A method and system for rural power energy distribution

Abstract

The present application provides a kind of rural electric power energy distribution method, comprising: step S1, the layout of electric power energy in region is analyzed, and the position distribution of existing first electric power energy distribution station is obtained;Step S2, according to the position distribution of first electric power energy distribution station obtained in step S1, and the position distribution of newly added second electric power energy distribution station obtained according to the prediction analysis of electric power energy structure, the electric power energy distribution station in region is carried out 3D visualization modeling, and the second real scene model is formed;Step S3, based on the real scene model formed in step S2, establish electric power energy automatic distribution module, realize the selection of electric power energy transmission line.This rural electric power energy distribution method provided by the present application can improve the regulation and control ability of electric power energy, improve the distribution efficiency of electric power energy, and through real-time monitoring of the load data of power supply line, the switching distribution of power supply line can be efficiently realized, with the advantages of improving energy utilization rate.

Description

Technical Field

[0001] This invention relates to the field of energy distribution, and more particularly to a method and system for rural power energy distribution. Background Technology

[0002] Beautiful villages and rural revitalization require the rational allocation of electricity and energy in rural areas. However, the original rural power lines were not designed and constructed with the huge increase in electricity demand due to the rapid development of rural areas. However, a comprehensive overhaul of the power project would require a lot of manpower and material resources. Therefore, there is an urgent need for a system specifically designed for the rational allocation of rural power energy to avoid spending a lot of manpower, material resources and financial resources on engineering renovation. At the same time, the system can also meet the electricity supply needs of rural construction and development to the greatest extent. Summary of the Invention

[0003] The purpose of this invention is to provide a rural power energy distribution method and system, which aims to solve the problem of low efficiency in existing power energy distribution, effectively avoid the cost of comprehensive power engineering renovation, reduce the cost of rural power energy distribution, and match power energy distribution with rural development.

[0004] To achieve the above objectives, the present invention provides a rural power energy distribution method, comprising: step S1, analyzing the power energy layout within the region to obtain the location distribution of existing first power energy distribution stations; step S2, based on the location distribution of the first power energy distribution stations obtained in step S1 and the location distribution of newly added second power energy distribution stations obtained from the predictive analysis of the power energy structure, performing 3D visualization modeling of the power energy distribution stations within the region to form a second real-scene model; step S3, based on the real-scene model formed in step S2, establishing an automatic power energy distribution module to realize the selection of power energy transmission lines.

[0005] Preferably, the location distribution of the existing first power energy distribution station is obtained by an oblique photogrammetry 3D data acquisition method; the oblique photogrammetry 3D data acquisition method is divided into field work and office work. The field work mainly involves on-site personnel operating drones to acquire aerial oblique data in order to form the location distribution of the existing first power energy distribution station.

[0006] Preferably, the on-site personnel's operation of the drone to acquire aerial tilt data includes the following steps: Step S101, planning n drone flight paths; Step S102, determining the drone's camera angle; the drone's camera shooting angle range is -120° to -30°; wherein, the shooting angle when shooting orthophotos is -90°, and the shooting angle when shooting 3D stereoscopic images is -45°; Step S103, setting the drone's aerial survey overlap; wherein the drone's forward overlap rate and lateral overlap rate are not less than 70% respectively; Step S104, setting the drone's return altitude to ensure that the drone will not collide with obstacles during return; Step S105, controlling the drone to start flying and performing shooting tasks on the surveyed area.

[0007] Preferably, the 3D visualization modeling of power energy distribution stations in the region includes: step S201, using real-scene modeling software to establish a first real-scene model of the location distribution of the existing first power energy distribution stations obtained by drone aerial photography in step S1; step S202, obtaining the location distribution of the second power energy distribution stations based on the analysis and prediction of the power energy structure, and adding the newly added second power energy distribution stations to the first real-scene model to form a second real-scene model.

[0008] Preferably, the predictive analysis of the power energy structure in step S202 includes the weight analysis of indicators affecting power energy distribution in the near term and the prediction of rural power energy structure in the medium and long term; wherein, the weight analysis of indicators affecting power energy distribution in the near term adopts the independent weighting method, and a second power energy distribution station is added in the area corresponding to the indicator with high weight.

[0009] Preferably, the medium- and long-term rural power energy structure prediction using Markov chains includes the following steps: Step S221, determining the power energy transfer probability matrix P; Step S222, determining the initial state probability vector; selecting an initial year, and using the proportion of various energy types in total energy consumption in that year as the component vector, establishing the initial state probability vector S. (0) Step S223: Predict the electricity consumption structure k years from now using a Markov chain. The calculation formula is S. (k) =S (0) ·P; where, according to the electrical energy structure predicted by the Markov chain k years later, in the state probability vector S (k) A second power distribution station will be added to the area corresponding to the larger value.

[0010] Preferably, the automatic power distribution module is an HVAC control module, which is connected to multiple rural power grids. The HVAC control module includes: a sensor unit, which is connected to all power supply lines in each rural power grid, for detecting the load power and power supply line temperature data of each power supply line in each rural power grid; a data transmission unit, one end of which is connected to the sensor unit and the other end of which is connected to the control unit, for transmitting the load power and power supply line temperature data collected by the sensor unit to the control unit; the control unit processes and analyzes the received load power and power supply line temperature data to generate control signals; and a power supply line switching unit, one end of which is connected to the control unit and the other end of which is connected to all power supply lines in each rural power grid, the power supply line switching unit receives the control signals sent by the control unit and switches the power supply lines in the rural power grid according to the control signals to realize the switching and distribution of power supply lines.

[0011] Preferably, the control unit processes and analyzes the received data, and the generated control signals include: a hold control signal and a switch control signal; if the temperature t of the power supply line detected by the sensor unit is lower than the set temperature T of the HVAC control module, the control unit generates a hold control signal, and the power supply line switching unit does not perform the switching operation of the power supply line; if the temperature t of the power supply line detected by the sensor unit is higher than the set temperature T of the HVAC control module, the control unit generates a switch control signal, and the power supply line switching unit performs the switching operation of the power supply line.

[0012] Preferably, the rural power energy distribution method further includes step S4: using the integrated data management module to integrate and analyze the energy data obtained in step S3, and rationally allocate energy flow through the backup network to reduce idle low load and alleviate full load or overload.

[0013] A rural power energy distribution system, applicable to the rural power energy distribution method according to any one of claims 1 to 9, comprises: an HVAC control module, whose input is connected to a high-voltage power grid and whose output is connected to a load display module and each rural power grid respectively; a comprehensive data management module, whose input is connected to each rural power grid and whose output is connected to a distribution network adjustment module, wherein the comprehensive data management module integrates and analyzes the load data of the rural power grid and transmits it to the distribution network adjustment module, and the distribution network adjustment module generates an adjustment signal based on the load data; a negative feedback circuit module, whose input is connected to the distribution network adjustment module, generates a feedback signal based on the received adjustment signal and transmits it to the HVAC control module; the HVAC control module, in conjunction with the feedback signal and load power and power supply line temperature data, generates a control signal to switch and distribute the power supply lines in each rural power grid.

[0014] In summary, compared with the prior art, the rural power energy distribution method and system provided by the present invention have the following beneficial effects: (1) By using the control signal generated by the HVAC control module, the power supply lines in the rural power grid are switched to achieve the switching and distribution of power supply lines, thereby achieving balanced load of the rural power grid; (2) By performing the switching operation of power supply lines through the power supply line switching unit in the HVAC control module, safety accidents caused by exceeding the load limit of the power supply lines are effectively avoided, and the safety of the rural power grid is improved; (3) By setting up a backup network to reasonably allocate energy flow, idle low load is reduced, full load or overload is alleviated, and the utilization efficiency of power energy is improved; (4) The rural power energy distribution system is composed of existing modules, avoiding the manpower, material resources and financial resources spent on engineering transformation, and can also meet the power supply needs of rural construction and development to the greatest extent. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of a rural power energy distribution method provided in an embodiment of the present invention;

[0017] Figure 2 This is a connection diagram of the HVAC control module provided in an embodiment of the present invention;

[0018] Figure 3 This is a modular structure diagram of a rural power energy distribution system provided in an embodiment of the present invention. Detailed Implementation

[0019] The following will refer to the appendices in the embodiments of the present invention. Figure 1 ~Attached Figure 3 The technical solutions in the embodiments of the present invention are clearly and completely described herein. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0020] It should be noted that, in this invention, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only the expressly listed elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0021] like Figure 1 As shown, Figure 1 This invention provides a rural power energy distribution method, comprising the following steps:

[0022] Step S1: Analyze the power energy layout within the region and obtain the location distribution of the existing first power energy distribution station.

[0023] The location distribution of the existing first power distribution station is obtained through oblique photogrammetry 3D data acquisition. This method consists of fieldwork and office work. Fieldwork primarily involves personnel using drones to acquire aerial oblique data to determine the location distribution of the existing first power distribution station. Office work mainly utilizes a high-performance dedicated modeling computer for 3D modeling. After data acquisition, BIM (Building Information Modeling) is used for manual 3D visualization modeling of the first power distribution station within the area.

[0024] Specifically, the process of on-site personnel operating a drone to acquire aerial tilt data includes the following steps:

[0025] Step S101: Plan n drone flight paths; each drone flight path must ensure that the drone can bypass all obstacles while flying along the path to avoid crashing into tall buildings during flight;

[0026] Step S102: Determine the camera angle of the UAV; the shooting angle range of the UAV camera is -120° to -30°; among which, the shooting angle when shooting orthophoto is -90° and the shooting angle when shooting 3D stereoscopic image is -45°. Therefore, when planning the UAV flight path, it is necessary to go beyond the measurement range of the UAV camera to ensure that the UAV can completely photograph the first power energy distribution station in the measured area.

[0027] Step S103: Set the overlap of UAV aerial survey; wherein the forward overlap rate and the lateral overlap rate of the UAV are not less than 70% respectively, to ensure that the pictures taken by the UAV include all the first power energy distribution stations in the survey area; wherein, the forward overlap rate refers to the probability that the first picture taken by the UAV overlaps with the second picture when the UAV moves forward to take pictures along a flight path; the lateral overlap rate refers to the probability that the picture taken by the UAV along the first flight path overlaps with the picture taken along the second flight path.

[0028] Step S104: Set the drone's return-to-home altitude to ensure that the drone will not collide with obstacles during its return-to-home process. It should be noted that the drone does not need to perform any filming work during its return-to-home process, so it does not have to follow the drone route planned in step S101. It can fly along the shortest route, but it must be ensured that there are no obstacles on the drone's return-to-home route.

[0029] Step S105: Control the drone to start flying, including: Step S151: Input the aerial photography mission for the first power distribution station in the ground area; Step S152: Start the drone self-test program to confirm the drone connection status, battery level, GPS positioning status, camera status, return point location, whether the drone is close to the survey area, and remote controller speed setting; Step S153: After the self-test program is completed, click the flight button and the drone will start flying.

[0030] According to the n flight routes planned in step S101, the UAV is controlled to perform n flight processes to collect image data of the first power energy distribution station in the ground area, thereby obtaining the location distribution of the first power energy distribution station in the ground area.

[0031] Step S2: Based on the location distribution of the first power energy distribution station obtained in Step S1 and the location distribution of the newly added second power energy distribution station obtained from the predictive analysis of the power energy structure, perform 3D visualization modeling of the power energy distribution stations in the region to form a second real-scene model.

[0032] Furthermore, the 3D visualization modeling of the regional power distribution stations includes:

[0033] Step S201: The location distribution of the existing first power energy distribution station obtained by drone aerial photography in step S1 is used to establish a first real scene model using real scene modeling software (ContextCapture software in this embodiment);

[0034] Step S202: Based on the analysis and prediction of the power energy structure, obtain the location distribution of the second power energy distribution station, and add the newly added second power energy distribution station to the first real scene model to form the second real scene model.

[0035] The predictive analysis of the power energy structure in step S202 is based on the analysis of the optional primary energy sources and potential energy quantities (such as geothermal, water, bioenergy, natural gas, liquefied natural gas and liquefied petroleum gas) in rural areas using geographic information. The predictive analysis of the power energy structure includes the weight analysis of indicators that affect the distribution of power energy in the near term (the indicators include price, development cost, policy, technology level, infrastructure and environmental factors) and the prediction of the rural power energy structure in the medium and long term.

[0036] Furthermore, the weighting analysis of the indicators affecting power energy distribution in the near term employs the independent weighting method. The weights are determined by the strength of collinearity among the indicators. If the first indicator among the indicators affecting power energy distribution in the near term has a strong correlation with other indicators, it indicates that the information contained in the first indicator overlaps significantly with the information contained in other indicators, meaning that the weight of the first indicator will be relatively low. Conversely, if the first indicator among the indicators affecting power energy distribution in the near term has a weak correlation with other indicators, it indicates that the first indicator carries a large amount of information, and other indicators do not contain the information corresponding to the first indicator; therefore, the first indicator should be assigned a higher weight.

[0037] It should be noted that the independence weighting method uses the multiple correlation coefficient R value obtained from regression analysis to represent the strength of collinearity (i.e., the strength of correlation). The larger the R value, the stronger the collinearity, and the lower the weight of the corresponding indicator. Specifically, in one embodiment, there are five recent indicators affecting power energy distribution: price, development cost, policy, technology level, and infrastructure. Price is used as the dependent variable, and the other four indicators are used as independent variables in regression analysis to obtain the first R value of the multiple correlation coefficient for price. Repeating regression analysis for the remaining four indicators yields the second to fourth R values. When calculating the weights using the multiple correlation coefficient R, the reciprocal of the R value, 1 / R, is first obtained, and then normalized to obtain the weight. Based on the indicator weights, a second power energy distribution station is added to the area corresponding to the indicator with the higher weight, thereby improving energy distribution efficiency.

[0038] Furthermore, because the power energy structure is influenced by various factors, such as energy policy, technological level, and energy supply, the relationships between them are complex and difficult to calculate precisely. Therefore, this embodiment uses Markov chains to predict the medium- and long-term rural power energy structure based on historical data on changes in the power energy structure.

[0039] Specifically, the prediction of the medium- to long-term rural power energy structure using Markov chains includes the following steps (in this embodiment, coal, natural gas, and electricity are used as examples):

[0040] Step S221: Determine the power energy transfer probability matrix P.

[0041]

[0042] Step S222: Determine the initial state probability vector. Select an initial year, and use the proportion of each type of energy in the total energy consumption in that year as a component vector to establish the initial state probability vector S. (0) ,

[0043]

[0044] in, These represent the initial state probability vectors for coal, natural gas, and electricity, respectively.

[0045] Step S223: Predict the electricity consumption structure k years from now using a Markov chain. The calculation formula is S. (k) =S (0) ·P (3).

[0046] Among them, based on the electrical energy structure predicted by the Markov chain k years later, in the state probability vector S (k) A second power distribution station is added to the location corresponding to the larger value. Furthermore, the principles for adding the new second power distribution station in the first real-world model include:

[0047] Principle 1: Standardize parameters to determine the scale of the newly added second power distribution station. With the goals of maximizing power energy utilization, management efficiency, and service level, the scale should be determined according to the degree of impact on power distribution business volume, following the method of "selecting parameters to determine the overall scale - setting the standard scale of power distribution stations - determining the number of power distribution stations." In this embodiment, a new second power distribution station is added within the region. The standard scale requirements for this second power distribution station include: one station is required within a power supply area of ​​50 square kilometers; and / or one station is required if the number of power customers exceeds 10,000; and / or one station is required if the length of the distribution line exceeds 100 kilometers; and / or one station manages no more than 50 distribution transformers.

[0048] Principle 2: Unify standards to determine the number of newly added second power distribution stations. In this embodiment, based on the standard for setting up all-purpose power distribution stations and the average number of devices managed by the company's power distribution stations, the number of second power distribution stations is determined by assessing the current standard, including the number of devices managed, the number of employees, and the number of townships served. The total number of second power distribution stations is further calculated based on the standard scale of each station. It should also be noted that stations with fewer than 14 staff members, fewer than 10 employees, fewer than 4,000 electricity customers, a distance of less than 10 kilometers between two stations (service radius not exceeding 30 kilometers), or two or more stations in a township or county will be integrated.

[0049] Step S3: Based on the second real-world model formed in step S2, establish an automatic power energy distribution module to enable the selection of power energy transmission lines.

[0050] In this embodiment, the automatic power distribution module is an HVAC control module 300 (heat power control and regulation module). Specifically, as shown... Figure 2 As shown, the HVAC control module 300 is connected to multiple rural power grids. In this embodiment, taking the connection between the HVAC control module 300 and the first rural power grid 401 as an example, the HVAC control module 300 includes a sensor unit 301, which is connected to all power supply lines in the first rural power grid 401, and is used to detect the load power and power supply line temperature data of each power supply line (including the first power supply line 411 to the nth power supply line 41n) in the first rural power grid 401; a data transmission unit 302, one end of which is connected to the sensor unit 301, and the other end of which is connected to the control unit 303, for transmitting the sensor data. The load power and power supply line temperature data collected by the device unit 301 are transmitted to the control unit 303. The control unit 303 processes and analyzes the received load power and power supply line temperature data and generates control signals. The power supply line switching unit 304 is connected to the control unit 303 at one end and to all power supply lines in the first rural power grid 401 at the other end. The power supply line switching unit 304 receives the control signals sent by the control unit 303 and switches the power supply lines in the first rural power grid 401 according to the control signals to realize the switching and distribution of power supply lines and achieve the purpose of load balancing.

[0051] Furthermore, the control unit 303 processes and analyzes the received data, generating control signals including a hold control signal and a switch control signal. If the temperature t of the power supply line detected by the sensor unit 301 is lower than the set temperature T of the HVAC control module 300 (i.e., t < T), the control signal generated by the control unit 303 is a hold control signal, and the power supply line switching unit 304 does not perform the switching operation on the power supply line. Conversely, if the temperature t of the power supply line detected by the sensor unit 301 is higher than the set temperature T of the HVAC control module 300 (i.e., t > T), the control signal generated by the control unit 303 is a switch control signal, and the power supply line switching unit 304 performs the switching operation on the power supply line, thereby realizing the switching and allocation of power supply lines. This effectively avoids safety accidents caused by exceeding the load limit of the power supply line and improves the safety of the rural power grid. Since the power supply line switching unit 304 is connected to all power supply lines in the first rural power grid 401, the power supply line switching unit 304 performs the power supply line switching operation. The switching and distribution of power supply lines refers to turning off the power supply line whose temperature t is higher than the set temperature T of the HVAC control module 300, and diverting the power energy that originally flowed through the power supply line to other power supply lines that are not overloaded (i.e., power supply lines whose temperature t is lower than the set temperature T of the HVAC control module 300), so as to realize the selection and control of power supply lines, improve the distribution efficiency of power energy and the security of the rural power grid.

[0052] like Figure 1 As shown, the rural power energy distribution method further includes step S4: integrating and analyzing the energy data obtained in step S3 using the integrated data management module 600, and adjusting the input energy in real time. Specifically, the energy data of each energy transmission line is obtained through the HVAC control module 300, and the energy flow is rationally allocated through the backup network, thereby reducing idle low loads and alleviating full load or overload.

[0053] like Figure 3 As shown, Figure 3This is a structural diagram of a rural power energy distribution system module provided by an embodiment of the present invention. This rural power energy distribution system is applicable to the aforementioned rural power energy distribution method. The rural power energy distribution system includes: an HVAC control module 300, whose input is connected to a high-voltage power grid 200, and whose output is connected to a load display module 500 and each rural power grid (including the first rural power grid 401 to the nth rural power grid 40n); a comprehensive data management module 600, whose input is connected to each rural power grid, and whose output is connected to a distribution network adjustment module 700. The comprehensive data management module 600 integrates and analyzes the load data of the rural power grid and transmits it to the distribution network adjustment module 700, which generates an adjustment signal based on the load data; and a negative feedback circuit module 800, whose input is connected to the distribution network adjustment module 700. Based on the received adjustment signal, it generates a feedback signal and transmits it to the HVAC control module 300. The HVAC control module combines the feedback signal with load power and power supply line temperature data to generate a control signal, thereby realizing the switching and distribution of power supply lines in each rural power grid.

[0054] The load display module 500 can display the power information of each power supply line in the rural power grid in real time, and graphically show the electricity demand of the rural power grid. In this embodiment, the load display module 500 uses flowing colors to display the electricity demand of the rural power grid. The flowing colors include red, yellow, green, and dark green. Specifically, red represents full load, yellow represents near load, green represents low load, and dark green represents idle. By setting different flowing colors, staff can more intuitively obtain the electricity demand of each power supply line in the rural power grid, thereby enabling them to promptly identify overloaded lines, rationally add infrastructure, and avoid electrical safety accidents.

[0055] In summary, compared with the prior art, the rural power energy distribution method and system provided by the present invention can improve the regulation capability of power energy, increase the distribution efficiency of power energy, and efficiently realize the switching and distribution of power supply lines by real-time monitoring of the load data of power supply lines, thus having advantages such as improving energy utilization.

[0056] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A method for rural power energy distribution, characterized in that, include: Step S1: Analyze the power energy layout within the region and obtain the location distribution of the existing first power energy distribution station; Step S2: Based on the location distribution of the first power energy distribution station obtained in Step S1 and the location distribution of the newly added second power energy distribution station obtained from the predictive analysis of the power energy structure, perform 3D visualization modeling of the power energy distribution stations in the region to form a second real-scene model. The predictive analysis of the power energy structure includes the weight analysis of indicators affecting power energy distribution in the near term and the prediction of rural power energy structure in the medium and long term; wherein, the weight analysis of indicators affecting power energy distribution in the near term adopts the independent weighting method, and a second power energy distribution station is added in the region corresponding to the indicator with high weight; The prediction of the medium- and long-term rural power energy structure using Markov chains includes the following steps: Step S221: Determine the electrical energy transfer probability matrix P; Step S222: Determine the initial state probability vector; select an initial year, and use the proportion of each type of energy in the total energy consumption in that year as a component vector to establish the initial state probability vector. ; Step S223: Predict the electricity consumption structure k years from now using a Markov chain. The calculation formula is as follows: Among them, based on the electrical energy structure predicted by the Markov chain after k years, in the state probability vector A second power distribution station will be added to the area corresponding to the larger value. Step S3: Based on the real-world model formed in step S2, establish an automatic power energy distribution module to enable the selection of power energy transmission lines; The automatic power distribution module is an HVAC control module (300), which is connected to multiple rural power grids; the HVAC control module (300) includes: The sensor unit (301) is connected to all power supply lines in each of the rural power grids and is used to detect the load power and power supply line temperature data of each power supply line in each of the rural power grids. The data transmission unit (302) is connected to the sensor unit (301) at one end and to the control unit (303) at the other end. It is used to transmit the load power and power supply line temperature data collected by the sensor unit (301) to the control unit (303). The control unit (303) processes and analyzes the received load power and power supply line temperature data to generate control signals; The power supply line switching unit (304) is connected at one end to the control unit (303) and at the other end to all the power supply lines in each rural power grid. The power supply line switching unit (304) receives the control signal sent by the control unit (303) and switches the power supply lines in the rural power grid according to the control signal to realize the switching and allocation of power supply lines.

2. The rural power energy distribution method as described in claim 1, characterized in that, The location distribution of the existing first power energy distribution station is obtained through an oblique photogrammetry 3D data acquisition method. The oblique photogrammetry 3D data acquisition method is divided into field work and office work. The field work mainly involves on-site personnel operating drones to acquire aerial oblique data in order to form the location distribution of the existing first power energy distribution station.

3. The rural power energy distribution method as described in claim 2, characterized in that, The process of having on-site personnel operate a drone to obtain aerial tilt data includes the following steps: Step S101: Plan n drone routes; Step S102: Determine the camera angle of the drone; the camera shooting angle range of the drone is -120° to -30°; wherein, the shooting angle when shooting orthophoto is -90° and the shooting angle when shooting 3D stereoscopic image is -45°. Step S103: Set the overlap of the UAV aerial survey; wherein the forward overlap rate and the lateral overlap rate of the UAV are not less than 70% respectively; Step S104: Set the drone's return-to-home altitude to ensure that the drone will not collide with obstacles during its return-to-home process; Step S105: Control the drone to start flying and perform the shooting task on the area to be measured.

4. The rural power energy distribution method as described in claim 3, characterized in that, The 3D visualization modeling of the regional power distribution station includes: Step S201: Use real-scene modeling software to establish the location distribution of the existing first power energy distribution station obtained through drone aerial photography; Step S202: Based on the predictive analysis of the power energy structure, obtain the location distribution of the second power energy distribution station, and add the newly added second power energy distribution station to the first real-scene model to form the second real-scene model.

5. The rural power energy distribution method as described in claim 1, characterized in that, The control unit (303) processes and analyzes the received data, and generates control signals including: hold control signal and switch control signal; If the temperature t of the power supply line detected by the sensor unit (301) is lower than the set temperature T of the HVAC control module (300), the control unit (303) generates a holding control signal and the power supply line switching unit (304) does not perform the switching operation of the power supply line. If the temperature t of the power supply line detected by the sensor unit (301) is higher than the set temperature T of the HVAC control module (300), the control unit (303) generates a switching control signal, and the power supply line switching unit (304) performs the switching operation of the power supply line.

6. The rural power energy distribution method as described in claim 5, characterized in that, The rural power energy distribution method further includes step S4: using the integrated data management module (600) to integrate and analyze the energy data obtained in step S3, and rationally allocate energy flow through the backup network to reduce idle low load and alleviate full load or overload.

7. A rural power energy distribution system, applicable to the rural power energy distribution method according to any one of claims 1 to 6, characterized in that, include: The HVAC control module (300) has its input connected to the high-voltage power grid (200) and its output connected to the load display module (500) and each rural power grid, respectively. The integrated data management module (600) has its input end connected to each rural power grid and its output end connected to the distribution network adjustment module (700). The integrated data management module (600) integrates and analyzes the load data of the rural power grid and transmits it to the distribution network adjustment module (700). The distribution network adjustment module (700) generates adjustment signals based on the load data. The negative feedback circuit module (800) has its input terminal connected to the power distribution network adjustment module (700). Based on the received adjustment signal, it generates a feedback signal and transmits it to the HVAC control module (300). The HVAC control module (300) includes: a sensor unit (301), which is connected to all power supply lines in each rural power grid, for detecting the load power and power supply line temperature data of each power supply line in each rural power grid; a data transmission unit (302), one end of which is connected to the sensor unit (301) and the other end of which is connected to the control unit (303), for transmitting the load power and power supply line temperature data collected by the sensor unit (301) to the control unit (303); the control unit (303) processes and analyzes the received load power and power supply line temperature data and generates control signals; and a power supply line switching unit (304), one end of which is connected to the control unit (303) and the other end of which is connected to all power supply lines in each rural power grid, the power supply line switching unit (304) receives the control signal sent by the control unit (303) and switches the power supply lines in the rural power grid according to the control signal to realize the switching and allocation of power supply lines.

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