Distribution network operation optimization method, system and equipment based on contact point, medium and product

Abstract

The invention relates to the technical field of electric power systems, and discloses a contact point-based distribution network operation optimization method, system, device, medium and product, and the method comprises the steps: obtaining CIM model data of a target power grid region system to recognize the current contact point position distribution, and recognizing a to-be-optimized contact point path; according to a plurality of remote control switches in a to-be-optimized contact point path, a new contact point candidate set is determined, a target contact point is screened out from the new contact point candidate set, and the to-be-optimized contact point path is reconstructed according to the target contact point, so that intelligent screening and path reconstruction of contact points can be completed without manual field investigation. According to the method, the working efficiency is greatly improved, the optimal contact point adjustment scheme can be quickly found, and meanwhile, multi-dimensional screening is carried out on the new contact points by combining the user data and the operation data, so that accurate optimization of the selected target contact point on the operation mode of the power distribution network is ensured.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a method, system, equipment, medium and product for optimizing distribution network operation based on tie points. Background Technology

[0002] In the operation of a distribution network, the line tie points, as the core nodes for line interconnection, directly affect the power supply reliability, operational economy, and load dispatch flexibility of the distribution network. Most existing tie points in the distribution network were set during the initial planning stages. With the growth of regional load, the integration of new energy sources, and changes in user electricity consumption characteristics, the locations of these original tie points are prone to mismatch with actual operational needs. For example, some lines may have excessively high load rates, excessively long power supply distances leading to increased line losses, and insufficient capacity to absorb new energy sources.

[0003] Traditional distribution network operation optimization relies heavily on manual analysis of line topology and operational data. Manually identifying the optimization potential of tie points requires meticulous verification of multi-dimensional data, including line interconnections, load rates, line losses, and user distribution. This process is not only labor-intensive and inefficient but also prone to oversights due to the complexity of the data, making it difficult to quickly find the optimal tie point adjustment scheme. Furthermore, manual analysis cannot comprehensively consider the multifaceted impact of tie point adjustments on the power grid, potentially leading to new operational problems after the optimization plan is implemented, such as overload on opposite lines, upgraded user number management, and excessive renewable energy penetration, hindering precise optimization of the distribution network operation. Summary of the Invention

[0004] In view of this, in order to solve the above-mentioned technical problems, the present invention provides a method, system, device, medium and product for optimizing the operation of distribution networks based on contact points.

[0005] The first aspect of this invention provides a distribution network operation optimization method based on contact points, comprising:

[0006] Acquire CIM model data, user data, and operational data of the target power grid area system;

[0007] The current contact point location distribution is identified based on the CIM model data, and the contact point path to be optimized is identified based on the current contact point location distribution.

[0008] Based on multiple remote control switches in the contact point path to be optimized, a new set of contact point candidates is determined;

[0009] Based on the user data and the operational data, target contact points are selected from the new contact point candidate set;

[0010] Based on the target contact point, the path of the contact point to be optimized is reconstructed to generate a contact point optimization scheme.

[0011] In one embodiment, the step of identifying the current contact point location distribution based on the CIM model data, and identifying the contact point path to be optimized based on the current contact point location distribution, includes:

[0012] Based on the CIM model data, determine the line topology data;

[0013] Based on the line topology data, determine the location distribution of the connection points of each circuit in the target power grid area system;

[0014] Based on the location distribution of the connection points, for each line connection point, the distance from the connection point to the outgoing switch of each side line is determined, as well as the jurisdiction of the power supply station to which each side line belongs.

[0015] If the distance from the connection point to the outgoing line switch on either side is greater than or equal to a preset distance threshold, or if the power supply stations of the lines corresponding to the connection point are different, then the connection point will be marked as a connection point to be optimized.

[0016] Based on the distance from the connection point to be optimized to the outgoing line switches on each side, the line segment between the outgoing line switch on the side with the longest distance and the connection point to be optimized is selected as the connection point path to be optimized.

[0017] In one embodiment, determining a new candidate set of contact points based on multiple remote control switches in the contact point path to be optimized includes:

[0018] Using the midpoint of the path to be optimized as the reference starting point, the remote control switches on the path to be optimized are traversed sequentially from the reference starting point toward the path to be optimized. Each remote control switch traversed is taken as a new candidate contact point, and the new candidate contact point set is formed.

[0019] In one embodiment, the step of selecting target contact points from the new contact point candidate set based on the user data and the operational data includes:

[0020] For each new candidate connection point in the new candidate connection point set, the operational indicators of the new candidate connection point after its commissioning are determined based on the user data and the operational data; wherein, the operational indicators include at least one of the following: number of transferred distribution transformers, line overload rate, theoretical line loss reduction, power supply radius reduction, user management level, dual-power user coverage rate, number of users, new energy penetration rate, and non-theoretical line loss reduction rate.

[0021] Based on the operational indicators, new candidate contact points that meet the preset operational indicator conditions are selected as the target contact points.

[0022] In one embodiment, the step of reconstructing the contact point path to be optimized based on the target contact point to generate a contact point optimization scheme includes:

[0023] Replace the contact points in the contact point path to be optimized with the target contact point, and update the load transfer path of each side line based on the replaced contact point to obtain the updated load transfer path as the contact point optimization scheme.

[0024] In one embodiment, after reconstructing the contact point path to be optimized based on the target contact point to generate a contact point optimization scheme, the method further includes:

[0025] The optimization scheme for the contact points is visualized by stitching together a map and a single-line graph.

[0026] Secondly, the present invention also provides a distribution network operation optimization system based on a contact point, comprising:

[0027] The data acquisition module is used to acquire CIM model data, user data, and operational data of the target power grid area system;

[0028] The contact point determination module is used to identify the current contact point location distribution based on the CIM model data, and to identify the contact point path to be optimized based on the current contact point location distribution.

[0029] The new contact point candidate module is used to determine a new contact point candidate set based on multiple remote control switches in the contact point path to be optimized.

[0030] The new contact point filtering module is used to filter target contact points from the new contact point candidate set based on the user data and the operation data.

[0031] The connection path optimization module is used to reconstruct the connection point path to be optimized based on the target connection point, and generate a connection point optimization scheme.

[0032] Thirdly, the present invention also provides an electronic device, the electronic device including a memory and a processor, the memory storing a computer program, the computer program being executed by the processor causing the processor to perform the steps of the network operation optimization method based on the contact point as described in the first aspect.

[0033] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the steps of the junction point-based distribution network operation optimization method as described in the first aspect.

[0034] Fifthly, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein, when the program instructions are executed by a computer, the computer performs the steps of the contact point-based distribution network operation optimization method as described in the first aspect.

[0035] As can be seen from the above technical solutions, this invention identifies the current location distribution of tie points by acquiring CIM model data of the target power grid area system and identifies the tie point paths to be optimized. Based on multiple remote control switches in the tie point paths to be optimized, a new set of tie point candidates is determined. Target tie points are selected from the new set of candidate tie points, and the tie point paths to be optimized are reconstructed based on the target tie points. Thus, intelligent selection and path reconstruction of tie points can be completed without manual on-site inspection, greatly improving work efficiency and quickly finding the optimal tie point adjustment scheme. At the same time, by combining user data and operational data, new tie points are screened from multiple dimensions, thereby ensuring that the selected target tie points achieve accurate optimization of the distribution network operation mode. Attached Figure Description

[0036] 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.

[0037] Figure 1 This is an application environment diagram of a distribution network operation optimization method based on a contact point, provided in an embodiment of the present invention.

[0038] Figure 2 A flowchart of a distribution network operation optimization method based on a contact point provided in an embodiment of the present invention;

[0039] Figure 3 This is a schematic diagram of the structure of a distribution network operation optimization system based on a contact point, provided in an embodiment of the present invention.

[0040] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0041] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Current technologies for optimizing distribution network operation rely on manual analysis, requiring the processing of multi-dimensional information such as line topology, operational data, and user data. This is labor-intensive, inefficient, and prone to oversights. The lack of systematic tie-point selection criteria makes it difficult to quickly and accurately identify tie-points with optimization potential and suitable new tie-point locations. Furthermore, the comprehensive impact of tie-point adjustments on distribution network load rate, line loss, power supply distance, renewable energy penetration, and user management is not fully considered, making implementation risks inherent in optimization solutions. Finally, the absence of standardized optimization solution output and visualization methods hinders business personnel from quickly understanding and implementing optimization solutions.

[0043] To address the shortcomings of existing technologies, embodiments of this application provide a distribution network operation optimization method based on contact points, which can be applied to, for example... Figure 1 In the application environment shown, terminal 101 communicates with server 102 via a network. A data storage system can store the data that server 102 needs to process. The data storage system can be integrated onto server 102 or placed on a cloud or other network server. Terminal 101 or server 102 executes a distribution network operation optimization method based on tie points, which includes: acquiring CIM model data, user data, and operational data of the target power grid area system; identifying the current tie point location distribution based on the CIM model data; identifying the tie point path to be optimized based on the current tie point location distribution; determining a new tie point candidate set based on multiple remote control switches in the tie point path to be optimized; selecting the target tie point from the new tie point candidate set based on the user data and operational data; and reconstructing the tie point path to be optimized based on the target tie point to generate a tie point optimization scheme.

[0044] Terminal 101 can be, but is not limited to, various personal computers, laptops, smartphones, and tablets.

[0045] Server 102 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides cloud computing services.

[0046] like Figure 2 As shown, this application provides a distribution network operation optimization method based on contact points, which is applied to... Figure 1Taking terminal 101 or server 102 as an example, the explanation includes the following steps S1 to S5. Wherein:

[0047] Step S1: Obtain CIM model data, user data, and operational data of the target power grid area system.

[0048] The target power grid area system refers to the distribution network area that requires operational optimization. The CIM (Common Information Model) is a standardized power system information modeling specification used to uniformly describe distribution network equipment, topology, and operational relationships.

[0049] The CIM model data primarily originates from the equipment center system, and this data is collected and synchronized in real-time or periodically through system interfaces. The CIM model stores detailed data on the distribution network's line topology, including node connections, equipment attributes, and operational status. By parsing the CIM model, complete distribution network structure data can be extracted, including key information such as line connection methods, segmentation information, and power supply range. Based on these parsing results, further analysis can yield basic information for each 10kV line, such as line length, load capacity, and detailed parameters of connected distribution transformers and switching equipment.

[0050] User data is primarily collected and aggregated through the marketing management system, including detailed information on electricity customers (such as user type, electricity load characteristics, etc.), the installed capacity and connection location of distributed photovoltaic systems, and the ledger and operational data of charging piles (stations). Based on the hierarchical topology between users, distribution transformers, and lines, a systematic analysis and statistics are conducted on the scale of new energy equipment connected to each 10kV line and the distribution of various types of electricity customers, thereby comprehensively understanding the resource structure and electricity consumption characteristics at the line level.

[0051] Operational data is primarily collected through a highly automated SCADA (Supervisory Control and Data Acquisition) system. This system can monitor various key equipment in the distribution network lines in real time, including outgoing switches and remote-controlled switching devices. Specific data collected includes real-time current values ​​and corresponding timestamps. Based on this real-time data, the system further performs multi-dimensional analysis and evaluation of the line load rate, providing data support for judging the power grid's operational status and making scheduling decisions.

[0052] Step S2: Identify the current contact point location distribution based on the CIM model data, and identify the contact point path to be optimized based on the current contact point location distribution.

[0053] Among them, the connection point refers to the switching node in the distribution network that can realize load transfer, and its location distribution directly determines the flexibility and reliability of load transfer.

[0054] This application embodiment accurately identifies the locations of connection points in the system by utilizing key information such as the topological attributes and electrical connectivity of switchgear in the CIM model. It then performs a comprehensive analysis based on the specific location distribution of each connection point's feeder. On this basis, connection points without optimization potential are further screened out, effectively narrowing down the optimization scope. Finally, using the screened connection points with optimization value, the paths to be optimized are constructed, providing clear objectives and a basis for subsequent optimization operations.

[0055] Step S3: Determine a new set of candidate contact points based on multiple remote control switches in the contact point path to be optimized.

[0056] Among them, remote control switches refer to switchgear with remote control functions. Their status can be adjusted in real time by the dispatch center, and they are the key execution units for realizing flexible load transfer.

[0057] In this embodiment, candidate switching devices for new contact points can be selected based on the electrical positions of remote control switches on the contact point path to be optimized, thereby forming a new contact point candidate set. The new contact point candidate set includes multiple remote control switches on the contact point path to be optimized.

[0058] Step S4: Based on user data and operational data, select target contact points from the new contact point candidate set.

[0059] Specifically, for each remote control switch in the new candidate contact point set, by comprehensively analyzing its corresponding user data and related operational data, target contact points that meet multi-dimensional operational conditions can be effectively screened. This process not only considers the comprehensiveness and accuracy of the data, but also ensures the feasibility and efficiency of the screening results in actual operation.

[0060] Step S5: Reconstruct the path of the contact point to be optimized based on the target contact point to generate a contact point optimization scheme.

[0061] In this process, the original contact points of the contact point path to be optimized are replaced by the target contact point, and a new path structure with higher transfer flexibility and power supply reliability is constructed to obtain the contact point optimization scheme.

[0062] Specifically, the connection point path to be optimized is reconstructed based on the target connection point to generate a connection point optimization scheme. This includes replacing the connection points in the connection point path to be optimized with the target connection point, and updating the load transfer path of each side line based on the replaced connection points to obtain the updated load transfer path as the connection point optimization scheme.

[0063] In this process, all original contact points in the contact point path to be optimized are deleted, and the target contact point is added as a new contact point. This replaces the original connecting path with a newly created connection pointing to the target contact point, thus achieving a systematic reconstruction of the overall electrical connection path. The new path formed after reconstruction specifically refers to a complete electrical connection channel formed by starting from the local line, establishing a connection through the target contact point, and then reconstructing the connection between the target contact point and the opposite line. Simultaneously, the area between the original contact point and the target contact point is clearly defined as a load transfer zone. All electrical loads within this zone will be smoothly and reliably transferred from their original local line to the opposite line, ultimately forming an updated and optimized load transfer path. This path is the core component of the contact point optimization scheme proposed in this paper.

[0064] The "local line" refers to the upstream power supply line of the branch where the target connection point is located, i.e., the upstream main feeder that directly provides power support to that connection point; while the "opposite line" refers to another independent feeder that is interconnected with the local line through electrical equipment such as tie switches, and the two form an electrical connection at the tie point. When a system fault occurs, users located in the load transfer zone can have their power supply seamlessly restored by the opposite line through the tie point after the faulty section is quickly isolated, thereby significantly improving the continuity and reliability of power supply in the entire area and effectively shortening the power outage time for users.

[0065] It should be noted that, in this embodiment of the application, the current location distribution of tie points is identified by acquiring the CIM model data of the target power grid area system, and the tie point path to be optimized is identified. Based on multiple remote control switches in the tie point path to be optimized, a new tie point candidate set is determined, and the target tie point is selected from the new tie point candidate set. The tie point path to be optimized is reconstructed based on the target tie point. Thus, intelligent selection and path reconstruction of tie points can be completed without manual on-site inspection, which greatly improves work efficiency and can quickly find the optimal tie point adjustment scheme. At the same time, by combining user data and operation data, the new tie points are screened in multiple dimensions to ensure that the selected target tie points achieve accurate optimization of the distribution network operation mode.

[0066] In some embodiments, identifying the current tie point location distribution based on CIM model data, and identifying the tie point path to be optimized based on the current tie point location distribution, includes: determining line topology data based on CIM model data; determining the tie point location distribution of each circuit in the target power grid area system based on the line topology data; determining the distance from the tie point to the outgoing switch of each side of the circuit, and the jurisdiction of the power supply station corresponding to each side of the circuit, for each tie point based on the tie point location distribution; if the distance from the tie point to the outgoing switch of any side of the circuit is greater than or equal to a preset distance threshold (the preset distance threshold is set based on experience or accuracy requirements, such as 5km), or the power supply station corresponding to each side of the circuit is different, then the tie point is marked as a tie point to be optimized; based on the distance from the tie point to be optimized to the outgoing switch of each side of the circuit, the line segment between the outgoing switch of the side of the circuit with the longest distance and the tie point to be optimized is selected as the tie point path to be optimized.

[0067] The CIM model stores complete line topology data. By deeply analyzing this CIM model, the distribution network structure data can be accurately extracted, and detailed analysis can be performed to obtain the basic information of each 10kV line. Furthermore, based on the basic information of the 10kV lines obtained from the CIM model, the location of each line's tie point can be obtained one by one. Using each tie point location as a benchmark, the upstream line to which the tie point belongs can be clearly defined; this line is defined as the local line. The other line connected to the tie point is defined as the opposite line. Each tie point corresponds to an independent record. By matching the basic information of the local and opposite lines, a complete 10kV line connection relationship is finally formed, i.e., the specific distribution of tie point locations.

[0068] For example, cross-jurisdictional power supply station connections can easily lead to difficulties in dispatching and coordination, and reduced fault isolation efficiency. Long-distance connections, on the other hand, exacerbate voltage fluctuations and line losses, affecting power supply reliability. Therefore, if the distance between the current connection point and the outgoing line switches on both sides of the line is less than 5km, the connection point is not considered a connection point to be optimized. If the distance between the current connection point and the outgoing line switch on either side of the line is greater than or equal to 5km, the connection point is marked as a connection point to be optimized. Similarly, if the two lines belong to different power supply stations, the connection point is also marked as a connection point to be optimized. This allows for the accurate location of connection points to be optimized, avoiding power supply risks caused by unclear dispatching responsibilities, delayed maintenance response, or large voltage fluctuations and line losses.

[0069] Since the greater the distance from the connection point to the outgoing switches on each side, the longer the time required to isolate the fault in the corresponding line segment; therefore, after identifying the connection point to be optimized, the distance to the outgoing switches on each side is compared, and the path segment on the farthest side is selected as the object to be optimized, so as to maximize the distance as the optimization priority, ensuring that the optimization scheme reduces the time required for fault isolation and improves the fault response efficiency.

[0070] Understandably, by using the above methods and comprehensively utilizing both the actual physical distance from the connection point to each outgoing switch and the administrative jurisdiction of the power supply station, weak links in the distribution network can be accurately and reliably identified. On this basis, the path segment with the longest electrical distance is taken as the core optimization object, and the reconfiguration scheme of the connection point and the optimization strategy of the switch equipment are systematically planned in a coordinated manner, thereby effectively and practically improving the load transfer capacity and safe operation resilience of the entire distribution network.

[0071] In some embodiments, determining a new candidate set of contact points based on multiple remote control switches in the contact point path to be optimized includes: taking half of the contact point path to be optimized as a reference starting point, sequentially traversing the remote control switches on the contact point path to be optimized from the reference starting point in the direction of the contact point to be optimized, taking each remote control switch traversed as a new contact candidate point, and forming a new candidate set of contact points.

[0072] For example, the initial reference is the line from the connection point to be optimized to its farthest outgoing switch, with half the total distance of that line segment used as the baseline length. Since the connection point to be optimized has been identified, the path from this point to the selected baseline is the path and direction to be optimized. This allows for the use of remote switches with electrical distances closer to the original connection point as new candidate connection points, avoiding delays in power transfer response caused by excessively long candidate connection points. Specifically, starting from this baseline point, topology analysis is performed sequentially along the line towards the original connection point. Each remote switch encountered is identified as a new candidate connection point. Based on these newly found candidate connection points as backup options, and integrating detailed records and data from the line log, a new list of connection point planning schemes is automatically created. This list is comprehensive, covering key information such as the basic parameters and operating status of the line, the configuration of existing connection points, and the location information of new candidate connection points. The location information of the new candidate connection points is obtained by parsing the line's geographical coordinates and the GPS positioning data of the switching equipment.

[0073] Understandably, by traversing the remote control switches on the path of the contact point to be optimized to construct a new candidate set of contact points, not only is the objectivity and operability of the candidate point selection significantly improved, but the optimization scheme also naturally has the capability to support remote control functionality.

[0074] In some embodiments, selecting target contact points from a new contact point candidate set based on user data and operational data includes: for each new contact point candidate in the new contact point candidate set, determining the operational indicators of the new contact point candidate after its commissioning based on user data and operational data; wherein the operational indicators include at least one of the following: number of transferred distribution transformers, line overload rate, theoretical line loss reduction, power supply radius reduction, user management level, dual-power user coverage rate, number of users, renewable energy penetration rate, and non-theoretical line loss reduction rate; and selecting new contact point candidate that meets the preset operational indicator conditions as the target contact point based on the operational indicators.

[0075] The user data includes user management level and number of users, while the operational data includes the number of transferred distribution transformers, line overload rate, theoretical line loss reduction, power supply radius reduction, dual-power user coverage rate, renewable energy penetration rate, and non-theoretical line loss reduction rate.

[0076] The number of transferable distribution transformers is calculated through distribution network topology and load transfer simulation, determining the total number of distribution transformers that can transfer load from the original lines and distribution transformer areas after a new tie point is put into operation. As a key indicator for measuring the load transfer capacity of a tie point, the number of transferable distribution transformers specifically reflects the number of distribution transformers that the candidate point can effectively support and transfer loads in specific scenarios such as system failures or maintenance. It is an important basis for evaluating its emergency load transfer capacity and flexibility.

[0077] The line overload rate is calculated based on the line's rated transmission power, combined with the optimized power flow calculation results of the new tie points, using the formula "actual transmission power of the line ÷ rated transmission power of the line × 100%". The line overload rate reflects the impact of the tie point's connection to the system on the load pressure borne by the existing trunk lines, and is directly related to the stability and safety margin of the power grid operation.

[0078] The theoretical reduction in line loss is calculated using the power flow method and the equivalent resistance method, respectively, for the distribution network before and after the commissioning of a new candidate interconnection point. The difference between the two calculations represents the theoretical reduction in line loss. The theoretical reduction in line loss characterizes the loss reduction efficiency brought about by network structure optimization and is an important parameter for evaluating economic efficiency and energy-saving effects.

[0079] The reduction in power supply radius is calculated using distribution network GIS geographic information and distribution network topology data. The average power supply radius from the user / distribution transformer to the power source is measured before and after the commissioning of the new interconnection candidate point. The difference between these two values ​​represents the reduction in power supply radius. This reduction directly correlates with and affects the improvement in voltage quality for end users, providing clear guidance for improving power supply quality.

[0080] The user management and control level is extracted directly from the user base files of the electricity marketing system and is an inherent level classified according to user importance (industrial enterprises, public welfare, general users, etc.). The dual-power supply user coverage rate is calculated by counting the number of dual-power supply users within the coverage area of ​​a new candidate connection point, dividing by the total number of users within that area, and then multiplying by 100%. These two indicators, user management and control level and dual-power supply user coverage rate, respectively reflect the power supply system's reliability classification and guarantee capabilities for different user groups, and the level of guarantee for continuous and reliable power supply to important loads.

[0081] The number of users is directly calculated from the user ledger of the marketing system and the list of users connected to the distribution transformer, which is the total number of users involved in the power supply coverage and load transfer of the new connection candidate points.

[0082] The renewable energy penetration rate is calculated by dividing the grid-connected installed capacity of renewable energy sources such as photovoltaics and wind power within the coverage area of ​​the connection point by the total distribution transformer capacity / total electricity load of the area, and then multiplying by 100%. The renewable energy penetration rate is used to assess the adaptability and acceptance capacity of the connection point for distributed photovoltaic and other renewable energy power generation, and is a key factor in measuring its degree of green and low-carbon transformation.

[0083] The non-theoretical line loss reduction rate is calculated by first determining the difference between actual and theoretical line losses to obtain the non-theoretical line loss. Then, the non-theoretical line loss is calculated by dividing the difference between the non-theoretical line losses before and after the commissioning of the new connection candidate point by the non-theoretical line loss before the commissioning of the new connection candidate point, and multiplying by 100%. The non-theoretical line loss reduction rate is a key indicator reflecting the effectiveness of metering anomaly management and the level of refined management in the transformer substation area, and is crucial for improving operational management efficiency.

[0084] This application calculates the operational indicators of each new candidate contact point after its deployment and compares these indicators with preset operational indicator conditions to select target contact points that meet the operational indicator conditions. This ensures that the optimization scheme achieves optimal results in multiple dimensions, including safety, economy, reliability, and green and low-carbon development.

[0085] For example, for each new contact point in the new contact point candidate set, after its operation indicators are implemented, the new contact point candidate that meets the preset operation indicator conditions is selected as the target contact point based on the comparison between the operation indicators after implementation and the preset operation indicator conditions.

[0086] The preset operating indicators are reasonable conditions set based on experience for each operating indicator, including no less than 2 transferred distribution transformers, line overload rate not exceeding 80%, theoretical line loss reduction greater than 0, power supply radius shortened by no less than 1000 meters, user management level reduced, dual power supply user coverage rate 0%, number of users not exceeding 5000, new energy penetration rate not exceeding 100%, and non-theoretical line loss reduction rate not less than 8%.

[0087] By comparing the operational indicators of each new candidate contact point after its implementation with the preset operational indicator conditions, target contact points that meet the operational indicator conditions are selected, including:

[0088] (1) The number of transfer transformers after the new connection candidate point is put into operation shall not be less than 2. For the new connection point scheme included in the analysis, according to the topology relationship of the CIM model, it is determined whether the number of normally operating transformers in the transfer area connected to the current connection point after the new connection candidate point is put into operation is less than 2. If it is less than 2, the scheme is determined not to meet the transfer capacity requirement, that is, it does not meet the operational index condition requirement for the number of transfer transformers. Otherwise, it meets the operational index condition requirement for the number of transfer transformers.

[0089] (2) The overload rate of the opposite line after the new candidate connection point is put into operation shall not exceed 80%. For the new connection point scheme included in the analysis, after the optimized transfer area is transferred to the opposite line, the overload rate of the line in the past year shall be calculated. If it exceeds 80%, the scheme shall be determined to not meet the line safety overload requirements, that is, not meet the operational index requirements of the line overload rate. Otherwise, the operational index requirements of the line overload rate shall be met.

[0090] (3) The theoretical line loss decreases after the new candidate connection point is put into operation, that is, the theoretical line loss reduction is greater than 0. For the new connection point scheme included in the analysis, the theoretical loss of the lines on both sides when the new connection point is used as the operating mode is calculated and compared with the theoretical loss of the lines on both sides when the original connection point is used as the operating mode. If the theoretical line loss increases, it is determined that the scheme does not meet the energy-saving optimization requirements, that is, it does not meet the operating index conditions for the theoretical line loss reduction. Otherwise, it meets the operating index conditions for the theoretical line loss reduction.

[0091] (4) The power supply radius of the new candidate connection point is shortened by no less than 1,000 meters after it is put into operation. For the new connection point scheme included in the analysis, the shortened power supply path is calculated when the new connection point is used as the operating mode. If the shortened power supply path is less than 1,000 meters, the scheme is determined not to meet the voltage quality improvement requirements. The shortened power supply path length is the difference between the current connection point and the local outgoing switch and the distance between the new candidate connection point and the opposite outgoing switch after it is put into operation. That is, it does not meet the operating index requirements for the shortened power supply radius. Otherwise, it meets the operating index requirements for the shortened power supply radius.

[0092] (5) The user control level of the opposite line is reduced after the new connection candidate point is put into operation: For the new connection point scheme included in the analysis, if the number of users in the load transfer area plus the number of users on the opposite line results in the upgrade of the user control level of the opposite line, it is defined as the upgrade of the user control level of the opposite line after the new connection candidate point is put into operation. This does not meet the requirement of the user control level reduction, that is, it does not meet the operational index conditions of the user control level. Conversely, it meets the operational index conditions of the user control level.

[0093] Specifically, for users on the opposite side of the line, lines with fewer than 1,000 important users are classified as Level 3 control lines; lines with 1,000 or more but less than 2,000 important users are classified as Level 2 control lines; and lines with 2,000 or more important users are classified as Level 1 control lines. The user level is determined based on a comprehensive assessment of user type (e.g., hospitals, data centers) and power supply reliability requirements. The list of important users, such as industrial power-consuming enterprises, is dynamically updated quarterly by the power grid dispatching department.

[0094] (6) Dual-power user coverage rate is 0%. For new tie-point schemes included in the analysis, if there is dual power supply in the load transfer area, it is defined as the load transfer area having dual power supply, which does not meet the requirement of zero coverage for dual-power users. This indicator aims to ensure that the tie-point optimization scheme only serves single-power users, avoiding power supply path conflicts or reliability degradation for dual-power users due to transfer, that is, not meeting the operational index requirements for dual-power user coverage. Conversely, it meets the operational index requirements for dual-power user coverage.

[0095] (7) The number of users on the opposite line after the new connection candidate point is put into operation shall not exceed 5,000. For new connection point schemes included in the analysis, if the number of users in the load transfer area plus the number of users on the opposite line exceeds 5,000, it is defined as the number of users on the opposite line after the new connection candidate point is put into operation exceeding 5,000, which does not meet the user capacity balance requirement, that is, it does not meet the user number operation index requirement. Conversely, it meets the user number operation index requirement. This threshold is set based on the typical feeder carrying capacity and operation and maintenance management specifications of the distribution network, taking into account both power supply reliability and load development margin.

[0096] (8) The new connection candidate point shall not exceed 100% of the renewable energy penetration rate after its commissioning. For new connection point schemes included in the analysis, if the renewable energy penetration rate after the adjustment of the remote control switch as the new connection point line exceeds 100%, the scheme shall be deemed not to meet the renewable energy absorption capacity constraint requirements, and will cause voltage over-limit, backfeeding, and grid oscillation, seriously threatening the safety of the distribution network. That is, it does not meet the operating index requirements for renewable energy penetration rate. Conversely, it meets the operating index requirements for renewable energy penetration rate. Wherein, renewable energy penetration rate = (total installed capacity of distributed photovoltaic, wind power and other renewable energy sources connected to the line / maximum load capacity of the line) × 100%.

[0097] (9) The reduction in non-theoretical line loss shall not be less than 8%. For new connection point schemes included in the analysis, calculate the theoretical losses of the lines on both sides when the new connection point is used as the operating mode, and compare them with the theoretical losses of the lines on both sides when the original connection point is used as the operating mode. Statistically calculate the reduction in theoretical line loss. It is required that the reduction in non-theoretical line loss after the new connection point is put into operation shall not be less than 8%. If the reduction in non-theoretical line loss after the new connection point is put into operation is less than 8%, the operating index condition requirement for the reduction in non-theoretical line loss is not met. Conversely, if it is greater, the operating index condition requirement for the reduction in non-theoretical line loss is met.

[0098] It should be noted that if the operation criteria of the above-mentioned new contact candidate point meet at least one of the above-mentioned operation indicator conditions, then the new contact candidate point will be used as the new contact point; if none of the above-mentioned new contact candidate points meet all the listed operation indicator conditions, then the operation and maintenance personnel will be notified to manually select a new contact point.

[0099] In some embodiments, after reconstructing the contact point path to be optimized based on the target contact point and generating a contact point optimization scheme, the method further includes: performing a visualization operation on the contact point optimization scheme under map and single-line graph stitching.

[0100] Based on the newly optimized contact point scheme included in this analysis, a combination of maps and single-line graphs is used for stitching and visualization, clearly showing key information such as the local power supply line, the opposite power supply line, and the load transfer area after the new contact candidate point is put into operation. Different colors are used to highlight key parameters, allowing for a direct comparison of the actual geographical locations of the old and new contact points, the shortened power supply distance after the new contact candidate point is put into operation, and the power supply range affected by the scheme adjustment. This comprehensive visualization method aims to provide business personnel with intuitive and comprehensive graphical support for in-depth analysis of the optimization scheme's effectiveness, evaluation of its feasibility and implementation benefits.

[0101] Understandably, by combining standardized list outputs with visual presentations, and relying on intelligent overview maps and single-line diagrams to intuitively display the optimized areas and adjustment effects, business personnel can easily implement the improvements. Through scientific optimization of connection points, line loads can be balanced, line losses reduced, power supply distances shortened, and the capacity for renewable energy absorption improved, achieving a dual improvement in the economic efficiency and reliability of the distribution network operation.

[0102] The following is a specific embodiment to illustrate the process of a distribution network operation optimization method based on a contact point proposed in this application.

[0103] (1) Acquisition of basic power grid data. By connecting the interfaces of multiple business systems, the comprehensive acquisition of multi-dimensional basic data of the distribution network is realized, providing data support for subsequent tie point analysis and optimization. Specifically, this includes: acquiring CIM model data of the single-line diagram of the distribution network based on the equipment center system. The CIM model data stores the line topology data. The distribution network structure data is obtained by parsing the CIM model, and the basic information of each 10kV line is obtained by analysis. Based on the basic information of the 10kV line obtained from the parsed CIM model, the tie position of each line is obtained. The line currently being analyzed is defined as the local line, and the line connected to the tie point is defined as the opposite line. Each tie point corresponds to one record. The local line and the opposite line form a 10kV line tie relationship by matching the basic information of the line.

[0104] (2) Acquisition of distribution network line user data: Based on the marketing management system, the data of electricity customers, distributed photovoltaic and charging pile (station) ledgers are obtained. According to the topological relationship of user-distribution transformer-line, the data of new energy and electricity customers connected to each 10kV line are analyzed.

[0105] (3) Acquisition of distribution network line operation data: Acquire the current data of the outgoing switches and other remote control switches of the distribution network line through the automated SCADA system, including the current value and time, and analyze their load rate.

[0106] (4) Connection point screening and new connection point search analysis. Based on the aforementioned basic power grid data, quantitative screening criteria are set to eliminate connection points with no optimization potential, automatically find reasonable new connection point locations, and generate a list of solutions. Specifically, this includes: preliminary connection point screening: analysis is performed based on the current connection points of the lines, analyzing the distances from the current connection point to the outgoing switches of each side of the line. If the distance from the current connection point to the outgoing switches of both sides of the line is less than 5km, then the connection point will not be included in the subsequent analysis. Analysis is performed on whether the lines on both sides of the current connection point belong to the same power supply station. If there is cross-station connection, it will not be included in the analysis.

[0107] (5) New contact point search analysis: Based on the line from the original contact point to the outgoing switch of the far substation, take half the distance from the original contact point to the outgoing switch of the substation as the basis, and topologically analyze each remote control switch from this half point towards the original contact point. Each remote control switch is defined as a new contact candidate point.

[0108] (6) Judgment analysis after the introduction of new contact candidate points. The specific judgment content after the introduction of new contact candidate points is as follows:

[0109] (6.1) Whether the number of distribution transformers transferred after the new connection candidate point is put into operation is less than 2: Calculate whether the number of distribution transformers operating normally in the transfer area of ​​the new connection candidate point after it is put into operation is less than 2 based on the topology of the CIM model. If it is less than 2, it is defined as the number of distribution transformers transferred after the new connection candidate point is put into operation is less than 2.

[0110] (6.2) Whether the overload rate of the opposite line exceeds 80% after the new connection candidate point is put into operation: For the new connection point scheme included in the analysis, after the optimization transfer area is transferred to the opposite line, calculate whether the overload rate of the line in the past year exceeds 80%. If it exceeds 80%, it is defined as the overload rate of the opposite line exceeding 80% after the new connection candidate point is put into operation.

[0111] (6.3) Does the theoretical line loss increase after the new candidate connection point is put into operation? For the new connection point scheme included in the analysis, calculate the theoretical loss of the lines on both sides when the new connection point is used as the operating mode, and compare it with the theoretical loss of the lines on both sides when the original connection point is used as the operating mode. If the theoretical line loss increases, it is defined as the theoretical line loss increasing after the new candidate connection point is put into operation.

[0112] (6.4) Whether the power supply distance is shortened by less than 1000 meters after the new connection candidate point is put into operation: For the new connection point scheme included in the analysis, calculate the power supply path shortened when the new connection point is used as the operating mode. If the power supply path is shortened by less than 1000 meters, it is defined as the power supply distance shortened by less than 1000 meters after the new connection candidate point is put into operation.

[0113] (6.5) Whether the control of the number of users on the opposite line is upgraded after the new contact candidate point is put into operation: For the new contact point scheme included in the analysis, if the number of users in the load transfer area plus the number of users on the opposite line results in the upgrade of the control of the number of users on the opposite line, it is defined as the upgrade of the control of the number of users on the opposite line after the new contact candidate point is put into operation.

[0114] (6.6) Whether there is a dual power supply in the load transfer area: For the new connection point scheme included in the analysis, if there is a dual power supply in the load transfer area, it is defined as having a dual power supply in the load transfer area.

[0115] (6.7) Does the number of users on the opposite line exceed 5,000 after the new contact candidate point is put into operation? For new contact point schemes included in the analysis, if the number of users in the load transfer area plus the number of users on the opposite line exceeds 5,000, it is defined as the number of users on the opposite line exceeding 5,000 after the new contact candidate point is put into operation.

[0116] (6.8) Whether the new connection candidate point has a new energy penetration rate of over 100% after being put into operation: For the new connection point scheme included in the analysis, if the new energy penetration rate of the remote control switch after the line adjustment of the new connection point exceeds 100%, it is defined as the new connection candidate point having a new energy penetration rate of over 100% after being put into operation.

[0117] (6.9) Whether the reduction of non-theoretical line loss is not less than 8%: For the new connection point scheme included in the analysis, calculate the theoretical loss of the lines on both sides when the new connection point is used as the operating mode, and compare it with the theoretical loss of the lines on both sides when the original connection point is used as the operating mode. Statistically analyze the change of non-theoretical line loss. If the reduction of non-theoretical line loss is less than 8%, then the reduction of non-theoretical line loss of the new connection candidate point is defined as not meeting the requirements.

[0118] (7) Determination of reserve plan: Based on the nine determination items in (6), identify new contact point plans that are feasible to implement as reserve plans according to the aforementioned operational indicator requirements.

[0119] (8) Output of optimization scheme for distribution network operation mode based on connection point adjustment. Based on the reserve scheme in (7) and the judgment content in (6), output a standardized optimization scheme and realize the visualization of the optimization transfer area to support the implementation of the scheme.

[0120] (9) Optimize the visualization of the transfer area: Based on the new contact point scheme included in the analysis, the local line, the opposite line, and the new and old contact points are visualized by using a map and single-line diagram splicing method. The geographical location of the new and old contact points and the shortened power supply distance are displayed intuitively by color marking, providing a visualization means for business personnel to further analyze the optimization scheme.

[0121] Based on the same inventive concept, this application also provides a junction point-based distribution network operation optimization system for implementing the junction point-based distribution network operation optimization method described above.

[0122] The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more tie-point-based distribution network operation optimization system embodiments provided below can be found in the limitations of the tie-point-based distribution network operation optimization method described above, and will not be repeated here.

[0123] like Figure 3As shown in the figure, this application provides a distribution network operation optimization system based on contact points, including: a data acquisition module 100, a contact point determination module 200, a new contact point candidate module 300, a new contact point screening module 400, and a contact path optimization module 500;

[0124] Data acquisition module 100 is used to acquire CIM model data, user data and operation data of the target power grid area system;

[0125] The contact point determination module 200 is used to identify the current contact point location distribution based on CIM model data, and to identify the contact point path to be optimized based on the current contact point location distribution.

[0126] New contact point candidate module 300 is used to determine a new contact point candidate set based on multiple remote control switches in the contact point path to be optimized;

[0127] The new contact point screening module 400 is used to screen target contact points from the new contact point candidate set based on user data and operational data.

[0128] The connection path optimization module 500 is used to reconstruct the connection path to be optimized based on the target connection point and generate a connection point optimization scheme.

[0129] In some embodiments, the contact point determination module 200 is configured to:

[0130] Based on the CIM model data, determine the line topology data;

[0131] Based on the line topology data, determine the location distribution of the connection points of each circuit in the target power grid area system;

[0132] Based on the location distribution of the connection points, for each line connection point, the distance from the connection point to the outgoing switch of each side line is determined, as well as the jurisdiction of the power supply station to which each side line belongs.

[0133] If the distance from the connection point to the outgoing line switch on either side is greater than or equal to the preset distance threshold, or if the power supply stations of the lines on each side corresponding to the connection point are different, then the connection point will be marked as a connection point to be optimized.

[0134] Based on the distance from the connection point to be optimized to the outgoing line switches on each side, the line segment between the outgoing line switch on the side with the longest distance and the connection point to be optimized is selected as the connection point path to be optimized.

[0135] In some embodiments, the new contact point candidate module 300 is used for:

[0136] Using the midpoint of the path to be optimized as the reference starting point, the remote control switches on the path to be optimized are traversed sequentially from the reference starting point toward the path to be optimized. Each remote control switch traversed is taken as a new candidate point for connection and a new candidate set of connection points is formed.

[0137] In some embodiments, the new contact point screening module 400 is used for:

[0138] For each new candidate connection point in the new candidate connection point set, the operational indicators of the new candidate connection point after commissioning are determined based on user data and operational data. Among them, the operational indicators include at least one of the following: number of transferred distribution transformers, line overload rate, theoretical reduction in line loss, reduction in power supply radius, user management level, dual-power user coverage rate, number of users, new energy penetration rate, and non-theoretical reduction in line loss.

[0139] Based on operational indicators, new candidate contact points that meet the preset operational indicator conditions are selected as target contact points.

[0140] In some embodiments, the connection path optimization module 500 is used for:

[0141] Replace the contact points in the contact point path to be optimized with the target contact point, and update the load transfer path of each side line based on the replaced contact point to obtain the updated load transfer path as the contact point optimization scheme.

[0142] In some embodiments, the system further includes a visualization module for visualizing the contact point optimization scheme using a map and single-line graph stitching method.

[0143] It should be noted that, in this embodiment of the application, the current location distribution of tie points is identified by acquiring the CIM model data of the target power grid area system, and the tie point path to be optimized is identified. Based on multiple remote control switches in the tie point path to be optimized, a new tie point candidate set is determined, and the target tie point is selected from the new tie point candidate set. The tie point path to be optimized is reconstructed based on the target tie point. Thus, intelligent selection and path reconstruction of tie points can be completed without manual on-site inspection, which greatly improves work efficiency and can quickly find the optimal tie point adjustment scheme. At the same time, by combining user data and operation data, the new tie points are screened in multiple dimensions to ensure that the selected target tie points achieve accurate optimization of the distribution network operation mode.

[0144] like Figure 4 As shown, this application provides an electronic device 10, which includes a memory 20 and a processor 30. The memory 20 stores a computer program. When the computer program is executed by the processor 30, the processor 30 performs the following steps:

[0145] Acquire CIM model data, user data, and operational data of the target power grid area system;

[0146] Identify the current contact point location distribution based on CIM model data, and identify the contact point path to be optimized based on the current contact point location distribution;

[0147] Based on multiple remote control switches in the contact point path to be optimized, determine a new set of contact point candidates;

[0148] Based on user data and operational data, target contact points are selected from the new contact point candidate set.

[0149] Based on the target contact point, the path of the contact point to be optimized is reconstructed to generate a contact point optimization scheme.

[0150] In some embodiments, processor 30 also performs:

[0151] Based on the CIM model data, determine the line topology data;

[0152] Based on the line topology data, determine the location distribution of the connection points of each circuit in the target power grid area system;

[0153] Based on the location distribution of the connection points, for each line connection point, the distance from the connection point to the outgoing switch of each side line is determined, as well as the jurisdiction of the power supply station to which each side line belongs.

[0154] If the distance from the connection point to the outgoing line switch on either side is greater than or equal to the preset distance threshold, or if the power supply stations of the lines on each side corresponding to the connection point are different, then the connection point will be marked as a connection point to be optimized.

[0155] Based on the distance from the connection point to be optimized to the outgoing line switches on each side, the line segment between the outgoing line switch on the side with the longest distance and the connection point to be optimized is selected as the connection point path to be optimized.

[0156] In some embodiments, processor 30 also performs:

[0157] Using the midpoint of the path to be optimized as the reference starting point, the remote control switches on the path to be optimized are traversed sequentially from the reference starting point toward the path to be optimized. Each remote control switch traversed is taken as a new candidate point for connection and a new candidate set of connection points is formed.

[0158] In some embodiments, processor 30 also performs:

[0159] For each new candidate connection point in the new candidate connection point set, the operational indicators of the new candidate connection point after commissioning are determined based on user data and operational data. Among them, the operational indicators include at least one of the following: number of transferred distribution transformers, line overload rate, theoretical reduction in line loss, reduction in power supply radius, user management level, dual-power user coverage rate, number of users, new energy penetration rate, and non-theoretical reduction in line loss.

[0160] Based on operational indicators, new candidate contact points that meet the preset operational indicator conditions are selected as target contact points.

[0161] In some embodiments, processor 30 also performs:

[0162] Replace the contact points in the contact point path to be optimized with the target contact point, and update the load transfer path of each side line based on the replaced contact point to obtain the updated load transfer path as the contact point optimization scheme.

[0163] In some embodiments, processor 30 also performs:

[0164] The optimization scheme for contact points can be visualized by stitching together maps and single-line diagrams.

[0165] It should be noted that, in this embodiment of the application, the current location distribution of tie points is identified by acquiring the CIM model data of the target power grid area system, and the tie point path to be optimized is identified. Based on multiple remote control switches in the tie point path to be optimized, a new tie point candidate set is determined, and the target tie point is selected from the new tie point candidate set. The tie point path to be optimized is reconstructed based on the target tie point. Thus, intelligent selection and path reconstruction of tie points can be completed without manual on-site inspection, which greatly improves work efficiency and can quickly find the optimal tie point adjustment scheme. At the same time, by combining user data and operation data, the new tie points are screened in multiple dimensions to ensure that the selected target tie points achieve accurate optimization of the distribution network operation mode.

[0166] This application provides a computer-readable storage medium storing a computer program thereon, which, when executed, performs the following steps:

[0167] Acquire CIM model data, user data, and operational data of the target power grid area system;

[0168] Identify the current contact point location distribution based on CIM model data, and identify the contact point path to be optimized based on the current contact point location distribution;

[0169] Based on multiple remote control switches in the contact point path to be optimized, determine a new set of contact point candidates;

[0170] Based on user data and operational data, target contact points are selected from the new contact point candidate set.

[0171] Based on the target contact point, the path of the contact point to be optimized is reconstructed to generate a contact point optimization scheme.

[0172] In some embodiments, the computer program, when executed, also implements:

[0173] Based on the CIM model data, determine the line topology data;

[0174] Based on the line topology data, determine the location distribution of the connection points of each circuit in the target power grid area system;

[0175] Based on the location distribution of the connection points, for each line connection point, the distance from the connection point to the outgoing switch of each side line is determined, as well as the jurisdiction of the power supply station to which each side line belongs.

[0176] If the distance from the connection point to the outgoing line switch on either side is greater than or equal to the preset distance threshold, or if the power supply stations of the lines on each side corresponding to the connection point are different, then the connection point will be marked as a connection point to be optimized.

[0177] Based on the distance from the connection point to be optimized to the outgoing line switches on each side, the line segment between the outgoing line switch on the side with the longest distance and the connection point to be optimized is selected as the connection point path to be optimized.

[0178] In some embodiments, the computer program, when executed, also implements:

[0179] Using the midpoint of the path to be optimized as the reference starting point, the remote control switches on the path to be optimized are traversed sequentially from the reference starting point toward the path to be optimized. Each remote control switch traversed is taken as a new candidate point for connection and a new candidate set of connection points is formed.

[0180] In some embodiments, the computer program, when executed, also implements:

[0181] For each new candidate connection point in the new candidate connection point set, the operational indicators of the new candidate connection point after commissioning are determined based on user data and operational data. Among them, the operational indicators include at least one of the following: number of transferred distribution transformers, line overload rate, theoretical reduction in line loss, reduction in power supply radius, user management level, dual-power user coverage rate, number of users, new energy penetration rate, and non-theoretical reduction in line loss.

[0182] Based on operational indicators, new candidate contact points that meet the preset operational indicator conditions are selected as target contact points.

[0183] In some embodiments, the computer program, when executed, also implements:

[0184] Replace the contact points in the contact point path to be optimized with the target contact point, and update the load transfer path of each side line based on the replaced contact point to obtain the updated load transfer path as the contact point optimization scheme.

[0185] In some embodiments, the computer program, when executed, also implements:

[0186] The optimization scheme for contact points can be visualized by stitching together maps and single-line diagrams.

[0187] It should be noted that, in this embodiment of the application, the current location distribution of tie points is identified by acquiring the CIM model data of the target power grid area system, and the tie point path to be optimized is identified. Based on multiple remote control switches in the tie point path to be optimized, a new tie point candidate set is determined, and the target tie point is selected from the new tie point candidate set. The tie point path to be optimized is reconstructed based on the target tie point. Thus, intelligent selection and path reconstruction of tie points can be completed without manual on-site inspection, which greatly improves work efficiency and can quickly find the optimal tie point adjustment scheme. At the same time, by combining user data and operation data, the new tie points are screened in multiple dimensions to ensure that the selected target tie points achieve accurate optimization of the distribution network operation mode.

[0188] This application provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, wherein when the program instructions are executed by a computer, the computer performs the following steps:

[0189] Acquire CIM model data, user data, and operational data of the target power grid area system;

[0190] Identify the current contact point location distribution based on CIM model data, and identify the contact point path to be optimized based on the current contact point location distribution;

[0191] Based on multiple remote control switches in the contact point path to be optimized, determine a new set of contact point candidates;

[0192] Based on user data and operational data, target contact points are selected from the new contact point candidate set.

[0193] Based on the target contact point, the path of the contact point to be optimized is reconstructed to generate a contact point optimization scheme.

[0194] In some embodiments, when program instructions are executed by a computer, the computer is also caused to perform:

[0195] Based on the CIM model data, determine the line topology data;

[0196] Based on the line topology data, determine the location distribution of the connection points of each circuit in the target power grid area system;

[0197] Based on the location distribution of the connection points, for each line connection point, the distance from the connection point to the outgoing switch of each side line is determined, as well as the jurisdiction of the power supply station to which each side line belongs.

[0198] If the distance from the connection point to the outgoing line switch on either side is greater than or equal to the preset distance threshold, or if the power supply stations of the lines on each side corresponding to the connection point are different, then the connection point will be marked as a connection point to be optimized.

[0199] Based on the distance from the connection point to be optimized to the outgoing line switches on each side, the line segment between the outgoing line switch on the side with the longest distance and the connection point to be optimized is selected as the connection point path to be optimized.

[0200] In some embodiments, when program instructions are executed by a computer, the computer is also caused to perform:

[0201] Using the midpoint of the path to be optimized as the reference starting point, the remote control switches on the path to be optimized are traversed sequentially from the reference starting point toward the path to be optimized. Each remote control switch traversed is taken as a new candidate point for connection and a new candidate set of connection points is formed.

[0202] In some embodiments, when program instructions are executed by a computer, the computer is also caused to perform:

[0203] For each new candidate connection point in the new candidate connection point set, the operational indicators of the new candidate connection point after commissioning are determined based on user data and operational data. Among them, the operational indicators include at least one of the following: number of transferred distribution transformers, line overload rate, theoretical reduction in line loss, reduction in power supply radius, user management level, dual-power user coverage rate, number of users, new energy penetration rate, and non-theoretical reduction in line loss.

[0204] Based on operational indicators, new candidate contact points that meet the preset operational indicator conditions are selected as target contact points.

[0205] In some embodiments, when program instructions are executed by a computer, the computer is also caused to perform:

[0206] Replace the contact points in the contact point path to be optimized with the target contact point, and update the load transfer path of each side line based on the replaced contact point to obtain the updated load transfer path as the contact point optimization scheme.

[0207] In some embodiments, when program instructions are executed by a computer, the computer is also caused to perform:

[0208] The optimization scheme for contact points can be visualized by stitching together maps and single-line diagrams.

[0209] It should be noted that, in this embodiment of the application, the current location distribution of tie points is identified by acquiring the CIM model data of the target power grid area system, and the tie point path to be optimized is identified. Based on multiple remote control switches in the tie point path to be optimized, a new tie point candidate set is determined, and the target tie point is selected from the new tie point candidate set. The tie point path to be optimized is reconstructed based on the target tie point. Thus, intelligent selection and path reconstruction of tie points can be completed without manual on-site inspection, which greatly improves work efficiency and can quickly find the optimal tie point adjustment scheme. At the same time, by combining user data and operation data, the new tie points are screened in multiple dimensions to ensure that the selected target tie points achieve accurate optimization of the distribution network operation mode.

[0210] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, electronic devices, computer storage media, and computer program products described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0211] It should be noted that the user information (including but not limited to basic user information) and data (including but not limited to data used for analysis, data stored, and data displayed) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0212] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification, claims and accompanying drawings of this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such processes, methods, products or devices.

[0213] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0214] In the several embodiments provided by this invention, it should be understood that the disclosed systems, electronic devices, computer storage media, computer program products, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0215] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0216] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0217] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the methods described in the various embodiments of the present invention through a computer device (which may be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0218] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A distribution network operation optimization method based on tie points, characterized in that, include: Acquire CIM model data, user data, and operational data of the target power grid area system; The current contact point location distribution is identified based on the CIM model data, and the contact point path to be optimized is identified based on the current contact point location distribution. Based on multiple remote control switches in the contact point path to be optimized, a new set of contact point candidates is determined; Based on the user data and the operational data, target contact points are selected from the new contact point candidate set; Based on the target contact point, the path of the contact point to be optimized is reconstructed to generate a contact point optimization scheme.

2. The distribution network operation optimization method based on contact points according to claim 1, characterized in that, The step of identifying the current contact point location distribution based on the CIM model data, and identifying the contact point path to be optimized based on the current contact point location distribution, includes: Based on the CIM model data, determine the line topology data; Based on the line topology data, determine the location distribution of the connection points of each circuit in the target power grid area system; Based on the location distribution of the connection points, for each line connection point, the distance from the connection point to the outgoing switch of each side line is determined, as well as the jurisdiction of the power supply station to which each side line belongs. If the distance from the connection point to the outgoing line switch on either side is greater than or equal to a preset distance threshold, or if the power supply stations of the lines corresponding to the connection point are different, then the connection point will be marked as a connection point to be optimized. Based on the distance from the connection point to be optimized to the outgoing line switches on each side, the line segment between the outgoing line switch on the side with the longest distance and the connection point to be optimized is selected as the connection point path to be optimized.

3. The distribution network operation optimization method based on contact points according to claim 2, characterized in that, The step of determining a new candidate set of contact points based on multiple remote control switches in the contact point path to be optimized includes: Using the midpoint of the path to be optimized as the reference starting point, the remote control switches on the path to be optimized are traversed sequentially from the reference starting point toward the path to be optimized. Each remote control switch traversed is taken as a new candidate contact point, and the new candidate contact point set is formed.

4. The distribution network operation optimization method based on tie points according to any one of claims 1 to 3, characterized in that, The step of selecting target contact points from the new contact point candidate set based on the user data and the operational data includes: For each new candidate connection point in the new candidate connection point set, the operational indicators of the new candidate connection point after its commissioning are determined based on the user data and the operational data; wherein, the operational indicators include at least one of the following: number of transferred distribution transformers, line overload rate, theoretical line loss reduction, power supply radius reduction, user management level, dual-power user coverage rate, number of users, new energy penetration rate, and non-theoretical line loss reduction rate. Based on the operational indicators, new candidate contact points that meet the preset operational indicator conditions are selected as the target contact points.

5. The distribution network operation optimization method based on tie points according to claim 1, characterized in that, The step of reconstructing the path of the contact point to be optimized based on the target contact point to generate a contact point optimization scheme includes: Replace the contact points in the contact point path to be optimized with the target contact point, and update the load transfer path of each side line based on the replaced contact point to obtain the updated load transfer path as the contact point optimization scheme.

6. The distribution network operation optimization method based on tie points according to claim 1, characterized in that, After reconstructing the path of the contact point to be optimized based on the target contact point to generate a contact point optimization scheme, the method further includes: The optimization scheme for the contact points is visualized by stitching together a map and a single-line graph.

7. A distribution network operation optimization system based on contact points, characterized in that, include: The data acquisition module is used to acquire CIM model data, user data, and operational data of the target power grid area system; The contact point determination module is used to identify the current contact point location distribution based on the CIM model data, and to identify the contact point path to be optimized based on the current contact point location distribution. The new contact point candidate module is used to determine a new contact point candidate set based on multiple remote control switches in the contact point path to be optimized. The new contact point filtering module is used to filter target contact points from the new contact point candidate set based on the user data and the operation data. The connection path optimization module is used to reconstruct the connection point path to be optimized based on the target connection point, and generate a connection point optimization scheme.

8. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the network operation optimization method based on a contact point as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the steps of the network operation optimization method based on the contact point as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, wherein when the program instructions are executed by a computer, the computer performs the steps of the junction point-based distribution network operation optimization method as described in any one of claims 1-6.

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