CN117932276B - Energy-saving loss-reducing adaptability evaluation method for medium-voltage distribution network line - Google Patents
Energy-saving loss-reducing adaptability evaluation method for medium-voltage distribution network line Download PDFInfo
- Publication number
- CN117932276B CN117932276B CN202410323292.6A CN202410323292A CN117932276B CN 117932276 B CN117932276 B CN 117932276B CN 202410323292 A CN202410323292 A CN 202410323292A CN 117932276 B CN117932276 B CN 117932276B
- Authority
- CN
- China
- Prior art keywords
- wind speed
- value
- loss reduction
- temperature
- fluctuation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 11
- 230000009467 reduction Effects 0.000 claims abstract description 197
- 238000000034 method Methods 0.000 claims abstract description 40
- 230000008859 change Effects 0.000 claims description 154
- 238000012545 processing Methods 0.000 claims description 48
- 230000007613 environmental effect Effects 0.000 claims description 44
- 238000012512 characterization method Methods 0.000 claims description 40
- 230000002159 abnormal effect Effects 0.000 claims description 27
- 238000001514 detection method Methods 0.000 claims description 18
- 230000003044 adaptive effect Effects 0.000 claims description 9
- 238000004458 analytical method Methods 0.000 claims description 6
- 238000004134 energy conservation Methods 0.000 claims description 6
- 238000003672 processing method Methods 0.000 claims description 2
- 230000000694 effects Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000000556 factor analysis Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Biology (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Physics (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Economics (AREA)
- Computational Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Operations Research (AREA)
- Probability & Statistics with Applications (AREA)
- Strategic Management (AREA)
- Algebra (AREA)
- Marketing (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Human Resources & Organizations (AREA)
- General Health & Medical Sciences (AREA)
- Water Supply & Treatment (AREA)
- Public Health (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention belongs to the technical field of line loss reduction evaluation, and provides a method for evaluating the energy-saving loss reduction adaptability of a medium-voltage distribution network line, which comprises the following steps: acquiring loss reduction data of loss reduction lines of a power distribution network under a plurality of scenes, recording scene environment data when the loss reduction data are acquired, classifying different scenes based on the scene environment data, respectively comparing and analyzing the classified scenes to obtain environment fluctuation deviation parameters, selecting a target scene according to the environment fluctuation deviation parameters, analyzing the loss reduction amount of the lines of the target scene to obtain loss reduction adaptability parameters, comparing the loss reduction adaptability parameters with loss reduction adaptability parameter thresholds, and evaluating the loss reduction adaptability of the lines according to comparison results.
Description
Technical Field
The invention belongs to the technical field of line loss reduction evaluation, and particularly relates to an energy-saving loss reduction adaptability evaluation method for a medium-voltage distribution network line.
Background
With the increasing demand of electric power, the problems of energy conservation and loss reduction of the power distribution network are increasingly prominent. The medium-voltage distribution network is used as an important link of power transmission, and the energy-saving and loss-reducing effects directly influence the operation efficiency and economic benefits of the whole power system. However, the evaluation of the energy-saving and loss-reducing effect is affected by environmental conditions, and how to accurately evaluate the adaptability of the energy-saving and loss-reducing effect to the medium-voltage distribution network becomes a problem to be solved urgently in the technical field of current power engineering.
One chinese patent application publication No. CN107016485A discloses a power line energy-saving and loss-reducing adaptability evaluation method, which includes: and (3) correcting and calculating the upper limit of the line capacity, the maintenance cost basic value after line faults, the fault probability basic value, the land solicitation level, the cable use length basic value and the line distance population concentration region coefficient by adopting the BP neural network to form a two-dimensional method for evaluating the energy-saving adaptability of the power line from the angle of energy saving and loss reduction. The invention improves the calculation precision of the period cost and the loss, evaluates the adaptability of the line from the economic and energy-saving two-dimensional standard, and provides an energy-saving and loss-reducing adaptability evaluation basis for the existing line and line planning and selection.
In the prior art, the economic index and the energy-saving index are adopted as the energy-saving and loss-reducing adaptability assessment means of the circuit, but the economic index and the energy-saving index evaluate the loss-reducing effect of the circuit from a macroscopic or long-term perspective, the circuit performance under specific environmental conditions may not be directly reflected, and the formulated loss-reducing strategy for the circuit cannot be provided for the specific environmental conditions.
Therefore, the invention provides an energy-saving and loss-reducing adaptability evaluation method for the medium-voltage distribution network line.
Disclosure of Invention
In order to overcome the deficiencies of the prior art, at least one technical problem presented in the background art is solved.
The technical scheme adopted for solving the technical problems is as follows: a medium-voltage distribution network line energy-saving loss-reducing adaptability evaluation method comprises the following steps:
Step one: acquiring loss reduction data of loss reduction lines of the distribution network under a plurality of scenes, and recording scene environment data when the loss reduction data are acquired, wherein the loss reduction data comprise loss reduction amounts, and the scene environment data comprise temperature values and wind speed values;
Step two: based on analysis of scene environment data under different scenes, obtaining an environment condition fluctuation value SE, classifying the different scenes according to the environment condition fluctuation value SE, wherein the classified scenes comprise a high-degree fluctuation scene and a low-degree fluctuation scene;
step three: respectively comparing and analyzing the classified scenes to obtain environment fluctuation deviation parameters ZXd, and selecting a target scene according to the environment fluctuation deviation parameters ZXd, wherein the target scene comprises a maximum fluctuation scene and a minimum fluctuation scene;
step four: the line loss reduction amount corresponding to the minimum fluctuation degree scene and the maximum fluctuation scene is compared and analyzed to obtain loss reduction adaptability parameters VH, the loss reduction adaptability parameters VH are compared with loss reduction adaptability parameter threshold VK, and the line loss reduction adaptability is evaluated according to the comparison result;
If the loss reduction adaptability parameter VH is more than or equal to the loss reduction adaptability parameter threshold VK, the loss reduction adaptability of the circuit is high;
If the loss reduction adaptive parameter VH < the loss reduction adaptive parameter threshold VK, the loss reduction adaptability of the line is low.
The invention further adopts the technical scheme that: the environmental condition fluctuation value SE is obtained by the following steps:
Respectively marking the temperature value and the wind speed value in the environmental data in different X-Y two-dimensional coordinate systems, and connecting the marked points to obtain a temperature change curve and a wind speed change curve in the detection duration;
obtaining an average wind speed value and an average temperature value in the detection duration according to the maximum temperature value, the minimum temperature value, the maximum wind speed value and the minimum wind speed value in the detection duration;
Based on the average wind speed value and the average temperature value, a temperature datum line and a wind speed datum line are made in an X-Y coordinate system;
carrying out ratio processing on the area enclosed between the wind speed datum line and the wind speed change curve and the area enclosed between the wind speed datum line and the X axis to obtain a wind speed fluctuation parameter Sg;
carrying out ratio processing on the area enclosed between the temperature datum line and the temperature change curve and the area enclosed between the temperature datum line and the X axis to obtain a temperature fluctuation parameter Sd;
by the formula: by the formula: and obtaining an environmental condition fluctuation value SE, wherein a1 and a2 are preset proportionality coefficients, a1 takes a value 1.021, and a2 takes a value of 1.154.
The invention further adopts the technical scheme that: comparing the obtained environmental condition fluctuation value SE with an environmental condition fluctuation threshold value:
presetting an environmental condition fluctuation threshold as SW;
If the environmental condition fluctuation value SE is more than or equal to the environmental condition fluctuation threshold value SW, the environmental condition fluctuation degree in the scene is larger;
if the environmental condition fluctuation value SE is smaller than the environmental condition fluctuation threshold value SW, the environmental condition fluctuation degree in the scene is smaller;
Based on the scene with larger fluctuation degree of the environmental condition, marking the scene as a scene with high fluctuation degree;
scenes that fluctuate less based on environmental conditions are marked as low-level fluctuating scenes.
The invention further adopts the technical scheme that: based on analysis of the high-degree fluctuation scene and the low-degree fluctuation scene, obtaining a temperature change mean difference duty ratio and a wind speed change mean difference duty ratio, and marking the temperature change mean difference duty ratio as ZJC and ZJY respectively;
by the formula: by the formula: obtaining an environment fluctuation deviation parameter ZXd, wherein s1 and s2 are preset proportionality coefficients, the value of s1 is 1.256, and the value of s2 is 1.231;
and selecting a high-degree fluctuation scene corresponding to the maximum environment fluctuation deviation parameter from the high-degree fluctuation scene and the low-degree fluctuation scene as the maximum fluctuation degree scene, and selecting a low-degree fluctuation scene corresponding to the maximum environment fluctuation deviation parameter as the minimum fluctuation degree scene.
The invention further adopts the technical scheme that: the temperature change mean value difference duty ratio ZJC and the air speed change mean value difference duty ratio ZJY are obtained in the following modes:
Based on a wind speed change curve corresponding to the high-degree fluctuation scene, counting the number of wave crests and wave troughs of the wind speed change curve corresponding to the high-degree fluctuation scene and obtaining wind speed values corresponding to the wave crests and the wave troughs;
based on the temperature change curve corresponding to the high-degree fluctuation scene, counting the number of wave crests and wave troughs of the temperature change curve corresponding to the high-degree fluctuation scene and obtaining temperature values corresponding to the wave crests and the wave troughs;
Summing the corresponding wind speed values of all wave crests and wave troughs respectively to obtain a wind speed total value;
summing the number of wave crests and wave troughs respectively, and summing the number of wave crests and wave troughs;
carrying out ratio processing on the sum of the total wind speed value and the number of wave crests and wave troughs to obtain a first wind speed change mean value;
Summing the corresponding temperature values of all wave crests and wave troughs respectively to obtain a temperature total value;
Performing ratio processing on the sum of the total temperature value and the number of wave crests and wave troughs to obtain a first temperature change average value;
analyzing based on a wind speed change curve and a temperature change curve corresponding to a low-degree fluctuation scene to obtain a second wind speed change average value and a second temperature change average value, wherein the obtaining method of the second wind speed change average value and the second temperature change average value is the same as the obtaining method of the first wind speed change average value and the first temperature change average value;
performing difference processing on the first temperature change mean value and the second temperature change mean value, and taking an absolute value of the difference value to obtain a temperature change mean value difference;
Performing difference processing on the first wind speed variation mean value and the second wind speed variation mean value, and taking an absolute value of the difference value to obtain a wind speed variation mean value difference;
carrying out ratio processing on the temperature change mean value difference and the second temperature change mean value to obtain a temperature change mean value difference duty cycle ZJC;
and carrying out ratio processing on the wind speed change mean value difference and the second wind speed change mean value to obtain the wind speed change mean value difference duty ratio ZJY.
The invention further adopts the technical scheme that: comparing and analyzing the line loss reduction amount corresponding to the minimum fluctuation degree scene and the maximum fluctuation scene to obtain loss reduction adaptability parameters VH;
In a scene of maximum fluctuation degree, dividing the detection time length of a loss reduction line into a plurality of continuous and equal first time subunits, obtaining the maximum loss reduction amount and the minimum loss reduction amount in each first time subunit, summing the maximum loss reduction amount and the minimum loss reduction amount, and obtaining an average loss reduction amount in each first time subunit;
In a scene of minimum fluctuation degree, dividing the detection duration of the loss reduction line into a plurality of continuous and equal second time subunits, obtaining the maximum loss reduction amount and the minimum loss reduction amount in each second time subunit, summing the maximum loss reduction amount and the minimum loss reduction amount, and taking an average value to obtain the average loss reduction amount in each second time subunit;
comparing all first time subunits with all second time subunits correspondingly:
If the average loss reduction amount in the first time subunit is not equal to the average loss reduction amount in the second time subunit, marking the first time subunit as an abnormal time subunit, and marking the second time subunit corresponding to the first time subunit as a comparison time subunit, wherein each abnormal time subunit corresponds to one comparison time subunit;
If the average loss reduction amount in the first time subunit is equal to the average loss reduction amount in the second time subunit, marking the first time subunit as a normal time subunit;
Counting the number of abnormal time subunits, carrying out ratio processing on the number of the abnormal time subunits and the number of the second time subunits to obtain the number ratio of the abnormal time subunits, and marking the number ratio as Vg;
Respectively carrying out difference processing on the loss reduction amount in each abnormal time subunit and the loss reduction amount in the corresponding contrast time subunit, summing the obtained difference values after taking absolute values to obtain average values, obtaining loss reduction amount deviation values in the abnormal time subunits, summing the loss reduction amounts in all second time subunits to obtain the total loss reduction amount of the second time subunits, carrying out ratio processing on the loss reduction amount deviation values in the abnormal time subunits and the total loss reduction amount of the second time subunits, obtaining the loss reduction deviation duty ratio of the abnormal time subunits, and marking the loss reduction deviation duty ratio as Vt;
By the formula: Obtaining a loss-reducing adaptive parameter VH, wherein/> And/>Are all preset proportional coefficients, wherein/(The value is 1.02,/>The value was 1.69.
The invention further adopts the technical scheme that: the method also comprises the following steps:
Step five: based on low loss reduction adaptability of the line, analyzing a temperature change curve, a wind speed change curve and a loss reduction change curve corresponding to a maximum fluctuation degree scene and a minimum fluctuation degree scene, acquiring a temperature influence parameter FG and a wind speed influence parameter GU, and correspondingly comparing the temperature influence parameter FG and the wind speed influence parameter GU with a temperature influence parameter threshold and a wind speed influence parameter threshold respectively;
If the temperature influence parameter FG is more than or equal to FD and the wind speed influence parameter GU is less than GJ, the influence of the temperature on the line loss reduction adaptability is shown, and the influence of the wind speed on the line loss reduction adaptability is not shown;
if the temperature influence parameter FG is less than FD and the wind speed influence parameter GU is more than or equal to GJ, the influence of the temperature on the line loss reduction adaptability is not shown, and the influence of the wind speed on the line loss reduction adaptability is shown;
If the temperature influence parameter FG is more than or equal to FD and the wind speed influence parameter GU is more than or equal to GJ, the influence of temperature and wind speed on the line loss reduction adaptability is shown;
Step six: based on the influence of temperature and wind speed on the line loss reduction adaptability, a temperature influence duty ratio characterization value XJ and a wind speed influence duty ratio characterization value XM are obtained, compared, and the main degrees of the temperature influence and the wind speed influence are judged according to the comparison result.
The invention further adopts the technical scheme that: the temperature influence duty ratio characterization value XJ and the wind speed influence duty ratio characterization value XM are obtained in the following ways:
Dividing the horizontal lengths of a temperature change curve, a wind speed change curve and a loss reduction change curve corresponding to the maximum fluctuation degree scene and the minimum fluctuation degree scene respectively into a plurality of continuous and equal-length subunits, and numbering the continuous and equal-length subunits, wherein the number and the number of the length subunits corresponding to the temperature change curve, the wind speed change curve and the loss reduction change curve are the same;
Comparing the temperature change curves corresponding to the maximum fluctuation degree scene and the minimum fluctuation degree scene respectively, cutting off the non-coincident part curves, and marking the reserved part curves as first reserved part curves;
according to the horizontal position and the horizontal length of the first reserved part curve, intercepting the wind speed change curves corresponding to the maximum fluctuation degree scene and the minimum fluctuation degree scene respectively at the same horizontal position and the same horizontal length, comparing the intercepted part curves again, intercepting the overlapped part curves, reserving the non-overlapped part curves, and marking the non-overlapped part curves as second reserved part curves;
According to the horizontal position and the horizontal length of the second reserved part curve, intercepting the loss reduction variable curves corresponding to the scene with the maximum fluctuation degree and the scene with the minimum fluctuation degree respectively at the same horizontal position and the same horizontal length, comparing the intercepted part curves again, intercepting the overlapped part curves, reserving the non-overlapped part curves, and marking the non-overlapped part curves as third reserved part curves;
Acquiring a length subunit number corresponding to the second reserved part curve and a length subunit number corresponding to the third reserved part curve, comparing the length subunit numbers, and counting the number of the length subunits with the same number;
Counting the sum of the number of the length subunits corresponding to the second reserved part curve and the number of the length subunits corresponding to the third reserved part curve;
carrying out ratio processing on the sum of the number of subunits with the same number and the number of length subunits corresponding to the second reserved part curve and the number of length subunits corresponding to the third reserved part curve to obtain a wind speed influence parameter GU;
the acquisition method of the temperature influence parameter FG is the same as the acquisition method of the wind speed influence parameter GU;
the method comprises the steps of firstly cutting off a temperature change curve, then cutting off and comparing the wind speed change curve, finally cutting off and comparing the loss reduction change curve, and obtaining a temperature influence parameter FG, namely firstly cutting off the wind speed change curve, then cutting off and comparing the temperature change curve, and finally cutting off and comparing the loss reduction change curve, wherein the cutting off, cutting off and comparing processing methods are the same.
The invention further adopts the technical scheme that: the temperature influence duty ratio characterization value XJ and the wind speed influence duty ratio characterization value XM are obtained in the following manner:
Carrying out difference processing on the temperature influence parameter FG and the temperature influence parameter threshold FD, taking an absolute value of the difference value to obtain a temperature influence difference value, and carrying out ratio processing on the temperature influence difference value and the temperature influence parameter threshold to obtain a temperature influence duty ratio characterization value XJ;
And carrying out difference processing on the wind speed influence parameter GU and the wind speed influence parameter threshold GJ, taking an absolute value of the difference value to obtain a wind speed influence difference value, and carrying out ratio processing on the wind speed influence difference value and the wind speed influence parameter threshold to obtain a wind speed influence duty ratio representation value XM.
The invention further adopts the technical scheme that: comparing the temperature influence duty cycle characterization value XJ with the wind speed influence duty cycle characterization value XM:
if the temperature influence duty ratio characterization value XJ is larger than the wind speed influence duty ratio characterization value XM, the main degree of the temperature influence is larger than the wind speed influence;
if the temperature influence duty ratio characterization value xj=the wind speed influence duty ratio characterization value XM, the main degree of the temperature influence is the same as the wind speed influence;
If the temperature influence duty ratio characterization value XJ is smaller than the wind speed influence duty ratio characterization value XM, the main degree of the temperature influence is smaller than the wind speed influence.
The beneficial effects of the invention are as follows:
1. According to the medium-voltage distribution network line energy-saving loss-reduction adaptability assessment method, loss-reduction data of a loss-reduction line of a distribution network under a plurality of scenes are collected, scene environment data when the loss-reduction data are collected are recorded, wherein the loss-reduction data comprise loss-reduction amounts, and the scene environment data comprise temperature values and wind speed values; based on analysis of scene environment data under different scenes, obtaining an environment condition fluctuation value SE, classifying the different scenes according to the environment condition fluctuation value SE, wherein the classified scenes comprise a high-degree fluctuation scene and a low-degree fluctuation scene; respectively comparing and analyzing the classified scenes to obtain environment fluctuation deviation parameters ZXd, and selecting a target scene according to the environment fluctuation deviation parameters ZXd, wherein the target scene comprises a maximum fluctuation scene and a minimum fluctuation scene; the method comprises the steps of comparing and analyzing line loss reduction amounts corresponding to a minimum fluctuation degree scene and a maximum fluctuation scene to obtain loss reduction adaptability parameters VH, comparing the loss reduction adaptability parameters VH with loss reduction adaptability parameter threshold VK, and evaluating the line loss reduction adaptability according to comparison results.
2. According to the medium-voltage distribution network line energy-saving loss-reducing adaptability assessment method, based on low loss-reducing adaptability of the line, the corresponding temperature change curve, wind speed change curve and loss-reducing quantity change curve under the maximum fluctuation degree scene and the minimum fluctuation degree scene are analyzed, the temperature influence parameter FG and the wind speed influence parameter GU are obtained, the temperature influence parameter FG and the wind speed influence parameter GU are respectively compared with the temperature influence parameter threshold and the wind speed influence parameter threshold correspondingly, the loss-reducing adaptability influence factors are analyzed, the line loss-reducing adaptability influence factors are analyzed, the loss-reducing adaptability influence factors are determined, and theoretical method basis can be provided for the loss-reducing adaptability influence factor analysis of the line in complex environment.
3. According to the medium-voltage distribution network line energy-saving loss-reducing adaptability assessment method, the temperature influence duty ratio representation value and the wind speed influence duty ratio representation value are obtained based on the influence of temperature and wind speed on line loss-reducing adaptability, and are compared, and the main degrees of the temperature influence and the wind speed influence are judged according to the comparison result.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a flowchart of a method for evaluating the adaptability of energy conservation and loss reduction of a medium-voltage distribution network line according to an embodiment of the invention;
fig. 2 is a flowchart of a first method for evaluating the adaptability of energy conservation and loss reduction of a line of an alternative medium-voltage distribution network according to an embodiment of the present invention;
fig. 3 is a flowchart of a second method for evaluating the adaptability of energy conservation and loss reduction of a line of an alternative medium-voltage distribution network according to an embodiment of the present invention.
Detailed Description
The invention is further described in connection with the following detailed description in order to make the technical means, the creation characteristics, the achievement of the purpose and the effect of the invention easy to understand.
Example 1
As shown in fig. 1, the method for evaluating the energy-saving and loss-reducing adaptability of the medium-voltage distribution network line according to the embodiment of the invention comprises the following steps:
Step one: acquiring loss reduction data of loss reduction lines of the distribution network under a plurality of scenes, and recording scene environment data when the loss reduction data are acquired, wherein the loss reduction data comprise loss reduction amounts, and the scene environment data comprise temperature values and wind speed values;
In some embodiments, detecting the input and the output of the loss reduction circuit through an electric energy meter, and setting the detection duration to obtain the loss reduction quantity of the loss reduction circuit;
in some embodiments, detecting the scene environment through a sensor, and setting the detection duration to obtain a temperature value, a humidity value and a wind speed value;
Step two: based on analysis of scene environment data under different scenes, obtaining environment condition fluctuation values, classifying the different scenes according to the environment condition fluctuation values, wherein the classified scenes comprise high-degree fluctuation scenes and low-degree fluctuation scenes;
Specifically, the temperature value and the wind speed value in the environmental data are respectively marked in different X-Y two-dimensional coordinate systems, and marked points are connected to obtain a temperature change curve and a wind speed change curve in the detection duration;
Obtaining a maximum temperature value, a minimum temperature value, a maximum wind speed value and a minimum wind speed value in the detection duration, summing the maximum wind speed value and the minimum wind speed value to obtain an average wind speed value in the detection duration, and summing the maximum temperature value and the minimum temperature value to obtain an average temperature value in the detection duration;
Marking the average wind speed value and the average temperature value as a wind speed reference value and a temperature reference value in a coordinate system of a corresponding temperature change curve and a corresponding wind speed change curve respectively, and respectively making a straight line parallel to an X axis through the temperature reference value and the wind speed reference value, and marking the straight line as a temperature datum line and a wind speed datum line;
The horizontal lengths of the temperature datum line and the wind speed datum line are respectively equal to the horizontal lengths of the temperature change curve and the wind speed change curve, wherein the horizontal lengths of the wind speed change curve and the temperature change curve are also equal correspondingly;
Measuring the area enclosed between the wind speed datum line and the wind speed change curve and the area enclosed between the temperature datum line and the temperature change curve respectively;
Measuring the area enclosed between the wind speed datum line and the X axis and the area enclosed between the temperature datum line and the X axis respectively;
carrying out ratio processing on the area enclosed between the wind speed datum line and the wind speed change curve and the area enclosed between the wind speed datum line and the X axis to obtain a wind speed fluctuation parameter;
performing ratio processing on the area surrounded by the temperature datum line and the temperature change curve and the area surrounded by the temperature datum line and the X axis to obtain a temperature fluctuation parameter;
marking the wind speed fluctuation parameter as Sg, and marking the temperature fluctuation parameter as Sd;
By the formula: obtaining an environmental condition fluctuation value SE, wherein a1 and a2 are preset proportionality coefficients, a1 takes a value 1.021, and a2 takes a value of 1.154;
comparing the obtained environmental condition fluctuation value SE with an environmental condition fluctuation threshold value, wherein the specific comparison process is as follows:
presetting an environmental condition fluctuation threshold as SW;
If the environmental condition fluctuation value SE is more than or equal to the environmental condition fluctuation threshold value SW, the environmental condition fluctuation degree in the scene is larger;
if the environmental condition fluctuation value SE is smaller than the environmental condition fluctuation threshold value SW, the environmental condition fluctuation degree in the scene is smaller;
Based on the scene with larger fluctuation degree of the environmental condition, marking the scene as a scene with high fluctuation degree;
based on the scene with smaller fluctuation degree of the environmental condition, marking the scene as a low-degree fluctuation scene;
step three: respectively comparing and analyzing the classified scenes to obtain environment fluctuation deviation parameters, and selecting a target scene according to the environment fluctuation deviation parameters, wherein the target scene comprises a maximum fluctuation scene and a minimum fluctuation scene;
Specifically, based on a wind speed change curve corresponding to a high-degree fluctuation scene, counting the number of wave crests and wave troughs of the wind speed change curve corresponding to the high-degree fluctuation scene and obtaining wind speed values corresponding to the wave crests and the wave troughs;
based on the temperature change curve corresponding to the high-degree fluctuation scene, counting the number of wave crests and wave troughs of the temperature change curve corresponding to the high-degree fluctuation scene and obtaining temperature values corresponding to the wave crests and the wave troughs;
Summing the corresponding wind speed values of all wave crests and wave troughs respectively to obtain a wind speed total value;
summing the number of wave crests and wave troughs respectively, and summing the number of wave crests and wave troughs;
carrying out ratio processing on the sum of the total wind speed value and the number of wave crests and wave troughs to obtain a first wind speed change mean value;
Summing the corresponding temperature values of all wave crests and wave troughs respectively to obtain a temperature total value;
Performing ratio processing on the sum of the total temperature value and the number of wave crests and wave troughs to obtain a first temperature change average value;
Analyzing based on a wind speed change curve and a temperature change curve corresponding to a low-degree fluctuation scene to obtain a second wind speed change mean value and a second temperature change mean value, wherein the obtaining method of the second wind speed change mean value and the second temperature change mean value is the same as the obtaining method of the first wind speed change mean value and the first temperature change mean value, and the detailed description is omitted herein;
performing difference processing on the first temperature change mean value and the second temperature change mean value, and taking an absolute value of the difference value to obtain a temperature change mean value difference;
Performing difference processing on the first wind speed variation mean value and the second wind speed variation mean value, and taking an absolute value of the difference value to obtain a wind speed variation mean value difference;
carrying out ratio processing on the temperature change mean value difference and the second temperature change mean value to obtain a temperature change mean value difference duty ratio;
Performing ratio processing on the wind speed variation mean value difference and the second wind speed variation mean value to obtain a wind speed variation mean value difference duty ratio;
the obtained temperature change mean difference ratio and the wind speed change mean difference ratio are respectively marked as ZJC and ZJY, and the formula is adopted: obtaining an environment fluctuation deviation parameter ZXd, wherein s1 and s2 are preset proportionality coefficients, the value of s1 is 1.256, and the value of s2 is 1.231;
Selecting a high-degree fluctuation scene corresponding to the maximum environment fluctuation deviation parameter from the high-degree fluctuation scene and the low-degree fluctuation scene as the maximum fluctuation degree scene, and selecting a low-degree fluctuation scene corresponding to the maximum environment fluctuation deviation parameter as the minimum fluctuation degree scene;
Step four: comparing and analyzing the line loss reduction amount corresponding to the minimum fluctuation degree scene and the maximum fluctuation scene to obtain loss reduction adaptability parameters, comparing the loss reduction adaptability parameters with loss reduction adaptability parameter thresholds, and evaluating the line loss reduction adaptability according to comparison results;
specifically, in a scene of maximum fluctuation degree, dividing the detection duration of a loss reduction line into a plurality of continuous and equal first time subunits, acquiring the maximum loss reduction amount and the minimum loss reduction amount in each first time subunit, summing the maximum loss reduction amount and the minimum loss reduction amount, and taking an average value to obtain the average loss reduction amount in each first time subunit;
In a scene of minimum fluctuation degree, dividing the detection duration of the loss reduction line into a plurality of continuous and equal second time subunits, obtaining the maximum loss reduction amount and the minimum loss reduction amount in each second time subunit, summing the maximum loss reduction amount and the minimum loss reduction amount, and taking an average value to obtain the average loss reduction amount in each second time subunit;
it should be noted that the number and time of the second time subunits are the same as the number and time of the first time subunits;
comparing all first time subunits with all second time subunits correspondingly:
If the average loss reduction amount in the first time subunit is not equal to the average loss reduction amount in the second time subunit, marking the first time subunit as an abnormal time subunit, and marking the second time subunit corresponding to the first time subunit as a comparison time subunit, wherein each abnormal time subunit corresponds to one comparison time subunit;
If the average loss reduction amount in the first time subunit is equal to the average loss reduction amount in the second time subunit, marking the first time subunit as a normal time subunit;
Counting the number of abnormal time subunits, carrying out ratio processing on the number of the abnormal time subunits and the number of the second time subunits to obtain the number ratio of the abnormal time subunits, and marking the number ratio as Vg;
Respectively carrying out difference processing on the loss reduction amount in each abnormal time subunit and the loss reduction amount in the corresponding contrast time subunit, summing the obtained difference values after taking absolute values to obtain average values, obtaining loss reduction amount deviation values in the abnormal time subunits, summing the loss reduction amounts in all second time subunits to obtain the total loss reduction amount of the second time subunits, carrying out ratio processing on the loss reduction amount deviation values in the abnormal time subunits and the total loss reduction amount of the second time subunits, obtaining the loss reduction deviation duty ratio of the abnormal time subunits, and marking the loss reduction deviation duty ratio as Vt;
By the formula: Obtaining a loss-reducing adaptive parameter VH, wherein/> And/>Are all preset proportional coefficients, wherein/(The value is 1.02,/>The value is 1.69;
Comparing the obtained loss reduction adaptability parameter VH with a loss reduction adaptability parameter threshold, and evaluating the line loss reduction adaptability according to a comparison result, wherein the specific comparison process is as follows:
presetting a loss reduction adaptability parameter threshold as VK;
If the loss reduction adaptability parameter VH is more than or equal to the loss reduction adaptability parameter threshold VK, the loss reduction adaptability of the circuit is high;
If the loss reduction adaptive parameter VH < the loss reduction adaptive parameter threshold VK, the loss reduction adaptability of the line is low.
Example 2
As shown in fig. 2 and fig. 3, based on the embodiment 1, the method for evaluating the adaptability of energy conservation and loss reduction of the medium-voltage distribution network line according to the embodiment of the invention further includes the following steps:
Step five: based on low loss reduction adaptability of the circuit, analyzing a temperature change curve, a wind speed change curve and a loss reduction change curve corresponding to a maximum fluctuation degree scene and a minimum fluctuation degree scene, acquiring a temperature influence parameter FG and a wind speed influence parameter GU, correspondingly comparing the temperature influence parameter FG and the wind speed influence parameter GU with a temperature influence parameter threshold and a wind speed influence parameter threshold, and analyzing influence factors of the loss reduction adaptability;
Specifically, the horizontal lengths of a temperature change curve, a wind speed change curve and a loss reduction change curve corresponding to the maximum fluctuation degree scene and the minimum fluctuation degree scene are divided into a plurality of continuous and equal length subunits, and the continuous and equal length subunits are numbered, wherein the number and the number of the length subunits corresponding to the temperature change curve, the wind speed change curve and the loss reduction change curve are the same, for example, the number of the length subunits corresponding to the temperature change curve is 100, the numbers are 1,2, 3, 4, 5, 4 and 6..100, the number of the length subunits of the wind speed change curve is 100, the numbers are 1,2, 3, 4, 5 and 6..100, and the loss reduction change curve is the same as the number and the number of the length subunits corresponding to the wind speed change curve and the temperature change curve;
Comparing the temperature change curves corresponding to the maximum fluctuation degree scene and the minimum fluctuation degree scene respectively, cutting off the non-coincident part curves, and marking the reserved part curves as first reserved part curves;
according to the horizontal position and the horizontal length of the first reserved part curve, intercepting the wind speed change curves corresponding to the maximum fluctuation degree scene and the minimum fluctuation degree scene respectively at the same horizontal position and the same horizontal length, comparing the intercepted part curves again, intercepting the overlapped part curves, reserving the non-overlapped part curves, and marking the non-overlapped part curves as second reserved part curves;
According to the horizontal position and the horizontal length of the second reserved part curve, intercepting the loss reduction variable curves corresponding to the scene with the maximum fluctuation degree and the scene with the minimum fluctuation degree respectively at the same horizontal position and the same horizontal length, comparing the intercepted part curves again, intercepting the overlapped part curves, reserving the non-overlapped part curves, and marking the non-overlapped part curves as third reserved part curves;
Acquiring a length subunit number corresponding to the second reserved part curve and a length subunit number corresponding to the third reserved part curve, comparing the length subunit numbers, and counting the number of the length subunits with the same number;
Counting the sum of the number of the length subunits corresponding to the second reserved part curve and the number of the length subunits corresponding to the third reserved part curve;
carrying out ratio processing on the sum of the number of subunits with the same number and the number of length subunits corresponding to the second reserved part curve and the number of length subunits corresponding to the third reserved part curve to obtain a wind speed influence parameter GU;
The method is the same as the method for obtaining the wind speed influence parameter GU, and the temperature influence parameter FG is obtained;
The method comprises the steps of firstly intercepting a temperature change curve, then intercepting and comparing the wind speed change curve, finally intercepting and comparing a loss reduction change curve, and firstly releasing the comparison of the wind speed change curve, then intercepting and comparing the temperature change curve, and finally intercepting and comparing the loss reduction change curve, wherein the intercepting, intercepting and comparing treatment methods are the same;
the temperature influence parameter FG and the wind speed influence parameter GU are correspondingly compared with corresponding temperature influence parameter thresholds and wind speed influence parameter thresholds respectively, and the specific comparison process is as follows:
the preset temperature influence parameter threshold value is FD, and the preset wind speed influence parameter threshold value is GJ;
If the temperature influence parameter FG is more than or equal to FD and the wind speed influence parameter GU is less than GJ, the influence of the temperature on the line loss reduction adaptability is shown, and the influence of the wind speed on the line loss reduction adaptability is not shown;
if the temperature influence parameter FG is less than FD and the wind speed influence parameter GU is more than or equal to GJ, the influence of the temperature on the line loss reduction adaptability is not shown, and the influence of the wind speed on the line loss reduction adaptability is shown;
If the temperature influence parameter FG is more than or equal to FD and the wind speed influence parameter GU is more than or equal to GJ, the influence of temperature and wind speed on the line loss reduction adaptability is shown;
Step six: based on the influence of temperature and wind speed on the line loss reduction adaptability, acquiring a temperature influence duty ratio representation value and a wind speed influence duty ratio representation value, comparing the temperature influence duty ratio representation value and the wind speed influence duty ratio representation value, and judging the main degree of the temperature influence and the wind speed influence according to a comparison result;
specifically, performing difference processing on the temperature influence parameter FG and the temperature influence parameter threshold FD, taking an absolute value of the difference value to obtain a temperature influence difference value, and performing ratio processing on the temperature influence difference value and the temperature influence parameter threshold to obtain a temperature influence duty ratio characterization value XJ;
performing difference processing on the wind speed influence parameter GU and a wind speed influence parameter threshold GJ, taking an absolute value of the difference value to obtain a wind speed influence difference value, and performing ratio processing on the wind speed influence difference value and the wind speed influence parameter threshold to obtain a wind speed influence duty ratio characterization value XM;
Comparing the temperature influence duty cycle characterization value XJ with the wind speed influence duty cycle characterization value XM:
if the temperature influence duty ratio characterization value XJ is larger than the wind speed influence duty ratio characterization value XM, the main degree of the temperature influence is larger than the wind speed influence;
if the temperature influence duty ratio characterization value xj=the wind speed influence duty ratio characterization value XM, the main degree of the temperature influence is the same as the wind speed influence;
If the temperature influence duty ratio characterization value XJ is smaller than the wind speed influence duty ratio characterization value XM, the main degree of the temperature influence is smaller than the wind speed influence.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (5)
1. A medium-voltage distribution network line energy-saving loss-reducing adaptability evaluation method is characterized by comprising the following steps of: comprising the following steps:
Step one: acquiring loss reduction data of loss reduction lines of the distribution network under a plurality of scenes, and recording scene environment data when the loss reduction data are acquired, wherein the loss reduction data comprise loss reduction amounts, and the scene environment data comprise temperature values and wind speed values;
Step two: based on analysis of scene environment data under different scenes, obtaining an environment condition fluctuation value SE, classifying the different scenes according to the environment condition fluctuation value SE, wherein the classified scenes comprise a high-degree fluctuation scene and a low-degree fluctuation scene;
the environmental condition fluctuation value SE is obtained by the following steps:
Respectively marking the temperature value and the wind speed value in the environmental data in different X-Y two-dimensional coordinate systems, and connecting the marked points to obtain a temperature change curve and a wind speed change curve in the detection duration;
obtaining an average wind speed value and an average temperature value in the detection duration according to the maximum temperature value, the minimum temperature value, the maximum wind speed value and the minimum wind speed value in the detection duration;
Based on the average wind speed value and the average temperature value, a temperature datum line and a wind speed datum line are made in an X-Y coordinate system;
carrying out ratio processing on the area enclosed between the wind speed datum line and the wind speed change curve and the area enclosed between the wind speed datum line and the X axis to obtain a wind speed fluctuation parameter Sg;
carrying out ratio processing on the area enclosed between the temperature datum line and the temperature change curve and the area enclosed between the temperature datum line and the X axis to obtain a temperature fluctuation parameter Sd;
By the formula: by the formula: obtaining an environmental condition fluctuation value SE, wherein a1 and a2 are preset proportionality coefficients, a1 takes a value 1.021, and a2 takes a value of 1.154;
Comparing the obtained environmental condition fluctuation value SE with an environmental condition fluctuation threshold value:
presetting an environmental condition fluctuation threshold as SW;
If the environmental condition fluctuation value SE is more than or equal to the environmental condition fluctuation threshold value SW, the environmental condition fluctuation degree in the scene is larger;
if the environmental condition fluctuation value SE is smaller than the environmental condition fluctuation threshold value SW, the environmental condition fluctuation degree in the scene is smaller;
Based on the scene with larger fluctuation degree of the environmental condition, marking the scene as a scene with high fluctuation degree;
based on the scene with smaller fluctuation degree of the environmental condition, marking the scene as a low-degree fluctuation scene;
step three: respectively comparing and analyzing the classified scenes to obtain environment fluctuation deviation parameters ZXd, and selecting a target scene according to the environment fluctuation deviation parameters ZXd, wherein the target scene comprises a maximum fluctuation scene and a minimum fluctuation scene;
Based on analysis of the high-degree fluctuation scene and the low-degree fluctuation scene, obtaining a temperature change mean difference duty ratio and a wind speed change mean difference duty ratio, and marking the temperature change mean difference duty ratio as ZJC and ZJY respectively;
By the formula: by the formula: obtaining an environment fluctuation deviation parameter ZXd, wherein s1 and s2 are preset proportionality coefficients, the value of s1 is 1.256, and the value of s2 is 1.231;
Selecting a high-degree fluctuation scene corresponding to the maximum environment fluctuation deviation parameter from the high-degree fluctuation scene and the low-degree fluctuation scene as the maximum fluctuation degree scene, and selecting a low-degree fluctuation scene corresponding to the maximum environment fluctuation deviation parameter as the minimum fluctuation degree scene;
the temperature change mean value difference duty ratio ZJC and the air speed change mean value difference duty ratio ZJY are obtained in the following modes:
Based on a wind speed change curve corresponding to the high-degree fluctuation scene, counting the number of wave crests and wave troughs of the wind speed change curve corresponding to the high-degree fluctuation scene and obtaining wind speed values corresponding to the wave crests and the wave troughs;
based on the temperature change curve corresponding to the high-degree fluctuation scene, counting the number of wave crests and wave troughs of the temperature change curve corresponding to the high-degree fluctuation scene and obtaining temperature values corresponding to the wave crests and the wave troughs;
Summing the corresponding wind speed values of all wave crests and wave troughs respectively to obtain a wind speed total value;
summing the number of wave crests and wave troughs respectively, and summing the number of wave crests and wave troughs;
carrying out ratio processing on the sum of the total wind speed value and the number of wave crests and wave troughs to obtain a first wind speed change mean value;
Summing the corresponding temperature values of all wave crests and wave troughs respectively to obtain a temperature total value;
Performing ratio processing on the sum of the total temperature value and the number of wave crests and wave troughs to obtain a first temperature change average value;
analyzing based on a wind speed change curve and a temperature change curve corresponding to a low-degree fluctuation scene to obtain a second wind speed change average value and a second temperature change average value, wherein the obtaining method of the second wind speed change average value and the second temperature change average value is the same as the obtaining method of the first wind speed change average value and the first temperature change average value;
performing difference processing on the first temperature change mean value and the second temperature change mean value, and taking an absolute value of the difference value to obtain a temperature change mean value difference;
Performing difference processing on the first wind speed variation mean value and the second wind speed variation mean value, and taking an absolute value of the difference value to obtain a wind speed variation mean value difference;
carrying out ratio processing on the temperature change mean value difference and the second temperature change mean value to obtain a temperature change mean value difference duty cycle ZJC;
Performing ratio processing on the wind speed variation mean value difference and the second wind speed variation mean value to obtain a wind speed variation mean value difference duty ratio ZJY;
step four: the line loss reduction amount corresponding to the minimum fluctuation degree scene and the maximum fluctuation scene is compared and analyzed to obtain loss reduction adaptability parameters VH, the loss reduction adaptability parameters VH are compared with loss reduction adaptability parameter threshold VK, and the line loss reduction adaptability is evaluated according to the comparison result;
In a scene of maximum fluctuation degree, dividing the detection time length of a loss reduction line into a plurality of continuous and equal first time subunits, obtaining the maximum loss reduction amount and the minimum loss reduction amount in each first time subunit, summing the maximum loss reduction amount and the minimum loss reduction amount, and obtaining an average loss reduction amount in each first time subunit;
In a scene of minimum fluctuation degree, dividing the detection duration of the loss reduction line into a plurality of continuous and equal second time subunits, obtaining the maximum loss reduction amount and the minimum loss reduction amount in each second time subunit, summing the maximum loss reduction amount and the minimum loss reduction amount, and taking an average value to obtain the average loss reduction amount in each second time subunit;
comparing all first time subunits with all second time subunits correspondingly:
If the average loss reduction amount in the first time subunit is not equal to the average loss reduction amount in the second time subunit, marking the first time subunit as an abnormal time subunit, and marking the second time subunit corresponding to the first time subunit as a comparison time subunit, wherein each abnormal time subunit corresponds to one comparison time subunit;
If the average loss reduction amount in the first time subunit is equal to the average loss reduction amount in the second time subunit, marking the first time subunit as a normal time subunit;
Counting the number of abnormal time subunits, carrying out ratio processing on the number of the abnormal time subunits and the number of the second time subunits to obtain the number ratio of the abnormal time subunits, and marking the number ratio as Vg;
Respectively carrying out difference processing on the loss reduction amount in each abnormal time subunit and the loss reduction amount in the corresponding contrast time subunit, summing the obtained difference values after taking absolute values to obtain average values, obtaining loss reduction amount deviation values in the abnormal time subunits, summing the loss reduction amounts in all second time subunits to obtain the total loss reduction amount of the second time subunits, carrying out ratio processing on the loss reduction amount deviation values in the abnormal time subunits and the total loss reduction amount of the second time subunits, obtaining the loss reduction deviation duty ratio of the abnormal time subunits, and marking the loss reduction deviation duty ratio as Vt;
by the formula: obtaining a loss-reducing adaptive parameter VH, wherein/> And/>Are all preset proportional coefficients, wherein/(The value is 1.02,/>The value is 1.69;
If the loss reduction adaptability parameter VH is more than or equal to the loss reduction adaptability parameter threshold VK, the loss reduction adaptability of the circuit is high;
If the loss reduction adaptive parameter VH < the loss reduction adaptive parameter threshold VK, the loss reduction adaptability of the line is low.
2. The method for evaluating the energy-saving and loss-reducing adaptability of the medium-voltage distribution network line according to claim 1, wherein the method comprises the following steps of: the method also comprises the following steps:
Step five: based on low loss reduction adaptability of the line, analyzing a temperature change curve, a wind speed change curve and a loss reduction change curve corresponding to a maximum fluctuation degree scene and a minimum fluctuation degree scene, acquiring a temperature influence parameter FG and a wind speed influence parameter GU, and correspondingly comparing the temperature influence parameter FG and the wind speed influence parameter GU with a temperature influence parameter threshold and a wind speed influence parameter threshold respectively;
If the temperature influence parameter FG is more than or equal to FD and the wind speed influence parameter GU is less than GJ, the influence of the temperature on the line loss reduction adaptability is shown, and the influence of the wind speed on the line loss reduction adaptability is not shown;
if the temperature influence parameter FG is less than FD and the wind speed influence parameter GU is more than or equal to GJ, the influence of the temperature on the line loss reduction adaptability is not shown, and the influence of the wind speed on the line loss reduction adaptability is shown;
If the temperature influence parameter FG is more than or equal to FD and the wind speed influence parameter GU is more than or equal to GJ, the influence of temperature and wind speed on the line loss reduction adaptability is shown;
Step six: based on the influence of temperature and wind speed on the line loss reduction adaptability, a temperature influence duty ratio characterization value XJ and a wind speed influence duty ratio characterization value XM are obtained, compared, and the main degrees of the temperature influence and the wind speed influence are judged according to the comparison result.
3. The method for evaluating the energy-saving and loss-reducing adaptability of the medium-voltage distribution network line according to claim 2, wherein the method is characterized by comprising the following steps of: the temperature influence duty ratio characterization value XJ and the wind speed influence duty ratio characterization value XM are obtained in the following ways:
Dividing the horizontal lengths of a temperature change curve, a wind speed change curve and a loss reduction change curve corresponding to the maximum fluctuation degree scene and the minimum fluctuation degree scene respectively into a plurality of continuous and equal-length subunits, and numbering the continuous and equal-length subunits, wherein the number and the number of the length subunits corresponding to the temperature change curve, the wind speed change curve and the loss reduction change curve are the same;
Comparing the temperature change curves corresponding to the maximum fluctuation degree scene and the minimum fluctuation degree scene respectively, cutting off the non-coincident part curves, and marking the reserved part curves as first reserved part curves;
according to the horizontal position and the horizontal length of the first reserved part curve, intercepting the wind speed change curves corresponding to the maximum fluctuation degree scene and the minimum fluctuation degree scene respectively at the same horizontal position and the same horizontal length, comparing the intercepted part curves again, intercepting the overlapped part curves, reserving the non-overlapped part curves, and marking the non-overlapped part curves as second reserved part curves;
According to the horizontal position and the horizontal length of the second reserved part curve, intercepting the loss reduction variable curves corresponding to the scene with the maximum fluctuation degree and the scene with the minimum fluctuation degree respectively at the same horizontal position and the same horizontal length, comparing the intercepted part curves again, intercepting the overlapped part curves, reserving the non-overlapped part curves, and marking the non-overlapped part curves as third reserved part curves;
Acquiring a length subunit number corresponding to the second reserved part curve and a length subunit number corresponding to the third reserved part curve, comparing the length subunit numbers, and counting the number of the length subunits with the same number;
Counting the sum of the number of the length subunits corresponding to the second reserved part curve and the number of the length subunits corresponding to the third reserved part curve;
carrying out ratio processing on the sum of the number of subunits with the same number and the number of length subunits corresponding to the second reserved part curve and the number of length subunits corresponding to the third reserved part curve to obtain a wind speed influence parameter GU;
the acquisition method of the temperature influence parameter FG is the same as the acquisition method of the wind speed influence parameter GU;
the method comprises the steps of firstly cutting off a temperature change curve, then cutting off and comparing the wind speed change curve, finally cutting off and comparing the loss reduction change curve, and obtaining a temperature influence parameter FG, namely firstly cutting off the wind speed change curve, then cutting off and comparing the temperature change curve, and finally cutting off and comparing the loss reduction change curve, wherein the cutting off, cutting off and comparing processing methods are the same.
4. A method for evaluating the adaptability of energy conservation and loss reduction of a medium-voltage distribution network line according to claim 3, which is characterized in that: the temperature influence duty ratio characterization value XJ and the wind speed influence duty ratio characterization value XM are obtained in the following manner:
Carrying out difference processing on the temperature influence parameter FG and the temperature influence parameter threshold FD, taking an absolute value of the difference value to obtain a temperature influence difference value, and carrying out ratio processing on the temperature influence difference value and the temperature influence parameter threshold to obtain a temperature influence duty ratio characterization value XJ;
And carrying out difference processing on the wind speed influence parameter GU and the wind speed influence parameter threshold GJ, taking an absolute value of the difference value to obtain a wind speed influence difference value, and carrying out ratio processing on the wind speed influence difference value and the wind speed influence parameter threshold to obtain a wind speed influence duty ratio representation value XM.
5. The method for evaluating the energy-saving and loss-reducing adaptability of the medium-voltage distribution network line according to claim 4, wherein the method comprises the following steps of: comparing the temperature influence duty cycle characterization value XJ with the wind speed influence duty cycle characterization value XM:
if the temperature influence duty ratio characterization value XJ is larger than the wind speed influence duty ratio characterization value XM, the main degree of the temperature influence is larger than the wind speed influence;
if the temperature influence duty ratio characterization value xj=the wind speed influence duty ratio characterization value XM, the main degree of the temperature influence is the same as the wind speed influence;
If the temperature influence duty ratio characterization value XJ is smaller than the wind speed influence duty ratio characterization value XM, the main degree of the temperature influence is smaller than the wind speed influence.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410323292.6A CN117932276B (en) | 2024-03-21 | 2024-03-21 | Energy-saving loss-reducing adaptability evaluation method for medium-voltage distribution network line |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410323292.6A CN117932276B (en) | 2024-03-21 | 2024-03-21 | Energy-saving loss-reducing adaptability evaluation method for medium-voltage distribution network line |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117932276A CN117932276A (en) | 2024-04-26 |
| CN117932276B true CN117932276B (en) | 2024-05-31 |
Family
ID=90752261
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410323292.6A Active CN117932276B (en) | 2024-03-21 | 2024-03-21 | Energy-saving loss-reducing adaptability evaluation method for medium-voltage distribution network line |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117932276B (en) |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017025483A1 (en) * | 2015-08-07 | 2017-02-16 | SensoMotoric Instruments Gesellschaft für innovative Sensorik mbH | Method and apparatus for data capture and evaluation of ambient data |
| CN106505556A (en) * | 2016-11-09 | 2017-03-15 | 国网山东省电力公司东阿县供电公司 | The method that city low and medium voltage distribution network drop is damaged |
| CN107016485A (en) * | 2017-02-20 | 2017-08-04 | 国网浙江省电力公司经济技术研究院 | A kind of power circuit saving energy and decreasing loss adaptability teaching method |
| CN110649644A (en) * | 2018-06-26 | 2020-01-03 | 南京理工大学 | Urban distribution network optimization loss reduction method containing distributed power supply |
| CN111967156A (en) * | 2020-08-13 | 2020-11-20 | 国家电网有限公司 | Multi-dimensional 10kV power grid loss reduction optimization method based on correlation analysis model |
| CN112862243A (en) * | 2020-12-31 | 2021-05-28 | 易事特集团股份有限公司 | Power distribution network energy-saving loss-reducing system and method based on big data |
| US11159253B1 (en) * | 2020-08-05 | 2021-10-26 | Shenzhen Jaguar Wave Technology Ltd. | Method for adjusting an antenna parameter, radio device, and apparatus with a storage function |
| CN115986917A (en) * | 2022-12-05 | 2023-04-18 | 贵州电网有限责任公司 | Medium voltage distribution network moving die system |
| CN116026389A (en) * | 2023-03-07 | 2023-04-28 | 湖南科技学院 | Intelligent sensor operation detection system based on data analysis |
| CN116975140A (en) * | 2023-07-27 | 2023-10-31 | 广东电网有限责任公司 | Method and system for visualizing loss reduction regulation result of power system |
| CN117175586A (en) * | 2023-11-03 | 2023-12-05 | 国网山东省电力公司菏泽供电公司 | Multi-scene energy-saving and loss-reducing processing system for medium-voltage line |
| CN117473253A (en) * | 2023-10-19 | 2024-01-30 | 杭州电力设备制造有限公司 | Power acquisition data quality assessment method |
| CN117669832A (en) * | 2023-12-14 | 2024-03-08 | 国网河北省电力有限公司电力科学研究院 | Loss reduction effect evaluation method and device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7940961B2 (en) * | 2007-12-20 | 2011-05-10 | The United States Of America As Represented By The Secretary Of The Navy | Method for enhancing ground-based detection of a moving object |
-
2024
- 2024-03-21 CN CN202410323292.6A patent/CN117932276B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017025483A1 (en) * | 2015-08-07 | 2017-02-16 | SensoMotoric Instruments Gesellschaft für innovative Sensorik mbH | Method and apparatus for data capture and evaluation of ambient data |
| CN106505556A (en) * | 2016-11-09 | 2017-03-15 | 国网山东省电力公司东阿县供电公司 | The method that city low and medium voltage distribution network drop is damaged |
| CN107016485A (en) * | 2017-02-20 | 2017-08-04 | 国网浙江省电力公司经济技术研究院 | A kind of power circuit saving energy and decreasing loss adaptability teaching method |
| CN110649644A (en) * | 2018-06-26 | 2020-01-03 | 南京理工大学 | Urban distribution network optimization loss reduction method containing distributed power supply |
| US11159253B1 (en) * | 2020-08-05 | 2021-10-26 | Shenzhen Jaguar Wave Technology Ltd. | Method for adjusting an antenna parameter, radio device, and apparatus with a storage function |
| CN111967156A (en) * | 2020-08-13 | 2020-11-20 | 国家电网有限公司 | Multi-dimensional 10kV power grid loss reduction optimization method based on correlation analysis model |
| CN112862243A (en) * | 2020-12-31 | 2021-05-28 | 易事特集团股份有限公司 | Power distribution network energy-saving loss-reducing system and method based on big data |
| CN115986917A (en) * | 2022-12-05 | 2023-04-18 | 贵州电网有限责任公司 | Medium voltage distribution network moving die system |
| CN116026389A (en) * | 2023-03-07 | 2023-04-28 | 湖南科技学院 | Intelligent sensor operation detection system based on data analysis |
| CN116975140A (en) * | 2023-07-27 | 2023-10-31 | 广东电网有限责任公司 | Method and system for visualizing loss reduction regulation result of power system |
| CN117473253A (en) * | 2023-10-19 | 2024-01-30 | 杭州电力设备制造有限公司 | Power acquisition data quality assessment method |
| CN117175586A (en) * | 2023-11-03 | 2023-12-05 | 国网山东省电力公司菏泽供电公司 | Multi-scene energy-saving and loss-reducing processing system for medium-voltage line |
| CN117669832A (en) * | 2023-12-14 | 2024-03-08 | 国网河北省电力有限公司电力科学研究院 | Loss reduction effect evaluation method and device |
Non-Patent Citations (3)
| Title |
|---|
| R. Droms ; Cisco Systems, Inc. ; D. Evans ; ARRIS International, Inc. ; .Time Protocol Servers and Time Offset Options for IPv6 DHCPdraft-droms-dhc-dhcpv6-rfc868-servers-02.txt.IETF .2005,全文. * |
| 随机故障场景下电压暂降的综合评估及其抑制方法研究;邹泽宇;硕士电子期刊2023年;20230115;全文 * |
| 马喜平 ; 贾嵘 ; 梁琛 ; 王维洲 ; 徐瑞.高比例新能源接入下电力系统降损研究综述.电网技术.2022,全文. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117932276A (en) | 2024-04-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114298863B (en) | Data acquisition method and system of intelligent meter reading terminal | |
| CN116186634B (en) | Intelligent management system for construction data of building engineering | |
| CN106407627B (en) | A kind of method and system of wind velocity distributing paremeter modeling | |
| CN106529741B (en) | Ultra-short-term wind power prediction method based on spatial correlation characteristics | |
| CN109918364B (en) | Data cleaning method based on two-dimensional probability density estimation and quartile method | |
| CN104794206A (en) | Transformer substation data quality evaluation system and method | |
| CN109779848B (en) | Method and device for obtaining full-field wind speed correction function and wind power plant | |
| CN110991701A (en) | Wind power plant fan wind speed prediction method and system based on data fusion | |
| CN117932501A (en) | Electric energy meter running state management method and system | |
| CN113626767A (en) | Fan power limit identification method, system, equipment and storage medium | |
| CN116470491A (en) | Photovoltaic power probability prediction method and system based on copula function | |
| CN116028887A (en) | Analysis method of continuous industrial production data | |
| CN117932276B (en) | Energy-saving loss-reducing adaptability evaluation method for medium-voltage distribution network line | |
| CN107808209B (en) | Wind power plant abnormal data identification method based on weighted kNN distance | |
| CN111797545B (en) | Wind turbine generator yaw reduction coefficient calculation method based on measured data | |
| CN116662466B (en) | Land full life cycle maintenance system through big data | |
| CN113177325A (en) | Method and device for correcting adjustable parameters of standard k-epsilon model under complex terrain and storage medium | |
| CN108197843B (en) | Wind power output characteristic evaluation method for flat terrain | |
| CN115898787A (en) | Method and device for dynamically identifying static yaw error of wind turbine generator | |
| CN111625525A (en) | Environmental data repairing/filling method and system | |
| CN110389394A (en) | A kind of statistical model of the mixed layer height prediction based on earth's surface meteorologic parameter | |
| CN116628411B (en) | High-precision flow online monitoring intelligent method based on full-sense fusion | |
| CN118091799B (en) | Multi-mode integrated forecasting method, system, device, storage medium and program product | |
| CN118376265B (en) | Flow measurement equipment operation intelligent evaluation system suitable for hydrologic station flow measurement | |
| CN113309661B (en) | Method for improving generating capacity of wind generating set |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |