Distribution network load control method and system for power distribution terminal load data deep analysis

Abstract

The invention discloses a distribution network load control method and system for power distribution terminal load data deep analysis, and relates to the technical field of distribution network load control. Calculating a daytime electricity utilization change coefficient and an air temperature electricity utilization change coefficient of a resident user line according to the resident load data; obtaining first load data of each power distribution branch line in the same power distribution main line, and calculating according to each first load data to obtain a power utilization change coefficient of each power distribution branch line; analyzing each power utilization change coefficient to obtain an analysis result, and determining the power distribution branch line meeting a preset condition as a branch line containing a non-resident load; according to the values of the electricity utilization change coefficients of the branch lines containing the non-resident loads, the distribution branch lines are shut down from large to small; dispatching personnel are supported to accurately disconnect corresponding branch lines under the condition that the main line load is out of limit, non-resident loads are timely subjected to voltage drop, and the defect that load voltage drop is carried out when the whole line is powered off in the prior art is overcome.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network load control, and more specifically, to a distribution network load control method and system for in-depth analysis of distribution terminal load data. Background Art

[0002] As the demand for power loads gradually increases, the world's energy shortage problem is becoming more and more serious. At the same time, the rise in natural gas and coal prices has greatly increased the cost of power generation in power plants, resulting in a shortage of power supply and a sharp increase in electricity prices. At this time, energy conservation is an important means to alleviate this contradiction. Distribution network voltage reduction energy conservation is a method for the distribution network to reduce the load voltage according to the static voltage characteristics of the load, while keeping the load voltage within the allowable range, thereby reducing energy consumption; At present, the means of load reduction in distribution network dispatching are mostly for the distribution network dispatcher to notify the power supply station to reduce the load, and the power supply station staff to notify the special transformer and special branch line to reduce the load, and basically the whole line voltage reduction is the main means. The load voltage reduction is not accurate enough and there are many human factors, which makes the load voltage reduction not objective, which will cause power outages for residential users. Summary of the invention

[0003] The purpose of the present invention is to provide a distribution network load control method and system for in-depth analysis of distribution terminal load data, to support dispatching personnel in accurately disconnecting corresponding branches when the main line load exceeds the limit, and to reduce non-residential loads in time, thereby solving the defect of existing whole-line power outage for load reduction. While ensuring the safety and stability of the power grid, it achieves accurate reduction of non-residential loads, thereby protecting residential loads, improving residents' electricity experience, and doing their utmost to allow the people to use electricity well.

[0004] The above technical objectives of the present invention are achieved through the following technical solutions:

[0005] In a first aspect, the present application provides a distribution network load control method for in-depth analysis of distribution terminal load data, including the following specific steps:

[0006] Obtaining residential load data of multiple residential user lines, and calculating the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient of the residential user lines according to the residential load data;

[0007] Obtaining first load data of each distribution branch line in the same distribution main line, and calculating the power consumption variation coefficient of each distribution branch line according to each first load data;

[0008] Based on the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient, each electricity consumption variation coefficient is analyzed, and the analysis result of each distribution branch line is obtained. If the analysis result meets the preset conditions, the distribution branch line that meets the preset conditions is determined as a branch line containing non-residential loads;

[0009] When there is a need to reduce the load voltage of the main distribution line, each distribution branch line will be shut down from large to small according to the numerical value of the power consumption change coefficient of the branch line containing non-residential loads.

[0010] Based on the above technical solution, the present invention can also be improved as follows.

[0011] Furthermore, the above-mentioned daytime electricity consumption variation coefficient includes a spring and autumn coefficient and a winter and summer coefficient. The spring and autumn coefficient or the winter and summer coefficient is obtained by the following method:

[0012] Obtaining resident load data in a preset first time period in spring, autumn, winter, and summer, and determining the load average in the first time period as a first value;

[0013] Obtaining resident load data in a preset second time period in spring, autumn, winter, and summer, and determining the load average in the second time period as a second value, wherein the first time period and the second time period are added together to form 24 hours in the same day;

[0014] The third value is calculated using the second value and the first value, and the average value of the third value of each residential user line is determined as the spring-autumn coefficient or the winter-summer coefficient.

[0015] Furthermore, the third value is specifically:

[0016] α n =A / B;

[0017] In the formula, α n represents a third value of the nth residential subscriber line, A represents the second value, and B represents the first value;

[0018] The spring and autumn coefficient or winter and summer coefficient is as follows:

[0019] α=(α 1 +α 2 +…+α n ) / n;

[0020] In the formula, α represents the spring and autumn coefficient or the winter and summer coefficient, n A third value representing the nth residential subscriber line, where n represents the total number of residential subscriber lines.

[0021] Furthermore, the temperature-electricity variation coefficient includes a first temperature interval coefficient, a second temperature interval coefficient and a third temperature interval coefficient. The first temperature interval coefficient, the second temperature interval coefficient or the third temperature interval coefficient is obtained by:

[0022] Acquire the resident load data corresponding to the temperature range in a preset first time period, and determine the load average in the first time period as a fourth value;

[0023] Obtaining the resident load data corresponding to the temperature range in a preset second time period, and determining the load average in the second time period as a fifth value, and the first time period and the second time period are added together to form 24 hours in the same day;

[0024] Based on the spring and autumn coefficient or the winter and summer coefficient, the sixth value is calculated according to the fourth value and the fifth value, and the average of the sixth values ​​of each residential user line is determined as the first temperature interval coefficient or the second temperature interval coefficient or the third temperature interval coefficient.

[0025] Furthermore, the sixth value is specifically:

[0026] β n =C / D;

[0027] In the formula, C represents the fifth value, D represents the fourth value, β n The sixth value representing the nth residential subscriber line;

[0028] The first temperature interval coefficient, the second temperature interval coefficient, or the third temperature interval coefficient is specifically:

[0029] β=(β 1 +β 2 +…+β n ) / n;

[0030] Where, β represents the first temperature interval coefficient, the second temperature interval coefficient, or the third temperature interval coefficient, β n A sixth value representing the nth residential subscriber line, where n represents the total number of residential subscriber lines.

[0031] Furthermore, the above electricity consumption variation coefficient is obtained by the following method:

[0032] Obtaining the residential load data of each distribution branch line in the distribution main line within a preset first time period, and determining the load average within the first time period as a seventh value;

[0033] Obtaining the residential load data of each distribution branch line in the distribution main line within a preset second time period, and determining the load average within the second time period as an eighth value, and the first time period and the second time period are added together to form 24 hours within the same day;

[0034] The seventh and eighth values ​​are used to calculate the power consumption variation coefficient.

[0035] Furthermore, the above electricity consumption variation coefficient is specifically:

[0036] γ=E / F; where γ represents the power consumption variation coefficient, E represents the eighth value, and F represents the seventh value;

[0037] The specific preconditions are:

[0038] γ>α+β; wherein, γ represents the electricity consumption variation coefficient, α represents the spring and autumn coefficient or the winter and summer coefficient, and β represents the first temperature interval coefficient or the second temperature interval coefficient or the third temperature interval coefficient.

[0039] In a second aspect, the present application provides a distribution network load control system for in-depth analysis of distribution terminal load data, which is applied to a distribution network load control method for in-depth analysis of distribution terminal load data according to any one of the first aspects, including:

[0040] The first module is used to obtain the residential load data of multiple residential user lines, and calculate the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient of the residential user lines according to the residential load data;

[0041] The second module is used to obtain the first load data of each distribution branch line in the same distribution main line, and calculate the power consumption change coefficient of each distribution branch line according to each first load data;

[0042] The third module is used to analyze each electricity consumption variation coefficient based on the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient, and obtain the analysis results of each distribution branch line. If the analysis result meets the preset conditions, the distribution branch line that meets the preset conditions is determined as a branch line containing non-residential loads;

[0043] The fourth module is used to shut down each distribution branch line from large to small according to the numerical value of the power consumption change coefficient of the branch line containing non-residential loads when there is a demand for load voltage reduction on the distribution main line.

[0044] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any one of the methods in the first aspect when executing the computer program.

[0045] In a fourth aspect, the present application provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions enable a computer to execute any one of the methods in the first aspect.

[0046] Compared with the prior art, the present invention has at least the following beneficial effects:

[0047] In the present application, firstly, the residential load data of the residential user lines that only include residential users are obtained in the power consumption system, and the daytime power consumption variation coefficient and the temperature power consumption variation coefficient of the residential user lines are calculated using the residential load data; secondly, the power consumption variation coefficient of each distribution branch line is calculated according to the load conditions of each distribution branch line in the distribution main line, and then the daytime power consumption variation coefficient of the corresponding season and the temperature power consumption variation coefficient of the corresponding temperature range are used, that is, the spring and autumn coefficient or the winter and summer coefficient, and the first temperature range coefficient or the second temperature range coefficient or the third temperature range coefficient are used to determine whether there is non-residential power consumption in each distribution branch line, and the distribution branch lines that meet the preset conditions are determined as branches containing non-residential loads; finally, when the distribution main line has a high load and needs to be reduced in voltage, according to the numerical value of the power consumption variation coefficient of the branch line containing non-residential loads, each distribution branch line is shut down from large to small, so as to achieve the effect of load reduction.

[0048] In the present application, each distribution branch line is judged by calculating various coefficients to determine whether there is non-residential electricity consumption, and according to the size of the electricity consumption variation coefficient of each distribution branch line, that is, the larger the electricity consumption variation coefficient is, the fewer residential users there are in the distribution branch line. The corresponding distribution branch lines are shut down in order from large to small, which not only achieves the effect of load reduction and ensures the safety of the power grid, but also reduces the impact on residents' electricity consumption. It can support dispatchers to accurately disconnect the corresponding branch lines when the main line load exceeds the limit, and reduce the non-residential load in time, which solves the defect of existing whole-line power outage for load reduction. While ensuring the safety and stability of the power grid, it achieves accurate reduction of non-residential load, thereby ensuring the residential load, improving the residents' electricity consumption experience, and doing our utmost to let the people use electricity well. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0050] Figure 1 A method flow chart of a control method in an embodiment of the present invention;

[0051] Figure 2 This is a connection diagram of a control system in an embodiment of the present invention;

[0052] Figure 3 Schematic diagram of the connection of electronic equipment in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0054] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0056] In the description of the embodiments of the present invention, "plurality" means at least 2.

[0057] Embodiment 1: In order to support dispatchers to accurately disconnect the corresponding branch line when the main line load exceeds the limit, timely reduce the non-residential load, solve the defects of the existing whole line power outage for load reduction, and ensure the safety and stability of the power grid while achieving accurate reduction of non-residential load, thereby protecting the residential load, improving the residents' electricity experience, and doing their best to let the people use electricity well, this embodiment provides a distribution network load control method with in-depth analysis of distribution terminal load data, such as Figure 1 As shown, the specific steps include:

[0058] S1, obtaining residential load data of multiple residential user lines, and calculating the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient of the residential user lines according to the residential load data.

[0059] Optionally, the daytime electricity consumption variation coefficient includes a spring-autumn coefficient and a winter-summer coefficient, and the spring-autumn coefficient or the winter-summer coefficient is obtained by:

[0060] S11, obtaining resident load data in a preset first time period in spring, autumn, winter, and summer, and determining the load average in the first time period as a first value.

[0061] S12, obtaining the resident load data in a preset second time period in spring and autumn or winter and summer, and determining the load average in the second time period as a second value, and the first time period and the second time period are added together to form 24 hours in the same day.

[0062] S13, calculating a third value using the second value and the first value, and determining an average of the third values ​​of each residential user line as a spring-autumn coefficient or a winter-summer coefficient.

[0063] Optionally, the third value is specifically:

[0064] α n =A / B;

[0065] In the formula, α n represents the third value of the nth residential user line, A represents the second value, and B represents the first value.

[0066] Furthermore, the spring and autumn coefficient or the winter and summer coefficient mentioned above is specifically:

[0067] α=(α 1 +α 2 +…+α n ) / n;

[0068] In the formula, α represents the spring and autumn coefficient or the winter and summer coefficient, n A third value representing the nth residential subscriber line, where n represents the total number of residential subscriber lines.

[0069] Optionally, the temperature-electricity variation coefficient includes a first temperature interval coefficient, a second temperature interval coefficient, and a third temperature interval coefficient, and the first temperature interval coefficient, the second temperature interval coefficient, or the third temperature interval coefficient is obtained by:

[0070] S14, obtaining the resident load data corresponding to the temperature range in a preset first time period, and determining the load average in the first time period as a fourth value.

[0071] S15, obtaining the resident load data corresponding to the temperature range in the preset second time period, and determining the load average in the second time period as the fifth value, and the first time period and the second time period are added together to form 24 hours in the same day.

[0072] S16, based on the spring and autumn coefficient or the winter and summer coefficient, calculate the sixth value according to the fourth value and the fifth value, and determine the average of the sixth values ​​of each residential user line as the first temperature interval coefficient or the second temperature interval coefficient or the third temperature interval coefficient.

[0073] Optionally, the sixth value is specifically:

[0074] β n =C / D;

[0075] In the formula, C represents the fifth value, D represents the fourth value, β n Indicates the sixth value of the nth residential subscriber line.

[0076] Furthermore, the first temperature interval coefficient, the second temperature interval coefficient, or the third temperature interval coefficient is specifically:

[0077] β=(β 1 +β 2 +…+β n ) / n;

[0078] Where, β represents the first temperature interval coefficient, the second temperature interval coefficient, or the third temperature interval coefficient, β n A sixth value representing the nth residential subscriber line, where n represents the total number of residential subscriber lines.

[0079] S2, obtaining first load data of each distribution branch line in the same distribution main line, and calculating the power consumption variation coefficient of each distribution branch line according to each first load data.

[0080] Optionally, the above electricity consumption variation coefficient is obtained by:

[0081] S21, obtaining the residential load data of each distribution branch line in the distribution main line within a preset first time period, and determining the load average within the first time period as a seventh value.

[0082] S22, obtaining the residential load data of each distribution branch line in the distribution main line within a preset second time period, and determining the load average within the second time period as an eighth value, and the first time period and the second time period are added together to form 24 hours within the same day.

[0083] S23, calculating the power consumption variation coefficient using the seventh value and the eighth value.

[0084] Optionally, the above electricity consumption variation coefficient is specifically:

[0085] γ=E / F; wherein, γ represents the electricity consumption variation coefficient, E represents the eighth value, and F represents the seventh value.

[0086] Among them, the above-mentioned first time period can be from 9 pm to 7 am, and the corresponding second time period can be from 7 am to 9 pm; the temperature range corresponding to the first temperature range coefficient can be 5-10℃ or 25-30℃, the temperature range of the second temperature range coefficient can be 0-5℃ or 30-35℃, and the temperature range of the third temperature range coefficient can be below 0℃ or above 35℃.

[0087] S3, based on the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient, each electricity consumption variation coefficient is analyzed, and the analysis result of each distribution branch line is obtained. If the analysis result meets the preset conditions, the distribution branch line that meets the preset conditions is determined as a branch line containing non-residential loads.

[0088] Among them, when analyzing each electricity consumption variation coefficient based on the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient, it is necessary to select the corresponding daytime electricity consumption variation coefficient and the corresponding temperature electricity consumption variation coefficient according to the current season and temperature conditions. For example, if the current season is summer, the winter and summer coefficient is selected. If the current temperature is 25°C, the first temperature interval coefficient is selected.

[0089] Optionally, the above preset conditions are specifically:

[0090] γ>α+β; wherein, γ represents the electricity consumption variation coefficient, α represents the spring and autumn coefficient or the winter and summer coefficient, and β represents the first temperature interval coefficient or the second temperature interval coefficient or the third temperature interval coefficient.

[0091] S4: When there is a demand for load reduction on the main distribution line, the distribution branches are shut down from large to small according to the numerical value of the power consumption change coefficient of the branch line containing non-residential loads, until the load reduction requirement is met, and then the shutdown of each distribution branch line is stopped.

[0092] Specifically, the larger the electricity consumption variation coefficient is, the fewer residential users there are in the distribution branch line. The corresponding distribution branch lines are shut down in order from large to small, which not only achieves the effect of load reduction and ensures the safety of the power grid, but also reduces the impact on residents' electricity consumption.

[0093] Embodiment 2: The embodiment of the present application provides a distribution network load control system for in-depth analysis of distribution terminal load data, which is applied to the distribution network load control method for in-depth analysis of distribution terminal load data in any one of Embodiment 1, such as Figure 2 As shown, including:

[0094] The first module is used to obtain the residential load data of multiple residential user lines, and calculate the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient of the residential user lines according to the residential load data;

[0095] The second module is used to obtain the first load data of each distribution branch line in the same distribution main line, and calculate the power consumption change coefficient of each distribution branch line according to each first load data;

[0096] The third module is used to analyze each electricity consumption variation coefficient based on the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient, and obtain the analysis results of each distribution branch line. If the analysis result meets the preset conditions, the distribution branch line that meets the preset conditions is determined as a branch line containing non-residential loads;

[0097] The fourth module is used to shut down each distribution branch line from large to small according to the numerical value of the power consumption change coefficient of the branch line containing non-residential loads when there is a demand for load voltage reduction on the distribution main line.

[0098] Embodiment 3: This embodiment of the present application provides an electronic device, such as Figure 3 As shown, it includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, any method in Embodiment 1 is implemented.

[0099] Embodiment 4: The embodiment of the present application provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions enable a computer to execute any method in Embodiment 1.

[0100] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A distribution network load control method based on in-depth analysis of distribution terminal load data, characterized in that: The specific steps include: Acquire residential load data of a plurality of residential user lines, and calculate the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient of the residential user lines according to the residential load data; Acquire first load data of each distribution branch line in the same distribution main line, and calculate the power consumption variation coefficient of each distribution branch line according to each of the first load data; Analyze each of the electricity consumption variation coefficients based on the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient, and obtain analysis results of each distribution branch line. If the analysis results meet the preset conditions, determine the distribution branch line that meets the preset conditions as a branch line containing non-residential loads; When there is a demand for load voltage reduction on the main distribution line, each distribution branch line is shut down from large to small according to the numerical value of the power consumption variation coefficient of the branch line containing non-residential loads.

2. The distribution network load control method for in-depth analysis of distribution terminal load data according to claim 1 is characterized in that: The daytime electricity consumption variation coefficient includes a spring and autumn coefficient and a winter and summer coefficient. The spring and autumn coefficient or the winter and summer coefficient is obtained by: Obtaining resident load data in a preset first time period in spring, autumn, winter, and summer, and determining the load average in the first time period as a first value; Obtaining resident load data in a preset second time period in spring, autumn, winter, and summer, and determining the load average in the second time period as a second value, wherein the first time period and the second time period are added together to form 24 hours in the same day; A third value is calculated using the second value and the first value, and an average value of the third values ​​of each residential user line is determined as the spring-autumn coefficient or the winter-summer coefficient.

3. The distribution network load control method for in-depth analysis of distribution terminal load data according to claim 2 is characterized in that: The third value is specifically: a n =A / B; In the formula, α n represents a third value of the nth residential subscriber line, A represents the second value, and B represents the first value; The spring and autumn coefficient or the winter and summer coefficient is specifically: α＝(α1+α2+…+α n ) / n； In the formula, α represents the spring and autumn coefficient or the winter and summer coefficient, n A third value representing the nth residential subscriber line, where n represents the total number of residential subscriber lines.

4. The distribution network load control method for in-depth analysis of distribution terminal load data according to claim 2, characterized in that: The temperature-electricity variation coefficient includes a first temperature interval coefficient, a second temperature interval coefficient and a third temperature interval coefficient. The first temperature interval coefficient, the second temperature interval coefficient or the third temperature interval coefficient is obtained by: Acquire the resident load data corresponding to the temperature range in a preset first time period, and determine the load average in the first time period as a fourth value; Obtaining residential load data corresponding to the temperature range in a preset second time period, and determining the load average in the second time period as a fifth value, wherein the first time period and the second time period are added together to form 24 hours in the same day; Based on the spring-autumn coefficient or the winter-summer coefficient, a sixth value is calculated according to the fourth value and the fifth value, and the average of the sixth values ​​of each residential user line is determined as the first temperature interval coefficient or the second temperature interval coefficient or the third temperature interval coefficient.

5. The distribution network load control method for in-depth analysis of distribution terminal load data according to claim 4 is characterized in that: The sixth value is specifically: b n =C / D; In the formula, C represents the fifth value, D represents the fourth value, β n The sixth value representing the nth residential subscriber line; The first temperature interval coefficient, the second temperature interval coefficient, or the third temperature interval coefficient is specifically: β＝(β1+β2+…+β n ) / n； Where, β represents the first temperature interval coefficient, the second temperature interval coefficient, or the third temperature interval coefficient, β n A sixth value representing the nth residential subscriber line, where n represents the total number of residential subscriber lines.

6. The distribution network load control method for in-depth analysis of distribution terminal load data according to claim 4, characterized in that: The power consumption variation coefficient is obtained by the following method: Obtaining the residential load data of each distribution branch line in the distribution main line within a preset first time period, and determining the load average within the first time period as a seventh value; Obtaining residential load data of each distribution branch line in the distribution main line within a preset second time period, and determining the load average within the second time period as an eighth value, wherein the first time period and the second time period are added together to form 24 hours within the same day; The power consumption variation coefficient is calculated using the seventh value and the eighth value.

7. The distribution network load control method for in-depth analysis of distribution terminal load data according to claim 6, characterized in that: The power consumption variation coefficient is specifically: γ=E / F; where γ represents the power consumption variation coefficient, E represents the eighth value, and F represents the seventh value; The preset conditions are specifically: γ>α+β; wherein, γ represents the electricity consumption variation coefficient, α represents the spring and autumn coefficient or the winter and summer coefficient, and β represents the first temperature interval coefficient or the second temperature interval coefficient or the third temperature interval coefficient.

8. A distribution network load control system for in-depth analysis of distribution terminal load data, applied to a distribution network load control method for in-depth analysis of distribution terminal load data according to any one of claims 1 to 7, characterized in that: include: The first module is used to obtain the residential load data of multiple residential user lines, and calculate the daytime electricity consumption variation coefficient and the temperature electricity consumption variation coefficient of the residential user lines according to the residential load data; The second module is used to obtain the first load data of each distribution branch line in the same distribution main line, and calculate the power consumption change coefficient of each distribution branch line according to each of the first load data; The third module is used to analyze each of the power consumption variation coefficients based on the daytime power consumption variation coefficient and the temperature power consumption variation coefficient, and obtain the analysis results of each distribution branch line. If the analysis results meet the preset conditions, the distribution branch line that meets the preset conditions is determined as a branch line containing non-residential loads; The fourth module is used to shut down each distribution branch line from large to small according to the numerical value of the power consumption variation coefficient of the branch line containing non-residential loads when there is a demand for load voltage reduction on the distribution main line.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the method according to any one of claims 1 to 7 is implemented when the processor executes the computer program.

10. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, which enable a computer to execute the method of any one of claims 1-7.

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