A distribution network construction method based on big data analysis

Abstract

The present invention provides a distribution network construction method based on big data analysis. Through big data analysis and positioning of key users that affect the heavy overload of the distribution network, targeted investment, construction and transformation of the power grid are carried out to achieve the effective construction of a new distribution network, which includes the following steps: 1) reading internal and external data of the power grid; 2) mining and optimizing key users through internal data of the power grid; 3) establishing an optimized construction plan through external data of the power grid; 4) implementing related projects according to the established optimized construction plan. The present invention realizes the access of new energy sources such as photovoltaics and wind power, greatly improves the proportion of green and clean energy in the current power grid, achieves the environmental benefits of energy conservation and emission reduction, and effectively helps the implementation of the dual carbon goals.

Description

Technical Field

[0001] The present invention relates to the field of electrical engineering technology, and in particular to a distribution network construction method based on big data analysis. Background Art

[0002] Heavy overload is an abnormal operating mode of the power grid, and the limited access capacity of power lines caused by it is a common problem in power grid construction. On the one hand, under the existing equipment level and operating technical conditions, the more ideal construction and transformation method is still to eliminate the heavy overload phenomenon by replacing large-capacity transformers and lines. Although it meets the management needs of heavy overload of the distribution network, the investment method is too extensive and the return on investment of power grid construction is low. On the other hand, with the proposal of the country's "carbon peak and carbon neutrality", central enterprises represented by State Grid have followed the general trend of the energy revolution and used new technologies such as "big cloud, things, mobile, intelligence and chain" to build a new power system and promote the transformation and upgrading of the power grid. Therefore, how to use new technologies such as big data and cloud computing to build a new distribution network under the new situation, and then solve the problem of heavy overload of the distribution network, has become an important research topic. Summary of the invention

[0003] In order to solve the current heavy overload problem of distribution network and effectively avoid the shortcomings of intensive and extensive traditional heavy overload management methods, as well as waste of power grid resources, this paper uses big data advanced technology to accurately analyze and locate key users that affect heavy overload of distribution network, determine the objects that need investment and construction, and unite power grid, enterprise and user, using clean power sources such as photovoltaics, flexible loads such as energy storage, and demand-side response and other new methods and means to jointly solve the heavy overload problem under the new distribution network and realize the effective construction of new distribution network driven by big data.

[0004] In order to achieve the above object, the technical solution of the present invention is: a distribution network construction method based on big data analysis, the specific steps of the method are as follows:

[0005] Step S1: For a distribution network with a heavy overload phenomenon, read the static data and dynamic data inside the power grid, and at the same time, combine external meteorological data, geographical data, construction land and other information to carry out data mining;

[0006] Step S2: using the internal data of the power grid to mine key users that affect heavy overload and determine the objects of optimization construction;

[0007] Step S3: Based on the mined key users, an optimization construction plan is established using external data of the power grid;

[0008] Step S4: According to the established optimization construction plan, relevant projects are implemented, incremental transformation is carried out, and the effective construction of the new distribution network is completed.

[0009] Preferably, step S2 comprises the following steps:

[0010] Step S21: Select the heavy overload data of the power distribution network in the past three years for preprocessing, calculate the user's daily average load curve and the daily average load rate curve, and lay the foundation for the following index calculation. The calculation formula is as follows:

[0011]

[0012] In the formula, S ki (t) is the load value of the kth user at time t on the i-th day, is the average load value of the kth user at time t within the day, is the average load rate of the distribution network at time t within a day, n is the number of heavily overloaded days in the past three years, m is the number of users of the distribution network, t is 1, 2, …, T, S N is the rated capacity of the distribution network;

[0013] Step S22: Calculate the influence of each user's load on the load rate of the distribution network;

[0014] (1) Calculation of change trend

[0015] Calculate the impact of each user's load change on the distribution network load rate, and quantify the trend of each user's load affecting the distribution network load rate. The larger the value, the greater the actual impact on the distribution network load rate change trend;

[0016] 1) In order to eliminate the impact of different dimensions of load and load rate, the user's daily average load curve and daily average load rate curve are standardized respectively. The calculation formula is as follows:

[0017]

[0018] In the formula, μ s is the average value of the daily average load of users, σ s is the variance of the average daily load of users, s k (t) is the average daily load of users The standardized value of , T is the sampling time of the daily load;

[0019]

[0020] In the formula, μ L is the average daily load factor of users, σ L is the variance of the average daily load rate of users, l(t) is the average daily load rate of users The standardized value of , T is the sampling time of the daily load;

[0021] 2) Using the standardized load and load rate data, calculate the impact of user load changes on the load rate of the distribution network. The calculation formula is as follows:

[0022]

[0023] In the formula, v k (t) is the influence coefficient of the kth user load change on the distribution network load rate, s k ′(t) is the derivative of the average daily load of users after standardization, l′(t) is the derivative of the average daily load rate of the distribution network after standardization;

[0024] (2) Numerical ratio calculation

[0025] Calculate the impact of each user's load on the distribution network load rate, and quantify the proportion of each user's load affecting the distribution network load rate. The larger the value, the greater the actual impact on the distribution network load rate numerical ratio. The formula is as follows:

[0026]

[0027] In the formula, ω k is the influence coefficient of the kth user load size on the load rate of the distribution network;

[0028] (3) Calculation of impact

[0029] Select the heavy overload period t i to j , using the change and size of user load to calculate the impact on the load rate of the distribution network during this period of time, the calculation formula is as follows:

[0030]

[0031] Where U k t i to j The impact value of the kth user on the load rate of the distribution network during the heavy overload period;

[0032] Step S23: sorting the impact values ​​of each user on the load rate of the distribution network during the heavy overload period, and the users with the highest ranking are the key users to be mined and are also the objects of optimization, construction and transformation;

[0033] Step S24: Propose corresponding suggestions for the mined user load types;

[0034] 1) If the key nodes discovered are large industrial loads or general industrial and commercial loads, then consider: ① The power grid company negotiates with relevant users to carry out demand-side response to reduce the demand for power supply during the heavy overload stage of the power grid; ② Configure distributed power sources on the user side with conditions to reduce the power supply demand of the power grid; ③ Configure energy storage on the user side with insufficient conditions to smooth the load demand by shaving peaks and filling valleys;

[0035] 2) If the key nodes discovered are agricultural loads or residential loads, consider configuring energy storage on the relevant user side to smooth out load demand by shaving peak loads and filling valleys;

[0036] 3) If the key node discovered is the electric vehicle load, then ① consider configuring energy storage to smooth the load demand by shaving peaks and filling valleys; ② carry out demand-side response and conduct orderly charging.

[0037] Preferably, step S3 comprises the following steps:

[0038] Step S31: Complete the on-site condition assessment through meteorological resource assessment, geographic information assessment, and government data reference, calculate the feasibility of various optimization construction plans, and provide support for the investor to formulate the optimization construction plan;

[0039] (1) Meteorological resource assessment

[0040] 1) Evaluate the solar and wind meteorological resources in the power supply area through meteorological data, calculate the feasibility of distributed power construction in the power supply area, and provide a reference for the establishment of the optimization plan. Taking photovoltaic as an example, the present invention briefly selects the total radiation and sunshine hours indicators to evaluate the solar energy resources in the power supply area, and the calculation is as follows:

[0041]

[0042] Where: H is the total radiation in the calculation period, n is the total number of hours in the calculation period, g i is the average total irradiance in the ith hour, h is the time, which is 1 hour, T p The peak sunshine hours in the calculation period; if the measurement unit of H is MJ / m 2 , it needs to be converted into kW / m 2 , 1kW / m 2 =3.6MJ / m 2 .

[0043] 2) Based on meteorological information, check whether there have been extreme weather events such as earthquakes, typhoons, sandstorms, etc. in the power supply area over the years, and determine whether there is a possibility that the distributed power supply and energy storage station cannot be built in the area due to natural disasters;

[0044] (2) Geographic Information Assessment

[0045] 1) Use satellite remote sensing to observe the topography of the site at the key node user to determine whether there are relevant sites around that are suitable for the construction of distributed power sources or energy storage stations;

[0046] 2) Through on-site investigation, determine whether the terrain and landform conditions in the area meet the requirements for the construction of distributed power or energy storage stations. For example, the requirements for distributed power photovoltaic stations are flat and open ground, suitable terrain orientation, small site slope, no protruding mountains and hills, and a certain soil thickness without hard soil and other geographical conditions;

[0047] (3) Data reference

[0048] 1) Clarify the nature and scope of land suitable for the construction of distributed power generation or energy storage;

[0049] 2) Investigate whether there are any external factors that are not compatible with the construction of distributed power generation or energy storage stations;

[0050] Step S32: Based on the feasibility of optimized construction of distributed power sources, energy storage, etc. obtained from the on-site condition assessment, several feasible construction implementation plans are formulated. At the same time, by combining the power grid, integrated energy enterprises, and users, the final construction implementation plan is established after comprehensively considering the benefits of all parties and the grid regulation effect.

[0051] The beneficial effects of the present invention are as follows:

[0052] The present invention proposes a distribution network construction method based on big data analysis, which only requires construction and transformation for the key users that have been located, breaking through the construction and transformation methods and concepts of traditional power grids and saving related investments in power grids; secondly, the method of the present invention only constructs and transforms a small number of users, and the number of affected users is also relatively small, thus avoiding temporary power outages for a large number of users and improving the power supply reliability of the power grid; finally, the present invention realizes the access of new energy such as photovoltaics and wind power, greatly increasing the proportion of green and clean energy in the current power grid, achieving the environmental benefits of energy conservation and emission reduction, and effectively contributing to the implementation of the dual carbon goals. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a flow chart of the new distribution network construction of the present invention.

[0054] Figure 2 Mining key user process maps for internal grid data. DETAILED DESCRIPTION

[0055] The present invention will be further described below in conjunction with the accompanying drawings. Figure 1 As shown, a distribution network construction method based on big data analysis includes the following steps:

[0056] Step S1: For a distribution network with a heavy overload phenomenon, read the static data and dynamic data inside the power grid, and at the same time, combine external meteorological data, geographical data, construction land and other information to carry out data mining;

[0057] Step S2: using the internal data of the power grid to mine key users that affect heavy overload and determine the objects of optimization construction;

[0058] Step S3: Based on the mined key users, an optimization construction plan is established using external data of the power grid;

[0059] Step S4: According to the established optimization construction plan, relevant projects are implemented, incremental transformation is carried out, and the effective construction of the new distribution network is completed.

[0060] The step S2 comprises the following steps:

[0061] Step S21: Select the heavy overload data of the power distribution network in the past three years for preprocessing, calculate the user's daily average load curve and the daily average load rate curve, and lay the foundation for the following index calculation. The calculation formula is as follows:

[0062]

[0063] In the formula, S ki (t) is the load value of the kth user at time t on the i-th day, is the average load value of the kth user at time t within the day, is the average load rate of the distribution network at time t within a day, n is the number of heavily overloaded days in the past three years, m is the number of users of the distribution network, t is 1, 2, …, T, S N is the rated capacity of the distribution network;

[0064] Step S22: Calculate the influence of each user's load on the load rate of the distribution network;

[0065] (3) Calculation of change trend

[0066] Calculate the impact of each user's load change on the distribution network load rate, and quantify the trend of each user's load affecting the distribution network load rate. The larger the value, the greater the actual impact on the distribution network load rate change trend;

[0067] 1) In order to eliminate the impact of different dimensions of load and load rate, the user's daily average load curve and daily average load rate curve are standardized respectively. The calculation formula is as follows:

[0068]

[0069] In the formula, μ s is the average value of the daily average load of users, σ sis the variance of the average daily load of users, s k (t) is the average daily load of users The standardized value of , T is the sampling time of the daily load;

[0070]

[0071] In the formula, μ L is the average daily load factor of users, σ L is the variance of the average daily load rate of users, l(t) is the average daily load rate of users The standardized value of , T is the sampling time of the daily load;

[0072] 2) Using the standardized load and load rate data, calculate the impact of user load changes on the load rate of the distribution network. The calculation formula is as follows:

[0073]

[0074] In the formula, v k (t) is the influence coefficient of the kth user load change on the distribution network load rate, s k ′(t) is the derivative of the average daily load of users after standardization, l′(t) is the derivative of the average daily load rate of the distribution network after standardization;

[0075] (4) Numerical ratio calculation

[0076] Calculate the impact of each user's load on the distribution network load rate, and quantify the proportion of each user's load affecting the distribution network load rate. The larger the value, the greater the actual impact on the distribution network load rate numerical ratio. The formula is as follows:

[0077]

[0078] In the formula, ω k is the influence coefficient of the kth user load size on the load rate of the distribution network;

[0079] (4) Calculation of impact

[0080] Select the heavy overload period t i to j , using the change and size of user load to calculate the impact on the load rate of the distribution network during this period of time, the calculation formula is as follows:

[0081]

[0082] Where U k t i to j The impact value of the kth user on the load rate of the distribution network during the heavy overload period;

[0083] Step S23: sorting the impact values ​​of each user on the load rate of the distribution network during the heavy overload period, and the users with the highest ranking are the key users to be mined and are also the objects of optimization, construction and transformation;

[0084] Step S24: Propose corresponding suggestions for the mined user load types;

[0085] 1) If the key nodes discovered are large industrial loads or general industrial and commercial loads, then consider: ① The power grid company negotiates with relevant users to carry out demand-side response to reduce the demand for power supply during the heavy overload stage of the power grid; ② Configure distributed power sources on the user side with conditions to reduce the power supply demand of the power grid; ③ Configure energy storage on the user side with insufficient conditions to smooth the load demand by shaving peaks and filling valleys;

[0086] 2) If the key nodes discovered are agricultural loads or residential loads, consider configuring energy storage on the relevant user side to smooth out load demand by shaving peak loads and filling valleys;

[0087] 3) If the key node discovered is the electric vehicle load, then ① consider configuring energy storage to smooth the load demand by shaving peaks and filling valleys; ② carry out demand-side response and conduct orderly charging.

[0088] The step S3 comprises the following steps:

[0089] Step S31: Complete the on-site condition assessment through meteorological resource assessment, geographic information assessment, and data reference, calculate the feasibility of various optimization construction plans, and provide support for the investor to formulate the optimization construction plan;

[0090] (4) Meteorological resource assessment

[0091] 1) Evaluate the solar and wind meteorological resources in the power supply area through meteorological data, calculate the feasibility of distributed power construction in the power supply area, and provide a reference for the establishment of the optimization plan. Taking photovoltaic as an example, the present invention briefly selects the total radiation and sunshine hours indicators to evaluate the solar energy resources in the power supply area, and the calculation is as follows:

[0092]

[0093] Where: H is the total radiation in the calculation period, n is the total number of hours in the calculation period, g i is the average total irradiance in the ith hour, h is the time, which is 1 hour, T p The peak sunshine hours in the calculation period; if the measurement unit of H is MJ / m 2 , it needs to be converted into kW / m 2 , 1kW / m 2 =3.6MJ / m 2 .

[0094] 3) Check whether there have been extreme weather events such as earthquakes, typhoons, sandstorms, etc. in the power supply area over the years based on meteorological information, and determine whether there is a possibility that the distributed power supply and energy storage station cannot be built in the area due to natural disasters;

[0095] (5) Geographic Information Assessment

[0096] 3) Use satellite remote sensing to observe the topography of the site at the key node user to determine whether there are relevant sites around that are suitable for the construction of distributed power sources or energy storage stations;

[0097] 4) Through on-site investigation, determine whether the terrain and landform conditions in the area meet the requirements for the construction of distributed power or energy storage stations. For example, the requirements for the ground of a distributed power photovoltaic station are flat and open, with a suitable terrain orientation, a small slope, no protruding mountains and hills, a certain thickness of soil layer, and no hard soil;

[0098] (6) Data reference

[0099] 3) Clarify the nature and scope of land suitable for the construction of distributed power generation or energy storage;

[0100] 4) Based on relevant data, check whether there are large-scale smelting, chemical, petrochemical and other large-scale high-consumption and polluting enterprises around the wind outlet, and whether there are external factors that are not suitable for the construction of distributed power sources or energy storage stations;

[0101] Step S32: Based on the feasibility of optimized construction of distributed power sources, energy storage, etc. obtained from the on-site condition assessment, several feasible construction implementation plans are formulated. At the same time, through the government's joint power grid-integrated energy enterprise-user, the final construction implementation plan is established after comprehensively considering the benefits of all parties and the power grid regulation effect. Specific embodiments

[0103] This embodiment provides a distribution network construction method based on big data analysis. The overall method flow is as follows: Figure 1 As shown, the specific steps are as follows:

[0104] Step S1: For a distribution network that is severely overloaded, read the static and dynamic data inside the power grid, and at the same time, conduct data mining in combination with external meteorological data, geographic data, government construction land and other information.

[0105] Step S2: Use the internal data of the power grid to mine the key users that affect the heavy overload and determine the objects of optimization construction. For the specific process, please refer to Figure 2 .

[0106] Step S21: Select the heavy overload data of the power distribution network in the past three years for preprocessing, calculate the user's daily average load curve and the daily average load rate curve, and lay the foundation for the following index calculation. The calculation formula is as follows:

[0107]

[0108] In the formula, S ki (t) is the load value of the kth user at time t on the i-th day, is the average load value of the kth user at time t within the day, is the average load rate of the distribution network at time t within a day, n is the number of heavily overloaded days in the past three years, m is the number of users of the distribution network, t is 1, 2, …, T, S N is the rated capacity of the distribution network.

[0109] Step S22: Calculate the influence of each user's load on the load rate of the distribution network.

[0110] (5) Calculation of change trend

[0111] Calculate the impact of each user's load change on the distribution network load rate, and quantify the trend of each user's load affecting the distribution network load rate. The larger the value, the greater the actual impact on the distribution network load rate change trend.

[0112] 1) In order to eliminate the impact of different dimensions of load and load rate, the user's daily average load curve and daily average load rate curve are standardized respectively. The calculation formula is as follows:

[0113]

[0114] In the formula, μ s is the average value of the daily average load of users, σ s is the variance of the average daily load of users, s k (t) is the average daily load of users The standardized value of T is the sampling time of the daily load, and the daily load is generally sampled 96 times.

[0115]

[0116] In the formula, μ L is the average daily load factor of users, σ L is the variance of the average daily load rate of users, l(t) is the average daily load rate of users The standardized value of T is the sampling time of the daily load, and the daily load is generally sampled 96 times.

[0117] 2) Using the standardized load and load rate data, calculate the impact of user load changes on the load rate of the distribution network. The calculation formula is as follows:

[0118]

[0119] In the formula, v k (t) is the influence coefficient of the kth user load change on the distribution network load rate, s k ′(t) is the derivative of the standardized average daily load of users, and l′(t) is the derivative of the standardized average daily load rate of the distribution network.

[0120] (6) Numerical ratio calculation

[0121] Calculate the impact of each user's load on the distribution network load rate, and quantify the proportion of each user's load affecting the distribution network load rate. The larger the value, the greater the actual impact on the distribution network load rate numerical ratio. The formula is as follows:

[0122]

[0123] In the formula, ω k is the influence coefficient of the kth user load size on the load rate of the distribution network.

[0124] (5) Calculation of impact

[0125] Select the heavy overload period t i to j , using the change and size of user load to calculate the impact on the load rate of the distribution network during this period of time, the calculation formula is as follows:

[0126]

[0127] Where U k t i to j The impact value of the kth user on the load rate of the distribution network during the heavy overload period.

[0128] Step S23: sorting the impact values ​​of each user on the load rate of the distribution network during the heavy overload period, and the users with the highest ranking are the key users to be mined and are also the objects of optimization, construction and transformation.

[0129] Step S24: Propose corresponding suggestions for the mined user load types.

[0130] 1) If the key nodes discovered are large industrial loads or general industrial and commercial loads, then consider ① the power grid company negotiates with relevant users to carry out demand-side response to reduce the demand for power supply during the heavy overload stage of the power grid; ② configure distributed power sources on the user side with conditions to reduce the power supply demand of the power grid; ③ configure energy storage on the user side where conditions are insufficient to smooth the load demand by shaving peaks and filling valleys.

[0131] 2) If the key nodes discovered are agricultural loads or residential loads, consider configuring energy storage on the relevant user side to smooth out load demand by shaving peak loads and filling valleys.

[0132] 3) If the key node discovered is the electric vehicle load, then ① consider configuring energy storage to smooth the load demand by shaving peaks and filling valleys; ② carry out demand-side response and conduct orderly charging.

[0133] Step S3: Based on the discovered key users, an optimized construction plan is established using external data from the power grid.

[0134] Step S31: Complete the on-site condition assessment through meteorological resource assessment, geographic information assessment, and government data reference, calculate the feasibility of various optimization construction plans, and provide support for the investor to formulate the optimization construction plan.

[0135] (7) Meteorological resource assessment

[0136] 1) Evaluate the meteorological resources such as solar energy and wind energy in the power supply area through meteorological data, calculate the feasibility of distributed power supply construction in the area, and provide a reference for the establishment of the optimization plan. Taking photovoltaic as an example, the present invention briefly selects the total radiation and sunshine hours indicators to evaluate the solar energy resources in the power supply area, and the calculation is as follows:

[0137]

[0138] Where: H is the total radiation in the calculation period, n is the total number of hours in the calculation period, g i is the average total irradiance in the ith hour, h is the time, which is 1 hour, T p The peak sunshine hours in the calculation period; if the measurement unit of H is MJ / m 2 , it needs to be converted into kW / m 2 , 1kW / m 2 =3.6MJ / m 2 ,The reference standards are shown in Table 1.

[0139] Table 1 Meteorological resource assessment criteria for the feasibility of photovoltaic stations

[0140]

[0141]

[0142] 4) Based on meteorological information, check whether the power supply area has experienced extreme weather such as earthquakes, typhoons, sandstorms, etc. over the years, and determine whether the area may be unable to build distributed power sources and energy storage stations due to natural disasters.

[0143] (8) Geographic Information Assessment

[0144] 5) Use satellite remote sensing to observe the topographic profile of the site at the key node user to determine whether there are related sites nearby that are suitable for the construction of distributed power sources or energy storage stations.

[0145] 6) Through on-site investigation, determine whether the terrain and landform conditions in the area are suitable for the construction of distributed power or energy storage stations. For example, the requirements for the ground of a distributed power photovoltaic station are flat and open, suitable terrain orientation, small site slope, no protruding mountains and hills, a certain soil thickness, no hard soil and other geographical conditions.

[0146] (9) Government data reference

[0147] 5) By consulting with relevant government agencies such as the Land and Resources Bureau and the Forestry Bureau, clarify the nature and scope of land suitable for the construction of distributed power sources or energy storage sites, and avoid agricultural land, forestry land, and sensitive areas such as military, cultural relics, and protected areas.

[0148] 6) Based on relevant government data, examine whether there are large-scale smelting, chemical, petrochemical and other large-scale high-consumption and polluting enterprises in the surrounding air outlets, and whether there are any external factors that are not suitable for the construction of distributed power sources or energy storage stations.

[0149] Step S32: Based on the feasibility of optimized construction of distributed power sources, energy storage, etc. obtained from the on-site condition assessment, several feasible construction implementation plans are formulated. At the same time, through the government's joint power grid-integrated energy enterprise-user, the final construction implementation plan is established after comprehensively considering the benefits of all parties and the power grid regulation effect.

[0150] Step S4: According to the established optimization construction plan, relevant projects are implemented, incremental transformation is carried out, and the effective construction of the new distribution network is completed.

[0151] The contents described in the embodiments of this specification are merely an enumeration of implementation forms of the inventive concept. The protection scope of the present invention should not be regarded as limited to the specific forms described in the embodiments. The protection scope of the present invention also includes equivalent technical means that can be thought of by those skilled in the art based on the inventive concept.

Claims

1. A distribution network construction method based on big data analysis, characterized in that: The specific steps of the method are as follows: Step S1: For a distribution network with a heavy overload phenomenon, read the static data and dynamic data inside the power grid, and at the same time, combine external meteorological data, geographic data and construction land information to carry out data mining; Step S2: using the internal data of the power grid to mine key users that affect heavy overload and determine the objects of optimization construction; Step S3: Based on the mined key users, an optimization construction plan is established using external data of the power grid; Step S4: According to the established optimization construction plan, relevant projects are implemented, incremental transformation is carried out, and the effective construction of the new distribution network is completed; The step S2 comprises the following steps: Step S21: Select the heavy overload data of the distribution network for preprocessing, calculate the user's daily average load curve and the daily average load rate curve, and lay the foundation for the following index calculation. The calculation formula is as follows: In the formula, S ki (t) is the load value of the kth user at time t on the i-th day, is the average load value of the kth user at time t within the day, is the average load rate of the distribution network at time t within a day, n is the number of heavily overloaded days, m is the number of users of the distribution network, t is 1, 2, …, T, S N is the rated capacity of the distribution network; Step S22: Calculate the influence of each user's load on the load rate of the distribution network; (1) Calculation of change trend Calculate the impact of each user's load change on the distribution network load rate, and quantify the trend of each user's load affecting the distribution network load rate. The larger the value, the greater the actual impact on the distribution network load rate change trend; 1) In order to eliminate the impact of different dimensions of load and load rate, the user's daily average load curve and daily average load rate curve are standardized respectively. The calculation formula is as follows: In the formula, μ s is the mean of the average daily load of users, σ s is the variance of the average daily load of users, s k (t) is the average daily load of users The standardized value of , T is the sampling time of the daily load; In the formula, μ L is the average daily load factor of users, σ L is the variance of the average daily load rate of users, l(t) is the average daily load rate of users The standardized value of , T is the sampling time of the daily load; 2) Using the standardized load and load rate data, calculate the impact of user load changes on the load rate of the distribution network. The calculation formula is as follows: In the formula, v k (t) is the influence coefficient of the kth user load change on the distribution network load rate, s k ′(t) is the derivative of the average daily load of users after standardization, l′(t) is the derivative of the average daily load rate of the distribution network after standardization; (2) Numerical ratio calculation Calculate the impact of each user's load on the distribution network load rate, and quantify the proportion of each user's load affecting the distribution network load rate. The larger the value, the greater the actual impact on the distribution network load rate numerical ratio. The formula is as follows: In the formula, ω k is the influence coefficient of the kth user load size on the load rate of the distribution network; (3) Calculation of impact Select the heavy overload period t i to j , using the change and size of user load to calculate the impact on the load rate of the distribution network during this period of time, the calculation formula is as follows: Where U k t i to j The impact value of the kth user on the load rate of the distribution network during the heavy overload period; Step S23: sorting the impact values ​​of each user on the load rate of the distribution network during the heavy overload period, and the users with the highest ranking are the key users to be mined and are also the objects of optimization, construction and transformation; Step S24: Propose corresponding suggestions for the mined user load types; 1) If the key nodes discovered are large industrial loads or general industrial and commercial loads, then consider: ① The power grid company negotiates with relevant users to carry out demand-side response to reduce the demand for power supply during the heavy overload stage of the power grid; ② Configure distributed power sources on the user side with conditions to reduce the power supply demand of the power grid; ③ Configure energy storage on the user side with insufficient conditions to smooth the load demand by shaving peaks and filling valleys; 2) If the key nodes discovered are agricultural loads or residential loads, consider configuring energy storage on the relevant user side to smooth out load demand by shaving peak loads and filling valleys; 3) If the key node discovered is the electric vehicle load, then ① consider configuring energy storage to smooth the load demand by shaving peaks and filling valleys; ② carry out demand-side response and conduct orderly charging.

2. The method for constructing a distribution network based on big data analysis according to claim 1, characterized in that: The step S3 comprises the following steps: Step S31: Complete the on-site condition assessment through meteorological resource assessment, geographic information assessment, and data reference, calculate the feasibility of various optimization construction plans, and provide support for the investor to formulate the optimization construction plan; (1) Meteorological resource assessment 1) Evaluate the solar and wind meteorological resources in the power supply area through meteorological data, calculate the feasibility of distributed power construction in the power supply area, and provide a reference for the establishment of the optimization plan. Taking photovoltaic as an example, the present invention briefly selects the total radiation and sunshine hours indicators to evaluate the solar energy resources in the power supply area, and the calculation is as follows: Where: H is the total radiation in the calculation period, n is the total number of hours in the calculation period, g i is the average total irradiance in the ith hour, h is the time, which is 1 hour, T p The peak sunshine hours in the calculation period; if the measurement unit of H is MJ / m 2 , it needs to be converted into kW / m 2 , 1kW / m 2 =3.6MJ / m 2 ; 2) Check whether there have been extreme weather events such as earthquakes, typhoons, and sandstorms in the power supply area over the years based on meteorological information, and determine whether there is a possibility that the distributed power supply and energy storage station cannot be built in the area due to natural disasters; (2) Geographic Information Assessment 1) Use satellite remote sensing to observe the topography of the site at the key node user to determine whether there are relevant sites around that are suitable for the construction of distributed power sources or energy storage stations; (3) Determine through on-site investigation whether the terrain and topography in the area are suitable for the construction of distributed power generation or energy storage stations; Data reference 1) Clarify the nature and scope of land suitable for the construction of distributed power generation or energy storage; 2) Investigate whether there are any external factors that are not compatible with the construction of distributed power generation or energy storage stations; Step S32: Based on the feasibility of the optimized construction of distributed power sources and energy storage obtained from the on-site condition assessment, several feasible construction implementation plans are formulated. At the same time, by combining the power grid, integrated energy enterprises and users, the final construction implementation plan is established after comprehensively considering the benefits of all parties and the grid regulation effect.

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