A calculation method of power transmission and distribution price based on effective asset valuation

Abstract

The embodiment of the application provides a kind of based on effective asset authorized transmission and distribution price calculation method, it is applied to electric power system technical field, by obtaining the environmental data of transmission line, equipment health data and operation data, calculate environmental adaptability coefficient and space redundancy parameter, and two multidimensional fusion forms effective asset quantization matrix, further mapping is the effective asset score and effective asset value of each transmission line;According to the comparison result of effective asset score and preset trigger threshold, calculate effective asset reduction ratio, and input effective asset value and reduction ratio into transmission and distribution price calculation model, determine the transmission and distribution price of each transmission line, realize the accurate matching of asset value and price allocation.

Description

Technical Field

[0001] This application relates to the field of power system technology, and in particular to a method for calculating transmission and distribution prices based on valid asset assessment. Background Technology

[0002] The existing method for determining transmission and distribution tariffs typically uses the original value or net value after depreciation of the fixed assets of the power grid company as a basis, and combines factors such as line length, equipment capacity, and electricity load level to determine the proportion and recovery amount of various power grid assets included in the transmission and distribution tariff according to regulatory and accounting standards. This method focuses on the fair allocation of book value and cost recovery, ensuring that power grid investment and operation and maintenance costs are reasonably included within the institutional framework.

[0003] In practice, existing methods for determining transmission and distribution prices typically involve determining the effective asset size based on the original value or net depreciation of fixed assets reported by the power grid company. Then, by combining operating parameters such as line length, equipment capacity, and user load levels, the allocation ratio of different asset categories in the transmission and distribution process is calculated. Next, according to the prescribed cost audit standards, expenses such as asset depreciation, operation and maintenance, and reasonable profits are summarized to form the total permitted revenue for transmission and distribution. Finally, this total revenue is allocated to various types of users according to electricity volume or capacity to obtain the transmission and distribution price.

[0004] The above-mentioned scheme still has some problems in practical application. Existing technology mainly relies on book financial data and fixed depreciation rules, which cannot reflect the actual usable life of similar assets under different environmental conditions. This leads to inaccurate inclusion of effective assets for lines with high environmental risk or high degradation. Furthermore, it fails to distinguish between primary and backup lines, making it impossible to reflect the reserve value and actual operational contribution of redundant resources in the assessment results. Therefore, the effective asset values ​​uniformly converted from book value cannot accurately reflect the actual operating status and reliability contribution of each line in the transmission and distribution price allocation calculation, resulting in asset value deviations and price allocation distortions in the transmission and distribution price calculation results. Summary of the Invention

[0005] This application provides a method for calculating transmission and distribution prices based on the assessment of effective assets. By comprehensively considering the environmental conditions, equipment health status, operational participation, and historical fault data of transmission lines, the effective assets of each transmission line are refined, quantified, and reduced. This allows the transmission and distribution price to accurately reflect the actual operating value, risk level, and redundancy utilization of the line, thereby improving the scientific nature, accuracy, and fairness of transmission and distribution price assessment.

[0006] To achieve the above objectives, this application adopts the following technical solution:

[0007] This application provides a method for calculating transmission and distribution tariffs based on effective asset assessment. The method includes: acquiring environmental data, equipment health data, and operational data of transmission lines; calculating an environmental adaptability coefficient of the transmission lines based on the environmental data and equipment health data, wherein the environmental adaptability coefficient is used to quantify the lifespan and health status of the transmission lines under different environmental conditions; calculating a spatial redundancy parameter of the transmission lines based on the operational data, wherein the spatial redundancy parameter is used to characterize the actual operational participation of the transmission lines in the transmission network; multi-dimensionally fusing the environmental adaptability coefficient and the spatial redundancy parameter according to the correspondence of the transmission lines to form an effective asset quantification matrix of the transmission lines; mapping the effective asset quantification matrix to an effective asset score and effective asset value for each transmission line, wherein the effective asset score is used to identify high-value lines, low-utilization lines, and lines with potential environmental risks; comparing the effective asset score with a preset trigger threshold to obtain a comparison result, and calculating the effective asset reduction ratio for each transmission line based on the comparison result; and inputting the effective asset value and the effective asset reduction ratio into a transmission and distribution tariff calculation model to determine the transmission and distribution tariff of the transmission lines.

[0008] In some possible implementations, the environmental data includes long-term climate parameters, frequency of extreme weather events, and regional corrosion indices; the equipment health data includes corrosion rate, insulation aging degree, and temperature cycling effects; and the calculation of the environmental adaptability coefficient of the transmission line based on the environmental data and equipment health data includes: calculating a climate impact index based on long-term climate parameters and frequency of extreme weather events, the climate impact index being used to characterize the long-term impact of the external environment on the structural fatigue and conductor performance degradation of the transmission line; calculating a material degradation index based on the regional corrosion index and corrosion rate, the material degradation index being used to characterize the material loss rate of the transmission line under specific geographical and chemical environments; calculating an insulation stability index based on the insulation aging degree and temperature cycling effects, the insulation stability index being used to characterize the dielectric performance retention capability of the line insulation layer; and performing calculations on the climate impact index, material degradation index, and insulation stability index according to a preset nonlinear fusion relationship to obtain the environmental adaptability coefficient, the nonlinear fusion relationship being used to characterize the interactive cumulative effect between environmental conditions and the material aging process.

[0009] In some possible implementations, the step of calculating the climate impact index, material degradation index, and insulation stability index according to a preset nonlinear fusion relationship to obtain an environmental adaptability coefficient includes: normalizing the climate impact index, material degradation index, and insulation stability index of each transmission line to obtain comparable index values; weighting and superimposing the comparable index values ​​according to a nonlinear relationship to obtain a preliminary comprehensive index for each transmission line; and correcting the preliminary comprehensive index according to a preset critical threshold to obtain the environmental adaptability coefficient.

[0010] In some possible implementations, the step of correcting the preliminary comprehensive index according to a preset critical threshold to obtain an environmental adaptability coefficient includes: setting a critical threshold, which includes a first critical threshold and a second critical threshold, wherein the first critical threshold is less than the second critical threshold; comparing the preliminary comprehensive index with the critical threshold to obtain a comparison result; selecting a corresponding correction rule based on the comparison result, wherein the correction rule includes a first correction rule and a second correction rule, specifically: if the preliminary comprehensive index is lower than the first critical threshold, then the first correction rule is used to adjust the preliminary comprehensive index to obtain an environmental adaptability coefficient; the first correction rule is configured to use an exponential decay function or a power law function to make the output environmental adaptability coefficient show an accelerated decreasing trend relative to the preliminary comprehensive index; if the preliminary comprehensive index is higher than the second critical threshold, then the second correction rule is used to adjust the preliminary comprehensive index to obtain an environmental adaptability coefficient; the second correction rule is configured to use a logarithmic function or a linear saturation function to make the output environmental adaptability coefficient show a gain saturation trend relative to the preliminary comprehensive index; if the preliminary comprehensive index is between the first critical threshold and the second critical threshold, then the preliminary comprehensive index is directly used as the environmental adaptability coefficient.

[0011] In some possible implementations, the line network information of the transmission lines is obtained, including the rated capacity of the transmission lines. The operational data includes the actual load of the lines, operation scheduling records, and reserve capacity. The calculation of the spatial redundancy parameter of the transmission lines based on the operational data includes: determining the long-term average load rate and utilization duration of each transmission line based on the actual load of the lines in the operational data; marking the transmission line as a low-utilization line when the long-term average load rate of the transmission line within a preset evaluation period is lower than a load rate threshold and the utilization duration is lower than a utilization duration threshold; analyzing the operation scheduling records of the low-utilization lines, and determining the low-utilization line as a redundant line when the ratio of the reserve capacity to the rated capacity of the low-utilization line exceeds a reserve capacity threshold; determining the ratio of the reserve capacity to the rated capacity of the redundant line as the redundancy reserve capacity ratio; obtaining a redundancy utilization rate index based on the actual load and operation scheduling records of the redundant lines; and calculating the spatial redundancy parameter of the transmission lines based on the redundancy reserve capacity ratio and the redundancy utilization rate index.

[0012] In some possible implementations, the step of multi-dimensionally fusing the environmental adaptability coefficient and the spatial redundancy parameter according to the correspondence of transmission lines to form an effective asset quantification matrix for transmission lines includes: constructing a two-dimensional decision coordinate system, defining the horizontal axis as the environmental adaptability coefficient and the vertical axis as the spatial redundancy parameter; mapping each transmission line to a coordinate point in the two-dimensional decision coordinate system based on its corresponding environmental adaptability coefficient and spatial redundancy parameter; using the region where the coordinate point is located in the two-dimensional decision coordinate system as an index to query a preset asset validity mapping table to obtain the effective asset value corresponding to the coordinate point, wherein the preset asset validity mapping table is used to store the correspondence between coordinate points and effective asset values, and the effective asset value is calculated from historical environmental adaptability coefficients and historical spatial redundancy parameters; and collecting the effective asset values ​​of all transmission lines to form an effective asset quantification matrix, wherein the effective asset quantification matrix is ​​used to reflect the effective asset value of each transmission line.

[0013] In some possible implementations, mapping the effective asset quantification matrix to an effective asset score and effective asset value for each transmission line includes: extracting features from the effective asset quantification matrix to obtain effective asset values ​​and corresponding effective asset vectors; calculating the covariance matrix of the effective asset quantification matrix and performing eigenvalue decomposition on the covariance matrix to obtain multiple eigenvectors and unique eigenvalues ​​for each eigenvector; selecting the eigenvector corresponding to the largest eigenvalue as the principal eigenvector, wherein the principal eigenvector represents the feature combination pattern that contributes the most to the effective assets of the transmission line; and projecting the effective asset vector of each transmission line onto the principal eigenvector to obtain an effective asset score for each transmission line.

[0014] In some possible implementations, comparing the effective asset score with a preset trigger threshold to obtain a comparison result, and calculating the effective asset reduction ratio for each transmission line based on the comparison result, includes: setting a trigger threshold, which includes a first threshold and a second threshold, wherein the first threshold is less than the second threshold; comparing the effective asset score of each transmission line with the trigger threshold to obtain a comparison result, and determining a basic reduction rate based on the comparison result, including: if the effective asset score is lower than the first threshold, the basic reduction rate is a first preset value; if the effective asset score is between the first threshold and the second threshold, the basic reduction rate is a second preset value; if the effective asset score is higher than the second threshold, the basic reduction rate is zero; calculating an adjustment factor for adjusting the basic reduction rate based on the acquired historical fault data of the transmission lines; and multiplying the basic reduction rate by the adjustment factor to obtain the effective asset reduction ratio for each transmission line.

[0015] In some possible implementations, the calculation of the adjustment factor for adjusting the base reduction rate based on the acquired historical fault data of the transmission line includes: acquiring historical fault data of the transmission line, the historical fault data including average fault frequency and average repair time; calculating a frequency impact value based on the fault frequency, the frequency impact value being exponentially correlated with the fault frequency; calculating a time impact value based on the average repair time, the time impact value being logarithmically correlated with the repair time; and calculating an adjustment factor based on the frequency impact value and the time impact value, the adjustment factor being used to correct the base reduction rate to reflect the effective asset reduction rate of the transmission line under historical fault risk.

[0016] In some possible implementations, the step of inputting the effective asset value and the effective asset reduction ratio into the transmission and distribution price calculation model to determine the transmission and distribution price of the transmission line includes: adjusting the effective asset value of each transmission line according to the effective asset reduction ratio to obtain a final effective asset value; inputting the final effective asset value into the transmission and distribution price calculation model so that the transmission and distribution price calculation model performs calculations based on the final effective asset value and a preset electricity price calculation formula, and outputs the transmission and distribution price corresponding to each transmission line, wherein the transmission and distribution price is used to reflect the asset value of the transmission line under a comprehensive evaluation of environmental conditions, health status, and operational participation.

[0017] As can be seen from the above technical solution, this application has the following beneficial effects:

[0018] 1. This application constructs environmental adaptability coefficients and spatial redundancy parameters by introducing transmission line environmental data, equipment health data, and operational data, and forms an effective asset quantification matrix through multi-dimensional fusion. This enables a refined quantitative assessment of the effective assets of transmission lines. Compared with existing technologies that mainly rely on book value and fixed depreciation rules, this application can reflect different environmental conditions, material aging status, and actual operational participation of the lines, thereby more accurately identifying high-value lines, low-utilization lines, and lines with potential environmental risks, and improving the scientificity and rationality of transmission and distribution price determination.

[0019] 2. This application adjusts the preliminary comprehensive index by setting critical thresholds and correction rules, and calculates reduction factors by combining historical fault data to dynamically reduce the effective asset value. This achieves a comprehensive assessment of the lifespan, health status, and fault risk of line assets. Compared with existing technologies that cannot distinguish between primary and backup lines or do not consider environmental and fault factors, this application can accurately reflect the reliability contribution and redundancy value of each line in the network, reducing asset value deviation and price allocation distortion.

[0020] 3. This application inputs the final effective asset value into the transmission and distribution price calculation model, and generates the transmission and distribution price through a comprehensive evaluation of environmental adaptability, health status and operational participation. This achieves a high degree of matching between asset value and price allocation. Compared with existing methods, this application can allocate transmission and distribution costs more fairly and reasonably while ensuring that grid investment and operation and maintenance costs are reasonably included, thereby improving the accuracy and credibility of transmission and distribution price determination. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating a method for calculating transmission and distribution tariffs based on valid asset verification, as described in this application. Detailed Implementation

[0022] The terms "first," "second," and "third," etc., used in this application specification, claims, and drawings are used to distinguish different objects, not to limit a specific order.

[0023] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0024] Research has revealed that existing technologies primarily rely on book financial data and fixed depreciation rules, failing to reflect the actual usable lifespan of similar assets under varying environmental conditions. This leads to inaccurate inclusion of effective assets in high-environment-risk or high-deterioration lines. Furthermore, the lack of distinction between primary and backup lines prevents the reflection of the reserve value and actual operational contribution of redundant resources in the assessment results. Therefore, the effective asset values ​​uniformly converted from book value cannot accurately reflect the actual operating status and reliability contribution of each line in transmission and distribution price allocation calculations, resulting in asset value deviations and distorted price allocation.

[0025] To address the aforementioned problems, this application provides a method for calculating transmission and distribution tariffs based on effective asset verification. The method includes: acquiring environmental data, equipment health data, and operational data of transmission lines; calculating an environmental adaptability coefficient for the transmission lines based on the environmental data and equipment health data, wherein the environmental adaptability coefficient is used to quantify the lifespan and health status of the transmission lines under different environmental conditions; calculating a spatial redundancy parameter for the transmission lines based on the operational data, wherein the spatial redundancy parameter characterizes the actual operational participation of the transmission lines in the transmission network; and comparing the environmental adaptability coefficient with the spatial redundancy parameter. Redundancy parameters are fused in multiple dimensions according to the correspondence of transmission lines to form an effective asset quantification matrix for transmission lines. The effective asset quantification matrix is ​​mapped to an effective asset score and effective asset value for each transmission line. The effective asset score is used to identify high-value lines, low-utilization lines, and lines with potential environmental risks. The effective asset score is compared with a preset trigger threshold to obtain a comparison result, and the effective asset reduction ratio for each transmission line is calculated based on the comparison result. The effective asset value and the effective asset reduction ratio are input into the transmission and distribution price calculation model to determine the transmission and distribution price of the transmission lines.

[0026] Example 1: As Figure 1 As shown, this application provides a method for calculating transmission and distribution tariffs based on valid asset assessment, the method comprising the following steps:

[0027] S1 acquires environmental data, equipment health data, and operational data of the transmission line, specifically:

[0028] A pre-defined data acquisition time window can be set, which can be one or more consecutive periods, such as a time span of 1 month, 3 months, or 6 months, depending on the voltage level, geographical region, and operational stability of the transmission line. By synchronously acquiring different types of data within the same time window, the temporal correspondence between environmental data, equipment health data, and operational data can be ensured, thereby improving the accuracy of subsequent analysis.

[0029] Within the data acquisition window, environmental data is collected using environmental monitoring devices deployed along the transmission line. These devices include temperature and humidity sensors, wind speed measurement modules, and air pollution monitoring units. The environmental data includes long-term climate parameters, frequency of extreme weather events, and regional corrosion indices, reflecting the corrosivity, stress load, and climate fluctuations of the external environment where the transmission line is located. Furthermore, statistical information from regional meteorological stations and historical climate databases can be used to supplement the measured results of the environmental monitoring devices, thereby improving the spatiotemporal completeness of the environmental data.

[0030] When acquiring equipment health data for transmission lines, multi-source information from the online monitoring system and regular inspection system is used to collect status data of conductors, insulators, fittings, and supporting components. This equipment health data includes corrosion rate, insulation aging degree, and the effects of temperature cycling, reflecting the performance degradation trend of the equipment under long-term operation and external stress. By analyzing the corrosion and aging characteristics of the equipment, health status indicators of each component can be obtained, providing basic data support for subsequent calculations of environmental adaptability coefficients.

[0031] During the data acquisition process, actual operational information of transmission lines is obtained through the dispatch control system and SCADA system. This operational data includes actual line load, operation dispatch records, and reserve capacity, used to characterize the actual operational intensity and participation level of transmission lines in the transmission network. Combining historical dispatch data and real-time monitoring results, the load utilization patterns and redundant operation characteristics of the lines can be further identified. Through these steps, a comprehensive dataset covering the three dimensions of environment, equipment, and operation is ultimately formed, providing a data foundation for subsequent calculations of the environmental adaptability coefficient and spatial redundancy parameters of transmission lines.

[0032] S2, based on the environmental data and equipment health data, calculate the environmental adaptability coefficient of the transmission line. The environmental adaptability coefficient is used to quantify the lifespan and health status of the transmission line under different environmental conditions. Specifically, it involves calculating multiple characterization indices based on the environmental data and equipment health data, including a climate impact index, a material degradation index, and an insulation stability index, and establishing a nonlinear fusion relationship on this basis to obtain the final environmental adaptability coefficient. This further includes the following steps:

[0033] A climate impact index is calculated based on long-term climate parameters and the frequency of extreme weather events. This index reflects the long-term impact of external climate conditions on the fatigue of transmission line structures and the degradation of conductor performance. Specifically, the intensity of long-term climate fluctuations is calculated using average temperature, humidity, wind speed, and the frequency of extreme weather events within a set time window, and the climate impact coefficient is determined by combining this with historical fault statistics. This climate impact index can quantify the cumulative effects of sudden changes in high and low temperatures, strong winds, and humidity fluctuations on the fatigue life of conductors and fittings.

[0034] The material degradation index is calculated based on the regional corrosion index and the equipment corrosion rate. This material degradation index characterizes the rate of material loss in transmission lines under specific geographical and chemical environments. Specifically, the regional corrosion index is determined based on the soil pH, salt spray concentration, and industrial pollution level of the transmission line location. This index is then combined with corrosion rate parameters of conductors and connectors obtained from online monitoring systems or periodic testing to form the material degradation index. This index reflects the attenuation trend of the mechanical strength and electrical conductivity of transmission line materials under different regional corrosive environments.

[0035] The insulation stability index is calculated based on the degree of insulation aging and the effects of temperature cycling. This index characterizes the ability of the insulation layer of transmission lines to retain its dielectric properties. An insulation aging model is established through statistical analysis of the insulator surface resistivity, dielectric loss factor, and temperature cycling frequency. The correlation between temperature change amplitude and aging rate is used to determine the insulation performance decay curve, thereby obtaining the insulation stability index. This index accurately reflects the stability of the insulation structure under long-term thermal and electrical stress.

[0036] The climate impact index, material degradation index, and insulation stability index are comprehensively calculated according to a preset nonlinear fusion relationship to obtain a preliminary comprehensive index for each transmission line. This preliminary comprehensive index is then corrected based on a preset critical threshold to obtain the environmental adaptability coefficient. The nonlinear fusion relationship, by introducing an index weighting factor and interactive coupling terms, comprehensively characterizes the mutual influence of different environmental factors and material aging characteristics. This fusion relationship reflects the cumulative effect of long-term climate fluctuations, corrosive environments, and temperature stress on line performance degradation at different stages, thus more realistically depicting the nonlinear variation law of transmission line lifespan reduction under the combined effect of multiple factors.

[0037] It should be noted that the advantages of calculating the environmental adaptability coefficient of transmission lines are as follows: by integrating the climate impact index, material degradation index, and insulation stability index in multiple dimensions, it can quantitatively reflect the coupling relationship between the external environment and equipment performance, thereby accurately identifying the differences in the lifespan and health status of transmission lines under different regions and climatic conditions. The introduction of this coefficient breaks through the traditional static assessment method based on fixed depreciation years or empirical reduction coefficients, enabling the effective asset assessment of transmission lines to dynamically reflect the actual impact of environmental load and material degradation, improving the scientific rigor and discriminative power of asset assessment results, and providing a more realistic, quantifiable, and traceable basis for environmental correction in transmission and distribution pricing.

[0038] S3, based on the operational data, calculate the spatial redundancy parameter of the transmission line. This spatial redundancy parameter characterizes the actual operational participation of the transmission line in the transmission network, specifically:

[0039] The long-term average load factor and utilization time of transmission lines are calculated based on the collected operational data. Specifically, based on the load time series data of the transmission line within a preset assessment period, the ratio of the line's average load to its rated capacity is calculated, i.e., the long-term average load factor. The cumulative duration of the line's operation within this period is also calculated as the utilization time indicator. The long-term average load factor reflects the line's load level, while the utilization time describes the line's operating frequency within the assessment period.

[0040] When the long-term average load factor of the transmission line is lower than a set load factor threshold, and the utilization time is lower than a utilization time threshold, the transmission line is marked as a low-utilization line. Subsequently, the operation and scheduling records of the low-utilization lines are statistically analyzed to extract the reserve capacity, number of operation switching, and reserve transfer time distribution information of each line in the scheduling plan. When the ratio of the reserve capacity to the rated capacity of the low-utilization line exceeds a preset reserve capacity threshold, the low-utilization line is determined to be a redundant line.

[0041] After identifying redundant lines, the ratio of their reserve capacity to rated capacity is calculated to obtain the redundancy reserve capacity ratio, which reflects the reserve proportion of the line in the redundancy structure of the transmission system. Simultaneously, combining the operation and scheduling records and actual load changes of the redundant line during the evaluation period, a redundancy utilization rate index is calculated. This index measures the frequency of participation and load-bearing level of the redundant line in multiple scheduling events.

[0042] Based on the redundancy reserve ratio and redundancy utilization rate, the spatial redundancy parameters of the transmission line are calculated using a preset weighted function relationship.

[0043] It should be noted that the spatial redundancy parameter comprehensively considers the backup status of the line in the transmission network and the actual dispatch participation, which can effectively distinguish between primary lines, long-term backup lines and structurally redundant lines. This provides a basis for network structure correction for subsequent effective asset quantification and transmission and distribution price calculation, and enables the determination of transmission and distribution prices to better fit the actual operation pattern of the transmission system, avoiding the deviation caused by evaluating solely based on book capacity or fixed depreciation.

[0044] S4, the environmental adaptability coefficient and the spatial redundancy parameter are multidimensionally fused according to the correspondence between transmission lines to form an effective asset quantification matrix for transmission lines, specifically:

[0045] A two-dimensional decision coordinate system is constructed, in which the horizontal axis represents the environmental adaptability coefficient and the vertical axis represents the spatial redundancy parameter, which is used to intuitively characterize the comprehensive performance of transmission lines under the two dimensions of environmental condition carrying capacity and network structure redundancy value.

[0046] The environmental adaptability coefficient and spatial redundancy parameter of each transmission line are mapped to a unique coordinate point in a two-dimensional decision coordinate system. This coordinate point comprehensively reflects the health status of the line under specific environmental conditions and its operational participation in the transmission network. Based on the regional location of the coordinate point in the two-dimensional decision coordinate system, a pre-established asset validity mapping table is consulted to obtain the corresponding effective asset value. The asset validity mapping table is established through statistical analysis of historical environmental adaptability coefficients and historical spatial redundancy parameters, recording the correspondence between different coordinate points and effective asset values, thereby scientifically reflecting the actual asset value contribution of each line under past operating conditions.

[0047] The effective asset values ​​corresponding to all transmission lines are aggregated to form an effective asset quantification matrix. This effective asset quantification matrix uses the line number as an index and the effective asset value as the matrix element, which can comprehensively reflect the distribution of effective assets of each line in the entire transmission network.

[0048] It should be noted that the effective asset quantification matrix, by integrating environmental adaptability coefficients and spatial redundancy parameters in a multi-dimensional manner, can comprehensively and quantitatively reflect the health status of each transmission line under different environmental conditions and its actual operational contribution to the transmission network. This avoids the biases caused by traditional assessment methods that rely solely on book capacity or fixed depreciation. Simultaneously, this matrix provides a unified data foundation for subsequent effective asset scoring of transmission lines and calculation of transmission and distribution prices, enabling asset assessment results to take into account line operational safety, environmental adaptability, and network redundancy value, achieving scientific, refined quantification and comparative analysis of transmission line asset value.

[0049] S5, the effective asset quantification matrix is ​​mapped to an effective asset score and an effective asset value for each transmission line. The effective asset score is used to identify high-value lines, low-utilization lines, and lines with potential environmental risks. Specifically:

[0050] Feature extraction is performed on the effective asset quantification matrix to obtain the effective asset value and its corresponding effective asset vector for each transmission line. The effective asset vector is used to characterize the comprehensive characteristics of the line in multiple dimensions such as environmental adaptability and spatial redundancy, providing basic data for subsequent scoring calculations.

[0051] The covariance matrix of the effective asset quantification matrix is ​​calculated to quantify the correlation between features in each dimension. The covariance matrix is ​​then subjected to eigenvalue decomposition to obtain multiple eigenvectors and their corresponding eigenvalues. Each eigenvector represents a comprehensive feature pattern in the matrix, while the corresponding eigenvalue reflects the contribution of that eigenvector to the distribution of effective assets.

[0052] The eigenvector corresponding to the largest eigenvalue is selected as the principal eigenvector. The principal eigenvector is used to characterize the comprehensive feature pattern that contributes the most to the value of line assets in the effective asset quantification matrix, which includes multi-dimensional features such as environmental adaptability, spatial redundancy and operational participation of each transmission line. It can reveal the relative weight of the impact of different feature combinations on the effective assets of the line.

[0053] The effective asset vector of each transmission line is projected onto the principal feature vector to obtain the effective asset score of each line. The effective asset score is used to distinguish between high-value lines, low-utilization lines, and lines with potential environmental risks.

[0054] It should be noted that the benefits of the effective asset scoring system are as follows: by projecting the effective asset vector of each transmission line onto the principal feature vector, the effective asset scoring system can comprehensively quantify multi-dimensional characteristics such as environmental adaptability, network redundancy, and operational participation, forming a comparable single indicator. This not only clearly distinguishes between high-value lines, low-utilization lines, and lines with potential environmental risks, but also provides a scientific basis for transmission and distribution pricing, avoiding the distortion of asset value caused by relying solely on book capacity or experience-based reduction factors. Simultaneously, the effective asset scoring system facilitates hierarchical management and risk identification of the transmission network, providing quantitative support for grid operation and maintenance optimization and asset investment decisions.

[0055] S6, compare the effective asset score with a preset trigger threshold to obtain a comparison result, and calculate the effective asset reduction ratio for each transmission line based on the comparison result, specifically:

[0056] A trigger threshold for asset reduction is set, including a first threshold and a second threshold, with the first threshold being less than the second threshold. This threshold is used to classify effective asset scores into three levels: low, medium, and high, thereby determining the initial reduction standard. Subsequently, the effective asset score of each transmission line is compared with the thresholds: when the effective asset score is lower than the first threshold, the basic reduction rate is set to a first preset value; when the effective asset score is between the first and second thresholds, the basic reduction rate is set to a second preset value; when the effective asset score is higher than the second threshold, the basic reduction rate is zero.

[0057] Historical fault data for each transmission line is acquired, including average fault frequency and average repair time. An adjustment factor for adjusting the base reduction rate is calculated based on this historical fault data. Specifically, a frequency impact value is calculated based on the fault frequency, which is exponentially correlated with the fault frequency and reflects the risk weighting of high-frequency fault lines. A duration impact value is calculated based on the average repair time, which is logarithmically correlated with the repair time and quantifies the impact of fault duration on asset value.

[0058] Multiply the base reduction rate by the adjustment factor to obtain the effective asset reduction ratio for each transmission line.

[0059] It should be noted that the reduction ratio can comprehensively consider the environmental adaptability, operational participation and historical fault risk of the line, and realize differentiated reduction of the asset value of different lines. This provides a scientific, quantitative and traceable basis for subsequent transmission and distribution price calculation, and effectively avoids the deviation caused by traditional reduction based solely on book data or experience.

[0060] It should be noted that the adjustment factor can be limited to two reasonably set thresholds. An adjustment factor less than 1 is used to amplify the basic reduction rate when the transmission line has a high historical fault frequency or a long average repair time, reflecting the impact of decreased asset availability. An adjustment factor greater than 1 is used to attenuate the basic reduction rate when the fault frequency is low or the repair time is short, reflecting the mitigating effect of reduction correction due to higher line reliability. The direction of change of the adjustment factor is inversely related to the reliability level of the transmission line; that is, the adjustment factor decreases when the line fault risk increases and increases when the line's operational stability improves.

[0061] S7, input the effective asset value and the effective asset reduction ratio into the transmission and distribution price calculation model to determine the transmission and distribution price of the transmission line, specifically:

[0062] The effective asset value of each transmission line is adjusted according to the effective asset reduction ratio to obtain the final effective asset value. This final effective asset value comprehensively reflects the impact of the line's environmental adaptability, operational participation, and historical fault risks on asset value, thereby achieving differentiated adjustments to the asset value of different lines.

[0063] The final effective asset value is input into a preset transmission and distribution price calculation model. The calculation model performs calculations based on a preset price calculation formula, converting the final effective asset value of each line into a corresponding transmission and distribution price. The resulting transmission and distribution price can scientifically reflect the actual asset value of transmission lines under the influence of factors such as comprehensive environmental conditions, equipment health status, and network operation participation, providing a quantitative basis for price determination by transmission companies.

[0064] It should be noted that the preset electricity price calculation formula can be a cost recovery model based on asset contribution adjustment, an asset depreciation correction model based on lifetime depreciation rate, or a revenue balance model based on discount factor. The aforementioned electricity price calculation formula couples the final effective asset value of transmission lines with their operational contribution to the transmission network, environmental adaptability, and lifetime depreciation effect. This allows the determined transmission and distribution price to comprehensively reflect the asset consumption level and service contribution of the lines under different operating and environmental conditions, thereby achieving a quantitative correlation between the asset value of transmission lines and the price determination results.

[0065] Example 2: As Figure 1 As shown in Example 1, the transmission and distribution price calculation method based on effective asset assessment described in this application further includes correcting the preliminary comprehensive index according to a preset critical threshold to obtain an environmental adaptability coefficient, specifically:

[0066] Two critical threshold levels are set: a first critical threshold and a second critical threshold, with the first critical threshold being lower than the second critical threshold. These are used to distinguish between high and low ranges for the environmental adaptability index. After obtaining the preliminary comprehensive index for each transmission line, it is compared with the aforementioned critical thresholds to determine the adaptability range of the line. If the preliminary comprehensive index is lower than the first critical threshold, it is identified as a low-adaptability line, and an accelerated decline correction rule is applied to adjust it, causing the environmental adaptability coefficient to decrease rapidly relative to the preliminary comprehensive index, thereby strengthening the conversion of lines with potential environmental risks. If the preliminary comprehensive index is higher than the second critical threshold, it is identified as a high-adaptability line, and a gain saturation correction rule is applied to adjust it, causing the environmental adaptability coefficient to gradually stabilize in the high-value region, thereby avoiding overestimation of high-adaptability lines. When the preliminary comprehensive index is between the first and second critical thresholds, the preliminary comprehensive index is directly used as the environmental adaptability coefficient to ensure the continuity and rationality of the environmental adaptability coefficient.

[0067] It should be noted that, after correction processing, this application can provide independent correction logic in the low and high value ranges, enabling the environmental adaptability coefficient to more accurately reflect the nonlinear interaction between the external environment and material aging, and to reflect the true health status of transmission lines under long-term operation. The final environmental adaptability coefficient can be directly used for subsequent effective asset quantification matrix construction and effective asset scoring calculation, thereby providing a more accurate, quantifiable, and traceable basis for transmission and distribution price determination. This embodiment closely integrates actual operating conditions and environmental characteristics in its technical logic, significantly improving the refinement and scientific rigor of environmental adaptability evaluation compared to the processing methods of single linear or static comprehensive indices in existing technologies.

[0068] The foregoing has shown and described the basic principles, main features, and advantages of this application. Those skilled in the art should understand that this application is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of this application. Various changes and modifications can be made to this application without departing from the spirit and scope thereof, and all such changes and modifications fall within the scope of this application as claimed. The scope of protection of this application is defined by the appended claims and their equivalents.

Claims

1. A method for calculating transmission and distribution tariffs based on valid asset verification, characterized in that, The method includes: (1) Obtain environmental data, equipment health data, and operational data of the transmission lines: The environmental data includes long-term climate parameters, frequency of extreme weather, and regional corrosion index; the equipment health data includes corrosion rate, insulation aging degree, and temperature cycling effect. (2) Based on the environmental data and equipment health data, calculate the environmental adaptability coefficient of the transmission line, which is used to quantify the lifespan and health status of the transmission line under different environmental conditions: Calculate the environmental adaptability coefficient of transmission lines, including: The climate impact index is calculated based on long-term climate parameters and the frequency of extreme weather events. The climate impact index is used to characterize the long-term impact of the external environment on the structural fatigue and conductor performance degradation of transmission lines. The material degradation index is calculated based on the regional corrosion index and corrosion rate. The material degradation index is used to characterize the material loss rate of transmission lines under specific geographical and chemical environments. The insulation stability index is calculated based on the degree of insulation aging and the effect of temperature cycling. The insulation stability index is used to characterize the ability of the line insulation layer to retain its dielectric properties. The climate impact index, material degradation index, and insulation stability index are calculated according to a preset nonlinear fusion relationship to obtain the environmental adaptability coefficient. The nonlinear fusion relationship is used to characterize the interactive cumulative effect between environmental conditions and the material aging process. (3) Based on the operational data, calculate the spatial redundancy parameter of the transmission line, which is used to characterize the actual operational participation of the transmission line in the transmission network: Obtaining transmission line network information, including the rated capacity of the transmission lines, and operational data including actual line load, operation scheduling records, and reserve capacity; calculating the spatial redundancy parameters of the transmission lines based on the operational data, including: Based on the actual load of the lines according to the operational data, determine the long-term average load rate and utilization duration of each transmission line; When the long-term average load rate of the transmission line is lower than the load rate threshold and the utilization time is lower than the utilization time threshold within the preset evaluation period, the transmission line will be marked as a low utilization line. The operation and scheduling records of the low-utilization line are analyzed. When the ratio of the reserve capacity to the rated capacity of the low-utilization line exceeds the reserve capacity threshold, the low-utilization line is determined to be a redundant line. The ratio of the spare capacity to the rated capacity of the redundant lines is defined as the redundancy spare capacity ratio. The redundancy utilization rate index is obtained based on the actual load and operation scheduling records of the redundant lines. The spatial redundancy parameters of the transmission line are calculated based on the redundancy reserve capacity ratio and redundancy utilization rate. (4) The environmental adaptability coefficient and the spatial redundancy parameter are fused in a multi-dimensional manner according to the correspondence of the transmission lines to form an effective asset quantification matrix of the transmission lines; (5) The effective asset quantification matrix is ​​mapped to the effective asset score and effective asset value of each transmission line, wherein the effective asset score is used to identify high-value lines, low-utilization lines and lines with potential environmental risks; (6) Compare the effective asset score with the preset trigger threshold to obtain the comparison result, and calculate the effective asset reduction ratio of each transmission line based on the comparison result; (7) Input the effective asset value and the effective asset reduction ratio into the transmission and distribution price calculation model to determine the transmission and distribution price of the transmission line.

2. The method according to claim 1, characterized in that, The step of calculating the environmental adaptability coefficient by applying a preset nonlinear fusion relationship to the climate impact index, material degradation index, and insulation stability index includes: The climate impact index, material degradation index, and insulation stability index of each transmission line were normalized to obtain comparable index values. The comparable index values ​​are weighted and superimposed according to a nonlinear relationship to obtain a preliminary comprehensive index for each transmission line; The preliminary comprehensive index is corrected based on the preset critical threshold to obtain the environmental adaptability coefficient.

3. The method according to claim 2, characterized in that, The step of correcting the preliminary comprehensive index according to a preset critical threshold to obtain the environmental adaptability coefficient includes: A critical threshold is set, which includes a first critical threshold and a second critical threshold, wherein the first critical threshold is less than the second critical threshold. The preliminary comprehensive index is compared with the critical threshold to obtain the comparison result; The corresponding correction rule is selected based on the comparison results. The correction rule includes a first correction rule and a second correction rule, specifically as follows: If the preliminary comprehensive index is lower than the first critical threshold, the preliminary comprehensive index is adjusted using a first correction rule to obtain an environmental adaptability coefficient. The first correction rule is configured to use an exponential decay function or a power law function to make the output environmental adaptability coefficient show an accelerated downward trend relative to the preliminary comprehensive index. If the preliminary comprehensive index is higher than the second critical threshold, the preliminary comprehensive index is adjusted using the second correction rule to obtain the environmental adaptability coefficient; the second correction rule is configured to make the output environmental adaptability coefficient show a gain saturation trend relative to the preliminary comprehensive index through a logarithmic function or a linear saturation function. If the preliminary comprehensive index is between the first critical threshold and the second critical threshold, then the preliminary comprehensive index is directly used as the environmental adaptability coefficient.

4. The method according to claim 1, characterized in that, The step of multi-dimensionally fusing the environmental adaptability coefficient and the spatial redundancy parameter according to the correspondence of transmission lines to form an effective asset quantification matrix for transmission lines includes: Construct a two-dimensional decision coordinate system, defining the horizontal axis as the environmental adaptability coefficient and the vertical axis as the spatial redundancy parameter; Each transmission line is mapped to a coordinate point in the two-dimensional decision coordinate system based on its corresponding environmental adaptability coefficient and spatial redundancy parameter. Using the region where the coordinate point is located in the two-dimensional decision coordinate system as the index, a preset asset validity mapping table is queried to obtain the valid asset value corresponding to the coordinate point. The preset asset validity mapping table is used to store the correspondence between the coordinate point and the valid asset value. The valid asset value is calculated by the historical environmental adaptability coefficient and the historical spatial redundancy parameter. The effective asset values ​​of all transmission lines are aggregated to form an effective asset quantification matrix, which is used to reflect the effective asset value of each transmission line.

5. The method according to claim 4, characterized in that, The process of mapping the effective asset quantification matrix to the effective asset score and effective asset value for each transmission line includes: Feature extraction is performed on the effective asset quantification matrix to obtain the effective asset value and the effective asset vector corresponding to the effective asset value; Calculate the covariance matrix of the effective asset quantification matrix, and perform eigenvalue decomposition on the covariance matrix to obtain multiple eigenvectors and the unique eigenvalues ​​corresponding to each eigenvector; The eigenvector corresponding to the largest eigenvalue is selected as the principal eigenvector, which represents the feature combination pattern that contributes the most to the effective assets of the transmission line. The effective asset vector of each transmission line is projected onto the principal feature vector to obtain the effective asset score of each transmission line.

6. The method according to claim 1, characterized in that, The step of comparing the effective asset score with a preset trigger threshold to obtain a comparison result, and calculating the effective asset reduction ratio for each transmission line based on the comparison result, includes: A trigger threshold is set, wherein the trigger threshold includes a first threshold and a second threshold, and the first threshold is less than the second threshold; The effective asset score of each transmission line is compared with the trigger threshold to obtain the comparison result. Based on the comparison result, the basic reduction rate is determined, including: If the effective asset score is lower than the first threshold, the basic reduction rate is the first preset value; If the effective asset score is between the first threshold and the second threshold, the base reduction rate is the second preset value; If the effective asset score is higher than the second threshold, the base discount rate is zero; The adjustment factor for adjusting the base reduction rate is calculated based on the acquired historical fault data of the transmission lines. Multiplying the base reduction rate by the adjustment factor yields the effective asset reduction ratio for each transmission line.

7. The method according to claim 6, characterized in that, The adjustment factor calculated based on the acquired historical fault data of transmission lines for adjusting the base reduction rate includes: Obtain historical fault data of transmission lines, including average fault frequency and average repair time; The frequency impact value is calculated based on the fault frequency, and the frequency impact value is exponentially correlated with the fault frequency; The duration impact value is calculated based on the average repair time, and the duration impact value is logarithmically correlated with the repair time. An adjustment factor is calculated based on the frequency impact value and the duration impact value. The adjustment factor is used to correct the base reduction rate to reflect the effective asset reduction rate of the transmission line under historical fault risk.

8. The method according to claim 6, characterized in that, The step of inputting the effective asset value and the effective asset reduction ratio into the transmission and distribution price calculation model to determine the transmission and distribution price of the transmission line includes: The effective asset value of each transmission line is adjusted according to the effective asset reduction ratio to obtain the final effective asset value; The final effective asset value is input into the transmission and distribution price calculation model, so that the transmission and distribution price calculation model performs calculations based on the final effective asset value and the preset electricity price calculation formula, and outputs the transmission and distribution price corresponding to each transmission line. The transmission and distribution price is used to reflect the asset value of the transmission line under the comprehensive evaluation of environmental conditions, health status and operational participation.

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