Power grid technical improvement project optimization decision-making method and system based on benefit indexes

Abstract

The invention discloses a power grid technical improvement project optimization decision-making method and system based on benefit indexes, and relates to the technical field of optimization decision-making, and the method comprises the following steps: obtaining project priority influence data of power grid technical improvement, the project priority influence data comprises equipment priority influence data, environment priority influence data and safety priority influence data, and the equipment priority influence data comprises equipment priority influence data, environment priority influence data and safety priority influence data; the evaluation standard is quantified into a unified evaluation standard; determining the weight of each item priority influence data by using an analytic hierarchy process, establishing a comprehensive item priority evaluation model based on a neural network, and inputting the item priority influence data into the model to generate a comprehensive priority evaluation coefficient; according to all the comprehensive priority evaluation coefficients needing technical improvement, the priority order of the projects needing technical improvement is arranged in a descending order mode, and the optimal power grid technical improvement project is decided in combination with investment data of the power grid technical improvement project. Through the benefit index decision-making method, the problems that the investment is limited and the optimal power grid technical improvement cannot be comprehensively decided are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of optimal decision-making for power grid technical transformation projects, and more specifically, to a method and system for optimal decision-making for power grid technical transformation projects based on benefit indicators. Background Art

[0002] Grid technical transformation projects refer to projects that transform, update, periodically replace, repair and maintain power transmission, distribution and power supply related equipment and corresponding ancillary facilities, aiming to improve the safety, stability and reliability of the power system. Grid technical transformation projects include equipment updates, technical transformation, factory maintenance and system upgrades.

[0003] With the changes in the global energy structure and the increasing demand for electricity, the reliability and stability of the power grid are facing severe challenges. The existing power grid technology transformation projects often lack systematicity and scientificity in the optimization decision-making, resulting in unsatisfactory project implementation results and serious waste of resources. Therefore, a new decision-making method is urgently needed to effectively evaluate the benefits of different technical transformation projects and select the optimal solution. In view of the above problems, the present invention proposes a solution. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method and system for optimizing decision-making for power grid technical transformation projects based on benefit indicators. The benefit indicator decision-making method is used to solve the problem that it is impossible to make a comprehensive decision on the optimal power grid technical transformation when investment is limited.

[0005] To achieve the above object, the present invention provides the following technical solutions: The invention discloses a method and system for optimizing decision-making of power grid technical transformation projects based on benefit indicators, comprising the following steps: obtaining priority impact data of projects that need to undergo technical transformation of power grids, wherein the project priority impact data include equipment priority impact data, environment priority impact data and safety priority impact data, and quantifying them into a unified evaluation standard; using the analytic hierarchy process to determine the weight of each project priority impact data, and establishing a comprehensive project priority evaluation model based on a neural network, and inputting the project priority impact data into the model to generate a comprehensive priority evaluation coefficient; according to the comprehensive priority evaluation coefficients of all projects that need to undergo technical transformation, arranging the priority order of projects that need to undergo technical transformation in descending order, and combining the investment data of the power grid technical transformation project, finally deciding on the optimal project for the power grid technical transformation.

[0006] In a preferred embodiment, the equipment priority impact data refers to an equipment priority impact coefficient, the environment priority impact data includes an environment quality impact coefficient, and the safety priority impact data includes a safety priority impact coefficient.

[0007] In a preferred embodiment, the equipment priority impact coefficient is specifically obtained by the following method: obtaining the first data of the equipment based on market research, the first data including the equipment maintenance cost, labor cost and equipment cost; obtaining the equipment work efficiency data by detecting the output data and loss data of the equipment during the working time H of the power equipment; collecting the original value, depreciation rate and service life of the equipment, and calculating the remaining residual value of the equipment based on a preset residual value formula; obtaining the equipment priority impact coefficient based on the preset equipment priority impact formula according to the first data, work efficiency data and remaining residual value of the equipment.

[0008] In a preferred embodiment, the environmental quality impact coefficient is specifically obtained by the following method: based on the superposition principle, the electric field strength component of any point in the space is calculated according to the equivalent charge on the wire; the electromagnetic pollution coefficient is obtained based on the electromagnetic radiation pollution formula in the power grid project according to the electric field component combined with the vertical and horizontal components of the industrial frequency magnetic field on the ground and at a certain distance from the ground; the power generation during the project operation is determined; the air carbon emission coefficient is obtained based on the preset carbon emission pollution formula according to the power generation and the project carbon emission factor detected by the monitoring equipment; a certain range is determined with the project to be tested as the center, and the noise level during the working time period within the range is measured to collect the noise pollution coefficient; the environmental quality impact coefficient is obtained based on the preset environmental quality impact formula according to the electromagnetic pollution coefficient, the air carbon emission coefficient and the noise pollution coefficient.

[0009] In a preferred embodiment, the safety priority influence coefficient is specifically obtained by the following method: based on the material strength test, the material compressive strength data and shear strength data of the project equipment are obtained; and the material strength coefficient is obtained based on the material strength calculation formula according to the compressive strength data and the shear strength data; By real-time monitoring and acquiring equipment performance parameter data, the performance parameter data includes stable data of voltage and current, and stable data of output power; the safety priority impact coefficient is obtained based on a preset equipment safety impact formula according to the material strength coefficient combined with the equipment performance parameter data.

[0010] In a preferred embodiment, the analytic hierarchy process is used to determine the weight of each project priority impact data, and a comprehensive project priority evaluation model is established based on a neural network, and the project priority impact data is input into the model to generate a comprehensive priority evaluation coefficient. The specific steps are as follows: a hierarchical model is established, and the priority impact data of the prioritized projects is input into the model; based on professional comments, the relative importance of each factor is compared, and a judgment matrix is ​​constructed based on a 1-9 scaling method; the weight of each project priority impact data is obtained by calculating the eigenvectors and eigenroots of the judgment matrix; based on neural network technology, historical data is collected and trained in combination with the weight of each project priority impact data, and a comprehensive project priority evaluation model is established through real-time feedback and adjustment; and equipment priority impact data, environmental priority impact data, and safety priority impact data are input into the comprehensive project priority evaluation model to generate a comprehensive priority evaluation coefficient for the project.

[0011] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Use the benefit indicator decision-making method to solve the problem of being unable to make comprehensive decisions on the optimal grid technical transformation when investment is limited.

[0012] 2. When using neural network technology to solve existing power grid technology transformation projects, there is a lack of systematicness and scientificity in the optimization decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A schematic diagram of the structure of a method for optimizing decision-making for power grid technical transformation projects based on benefit indicators provided in an embodiment of the present application.

[0014] Figure 2 A schematic diagram of the structure of a power grid technical transformation project optimization decision-making system based on benefit indicators provided in an embodiment of the present application. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0016] Embodiment 1, Figure 1 The schematic diagram of the structure of the optimal decision-making method for power grid technical transformation projects based on benefit indicators provided in the embodiment of the present application includes the following steps: S1, obtain the priority impact data of projects that need to undergo power grid technical transformation, where the project priority impact data includes equipment priority impact data, environment priority impact data, and safety priority impact data, and quantify them into a unified evaluation standard.

[0017] In this example, the equipment priority impact data refers to the equipment priority impact coefficient. The equipment priority impact coefficient refers to the decline in the working or production efficiency of the current equipment during the operation of electricity due to some reasons of the power equipment, which brings about a decline in power efficiency. For example: aging of equipment, excessive service life of equipment, higher maintenance costs of equipment, and the cost of equipment being higher than the output of the equipment. For equipment with more serious situations like these, further equipment technology improvements will be made. Equipment priority impact data is crucial in the optimization decision of power grid projects. It not only affects the selection and configuration of equipment, but is also directly related to the operating efficiency, economy and sustainability of the power grid.

[0018] Analyzing equipment priority impact data to make optimal decisions on power grid technical transformation projects has the following advantages: Improve the scientificity and accuracy of decision-making: By collecting and analyzing the priority impact data of equipment, an objective basis can be provided for decision-making, reducing the deviation caused by subjective judgment. Equipment priority impact data can quantify the performance and status of each device, making it easier to compare the advantages and disadvantages of different devices and helping decision makers make more accurate choices.

[0019] Optimize resource allocation: Rationally allocate investment and give priority to equipment that has a greater impact on the operation and stability of the power grid, which can make capital investment more efficient and avoid waste of resources. Improve equipment utilization. By giving priority to upgrading or transforming key equipment, the efficiency of equipment use and the overall operation capacity of the power grid can be improved.

[0020] Reduce risks: Identify and avoid hidden dangers. Analyzing equipment priority impact data can identify potential faults and hidden dangers in advance, reduce risks in power grid operation, and ensure power supply safety. Improve reliability. Optimal decision-making can improve the overall reliability of the power grid system and ensure that the power grid can still operate stably under high load or extreme weather conditions.

[0021] Support sustainable development: Promote green transformation. By analyzing the priority impact of equipment, we can give priority to technical transformation of equipment with good energy-saving and emission-reduction effects to support the green development goals of the power grid. Enhance system flexibility and give priority to the transformation of equipment that has a great impact on the access and dispatch of renewable energy, which can improve the adaptability of the power grid to clean energy and promote sustainable development.

[0022] Improve operational efficiency: Reduce power outage time caused by faults. By optimizing equipment transformation and upgrading, it is possible to effectively reduce power outage time caused by equipment failures and improve the operational efficiency of the power grid. Optimizing scheduling and load management and analyzing equipment priority impact data can improve the scheduling strategy of the power grid, optimize load distribution, and improve overall operational efficiency.

[0023] Enhance emergency response capabilities: Develop emergency plans. By analyzing the impact on equipment, more effective emergency response plans can be developed to improve the ability to respond to emergencies. Rapid power restoration and optimal transformation of key equipment can shorten the recovery time after a failure and ensure the stability of power supply.

[0024] Promote technological innovation: encourage the application of new technologies, introduce new technologies and new equipment in the optimal decision-making process, and promote continuous technological progress and innovation. Promote industrial upgrading, promote the replacement of power grid equipment through analysis and evaluation, and contribute to the upgrading and development of the entire power industry.

[0025] The specific method for obtaining the device priority influence coefficient is as follows: Acquire first data of the equipment according to market research, wherein the first data includes maintenance cost, labor cost and equipment cost of the equipment; During the working time of the power equipment, the working efficiency data of the equipment is obtained by detecting the output data and loss data of the equipment; Collect the original value, depreciation rate and useful life of the equipment and calculate the remaining residual value of the equipment based on the preset residual value formula; The equipment priority influence coefficient is obtained based on a preset equipment priority influence formula according to the first data, work efficiency data and remaining residual value of the equipment.

[0026] The specific calculation formula for the equipment working efficiency data is as follows:

[0027] The specific calculation formula for the residual value of the equipment is as follows:

[0028] The specific calculation formula of the equipment priority influence coefficient is as follows:

[0029] In the formula, Y is the equipment priority influence coefficient, For work efficiency data, is the residual value of the equipment, For maintenance costs, is labor cost, S is equipment cost, is the output data of the equipment, is the power of the device, is the machine power factor of the equipment, is the loss data, is the machine loss factor, H is the working time of the equipment, D is the output data of the equipment, d(t) is the depreciation rate that changes with time, and t is the useful life.

[0030] It should be noted that when the equipment's working efficiency data is getting lower and lower, and the residual value of the equipment is getting lower and lower, the equipment priority impact coefficient will become larger and larger, indicating that the situation of the project equipment is getting more and more serious, and the various costs will also be higher and higher. Therefore, the equipment of this project can be given priority to carry out production technology transformation to improve the production technology of the equipment, thereby reducing additional maintenance costs, labor costs and operating costs, thereby improving the advantages of the overall project equipment and playing an important role in the power grid project.

[0031] Environmental priority impact data include environmental quality impact coefficients, which refer to data that prioritizes and quantifies the environmental quality impacts of power infrastructure projects when evaluating and selecting them. This type of data usually involves multiple aspects, including the impact of the project on environmental factors such as air, noise, electromagnetic radiation, and carbon emissions. The environmental quality impact coefficient plays a vital role in the decision-making of power grid project optimization. It is not only related to environmental protection, but also affects the feasibility, legality, and social acceptance of the project. Through scientific and reasonable environmental assessments, decision makers can better achieve a win-win situation for the economy and the environment.

[0032] The advantages of analyzing environmental priority impact data to make optimal decisions on power grid technical transformation projects are as follows: Improve environmental sustainability: Reduce environmental burdens. By giving priority to environmental factors, the negative impact of grid technology transformation on the ecological environment can be effectively reduced, such as reducing carbon emissions and other pollutant emissions. Support the access of renewable energy. Analyzing environmental priority impact data helps identify areas suitable for access to renewable energy (such as wind and solar energy) and improve the greenness of the grid.

[0033] Promote social acceptance: Enhance public trust. The decision-making process that prioritizes the environment can improve public acceptance of power grid projects, because the public generally pays attention to environmental issues, and relevant analysis will make the project more transparent. Reduce social conflicts. By fully evaluating and disclosing environmental impacts, residents' opposition and social conflicts caused by project implementation can be reduced.

[0034] Optimize economic benefits: Reduce environmental governance costs. Consider environmental factors in the early stages of a project to avoid governance costs and legal liabilities caused by environmental problems in the later stages. Improve project investment returns. Green projects can often attract more investment, especially those that focus on sustainable development, further improving economic benefits.

[0035] Technological innovation and improvement: Encouraging the research and development of green technologies and paying attention to environmental factors in optimal decision-making can stimulate innovation in related technologies, such as energy-saving technologies, smart grid technologies, and energy management systems. Promoting the intelligence of the power grid, through the analysis of the priority impacts on the environment, can promote investment in the intelligence and informatization of the power grid to better manage and dispatch energy.

[0036] Comprehensive risk management: Identify potential risks. Environmental-first analysis helps to identify possible environmental risks early, so that necessary risk assessments and response strategies can be formulated during the project planning stage. Enhance resilience. In the face of uncertainties brought about by environmental factors such as climate change, giving priority to environmental impacts can enhance the adaptability and resilience of the power grid system.

[0037] The specific method for obtaining the environmental quality impact coefficient is as follows: Based on the superposition principle, the electric field intensity components at any point in space are calculated according to the equivalent charge on the wire; The electromagnetic pollution coefficient is obtained based on the electromagnetic radiation pollution formula in power grid engineering according to the electric field component combined with the vertical and horizontal components of the power frequency magnetic field on the ground and at a certain distance from the ground; Determine the amount of electricity generated during the project work; The air carbon emission coefficient is obtained based on the preset carbon emission pollution formula according to the power generation and the project carbon emission factor detected by the monitoring equipment; Centered on the project to be tested, determine a certain range, measure the noise level during the working hours within the range, and collect the noise pollution coefficient; The environmental quality impact coefficient is obtained based on the preset environmental quality impact formula according to the electromagnetic pollution coefficient, the air carbon emission coefficient and the noise pollution coefficient.

[0038] The specific calculation formula of the electromagnetic pollution coefficient is as follows:

[0039] The specific calculation formula of the carbon emission coefficient is as follows:

[0040] The specific calculation formula of the environmental quality impact coefficient is as follows:

[0041] In the formula, is the environmental quality impact coefficient, E is the electromagnetic pollution coefficient, G is the carbon emission coefficient, is the noise pollution coefficient, For reference of reasonable noise coefficient, For electricity consumption, is the carbon emission factor, is the carbon emission time, is the carbon emission absorbed by the absorption device, m is the total number of wires, i is the i-th wire, i=1,2,3...,n, n is an integer, and are the horizontal and vertical coordinates of wire i, L is the distance from wire i and its mirror image to the calculation point, and is the unit matrix on each wire.

[0042] It should be noted that when the electromagnetic pollution coefficient becomes larger and larger, the carbon emission coefficient becomes higher and higher, and the noise pollution coefficient becomes larger and larger, it means that the environmental quality impact coefficient is getting larger and larger, and the project has caused pollution to the current environment, and it is necessary to give priority to technical transformation and treatment.

[0043] Safety priority impact data includes the safety priority impact coefficient, which is a key indicator used in power grid technology transformation decision-making. It measures the priority of safety factors when performing power grid transformation. Specifically, it helps decision makers evaluate the impact of safety on the overall system operation in different transformation plans to ensure that the safety of the power grid is not neglected while pursuing efficiency and cost optimization.

[0044] Analyzing the safety priority impact coefficient to make optimal decisions on power grid technical transformation projects has the following advantages: Improve safety: Risk identification and management, safety-first analysis can help identify potential safety risks, ensure that these factors are given priority in the decision-making process, and reduce the probability of accidents and failures. Safety standards compliance, during technical transformation, ensure compliance with the latest safety standards and specifications, thereby improving the overall safety level of the power grid.

[0045] Cost control for economic benefits: By analyzing safety data in the early stage, high compensation and repair costs caused by accidents can be prevented, thereby effectively controlling overall costs. Return on investment, giving priority to projects with higher safety performance, can usually reduce economic losses caused by power outages and equipment failures, and improve return on investment.

[0046] Technical feasibility: Data-driven decision-making, using safety-first data analysis, can more scientifically evaluate the feasibility of technical solutions, thereby selecting a more appropriate technical path. Innovation and optimization: During the analysis process, the shortcomings of existing technologies may be discovered, which can stimulate technological innovation and improve the overall quality of the transformation plan.

[0047] Sustainable development: Safety-first decisions help consider environmental impacts, promote the use of clean and renewable energy, and reduce negative impacts on the environment.

[0048] Enhance public confidence: Transparent consideration of safety factors in the project decision-making process can enhance public trust in grid transformation and improve social recognition of the project.

[0049] Long-term stability: System resilience. Giving priority to transformation solutions with higher safety performance can improve the resilience of the power grid, enabling it to better respond to natural disasters or emergencies and maintain system stability.

[0050] The specific method for obtaining the safety priority impact coefficient is as follows: Based on material strength testing, obtain material compressive strength data and shear strength data of project equipment; Obtain material strength coefficient based on material strength calculation formula according to compressive strength data and shear strength data; By real-time monitoring and obtaining equipment performance parameter data, the performance parameter data includes stable data of voltage and current, and stable data of output power; The safety priority impact coefficient is obtained based on the material strength coefficient combined with the equipment performance parameter data based on the preset equipment safety impact formula.

[0051] The specific calculation formula of the material strength coefficient is as follows:

[0052] The specific calculation formula of the safety priority impact coefficient is as follows:

[0053] In the formula, AC is the safety priority influence coefficient, is the voltage stability data, is the current stability data, For output power stability data, is the material strength coefficient, To test the force, is the force bearing area, is the compressive strength data, is the shear strength data, is the length of the device.

[0054] It should be noted that in the process of technical transformation of power grid projects, obtaining the material strength of the equipment is crucial to ensure the safe operation of the equipment and the entire power grid system. Through accurate material strength testing, the pressure resistance, deformation resistance and damage resistance of the equipment can be evaluated, so as to make more scientific decisions when selecting and replacing equipment. When the material strength coefficient becomes smaller and smaller, and the stable data of voltage and current, and the stable data of output power become larger and larger, the safety priority impact coefficient also becomes larger and larger, indicating that the safety of the equipment at this time is getting lower and lower. From a safety perspective, it is necessary to give priority to technical transformation. ‌

[0055] S, ,Using the hierarchical analysis method, the weight of each project priority ,impact data is determined, and a comprehensive project priority evaluation model is established ,based on neural network, and the project priority impact data is input ,into the model to generate the comprehensive priority evaluation coefficient. ,The specific steps are as follows: Establish a hierarchical model and input the priority impact data of the prioritized projects into the model; According to professional comments, the relative importance of each factor was compared and a judgment matrix was constructed based on the 1-9 scale. By calculating the eigenvectors and eigenroots of the judgment matrix, the weight of each item's priority impact data is obtained; Based on neural network technology, historical data is collected and trained in combination with the weights of each project's priority impact data. Through real-time feedback and adjustment, a comprehensive project priority assessment model is established; The equipment priority impact data, environmental priority impact data and safety priority impact data are input into the comprehensive project priority assessment model to generate a comprehensive priority evaluation coefficient for the project.

[0056] The specific calculation method of the comprehensive project priority evaluation model is as follows:

[0057] In the formula, is the comprehensive priority evaluation coefficient, is the environmental quality impact coefficient, Y is the equipment priority impact coefficient, AC is the safety priority impact coefficient, , , is the weight coefficient.

[0058] It should be noted that when the environmental quality impact coefficient becomes larger and larger, the equipment priority impact coefficient becomes higher and higher, and the safety priority impact coefficient becomes larger and larger, the comprehensive priority evaluation coefficient becomes larger and larger, indicating that the power grid technology improvement of the project should be given priority.

[0059] S,, according to the comprehensive priority evaluation coefficients of all projects that need technical transformation, the priority of the projects that need technical transformation is arranged in descending order, and combined with the investment data of the power grid technical transformation projects, the optimal project for power grid technical transformation is finally decided. The specific steps are as follows: Through discussions among professionals on power grid technology improvement projects that require technical improvement, and through calculation to obtain the comprehensive priority evaluation coefficients of the projects to be improved, these data are sorted from large to small in descending order, and a ranking table for priority transformation is obtained. According to the priority transformation ranking table, the project equipment with more serious conditions will be given priority for technical transformation. Since the investment amount for the transformation of power grid projects is limited, it is impossible to carry out technical transformation on all power grid projects. Therefore, according to the ranking table based on the comprehensive priority evaluation coefficient and combined with the investment data of the project, priority is given to technical transformation of the top-ranked power grid projects, and within the reasonable range of the investment data, the best decision is finally made on the project for technical transformation of the power grid, so as to avoid further deterioration of the problem, thereby reducing safety accidents and economic losses caused by serious equipment aging or excessive environmental impact.

[0060] Embodiment 2, Figure 2 The schematic diagram of the structure of the optimal decision-making system for power grid technical transformation projects based on benefit indicators of the present invention is given, including a priority impact data acquisition module, a model building module, and a data analysis module, and there are connections between the modules: The priority impact data acquisition module is used to obtain the priority impact data of projects that need to undergo power grid technical transformation, where the project priority impact data includes equipment priority impact data, environment priority impact data, and safety priority impact data, and quantify them into a unified evaluation standard; The model building module is used to determine the weight of each project priority impact data using the hierarchical analysis method, and to establish a comprehensive project priority evaluation model based on a neural network, and to input the project priority impact data into the model to generate a comprehensive priority evaluation coefficient; The data analysis module is used to arrange the priorities of the projects that need technical transformation in descending order according to the comprehensive priority evaluation coefficients of all the projects that need technical transformation, and finally decide on the best project for power grid technical transformation based on the investment data of power grid technical transformation projects.

[0061] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0062] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0063] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0064] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0065] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0066] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optimizing and deciding on power grid technical transformation projects based on benefit indicators, characterized in that: The steps include: Obtain priority impact data for projects that require power grid technical transformation, including equipment priority impact data, environmental priority impact data, and safety priority impact data, and quantify them into a unified evaluation standard; Using the analytic hierarchy process, the weights of the priority impact data of each project are determined, and a comprehensive project priority evaluation model is established based on a neural network. The project priority impact data are input into the model to generate a comprehensive priority evaluation coefficient; According to the comprehensive priority evaluation coefficients of all projects that need technical transformation, the priority of the projects that need technical transformation is arranged in descending order, and combined with the investment data of power grid technical transformation projects, the best project for power grid technical transformation is finally decided.

2. The method for optimizing and deciding power grid technical transformation projects based on benefit indicators according to claim 1 is characterized in that: The equipment priority impact data refers to the equipment priority impact coefficient, the environment priority impact data includes the environment quality impact coefficient, and the safety priority impact data includes the safety priority impact coefficient.

3. The method for optimizing and deciding power grid technical transformation projects based on benefit indicators according to claim 2 is characterized in that: The specific method for obtaining the device priority influence coefficient is as follows: Acquire first data of the equipment according to market research, wherein the first data includes maintenance cost, labor cost and equipment cost of the equipment; During the working time of the power equipment, the working efficiency data of the equipment is obtained by detecting the output data and loss data of the equipment; Collect the original value, depreciation rate and useful life of the equipment and calculate the remaining residual value of the equipment based on the preset residual value formula; The equipment priority influence coefficient is obtained based on a preset equipment priority influence formula according to the first data, work efficiency data and remaining residual value of the equipment.

4. The method for optimizing and deciding power grid technical transformation projects based on benefit indicators according to claim 2 is characterized in that: The specific method for obtaining the environmental quality impact coefficient is as follows: Based on the superposition principle, the electric field intensity component at any point in space is calculated according to the equivalent charge on the wire; The electromagnetic pollution coefficient is obtained based on the electromagnetic radiation pollution formula in power grid engineering according to the electric field component combined with the vertical and horizontal components of the power frequency magnetic field on the ground and at a certain distance from the ground; Determine the amount of electricity generated during the project work; The air carbon emission coefficient is obtained based on the preset carbon emission pollution formula according to the power generation and the project carbon emission factor detected by the monitoring equipment; Centered on the project to be tested, determine a certain range, measure the noise level during the working hours within the range, and collect the noise pollution coefficient; The environmental quality impact coefficient is obtained based on the preset environmental quality impact formula according to the electromagnetic pollution coefficient, the air carbon emission coefficient and the noise pollution coefficient.

5. The method for optimizing and deciding power grid technical transformation projects based on benefit indicators according to claim 2 is characterized in that: The specific method for obtaining the safety priority impact coefficient is as follows: Based on material strength testing, obtain material compressive strength data and shear strength data of project equipment; Obtain material strength coefficient based on material strength calculation formula according to compressive strength data and shear strength data; By real-time monitoring and obtaining equipment performance parameter data, the performance parameter data includes stable data of voltage and current, and stable data of output power; The safety priority impact coefficient is obtained based on the material strength coefficient combined with the equipment performance parameter data based on the preset equipment safety impact formula.

6. The method for optimizing and deciding power grid technical transformation projects based on benefit indicators according to claim 1 is characterized in that: The hierarchical analysis method is used to determine the weight of each project priority impact data, and a comprehensive project priority evaluation model is established based on a neural network. The project priority impact data is input into the model to generate a comprehensive priority evaluation coefficient. The specific steps are as follows: Establish a hierarchical model and input the priority impact data of the prioritized projects into the model; According to professional comments, the relative importance of each factor was compared and a judgment matrix was constructed based on the 1-9 scale. By calculating the eigenvectors and eigenroots of the judgment matrix, the weight of each item's priority impact data is obtained; Based on neural network technology, historical data is collected and trained in combination with the weights of each project's priority impact data. Through real-time feedback and adjustment, a comprehensive project priority assessment model is established; The equipment priority impact data, environmental priority impact data and safety priority impact data are input into the comprehensive project priority assessment model to generate a comprehensive priority evaluation coefficient for the project.

7. The method for optimizing and deciding power grid technical transformation projects based on benefit indicators according to claim 3 is characterized in that: The working efficiency data of the equipment is calculated by the following specific formula: The specific calculation formula for the residual value of the equipment is as follows: The specific calculation formula of the equipment priority influence coefficient is as follows: In the formula, Y is the equipment priority influence coefficient, For work efficiency data, is the residual value of the equipment, For maintenance costs, is labor cost, S is equipment cost, is the output data of the equipment, is the power of the device, is the machine power factor of the equipment, is the loss data, is the machine loss factor, H is the working time of the equipment, D is the output data of the equipment, dt is the depreciation rate that changes with time, and t is the service life.

8. The method for optimizing and deciding power grid technical transformation projects based on benefit indicators according to claim 4 is characterized in that: The specific calculation formula of the electromagnetic pollution coefficient is as follows: The specific calculation formula of the carbon emission coefficient is as follows: The specific calculation formula of the environmental quality impact coefficient is as follows: In the formula, is the environmental quality impact coefficient, E is the electromagnetic pollution coefficient, G is the carbon emission coefficient, is the noise pollution coefficient, For reference of reasonable noise coefficient, For electricity consumption, is the carbon emission factor, is the carbon emission time, is the carbon emission absorbed by the absorption device, m is the total number of wires, i is the i-th wire, i=1,2,3...,n, n is an integer, and are the horizontal and vertical coordinates of wire i, L is the distance from wire i and its mirror image to the calculation point, and is the unit matrix on each wire.

9. The method for optimizing and deciding power grid technical transformation projects based on benefit indicators according to claim 6 is characterized in that: The specific calculation method of the comprehensive project priority evaluation model is as follows: In the formula, is the comprehensive priority evaluation coefficient, is the environmental quality impact coefficient, Y is the equipment priority impact coefficient, AC is the safety priority impact coefficient, , , is the weight coefficient.

10. A system using the method for optimizing decision-making of power grid technical transformation projects based on benefit indicators as claimed in any one of claims 1 to 9, comprising a priority impact data acquisition module, a model building module, and a data analysis module, wherein the modules are connected: The priority impact data acquisition module is used to obtain the priority impact data of projects that need to undergo power grid technical transformation, where the project priority impact data includes equipment priority impact data, environment priority impact data, and safety priority impact data, and quantify them into a unified evaluation standard; The model building module is used to determine the weight of each project priority impact data using the hierarchical analysis method, and to establish a comprehensive project priority evaluation model based on a neural network, and to input the project priority impact data into the model to generate a comprehensive priority evaluation coefficient; The data analysis module is used to arrange the priorities of the projects that need technical transformation in descending order according to the comprehensive priority evaluation coefficients of all the projects that need technical transformation, and finally decide on the best project for power grid technical transformation based on the investment data of power grid technical transformation projects.

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