Power grid management platform operation cost evaluation method and system based on big data, and medium

Abstract

The invention provides a power grid management platform operation cost evaluation method and system based on big data, and a medium. The method comprises the steps of obtaining current power grid operation state data information of a power grid management area through a big data technology; modeling based on the current power grid operation state data information to simulate a constructed power grid operation virtual system; making a corresponding power grid transformation scheme based on the power grid operation virtual system according to a transformation evaluation algorithm; based on the power grid transformation scheme and through a power grid transformation cost assessment model, assessing the power grid transformation operation cost; updating the power grid operation virtual system according to the power grid reconstruction scheme; and performing operation cost evaluation based on the updated power grid operation virtual system to obtain the power grid management operation cost of the power grid management area. Precise evaluation of the power grid operation cost is realized through big data analysis and a data modeling technology, and a main support basis is provided for stabilizing operation balance of a power grid system.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid management, and in particular to a method, system and medium for evaluating the operating cost of a power grid management platform based on big data. Background Art

[0002] With the continuous advancement of science and technology, the demand for electric energy is also increasing. Electricity has become the basis of production and life in modern society. Almost all industries and fields require electricity support. Whether it is industrial production, transportation or daily life, electricity plays a vital role, which makes the scale of the power grid continue to increase.

[0003] At present, the analysis and evaluation of operating costs in power grids is a very important task. It can better understand the operating cost status of power grids and formulate corresponding energy-saving and consumption-reducing improvement measures. However, conventional cost analysis and evaluation methods require manual data processing and analysis. Therefore, when processing large amounts of data, manual work may not be able to quickly and accurately complete the analysis and evaluation of power grid operating costs.

[0004] With the rapid development of the global economy, the demand for electricity is growing. The grid operation cost occupies an important position in the power industry. Its optimization is of great significance to improving the operating efficiency of the power system, reducing electricity prices, and ensuring the stability of power supply. In this context, big data analysis, as an emerging technology, provides new ideas and methods for the evaluation and optimization of grid operation costs. Summary of the invention

[0005] In order to solve at least one of the above technical problems, the present invention proposes a method, system and medium for evaluating the operating cost of a power grid management platform based on big data, which realizes accurate evaluation of the operating cost of the power grid through big data analysis technology, is conducive to accurately understanding the operating cost status of the power grid, and provides the main support basis for stabilizing the operational balance of the power grid system. At the same time, it is conducive to improving the operating efficiency of the power system, reducing electricity prices, and ensuring the stability of power supply.

[0006] The first aspect of the present invention proposes a method for evaluating the operation cost of a power grid management platform based on big data, the method comprising: Obtain the current grid operation status data information in the grid management area through big data technology; A virtual grid operation system is constructed by modeling based on current grid operation status data information to simulate; Based on the virtual system of power grid operation, a corresponding power grid transformation plan is formulated according to the transformation evaluation algorithm; Based on the grid transformation plan and through the grid transformation cost assessment model, the corresponding grid transformation operation cost is evaluated; The power grid operation virtual system is updated according to the power grid transformation plan, and an updated power grid operation virtual system is formed; An operating cost assessment is conducted based on the updated grid operation virtual system to obtain the grid management operating cost of the grid management area.

[0007] Furthermore, based on the grid operation virtual system and the transformation evaluation algorithm, a corresponding grid transformation plan is formulated, including: Obtain the target power grid area to be transformed; According to multiple transformable nodes in the target power grid area, all pre-selected transformation schemes are enumerated through a transformation preview method and added to a pre-selected transformation scheme library; According to the transformation evaluation algorithm, the pre-selected transformation schemes in the pre-selected transformation scheme library are optimized and analyzed to obtain the power grid transformation scheme for the target power grid area to be transformed.

[0008] Further, according to the transformation evaluation algorithm, the pre-selected transformation schemes in the pre-selected transformation scheme library are subjected to optimization analysis and processing to obtain the power grid transformation scheme of the target power grid area to be transformed, which specifically includes: For each pre-selected transformation scheme in the pre-selected transformation scheme library, respectively obtaining parameter data under each pre-selected transformation scheme; Compare the parameter data of all pre-selected transformation schemes in the pre-selected transformation scheme library in pairs, and score each pre-selected transformation scheme using a preset scoring algorithm; In the pre-selected transformation plan library, the pre-selected transformation plan with the highest score is selected as the power grid transformation plan for the target power grid area to be transformed.

[0009] Furthermore, based on the grid transformation plan and through the grid transformation cost assessment model, the corresponding grid transformation operating costs are evaluated, including: Construct a cost assessment model for power grid transformation; The power grid transformation cost assessment model is trained and optimized through sample data to obtain an optimized power grid transformation cost assessment model; Based on big data information technology, obtain terrain information, traffic information, and unit price information of manpower and material costs in the area involved in the power grid transformation plan; The terrain information, traffic information, and unit price information of manpower and material resources are combined with the grid transformation plan and evaluated through the grid transformation cost evaluation model to obtain the grid transformation operation cost.

[0010] Furthermore, the operation cost is evaluated based on the updated grid operation virtual system to obtain the grid management operation cost, which specifically includes: Construct a power grid failure maintenance cost assessment model; The power grid failure maintenance cost assessment model is trained and optimized through sample data to obtain an optimized power grid failure maintenance cost assessment model; Based on big data information technology, obtain the current geographic information, weather information, and unit price information of human and material costs in the power grid management area; The geographic information, weather information, and unit price information of human and material costs in the power grid management area are combined with the updated power grid operation virtual system and evaluated through the power grid fault maintenance cost evaluation model to obtain the power grid fault maintenance operation cost.

[0011] Furthermore, after evaluating the power grid failure maintenance cost evaluation model to obtain the power grid management operation cost of the power grid management area, the method further includes: Based on big data information technology, historical grid operation data of multiple other grid areas are obtained, and the historical grid operation data of each other grid area at least includes: geographic information of other grid areas, weather information at historical time, unit price information of human and material costs, and grid operation status data information, and actual cost of grid fault maintenance and operation in other grid areas; Based on the historical power grid operation data of each other power grid area, the geographical information of the other power grid areas and the weather information at the historical time included therein are subjected to feature calculation to obtain the feature value of each other power grid area; Perform feature calculation on the geographic information and weather information of the power grid management area to obtain the feature value of the power grid management area; Perform a difference operation on the characteristic value of each other power grid area and the characteristic value of the power grid management area; Determine whether the difference between the two is less than a third preset threshold value, and if so, mark the historical power grid operation data corresponding to other power grid areas as valuable data and enter them into the value database; Based on the grid operation status data information of the historical grid operation data of each other grid area in the value database, modeling is performed to simulate the grid operation virtual system of other grid areas; The geographical information of each other power grid area in the value database, the weather information in historical time, the unit price information of human and material costs, and the power grid operation virtual system are evaluated through the power grid fault maintenance cost evaluation model to obtain the power grid fault maintenance operation evaluation cost of each other power grid area; Based on each other power grid area in the value database, the actual cost of the corresponding power grid fault maintenance operation is subtracted from the assessed cost of the power grid fault maintenance operation to obtain the cost difference; Perform a vector sum operation on the cost differences corresponding to all other power grid areas in the value database to obtain a cost difference vector sum; Divide the sum of the cost difference vectors by the number of other grid areas in the value database to obtain a cost difference average vector; The obtained power grid management and operation cost of the power grid management area is added to the cost difference average vector to obtain the revised power grid management and operation cost of the power grid management area.

[0012] The second aspect of the present invention further proposes a power grid management platform operation cost evaluation system based on big data, comprising a memory and a processor, wherein the memory comprises a power grid management platform operation cost evaluation method program based on big data, and when the power grid management platform operation cost evaluation method program based on big data is executed by the processor, the following steps are implemented: Obtain the current grid operation status data information in the grid management area through big data technology; A virtual grid operation system is constructed by modeling based on current grid operation status data information to simulate; Based on the virtual system of power grid operation, a corresponding power grid transformation plan is formulated according to the transformation evaluation algorithm; Based on the grid transformation plan and through the grid transformation cost assessment model, the corresponding grid transformation operation cost is evaluated; The power grid operation virtual system is updated according to the power grid transformation plan, and an updated power grid operation virtual system is formed; An operating cost assessment is conducted based on the updated grid operation virtual system to obtain the grid management operating cost of the grid management area.

[0013] Furthermore, based on the grid transformation plan and through the grid transformation cost assessment model, the corresponding grid transformation operating costs are evaluated, including: Construct a cost assessment model for power grid transformation; The power grid transformation cost assessment model is trained and optimized through sample data to obtain an optimized power grid transformation cost assessment model; Based on big data information technology, obtain terrain information, traffic information, and unit price information of manpower and material costs in the area involved in the power grid transformation plan; The terrain information, traffic information, and unit price information of manpower and material resources are combined with the grid transformation plan and evaluated through the grid transformation cost evaluation model to obtain the grid transformation operation cost.

[0014] Furthermore, the operation cost is evaluated based on the updated grid operation virtual system to obtain the grid management operation cost, which specifically includes: Construct a power grid failure maintenance cost assessment model; The power grid failure maintenance cost assessment model is trained and optimized through sample data to obtain an optimized power grid failure maintenance cost assessment model; Based on big data information technology, obtain the current geographic information, weather information, and unit price information of human and material costs in the power grid management area; The geographic information, weather information, and unit price information of human and material costs in the power grid management area are combined with the updated power grid operation virtual system and evaluated through the power grid fault maintenance cost evaluation model to obtain the power grid fault maintenance operation cost.

[0015] The third aspect of the present invention also proposes a computer-readable storage medium, which includes a power grid management platform operating cost assessment method program based on big data. When the power grid management platform operating cost assessment method program based on big data is executed by a processor, the steps of the above-mentioned power grid management platform operating cost assessment method based on big data are implemented.

[0016] The present invention proposes a method, system and medium for evaluating the operation cost of a power grid management platform based on big data. Through big data analysis technology and data modeling technology, and with the help of an evaluation model, the intelligent analysis and evaluation of the operation cost of the power grid management platform is realized. Compared with the traditional method of manual data analysis and cost evaluation, it can effectively simplify the difficulty of evaluating the operation cost of the power grid, improve the accuracy of the evaluation of the operation cost of the power grid, and provide the main support basis for stabilizing the operation balance of the power grid system. At the same time, it is conducive to improving the operating efficiency of the power system, reducing electricity prices, and ensuring the stability of power supply.

[0017] Additional aspects and advantages of the present invention will be given in part in the following description, and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flowchart of a method for evaluating the operation cost of a power grid management platform based on big data is shown in the present invention; Figure 2 A flow chart showing the evaluation of the power grid transformation operation cost of the present invention is shown; Figure 3 A flow chart showing the evaluation of the power grid failure maintenance operation cost of the present invention is shown; Figure 4 A block diagram of a power grid management platform operating cost evaluation system based on big data of the present invention is shown. DETAILED DESCRIPTION

[0019] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0020] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0021] Figure 1 A flow chart of a method for evaluating operating costs of a power grid management platform based on big data is shown in the present invention.

[0022] like Figure 1 As shown, the first aspect of the present invention proposes a method for evaluating the operation cost of a power grid management platform based on big data, the method comprising: S102, obtaining current power grid operation status data information in the power grid management area through big data technology; S104, modeling based on the current grid operation status data information to simulate and construct a grid operation virtual system; S106, based on the power grid operation virtual system, and according to the transformation evaluation algorithm, a corresponding power grid transformation plan is formulated; S108, based on the power grid transformation plan and through the power grid transformation cost evaluation model, evaluating the corresponding power grid transformation operation cost; S110, updating the power grid operation virtual system according to the power grid transformation plan, and forming an updated power grid operation virtual system; S112, performing an operation cost assessment based on the updated power grid operation virtual system to obtain the power grid management operation cost of the power grid management area.

[0023] It should be noted that the various data and information required for the evaluation of the power grid management and operation costs in this application are extracted from a third-party platform. To be precise, the technical solution of this application is a solution for obtaining information, data, and parameters for technical processing by interacting with external data on a third-party power grid management platform. The technical solution of this application has means of information acquisition, data interaction and extraction, and data processing technology, and is not based on artificially set rules or economic / market / policy / project laws. The technical solution of this application has technical laws.

[0024] It should be noted that the present invention uses big data technology and data modeling technology to simulate and construct a virtual system for power grid operation, and on the basis of the virtual system for power grid operation, performs power grid transformation, and evaluates the corresponding power grid transformation operating cost through the power grid transformation cost evaluation model. Then, the power grid operation virtual system is updated according to the power grid transformation plan, and an updated power grid operation virtual system is formed. Finally, the operation cost is evaluated based on the updated power grid operation virtual system to obtain the power grid management operation cost. The present invention combines big data analysis technology and data modeling technology, and uses the evaluation model to realize the intelligent analysis and evaluation of the operation cost of the power grid management platform. Compared with the traditional method of manual data analysis and cost evaluation, it can effectively simplify the difficulty of power grid operation cost evaluation, improve the accuracy of power grid operation cost evaluation, and provide the main support basis for stabilizing the operation balance of the power grid system. At the same time, it is conducive to improving the operating efficiency of the power system, reducing electricity prices, and ensuring the stability of power supply.

[0025] According to a specific embodiment of the present invention, the current power grid operation status data information of the power grid management area is obtained by big data technology, specifically including: Acquire multiple pieces of operating status data information about target power grid nodes based on big data technology; Each piece of operation status data information about the target power grid node is compared with other operation status data information one by one for conflicts. If the two are in conflict, the former operation status data information is marked as conflict information, otherwise it is not marked; After the multiple pieces of operation status data information about the target power grid node have completed the pairwise conflict comparison, the total number of times each piece of operation status data information is marked as conflict information is counted; The running status data information whose total number of times marked as conflict information is greater than a first preset threshold is eliminated.

[0026] It can be understood that the conflict of the present invention refers to the contradiction between two pieces of information A and B, that is, if information A is true, then information B is not true; or if information B is true, then information A is not true.

[0027] It can be understood that the operating status data information about the target power grid node may include multiple types, such as the geographic information of the power grid node, administrative area divisions, distribution voltage numerical information, distribution current information, etc. There is a certain correlation and influence relationship between these information. If the geographic information conflicts with the administrative area division, this means that one of the two is wrong information. The present invention compares multiple information pairwise, thereby eliminating information that conflicts with the majority of information, and determines that it is likely to be wrong information, which can effectively screen out accurate operating status data information, thereby facilitating the subsequent accurate assessment of the power grid management and operation costs.

[0028] According to an embodiment of the present invention, based on the power grid operation virtual system and according to the transformation evaluation algorithm, a corresponding power grid transformation plan is formulated, which specifically includes: Obtain the target power grid area to be transformed; According to multiple transformable nodes in the target power grid area, all pre-selected transformation schemes are enumerated through a transformation preview method and added to a pre-selected transformation scheme library; According to the transformation evaluation algorithm, the pre-selected transformation schemes in the pre-selected transformation scheme library are optimized and analyzed to obtain the power grid transformation scheme for the target power grid area to be transformed.

[0029] According to a specific embodiment of the present invention, based on multiple transformable nodes in the target power grid area, all pre-selected transformation schemes are enumerated through a transformation preview method and added to a pre-selected transformation scheme library, specifically including: The preset target power grid area includes m power grid transformable nodes, and the transformation expected index of the target power grid area is K, where m is a positive integer greater than or equal to 1; Select one grid transformable node from each of the m grid transformable nodes, and perform a transformation preview according to the transformation plan corresponding to the selected grid transformable node, and evaluate whether this transformation reaches the transformation expected index K of the target grid area to be transformed. If it reaches, mark the grid transformable node selected this time, and associate and combine the grid transformable node selected this time and the corresponding transformation plan as a pre-selected transformation plan, and enter it into the pre-selected transformation plan library, and repeat this step until all grid transformable nodes are polled; Remove the marked nodes from the m grid-transformable nodes, and select every two grid-transformable nodes from the remaining grid-transformable nodes in turn, and perform transformation preview according to the transformation schemes corresponding to the selected grid-transformable nodes, and evaluate whether this transformation reaches the transformation expected index K of the target grid area to be transformed. If so, mark the two grid-transformable nodes selected this time, and associate and combine the two grid-transformable nodes selected this time and their corresponding transformation schemes as a pre-selected transformation scheme, and enter them into the pre-selected transformation scheme library, and repeat this step until all unmarked grid-transformable nodes are polled; The grid transformable nodes that have been marked in the previous p steps are removed, and each p grid transformable nodes are selected from the remaining grid transformable nodes in turn, and the transformation preview is performed according to the transformation schemes corresponding to the selected grid transformable nodes, and it is evaluated whether this transformation reaches the expected transformation index K of the target grid area to be transformed. If it reaches it, the p grid transformable nodes selected this time are marked, and the p grid transformable nodes selected this time and their corresponding transformation schemes are associated and combined as a pre-selected transformation scheme, and entered into the pre-selected transformation scheme library, and this step is repeated until all unmarked grid transformable nodes are polled, where p is a positive integer greater than or equal to 1 and less than or equal to m / 2.

[0030] It can be understood that the target grid area to be transformed is located in the grid management area, and the target grid area to be transformed may be a low voltage area in the grid management area, but is not limited thereto.

[0031] It can be understood that the grid transformable node is located in the target grid area to be transformed, and when the target grid area to be transformed may be a low voltage area in the grid management area, the corresponding grid transformable node is a substation.

[0032] It is understandable that with the continuous increase in rural and urban electricity consumption, some regional distribution networks have experienced increasingly serious low voltage problems, which have harmed the operation of electrical equipment and power systems, increased grid losses, and increased power supply costs, making it impossible to meet residents' electricity needs. The present invention transforms the distribution network area that produces low voltage, reduces grid losses, and can effectively reduce power supply costs and meet residents' electricity needs.

[0033] It can be understood that when obtaining multiple transformable grid nodes in the target grid area, the present invention can enumerate all transformable nodes in the target grid area, and then combine them based on these transformable nodes and the above-mentioned analysis algorithm to form a corresponding pre-selected transformation plan.

[0034] In a specific embodiment, m is preset to be equal to 3, and they are respectively grid transformable nodes D1, grid transformable nodes D2, and grid transformable nodes D3; the number of grid transformable nodes marked in the first step is preset to be 0, and the number of remaining and unmarked grid transformable nodes in the second step is 3, namely, grid transformable nodes D1, D2, and D3; at this time, three combinations of every 2 grid transformable nodes are selected, namely, combination 1: D1, D2, combination 2: D1, D3, and combination 3: D2, D3. It is necessary to judge the three combinations separately, that is, first select combination 1, if it is evaluated that this transformation reaches the transformation expected index K of the target grid area to be transformed, then D1 and D2 of combination 1 are associated and marked separately; similarly, then select combination 2 and combination 3 in turn, and respectively evaluate whether the transformation previewed in combination 2 or combination 3 reaches the transformation expected index K of the target grid area to be transformed. From the above, it can be seen that the present invention gradually increases the selected grid transformable nodes from the first step to the second step. It can be understood that if one grid transformable node is selected for transformation in the first step, the expected transformation index K of the target grid area can be achieved. Based on avoiding reducing too many unnecessary transformations, there is no need to involve the grid transformable nodes marked in the first step in the process of selecting two grid transformable nodes in the second step.

[0035] It can be understood that the transformation expected index K is based on the expected transformation effect of the target power grid area. For example, if the target power grid area is a low voltage area, the transformation expected index K can be set to a standard voltage value. However, it is not limited thereto.

[0036] According to an embodiment of the present invention, a preferred analysis process is performed on the pre-selected transformation schemes in the pre-selected transformation scheme library according to the transformation evaluation algorithm to obtain a power grid transformation scheme for the target power grid area to be transformed, specifically including: For each pre-selected transformation scheme in the pre-selected transformation scheme library, respectively obtaining parameter data under each pre-selected transformation scheme; Compare the parameter data of all pre-selected transformation schemes in the pre-selected transformation scheme library in pairs, and score each pre-selected transformation scheme using a preset scoring algorithm; In the pre-selected transformation plan library, the pre-selected transformation plan with the highest score is selected as the power grid transformation plan for the target power grid area to be transformed.

[0037] According to a specific embodiment of the present invention, all pre-selected transformation schemes in the pre-selected transformation scheme library are compared with each other in terms of parameter data, and each pre-selected transformation scheme is scored by a preset scoring algorithm; in the pre-selected transformation scheme library, the pre-selected transformation scheme with the highest score is selected as the power grid transformation scheme for the target power grid area to be transformed, specifically including: The parameter data preset under each pre-selected transformation plan include: the number of nodes that can be transformed in the power grid, the excess amount exceeding the expected transformation index K, and the difficulty of transformation; The number of transformable nodes of the power grid under each pre-selected transformation scheme in the pre-selected transformation scheme library is compared one by one with the number of transformable nodes of the power grid under the remaining pre-selected transformation schemes. If the former is less than the latter, the quantity advantage item of the former pre-selected transformation scheme is added 1 point; The excess amount of the transformation target grid area achieved under each pre-selected transformation scheme in the pre-selected transformation scheme library exceeding the transformation expected index K is compared one by one with the excess amount of the transformation target grid area achieved under the remaining pre-selected transformation schemes exceeding the transformation expected index K. If the former is greater than the latter, the transformation effect item of the former pre-selected transformation scheme is added with 1 point; The transformation difficulty of each pre-selected transformation plan in the pre-selected transformation plan library is compared with the transformation difficulty of the remaining pre-selected transformation plans one by one. If the former is less than the latter, the transformation difficulty item of the former pre-selected transformation plan is increased by 1 point; All pre-selected transformation schemes in the pre-selected transformation scheme library are compared in pairs for the number of nodes that can be transformed in the power grid, and the total score of the quantity advantage item under each pre-selected transformation scheme is calculated statistically; all pre-selected transformation schemes in the pre-selected transformation scheme library are compared in pairs for the excess amount exceeding the expected transformation index K, and the total score of the transformation effect item under each pre-selected transformation scheme is calculated statistically; all pre-selected transformation schemes in the pre-selected transformation scheme library are compared in pairs for the transformation difficulty, and the total score of the transformation difficulty item under each pre-selected transformation scheme is calculated statistically; The influence weights of the preset quantity advantage item, transformation effect item and transformation difficulty item on the selection of power grid transformation schemes are different. The total score of the quantity advantage item of each pre-selected transformation scheme is multiplied by the corresponding influence weight to obtain the weight score of the quantity advantage item, the total score of the transformation effect item of each pre-selected transformation scheme is multiplied by the corresponding influence weight to obtain the weight score of the transformation effect item, and the total score of the transformation difficulty item of each pre-selected transformation scheme is multiplied by the corresponding influence weight to obtain the weight score of the transformation difficulty item; The weighted scores of the quantity advantage item, the transformation effect item, and the transformation difficulty item of each pre-selected transformation plan are added together to obtain the weighted total score of each pre-selected transformation plan; In the pre-selected transformation plan library, the pre-selected transformation plan with the highest total weight score is selected as the power grid transformation plan for the target power grid area to be transformed.

[0038] It can be understood that, based on the premise of achieving the expected transformation indicator K, unnecessary excessive transformation should be minimized as much as possible, and the fewer the number of transformable grid nodes included in the pre-selected transformation plan, the better; at the same time, under the premise of including the same number of transformable grid nodes in the same two pre-selected transformation plans, the larger the excess amount that exceeds the expected transformation indicator K, the better.

[0039] Based on the above-mentioned optimization analysis method, the present invention combines multiple dimensions such as quantity advantage, transformation effect and transformation difficulty for comparison, and further normalizes the different influence weights of the selection in combination with each dimension, so as to reasonably select the best power grid transformation plan suitable for the target power grid area to be transformed.

[0040] like Figure 2 As shown in the figure, based on the grid transformation plan and through the grid transformation cost evaluation model, the corresponding grid transformation operating costs are evaluated, including: S202, constructing a cost assessment model for power grid transformation; S204, training and optimizing the power grid transformation cost assessment model through sample data to obtain an optimized power grid transformation cost assessment model; S206, based on big data information technology, obtaining terrain information, traffic information, and unit price information of manpower and material cost in the area involved in the power grid transformation plan; S208, combining terrain information, traffic information, and unit price information of manpower and material resources with the power grid transformation plan, and evaluating through a power grid transformation cost evaluation model to obtain the power grid transformation operation cost.

[0041] like Figure 3 As shown in the figure, the operation cost is evaluated based on the updated grid operation virtual system to obtain the grid management operation cost, which specifically includes: S302, constructing a power grid failure maintenance cost assessment model; S304, training and optimizing the power grid failure maintenance cost evaluation model through sample data to obtain an optimized power grid failure maintenance cost evaluation model; S306, based on big data information technology, obtaining current geographic information, weather information, and unit price information of human and material cost in the power grid management area; S308, combining the geographic information, weather information, and unit price information of manpower and material cost in the power grid management area with the updated power grid operation virtual system, and evaluating through the power grid fault maintenance cost evaluation model to obtain the power grid fault maintenance operation cost.

[0042] It can be understood that the power grid fault maintenance operation cost is a major part of the power grid operation cost. The present invention combines the current geographic information, weather information, and unit price information of human and material costs in the power grid management area, as well as the updated power grid operation virtual system, and accurately evaluates the power grid fault maintenance operation cost through a power grid fault maintenance cost evaluation model.

[0043] According to a specific embodiment of the present invention, an operation cost assessment is performed based on the updated power grid operation virtual system to obtain the power grid management operation cost, which specifically includes: Construct a cost assessment model for power grid generation; The power grid generation cost assessment model is trained and optimized through sample data to obtain an optimized power grid generation cost assessment model; Based on big data information technology, obtain traditional energy information in the power grid management area and local clean energy information; The geographic information, traditional energy information and local clean energy information are combined with the updated grid operation virtual system and evaluated through the grid power generation cost evaluation model to obtain the grid power generation operation cost.

[0044] It can be understood that the power grid power generation operating cost is a major part of the power grid operating cost. Preferably, the traditional energy information can include unit price information of coal, oil, natural gas, etc., and the clean energy information can include unit price information of wind energy, solar energy, tidal energy, etc.

[0045] According to an embodiment of the present invention, after evaluating through the power grid fault maintenance cost evaluation model to obtain the power grid management operation cost of the power grid management area, the method further includes: Based on big data information technology, historical grid operation data of multiple other grid areas are obtained, and the historical grid operation data of each other grid area at least includes: geographic information of other grid areas, weather information at historical time, unit price information of human and material costs, and grid operation status data information, and actual cost of grid fault maintenance and operation in other grid areas; Based on the historical power grid operation data of each other power grid area, the geographical information of the other power grid areas and the weather information at the historical time included therein are subjected to feature calculation to obtain the feature value of each other power grid area; Perform feature calculation on the geographic information and weather information of the power grid management area to obtain the feature value of the power grid management area; Perform a difference operation on the characteristic value of each other power grid area and the characteristic value of the power grid management area; Determine whether the difference between the two is less than a third preset threshold value, and if so, mark the historical power grid operation data corresponding to other power grid areas as valuable data and enter them into the value database; Based on the grid operation status data information of the historical grid operation data of each other grid area in the value database, modeling is performed to simulate the grid operation virtual system of other grid areas; The geographical information of each other power grid area in the value database, the weather information in historical time, the unit price information of human and material costs, and the power grid operation virtual system are evaluated through the power grid fault maintenance cost evaluation model to obtain the power grid fault maintenance operation evaluation cost of each other power grid area; Based on each other power grid area in the value database, the actual cost of the corresponding power grid fault maintenance operation is subtracted from the assessed cost of the power grid fault maintenance operation to obtain the cost difference; Perform a vector sum operation on the cost differences corresponding to all other power grid areas in the value database to obtain a cost difference vector sum; Divide the sum of the cost difference vectors by the number of other grid areas in the value database to obtain a cost difference average vector; The obtained power grid management and operation cost of the power grid management area is added to the cost difference average vector to obtain the revised power grid management and operation cost of the power grid management area.

[0046] It can be understood that the present invention obtains historical grid operation data of multiple other grid areas through big data information technology, and uses the historical grid operation data of multiple other grid areas to correct the assessed grid management operation costs of the grid management area, so as to obtain more accurate grid management operation costs.

[0047] According to a specific embodiment of the present invention, based on the historical power grid operation data of each other power grid area, the geographical information of the other power grid areas and the weather information at the historical time included therein are subjected to feature calculation to obtain the feature value of each other power grid area; the geographical information and weather information of the power grid management area are subjected to feature calculation to obtain the feature value of the power grid management area; the feature value of each other power grid area is subjected to difference calculation with the feature value of the power grid management area, specifically including: The preset geographic information includes the regional center latitude information, mountain area ratio, and plain ratio; The regional center latitude information, mountain proportion, and plain proportion in the geographic information of other power grid areas are multiplied respectively to obtain the geographic characteristic values ​​of other power grid areas, and the regional center latitude information, mountain proportion, and plain proportion in the geographic information of the power grid management area are multiplied respectively to obtain the geographic characteristic value of the power grid management area; Preset weather information includes the average number of snow days per year, the average number of freezing rain days per year, and the average number of typhoons per year; The annual average number of snow days, annual average number of freezing rain, and annual average number of typhoons in the weather information of other power grid areas are added to obtain the weather characteristic values ​​of other power grid areas, and the annual average number of snow days, annual average number of freezing rain, and annual average number of typhoons in the weather information of the power grid management area are added to obtain the weather characteristic value of the power grid management area; Perform difference calculation on the geographical characteristic values ​​of other power grid areas and the power grid management area to obtain the difference G1 of the geographical characteristic values; Perform difference calculation on the weather characteristic values ​​of other power grid areas and the power grid management area to obtain the difference G2 of the weather characteristic values; The influence weight of geographic information on the power grid operation cost of the two regions is preset as W1, and the influence weight of weather information on the power grid operation cost of the two regions is preset as W2; Multiply the geographic feature value difference G1 by the corresponding influence weight W1 to obtain the geographic feature value difference weight G1* W1, and multiply the weather feature value difference G2 by the corresponding influence weight W2 to obtain the weather feature value difference weight G2* W2; Add the geographical feature value difference weight value G1* W1 and the weather feature value difference weight value G2* W2 to obtain the difference weight sum (G1* W1+ G2* W2), and divide the difference weight sum (G1* W1+ G2* W2) by (W1+ W2) to obtain the difference (G1* W1+ G2* W2) / (W1+ W2).

[0048] Figure 4 A block diagram of a power grid management platform operating cost evaluation system based on big data of the present invention is shown.

[0049] like Figure 4 As shown, the second aspect of the present invention further proposes a power grid management platform operation cost evaluation system 4 based on big data, including a memory 41 and a processor 42, wherein the memory includes a power grid management platform operation cost evaluation method program based on big data, and the power grid management platform operation cost evaluation method program based on big data is executed by the processor to implement the following steps: Obtain the current grid operation status data information in the grid management area through big data technology; A virtual grid operation system is constructed by modeling based on current grid operation status data information to simulate; Based on the virtual system of power grid operation, a corresponding power grid transformation plan is formulated according to the transformation evaluation algorithm; Based on the grid transformation plan and through the grid transformation cost assessment model, the corresponding grid transformation operation cost is evaluated; The power grid operation virtual system is updated according to the power grid transformation plan, and an updated power grid operation virtual system is formed; An operating cost assessment is conducted based on the updated grid operation virtual system to obtain the grid management operating cost of the grid management area.

[0050] According to an embodiment of the present invention, based on the power grid transformation plan and through the power grid transformation cost evaluation model, the corresponding power grid transformation operation cost is evaluated, specifically including: Construct a cost assessment model for power grid transformation; The power grid transformation cost assessment model is trained and optimized through sample data to obtain an optimized power grid transformation cost assessment model; Based on big data information technology, obtain terrain information, traffic information, and unit price information of manpower and material costs in the area involved in the power grid transformation plan; The terrain information, traffic information, and unit price information of manpower and material resources are combined with the grid transformation plan and evaluated through the grid transformation cost evaluation model to obtain the grid transformation operation cost.

[0051] According to an embodiment of the present invention, an operation cost assessment is performed based on the updated power grid operation virtual system to obtain the power grid management operation cost, which specifically includes: Construct a power grid failure maintenance cost assessment model; The power grid failure maintenance cost assessment model is trained and optimized through sample data to obtain an optimized power grid failure maintenance cost assessment model; Based on big data information technology, obtain the current geographic information, weather information, and unit price information of human and material costs in the power grid management area; The geographic information, weather information, and unit price information of human and material costs in the power grid management area are combined with the updated power grid operation virtual system and evaluated through the power grid fault maintenance cost evaluation model to obtain the power grid fault maintenance operation cost.

[0052] The third aspect of the present invention also proposes a computer-readable storage medium, which includes a power grid management platform operating cost assessment method program based on big data. When the power grid management platform operating cost assessment method program based on big data is executed by a processor, the steps of the above-mentioned power grid management platform operating cost assessment method based on big data are implemented.

[0053] The method, system and medium for evaluating the operation cost of a power grid management platform based on big data proposed in the present invention simulate the power grid operation virtual system constructed by big data technology and data modeling technology, and on the basis of the power grid operation virtual system, the power grid is transformed, and the corresponding power grid transformation operation cost is evaluated by the power grid transformation cost evaluation model. Then, the power grid operation virtual system is updated according to the power grid transformation plan, and an updated power grid operation virtual system is formed. Finally, the operation cost is evaluated based on the updated power grid operation virtual system to obtain the power grid management operation cost. The present invention combines big data analysis technology and data modeling technology, and uses the evaluation model to realize the intelligent analysis and evaluation of the operation cost of the power grid management platform. Compared with the traditional method of manual data analysis and cost evaluation, it can effectively simplify the difficulty of power grid operation cost evaluation, improve the accuracy of power grid operation cost evaluation, and provide the main support basis for stabilizing the operation balance of the power grid system. At the same time, it is conducive to improving the operation efficiency of the power system, reducing electricity prices, and ensuring the stability of power supply.

[0054] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0055] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0056] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0057] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0058] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0059] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for evaluating the operation cost of a power grid management platform based on big data, characterized in that: The method comprises: Obtain the current grid operation status data information in the grid management area through big data technology; A virtual grid operation system is constructed by modeling based on the current grid operation status data information to simulate the grid operation; Based on the virtual system of power grid operation, a corresponding power grid transformation plan is formulated according to the transformation evaluation algorithm; Based on the grid transformation plan and through the grid transformation cost assessment model, the corresponding grid transformation operating costs are evaluated; The power grid operation virtual system is updated according to the power grid transformation plan, and an updated power grid operation virtual system is formed; An operating cost assessment is conducted based on the updated grid operation virtual system to obtain the grid management operating cost of the grid management area.

2. According to the big data-based power grid management platform operation cost evaluation method of claim 1, it is characterized in that: Based on the virtual system of power grid operation and the transformation evaluation algorithm, a corresponding power grid transformation plan is formulated, including: Obtain the target power grid area to be transformed; According to multiple transformable nodes in the target power grid area, all pre-selected transformation schemes are enumerated through a transformation preview method and added to a pre-selected transformation scheme library; According to the transformation evaluation algorithm, the pre-selected transformation schemes in the pre-selected transformation scheme library are optimized and analyzed to obtain the power grid transformation scheme for the target power grid area to be transformed.

3. According to the big data-based power grid management platform operation cost evaluation method of claim 2, it is characterized in that: According to the transformation evaluation algorithm, the pre-selected transformation schemes in the pre-selected transformation scheme library are optimized and analyzed to obtain a power grid transformation scheme for the target power grid area to be transformed, which specifically includes: For each pre-selected transformation scheme in the pre-selected transformation scheme library, respectively obtaining parameter data under each pre-selected transformation scheme; Compare the parameter data of all pre-selected transformation schemes in the pre-selected transformation scheme library in pairs, and score each pre-selected transformation scheme using a preset scoring algorithm; In the pre-selected transformation plan library, the pre-selected transformation plan with the highest score is selected as the power grid transformation plan for the target power grid area to be transformed.

4. The method for evaluating the operation cost of a power grid management platform based on big data according to claim 1, characterized in that: Based on the grid transformation plan and through the grid transformation cost assessment model, the corresponding grid transformation operating costs are evaluated, including: Construct a cost assessment model for power grid transformation; The power grid transformation cost assessment model is trained and optimized through sample data to obtain an optimized power grid transformation cost assessment model; Based on big data information technology, obtain terrain information, traffic information, and unit price information of manpower and material costs in the area involved in the power grid transformation plan; The terrain information, traffic information, and unit price information of manpower and material resources are combined with the grid transformation plan and evaluated through the grid transformation cost evaluation model to obtain the grid transformation operation cost.

5. The method for evaluating the operation cost of a power grid management platform based on big data according to claim 1, characterized in that: Based on the updated grid operation virtual system, the operation cost is evaluated to obtain the grid management operation cost, which includes: Construct a power grid failure maintenance cost assessment model; The power grid failure maintenance cost assessment model is trained and optimized through sample data to obtain an optimized power grid failure maintenance cost assessment model; Based on big data information technology, obtain the current geographic information, weather information, and unit price information of human and material costs in the power grid management area; The geographic information, weather information, and unit price information of human and material costs in the power grid management area are combined with the updated power grid operation virtual system and evaluated through the power grid fault maintenance cost evaluation model to obtain the power grid fault maintenance operation cost.

6. The method for evaluating the operation cost of a power grid management platform based on big data according to claim 5 is characterized in that: After evaluating the power grid failure maintenance cost evaluation model to obtain the power grid management operation cost of the power grid management area, the method further includes: Based on big data information technology, historical grid operation data of multiple other grid areas are obtained, and the historical grid operation data of each other grid area at least includes: geographic information of other grid areas, weather information at historical time, unit price information of human and material costs, and grid operation status data information, and actual cost of grid fault maintenance and operation in other grid areas; Based on the historical power grid operation data of each other power grid area, the geographical information of the other power grid areas and the weather information at the historical time included therein are subjected to feature calculation to obtain the feature value of each other power grid area; Perform feature calculation on the geographic information and weather information of the power grid management area to obtain the feature value of the power grid management area; Perform a difference operation on the characteristic value of each other power grid area and the characteristic value of the power grid management area; Determine whether the difference between the two is less than a third preset threshold value, and if so, mark the historical power grid operation data corresponding to other power grid areas as valuable data and enter them into the value database; Based on the grid operation status data information of the historical grid operation data of each other grid area in the value database, modeling is performed to simulate the grid operation virtual system of other grid areas; The geographical information of each other power grid area in the value database, the weather information in historical time, the unit price information of human and material costs, and the power grid operation virtual system are evaluated through the power grid fault maintenance cost evaluation model to obtain the power grid fault maintenance operation evaluation cost of each other power grid area; Based on each other power grid area in the value database, the actual cost of the corresponding power grid fault maintenance operation is subtracted from the assessed cost of the power grid fault maintenance operation to obtain the cost difference; Perform a vector sum operation on the cost differences corresponding to all other power grid areas in the value database to obtain a cost difference vector sum; Divide the sum of the cost difference vectors by the number of other grid areas in the value database to obtain a cost difference average vector; The obtained power grid management and operation cost of the power grid management area is added to the cost difference average vector to obtain the revised power grid management and operation cost of the power grid management area.

7. A power grid management platform operation cost evaluation system based on big data, characterized in that: The invention comprises a memory and a processor, wherein the memory comprises a method program for evaluating the operation cost of a power grid management platform based on big data, and when the method program for evaluating the operation cost of a power grid management platform based on big data is executed by the processor, the following steps are implemented: Obtain the current grid operation status data information in the grid management area through big data technology; A virtual grid operation system is constructed by modeling based on the current grid operation status data information to simulate the grid operation; Based on the virtual system of power grid operation, a corresponding power grid transformation plan is formulated according to the transformation evaluation algorithm; Based on the grid transformation plan and through the grid transformation cost assessment model, the corresponding grid transformation operating costs are evaluated; The power grid operation virtual system is updated according to the power grid transformation plan, and an updated power grid operation virtual system is formed; An operating cost assessment is conducted based on the updated grid operation virtual system to obtain the grid management operating cost of the grid management area.

8. The big data-based power grid management platform operation cost evaluation system according to claim 7, characterized in that: Based on the grid transformation plan and through the grid transformation cost assessment model, the corresponding grid transformation operating costs are evaluated, including: Construct a cost assessment model for power grid transformation; The power grid transformation cost assessment model is trained and optimized through sample data to obtain an optimized power grid transformation cost assessment model; Based on big data information technology, obtain terrain information, traffic information, and unit price information of manpower and material costs in the area involved in the power grid transformation plan; The terrain information, traffic information, and unit price information of manpower and material resources are combined with the grid transformation plan and evaluated through the grid transformation cost evaluation model to obtain the grid transformation operation cost.

9. The big data-based power grid management platform operation cost evaluation system according to claim 7, characterized in that: Based on the updated grid operation virtual system, the operation cost is evaluated to obtain the grid management operation cost, which includes: Construct a power grid failure maintenance cost assessment model; The power grid failure maintenance cost assessment model is trained and optimized through sample data to obtain an optimized power grid failure maintenance cost assessment model; Based on big data information technology, obtain the current geographic information, weather information, and unit price information of human and material costs in the power grid management area; The geographic information, weather information, and unit price information of human and material costs in the power grid management area are combined with the updated power grid operation virtual system and evaluated through the power grid fault maintenance cost evaluation model to obtain the power grid fault maintenance operation cost.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a method program for evaluating the operating cost of a power grid management platform based on big data. When the method program for evaluating the operating cost of a power grid management platform based on big data is executed by a processor, the steps of a method for evaluating the operating cost of a power grid management platform based on big data as described in any one of claims 1 to 6 are implemented.

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