Distribution Network Peak Load Safety Inspection Method and System

Abstract

The present invention discloses a method and system for peak load safety supervision of a distribution network, which relates to the technical field of power grid supervision. It includes Step 1 of creating a regional visualization information map, which includes: obtaining the location data of power supply function sites within the supervision area and respectively importing them into a pre-uploaded GIS map for marking to generate corresponding nodes; obtaining the power grid distribution data between each node and importing it into the GIS map with marked nodes to generate a regional power grid simulation map; allocating a storage space for any one node and recording the corresponding site association data; Step 2 of implementing safety supervision, which includes: obtaining the energy consumption supervision statistical data of authorized units within the supervision area; respectively associating and binding the corresponding energy consumption supervision statistical data to the corresponding blocks in the regional power grid simulation map by administrative region and using them for calling and display; determining the daily / weekly energy consumption peak values of each administrative region according to the historical energy consumption supervision statistical data. This application has the effect of facilitating comprehensive overall management of power grid peak load work by relevant staff.

Description

Technical Field

[0001] This application relates to the technical field of power grid supervision, and particularly to a method and system for peak load safety inspection of a distribution network. Background Art

[0002] Affected by many factors such as the increase in greenhouse gases and the urban heat island effect, the summer temperatures in some regions of the country have reached record highs, which has led to an increased dependence on refrigeration equipment such as air conditioners, and the daily electricity consumption in summer has also reached a peak. The safety and reliability of the distribution network during this stage have faced a major test.

[0003] In order to ensure the safety and reliability of the power grid during peak load periods, the following work can be carried out:

[0004] First, promote the smooth construction of power grid projects and complete the commissioning of expansion and new projects before peak load;

[0005] Second, allocate electric energy in each region and optimize resource allocation, that is, transmit the electric energy in regions with sufficient power generation and energy storage sites to regions with large electricity consumption, industrial heavyweights, and economically active and populous areas through ultra-high voltage power transmission projects.

[0006] In the process of carrying out the above work, there is currently a lack of technology capable of managing the entire distribution network during peak load. Information islands have formed among various units and departments, and it is complicated for relevant staff to coordinate and manage peak load work, occupying a lot of manpower. Therefore, this application proposes a new technical solution. Summary of the Invention

[0007] In order to facilitate relevant staff to comprehensively plan and manage the power grid peak load work, this application provides a method and system for peak load safety inspection of a distribution network.

[0008] In the first aspect, this application provides a method for peak load safety inspection of a distribution network, adopting the following technical solution:

[0009] A method for peak load safety inspection of a distribution network includes:

[0010] Step 1. Create a regional visualization information map, which includes:

[0011] Obtain the location data of power supply function sites in the inspection area, and import them into the pre-uploaded GIS map for marking to generate corresponding nodes; among them, the power supply function sites include power stations, energy storage stations, and substations in operation, newly built, expanded, and under maintenance;

[0012] Obtain the power grid distribution data between each node, import it into the GIS map with marked nodes, and generate a regional power grid simulation map;

[0013] Allocate a storage space for any node and record the corresponding site - related data; among them, the site - related data includes one or more of site operation data, construction data, and maintenance data;

[0014] Step 2: Implement safety supervision, which includes:

[0015] Obtain the energy consumption supervision and statistics data of the authorized units within the supervision area;

[0016] Taking administrative regions as units, respectively associate and bind the corresponding energy consumption supervision and statistics data to the corresponding blocks in the regional power grid simulation diagram for calling and display;

[0017] Determine the daily / weekly energy consumption peak values of each administrative region based on historical energy consumption supervision and statistics data;

[0018] Analyze and evaluate the energy supply load rates on the days, weeks, months, and quarters when the peak values occur based on the historical site - related data of the nodes belonging to each administrative region;

[0019] If the power supply load rate reaches the preset power - limiting threshold, then count the power - limiting duration, and summarize the corresponding energy consumption supervision and statistics data and power supply load rate to generate resource optimization and allocation recommendation data;

[0020] Conduct AI diagnosis on the site - related data of any node, and perform risk investigation and tracking, and peak - load planning analysis for ongoing projects according to the diagnosis results.

[0021] Optionally, the implementation of safety supervision further includes:

[0022] Obtain the production plans of enterprises that meet the statistical conditions within the area corresponding to the node;

[0023] Conduct energy prediction based on the production plan, and calculate the expected energy consumption increase or decrease parameters based on historical energy consumption supervision and statistics data;

[0024] Generate recommended expansion information according to the energy consumption increase or decrease parameters and the design parameters of power supply function sites of various specifications stored in advance;

[0025] Summarize the expected energy consumption increase or decrease parameters and the recommended expansion information as resource optimization and allocation recommendation data.

[0026] Optionally, the conduct of AI diagnosis on the site - related data of any node includes:

[0027] Obtain the operation data of the nodes in operation, compare it with the preset standard data, and generate a diagnosis result;

[0028] Obtain the images of power facilities during the inspection of the nodes in operation;

[0029] Based on images, risk characteristics are identified to obtain machine recognition results and send them to the bound users, receive feedback, and generate diagnostic results;

[0030] Among them, the image acquisition methods include image collection and uploading through drones / personal terminals equipped with visual units.

[0031] Optionally, the AI diagnosis of the site association data of any node includes:

[0032] Call the construction data of the under-construction node;

[0033] Based on the construction data, analyze the construction progress and estimate the project completion time;

[0034] Identify the downstream nodes of the under-construction node and determine the power consumption administrative region;

[0035] Search for historical data to determine the historical energy consumption peak time of the power consumption administrative region or receive the uploaded custom energy consumption peak time;

[0036] According to the project completion time, judge whether the project is completed before the energy consumption peak time. If so, maintain project progress tracking; if not, output the project delay interference peak shaving information as the diagnostic result.

[0037] Optionally, the peak shaving planning analysis of the under-construction project includes:

[0038] Obtain the product parameters and quantities of private and self-owned power generation facilities in the power consumption administrative region;

[0039] Calculate the maximum self-generated power based on the product parameters and quantities, and output it as the peak shaving plan data.

[0040] Optionally, the peak shaving planning analysis of the under-construction project further includes:

[0041] Obtain the solutions after project delay and identify them;

[0042] If the solution is to adjust the power transmission route of the original power grid structure, obtain the estimated power transmission loss and calculate the economic loss based on the current electricity price;

[0043] Determine the gap power according to the energy consumption increase and decrease parameters;

[0044] If the difference between the gap power and the maximum self-generated power is less than the preset proximity threshold, calculate the unit power loss based on the maximum self-generated power and the economic loss, and define it as the self-generated power compensation data and output it as the peak shaving plan data.

[0045] Optionally, the implementation of safety supervision and inspection further includes:

[0046] Calculate the power transmission loss data between nodes based on the site operation data corresponding to each operating node;

[0047] Bind the power transmission loss data to the corresponding power grid section and use it for calling and display.

[0048] In a second aspect, the present application provides a peak - load safety supervision system for a distribution network, adopting the following technical solution:

[0049] A peak - load safety supervision system for a distribution network includes a cloud server, and the cloud server stores a computer program that can be loaded and executed by a processor to perform any one of the above - mentioned peak - load safety supervision methods for a distribution network.

[0050] In summary, the present application includes the following beneficial technical effects:

[0051] 1. It enables staff to understand the power grid distribution within the supervision area on an electronic map, and staff can retrieve and view the situation of any node (power generation station, energy storage station, substation) at any time;

[0052] 2. Analyze historical data to obtain the historical power supply load rate of each administrative region, and generate resource optimization allocation suggestion data for staff reference to determine whether to expand substations or adjust power distribution;

[0053] 3. Conduct AI supervision on nodes, timely detect and investigate risks in operating nodes; conduct tracking analysis and intelligent planning on under - construction projects to ensure the safety and reliability of peak - load work. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 is the main process schematic diagram of the method of the present application;

[0055] Figure 2 is the process schematic diagram of the step of creating a regional visualization information map;

[0056] Figure 3 is the process schematic diagram of the step of implementing safety supervision. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] The following further elaborates on the present application with reference to the attached... Figures 1 - 3 Make a further detailed description of the present application.

[0058] The embodiments of the present application disclose a peak - load safety supervision method for a distribution network.

[0059] Refer to... Figure 1 , the peak - load safety supervision method for a distribution network includes:

[0060] Step 1: Create a regional visualization information map;

[0061] Step 2: Implement safety supervision.

[0062] Among them, the visualization information map is established on the cloud platform, which docks with the corresponding online management systems of the Energy Bureau, power companies, power project contractors, etc. through various protocols to implement this method.

[0063] Refer to Figure 2 , regarding Step 1, creating a regional visualization information map, which includes:

[0064] S11. Obtain the location data of power supply function sites within the supervision area, and import them into the pre-uploaded GIS map for marking to generate corresponding nodes.

[0065] Among them, the power supply function sites include power generation stations, energy storage stations, and substations in operation, newly built, expanded, and under repair. It can be understood that when the platform capacity is surplus, box-type substations in lower-level communities and streets, and each power tower, etc. can be used as sites to meet the requirements of high-granularity and refined management.

[0066] S12. Obtain the power grid distribution data between each node, and import it into the GIS map with marked nodes to generate a regional power grid simulation map.

[0067] Application example: Bind any node to the directly connected cable. In the UI interface, if the user selects a certain node, then highlight the node and the directly connected cable and display them in another distinguishing color. The advantage of this design is that it can help relevant personnel understand the power distribution relationship more clearly and intuitively. Especially after marking the current direction indication arrows for each cable based on the node function attributes, the power resource allocation information can be read more intuitively.

[0068] S13. Allocate a storage space for any node and record the corresponding site association data.

[0069] Among them, the site association data includes one or more of site operation data, construction data, and maintenance data. Example of operation data: real-time power generation, load rate, and fault details of a power generation station; construction data, that is, the project data of any under-construction power engineering project. The source of this data can be the BIM management platform of the project party, the active report of the project party, or the analysis obtained from the cameras in the project site.

[0070] Refer to Figure 3 , Step 2, safety supervision implementation, which includes:

[0071] S21. Obtain the energy consumption supervision and statistical data, that is, power consumption data, of the authorized units (such as the Energy Bureau, power companies, and statistical bureaus) within the supervision area.

[0072] S22. Taking administrative regions (districts, counties, cities) as units, respectively associate and bind the corresponding energy consumption supervision and statistics data to the corresponding blocks in the regional power grid simulation diagram, and use them for calling and display.

[0073] If the energy consumption supervision and statistics data are displayed in each block on a UI interface of the data dashboard, the display content is updated according to the latest data obtained.

[0074] S23. Determine the daily / weekly energy consumption peaks of each administrative region according to the historical energy consumption supervision and statistics data;

[0075] According to the historical site association data analysis of the nodes to which each administrative region belongs, evaluate the power supply load rates on the days, weeks, months, and quarters when the peaks occur.

[0076] It can be understood that the power supply range of each region is relatively fixed under the condition of unchanged facilities. For example, a comprehensive industrial park uses 2 million kWh of electricity per month. Among them, the daily electricity consumption is less than 60,000 kWh for 7 days, and the electricity consumption is 1.58 million kWh at other times, and the operation data of the nodes in the region indicates full-load operation. Then evaluate the load rate of 90% for 7 days and full load rate at other times.

[0077] S24. If the power supply load rate reaches the preset power limit threshold, count the power limit duration, and summarize the corresponding energy consumption supervision and statistics data and power supply load rate to generate resource optimization allocation suggestion data.

[0078] It can be understood that the power limit policy is issued by the relevant management unit. If this method cannot obtain the latest information in real time to obtain the power limit threshold, it is necessary to upload the design parameters of the power facilities in advance, and the background sets a power limit threshold for power supply load rate analysis, resource optimization suggestions, etc.

[0079] S25. Conduct AI diagnosis on the site association data of any node, and conduct risk investigation and tracking, and analysis of the peak load planning of the under-construction projects according to the diagnosis results.

[0080] According to the above settings, this method:

[0081] 1. It can enable the staff to understand the power grid distribution in the supervision area on an electronic map, and the staff can view the situation of any node (power generation station, energy storage station, substation) at any time;

[0082] 2. Analyze the historical data to obtain the historical power supply load rates of each administrative region, and generate resource optimization allocation suggestion data for the staff to refer to and judge whether to expand the substation and adjust the power distribution;

[0083] 3. Conduct AI supervision on the nodes, timely discover and investigate the risks of the operating nodes; conduct tracking analysis on the under-construction projects and make intelligent planning to ensure the safety and reliability of the peak load work.

[0084] In addition to the energy consumption supervision and statistics data, the power supply load rate, and the power cut duration, the above-mentioned resource optimization allocation recommendation data also includes:

[0085] Obtain the production plans of enterprises that meet the statistical conditions (quarterly electricity consumption up to standard or above-scale) in the area corresponding to the node; Example: Open the account registration permission for electricity use in the area, and standardize and guide enterprises to actively report their quarterly and annual production plans.

[0086] Conduct energy forecasting based on the production plan, and calculate the expected energy consumption increase or decrease parameters based on the historical energy consumption supervision and statistics data; Example: If the production plan for the third quarter of 2023 is 1.5 times that of the second quarter, then the expected energy consumption is 1.5 times that of the second quarter, and the expected energy consumption increase or decrease parameters can be calculated based on the historical electricity consumption.

[0087] Generate recommended expansion information based on the energy consumption increase or decrease parameters and the design parameters of power supply function sites of various specifications stored in advance; Example: If the expected energy consumption increase is greater than the designed power transmission capacity of a substation of the smallest specification, it is recommended to expand a substation of a higher level.

[0088] The expected energy consumption increase or decrease parameters and the recommended expansion information are summarized into the resource optimization allocation recommendation data.

[0089] According to the above settings, this method can link high-power-consuming enterprises in the administrative region, and more accurately give recommendations in combination with their production plans, etc., to ensure the smooth progress of industrial production during peak load periods and reduce the restrictions of power cuts on economic growth.

[0090] In another embodiment of this method, perform AI diagnosis on the site association data of any node, which includes:

[0091] Obtain the operation data of the operating node, compare it with the preset standard data, and generate a diagnosis result;

[0092] Obtain the images of power facilities during the inspection of the operating node;

[0093] Perform risk feature recognition based on the images, obtain the machine recognition result and send it to the bound user, receive the feedback, and generate a diagnosis result; that is, identify the feedback and judge whether the recognition result needs to be adjusted.

[0094] Among them, the image acquisition method includes image collection and upload by an unmanned aerial vehicle / personal terminal equipped with a vision unit. Special examples of risks: damage to cables, rupture characteristics of electrical structures.

[0095] According to the above settings, on the one hand, it can facilitate the on-site operation staff to quickly complete the inspection work, on the other hand, record the actual situation during the inspection process, use image recognition technology to detect leaks, and at the same time can also keep records for accountability in case of safety accidents.

[0096] Based on the above, the aforementioned risk tracking, that is, after discovering a safety risk, performing maintenance tracking and recording the maintainer, maintenance time, and maintenance result.

[0097] The above is for nodes that are already in operation. For under-construction power projects, AI diagnosis is performed on the site association data of the corresponding nodes, which includes:

[0098] Call the construction data of the under-construction node;

[0099] Based on the construction data, analyze the construction progress and estimate the project completion time; Example: Call the progress tracking record of the construction party's BIM system. The original planned duration is 5 months. 3 months have passed since the start time of the project, and the project progress is 30%. Then it is estimated that the project will be completed in the seventh month after the current time;

[0100] Identify the downstream nodes of the under-construction node and determine the electricity administrative region; among them, the downstream node refers to the node that receives the electric energy sent by the under-construction node;

[0101] Search for historical data to determine the historical energy consumption peak time of the electricity administrative region or receive the custom energy consumption peak time uploaded;

[0102] Based on the project completion time, judge whether the project is completed before the energy consumption peak time. If so, maintain the project progress tracking; if not, output the project delay interference peak shaving information as the diagnosis result.

[0103] According to the above settings, this method can analyze the project completion time using the construction data uploaded by the under-construction node and combine the historical energy consumption time of the corresponding electricity administrative region to diagnose whether the project will affect the peak shaving work.

[0104] In another embodiment of this method, after the project delay interferes with peak shaving, analyze the peak shaving plan for the under-construction project, which includes:

[0105] Obtain the product parameters and quantities of private and self-owned power generation / storage facilities in the electricity administrative region; It can be understood that enterprises, especially large manufacturing enterprises, often prepare their own generators to ensure production safety, and even build energy storage stations using technologies such as flow battery technology.

[0106] Calculate the maximum self-generated electricity based on the product parameters and quantities and output it as the peak shaving plan data.

[0107] According to the above settings, this method will count the self-generated electricity capacity of the corresponding administrative region after discovering the project delay and output it, so as to help the staff as a reference when arranging how to solve the impact brought by the project delay, which is helpful for making full use of private resources and coordinating in advance to ensure the implementation of peak shaving work.

[0108] Based on the above, this method further includes:

[0109] Obtain the solution after the project extension actively uploaded by the staff and perform (graphic, audio) recognition.

[0110] If the solution is to adjust the power transmission route of the original power grid structure, obtain the estimated power transmission loss and calculate the economic loss based on the current electricity price. It can be understood that there are multiple power transmission paths at the power transmission nodes, but generally some will not be switched because the power transmission loss is relatively large under factors such as long-distance allocation.

[0111] In this embodiment, define the path with the largest loss or do not include about 5%-15% of its power transmission capacity in the node full-load parameter.

[0112] Based on the above: Determine the shortage power according to the energy consumption increase and decrease parameter; because the energy consumption increase and decrease parameter is mainly industrial electricity consumption and does not consider the increase and decrease of civil electricity consumption, so the shortage power here is an estimated value, such as: the estimated daily / weekly / monthly shortage power.

[0113] If the difference between the (daily average, weekly average, monthly average) shortage power and the (daily average, weekly average, monthly average) maximum self-generated power is less than the preset proximity threshold, calculate the unit power loss based on the maximum self-generated power and the economic loss. For example: economic loss / maximum self-generated power = unit power loss, and define it as the self-generated power compensation data output as the peak shaving plan data.

[0114] The above is to reasonably distribute the economic loss caused by remote power transmission to private enterprises in the form of subsidies, fully encouraging the rational use of private resources and reducing the power supply pressure; after all, the cross-regional allocation process involves many aspects and will affect the electricity consumption of other regions. A typical example is: the power generation in the inland is allocated to the east, but the electricity consumption of many local enterprises is restricted instead.

[0115] In another embodiment of this method, considering the power transmission loss pointed out above, the safety supervision implementation is set to further include:

[0116] Calculate the power grid power transmission loss data between nodes according to the site operation data corresponding to each operating node; example: The K1 node transmits 100,000 degrees of electricity per week, and the k2 node receives 96,000 degrees, then the loss is 4,000 degrees, and the loss rate is 4%.

[0117] Bind the power transmission loss data to the corresponding power grid section and use it for calling and display.

[0118] On the one hand, the above data can be used to present in the corresponding power grid section on the data dashboard, facilitating the staff on duty to understand the losses of each distribution network; on the other hand, it can also be provided for the aforementioned analysis of self-generated point compensation.

[0119] The embodiment of the present application also discloses a peak load safety supervision system for a distribution network.

[0120] The peak load safety supervision system for a distribution network includes a cloud server, and the cloud server stores a computer program that can be loaded and executed by a processor to perform any one of the above-mentioned peak load safety supervision methods for a distribution network.

[0121] The above are all preferred embodiments of the present application. Without limiting the protection scope of the present application accordingly, therefore: Any equivalent changes made according to the structure, shape, and principle of the present application shall be covered within the protection scope of the present application.

Claims

1. A method for peak load safety supervision of a distribution network, characterized in that, Including: Step 1: Create a regional visualization information map, which includes: Obtain the location data of power supply function sites within the supervision area, and import them into the pre-uploaded GIS map for marking respectively to generate corresponding nodes; among them, the power supply function sites include power stations, energy storage stations, and substations in operation, under construction, under expansion, and under maintenance; Obtain the power grid distribution data between each node, and import it into the GIS map with marked nodes to generate a regional power grid simulation map; Allocate a storage space for any one node and record the corresponding site association data; among them, the site association data includes one or more of site operation data, construction data, and maintenance data; Step 2: Implement safety supervision, which includes: Obtain the energy consumption supervision statistical data of authorized units within the supervision area; Taking administrative regions as units, respectively associate and bind the corresponding energy consumption supervision statistical data to the corresponding blocks in the regional power grid simulation map for calling and display; Determine the daily / weekly energy consumption peak values of each administrative region according to the historical energy consumption supervision statistical data; Analyze and evaluate the energy supply load rates of the peak days, weeks, months, and quarters according to the historical site association data of the nodes to which each administrative region belongs; If the power supply load rate reaches the preset power limit threshold, then count the power limit duration, and summarize the corresponding energy consumption supervision statistical data and energy supply load rate to generate resource optimization allocation recommendation data; Conduct AI diagnosis on the site association data of any one node, and conduct risk investigation and tracking and peak load planning analysis of under-construction projects according to the diagnosis results.

2. The peak load safety supervision method for a distribution network according to claim 1, wherein, The implementation of the safety supervision also includes: Obtain the production plans of enterprises that meet the statistical conditions within the area corresponding to the node; Conduct energy prediction based on the production plan, and calculate the expected energy consumption increase or decrease parameters based on the historical energy consumption supervision statistical data; Generate recommended expansion information according to the energy consumption increase or decrease parameters and the design parameters of various specifications of power supply function sites stored in advance; The expected energy consumption increase or decrease parameters and the recommended expansion information are summarized into resource optimization allocation recommendation data.

3. The method for peak load safety supervision of a distribution network according to claim 1, wherein The AI diagnosis of the site association data of any one node includes: Obtain the operation data of the operating node, compare it with the preset standard data, and generate a diagnosis result; Obtain the images of power facilities during the inspection of the operating node; Conduct risk feature recognition based on the images, obtain the machine recognition result and send it to the bound user, receive the feedback, and generate a diagnosis result; Among them, the image acquisition method includes image acquisition and uploading through an unmanned aerial vehicle / personal terminal equipped with a vision unit.

4. The method for peak load safety supervision of a distribution network according to claim 1, wherein, The AI diagnosis of the site association data of any one node includes: Call the construction data of the under-construction node; Conduct construction progress analysis based on the construction data and estimate the project completion time; Identify the downstream nodes of the under-construction node and determine the electricity-consuming administrative region; Search for historical data to determine the historical energy consumption peak time of the electricity-consuming administrative region or receive the uploaded custom energy consumption peak time; Judge whether the project is completed before the energy consumption peak time according to the project completion time. If so, maintain the project progress tracking; if not, output the project delay interference peak load information as the diagnosis result.

5. The method for peak load safety supervision of a distribution network according to claim 4, wherein The peak load planning analysis of the under-construction project includes: Obtain the product parameters and quantities of private and self-owned power generation facilities in the electricity-consuming administrative region; Calculate the maximum self-generated power according to the product parameters and quantity, and output it as the data for the peak load shaving plan.

6. The method for peak load safety supervision of a distribution network according to claim 5, characterized in that The peak load shaving planning analysis of the construction project also includes: Obtain the solutions after the project extension and identify them; If the solution is to adjust the power transmission route of the original power grid structure, obtain the estimated power transmission loss and calculate the economic loss based on the current electricity price; Determine the shortage of electricity according to the energy consumption increase and decrease parameters; If the difference between the shortage of electricity and the maximum self-generated power is less than the preset proximity threshold, calculate the unit power loss based on the maximum self-generated power and the economic loss, and define it as the self-generated power compensation data and output it as the data for the peak load shaving plan.

7. The method for peak load safety supervision of a distribution network according to claim 6, wherein: The implementation of safety supervision also includes: Calculate the power grid power transmission loss data between nodes according to the site operation data corresponding to each operating node; Bind the power transmission loss data to the corresponding power grid section and use it for calling and displaying.

8. A peak-load safety supervision system for a distribution network, characterized in that: It includes a cloud server, and the cloud server stores a computer program that can be loaded and executed by a processor, such as any one of the power distribution network peak load shaving safety supervision methods in claims 1 to 7.

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