A wind farm power collection line path optimization method and system thereof

Abstract

The application discloses a wind farm power collection line path optimization method and system, wherein the wind farm power collection line path optimization method comprises the following steps: determining a power transmission planning area, performing map grid processing on the power transmission planning area, determining a first path in the map grid, performing update optimization judgment on the first path according to a weight parameter in the map grid, continuously optimizing the path result after the update optimization, and outputting an optimal path. In the process of determining the wind farm power collection line path, a path is first quickly determined, and the path is continuously optimized through different parameters and directions in the subsequent process, the path is comprehensively optimized from multiple angles, and the accuracy of path optimization is improved.

Description

Technical Field

[0001] This application relates to the field of data processing, and more specifically, to a method and system for optimizing the path of wind farm collector lines. Background Technology

[0002] With continuous technological development, wind farm power collection lines currently take three forms: overhead lines, cable connections, and a combination of overhead and cable connections. The overhead line method involves the wind turbines being stepped up at a prefabricated substation before being connected to the nearest overhead power line tower via cable. The cable connection method utilizes the electricity generated by the wind turbines, connecting to the high-voltage side of a nearby prefabricated substation. The wind farm power collection line path refers to the route taken by the transmission lines within the wind farm that collect the electricity generated by each wind turbine through cables or overhead lines to the step-up substation (or switching station). It is a crucial component of the wind farm's power collection system, and its design and route selection directly affect the wind farm's construction costs, operational reliability, construction difficulty, and impact on the surrounding environment. Currently, wind farm power collection line path planning is conducted using basic information about the wind farm, topographical and environmental data. After planning, the path is typically optimized using a minimum route approach to minimize the total length of the planned route. However, current methods for route optimization are often too simplistic and do not take into account factors such as regional security and regional characteristics when optimizing routes.

[0003] Therefore, how to provide a method that comprehensively optimizes the path from multiple perspectives has become an urgent problem to be solved in this field. Summary of the Invention

[0004] To address the aforementioned issues, this application proposes a method for optimizing the transmission line path in a wind farm, comprising the following steps: determining the transmission planning area and performing map raster processing on the transmission planning area; determining a first path in the map raster; updating and optimizing the first path based on the weight parameters in the map raster; continuously optimizing the updated and optimized path results and outputting the optimal path.

[0005] The wind farm power collection line path optimization method described above includes determining the transmission planning area and performing map raster processing on the transmission planning area, which involves taking the area adjacent to the wind farm power collection line as the transmission planning area and dividing the area into N... A raster map with N cells.

[0006] The wind farm power collection line path optimization method described above includes determining the first path in the map grid by: determining the starting node, intermediate node, and ending node in the map grid; and constructing the first path of the power collection line based on the starting node, intermediate node, and ending node.

[0007] The wind farm power collection line path optimization method described above uses a wind turbine connected to a single branch box as the starting node, a branch box connected to multiple wind turbines as an intermediate node, and a booster station as the ending node.

[0008] The wind farm collector line path optimization method described above, wherein let , This represents the path distance from the starting node a to the intermediate node k. This represents the path distance from intermediate node k to the final node b. This represents the path distance from the starting node a to the ending node b; when intermediate nodes exist... , making If the path is not found, then a path update is performed. The path updated after traversing all intermediate nodes is the first path.

[0009] A wind farm power collection line path optimization system includes: a map grid processing unit, a first path determination unit, an optimization judgment unit, and a continuous optimization unit; the map grid processing unit is used to determine the power transmission planning area and perform map grid processing on the power transmission planning area; the first path determination unit is used to determine a first path in the map grid; the optimization judgment unit is used to update and optimize the first path according to the weight parameters in the map grid; and the continuous optimization unit is used to continuously optimize and judge the updated and optimized path results and output the optimal path.

[0010] The wind farm power collection line path optimization system described above includes a map raster processing unit that determines the transmission planning area. Map raster processing of the transmission planning area includes using the adjacent area of ​​the wind farm power collection line as the transmission planning area and dividing this area into N... A raster map with N cells.

[0011] The wind farm power collection line path optimization system described above, wherein the first path determination unit determines the first path in the map grid by: determining the starting node, intermediate node and ending node in the map grid; and constructing the first path of the power collection line based on the starting node, intermediate node and ending node.

[0012] In the wind farm collection line path optimization system described above, the first path determination unit determines the first path in the map grid, taking the wind turbine connected to one branch box as the starting node, the branch box connected to multiple wind turbines as the intermediate node, and the booster station as the ending node.

[0013] In the wind farm collector line path optimization system described above, in the first path determination unit, let , This represents the path distance from the starting node a to the intermediate node k. This represents the path distance from intermediate node k to the final node b. This represents the path distance from the starting node a to the ending node b; when intermediate nodes exist... , making If the path is not found, then a path update is performed. The path updated after traversing all intermediate nodes is the first path.

[0014] This application has the following beneficial effects: In determining the path of the wind farm's power collection line, this application uses the shortest distance method to determine the path and then continuously optimizes the path using different parameters and emphases. This comprehensive optimization from multiple perspectives improves the accuracy of path optimization. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application 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 recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings.

[0016] Figure 1 This is a flowchart illustrating the wind farm collector line path optimization method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the internal structure of a wind farm collector line path optimization system provided according to an embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0018] Example 1 like Figure 1 As shown in the figure, this embodiment provides a method for optimizing the path of wind farm collection lines, which specifically includes the following steps: Step S1: Determine the power transmission planning area and perform map raster processing on the power transmission planning area.

[0019] The area adjacent to the wind farm's collection lines is designated as the transmission planning area. Within this area, GIS technology is used to create a map raster, which includes information such as terrain and obstacles for each region. The map raster should also be marked with the specific locations of wind turbines, branch boxes, and substations.

[0020] The area adjacent to the wind farm's power collection lines is divided into N zones using GIS data. A raster map with N cells is used to facilitate the subsequent extraction of weight parameters for the areas traversed by the proposed route.

[0021] Step S2: Determine the first path in the map grid.

[0022] The method for determining the first path is to identify the shortest path of the wind farm's collection lines within the map grid.

[0023] Based on the wind turbine distribution, the entire wind farm is divided into several collection line groups, each corresponding to one collection line, for example, 10-15 wind turbines per group. The electrical energy generated by each wind turbine in each group is connected to one or more branch boxes via cables or overhead lines, and then transmitted through trunk cables to the substation (or switching station). The route of the transmission line is the collection line path for that group. Therefore, in the map grid, multiple wind turbines are grouped, with the wind turbine connected to a branch box defined as the starting node. Multiple branch boxes connected to multiple wind turbines are intermediate nodes, and the substation is the endpoint node, thus constructing the first path for each group of collection lines.

[0024] If there are multiple branch boxes to choose from, one branch box is selected to connect multiple wind turbines. Therefore, in this embodiment, multiple branch boxes are traversed to determine an intermediate node that can build the shortest path.

[0025] In this embodiment, the default is... , This represents the path distance from the starting node a to the intermediate node k. This represents the path distance from intermediate node k to the final node b. This represents the path distance from the starting node 'a' to the ending node 'b'. This is applicable when intermediate nodes exist. , making Then, perform a path update, traversing all intermediate nodes and recording the path. The distance is the shortest path from the starting node to the ending node, which is the first path of the collection lines in the current wind farm.

[0026] The above method can be used to determine the first path of the collection lines in each wind farm.

[0027] Step S3: Update and optimize the first path based on the weight parameters in the map grid.

[0028] Specifically, it includes the following sub-steps: Step S31: Determine the weight parameters in the map grid, and determine the comprehensive weight based on the weight parameters.

[0029] In this embodiment, the weighting parameters selected include slope, vegetation coverage, obstacle density, and electromagnetic interference. The comprehensive weight value for each grid cell is determined based on the weighting parameters in each grid cell. Specifically, it is expressed as:

[0030] Where n represents the number of weight parameters. This represents the coefficient value of the i-th weight parameter, which can be preset by the staff. This represents the quantized value of the i-th weight parameter in the map grid.

[0031] For example, when the weight parameter is the slope value, the quantization value is 10 when the slope is greater than 20° and 5 when it is less than 20°. The higher the slope, the larger the quantization value. When the weight parameter is vegetation cover, the quantization value is 5 for forest areas, 2 for grasslands, and 1 for bare ground.

[0032] Step S32: Determine the comprehensive weight value of the map grids traversed by the first path, and determine whether the first path needs to be updated and optimized based on the comprehensive weight value.

[0033] Since the first path is the shortest path, this embodiment does not perform the search for the path with the minimum comprehensive weight. Instead, it sets a comprehensive threshold based on historical experience. When the comprehensive weight value of the first path is less than the specified threshold, it is considered that the first path does not need to be optimized and can be directly output as the optimal path. Otherwise, it is considered that even if the first path is the shortest path, the geographical environment information has a significant impact on it, and step S33 is executed.

[0034] Step S33: Find the path with the smallest comprehensive weight value and update and optimize the first path.

[0035] Determine the minimum comprehensive weight value, obtain the second path based on the path position at the minimum comprehensive weight value, and use the second path as the updated and optimized path.

[0036] Step S4: Continuously optimize and judge the updated and optimized path results, and output the optimal path.

[0037] If the updated and optimized result is the second path or still the first path, it is necessary to determine the comprehensive power loss in the second or first path, and make a judgment based on the comprehensive power loss to decide whether continuous optimization is needed.

[0038] Based on this, step S4 includes the following sub-steps: Step S41: Determine the overall power loss in the update optimization path.

[0039] The combined power loss in the first or second path is specifically expressed as follows:

[0040] Where T represents the total power loss of the transformer in the first path (or the second path), This indicates the rated no-load loss of the first path (or the second path). This represents the load fluctuation loss coefficient in the first path (or second path). This represents the average load factor in the first path (or second path). This indicates the rated load loss in the first path (or second path). This indicates the rated load leakage flux power in the first path (or second path). It represents the economic equivalent of reactive power.

[0041] Because the outlet voltage of wind turbines in wind farms is typically three-phase 380V, after being stepped up to 35kV (three-phase) by a box-type transformer, the collector lines must use three-phase power lines to transmit the electrical energy. Where I represents the load current, This indicates the resistance per unit length of copper or aluminum wire at 20 degrees Celsius, as obtained from a technical manual. The conductor temperature coefficient is typically 0.4, and yc represents the average ambient temperature of the collector line in one path (or the second path).

[0042] If the combined power loss T of the first or second path exceeds a specified threshold, then the first or second path is considered to require further optimization, and step S42 is executed. Otherwise, the current first or second path is considered not to require optimization, and it is output as the optimal path.

[0043] Step S42: Adjust the parameters of the collector lines in the update and optimization path.

[0044] The parameter adjustments for the collector lines in the first or second path include redetermining the voltage level and reselecting the conductor or cable type and cross-sectional area.

[0045] As an example, a lower voltage level can be selected to reduce overall power loss and / or a larger cross-sectional area can be increased to reduce overall power loss.

[0046] After adjusting the parameters, the overall power loss of the first or second path is redefined until the overall power loss is less than the specified threshold.

[0047] If, after parameter adjustment, the combined power loss of the first or second path still exceeds the specified threshold, the process will exit and path planning will need to be re-performed.

[0048] Example 2 like Figure 2 As shown, a wind farm power collection line path optimization system provided in this application embodiment includes: a map grid processing unit 210, a first path determination unit 220, an optimization judgment unit 230, and a continuous optimization unit 240.

[0049] The map raster processing unit 210 is used to determine the power transmission planning area and perform map raster processing on the power transmission planning area.

[0050] The area adjacent to the wind farm's collection lines is designated as the transmission planning area. Within this area, GIS technology is used to create a map raster, which includes information such as terrain and obstacles for each region. The map raster should also be marked with the specific locations of wind turbines, branch boxes, and substations.

[0051] The area adjacent to the wind farm's power collection lines is divided into N zones using GIS data. A raster map with N cells is used to facilitate the subsequent extraction of weight parameters for the areas traversed by the proposed route.

[0052] The first path determination unit 220 is used to determine the first path in the map grid.

[0053] The method for determining the first path is to identify the shortest path of the wind farm's collection lines within the map grid.

[0054] Based on the wind turbine distribution, the entire wind farm is divided into several collection line groups, each corresponding to one collection line, for example, 10-15 wind turbines per group. The electrical energy generated by each wind turbine in each group is connected to one or more branch boxes via cables or overhead lines, and then transmitted through trunk cables to the substation (or switching station). The route of the transmission line is the collection line path for that group. Therefore, in the map grid, multiple wind turbines are grouped, with the wind turbine connected to a branch box defined as the starting node. Multiple branch boxes connected to multiple wind turbines are intermediate nodes, and the substation is the endpoint node, thus constructing the first path for each group of collection lines.

[0055] If there are multiple branch boxes to choose from, one branch box is selected to connect multiple wind turbines. Therefore, in this embodiment, multiple branch boxes are traversed to determine an intermediate node that can build the shortest path.

[0056] In this embodiment, the default is... , This represents the path distance from the starting node a to the intermediate node k. This represents the path distance from intermediate node k to the final node b. This represents the path distance from the starting node 'a' to the ending node 'b'. This is applicable when intermediate nodes exist. , making Then, perform a path update, traversing all intermediate nodes and recording the path. The distance is the shortest path from the starting node to the ending node, which is the first path of the collection lines in the current wind farm.

[0057] The above method can be used to determine the first path of the collection lines in each wind farm.

[0058] The optimization judgment unit 230 is used to update and optimize the first path based on the weight parameters in the map grid.

[0059] The optimization judgment unit 230 specifically executes the following sub-steps: Step V1: Determine the weight parameters in the map grid, and determine the overall weight based on the weight parameters.

[0060] In this embodiment, the weighting parameters selected include slope, vegetation coverage, obstacle density, and electromagnetic interference. The comprehensive weight value for each grid cell is determined based on the weighting parameters in each grid cell. Specifically, it is expressed as:

[0061] Where n represents the number of weight parameters. This represents the coefficient value of the i-th weight parameter, which can be preset by the staff. This represents the quantized value of the i-th weight parameter in the map grid.

[0062] For example, when the weight parameter is the slope value, the quantization value is 10 when the slope is greater than 20° and 5 when it is less than 20°. The higher the slope, the larger the quantization value. When the weight parameter is vegetation cover, the quantization value is 5 for forest areas, 2 for grasslands, and 1 for bare ground.

[0063] Step V2: Determine the comprehensive weight value of the map grids traversed by the first path, and determine whether the first path needs to be updated and optimized based on the comprehensive weight value.

[0064] Since the first path is the shortest path, this embodiment does not perform the search for the path with the minimum comprehensive weight. Instead, it sets a comprehensive threshold based on historical experience. When the comprehensive weight value of the first path is less than the specified threshold, it is considered that the first path does not need to be optimized and can be directly output as the optimal path. Otherwise, it is considered that even if the first path is the shortest path, the geographical environment information has a significant impact on it, and step V3 is executed.

[0065] Step V3: Find the path with the smallest overall weight value and update and optimize the first path.

[0066] Determine the minimum comprehensive weight value, obtain the second path based on the path position at the minimum comprehensive weight value, and use the second path as the updated and optimized path.

[0067] The continuous optimization unit 240 is used to continuously optimize and judge the updated and optimized path results and output the optimal path.

[0068] If the updated and optimized result is the second path or still the first path, it is necessary to determine the comprehensive power loss in the second or first path, and make a judgment based on the comprehensive power loss to decide whether continuous optimization is needed.

[0069] Based on this, the continuous optimization unit 240 performs the following sub-steps: Step E1: Determine the overall power loss in the update optimization path.

[0070] The combined power loss in the first or second path is specifically expressed as follows:

[0071] Where T represents the total power loss of the transformer in the first path (or the second path), This indicates the rated no-load loss of the first path (or the second path). This represents the load fluctuation loss coefficient in the first path (or second path). This represents the average load factor in the first path (or second path). This indicates the rated load loss in the first path (or second path). This indicates the rated load leakage flux power in the first path (or second path). It represents the economic equivalent of reactive power.

[0072] Because the outlet voltage of wind turbines in wind farms is typically three-phase 380V, after being stepped up to 35kV (three-phase) by a box-type transformer, the collector lines must use three-phase power lines to transmit the electrical energy. Where I represents the load current, This indicates the resistance per unit length of copper or aluminum wire at 20 degrees Celsius, as obtained from a technical manual. The conductor temperature coefficient is typically 0.4, and yc represents the average ambient temperature of the collector line in one path (or the second path).

[0073] If the combined power loss T of the first or second path exceeds a specified threshold, then the first or second path is considered to require further optimization, and step S42 is executed. Otherwise, the current first or second path is considered not to require optimization, and it is output as the optimal path.

[0074] Step E2: Adjust the parameters of the collector lines in the update and optimization path.

[0075] The parameter adjustments for the collector lines in the first or second path include redetermining the voltage level and reselecting the conductor or cable type and cross-sectional area.

[0076] As an example, a lower voltage level can be selected to reduce overall power loss and / or a larger cross-sectional area can be increased to reduce overall power loss.

[0077] After adjusting the parameters, the overall power loss of the first or second path is redefined until the overall power loss is less than the specified threshold.

[0078] If, after parameter adjustment, the combined power loss of the first or second path still exceeds the specified threshold, the process will exit and path planning will need to be re-performed.

[0079] This application also provides a computer storage medium storing computer instructions, which, when invoked, are used to execute the wind farm power collection line path optimization method.

[0080] The embodiments disclosed in this invention provide a computer-readable storage medium storing computer program instructions. When the computer program instructions are executed on a computer, the computer performs the aforementioned wind farm power collection line path optimization method.

[0081] This invention provides a processor for processing the above-described method for optimizing the path of a wind farm power collection line.

[0082] In this embodiment of the invention, the processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0083] The various methods, steps, and logic diagrams disclosed in the embodiments of this invention can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor reads information from the storage medium and, in conjunction with its hardware, completes the steps of the above methods.

[0084] The storage medium can be memory, such as volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0085] Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate Synchronous DRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM).

[0086] This application has the following beneficial effects: In determining the path of the wind farm's power collection line, this application uses the shortest distance method to determine the path and then continuously optimizes the path using different parameters and emphases. This comprehensive optimization from multiple perspectives improves the accuracy of path optimization.

[0087] Although the examples referenced in this application are described for illustrative purposes only and not for limiting the scope of this application, changes, additions and / or deletions to the implementation may be made without departing from the scope of this application.

[0088] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for optimizing the path of power collection lines in a wind farm, characterized in that, Includes the following steps: Determine the power transmission planning area and perform map rasterization on the power transmission planning area; Determine the first path in the map grid; The first path is updated and optimized based on the weight parameters in the map grid. Continuously optimize and judge the updated and optimized path results, and output the optimal path; The process of continuously optimizing the updated and optimized path results and outputting the optimal path includes the following sub-steps: Determine the overall power loss in the update and optimization path; Adjust the parameters of the collector lines in the update and optimization path; The combined power loss in the first or second path is expressed as: Where T represents the total power loss of the transformer in the first or second path. Indicates the rated no-load loss of the first or second path. This represents the load fluctuation loss coefficient in the first or second path. This represents the average load factor in the first or second path. Indicates the rated load loss in the first or second path. Indicates the rated load leakage flux power in the first or second path. It represents the economic equivalent of reactive power.

2. The wind farm collector line path optimization method as described in claim 1, characterized in that, The process of defining the power transmission planning area and performing map rasterization on this area includes defining the area adjacent to the wind farm's collection lines as the power transmission planning area, and dividing this area into N... A raster map with N cells.

3. The wind farm collector line path optimization method as described in claim 2, characterized in that, Determining the first path within the map grid includes: Define the start node, intermediate nodes, and end node in the map grid; Construct the first path of the collector line based on the starting node, intermediate nodes, and ending node.

4. The wind farm collector line path optimization method as described in claim 3, characterized in that, The wind turbine connected to one branch box is taken as the starting node, the branch box connected to multiple wind turbines is taken as the intermediate node, and the substation is taken as the ending node.

5. The wind farm collector line path optimization method as described in claim 4, characterized in that, make , This represents the path distance from the starting node a to the intermediate node k. This represents the path distance from intermediate node k to the final node b. This represents the path distance from the starting node a to the ending node b; when intermediate nodes exist... , making If the path is not found, then a path update is performed. The path updated after traversing all intermediate nodes is the first path.

6. A wind farm collector line path optimization system, characterized in that, include: The system includes a map raster processing unit, a first path determination unit, an optimization judgment unit, and a continuous optimization unit. The map raster processing unit is used to determine the power transmission planning area and perform map raster processing on the power transmission planning area; The first path determination unit is used to determine the first path in the map grid; The optimization judgment unit is used to update and optimize the first path based on the weight parameters in the map grid. The continuous optimization unit is used to continuously optimize the updated and optimized path results and output the optimal path. The continuous optimization unit continuously optimizes the updated path results and outputs the optimal path, including the following sub-steps: Determine the overall power loss in the update and optimization path; Adjust the parameters of the collector lines in the update and optimization path; The combined power loss in the first or second path is expressed as: Where T represents the total power loss of the transformer in the first or second path. Indicates the rated no-load loss of the first or second path. This represents the load fluctuation loss coefficient in the first or second path. This represents the average load factor in the first or second path. Indicates the rated load loss in the first or second path. Indicates the rated load leakage flux power in the first or second path. It represents the economic equivalent of reactive power.

7. The wind farm collector line path optimization system as described in claim 6, characterized in that, The map raster processing unit determines the power transmission planning area. Map raster processing of the power transmission planning area includes defining the area adjacent to the wind farm's collection lines as the power transmission planning area, and dividing this area into N... A raster map with N cells.

8. The wind farm collector line path optimization system as described in claim 7, characterized in that, The first path determination unit determines the first path in the map grid, including: Define the start node, intermediate nodes, and end node in the map grid; Construct the first path of the collector line based on the starting node, intermediate nodes, and ending node.

9. The wind farm collector line path optimization system as described in claim 8, characterized in that, The first path determination unit determines the first path in the map grid, taking the wind turbine connected to one branch box as the starting node, the branch box connected to multiple wind turbines as the intermediate node, and the booster station as the ending node.

10. The wind farm collector line path optimization system as described in claim 9, characterized in that, In the first path determination unit, let , This represents the path distance from the starting node a to the intermediate node k. This represents the path distance from intermediate node k to the final node b. This represents the path distance from the starting node a to the ending node b; when intermediate nodes exist... , making If the path is not found, then a path update is performed. The path updated after traversing all intermediate nodes is the first path.

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