CN113780775B - Power grid theoretical line loss calculation result evaluation method and system - Google Patents
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Abstract
The invention discloses a method and a system for evaluating a power grid theoretical line loss calculation result. The evaluation method of the invention comprises the following steps: acquiring parameter data related to the power grid and the theoretical line loss in real time, preprocessing the parameter data, and establishing a typical parameter database from the preprocessed data; calculating theoretical line loss by using a self-adaptive enhancement algorithm to obtain a theoretical line loss calculation result; and constructing a theoretical line loss analysis evaluation model, checking the theoretical line loss calculation result, and if an unreasonable result appears, performing reverse checking and locating an unreasonable cause. The invention improves the calculation precision of the theoretical line loss, eliminates the problem of lack of practicability and operability, and greatly reduces the limitation thereof.
Description
Technical Field
The invention relates to the technical field of power distribution network line loss, in particular to a power grid theoretical line loss calculation result evaluation method and system.
Background
The line loss is the electric energy loss generated in the electric energy transmission process, the line loss rate is an index for measuring the running management level of the power grid, and the line loss rate is also an important reference basis in the planning and construction of the intelligent power grid. The theoretical line loss calculation can comprehensively reflect the planning design level, the power grid construction level, the technical progress level and the production operation and operation management level of the power grid, and is also an important technical management means of power supply enterprises. Compared with other works, the line loss management has certain specificity, the data acquisition and information maintenance requirements in the maintenance period are continuous and uninterrupted, the workload is uniformly distributed on the whole time axis, and meanwhile, the calculation period with larger workload of loss calculation and result analysis exists, namely, the remarkable large-scale burst calculation amount exists, and particularly, the large-scale power grid performance is more outstanding. In the analysis of the line loss statistics, the power supply enterprises are often influenced by factors such as large fluctuation of the line loss rate, more abnormal constant values of the line loss rate and the like, and reasonable loss reduction measures cannot be provided only by analyzing and counting the line loss rate. The theoretical line loss calculation of the power grid is one of important technical means adopted by power grid companies for analysis and decision making of the power system, and various indexes of the power grid are analyzed through the theoretical line loss calculation, so that the current problems of the power grid, such as the defects of grid structure and system operation of the power grid, are found, and a theoretical basis is provided for energy conservation and loss reduction of the power grid.
The existing theoretical line loss computing system often adopts independent design, independent construction and self-maintenance modes, and has the problems of long construction period, high construction cost, incomplete maintenance, inflexible expansion and the like; meanwhile, the calculation results of a plurality of branch departments are difficult to collect, and timely and comprehensive analysis cannot be performed. In addition, the existing modes such as offline calculation and the like influence the accuracy of theoretical line loss calculation to a certain extent, and along with the development of line loss refinement work, theoretical line loss level evaluation in different areas has great guiding significance on the level of theoretical line loss in each solution area and the difference between the theoretical line loss level evaluation and the theoretical line loss level evaluation in each solution area for line loss practitioners, and the evaluation of line loss work is facilitated for management departments.
Conventionally, the conventional evaluation mode of the theoretical line loss level of the regions is only based on experience and lack of scientific judgment basis, the problem of lack of practicability and operability in evaluating the theoretical line loss level of each region exists, and the conventional evaluation method still has certain limitations.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the defects in the prior art, and provide a method and a system for evaluating the calculation result of the theoretical line loss of a power grid, so as to improve the calculation precision of the theoretical line loss, eliminate the problem of lack of practicality and operability and reduce the limitation of the theoretical line loss.
In order to solve the technical problems, the invention adopts the following technical scheme: a power grid theoretical line loss calculation result evaluation method comprises the following steps:
acquiring parameter data related to the power grid and the theoretical line loss in real time, preprocessing the parameter data, and establishing a typical parameter database from the preprocessed data;
Calculating theoretical line loss by using a self-adaptive enhancement algorithm to obtain a theoretical line loss calculation result;
and constructing a theoretical line loss analysis evaluation model, checking the theoretical line loss calculation result, and if an unreasonable result appears, performing reverse checking and locating an unreasonable cause.
Further, the parameter data includes current, voltage, power path, resistivity, line length, resistance, total line resistance, feeder power radius, operating voltage, loss constant, and load profile.
Further, the step of preprocessing the parameter data includes:
Carrying out feature construction, data grading and data quantization on the data;
carrying out data statistics on the quantized data, and merging the data into a unified data storage;
And detecting and removing samples which still possibly have abnormality in the stored data by adopting an outlier sample detection strategy based on clustering.
Further, the adaptive enhancement algorithm includes:
Defining the current and the voltage of a three-phase line of a power grid as I V、UV respectively;
Load current unbalance of the three-phase line Load voltage imbalance/>The method comprises the following steps:
Wherein, Respectively represent phase current and phase voltage,/>Is 1, 2 or 3,/>
The total loss of the power grid is as follows:
Δp＝K(UV-U)2
Wherein L represents a total loss value, M represents a power grid structural coefficient, R represents a resistor, deltap represents single-phase corona loss power, t represents a temperature value, n represents the number of power grid wires, K represents a correlation coefficient, U represents an initial voltage, and the values of the initial voltage and the power grid wire are scalar.
Further, the step of constructing the theoretical line loss analysis and evaluation model comprises the following steps:
acquiring rule data information and establishing a data acquisition rule;
Traversing the calculated values of the history theory line loss and the data in the typical parameter database, analyzing the characteristic data of the data information according to a decision tree, and acquiring the characteristic data for 2 times according to the data acquisition rule to obtain the proportion of the positive examples of the characteristic data;
Calculating a positive proportion ratio of 2 times of characteristic data acquisition;
If the proportion ratio of the positive examples is larger than a preset threshold, the obtained characteristic data are invalid, and the historical theoretical line loss calculation value and the data in the typical parameter database are traversed again;
if the proportion ratio of the positive examples is smaller than or equal to a preset threshold value, the obtained characteristic data are valid;
And constructing a theoretical line loss analysis evaluation model according to the effective characteristic data and the least square method.
Further, the theoretical line loss analysis and evaluation model is as follows:
Wherein L, B represents a theoretical line loss and an actual line loss, J (L, B) represents an output value, J represents a constant coefficient, m represents an iteration coefficient, ω represents a weight coefficient, s i represents a corresponding characteristic data value of i lines, B j represents an actual line loss coefficient corresponding to J lines, μ represents a characteristic dimension, and R represents a real number.
Still further, checking the theoretical line loss calculation result, and judging whether the checking result is reasonable or not includes:
Obtaining an output value of the theoretical line loss analysis evaluation model, and judging whether a checking result is reasonable or not based on an optimal solution of the output value:
And when tau epsilon [0,0.135], judging that the checking result is reasonable, and outputting the theoretical line loss.
Further, the step of reverse checking includes:
And analyzing the theoretical line loss output result, comparing the real-time theoretical line loss with the historical theoretical line loss value and the actual line loss value, and outputting the positioning result when the positioning comparison error is larger than a preset value, wherein the unreasonable cause is obtained by expert database data.
The invention adopts another technical scheme that: a power grid theoretical line loss calculation result evaluation system, comprising:
Typical parameter database building unit: acquiring parameter data related to the power grid and the theoretical line loss in real time, preprocessing the parameter data, and establishing a typical parameter database from the preprocessed data;
theoretical line loss result calculation unit: calculating theoretical line loss by using a self-adaptive enhancement algorithm to obtain a theoretical line loss calculation result;
Theoretical line loss calculation result checking unit: and constructing a theoretical line loss analysis evaluation model, checking the theoretical line loss calculation result, and if an unreasonable result appears, performing reverse checking and locating an unreasonable cause.
Further, the step of constructing the theoretical line loss analysis and evaluation model comprises the following steps:
acquiring rule data information and establishing a data acquisition rule;
Traversing the calculated values of the history theory line loss and the data in the typical parameter database, analyzing the characteristic data of the data information according to a decision tree, and acquiring the characteristic data for 2 times according to the data acquisition rule to obtain the proportion of the positive examples of the characteristic data;
Calculating a positive proportion ratio of 2 times of characteristic data acquisition;
If the proportion ratio of the positive examples is larger than a preset threshold, the obtained characteristic data are invalid, and the historical theoretical line loss calculation value and the data in the typical parameter database are traversed again;
if the proportion ratio of the positive examples is smaller than or equal to a preset threshold value, the obtained characteristic data are valid;
constructing a theoretical line loss analysis evaluation model according to the effective characteristic data and a least square method;
The theoretical line loss analysis and evaluation model is as follows:
Wherein L, B represents a theoretical line loss and an actual line loss, J (L, B) represents an output value, J represents a constant coefficient, m represents an iteration coefficient, ω represents a weight coefficient, s i represents a corresponding characteristic data value of i lines, B j represents an actual line loss coefficient corresponding to J lines, μ represents a characteristic dimension, and R represents a real number.
The invention has the beneficial effects that: according to the method, by designing an intelligent theoretical line loss calculation and evaluation method, the theoretical line loss calculation precision is improved, the problem of lack of practicality and operability is solved, and the limitation of the theoretical line loss is greatly reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
Fig. 1 is a basic flow diagram of an evaluation method for a theoretical line loss calculation result of a power grid according to an embodiment of the present invention.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Example 1
Referring to fig. 1, for one embodiment of the present invention, a method for evaluating a calculation result of a theoretical line loss of a power grid is provided, which includes the following steps:
S1: acquiring parameter data related to the power grid and the theoretical line loss in real time, preprocessing the parameter data, and establishing a typical parameter database from the preprocessed data; it should be noted that:
The parameter data includes current, voltage, power path, resistivity, line length, resistance, total line resistance, feeder power radius, operating voltage, loss constant, and load profile.
Specifically, the preprocessing parameter data includes:
Cleaning the blank value, format content, logic error and non-required data;
Carrying out feature construction, data grading and data quantization on the data;
carrying out data statistics on the quantized data, and merging the data into a unified data storage;
And detecting and rejecting samples which can still possibly have abnormality in the stored data samples by adopting an outlier sample detection strategy based on clustering.
S2: calculating theoretical line loss by using a self-adaptive enhancement algorithm to obtain a theoretical line loss calculation result; it should be noted that:
The adaptive enhancement algorithm includes:
Defining the current and the voltage of a three-phase line of a power grid as I V、UV respectively;
Load current imbalance of three-phase line Load voltage imbalance/>The method comprises the following steps:
Wherein, Respectively represent phase current and phase voltage,/>
The total loss of the power grid is as follows:
Δp＝K(UV-U)2
Wherein L represents a total loss value, M represents a power grid structural coefficient, R represents a resistor, deltap represents single-phase corona loss power, t represents a temperature value, n represents the number of power grid wires, K represents a correlation coefficient, U represents an initial voltage, and the values of the initial voltage and the power grid wire are scalar.
S3: constructing a theoretical line loss analysis evaluation model, checking a theoretical line loss calculation result, and if an unreasonable result appears, performing reverse check to locate an unreasonable cause; it should be noted that:
the construction of the theoretical line loss analysis and evaluation model comprises the following steps:
acquiring rule data information and establishing a data acquisition rule;
Traversing the data in the history theory line loss calculation value and typical parameter database, analyzing the characteristic data of the data information according to the decision tree, and acquiring the characteristic data for 2 times according to the data acquisition rule to obtain the positive proportion of the characteristic data;
Calculating a positive proportion ratio of 2 times of characteristic data acquisition;
If the proportion ratio of the positive examples is larger than a preset threshold, the obtained characteristic data are invalid, and the data in the history theoretical line loss calculation value and the typical parameter database are traversed again;
If the ratio of the positive examples is smaller than or equal to a preset threshold value, the obtained characteristic data are valid;
And constructing a theoretical line loss analysis evaluation model according to the effective characteristic data and the least square method.
The theoretical line loss analysis and evaluation model is as follows:
Wherein L, B represents a theoretical line loss and an actual line loss, J (L, B) represents an output value, J represents a constant coefficient, n represents an iteration coefficient, ω represents a weight coefficient, s i represents a corresponding characteristic data value of i lines, B j represents an actual line loss coefficient corresponding to J lines, μ represents a characteristic dimension, and R represents a real number.
The method for checking the theoretical line loss calculation result comprises the following steps of:
Obtaining an output value of a theoretical line loss analysis evaluation model, and judging whether a checking result is reasonable or not based on an optimal solution of the output value:
and when tau epsilon [0,0.135], judging that the checking result is reasonable, and outputting the theoretical line loss.
More specifically, the step of reverse checking includes: and analyzing the theoretical line loss output result, comparing the real-time theoretical line loss with the historical theoretical line loss value and the actual line loss value, and outputting a positioning result when the positioning comparison error is larger than a preset value, wherein the unreasonable cause is obtained by expert database data.
Example 2
The embodiment provides a power grid theoretical line loss calculation result evaluation system, which comprises:
Typical parameter database building unit: acquiring parameter data related to the power grid and the theoretical line loss in real time, preprocessing the parameter data, and establishing a typical parameter database from the preprocessed data;
theoretical line loss result calculation unit: calculating theoretical line loss by using a self-adaptive enhancement algorithm to obtain a theoretical line loss calculation result;
Theoretical line loss calculation result checking unit: and constructing a theoretical line loss analysis evaluation model, checking the theoretical line loss calculation result, and if an unreasonable result appears, performing reverse checking and locating an unreasonable cause.
In a typical parameter database building block, the parameter data includes current, voltage, power path, resistivity, line length, resistance, total line resistance, feeder power radius, operating voltage, loss constant, and load curve.
The preprocessing parameter data includes:
Cleaning the blank value, format content, logic error and non-required data;
Carrying out feature construction, data grading and data quantization on the data;
carrying out data statistics on the quantized data, and merging the data into a unified data storage;
And detecting and rejecting samples which can still possibly have abnormality in the stored data samples by adopting an outlier sample detection strategy based on clustering.
In the theoretical line loss result calculation unit, the adaptive enhancement algorithm includes:
Defining the current and the voltage of a three-phase line of a power grid as I V、UV respectively;
Load current imbalance of three-phase line Load voltage imbalance/>The method comprises the following steps:
Wherein, Respectively represent phase current and phase voltage,/>
The total loss of the power grid is as follows:
Δp＝K(UV-U)2
Wherein L represents a total loss value, M represents a power grid structural coefficient, R represents a resistor, deltap represents single-phase corona loss power, t represents a temperature value, n represents the number of power grid wires, K represents a correlation coefficient, U represents an initial voltage, and the values of the initial voltage and the power grid wire are scalar.
In the theoretical line loss calculation result checking unit, the construction of the theoretical line loss analysis and evaluation model comprises the following steps:
acquiring rule data information and establishing a data acquisition rule;
Traversing the data in the history theory line loss calculation value and typical parameter database, analyzing the characteristic data of the data information according to the decision tree, and acquiring the characteristic data for 2 times according to the data acquisition rule to obtain the positive proportion of the characteristic data;
Calculating a positive proportion ratio of 2 times of characteristic data acquisition;
If the proportion ratio of the positive examples is larger than a preset threshold, the obtained characteristic data are invalid, and the data in the history theoretical line loss calculation value and the typical parameter database are traversed again;
If the ratio of the positive examples is smaller than or equal to a preset threshold value, the obtained characteristic data are valid;
And constructing a theoretical line loss analysis evaluation model according to the effective characteristic data and the least square method.
The theoretical line loss analysis and evaluation model is as follows:
Wherein L, B represents a theoretical line loss and an actual line loss, J (L, B) represents an output value, J represents a constant coefficient, n represents an iteration coefficient, ω represents a weight coefficient, s i represents a corresponding characteristic data value of i lines, B j represents an actual line loss coefficient corresponding to J lines, μ represents a characteristic dimension, and R represents a real number.
Checking the theoretical line loss calculation result, and judging whether the checking result is reasonable or not includes: obtaining an output value of a theoretical line loss analysis evaluation model, and judging whether a checking result is reasonable or not based on an optimal solution of the output value:
and when tau epsilon [0,0.135], judging that the checking result is reasonable, and outputting the theoretical line loss.
The step of reverse checking includes: and analyzing the theoretical line loss output result, comparing the real-time theoretical line loss with the historical theoretical line loss value and the actual line loss value, and outputting a positioning result when the positioning comparison error is larger than a preset value, wherein the unreasonable cause is obtained by expert database data.
Application example
The application example provides a verification test of a power grid theoretical line loss calculation result evaluation method, and in order to verify and explain the technical effects adopted in the method, the application example adopts a traditional technical scheme to carry out a comparison test with the method, and the test results are compared by a scientific demonstration means so as to verify the true effects of the method.
The traditional technical scheme is as follows: the theoretical line loss calculation accuracy is low, the practicality and the operability are low, and the limitation is high. In order to verify that the method has higher calculation accuracy compared with the traditional method. In the application example, the traditional line loss level evaluation method based on the characteristic difference of the power grid and the method of the invention are adopted to respectively measure and compare the theoretical line loss rate of the simulated power grid in real time.
Test environment: the method comprises the steps of selecting 110kv, 220kv, 10kv and 500kv power grid lines for measurement, wherein the lead structure is 4-LGL-300 split leads, the diameter is 24.26mm, the split distance is 450mm, three lines are horizontally arranged, the inter-phase distance is 13m, the circuit length is 300km, and the line parameter table is as follows:
table 1: line parameter table
| Line model | Reactance omega/km | Susceptance s/km | Wire radius cm | Geometric mean distance cm | Resistance omega/km |
| 4*LGL-300 | 0.281 | 3.956*10-6 | 1.213 | 1638 | 0.02625 |
The method and the device respectively utilize the traditional method and the method of the invention, start automatic test equipment and utilize MATLB software programming to realize simulation tests of the two methods, and obtain simulation data according to experimental results. The results are shown in the following table.
Table 2: comparison table of experimental results
The experimental result shows that the method has better calculation accuracy compared with the traditional method, thereby embodying the effectiveness of the method.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted without departing from the spirit and scope of the technical solution of the present invention, which is intended to be covered in the scope of the claims of the present invention.
Claims (6)
1. The method for evaluating the calculation result of the theoretical line loss of the power grid is characterized by comprising the following steps of:
acquiring parameter data related to the power grid and the theoretical line loss in real time, preprocessing the parameter data, and establishing a typical parameter database from the preprocessed data;
Calculating theoretical line loss by using a self-adaptive enhancement algorithm to obtain a theoretical line loss calculation result;
constructing a theoretical line loss analysis evaluation model, checking the theoretical line loss calculation result, and if an unreasonable result appears, performing reverse check to locate an unreasonable cause;
the adaptive enhancement algorithm includes:
Defining the current and the voltage of a three-phase line of a power grid as I V、UV respectively;
Load current unbalance of the three-phase line Load voltage imbalance/>The method comprises the following steps:
Wherein, Respectively represent phase current and phase voltage,/>Is 1, 2 or 3,/>
The total loss of the power grid is as follows:
Δp＝K(UV-U)2
Wherein L represents a total loss value, M represents a power grid structural coefficient, R represents a resistor, deltap represents single-phase corona loss power, t represents a temperature value, n represents the number of wires of the power grid, K represents a correlation coefficient, U represents an initial voltage, and the values of the initial voltage and the power grid are scalar;
The step of constructing the theoretical line loss analysis and evaluation model comprises the following steps:
acquiring rule data information and establishing a data acquisition rule;
Traversing the calculated values of the history theory line loss and the data in the typical parameter database, analyzing the characteristic data of the data information according to a decision tree, and acquiring the characteristic data for 2 times according to the data acquisition rule to obtain the proportion of the positive examples of the characteristic data;
Calculating a positive proportion ratio of 2 times of characteristic data acquisition;
If the proportion ratio of the positive examples is larger than a preset threshold, the obtained characteristic data are invalid, and the historical theoretical line loss calculation value and the data in the typical parameter database are traversed again;
if the proportion ratio of the positive examples is smaller than or equal to a preset threshold value, the obtained characteristic data are valid;
Constructing a theoretical line loss analysis evaluation model according to the effective characteristic data and a least square method;
The theoretical line loss analysis and evaluation model is as follows:
Wherein L, B represents a theoretical line loss and an actual line loss, J (L, B) represents an output value, J represents a constant coefficient, m represents an iteration coefficient, ω represents a weight coefficient, s i represents a corresponding characteristic data value of i lines, B j represents an actual line loss coefficient corresponding to J lines, μ represents a characteristic dimension, and R represents a real number.
2. The method of evaluating a theoretical line loss calculation result of a power grid according to claim 1, wherein the parameter data includes current, voltage, power supply path, resistivity, line length, resistance, total line resistance, feeder power supply radius, operating voltage, loss constant, and load curve.
3. The method for evaluating the result of calculation of the theoretical line loss of a power grid according to claim 1, wherein the step of preprocessing the parameter data includes:
Carrying out feature construction, data grading and data quantization on the data;
carrying out data statistics on the quantized data, and merging the data into a unified data storage;
And detecting and removing samples which still possibly have abnormality in the stored data by adopting an outlier sample detection strategy based on clustering.
4. The method for evaluating a theoretical line loss calculation result of a power grid according to claim 1, wherein the step of checking the theoretical line loss calculation result, and the step of judging whether the check result is reasonable includes:
Obtaining an output value of the theoretical line loss analysis evaluation model, and judging whether a checking result is reasonable or not based on an optimal solution of the output value:
and when tau epsilon [0,0.135], judging that the checking result is reasonable, and outputting the theoretical line loss.
5. The method for evaluating the theoretical line loss calculation result of a power grid according to any one of claims 1 to 4, wherein the step of reversely checking includes:
And analyzing the theoretical line loss output result, comparing the real-time theoretical line loss with the historical theoretical line loss value and the actual line loss value, and outputting a positioning result when the positioning comparison error is larger than a preset value, wherein the unreasonable cause is obtained by expert database data.
6. The utility model provides a power grid theoretical line loss calculation result evaluation system which characterized in that includes:
Typical parameter database building unit: acquiring parameter data related to the power grid and the theoretical line loss in real time, preprocessing the parameter data, and establishing a typical parameter database from the preprocessed data;
theoretical line loss result calculation unit: calculating theoretical line loss by using a self-adaptive enhancement algorithm to obtain a theoretical line loss calculation result;
Theoretical line loss calculation result checking unit: constructing a theoretical line loss analysis evaluation model, checking the theoretical line loss calculation result, and if an unreasonable result appears, performing reverse check to locate an unreasonable cause;
in the theoretical line loss result calculation unit, the adaptive enhancement algorithm includes:
Defining the current and the voltage of a three-phase line of a power grid as I V、UV respectively;
Load current imbalance of three-phase line Load voltage imbalance/>The method comprises the following steps:
Wherein, Respectively represent phase current and phase voltage,/>
The total loss of the power grid is as follows:
Δp＝K(UV-U)2
Wherein L represents a total loss value, M represents a power grid structural coefficient, R represents a resistor, deltap represents single-phase corona loss power, t represents a temperature value, n represents the number of wires of the power grid, K represents a correlation coefficient, U represents an initial voltage, and the values of the initial voltage and the power grid are scalar;
in the theoretical line loss calculation result checking unit, the step of constructing the theoretical line loss analysis and evaluation model comprises the following steps:
acquiring rule data information and establishing a data acquisition rule;
Traversing the calculated values of the history theory line loss and the data in the typical parameter database, analyzing the characteristic data of the data information according to a decision tree, and acquiring the characteristic data for 2 times according to the data acquisition rule to obtain the proportion of the positive examples of the characteristic data;
Calculating a positive proportion ratio of 2 times of characteristic data acquisition;
If the proportion ratio of the positive examples is larger than a preset threshold, the obtained characteristic data are invalid, and the historical theoretical line loss calculation value and the data in the typical parameter database are traversed again;
if the proportion ratio of the positive examples is smaller than or equal to a preset threshold value, the obtained characteristic data are valid;
Constructing a theoretical line loss analysis evaluation model according to the effective characteristic data and a least square method;
The theoretical line loss analysis and evaluation model is as follows:
Wherein L, B represents a theoretical line loss and an actual line loss, J (L, B) represents an output value, J represents a constant coefficient, m represents an iteration coefficient, ω represents a weight coefficient, s i represents a corresponding characteristic data value of i lines, B j represents an actual line loss coefficient corresponding to J lines, μ represents a characteristic dimension, and R represents a real number.
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