Power grid investment intelligent decision-making method, system, equipment and medium

Abstract

The invention provides a power grid investment intelligent decision-making method, system and device and a medium, and the method comprises the steps: generating a power grid resource efficiency distribution index through a resource distribution evaluation model based on the resource data of a power grid; based on the equipment operation data of the power grid, the operation feasibility analysis engine outputs a power grid reliability index; based on the electric energy data and the equipment operation data of the power grid, calculating an environmental influence index by using an environmental influence calculation unit; performing multi-dimensional index fusion calculation on the power grid resource efficiency distribution index, the power grid reliability index and the environmental influence index, and generating an investment strategy of a power grid investment project in combination with the power market data and the resource data of the power grid; executing the investment strategy of the power grid investment project, and driving the power grid to perform operation strategy adjustment. According to the method, comprehensive evaluation of the power grid investment project from all aspects is facilitated, the decision accuracy of the power grid investment project can be improved, and safe and reliable operation of the power grid is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid investment decision-making, and specifically relates to an intelligent decision-making method, system, device and medium for power grid investment. Background Art

[0002] In traditional power grid investment decision-making methods, it mainly relies on the knowledge and experience accumulated by professionals over a long time. They evaluate and make decisions on current power grid investment projects based on the results, experiences and lessons of previous similar projects. Moreover, when conducting evaluations and decisions, professionals mainly rely on a single static economic indicator for analysis, such as only considering static economic indicators like net present value and internal rate of return, lacking comprehensive consideration from dimensions such as the safety of power grid operation and environmental sustainability, and being unable to comprehensively reflect the comprehensive performance of investment projects in complex operating environments.

[0003] Therefore, relying on a single static indicator and human experience cannot comprehensively reflect the comprehensive performance of investment projects in complex operating environments, which will increase the risk of decision-making errors in investment projects and lead to an impact on the safe and reliable operation of the power grid. Summary of the Invention

[0004] In order to overcome the defects that in the above-mentioned traditional power grid investment decision-making method, a single static indicator and human experience cannot comprehensively reflect the comprehensive performance of investment projects in complex operating environments, which will increase the risk of decision-making errors in investment projects and lead to an impact on the safe and reliable operation of the power grid, the present invention provides an intelligent decision-making method for power grid investment, including: Based on the resource data of the power grid, using a resource allocation evaluation model to generate power grid resource efficiency allocation indicators; Based on the equipment operation data of the power grid, running a feasibility analysis engine to output power grid reliability indicators; Based on the electric energy data of the power grid and the equipment operation data, using an environmental impact calculation unit to calculate environmental impact indicators; Performing multi-dimensional index fusion calculation on the power grid resource efficiency allocation indicators, the power grid reliability indicators and the environmental impact indicators, and combining the power market data of the power grid and the resource data to generate an investment strategy for a power grid investment project; Executing the investment strategy of the power grid investment project to drive the power grid to adjust its operation strategy.

[0005] Optionally, the generating power grid resource efficiency allocation indicators based on the resource data of the power grid using a resource allocation evaluation model includes: Based on the initial resources and resource allocation situation in the resource data of the power grid, using the resource allocation risk sub-model in the resource allocation evaluation model to generate resource allocation feasibility data; the resource allocation feasibility data is used to represent the resource flow situation and allocation risk during resource allocation; Based on the initial resources, the average annual resource allocation in the resource data, and the resource allocation feasibility data, a grid resource efficiency allocation index is generated using the resource allocation efficiency sub-model in the resource allocation evaluation model; The resource allocation feasibility data satisfies the following formula: , where is the resource allocation feasibility data, is the resource allocation parameter, is the resource allocation situation in the i-th year, where the value of i is in the range of [1, n], and n is the total number of years, is the initial resource; The grid resource efficiency allocation index satisfies the following formula: , where is the grid resource efficiency allocation index, is the average annual resource allocation situation.

[0006] Optionally, based on the equipment operation data of the power grid, the operation feasibility analysis engine outputs grid reliability indicators including: Based on the total power supply time, planned power outage time, and fault power outage time in the equipment operation data, the operation feasibility analysis engine executes a power supply reliability algorithm to output the power supply reliability rate; Based on the total operation time of the equipment in the equipment operation data, the feasibility analysis engine is run to output the mean time between failures; The feasibility analysis engine is run to perform a weighted sum of the power supply reliability rate and the mean time between failures to obtain a grid reliability indicator; The power supply reliability rate satisfies the following formula: , where is the power supply reliability rate, is the total power supply time, is the planned power outage time, is the fault power outage time; The mean time between failures satisfies the following formula: , where is the mean time between failures, is the total operation time of the equipment, is a constant, is the total maintenance time.

[0007] Optionally, based on the electrical energy data and the equipment operation data of the power grid, the environmental impact calculation unit calculates environmental impact indicators including: Based on the total power supply of the power grid, the total operation time of the device, and the rated power of the device in the device operation data, calculate the energy consumption intensity using the energy consumption algorithm in the environmental impact calculation unit; Based on the renewable energy power generation and the total power generation of the power grid in the power data of the power grid, calculate the renewable energy utilization rate using the renewable energy algorithm in the environmental impact calculation unit; Perform a weighted sum of the energy consumption intensity and the renewable energy utilization rate to obtain an environmental impact index; The energy consumption intensity satisfies the following formula: , where is the energy consumption intensity, is the total energy consumed during the operation of the power grid, is the rated power of the device, is the total operation time of the device, is the total power supply of the power grid, is the energy conversion efficiency of the device; The renewable energy utilization rate satisfies the following formula: , where is the renewable energy utilization rate, is the renewable energy power generation, is the proportion of the maintenance time of the renewable energy power generation equipment, is the stability coefficient, is the total power generation of the power grid.

[0008] Optionally, perform a multi-dimensional index fusion calculation on the power grid resource efficiency allocation index, the power grid reliability index, and the environmental impact index, and combine the power market data of the power grid and the resource data to generate an investment strategy for a power grid investment project, including: Perform a multi-dimensional index fusion calculation on the power grid resource efficiency allocation index, the power grid reliability index, and the environmental impact index to obtain a feasibility evaluation index for a power grid investment project; When the feasibility evaluation index indicates that the power grid investment project has investment feasibility, trigger the strategy generation module, and based on the feasibility evaluation index, combine the power market data of the power grid and the resource data to generate an investment strategy for the power grid investment project.

[0009] Optionally, the strategy generation module, based on the feasibility evaluation index, combines the power market data of the power grid and the resource data to generate an investment strategy for a power grid investment project, including: The strategy generation module calculates the expected return based on the feasibility evaluation index, the market average growth rate in the power market data of the power grid, the total project resources and the project cycle in the resource data; Calculate a risk balance coefficient using a risk balance algorithm based on the feasibility evaluation indicators and the expected return; Calculate a comprehensive return based on the expected return and the risk balance coefficient; calculate a comprehensive evaluation indicator based on the comprehensive return; If the comprehensive evaluation indicator is less than a preset comprehensive evaluation indicator threshold, determine that the investment strategy for the power grid investment project includes not being able to invest; otherwise, determine that the investment strategy for the power grid investment project includes being able to invest.

[0010] The expected return satisfies the following formula: , where is the expected return, is the feasibility evaluation indicator, is the total project resources, is the project cycle, is the market average growth rate; The risk balance coefficient satisfies the following formula: , where is the risk balance coefficient, is the expected return, is the feasibility evaluation indicator; The comprehensive return satisfies the following formula: , where is the comprehensive return, is the expected return, is the risk balance coefficient, is the risk aversion coefficient; The comprehensive evaluation indicator satisfies the following formula: , where is the comprehensive evaluation indicator, is the comprehensive return, is the return standard deviation, is the average rate of return, is the return volatility coefficient.

[0011] Optionally, after calculating the feasibility evaluation indicator of the power grid investment project by performing multi-dimensional index fusion calculation on the power grid resource efficiency allocation indicator, the power grid reliability indicator, and the environmental impact indicator, it further includes: Compare the feasibility evaluation indicator with a preset evaluation indicator threshold; If the feasibility evaluation indicator is less than or equal to the evaluation indicator threshold, determine that the power grid investment project does not have investment feasibility and send an alarm signal; If the feasibility evaluation index is greater than the evaluation index threshold, it is determined that the power grid investment project has investment feasibility.

[0012] On the other hand, this method also provides a power grid investment intelligent decision-making system, which is characterized by including a data acquisition device and a server connected by communication; a resource allocation evaluation model, a feasibility analysis engine, and an environmental impact calculation unit are deployed on the server; The data acquisition device is used to collect resource data, equipment operation data, power data, and power market data of the power grid; The server is used to generate a power grid resource efficiency allocation index by using the resource allocation evaluation model based on the resource data of the power grid; run the feasibility analysis engine based on the equipment operation data of the power grid to output the power grid reliability index; calculate the environmental impact index by using the environmental impact calculation unit based on the power data of the power grid and the equipment operation data; perform multi-dimensional index fusion calculation on the power grid resource efficiency allocation index, the power grid reliability index, and the environmental impact index, and combine the power market data and the resource data of the power grid to generate an investment strategy for the power grid investment project; execute the investment strategy of the power grid investment project to drive the power grid to adjust the operation strategy.

[0013] On the other hand, this method also provides a power grid investment intelligent decision-making system, including: An efficiency allocation index determination module, which is used to generate a power grid resource efficiency allocation index by using the resource allocation evaluation model based on the resource data of the power grid; A power grid reliability index determination module, which is used to run the feasibility analysis engine based on the equipment operation data of the power grid to output the power grid reliability index; An environmental impact index determination module, which is used to calculate the environmental impact index by using the environmental impact calculation unit based on the power data of the power grid and the equipment operation data; An investment decision module, which is used to perform multi-dimensional index fusion calculation on the power grid resource efficiency allocation index, the power grid reliability index, and the environmental impact index, and combine the power market data and the resource data of the power grid to generate an investment strategy for the power grid investment project; An operation strategy adjustment module, which is used to execute the investment strategy of the power grid investment project to drive the power grid to adjust the operation strategy.

[0014] Optionally, the efficiency allocation index determination module includes: A resource allocation credibility calculation unit, which is used to generate resource allocation feasibility data by using the resource allocation risk sub-model in the resource allocation evaluation model based on the initial resources and resource allocation situation in the resource data of the power grid; the resource allocation feasibility data is used to represent the resource flow situation and allocation risk during resource allocation; A resource efficiency allocation calculation unit, configured to generate a power grid resource efficiency allocation index by using a resource allocation efficiency sub-model in a resource allocation evaluation model based on the initial resources, the average annual resource allocation in the resource data, and the resource allocation feasibility data; The resource allocation feasibility data satisfies the following formula: , where is the resource allocation feasibility data, is the resource allocation parameter, is the resource allocation in the i-th year, and the value range of i is [1, n], where n is the total number of years, is the initial resource; The power grid resource efficiency allocation index satisfies the following formula: , where is the power grid resource efficiency allocation index, is the average annual resource allocation.

[0015] Optionally, the power grid reliability index determination module includes: A power supply reliability rate calculation unit, configured to execute a power supply reliability algorithm by running a feasibility analysis engine based on the total power supply time, planned power outage time, and fault power outage time in the device operation data to output the power supply reliability rate; A fault-free time calculation unit, configured to output the average fault-free time by running the feasibility analysis engine based on the total device operation time in the device operation data; A reliability index calculation unit, configured to run the feasibility analysis engine to perform weighted summation on the power supply reliability rate and the average fault-free time to obtain a power grid reliability index; The power supply reliability rate satisfies the following formula: , where is the power supply reliability rate, is the total power supply time, is the planned power outage time, is the fault power outage time; The average fault-free time satisfies the following formula: , where is the average fault-free time, is the total device operation time, is a constant, is the total maintenance time.

[0016] Optionally, the environmental impact index determination module includes: An energy consumption calculation unit for calculating the energy consumption intensity based on the total power supply of the power grid, the total operating time of the equipment, and the rated power of the equipment in the equipment operation data, using the energy consumption algorithm in the environmental impact calculation unit; A renewable energy utilization rate calculation unit for calculating the renewable energy utilization rate based on the renewable energy power generation and the total power generation of the power grid in the power grid power data, using the renewable energy algorithm in the environmental impact calculation unit; An impact index calculation unit for performing weighted summation on the energy consumption intensity and the renewable energy utilization rate to obtain an environmental impact index; The energy consumption intensity satisfies the following formula: , where is the energy consumption intensity, is the total energy consumed during the operation of the power grid, is the rated power of the equipment, is the total operating time of the equipment, is the total power supply of the power grid, is the equipment energy conversion efficiency; The renewable energy utilization rate satisfies the following formula: , where is the renewable energy utilization rate, is the renewable energy power generation, is the proportion of the maintenance time of the renewable energy power generation equipment, is the stability coefficient, is the total power generation of the power grid.

[0017] Optionally, the investment decision module includes: A feasibility evaluation calculation unit for performing multi-dimensional index fusion calculation on the power grid resource efficiency allocation index, the power grid reliability index, and the environmental impact index to obtain a feasibility evaluation index for the power grid investment project; An investment strategy generation unit for triggering the strategy generation module when the feasibility evaluation index indicates that the power grid investment project has investment feasibility, and generating an investment strategy for the power grid investment project based on the feasibility evaluation index, combined with the power market data and the resource data of the power grid; Optionally, the investment strategy generation unit is specifically configured to trigger the strategy generation module to calculate the expected return based on the feasibility evaluation index, the market average growth rate in the power market data of the power grid, the total project resources and the project cycle in the resource data; calculate the risk balance coefficient by using the risk balance algorithm based on the feasibility evaluation index and the expected return; calculate the comprehensive return based on the expected return and the risk balance coefficient; calculate the comprehensive evaluation index based on the comprehensive return; if the comprehensive evaluation index is less than the preset comprehensive evaluation index threshold, determine that the investment strategy of the power grid investment project includes that investment cannot be made; otherwise, determine that the investment strategy of the power grid investment project includes that investment can be made.

[0018] The expected return satisfies the following formula: , where is the expected return, is the feasibility evaluation index, is the total project resources, is the project cycle, is the market average growth rate; The risk balance coefficient satisfies the following formula: , where is the risk balance coefficient, is the expected return, is the feasibility evaluation index; The comprehensive return satisfies the following formula: , where is the comprehensive return, is the expected return, is the risk balance coefficient, is the risk aversion coefficient; The comprehensive evaluation index satisfies the following formula: , where is the comprehensive evaluation index, is the comprehensive return, is the return standard deviation, is the average rate of return, is the return volatility coefficient.

[0019] Optionally, it further includes: The risk status determination module is configured to compare the feasibility evaluation index with the preset evaluation index threshold; if the feasibility evaluation index is less than or equal to the evaluation index threshold, determine that the power grid investment project does not have investment feasibility and send an alarm signal; if the feasibility evaluation index is greater than the evaluation index threshold, determine that the power grid investment project has investment feasibility.

[0020] On the other hand, the present invention further provides an electronic device, including: at least one processor and a memory; the memory and the processor are connected by a bus; the memory is used for storing one or more programs; when the one or more programs are executed by the at least one processor, the above-mentioned intelligent decision-making method for power grid investment is implemented.

[0021] On the other hand, the present invention further provides a readable storage medium, on which an execution program is stored, and when the execution program is executed, the above-mentioned intelligent decision-making method for power grid investment is implemented.

[0022] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention provides an intelligent decision-making method for power grid investment, including: based on the resource data of the power grid, using a resource allocation evaluation model to generate power grid resource efficiency allocation indicators; based on the equipment operation data of the power grid, running a feasibility analysis engine to output power grid reliability indicators; based on the power energy data and equipment operation data of the power grid, using an environmental impact calculation unit to calculate environmental impact indicators; performing multi-dimensional index fusion calculation on the power grid resource efficiency allocation indicators, power grid reliability indicators and environmental impact indicators, and combining the power market data and resource data of the power grid to generate an investment strategy for power grid investment projects; implementing the investment strategy of the power grid investment project to drive the power grid to adjust the operation strategy. In this method, through the resource data, equipment operation data, power energy data and power market data of the power grid, different types of data reflect the operation status and market environment of the power grid from multiple dimensions, and intelligent decision-making is carried out in combination with a resource allocation evaluation model, a feasibility analysis engine and an environmental impact calculation unit, which helps to comprehensively evaluate power grid investment projects from all aspects, can improve the decision-making accuracy of power grid investment projects, and ensure the safe and reliable operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a schematic flow chart of the intelligent decision-making method for power grid investment of the present invention; Figure 2 is a schematic diagram of the working steps of the intelligent decision-making method for power grid investment of the present invention; Figure 3 is a schematic structural diagram of the intelligent decision-making system for power grid investment of the present invention; Figure 4 is a schematic structural diagram of the electronic device of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] The following further describes in detail the specific embodiments of the present invention with reference to the accompanying drawings.

[0025] Embodiment 1: An intelligent decision-making method for power grid investment provided by the present invention, the schematic flow chart is asFigure 1 As shown in Step 101: Based on the resource data of the power grid, use the resource allocation evaluation model to generate power grid resource efficiency allocation indicators; Step 102: Based on the equipment operation data of the power grid, run the feasibility analysis engine to output power grid reliability indicators; Step 103: Based on the power energy data and equipment operation data of the power grid, use the environmental impact calculation unit to calculate environmental impact indicators; Step 104: Perform multi-dimensional index fusion calculation on the power grid resource efficiency allocation indicators, power grid reliability indicators and environmental impact indicators, and combine the power market data and resource data of the power grid to generate an investment strategy for power grid investment projects; Step 105: Execute the investment strategy of the power grid investment project to drive the power grid to adjust its operation strategy.

[0026] In the embodiment of the present invention, through the resource data, equipment operation data, power energy data and power market data of the power grid, different types of data reflect the operation status and market environment of the power grid from multiple dimensions, and intelligent decision-making is carried out in combination with the resource allocation evaluation model, feasibility analysis engine and environmental impact calculation unit, which helps to comprehensively evaluate power grid investment projects from all aspects, can improve the decision-making accuracy of power grid investment projects, and ensure the safe and reliable operation of the power grid. Here, comprehensive analysis and dynamic evaluation are carried out based on real-time collected data, which can improve the intelligent evaluation ability and risk control level of power grid investment projects, so as to ensure the safe and reliable operation of the power grid.

[0027] In the embodiment of the present invention, the resource data, equipment operation data, power energy data and power market data of the power grid can be collected, and all aspects of information on the operation of the power grid can be comprehensively grasped. It can provide a rich data basis for subsequent accurate analysis and decision-making. Different types of data reflect the operation status and market environment of the power grid from multiple dimensions, which helps to comprehensively evaluate all aspects of power grid investment projects, ensures that the evaluation of power grid investment projects has sufficient data support, and avoids one-sided decision-making caused by data missing.

[0028] The resource data includes but is not limited to power equipment data, regional load data and economic data in the power grid. The power equipment data can include the number of power equipment and power equipment topology parameters, etc., reflecting the equipment resources in the power grid investment project. The regional load data can reflect the load characteristics of the power grid, reflecting the available load resources in the power grid investment project. The economic data includes but is not limited to existing cash flow and investment value, reflecting the economic resources in the power grid investment project.

[0029] In some scenarios, the resource data includes economic data. In this scenario, through the economic data, equipment operation data, power energy data, and power market data of the power grid, combined with intelligent decision-making algorithms, different types of data reflect the operation status and market environment of the power grid from multiple dimensions, which helps to comprehensively evaluate power grid investment projects from all aspects.

[0030] In a possible implementation, the resource allocation evaluation model includes a resource allocation risk sub-model and a resource allocation efficiency sub-model. The resource data includes initial resources, resource allocation situations, and average annual resource allocation situations. For example, in step 101 above, based on the initial resources and resource allocation situations in the resource data of the power grid, the resource allocation risk sub-model in the resource allocation evaluation model is used to generate resource allocation feasibility data; the resource allocation feasibility data is used to represent the resource flow situation and allocation risk during resource allocation; based on the initial resources, the average annual resource allocation situation in the resource data, and the resource allocation feasibility data, the resource allocation efficiency sub-model in the resource allocation evaluation model is used to generate power grid resource efficiency allocation indicators. The resource data can be obtained from channels such as project files and operation reports.

[0031] The resource allocation feasibility data satisfies the following formula: , where is the resource allocation feasibility data, is the resource allocation parameter, is the resource allocation situation in the i-th year, and the value range of i is [1, n], where n is the total number of years, is the initial resource; The power grid resource efficiency allocation indicator satisfies the following formula: , where is the power grid resource efficiency allocation indicator, is the average annual resource allocation situation.

[0032] In this implementation, still taking the above scenario as an example, if the resource data includes economic data, then the resource allocation feasibility data can be the net present value , and the power grid resource efficiency allocation indicator can be the economic benefit indicator , that is, in step 101 above, the net present value can be calculated according to the economic data , and based on the net present value and the economic data, the economic benefit indicator is calculated.

[0033] In this scenario, the economic data includes the initial investment value (an example of initial resources), the cash flow (an example of the resource allocation situation), and the average annual cash flow (An example of the average annual resource allocation). For example, the initial investment value can be obtained from the grid investment project budget document. . By examining the annual electricity revenue statement and operating cost statement, calculate the difference between cash inflows and outflows to obtain the cash flow. . By adding up the cash flows over the past few years and then dividing by the number of years, the average annual cash flow is obtained. .

[0034] When calculating the net present value based on the economic data as described above , the initial investment value and the cash flow in the economic data of the power grid can be used to calculate the net present value using the resource allocation risk sub-model. . The net present value can satisfy the following formula: , where is the net present value, is the discount rate (an example of a resource allocation parameter), is the cash flow in the i-th year, where i ranges from [1, n], and n is the total number of investment years (an example of the total number of years) and takes positive integer values, is the initial investment value. It can be understood that this formula is an example of the resource allocation risk sub-model. In this formula, in the formula means discounting all the cash flows of the investment project from the 1st year to the nth year to the time point of the initial investment, and finally subtracting the initial investment value to obtain the net present value , which can reflect that the net present value measures the net income of the project after considering the initial investment cost.

[0035] Discount rate : The discount rate can be calculated by obtaining the national debt interest rate and the market average return rate , and the calculation formula is: , where , and is the project risk coefficient.

[0036] When calculating the economic benefit index based on the net present value and the economic data as described above, the initial investment value , the average annual cash flow in the economic data, and the net present value can be used to calculate the economic benefit index using the resource allocation efficiency sub-model. . The economic benefit index It can satisfy the following formula: , where is the economic benefit index, is the average annual cash flow. It can be understood that this formula is the resource allocation efficiency sub-model. In this formula, reflects the proportional relationship between the average annual cash flow that the project can generate and the initial investment. The higher this ratio, the more cash returns the project can generate relative to the initial investment during the operation process. represents the sum of the discount factors for all years, indicating that the time value of the cash flow throughout the project cycle is considered. is a kind of standardization process for the net present value, enabling comprehensive calculation on the same magnitude as the ratio of the numerator part. This index comprehensively considers the average annual cash flow, initial investment, net present value of the project, and the time value of funds. It can comprehensively evaluate the economic benefits of the project.

[0037] In the scenario of this implementation method, by calculating the economic benefit index, the economic performance of the power grid investment project can be quantified. This helps to intuitively understand the profitability and economic feasibility of the project, facilitating the comparison and screening of the economic benefits of different investment projects; calculating the power grid reliability index can accurately reflect the operation stability of the power grid. It is of great significance for ensuring the continuity and stability of power supply and helps to reduce economic losses caused by power grid failures; calculating the environmental impact index can quantify the impact of the power grid investment project on the environment.

[0038] In a possible implementation method, in the above step 102, the power supply reliability rate and the mean time between failures can be calculated respectively according to the device operation data. According to the power supply reliability rate and the mean time between failures , the power grid reliability index is calculated.

[0039] In this implementation method, the device operation data includes the total power supply time , the planned power outage time , the fault power outage time , and the total operation time of the device . Since the power monitoring system can record the power supply situation of the power grid in real time, the total power supply time is obtained by summarizing the data of the monitoring system. Since the power grid dispatching system records the planned power outage operations, the planned power outage time is obtained by querying and summarizing the planned power outage time in the dispatching system.When the power grid fails and power is cut off, the fault recording system will record information such as the time of the fault; by statistically analyzing these fault recording data, the fault power outage time can be calculated. Since the equipment operation log records information such as the start time, stop time, and operation status of the equipment, by analyzing the equipment operation log, the total operation time of the equipment can be calculated. 。

[0040] The above calculation of the power supply reliability rate based on equipment operation data can be based on the total power supply time in the equipment operation data , planned power outage time and fault power outage time . The operation feasibility analysis engine executes the power supply reliability algorithm to output the power supply reliability rate. The power supply reliability rate can satisfy the following formula: , where is the power supply reliability rate, is the total power supply time, is the planned power outage time, is the fault power outage time. It can be understood that this formula is the power supply reliability algorithm. In this formula, obtains the proportion of the effective power supply time in the total power supply time, and finally multiplies by and then adds 1, and the obtained value is the power supply reliability rate . The closer this value is to , the higher the power supply reliability of the power grid, that is, within the total power supply time, the proportion of the power outage time is smaller.

[0041] The above calculation of the mean time between failures based on equipment operation data can be based on the total operation time of the equipment in the equipment operation data . The operation feasibility analysis engine outputs the mean time between failures . The mean time between failures can satisfy the following formula: , where is the mean time between failures, is the total operation time of the equipment, is a constant, is the total repair time. In this formula, this part represents considering the impact of repair time on equipment operation. Adding 1 means quantifying and incorporating the impact of repair time into the calculation. After adding the constant S, the denominator comprehensively considers the impact of the equipment's own characteristics and repair time on equipment operation, and then divides the total operation time of the equipment by this denominator to obtain the mean time between failures .

[0042] Total maintenance time : The start time and end time of each maintenance are automatically recorded by the electronic maintenance management system. The system automatically calculates the time of each maintenance and accumulates it automatically to obtain the total maintenance time .

[0043] Based on the power supply reliability and the mean time between failures , when calculating the power grid reliability index , the feasibility analysis engine can be run to perform a weighted sum of the power supply reliability and the mean time between failures to obtain the power grid reliability index . The power grid reliability index can satisfy the following formula: , where is the weight coefficient of the power supply reliability , and its value can be 0.5 - 0.7; is the weight coefficient of the mean time between failures , and its value can be 0.3 - 0.5; and a + b = 1. In this weighted sum formula, both the power supply reliability and the mean time between failures are comprehensively considered. Each parameter has a corresponding weight coefficient, indicating the degree of importance attached to different parameters when calculating the power grid reliability index . By multiplying each parameter by its corresponding weight coefficient and then summing, a power grid reliability index that can comprehensively describe the power grid is obtained .

[0044] In addition to the above formula, in this implementation, the reliability analysis engine can also use the Monte Carlo simulation algorithm to perform N - 1 fault simulation on the operation of power grid equipment and output the system risk quantification index as the power grid reliability index

[0045] In a possible implementation, the environmental impact calculation unit integrates an energy consumption algorithm and a renewable energy algorithm. For example, in step 103 above, the energy consumption intensity is calculated based on the equipment operation data , the renewable energy utilization rate is calculated based on the electrical energy data , and the environmental impact index is calculated according to the energy consumption intensity and the renewable energy utilization rate .

[0046] In this implementation, the equipment operation data also includes the total power supply of the power grid and the rated power of the equipment Since the power metering system of the power grid company is used to record the power output data of each substation, transmission line and distribution line; through these metering systems, all power output data are summarized to obtain the total power supply of the power grid Obtain the rated power of the equipment by referring to the technical manual of the equipment Power data includes the power generation of renewable energy and the total power generation of the power grid By installing a high-precision electricity meter at the output end of the renewable energy power generation equipment, the electricity meter records the electricity data generated by the power generation equipment in real time, and the power generation of renewable energy can be obtained Install electricity meters at the connection points between the power grid and each power plant. These electricity meters record the electricity flowing from the power plant into the power grid in real time, and summarize these electricity to obtain the total power generation of the power grid 。

[0047] The above-mentioned calculation of the energy consumption intensity based on the equipment operation data and the calculation of the renewable energy utilization rate based on the power data When calculating, the total power supply of the power grid, the total operation time of the equipment and the rated power of the equipment in the equipment operation data can be used. The energy consumption algorithm in the environmental impact calculation unit is used to calculate the energy consumption intensity The energy consumption intensity can satisfy the following formula: where is the energy consumption intensity, is the total energy consumed during the operation of the power grid, is the rated power of the equipment, is the total operation time of the equipment, is the total power supply of the power grid, is the energy conversion efficiency of the equipment. It can be understood that this formula is the energy consumption algorithm. In this formula, represents the total energy consumption of the power grid; represents the actually effective output energy of the power grid. The whole formula calculates the ratio of the total energy consumption during the operation of the power grid to the actually effective output electric energy to obtain the energy consumption intensity. The larger this value is, the more energy the power grid consumes during operation, and the lower the energy utilization efficiency is

[0048] The total energy consumed during the operation of the power grid : By installing energy metering devices such as electricity meters, gas meters, and oil meters at each energy consumption link of the power grid, directly measure the energy consumption of each link, and then summarize to obtain the total energy consumed during the operation of the power grid For example, for electric energy, it is usually measured in kilowatt-hours and converted to joules. For natural gas energy, it is usually measured in cubic meters, and the calorific value of natural gas is which is converted to joules and is For fuel oil energy, it is usually measured in liters, and its calorific value is which is converted to joules and is Finally, different types of energy are uniformly converted to heat values in joules and then summed up as the total energy consumed during the operation of the power grid. 。

[0049] Equipment energy conversion efficiency : Since the equipment nameplate will indicate the energy conversion efficiency parameters of the equipment, the equipment energy conversion efficiency can be directly obtained. 。

[0050] When calculating the renewable energy utilization rate based on the electric energy data as described above it is possible to calculate the renewable energy utilization rate using the renewable energy algorithm in the environmental impact calculation unit based on the renewable energy power generation in the electric energy data of the power grid and the total power generation of the power grid. The renewable energy utilization rate can satisfy the following formula: where is the renewable energy utilization rate, is the renewable energy power generation, is the proportion of the maintenance time of the renewable energy power generation equipment, is the stability coefficient, is the total power generation of the power grid. It can be understood that this formula is the renewable energy algorithm. In this formula, represents the effective power generation that the renewable energy can actually provide after considering the equipment maintenance time, and then multiplied by is to further consider the instability of the renewable energy power generation and deduct the part of the power that cannot be effectively utilized due to instability. The total power generation of the power grid is used as the denominator to compare the actual effective power generation of the renewable energy with the overall power generation situation of the power grid to obtain the proportion of the renewable energy in the total power generation of the power grid, that is, the renewable energy utilization rate 。

[0051] Proportion of the maintenance time of the renewable energy power generation equipment : By recording the start time and end time of each maintenance of the device, calculating the duration of each maintenance, then counting the total maintenance duration, and dividing the total maintenance duration by the total operating duration of the device, the proportion of the maintenance time of the renewable energy power generation device can be obtained. .

[0052] Stability coefficient : By obtaining the performance parameters of the device and environmental data such as wind speed, wind direction, and light intensity of the environment where the device is located, and based on the device performance, environmental data, and historical power generation data, a mathematical model is established to predict the power generation of the device under different environmental conditions. For each time point, such as every hour or every day, the environmental data at that time point is input into the model to obtain the simulated power generation at that time point. The actual power generation of the device during the corresponding time period is obtained through an electric meter installed at the output end of the device. Calculate the average value of the simulated power generation and the actual power generation at each time point, and then take the square root of the average value to obtain the root mean square error. Subtract the ratio of the root mean square error to the average value of the actual power generation from 1 to obtain the stability coefficient. .

[0053] The above-mentioned calculation of the environmental impact index and the renewable energy utilization rate can be achieved by performing a weighted sum of the energy consumption intensity and the renewable energy utilization rate to obtain the environmental impact index . The environmental impact index can satisfy the following formula: , where , and is the weight coefficient of the energy consumption intensity , and its value can be 0.4 - 0.6; is the weight coefficient of the renewable energy utilization rate , and its value can be 0.5 - 0.6; and c + d = 1; this weighted sum formula comprehensively considers the energy consumption intensity and the renewable energy utilization rate these two important parameters. Each parameter has a corresponding weight coefficient, indicating the degree of importance attached to different parameters when calculating the environmental impact index . By multiplying each parameter by its corresponding weight coefficient and then summing, the environmental impact index is obtained.

[0054] In addition to the above formula, in this implementation method, a carbon footprint tracking algorithm can also be used by the environmental impact calculation unit to generate an emission reduction benefit matrix, and this emission reduction benefit matrix represents the environmental impact index.

[0055] In the above steps 101 to 103, by calculating the economic benefit indicators, the economic performance of the power grid investment project can be quantified. This helps to intuitively understand the profitability and economic feasibility of the project, providing a key economic basis for investment decisions; by calculating the power grid reliability indicators, the operating stability of the power grid can be accurately evaluated. It is of great significance for ensuring power supply and reducing power outage accidents, and also reflects the quality and operation and maintenance level of the power grid infrastructure; by calculating the environmental impact indicators, the impact of the power grid project on the environment can be comprehensively evaluated. This helps to promote the power grid to develop in a green and sustainable direction, meet environmental protection requirements, and reduce environmental costs in the long-term operation.

[0056] In the above step 104, the power grid resource efficiency allocation indicator, the power grid reliability indicator and the environmental impact indicator can be calculated through multi-dimensional index fusion to obtain the feasibility evaluation indicator of the power grid investment project; when the feasibility evaluation indicator indicates that the power grid investment project has investment feasibility, the strategy generation module is triggered, and based on the feasibility evaluation indicator, combined with the power market data and resource data of the power grid, an investment strategy for the power grid investment project is generated.

[0057] When calculating the feasibility evaluation indicator of the power grid investment project through multi-dimensional index fusion of the power grid resource efficiency allocation indicator, the power grid reliability indicator and the environmental impact indicator, the power grid resource efficiency allocation indicator and the power grid reliability indicator and the environmental impact indicator can be weighted and summed to calculate the feasibility evaluation indicator of the power grid investment project . The feasibility evaluation indicator can satisfy the following formula: , where is the weight coefficient of the power grid resource efficiency allocation indicator (for example, the economic benefit indicator ), and its value can be 0.2 to 0.4; is the weight coefficient of the power grid reliability indicator , and its value can be 0.3 to 0.5; is the weight coefficient of the environmental impact indicator , and its value can be 0.1 to 0.5; and . This weighted summation formula comprehensively considers the three important parameters of the power grid resource efficiency allocation indicator , the power grid reliability indicator and the environmental impact indicator . Each parameter has a corresponding weight coefficient, indicating the degree of importance attached to different parameters when calculating the feasibility evaluation indicator . By multiplying each parameter by its corresponding weight coefficient and then summing, the feasibility evaluation indicator is obtained.

[0058] In addition to the weighted summation algorithm, a multi-objective optimization decision model can be established here. Taking the power supply capacity requirement, system risk threshold, and emission reduction constraint conditions as boundary parameters, a genetic algorithm is used to perform multi-dimensional index fusion calculations on the grid resource efficiency allocation index, grid reliability index, and environmental impact index to obtain a feasibility evaluation index.

[0059] In a possible implementation manner, an evaluation index threshold can also be preset in the embodiments of the present application. After obtaining the feasibility evaluation index of the grid investment project, the feasibility evaluation index can also be compared with the preset evaluation index threshold; if the feasibility evaluation index is less than or equal to the evaluation index threshold, it is determined that the grid investment project does not have investment feasibility and is a risk project, and an alarm signal is sent; if the feasibility evaluation index is greater than the evaluation index threshold, it is determined that the grid investment project has investment feasibility and is a healthy project. By comparing the feasibility evaluation index with the evaluation index threshold , it is judged whether the grid investment project is a risk project or a healthy project according to the result; when the grid investment project is a risk project, an alarm signal is sent.

[0060] In this implementation manner, the specific steps for judging whether the grid investment project is a risk project or a healthy project are as follows: Preset the evaluation index threshold ; by collecting historical data of a large number of grid investment projects, obtaining the net present value data of different projects, and screening projects with a net present value greater than 0, calculate the evaluation index of each project through the above steps; calculate the average value of the evaluation indexes of these projects as the evaluation index threshold .

[0061] When , it is judged that the grid investment project is a risk project and an alarm signal is sent.

[0062] When , it is judged that the grid investment project is a healthy project. In this implementation manner, the risk status of the grid investment project is judged by calculating the evaluation index and comparing it with the preset threshold, realizing the comprehensive risk assessment of the grid investment project, being able to detect potential risks in a timely manner, and sending an alarm signal when the project is in a risk state, and corresponding measures can be taken quickly for risk prevention or adjustment of the investment strategy. Timely detecting projects in a risk state and sending an alarm signal helps to take risk response measures in advance to avoid or reduce potential investment losses.

[0063] In step 105 above, when the grid investment project is a healthy project with investment feasibility, the strategy generation module can be triggered to calculate the expected return based on the feasibility evaluation indicators, the market average growth rate in the power market data of the grid, the total project resources in the resource data, and the project cycle; calculate the risk balance coefficient using the risk balance algorithm based on the feasibility evaluation indicators and the expected return; calculate the comprehensive evaluation indicator based on the expected return and the risk balance coefficient; if the comprehensive evaluation indicator is less than the preset comprehensive evaluation indicator threshold, it is determined that the investment strategy of the grid investment project includes that investment cannot be made; otherwise, it is determined that the investment strategy of the grid investment project includes that investment can be made.

[0064] In this implementation, the power market data includes the market average growth rate . For every two adjacent years, the power market index value in the m-th year and the power market index value in the (m + 1)-th year are respectively obtained; then the market average growth rate for that year is calculated, and the calculation formula is: . The average value of the growth rates calculated for all adjacent years is obtained as the power market average growth rate . The resource data also includes the total project resources and the project cycle . According to the feasibility study report of the project, the total project resources are obtained. The project plan document is obtained from the project management department, and the start time and the expected end time of the project are found, and the time difference between the two is the project cycle .

[0065] The expected return satisfies the following formula: , where is the expected return, is the feasibility evaluation indicator, is the total project resources, is the project cycle, is the market average growth rate; The risk balance coefficient satisfies the following formula: , where is the risk balance coefficient, is the expected return, is the feasibility evaluation indicator.

[0066] When calculating the comprehensive evaluation indicator based on the expected return and the risk balance coefficient above, the comprehensive return can be calculated based on the expected return and the risk balance coefficient; the comprehensive evaluation indicator is calculated based on the comprehensive return.

[0067] The comprehensive return satisfies the following formula: , where is the comprehensive return, is the expected return, is the risk balance coefficient, is the risk aversion coefficient; The comprehensive evaluation index satisfies the following formula: , where is the comprehensive evaluation index, is the comprehensive return, is the return standard deviation, is the average rate of return, is the return volatility coefficient.

[0068] Taking the scenario where the resource data includes economic data as an example, in this process, the expected benefit value EF (an example of the expected return) can be calculated based on the electricity market data, economic data, and the evaluation index MKS; based on the evaluation index MKS and the expected benefit value EF, the risk balance coefficient ERBC can be further calculated; based on the expected benefit value EF and the risk balance coefficient ERBC, the comprehensive evaluation index CDI is calculated, a threshold value of the comprehensive evaluation index is preset, the comprehensive evaluation index CDI is compared with the threshold value of the comprehensive evaluation index, and it is judged whether investment can be made according to the result.

[0069] In this implementation method, the economic data also includes the total project investment (an example of the total project resources) and the investment cycle (an example of the project cycle). According to the feasibility study report of the project, the total project investment is obtained. The project plan document is obtained from the project management department, and the start time and the estimated end time of the project are found, and the time difference between the two is the investment cycle .

[0070] When calculating the expected benefit value EF based on the electricity market data, economic data, and the evaluation index MKS as described above, it can be based on the evaluation index , the market average growth rate in the electricity market data of the power grid, the total project investment in the economic data, and the investment cycle , and the benefit algorithm in the strategy generation module is used to calculate the expected benefit value . The expected benefit value can satisfy the following formula: , where is the expected benefit value, is the feasibility evaluation index, is the total project investment, is the investment cycle, is the market average growth rate. It can be understood that this formula is the revenue algorithm. In this formula, represents that, on the basis of considering the project investment scale and time span, the potential revenue of the project is measured by combining evaluation indicators. represents that as time goes by, the market growth will increase the potential revenue of the project, and the concept of compound growth is used here. represents a discount or adjustment of the expected revenue of the project under the consideration of the investment cycle.

[0071] When calculating the risk equilibrium coefficient ERBC according to the evaluation indicator MKS and the expected revenue value EF as above, the risk equilibrium coefficient ERBC can be calculated based on the evaluation indicator MKS and the expected revenue value EF by using the risk equilibrium algorithm in the strategy generation module. The risk equilibrium coefficient ERBC satisfies the following formula: , where is the risk equilibrium coefficient, is the expected revenue value, is the evaluation indicator. It can be understood that this formula is the risk equilibrium algorithm. In this formula, this term indicates that when MKS increases, the numerator increases, indicating that the comprehensive impact of risk and revenue is increasing. this term indicates that when MKS increases, the denominator also increases, but the growth rate may be different from that of the numerator, so as to obtain an equilibrium coefficient that comprehensively considers risk and revenue.

[0072] When calculating the comprehensive evaluation indicator CDI based on the expected revenue value EF and the risk equilibrium coefficient ERBC as above, the comprehensive revenue RAEP can be calculated based on the expected revenue value EF and the risk equilibrium coefficient ERBC by using the comprehensive revenue algorithm in the strategy generation module; based on the comprehensive revenue RAEP, the comprehensive evaluation indicator CDI is calculated.

[0073] The comprehensive revenue RAEP can satisfy the following formula: , where is the comprehensive revenue (an example of comprehensive return), is the expected revenue value, is the risk equilibrium coefficient, is the risk aversion coefficient. It can be understood that this formula is the comprehensive revenue algorithm. In this formula, this part normalizes the risk equilibrium coefficient, and its value is between 0 and 1, represents that according to the risk aversion coefficient, the normalized risk equilibrium coefficient is weighted to obtain a ratio that needs to be adjusted due to risk aversion, and finally multiplied by the expected revenue value , the comprehensive return value is obtained after comprehensively considering the expected return, risk balance, and risk aversion.

[0074] Risk aversion coefficient : By collecting data on past grid investment projects participated in, including the risk levels of the projects and the investment proportions in the projects; establishing a portfolio theory-based model, training the model, and performing regression analysis with the investment proportions in different projects as the dependent variable and the expected returns and variances of the projects as the independent variables, the estimated value of the risk aversion coefficient can be obtained .

[0075] The comprehensive evaluation index CDI can satisfy the following formula: , where is the comprehensive evaluation index, is the comprehensive return, is the standard deviation of returns (an example of the standard deviation of returns), is the average return on investment (an example of the average return rate), is the return volatility coefficient (an example of the return volatility coefficient); e is the natural constant, with a value of 2.71828. In this formula, this part is related to the standard deviation of returns SD. The standard deviation of returns reflects the degree of dispersion of returns. The larger the standard deviation, the greater the volatility of returns. The expression here makes the value of this part increase when SD increases. is related to the average return on investment AIR. The higher the average return on investment, the larger the value of this part. is also related to the standard deviation of returns SD. Here, the impact of the standard deviation on the denominator is again processed through a logical function, making the larger the standard deviation, the larger the denominator. The overall formula divides the numerator that comprehensively considers the comprehensive return, the standard deviation of returns, and the average return on investment by the denominator that considers the return volatility coefficient and the standard deviation of returns to obtain a comprehensive evaluation index CDI for comprehensively evaluating the return and risk of the project.

[0076] Standard deviation of returns : Collect the returns of each period of the grid investment project ; Based on the returns of each period , calculate the average return , and the calculation formula is:

[0077] where is the return in the jth year, and the value of j is [1, M]; M is the total number of years of returns and takes a positive integer value.

[0078] According to the returns of each period and the average return , calculate the standard deviation of returns , and the calculation formula is: .

[0079] Average return on investment : By collecting the return on investment data of each period of the power grid within a certain period, such as the past 5 years or 10 years, and dividing the return on investment of each period by the total number of periods, the average value of the return on investment data of each period is obtained, that is, the average return on investment .

[0080] Coefficient of return volatility : Based on the standard deviation of returns and the average return on investment , calculate the coefficient of return volatility , so as to obtain the coefficient of return volatility .

[0081] In the embodiment of the present invention, a comprehensive evaluation index threshold can also be preset : By analyzing the past investment projects of the power grid enterprise itself, calculate the comprehensive evaluation index of these projects , and summarize the distribution of successful projects and failed projects. If the past successful projects are generally greater than a certain value, while the failed projects are less than this value, then this value is used as the comprehensive evaluation index threshold. For example, if the past successful projects are generally greater than 0.6, while the failed projects are all less than 0.6, then 0.6 is used as the comprehensive evaluation index threshold.

[0082] When comparing the comprehensive evaluation index CDI with the comprehensive evaluation index threshold and judging whether investment can be made according to the result, if the comprehensive evaluation index is less than the preset comprehensive evaluation index threshold ( ), it is determined that the investment strategy of the power grid investment project includes that investment cannot be made; if the comprehensive evaluation index is not less than the preset comprehensive evaluation index threshold ( ), it is determined that the investment strategy of the power grid investment project includes that investment can be made.

[0083] The investment strategy of the power grid investment project in step 104 can be used as the basis for adjusting the operation strategy to guide the power grid to adjust its operation strategy. For example, in step 105, a resource optimization configuration algorithm can be executed. Based on the investment strategy of the power grid investment project and combined with the resource data, equipment operation data, and power data of the power grid, the strategy is adjusted for equipment updates, technological transformations, construction timings, etc., to obtain a technical implementation plan including equipment replacement priorities, technological transformation paths, and construction timing plans. After adjusting the operation strategy, the smart grid can also perform feedback control to achieve closed-loop control between the power grid investment project and the smart grid, better meeting the development needs of the future smart grid. Optionally, the operation strategy can also be flexibly adjusted in combination with factors such as regional energy policies to enhance the feasibility of the solution in the embodiments of the present invention.

[0084] In the above steps 104-105, the expected return, risk balance coefficient, and comprehensive income are calculated, and it is judged whether investment can be made by comparing the comprehensive evaluation index with the threshold. This fully considers the balance between the income and risk of the investment project, provides a scientific and reasonable investment basis, helps optimize the investment decision, and improves the success rate and return rate of power grid investment.

[0085] For further illustration, in the embodiments of the present invention, for the operation data of a certain regional power grid (including 58 nodes of 220 kV and above) from 2021 to 2023, the traditional power grid investment decision-making scheme that only uses economic indicators is simulated in parallel with the power grid investment intelligent decision-making scheme in the embodiments of the present invention that uses multi-dimensional indicators combined with intelligent decision-making algorithms for 6 months, and the following table is obtained:

[0086] It can be seen from the above table that the power grid investment intelligent decision-making scheme provided by the embodiments of the present invention can greatly improve the evaluation accuracy of power grid investment projects compared with the traditional scheme, can identify high-risk scenarios, avoid misjudgment scenarios, improve the misjudgment avoidance ability, reduce the decision-making error risk in complex scenarios, ensure the safe and reliable operation of the power grid, and can also assist the operator to avoid investment losses in advance.

[0087] The following uses a specific embodiment to illustrate the embodiments of the present invention. See Figure 2 , including the following process: Collect the economic data, equipment operation data, power data, and power market data of the power grid; Calculate the net present value based on economic data, and calculate the economic benefit indicators based on the net present value and economic data; calculate the power supply reliability rate and the mean time between failures respectively according to the equipment operation data, and calculate the power grid reliability indicators based on the power supply reliability rate and the mean time between failures; calculate the energy consumption intensity based on the equipment operation data, calculate the renewable energy utilization rate based on the electric energy data, and calculate the environmental impact indicators based on the energy consumption intensity and the renewable energy utilization rate; Calculate the evaluation indicators based on the economic benefit indicators, the power grid reliability indicators and the environmental impact indicators; preset the evaluation indicator threshold, compare the evaluation indicators with the evaluation indicator threshold, and judge whether the power grid investment project is a risky project or a healthy project according to the result; when the power grid investment project is a risky project, send an alarm signal; When the power grid investment project is a healthy project, calculate the expected revenue value according to the power market data, the economic data and the evaluation indicators; further calculate the risk balance coefficient according to the evaluation indicators and the expected revenue value; calculate the comprehensive revenue according to the expected revenue value and the risk balance coefficient; calculate the comprehensive evaluation indicator based on the comprehensive revenue, preset the comprehensive evaluation indicator threshold, compare the comprehensive evaluation indicator with the comprehensive evaluation indicator threshold, and judge whether investment can be made according to the result.

[0088] In this embodiment, by collecting multiple data of the power grid; calculating the economic benefit indicators, the power grid reliability indicators and the environmental impact indicators respectively, further calculating the evaluation indicators, presetting the evaluation indicator threshold and comparing to judge whether the power grid investment project is a risky project or a healthy project; when the power grid investment project is a healthy project, calculating the expected revenue value based on the evaluation indicators, and then calculating the risk balance coefficient; calculating the comprehensive revenue according to the expected revenue value and the risk balance coefficient; calculating the comprehensive evaluation indicator based on the comprehensive revenue; presetting the threshold and comparing to judge whether investment can be made. This method can comprehensively evaluate the risks and benefits of the power grid investment project, and provide a scientific and accurate basis for investment decision-making.

[0089] Embodiment 2: Based on the same inventive concept, the present invention also provides a power grid investment intelligent decision-making system, including a data acquisition device and a server connected by communication; a resource allocation evaluation model, a feasibility analysis engine and an environmental impact calculation unit are deployed on the server; The data acquisition device is used to collect the resource data, equipment operation data, electric energy data and power market data of the power grid; A server is used to generate grid resource efficiency allocation indicators by using a resource allocation evaluation model based on the resource data of the power grid; run a feasibility analysis engine based on the equipment operation data of the power grid to output grid reliability indicators; calculate environmental impact indicators by using an environmental impact calculation unit based on the power energy data and equipment operation data of the power grid; perform multi-dimensional index fusion calculation on the grid resource efficiency allocation indicators, grid reliability indicators and environmental impact indicators, and generate an investment strategy for grid investment projects in combination with the power market data and resource data of the power grid; execute the investment strategy of grid investment projects to drive the power grid to adjust its operation strategy.

[0090] The server can implement the grid investment intelligent decision-making method in the above embodiments, which will not be elaborated here.

[0091] Considering the large coverage area of the power grid, in order to ensure the efficient completion of grid investment intelligent decision-making, the server can be deployed in the form of edge computing nodes and combined with data acquisition devices to achieve closed-loop processing. Or the server can also be deployed with a power grid digital platform, which integrates grid investment decision-making methods and has good engineering adaptability.

[0092] Embodiment 3: Based on the same inventive concept, the present invention also provides a grid investment intelligent decision-making system, the structural schematic diagram of which is as Figure 3 shown, including: An efficiency allocation index determination module, which is used to generate grid resource efficiency allocation indicators by using a resource allocation evaluation model based on the resource data of the power grid; A grid reliability index determination module, which is used to run a feasibility analysis engine based on the equipment operation data of the power grid to output grid reliability indicators; An environmental impact index determination module, which is used to calculate environmental impact indicators by using an environmental impact calculation unit based on the power energy data and equipment operation data of the power grid; An investment decision module, which is used to perform multi-dimensional index fusion calculation on the grid resource efficiency allocation indicators, grid reliability indicators and environmental impact indicators, and generate an investment strategy for grid investment projects in combination with the power market data and resource data of the power grid; An operation strategy adjustment module, which is used to execute the investment strategy of grid investment projects to drive the power grid to adjust its operation strategy.

[0093] Optionally, the efficiency allocation index determination module includes: A resource allocation credibility calculation unit, which is used to generate resource allocation feasibility data by using a resource allocation risk sub-model in the resource allocation evaluation model based on the initial resources and resource allocation situation in the resource data of the power grid; the resource allocation feasibility data is used to represent the resource flow situation and allocation risk during resource allocation; A resource efficiency allocation calculation unit, configured to generate a power grid resource efficiency allocation index by using a resource allocation efficiency sub-model in a resource allocation evaluation model based on initial resources, the average annual resource allocation in resource data, and resource allocation feasibility data. The resource allocation feasibility data satisfies the following formula: , where is the resource allocation feasibility data, is a resource allocation parameter, is the resource allocation in the i-th year, where i ranges from [1, n] and n is the total number of years, is the initial resource; The power grid resource efficiency allocation index satisfies the following formula: , where is the power grid resource efficiency allocation index, is the average annual resource allocation.

[0094] Optionally, the power grid reliability index determination module includes: A power supply reliability rate calculation unit, configured to execute a power supply reliability algorithm based on the total power supply time, planned power outage time, and fault power outage time in equipment operation data by using a feasibility analysis engine to output the power supply reliability rate; A fault-free time calculation unit, configured to output the average fault-free time by using a feasibility analysis engine based on the total equipment operation time in equipment operation data; A reliability index calculation unit, configured to use a feasibility analysis engine to perform weighted summation on the power supply reliability rate and the average fault-free time to obtain a power grid reliability index; The power supply reliability rate satisfies the following formula: , where is the power supply reliability rate, is the total power supply time, is the planned power outage time, is the fault power outage time; The average fault-free time satisfies the following formula: , where is the average fault-free time, is the total equipment operation time, is a constant, is the total maintenance time.

[0095] Optionally, the environmental impact index determination module includes: An energy consumption calculation unit, which is used to calculate the energy consumption intensity based on the total power supply of the power grid, the total operating time of the equipment, and the rated power of the equipment in the equipment operation data, by using the energy consumption algorithm in the environmental impact calculation unit; A renewable energy utilization rate calculation unit, which is used to calculate the renewable energy utilization rate based on the renewable energy power generation and the total power generation of the power grid in the electric energy data of the power grid, by using the renewable energy algorithm in the environmental impact calculation unit; An impact index calculation unit, which is used to perform weighted summation on the energy consumption intensity and the renewable energy utilization rate to obtain an environmental impact index; The energy consumption intensity satisfies the following formula: , where is the energy consumption intensity, is the total energy consumed during the operation of the power grid, is the rated power of the equipment, is the total operating time of the equipment, is the total power supply of the power grid, is the energy conversion efficiency of the equipment; The renewable energy utilization rate satisfies the following formula: , where is the renewable energy utilization rate, is the renewable energy power generation, is the proportion of the maintenance time of the renewable energy power generation equipment, is the stability coefficient, is the total power generation of the power grid.

[0096] Optionally, the investment decision module includes: A feasibility evaluation calculation unit, which is used to perform multi-dimensional index fusion calculation on the power grid resource efficiency allocation index, the power grid reliability index, and the environmental impact index to obtain a feasibility evaluation index for the power grid investment project; An investment strategy generation unit, which is used to trigger the strategy generation module when the feasibility evaluation index indicates that the power grid investment project has investment feasibility, and generate an investment strategy for the power grid investment project based on the feasibility evaluation index, combined with the power market data and resource data of the power grid; Optionally, the investment strategy generation unit is specifically configured to trigger the strategy generation module to calculate the expected return based on the feasibility evaluation index, the market average growth rate in the power market data of the power grid, the total project resources in the resource data, and the project cycle; calculate the risk balance coefficient using the risk balance algorithm based on the feasibility evaluation index and the expected return; calculate the comprehensive return based on the expected return and the risk balance coefficient; calculate the comprehensive evaluation index based on the comprehensive return; if the comprehensive evaluation index is less than the preset comprehensive evaluation index threshold, determine that the investment strategy of the power grid investment project includes that investment cannot be made; otherwise, determine that the investment strategy of the power grid investment project includes that investment can be made.

[0097] The expected return satisfies the following formula: , where is the expected return, is the feasibility evaluation index, is the total project resources, is the project cycle, is the market average growth rate; The risk balance coefficient satisfies the following formula: , where is the risk balance coefficient, is the expected return, is the feasibility evaluation index; The comprehensive return satisfies the following formula: , where is the comprehensive return, is the expected return, is the risk balance coefficient, is the risk aversion coefficient; The comprehensive evaluation index satisfies the following formula: , where is the comprehensive evaluation index, is the comprehensive return, is the return standard deviation, is the average rate of return, is the return volatility coefficient.

[0098] Optionally, it further includes: The risk status determination module is configured to compare the feasibility evaluation index with the preset evaluation index threshold; if the feasibility evaluation index is less than or equal to the evaluation index threshold, determine that the power grid investment project does not have investment feasibility and send an alarm signal; if the feasibility evaluation index is greater than the evaluation index threshold, determine that the power grid investment project has investment feasibility.

[0099] Example 4: AsFigure 4 As shown, the present invention also provides an electronic device, which may be a computer device, a single-chip microcomputer device, a smart mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, the processor, and the transceiver component are connected by a bus; the memory can be used to store an execution program, and an exemplary execution program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, and this data can be called and / or modified when the instructions are executed.

[0100] The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of a power grid investment intelligent decision-making method in the above embodiment.

[0101] Embodiment 5: Based on the same inventive concept, the present invention also provides a readable storage medium, specifically an electronic device-readable storage medium (Memory). The electronic device-readable storage medium is a memory device in the electronic device and is used to store programs and data. It can be understood that the storage medium here can include both the built-in storage medium in the electronic device and, of course, the extended storage medium supported by the electronic device. The storage medium provides a storage space, and the operating system of the terminal is stored in this storage space. And, one or more instructions suitable for being loaded and executed by the processor are also stored in this storage space. These instructions can be one or more execution programs (including program codes). It should be noted that the storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. By the processor loading and executing one or more instructions stored in the storage medium, the steps of a power grid investment intelligent decision-making method in the above embodiment can be implemented.

[0102] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0103] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0104] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0105] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit its protection scope. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that after reading the present invention, various changes, modifications, or equivalent replacements can still be made to the specific implementation manners of the invention. However, these changes, modifications, or equivalent replacements are all within the protection scope of the pending claims of the invention.

Claims

1. An intelligent decision-making method for power grid investment, characterized in that, The method includes: Based on the resource data of the power grid, using a resource allocation evaluation model to generate power grid resource efficiency allocation indicators; Based on the equipment operation data of the power grid, running a feasibility analysis engine to output power grid reliability indicators; Based on the power energy data of the power grid and the equipment operation data, using an environmental impact calculation unit to calculate environmental impact indicators; Performing multi-dimensional index fusion calculation on the power grid resource efficiency allocation indicators, the power grid reliability indicators and the environmental impact indicators, and combining the power market data of the power grid and the resource data to generate an investment strategy for power grid investment projects; Executing the investment strategy of the power grid investment project to drive the power grid to adjust its operation strategy.

2. The method according to claim 1, characterized in that, The step of based on the resource data of the power grid, using a resource allocation evaluation model to generate power grid resource efficiency allocation indicators includes: Based on the initial resources and resource allocation situation in the resource data of the power grid, using the resource allocation risk sub-model in the resource allocation evaluation model to generate resource allocation feasibility data; the resource allocation feasibility data is used to represent the resource flow situation and allocation risk during resource allocation; Based on the initial resources, the average annual resource allocation situation in the resource data and the resource allocation feasibility data, using the resource allocation efficiency sub-model in the resource allocation evaluation model to generate power grid resource efficiency allocation indicators; The resource allocation feasibility data satisfies the following formula: , where is the resource allocation feasibility data, is the resource allocation parameter, is the resource allocation situation in the i-th year, where the value range of i is [1, n], and n is the total number of years, is the initial resource; The power grid resource efficiency allocation indicators satisfy the following formula: , where is the power grid resource efficiency allocation index, is the average annual resource allocation situation.

3. The method according to claim 1, wherein The step of based on the equipment operation data of the power grid, running a feasibility analysis engine to output power grid reliability indicators includes: Based on the total power supply time, planned power outage time and fault power outage time in the equipment operation data, running a feasibility analysis engine to execute a power supply reliability algorithm to output a power supply reliability rate; Based on the total equipment operation time in the equipment operation data, running the feasibility analysis engine to output the mean time between failures; Running the feasibility analysis engine to perform weighted summation on the power supply reliability rate and the mean time between failures to obtain power grid reliability indicators; The power supply reliability rate satisfies the following formula: , where is the power supply reliability rate, is the total power supply time, is the planned power outage time, is the fault power outage time; The mean time between failures satisfies the following formula: , where is the mean time between failures, is the total operating time of the device, is a constant, is the total repair time.

4. The method according to claim 1, wherein The step of based on the power energy data of the power grid and the equipment operation data, using an environmental impact calculation unit to calculate environmental impact indicators includes: Based on the total power supply of the power grid, total equipment operation time and rated power of the equipment in the equipment operation data, using the energy consumption algorithm in the environmental impact calculation unit to calculate the energy consumption intensity; Based on the renewable energy power generation and total power generation of the power grid in the power energy data of the power grid, using the renewable energy algorithm in the environmental impact calculation unit to calculate the renewable energy utilization rate; Performing weighted summation on the energy consumption intensity and the renewable energy utilization rate to obtain environmental impact indicators; The energy consumption intensity satisfies the following formula: , where is the energy consumption intensity, is the total amount of energy consumed during the operation of the power grid, is the rated power of the equipment, is the total operating time of the equipment, is the total power supply of the power grid, is the energy conversion efficiency of the equipment; The renewable energy utilization rate satisfies the following formula: , where is the utilization rate of renewable energy, is the power generation of renewable energy, is the proportion of maintenance time of renewable energy power generation equipment, is the stability coefficient, is the total power generation of the power grid.

5. The method according to any one of claims 1-4, characterized in that, The step of performing multi-dimensional index fusion calculation on the power grid resource efficiency allocation indicators, the power grid reliability indicators and the environmental impact indicators, and combining the power market data of the power grid and the resource data to generate an investment strategy for power grid investment projects includes: Perform multi-dimensional index fusion calculation on the grid resource efficiency allocation index, the grid reliability index, and the environmental impact index to obtain a feasibility evaluation index for the grid investment project; When the feasibility evaluation index indicates that the grid investment project has investment feasibility, trigger the strategy generation module, and based on the feasibility evaluation index, combine the power market data and the resource data of the grid to generate an investment strategy for the grid investment project; The trigger strategy generation module generates an investment strategy for the grid investment project based on the feasibility evaluation index, combining the power market data and the resource data of the grid, including: The trigger strategy generation module calculates the expected return based on the feasibility evaluation index, the market average growth rate in the power market data of the grid, the total project resources and the project cycle in the resource data; Based on the feasibility evaluation index and the expected return, calculate the risk balance coefficient using the risk balance algorithm; Based on the expected return and the risk balance coefficient, calculate the comprehensive return; calculate the comprehensive evaluation index based on the comprehensive return; If the comprehensive evaluation index is less than the preset comprehensive evaluation index threshold, determine that the investment strategy for the grid investment project includes that investment cannot be made; otherwise, determine that the investment strategy for the grid investment project includes that investment can be made; The expected return satisfies the following formula: , where is the expected return, is the feasibility evaluation index, is the total project resources, is the project cycle, is the average market growth rate; The risk balance coefficient satisfies the following formula: , where is the risk balance coefficient, is the expected return, is the feasibility evaluation index; The comprehensive return satisfies the following formula: , where is the comprehensive return, is the expected return, is the risk balance coefficient, is the risk aversion coefficient; The comprehensive evaluation index satisfies the following formula: , where is the comprehensive evaluation index, is the comprehensive return, is the standard deviation of returns, is the average rate of return, is the return volatility coefficient.

6. The method according to claim 5, wherein After performing multi-dimensional index fusion calculation on the grid resource efficiency allocation index, the grid reliability index, and the environmental impact index to obtain a feasibility evaluation index for the grid investment project, it further includes: Compare the feasibility evaluation index with the preset evaluation index threshold; If the feasibility evaluation index is less than or equal to the evaluation index threshold, determine that the grid investment project does not have investment feasibility and issue an alarm signal; If the feasibility evaluation index is greater than the evaluation index threshold, determine that the grid investment project has investment feasibility.

7. An intelligent decision-making system for power grid investment, characterized in that, It includes a data acquisition device and a server connected by communication; a resource allocation evaluation model, a feasibility analysis engine, and an environmental impact calculation unit are deployed on the server; The data acquisition device is used to collect resource data, equipment operation data, power data, and power market data of the grid; The server is used to generate a grid resource efficiency allocation index using the resource allocation evaluation model based on the resource data of the grid; run the feasibility analysis engine to output the grid reliability index based on the equipment operation data of the grid; calculate the environmental impact index using the environmental impact calculation unit based on the power data and the equipment operation data of the grid; perform multi-dimensional index fusion calculation on the grid resource efficiency allocation index, the grid reliability index, and the environmental impact index, and combine the power market data and the resource data of the grid to generate an investment strategy for the grid investment project; Execute the investment strategy of the grid investment project to drive the grid to adjust the operation strategy.

8. An intelligent decision-making system for power grid investment, characterized in that, It includes: An efficiency allocation index determination module, configured to generate grid resource efficiency allocation indexes based on the resource data of the power grid by using a resource allocation evaluation model; A grid reliability index determination module, configured to output grid reliability indexes based on the equipment operation data of the power grid by an operation feasibility analysis engine; An environmental impact index determination module, configured to calculate environmental impact indexes by using an environmental impact calculation unit based on the electric energy data of the power grid and the equipment operation data; An investment decision-making module, configured to perform multi-dimensional index fusion calculation on the grid resource efficiency allocation indexes, the grid reliability indexes and the environmental impact indexes, and generate an investment strategy for a grid investment project in combination with the power market data of the power grid and the resource data; An operation strategy adjustment module, configured to execute the investment strategy of the grid investment project and drive the power grid to adjust the operation strategy.

9. An electronic device, characterized in that, Comprising: At least one processor and a memory; The memory and the processor are connected by a bus; The memory is configured to store one or more programs; When the one or more programs are executed by the at least one processor, the grid investment intelligent decision-making method according to any one of claims 1 to 6 is implemented.

10. A readable storage medium, characterized in that, An execution program is stored thereon, and when the execution program is executed, the grid investment intelligent decision-making method according to any one of claims 1 to 6 is implemented.

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