Alternating-current and direct-current hybrid power grid network loss allocation and cooperative loss reduction optimization method
By using a network loss responsibility feature identification method based on topology region division and power imbalance analysis in AC/DC hybrid power grids, the problem of unreasonable network loss responsibility division in existing technologies is solved, and the refined identification and allocation of power grid losses is realized, thereby improving the power grid operation efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- STATE GRID GANSU ELECTRIC POWER RESEARCH INSTITUTE
- Filing Date
- 2026-03-25
- Publication Date
- 2026-04-28
AI Technical Summary
Existing technologies are insufficient to accurately identify the actual network loss responsibility of different power flow entities in the multi-path transmission process of AC/DC hybrid power grids. The lack of a refined network loss sharing mechanism leads to unreasonable division of network loss responsibility and makes it difficult to provide an effective basis for coordinated power grid loss reduction scheduling.
By using a power imbalance identification mechanism based on grid topology region division, a power flow contribution index is constructed by combining the main transmission path and transmission power to generate network loss responsibility characteristics. Then, a network loss ratio calculation based on path branch statistics and a multi-subject collaborative allocation scheduling mechanism are adopted to achieve refined identification and quantitative allocation of network loss responsibility.
It enables the dynamic positioning of key areas of network loss and the precise identification of network loss responsibilities by multiple entities, improving the rationality of network loss responsibility definition and optimizing the overall operating efficiency of the power grid.
Smart Images
Figure CN121939431A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of loss reduction optimization technology, and more specifically, to a method for loss allocation and collaborative loss reduction optimization of AC / DC hybrid power grids. Background Technology
[0002] With the continuous expansion of the scale of new energy grid connection and the continuous improvement of the interconnection of the power system, the power system is gradually evolving from the traditional AC grid to the AC-DC hybrid grid structure. The AC-DC hybrid grid realizes cross-regional power transmission and multi-energy coordinated dispatch through the coordinated operation of AC transmission network and DC transmission channel. While improving the power grid transmission capacity and operational flexibility, it also makes the grid structure more complex, and the power transmission path presents the characteristics of multi-source, multi-path and multi-level coupling.
[0003] The existing technology has the following shortcomings: Currently, existing network loss calculation methods are mostly based on overall power flow calculation or equipment loss statistical models, which makes it difficult to accurately identify the actual network loss responsibility of different power flow entities in the multi-path transmission process in AC / DC hybrid power grids. They also lack a refined network loss allocation mechanism that combines the power grid topology and power transmission path characteristics, resulting in unreasonable division of network loss responsibility and difficulty in providing an effective basis for coordinated network loss reduction scheduling. Therefore, this paper proposes an optimization method for network loss allocation and coordinated loss reduction in AC / DC hybrid power grids.
[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention
[0005] To overcome the aforementioned deficiencies in the prior art, embodiments of the present invention provide a method for optimizing network loss allocation and collaborative loss reduction in AC / DC hybrid power grids. This method addresses the problems mentioned in the background art by employing a power imbalance identification mechanism based on grid topology region division, a network loss quantification analysis mechanism that combines the main transmission path and transmission power to construct a power flow contribution index and generate network loss responsibility characteristics, and a network loss proportion calculation and multi-subject collaborative allocation scheduling mechanism based on path branch statistics.
[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for optimizing network loss allocation and collaborative loss reduction in AC / DC hybrid power grids, comprising the following steps: Step S1: Retrieve the power grid topology information of the power grid under test, divide the power grid under test into topology regions using the power grid topology information, collect the bus cross-section exchange power of the topology region, and analyze the power imbalance state based on the bus cross-section exchange power. Step S2: Access the equipment handling library to obtain the abnormal repair records of the topology area, filter the network loss analysis area based on the power imbalance status, retrieve the main power flow information of the network loss analysis area and extract the main power flow. Step S3: Collect the main transmission path data and main transmission power data of the main body of power flow, generate the power flow contribution index based on the main transmission power data, and generate the network loss liability characteristics by combining the power flow contribution index and the main transmission path data; Step S4: After screening and marking the main body of power flow using the network loss responsibility characteristics, count the number of path branches of the marked main body of power flow and calculate the network loss allocation ratio. Generate the allocation scheduling result of each marked main body of power flow based on the network loss allocation ratio.
[0007] In a preferred embodiment, in step S1, the power grid topology information of the power grid under test is retrieved from the power grid operation database, including the information of each bus node in the power grid under test and the connection relationship of transmission lines. Based on the power grid topology information, a power grid topology network consisting of bus nodes and transmission lines is constructed. The topology network is divided into regions according to the connection relationship of transmission channels, so that bus nodes that form the same power transmission path through continuous transmission lines are assigned to the same topology region. The active power measurement data of each bus node connected branch in the topology area is read by the power measurement device. The side of the active power measurement data pointing to the bus node is taken as the active power flowing into the branch, and the side of the active power measurement data leaving the bus node is taken as the active power flowing out of the branch. The difference between the sum of the active power of each inflow branch and the sum of the active power of each outflow branch in the bus node is taken as the bus cross-sectional exchange power.
[0008] In a preferred embodiment, in step S1, the ratio of the absolute value of the bus cross-sectional exchange power to the maximum power value of the bus is taken as the bus exchange deviation rate, and the maximum value of the bus exchange deviation rate in the topology region is taken as the power imbalance value. The maximum power value of the busbar is the larger of the sum of the active power of each inflow branch and the sum of the active power of each outflow branch at that busbar node. If the power imbalance value is greater than the preset power imbalance threshold, the power imbalance state of the topology region is determined to be a power imbalance state. Conversely, the power imbalance state of the topological region is determined to be a power balance state.
[0009] In a preferred embodiment, in step S2, the device handling library is accessed to obtain the anomaly repair record of the topology region, including the bus node to which the anomaly device type belongs, the anomaly start time, and the repair completion time. The difference between the anomaly start time and the repair completion time is taken as the anomaly repair duration; The weights of equipment are set by the type of abnormal equipment. Specifically, the number of abnormal impact path nodes corresponding to the occurrence of various equipment abnormalities in historical operation data is counted, the number of abnormal impact path nodes is standardized, and the standardization result is used as the equipment weight. The product of the anomaly repair duration and the device weight is used as the anomaly impact value. The anomaly impact values of each anomaly within the topology area are accumulated to obtain the regional anomaly recovery index.
[0010] In a preferred embodiment, in step S2, the regional anomaly recovery index is compared with a preset anomaly recovery threshold to analyze the anomaly recovery impact status of the topological region; If the regional anomaly recovery index is greater than the preset anomaly recovery threshold, the anomaly recovery impact state of the topology region is determined to be an anomaly impact state. Conversely, the abnormal recovery impact state of the topological region is determined to be a normal recovery state; If the abnormal recovery impact status of a topology region is an abnormal impact status and the power imbalance status is a power imbalance status, then the topology region is selected as a network loss analysis region. Conversely, the topology region will not be selected as a network loss analysis region.
[0011] In a preferred embodiment, in step S3, the energy management system acquires the transmission path data and transmission power data of each electrical energy flow subject within a preset time window. An energy management system is a comprehensive information platform used for centralized monitoring, data acquisition, and operation control of the power grid. The main transmission path data refers to the length of the transmission branches that the main body of electrical energy travels through when transmitting electrical energy through transmission lines in the network loss analysis area; Main transmission power data refers to the active power of the main body of electrical energy flow on each transmission branch; The total active power flow of each power flow entity in the network loss analysis area is obtained by summing the absolute values of its active power flow.
[0012] In a preferred embodiment, in step S3, the transmission power of all electrical energy flow entities within the network loss analysis area is summarized to obtain the total transmission power of the area. The power flow contribution index is obtained by dividing the total power transmitted by each main body of electrical energy flow by the total power transmitted in the region. The main transmission path length is obtained by summing the line lengths of each power flow subject through each transmission branch within the network loss analysis area; The result of multiplying the power flow contribution index by the main transmission path length is used as the network loss liability characteristic.
[0013] In a preferred embodiment, in step S4, the network loss liability characteristics of all power flow entities are statistically analyzed and the average value of the network loss liability characteristics is calculated. When the network loss liability characteristic of a certain power flow entity is greater than or equal to the average value of the network loss liability characteristic, the corresponding power flow entity is selected and marked. If the network loss liability characteristic of a certain power flow entity is less than the average value of the network loss liability characteristic, then the corresponding power flow entity will not be screened or marked. Based on the power grid topology model, the number of path branches traversed by the marked power flow subject during power transmission is obtained by identifying the path branches traversed by the marked power flow subject within the network loss analysis area.
[0014] In a preferred embodiment, in step S4, the total number of path branches of all marked electrical flow entities within the network loss analysis area is counted; Divide the number of path branches for each marked electrical energy flow subject by the total number of path branches to obtain the path branch weight coefficient; The network loss liability weight is generated by multiplying the path branch weight coefficient with the network loss liability feature. The network loss responsibility weights of all marked power flow entities are normalized to calculate the network loss allocation ratio; The total network loss power in the network loss analysis area within the preset statistical period is obtained by monitoring the line loss through the line monitoring device. The total network loss power is multiplied by the network loss allocation ratio to calculate the network loss sharing power borne by the marked power flow subject. The power loss allocated to each marked power flow entity is used as the allocation and scheduling result.
[0015] The technical effects and advantages of this invention are as follows: This invention retrieves the topology information of the power grid under test, divides the power grid into topological regions, collects the exchange power of the bus sections in each topological region, analyzes the regional power imbalance, combines equipment anomaly repair records to screen network loss analysis areas, and extracts the main entities involved in power exchange within the region. Further, it collects the transmission path data and transmission power data of these entities to form network loss responsibility characteristics. Based on these characteristics, it screens and marks the main entities involved in power flow, counts the number of transmission path branches, and calculates the network loss allocation ratio. Based on this, it generates network loss allocation scheduling results for each entity involved in power flow, achieving dynamic positioning of key network loss areas and refined identification and quantitative allocation of network loss responsibilities for multiple entities. This improves the rationality of network loss responsibility definition and optimizes the overall operating efficiency of the power grid. Attached Figure Description
[0016] Figure 1 This is a flowchart illustrating the implementation of an AC / DC hybrid power grid loss allocation and collaborative loss reduction optimization method according to the present invention.
[0017] Figure 2 This is a schematic diagram illustrating the process of an AC / DC hybrid power grid loss allocation and collaborative loss reduction optimization method according to the present invention. Detailed Implementation
[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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.
[0019] This invention retrieves the topology information of the power grid under test, divides the power grid into topological regions, collects the exchange power of the bus sections in each topological region, analyzes the regional power imbalance, combines equipment anomaly repair records to screen network loss analysis areas, and extracts the main entities involved in power exchange within the region. Further, it collects the transmission path data and transmission power data of these entities to form network loss responsibility characteristics. Based on these characteristics, it screens and marks the main entities involved in power exchange, counts the number of their transmission path branches, and calculates the network loss allocation ratio. Based on this, it generates network loss allocation scheduling results for each entity involved in power exchange, achieving dynamic positioning of key network loss areas and refined identification and quantitative allocation of network loss responsibilities for multiple entities.
[0020] Example 1, such as Figures 1 to 2 As shown, a method for optimizing network loss allocation and collaborative loss reduction in a hybrid AC / DC power grid includes the following steps: Step S1: Retrieve the power grid topology information of the power grid under test, divide the power grid under test into topology regions using the power grid topology information, collect the bus cross-section exchange power of the topology region, and analyze the power imbalance state based on the bus cross-section exchange power. Step S2: Access the equipment handling library to obtain the abnormal repair records of the topology area, filter the network loss analysis area based on the power imbalance status, retrieve the main power flow information of the network loss analysis area and extract the main power flow. Step S3: Collect the main transmission path data and main transmission power data of the main body of power flow, generate the power flow contribution index based on the main transmission power data, and generate the network loss liability characteristics by combining the power flow contribution index and the main transmission path data; Step S4: After screening and marking the main body of power flow using the network loss responsibility characteristics, count the number of path branches of the marked main body of power flow and calculate the network loss allocation ratio. Generate the allocation scheduling result of each marked main body of power flow based on the network loss allocation ratio.
[0021] The specific implementation is as follows: In step S1, the power grid topology information of the power grid under test is retrieved through the power grid operation database. The power grid topology information is structural data used to describe the connection relationship of each electrical device in the power grid under test, including the information of each bus node and the connection relationship of transmission lines in the power grid under test. Among them, busbar node information refers to the node identifier, node type, and branch information connected to each substation busbar; transmission line connection relationship refers to the electrical connection relationship between different busbar nodes through transmission lines. Based on the power grid topology information, the power grid under test is divided into topological regions. Specifically, bus nodes are used as topology division nodes, and transmission lines between buses are used as connecting edges. The power grid under test is represented as a topological network structure composed of multiple nodes and connecting edges. The topological network is divided into regions according to the connection relationship of transmission channels, so that nodes that are directly connected by continuous transmission lines to form power transmission paths within the same transmission channel belong to the same topological region.
[0022] It should be explained that the power grid operation database is a basic information database for power grids used to store and manage data on the power grid operation structure and equipment connection relationships.
[0023] For example, in the power grid under test, a certain new energy transmission channel consists of a wind farm booster station bus A, a regional collection substation bus B, and an external transmission converter station bus C connected sequentially by two transmission lines. A and B are connected by a first AC transmission line, and B and C are connected by a second AC transmission line. These three form a continuous power transmission path in the power grid topology. When dividing the topology, A, B, and C are used as topology nodes, and the first and second AC transmission lines are used as connecting edges. Based on the connection relationship of the transmission channels, it is identified that A, B, and C form a continuous power transmission path. Therefore, A, B, and C belong to the same topology region. Furthermore, if there is another transmission line connected at B to the load center substation bus D, and this transmission line does not belong to the aforementioned new energy transmission channel, then D does not form a continuous transmission channel with A, B, and C. Therefore, during the topology region division process, bus D is assigned to another topology region.
[0024] The power exchange of bus nodes in each topology region is detected and analyzed. Specifically, the active power measurement data of each bus node connection branch in the topology region is read by the power measurement device set on the connection branch of the bus node. The side of the active power measurement data pointing to the bus node is taken as the active power flowing into the branch, and the side of the active power measurement data leaving the bus node is taken as the active power flowing out of the branch. The difference between the sum of active power of each inflow branch and the sum of active power of each outflow branch in the bus node is taken as the bus section exchange power, which reflects the degree of power exchange of the bus node in the power grid. The cross-sectional switching power of all bus nodes in each topology region is statistically analyzed, and the ratio of the absolute value of the cross-sectional switching power of the bus to the maximum power value of the bus is used as the bus switching deviation rate to characterize the power balance of the bus. The maximum power value of the busbar is the larger of the sum of the active power of each inflow branch and the sum of the active power of each outflow branch at that busbar node. The maximum value of the bus exchange deviation rate in the topology region is taken as the power imbalance value, which reflects the overall power imbalance of the topology region under the current operating condition. The power imbalance value is compared with a preset power imbalance threshold to analyze the power imbalance status. If the power imbalance value is greater than the preset power imbalance threshold, the power imbalance state of the topology region is determined to be a power imbalance state. Conversely, the power imbalance state of the topological region is determined to be a power balance state; When the power imbalance state is in a state of power imbalance, it indicates that there is a significant deviation in the power exchange within the topological region; When the power imbalance state is the power balance state, it means that the inflow power and outflow power of the bus nodes in the topology region are basically balanced.
[0025] It should be noted that the power measurement device is a power monitoring device that calculates the active power data of the corresponding branch by collecting line voltage and current signals. The preset power imbalance threshold can be set according to the statistical distribution range of the bus exchange deviation rate under historical normal operating conditions. For example, 1.2 to 1.5 times the average bus exchange deviation rate in historical operating data can be taken as the threshold range.
[0026] In step S2, the device disposal library is accessed to obtain the anomaly repair record of the topology area. The anomaly repair record refers to the anomaly registration information and corresponding repair and disposal information formed after the power grid equipment has an operational anomaly within the preset anomaly statistics period. It reflects the operational stability of the power grid equipment in the topology area and the frequency of power transmission path adjustment. The anomaly repair record includes the bus node to which the abnormal equipment type belongs, the anomaly start time, and the repair completion time. The difference between the anomaly start time and the repair completion time is taken as the anomaly repair duration; The weight of equipment is set by the type of abnormal equipment. Specifically, the number of abnormal impact path nodes corresponding to the occurrence of abnormal equipment in the historical operation data is counted. The number of abnormal impact path nodes refers to the number of bus nodes covered by the path formed by the power transmission line along the power grid starting from the bus node to which the abnormal equipment belongs. The more nodes the anomaly affects, the wider the impact of this type of equipment anomaly on the power grid, and the higher the corresponding equipment weight should be. The number of path nodes affected by anomalies is standardized, and the standardized result is used as the device weight.
[0027] The product of the anomaly repair duration and the equipment weight is used as the anomaly impact value. The anomaly impact values of each anomaly within the topology area are accumulated to obtain the regional anomaly recovery index, which is used to reflect the degree of impact of equipment anomalies in the topology area on the power grid operation status.
[0028] It should be explained that the equipment handling database is an operation management database used to store abnormal events of power grid equipment and their handling and recovery information; the preset abnormality statistics cycle can be set according to the historical equipment abnormality statistics cycle; the standardization processing methods include, but are not limited to, standard linear transformation based on interval scaling, Z-Score standardization method based on statistics, or normalization method based on nonlinear mapping function. The application methods of standardization processing will not be elaborated here.
[0029] The regional anomaly recovery index is compared with the preset anomaly recovery threshold to analyze the impact of anomaly recovery on the topological region. If the regional anomaly recovery index is greater than the preset anomaly recovery threshold, the anomaly recovery impact state of the topology region is determined to be an anomaly impact state. Conversely, the abnormal recovery impact state of the topological region is determined to be a normal recovery state; Further, based on the impact of abnormal recovery and power imbalance, the topology region is filtered to select areas for network loss analysis: If the abnormal recovery impact status of a topology region is an abnormal impact status and the power imbalance status is a power imbalance status, then the topology region is selected as a network loss analysis region. Conversely, the topology region will not be selected as a network loss analysis region.
[0030] The main information of power flow in the power loss analysis area is retrieved from the power grid energy management database. The main information of power flow refers to the operating information of equipment that is connected to the power grid through the bus node and participates in power injection or power consumption in the power loss analysis area. The main information of power flow includes the type of main equipment and the bus node to which the main equipment belongs. Equipment whose bus nodes are located within the network loss analysis area and have the ability to inject or consume power is extracted as the main body of power flow, which is used to identify the main body of power exchange participating in the network loss formation process.
[0031] It should be noted that the preset anomaly recovery threshold can be set according to the statistical distribution range of the regional anomaly recovery index in historical operation data; the power grid energy management library is used to store operation data such as power grid equipment connection relationships, equipment operating status, and equipment power information.
[0032] This step retrieves and extracts the main entities involved in the power flow in the network loss analysis area, thereby identifying the objects participating in the power exchange process. This provides an analytical basis for subsequent statistical analysis of the main entity transmission path data and main entity transmission power data, enabling network loss analysis to be performed with precision starting from specific power exchange entities.
[0033] In step S3, operational data is collected from the identified power flow entities. The energy management system acquires the transmission path data and power transmission data of each entity within a preset time window. The transmission path data refers to the length of the transmission branches traversed by the power flow entity when transmitting power through transmission lines in the network loss analysis area. The power transmission data refers to the active power of the power flow on each transmission branch. The power transmission data reflects the actual power transmission scale of the power flow entity in the network loss analysis area. A higher value indicates a greater power transmission workload for the entity in the network loss analysis area, and a more significant impact on line current and the resulting resistance loss.
[0034] It should be noted that the energy management system is a comprehensive information platform used for centralized monitoring, data acquisition, and operation control of the power grid. The collected data is stored and processed in time series. The main transmission path data comes from the power grid topology model stored in the energy management system, and the main transmission power data comes from the power flow measurement data of each transmission branch.
[0035] The total power transmission of the main energy flow entity in the entire network loss analysis area is calculated based on the main energy transmission power data. This is achieved by summing the absolute values of the active power flow power of each main energy flow entity in the network loss analysis area. The absolute value of the active power flow power is used to eliminate the influence of the power flow direction on the power statistics, so that the main power transmission power can truly reflect the scale of energy transmission of the main energy flow entity in the network loss analysis area.
[0036] After obtaining the total transmission power of each power flow entity, the transmission power of all power flow entities within the network loss analysis area is summarized to obtain the total regional transmission power. The total regional transmission power represents the total amount of power transmitted by all power flow entities through the network loss analysis area within a preset time window. The larger the value, the more frequent the power flow within the network loss analysis area, the higher the line current level, and the more obvious the potential impact on line resistance loss.
[0037] The power flow contribution index is obtained by dividing the total transmission power of each power flow entity by the total transmission power of the region. The power flow contribution index reflects the proportion of power flow entities in the power flow transmission within the network loss analysis area, and its value ranges from [0,1]. The larger the power flow contribution index, the higher the proportion of the power flow entity in the regional power flow structure, and the greater its influence on line current distribution and resistance loss. Therefore, it should bear a higher weight in the allocation of network loss responsibility.
[0038] After obtaining the power flow contribution index, the main transmission path data is quantified. Specifically, the main transmission path length is obtained by summing the line lengths of each power flow subject through each transmission branch in the network loss analysis area.
[0039] It should be noted that when the main flow of electrical energy passes through any transmission branch, the line length is taken; otherwise, the line length is taken as 0.
[0040] The main transmission path length is used to reflect the power transmission distance of the main power flow in the network loss analysis area. The larger the value, the longer the power flow needs to go through the transmission line to complete the transmission process, thus generating a higher potential loss level in the resistance loss calculation.
[0041] After obtaining the power flow contribution index and the main transmission path length, the two types of parameters are combined to generate the network loss responsibility characteristic. Specifically, the result of multiplying the power flow contribution index by the main transmission path length is used as the network loss responsibility characteristic. This characteristic comprehensively characterizes the overall impact of the power flow entity on line loss formation in the network loss analysis area. This parameter considers both power flow scale and transmission distance factors: when the main transmission power accounts for a large proportion and the transmission path is long, the network loss responsibility characteristic will increase significantly; when the main transmission power is small or the transmission path is short, the network loss responsibility characteristic will decrease accordingly. Therefore, the network loss responsibility characteristic quantitatively reflects the relative responsibility of each power flow entity for network loss formation and serves as important input data for network loss responsibility allocation and collaborative loss reduction scheduling analysis in subsequent steps.
[0042] In step S4, the power flow entities are screened and labeled based on network loss responsibility characteristics. A higher value for the network loss responsibility characteristic indicates a higher power proportion and longer transmission path for the power flow entity in the regional power flow structure, resulting in a more significant impact on line current and resistance losses. Therefore, it should be given priority in network loss responsibility allocation. The network loss responsibility characteristics of all power flow entities are statistically analyzed and the average value is calculated. The average value reflects the overall level of influence of each power flow entity on network losses within the network loss analysis area.
[0043] When the network loss liability characteristic of a certain power flow entity is greater than or equal to the average value of the network loss liability characteristic, the corresponding power flow entity is selected and marked. If the network loss liability characteristic of a certain power flow entity is less than the average value of the network loss liability characteristic, then the corresponding power flow entity will not be screened or marked.
[0044] Through the above screening and labeling process, the main entities of power flow that have a significant impact on network loss are identified, providing a scope of objects for subsequent network loss allocation calculations.
[0045] After screening and marking the main power flow entities, a statistical analysis is performed on the transmission path structure of each marked power flow entity within the network loss analysis area. Specifically, based on the power grid topology model, the number of path branches traversed by the marked power flow entities during power transmission is obtained by identifying the path branch nodes during power transmission. The number of path branches refers to the number of transmission branches involved in the power transmission process of the marked power flow entity, which reflects the degree of network coupling of the marked power flow entity in the network loss analysis area. The larger the value, the more transmission branches the marked power flow entity is involved in the power transmission process, and the wider the influence range of the power flow distribution, which affects the resistance loss of multiple lines.
[0046] It should be noted that power grid topology information is a set of data used to describe the connection relationships and structural characteristics between various electrical devices in the power grid. It includes bus node information, transmission branch connection relationships, transformer connection relationships, and converter equipment connection relationships, and is expressed in a node-branch structure model. In this model, a node is used to represent a bus or equipment access point, and a branch is used to represent a transmission line or transformer equipment connecting two nodes.
[0047] After obtaining the number of path branches for all marked power flow entities, the number of path branches is summarized. Specifically, the total number of path branches for all marked power flow entities within the network loss analysis area is counted. The total number of path branches represents the scale of the number of transmission branches involved in the power transmission path of all marked power flow entities within the network loss analysis area.
[0048] The number of path branches for each marked energy flow entity is divided by the total number of path branches to normalize the number of path branches and obtain the path branch weight coefficient. The path branch weight coefficient reflects the proportion of the path structure of the corresponding marked energy flow entity among all marked energy flow entities, and its value range is [0,1].
[0049] The more path branches a marked power flow entity has, the larger its path branch weight coefficient, indicating that the corresponding marked power flow entity is involved in a wider range of transmission branches during power transmission, and has a higher degree of structural impact on network loss formation.
[0050] The network loss responsibility weight is generated by multiplying the path branch weight coefficient with the network loss responsibility characteristics. The network loss responsibility weight reflects the comprehensive influence of the marked power flow subject on the formation of network loss in terms of power flow scale, transmission path length and network coupling structure.
[0051] The network loss liability weights of all marked energy flow entities are normalized, and the network loss allocation ratio is calculated using the following formula: ; in, For the first The proportion of network loss allocation for each marked power flow entity. For the first The network loss liability weight of each marker of the main body of electricity flow. To mark the serial number index of the main body of electrical energy flow, The sum of the network loss liability weights for all marked energy flow entities. For summation index variables, The total number of entities marking electrical energy flow within the network loss analysis area.
[0052] The network loss allocation ratio represents the proportion of network loss responsibility that the marked power flow entity should bear in the network loss analysis area. Its value ranges from [0,1]. The larger the value, the more significant the comprehensive impact of the corresponding marked power flow entity on the formation of network loss in terms of power flow contribution, transmission distance and network path structure. Therefore, it bears a higher proportion in the network loss responsibility allocation.
[0053] After obtaining the network loss allocation ratio of each marked power flow entity, the allocation and scheduling results are generated by combining the actual network loss status of the network loss analysis area.
[0054] Specifically, the total network loss power within a preset statistical period in the network loss analysis area is obtained by monitoring the line loss through the line monitoring device. The total network loss power is multiplied by the network loss allocation ratio to calculate the network loss sharing power borne by the marked power flow subject. The network loss sharing power represents the scale of grid loss responsibility borne by the marked power flow subject under the current operating state. The larger the value, the more significant the impact of the corresponding marked power flow subject on the formation of grid loss during power transmission.
[0055] The power loss of each marked power flow subject is used as the allocation and scheduling result. In specific implementation, the power loss is used as the scheduling optimization constraint parameter and input into the power grid dispatching system to achieve coordinated adjustment of power generation output, energy storage charging and discharging power and power allocation of transmission channels, so as to achieve the operational goal of reducing overall power grid losses and optimizing power transmission efficiency.
[0056] It should be noted that the line monitoring device is a power monitoring device installed at the interval of the transmission line to collect and monitor the operating status parameters of the transmission line in real time; the power grid dispatching system is an operation management platform used to realize the power grid operation dispatching decision and control command issuance. Its functions include power grid operation status monitoring, power flow analysis, safety verification, economic dispatching, and control strategy execution.
[0057] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.
[0058] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0059] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.
[0060] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.
[0061] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A method for optimizing network loss allocation and collaborative loss reduction in a hybrid AC / DC power grid, characterized in that: Includes the following steps: Step S1: Retrieve the power grid topology information of the power grid under test, divide the power grid under test into topology regions using the power grid topology information, collect the bus cross-section exchange power of the topology region, and analyze the power imbalance state based on the bus cross-section exchange power. Step S2: Access the equipment handling library to obtain the abnormal repair records of the topology area, filter the network loss analysis area based on the power imbalance status, retrieve the main power flow information of the network loss analysis area and extract the main power flow. Step S3: Collect the main transmission path data and main transmission power data of the main body of power flow, generate the power flow contribution index based on the main transmission power data, and generate the network loss liability characteristics by combining the power flow contribution index and the main transmission path data; Step S4: After screening and marking the main body of power flow using the network loss responsibility characteristics, count the number of path branches of the marked main body of power flow and calculate the network loss allocation ratio. Generate the allocation scheduling result of each marked main body of power flow based on the network loss allocation ratio.
2. The method for optimizing network loss allocation and collaborative loss reduction in an AC / DC hybrid power grid according to claim 1, characterized in that: In step S1, the power grid topology information of the power grid under test is retrieved from the power grid operation database, including the information of each bus node and the connection relationship of transmission lines in the power grid under test. Based on the power grid topology information, a power grid topology network consisting of bus nodes and transmission lines is constructed. The topology network is divided into regions according to the connection relationship of transmission channels, so that bus nodes that form the same power transmission path through continuous transmission lines are assigned to the same topology region. The active power measurement data of each bus node connected branch in the topology area is read by the power measurement device. The side of the active power measurement data pointing to the bus node is taken as the active power flowing into the branch, and the side of the active power measurement data leaving the bus node is taken as the active power flowing out of the branch. The difference between the sum of the active power of each inflow branch and the sum of the active power of each outflow branch in the bus node is taken as the bus cross-sectional exchange power.
3. The method for optimizing network loss allocation and collaborative loss reduction in a hybrid AC / DC power grid according to claim 2, characterized in that: In step S1, the ratio of the absolute value of the bus cross-section exchange power to the maximum power value of the bus is taken as the bus exchange deviation rate, and the maximum value of the bus exchange deviation rate in the topology region is taken as the power imbalance value. The maximum power value of the busbar is the larger of the sum of the active power of each inflow branch and the sum of the active power of each outflow branch at that busbar node. If the power imbalance value is greater than the preset power imbalance threshold, the power imbalance state of the topology region is determined to be a power imbalance state. Conversely, the power imbalance state of the topological region is determined to be a power balance state.
4. The method for optimizing network loss allocation and collaborative loss reduction in an AC / DC hybrid power grid according to claim 3, characterized in that: In step S2, the device handling library is accessed to obtain the anomaly repair record of the topology area, including the bus node to which the anomaly device type belongs, the anomaly start time, and the repair completion time; The difference between the anomaly start time and the repair completion time is taken as the anomaly repair duration; The weights of equipment are set by the type of abnormal equipment. Specifically, the number of abnormal impact path nodes corresponding to the occurrence of various equipment abnormalities in historical operation data is counted, the number of abnormal impact path nodes is standardized, and the standardization result is used as the equipment weight. The product of the anomaly repair duration and the device weight is used as the anomaly impact value. The anomaly impact values of each anomaly within the topology area are accumulated to obtain the regional anomaly recovery index.
5. The method for optimizing network loss allocation and collaborative loss reduction in a hybrid AC / DC power grid according to claim 4, characterized in that: In step S2, the regional anomaly recovery index is compared with the preset anomaly recovery threshold to analyze the impact status of anomaly recovery in the topological region; If the regional anomaly recovery index is greater than the preset anomaly recovery threshold, the anomaly recovery impact state of the topology region is determined to be an anomaly impact state. Conversely, the abnormal recovery impact state of the topological region is determined to be a normal recovery state; If the abnormal recovery impact status of a topology region is an abnormal impact status and the power imbalance status is a power imbalance status, then the topology region is selected as a network loss analysis region. Conversely, the topology region will not be selected as a network loss analysis region.
6. The method for optimizing network loss allocation and collaborative loss reduction in an AC / DC hybrid power grid according to claim 5, characterized in that: In step S3, the energy management system acquires the transmission path data and transmission power data of each electrical energy flow subject within a preset time window. An energy management system is a comprehensive information platform used for centralized monitoring, data acquisition, and operation control of the power grid. The main transmission path data refers to the length of the transmission branches that the main body of electrical energy travels through when transmitting electrical energy through transmission lines in the network loss analysis area; Main transmission power data refers to the active power of the main body of electrical energy flow on each transmission branch; The total active power flow of each power flow entity in the network loss analysis area is obtained by summing the absolute values of its active power flow.
7. The method for optimizing network loss allocation and collaborative loss reduction in an AC / DC hybrid power grid according to claim 6, characterized in that: In step S3, the transmission power of all electrical energy flow entities within the network loss analysis area is summarized to obtain the total transmission power of the area; The power flow contribution index is obtained by dividing the total power transmitted by each main body of electrical energy flow by the total power transmitted in the region. The main transmission path length is obtained by summing the line lengths of each power flow subject through each transmission branch within the network loss analysis area; The result of multiplying the power flow contribution index by the main transmission path length is used as the network loss liability characteristic.
8. The method for optimizing network loss allocation and collaborative loss reduction in a hybrid AC / DC power grid according to claim 7, characterized in that: In step S4, the network loss liability characteristics of all power flow entities are statistically analyzed and the average value of the network loss liability characteristics is calculated. When the network loss liability characteristic of a certain power flow entity is greater than or equal to the average value of the network loss liability characteristic, the corresponding power flow entity is selected and marked. If the network loss liability characteristic of a certain power flow entity is less than the average value of the network loss liability characteristic, then the corresponding power flow entity will not be screened or marked. Based on the power grid topology model, the number of path branches traversed by the marked power flow subject during power transmission is obtained by identifying the path branches traversed by the marked power flow subject within the network loss analysis area.
9. The method for optimizing network loss allocation and collaborative loss reduction in a hybrid AC / DC power grid according to claim 8, characterized in that: In step S4, the total number of path branches for all marked electrical flow entities within the network loss analysis area is calculated. Divide the number of path branches for each marked electrical energy flow subject by the total number of path branches to obtain the path branch weight coefficient; The network loss liability weight is generated by multiplying the path branch weight coefficient with the network loss liability feature. The network loss responsibility weights of all marked power flow entities are normalized to calculate the network loss allocation ratio; The total network loss power in the network loss analysis area within the preset statistical period is obtained by monitoring the line loss through the line monitoring device. The total network loss power is multiplied by the network loss allocation ratio to calculate the network loss sharing power borne by the marked power flow subject. The power loss allocated to each marked power flow entity is used as the allocation and scheduling result.