reference parameters, constructs a correction model that can dynamically adapt to temperature changes in different feeder segments.

[0114] Compared to existing technologies, traditional methods often rely on fixed temperature coefficients or regional ambient temperatures to estimate line resistance, failing to reflect the actual temperature differences between different line segments. This solution, however, measures the temperature of each line segment online and calculates differential correction factors. For example, for the same feeder line segment exposed to direct sunlight and the buried segment, different temperature correction factors can be calculated based on the measured temperature, thus accurately reflecting the impact of uneven temperature distribution on line loss.

[0115] Through the above technical solution, this application achieves dynamic and accurate correction of the temperature effect in theoretical line loss calculation. When the line operating temperature fluctuates, such as when the temperature of a feeder segment rises due to high summer temperatures, the system can automatically calculate the corresponding temperature correction factor and correct the theoretical line loss of that segment, avoiding errors caused by ignoring temperature changes or using average temperature estimation in traditional methods. For mixed lines using different materials, such as copper cables for the main line and aluminum cables for branch lines, the system can apply the corresponding temperature coefficient of resistance for correction, effectively solving the problem of material characteristic mismatch caused by a uniform correction factor in existing technologies.

[0116] Preferably, the present invention further proposes the following expression for the theoretical correction model: ;

[0117] In the expression, This refers to the theoretical correction for line loss in the distribution network feeder. This represents the theoretical line loss of feeder segment i. This represents the temperature correction factor. This represents the total number of line segments in the feeder. This represents the total loss of the distribution transformer;

[0118] Among them, the total loss of the distribution transformer refers to the sum of iron loss and copper loss generated by the distribution transformer during operation. It can be calculated from the transformer no-load test and load test data, and is used to independently characterize the impact of the transformer's own loss on the theoretical line loss.

[0119] The temperature correction factor is a coefficient that dynamically adjusts the line loss calculation based on the difference between the actual temperature and the reference temperature of the feeder segment. Specifically, it can be calculated using the linear relationship between the temperature coefficient of resistance and the temperature deviation, and is used to eliminate the impact of line resistance fluctuations caused by changes in ambient temperature on line loss.

[0120] The theoretical correction model is a mathematical model that superimposes transformer losses with the temperature-corrected losses of each line segment. It achieves a refined calculation of theoretical line losses by introducing independent loss terms and dynamic correction factors.

[0121] Specifically, this technical solution incorporates the total loss of the distribution transformer as an independent item into the theoretical line loss calculation, avoiding the cumulative errors caused by neglecting transformer losses in traditional methods. Simultaneously, it calculates the product of the theoretical line loss and a temperature correction factor for each feeder segment, ensuring that temperature differences between segments are accurately reflected. For example, when the temperature of a segment is higher than the reference temperature, its resistance increases with temperature, and the corresponding temperature correction factor automatically adjusts the loss value of that segment upwards, thus achieving dynamic compensation for line losses. Finally, by accumulating the corrected loss values ​​of all segments and superimposing them with the transformer loss, a complete theoretically corrected line loss calculation result is formed.

[0122] Compared to existing technologies, traditional methods typically use a fixed temperature coefficient or ignore transformer losses when estimating theoretical line losses, resulting in calculations that fail to reflect the actual operating conditions of the equipment. This solution, however, by independently calculating transformer losses and applying segmented temperature corrections, can simultaneously capture the dual impact of equipment loss characteristics and line temperature variations.

[0123] Through the above technical solution, this application solves the problem of theoretical line loss calculation deviation caused by neglecting transformer losses and dynamic temperature correction in traditional methods, making the corrected theoretical line loss value closer to actual operating conditions. This solution can accurately identify line loss anomalies caused by events such as equipment aging or electricity theft, providing a high-precision theoretical benchmark for distribution network line loss monitoring, thereby improving the reliability of line loss anomaly detection.

[0124] Preferably, the present invention further proposes a method for generating the actual line loss of the distribution network, specifically including:

[0125] Through the formula: ;

[0126] Generate actual line losses in the distribution network ;

[0127] In the formula, This represents the active power at the beginning of the distribution network. This represents the active power at load point j, and M represents the total number of load points.

[0128] Among them, the active power at the head end refers to the total active power on the input side of the distribution network, which can be collected in real time by power sensors installed at the head end of the distribution network and is used to characterize the overall input energy of the distribution network.

[0129] Active power at load points refers to the active power actually consumed by each load node in the distribution network. Specifically, it can be periodically measured and summarized by smart meters deployed at load points to reflect the total electricity consumption of end users.

[0130] The actual line loss calculation formula directly calculates the line loss by the difference between the active power at the head end and the sum of the active power at all load points, covering the differences in load distribution across the entire network and avoiding errors caused by neglecting some load points or using approximate statistical values ​​in traditional methods.

[0131] Specifically, this technical solution collects active power data at the headend in real time and simultaneously acquires active power measurements from all load points, summing them to obtain the total load power. The difference between the headend power and the total load power represents the actual line loss that is not effectively utilized. For example, when there are multiple load points in a distribution network, the active power at each load point may dynamically change due to differences in user electricity consumption behavior. By traversing all load points and summing their power values, the actual total electricity consumption can be accurately reflected. This calculation process dynamically correlates with real-time data, providing an accurate benchmark for subsequent comparison with theoretically corrected line losses, thereby supporting the generation of anomaly coefficients and the reliability of line loss monitoring.

[0132] Compared to existing technologies, traditional methods typically calculate line loss by using the power difference between the beginning and a single end point, or by estimating the total load based on historical statistical data. This results in the actual line loss calculation being significantly affected by uneven load distribution or missing data. This solution, however, comprehensively collects real-time active power data from all load points and uses an additive calculation method, eliminating errors caused by missing data or statistical biases at local load points. Furthermore, through a dynamic data association mechanism, it enables real-time comparison between actual and theoretical line losses.

[0133] Through the above technical solution, this application can accurately calculate the actual line loss of the distribution network, avoiding the line loss assessment deviation caused by incomplete load point data or statistical errors in traditional methods. By dynamically linking the real-time power data of the head-end with all load points, a reliable data foundation is provided for the detection of line loss anomalies, thereby supporting the timely detection of line loss anomalies.

[0134] Preferably, the present invention further proposes a method for generating the line loss anomaly coefficient, specifically including:

[0135] Through the formula: ;

[0136] Generate the line loss anomaly coefficient K;

[0137] In the formula, This represents the actual line loss of the distribution network. This refers to the theoretical correction for line loss in the distribution network feeder;

[0138] Among them, the actual line loss of the distribution network refers to the real-time loss value calculated by the difference between the active power at the head end and the sum of the active power at all load points. Specifically, it can be realized by performing difference calculation on the power data collected by the power metering device, which is used to reflect the total actual loss that occurs in the operation of the distribution network.

[0139] The theoretically corrected line loss of a distribution network feeder refers to the calculated theoretical line loss after temperature correction. Specifically, it can be obtained by applying a temperature correction factor to the theoretical line loss of each feeder segment and then summing the results. It is used to reflect a refined theoretical loss prediction that takes into account the influence of temperature changes.

[0140] The line loss anomaly coefficient refers to the dynamic ratio of actual loss to theoretically predicted loss. Specifically, it can be achieved by calculating the ratio in real time and setting a threshold range, and is used to quantitatively characterize the degree of line loss anomaly and the direction of deviation.

[0141] Specifically, this technical solution calculates the actual line loss of the distribution network by acquiring the active power at the head end and the active power at the load point in real time. Simultaneously, based on the length, reference resistance, and temperature data of each feeder segment, a temperature-corrected theoretical line loss is generated. These two values ​​are then input into an anomaly coefficient calculation formula to obtain a normalized ratio. When this ratio significantly deviates from a preset benchmark value, it indicates an abnormal deviation between the actual loss and the theoretical prediction, triggering an alarm mechanism in the monitoring system. For example, during the temperature correction process, by introducing the resistance temperature coefficient and feeder segment temperature parameters, the theoretical line loss value of each segment is dynamically adjusted, thereby eliminating the impact of temperature fluctuations on the theoretical calculation and improving the accuracy of the comparison results.

[0142] Compared to existing technologies, which typically employ fixed temperature coefficients or neglect temperature correction, leading to accumulated deviations in theoretical line loss calculations and failing to effectively identify additional line losses caused by resistance variations, this solution achieves precise alignment between theoretical predictions and operational data by dynamically correcting theoretical line losses and simultaneously calculating real-time actual line losses. Furthermore, existing technologies lack standardized anomaly criteria, while this solution, through a normalized ratio approach, enables feeder systems of different scales and voltage levels to adopt a unified anomaly judgment standard.

[0143] Through the above technical solution, this application can achieve dynamic and accurate comparison between actual line loss and theoretical line loss. It eliminates environmental interference through temperature-corrected theoretical calculations, and uses anomaly coefficients to quickly identify loss anomalies and locate problem segments. This solves the problem of misjudgment caused by the coarse theoretical model and lack of dynamic correction in traditional methods, and improves the sensitivity and reliability of line loss monitoring.

[0144] Please see Figure 5 The present invention also proposes an intelligent monitoring system for distribution network line losses, which is used to execute the above-mentioned intelligent monitoring method for distribution network line losses, specifically including:

[0145] Data acquisition unit 10 is used to acquire the line segment length, reference resistance, active power at the head end, active power at the load point, and feeder line segment temperature of the feeder in the distribution network; wherein, the reference resistance refers to the resistance value per unit feeder at standard temperature.

[0146] The line segment theoretical line loss analysis unit 20 is used to establish a theoretical analysis model based on the line segment length and reference resistance of the feeder in the distribution network, and generate the line segment theoretical line loss of the feeder in the distribution network.

[0147] Theoretical correction unit 30 is used to establish a theoretical correction model based on the theoretical line loss of feeder segments and the temperature of feeder segments in the distribution network, and to generate the theoretical correction line loss of the feeder in the distribution network.

[0148] The actual line loss analysis unit 40 is used to generate the actual line loss of the distribution network based on the active power at the head end and the active power at the load point.

[0149] The line loss anomaly analysis unit 50 is used to correct line loss based on the actual line loss of the distribution network and the theoretical distribution network feeder, and generate a line loss anomaly coefficient.

[0150] The monitoring unit 60 is used to monitor the line loss of the distribution network based on the line loss anomaly coefficient.

[0151] For preferred options, please refer to [link / reference]. Figure 6 The present invention further proposes that the line segment theoretical line loss analysis unit 20 specifically includes:

[0152] The total reference resistance generation module 21 is used to generate the total reference resistance of the feeder segments in the distribution network based on the line length and reference resistance of the feeder segments in the distribution network.

[0153] The line segment theoretical line loss generation module 22 is used to establish a theoretical analysis model based on the total reference resistance loss of the line segment in the feeder and generate the line segment theoretical line loss of the feeder in the distribution network.

[0154] For preferred options, please refer to [link / reference]. Figure 7 The present invention further proposes that the theoretical correction unit 30 specifically includes:

[0155] The correction factor generation module 31 is used to generate a temperature correction factor based on the temperature of the feeder segment.

[0156] The theoretical correction line loss generation module 32 is used to establish a theoretical correction model based on the temperature correction factor and the theoretical line loss of the feeder segments in the distribution network, and generate the theoretical correction line loss of the feeder in the distribution network.

[0157] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A power distribution network line loss intelligent monitoring method, characterized in that, Specifically comprising the following steps: Obtaining the line segment length, reference resistance, head-end active power, load point active power and feeder line segment temperature of the feeder in the power distribution network; wherein the reference resistance refers to the resistance value of a unit feeder at a standard temperature; According to the line segment length and reference resistance of the feeder in the power distribution network, a theoretical analysis model is established to generate the line segment theoretical line loss of the feeder in the power distribution network; According to the line segment theoretical line loss of the feeder in the power distribution network and the feeder line segment temperature, a theoretical correction model is established to generate the power distribution network feeder theoretical correction line loss; According to the head-end active power and the load point active power, the actual line loss of the power distribution network is generated; According to the actual line loss of the power distribution network and the power distribution network feeder theoretical correction line loss, the line loss anomaly coefficient is generated; According to the line loss anomaly coefficient, the line loss of the power distribution network is monitored.

2. The power distribution network line loss intelligent monitoring method according to claim 1, characterized in that, The generation method of the power distribution network theoretical line loss specifically comprises: According to the line segment length and reference resistance of the feeder in the power distribution network, the total reference resistance of the line segment of the feeder in the power distribution network is generated; According to the total reference resistance of the line segment of the feeder, a theoretical analysis model is established to generate the line segment theoretical line loss of the feeder in the power distribution network.

3. The power distribution network line loss intelligent monitoring method according to claim 2, characterized in that, The generation method of the feeder line segment theoretical line loss specifically comprises: By the formula: ; Generating a total reference resistance for a line segment ; In the formula, Ri represents the reference resistance of the line section i in the feeder, Li represents the length of the line section i in the feeder.

4. The power distribution network line loss intelligent monitoring method according to claim 2, characterized in that, The expression of the theoretical analysis model is specifically: ； In the expression, represents the line segment theoretical line loss of the feeder line segment i in the distribution network, represents the current flowing through the line segment i in the feeder line, represents the line segment total reference resistance of the line segment i in the feeder line.

5. The power distribution network line loss intelligent monitoring method according to claim 1, characterized in that, The generation method of the power distribution network theoretical correction line loss specifically comprises: According to the feeder line segment temperature, a temperature correction factor is generated; According to the temperature correction factor and the line segment theoretical line loss of the feeder in the power distribution network, a theoretical correction model is established to generate the power distribution network feeder theoretical correction line loss.

6. The power distribution network line loss intelligent monitoring method according to claim 5, characterized in that, The generation method of the feeder resistance correction value specifically comprises: Through the formula: ； Generation of temperature correction factor ; In the formula, represents the resistance temperature coefficient of the line segment i in the distribution network feeder, represents the feeder line segment temperature of the line segment i in the distribution network feeder, represents the standard temperature in the reference resistance, represents the reference resistance of the line segment i in the feeder.

7. The power distribution network line loss intelligent monitoring method according to claim 5, characterized in that, The expression of the theoretical correction model is specifically: ； In the expression, represents the theoretical line loss of the distribution feeder, represents the line segment theoretical line loss of the feeder line segment i, represents the temperature correction factor, represents the total number of line segments in the feeder, represents the total loss of the distribution transformer. 8.The power distribution network line loss intelligent monitoring method of claim 1, characterized in that, The generation method of the actual line loss of the power distribution network specifically comprises: Through the formula: ； Generating actual line loss of a power distribution network ; In the formula, P0 represents the active power of the first end of the distribution network, Pj represents the active power of the load point j, and M represents the total number of load points.

9. The power distribution network line loss intelligent monitoring method according to claim 1, characterized in that, The generation method of the line loss anomaly coefficient specifically comprises: Through the formula: ； The line loss anomaly coefficient K is generated; In the formula, represents the actual line loss of the distribution network, represents the theoretical corrected line loss of the feeder of the distribution network.

10. A power distribution network line loss intelligent monitoring system, characterized in that, The system is used to execute the power distribution network line loss intelligent monitoring method of any one of claims 1-9, specifically comprising: A data acquisition unit is configured to obtain the line segment length, reference resistance, head-end active power, load point active power and feeder line segment temperature of the feeder in the power distribution network; wherein the reference resistance refers to the resistance value of a unit feeder at a standard temperature; A line segment theoretical line loss analysis unit is configured to establish a theoretical analysis model according to the line segment length and reference resistance of the feeder in the power distribution network, and generate the line segment theoretical line loss of the feeder in the power distribution network; A theoretical correction unit is configured to establish a theoretical correction model according to the line segment theoretical line loss of the feeder in the power distribution network and the feeder line segment temperature, and generate the power distribution network feeder theoretical correction line loss; An actual line loss analysis unit is configured to generate the actual line loss of the power distribution network according to the head-end active power and the load point active power; A line loss anomaly analysis unit is configured to generate the line loss anomaly coefficient according to the actual line loss of the power distribution network and the power distribution network feeder theoretical correction line loss; A monitoring unit is configured to monitor the line loss of the power distribution network according to the line loss anomaly coefficient.

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