A method and system for investment decision-making analysis of power plant construction projects based on power big data

Abstract

The present invention discloses a method and system for investment decision-making analysis of power plant construction projects based on power big data, including the following steps: data collection: obtaining project data corresponding to the projects to be evaluated and predicted through financial budget statements and a power big data platform; data processing is divided into primary processing and secondary processing; generating a report; in the traditional investment decision-making analysis system for power plant construction projects, the cited data is relatively lacking, while this system cites more data, including industry data, competitor data, economic indicator libraries, policy data, and regional data. The data sources mainly include obtaining through economic evaluation tools, manual input, web crawler import, docking with third-party platforms, and provision by relevant authoritative institutions. The diversity of data sources makes the analysis results more accurate, and the authority of data sources further improves the accuracy of the analysis results.

Description

Technical Field

[0001] The present invention belongs to the technical field of power plant investment decision - making analysis, and particularly relates to a method and system for investment decision - making analysis of power plant construction projects based on power big data. Background Art

[0002] In the development process of power economics, the introduction of power big data, especially power consumption big data, is an important supplement and improvement to the sub - discipline of observing the economy through power in power economics, opening up new research directions and methods. However, at present, the methods and results of associative analysis between power big data and economic evaluation - type data are not intuitive and clear enough, and there is still much room for further optimization in data sources and data selection. In order to make full use of the value contained in power big data, more in - depth analysis and exploration are needed;

[0003] In the past, economic evaluations of power construction projects usually used Excel to create models, input corresponding data, and perform calculations through Excel functions for analysis, and made investment judgments based on the calculation and analysis results. This method relies on manual processing, has extremely high requirements for the professionalism of personnel; and cannot be replicated, increasing the workload significantly; it has poor flexibility and cannot be adjusted flexibly as needed;

[0004] Both stand - alone and network - based economic evaluation systems have emerged, with a certain degree of flexibility and improved efficiency. However, the current such systems only perform evaluation and analysis based on the input data, without associating with investment decisions. Moreover, the current such systems adopt an embedded method for economic evaluation parameters and methods, and cannot be adjusted when parameters or methods change, requiring the development of new software or the overall upgrade of the entire system;

[0005] With the development of Internet and big data - related technologies, the componentization degree of computing engines is getting higher and higher, and the computing engine mode is used in many projects. As the name implies, a computing engine is the power core of a system, responsible for the source of data, data operations, data management during calculations, and returning appropriate calculation results as required. There are many different categories according to different purposes of data processing. Summary of the Invention

[0006] The purpose of the present invention is to provide a method and system for investment decision - making analysis of power plant construction projects based on power big data, so as to solve the problems proposed in the above background art that the current such systems only perform evaluation and analysis based on the input data, without associating with investment decisions, and the current such systems adopt an embedded method for economic evaluation parameters and methods, and cannot be adjusted when parameters or methods change, requiring the development of new software or the overall upgrade of the entire system.

[0007] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0008] A method for investment decision-making analysis of a power plant construction project based on power big data, comprising the following steps:

[0009] S1: Data collection: Obtain project data corresponding to the project to be evaluated and predicted through financial budget statements and a power big data platform;

[0010] S2: Data processing:

[0011] Primary processing: First, preprocess the collected data through a preprocessing system, then calculate the preprocessed data to obtain the incremental revenue and operation and maintenance costs after the project to be evaluated and predicted is put into production, and use a value chain analysis tool and a financial calculation model to calculate the cost allocated after the project is put into production, and calculate the project capital cost of the project to be evaluated and predicted in combination with the capital cost rate. Then, based on the incremental revenue after production, operation and maintenance costs after production, allocated costs after production, and project capital cost calculated for the project to be evaluated and predicted above, and in combination with a calculation engine and an economic evaluation model, analyze the economic feasibility of the project to be evaluated through a cloud computing platform, and save the calculated values to a database;

[0012] Secondary processing: Deeply analyze the data in the database in combination with data such as information on operating generating units, generating units under construction, regional new energy consumption levels, regional electricity demand levels, photovoltaic resource data, regional power grid capacity, and regional wind resource capacity in the economic evaluation database by using a benchmarking and competitiveness analysis tool and an energy and policy research tool;

[0013] S3: Report generation: Make a benchmarking decision on the key indicators and parameters of the project based on the analysis structure of the secondary processing, and compare the analysis results with the average level and leading level in the industry, and generate a decision-making analysis report accordingly.

[0014] As a further solution of the present invention, the method for investment decision-making analysis of a power plant construction project based on power big data is applied to an investment decision-making analysis system for a power plant construction project based on power big data. The investment decision-making analysis system for a power plant construction project based on power big data includes an economic evaluation subsystem, a visual decision support subsystem, a competition evaluation map subsystem, an economic evaluation database, a cloud computing platform, and a cloud storage platform.

[0015] As a further solution of the present invention, the economic evaluation subsystem includes an index system preprocessing management system, a data parameter preprocessing management system, a single-factor uncertainty analysis and prediction system, a multi-factor uncertainty analysis and prediction system, a trial calculation system, an early warning system, and a calculation engine, where the evaluation is divided into economic evaluation and investment judgment evaluation.

[0016] As a further solution of the present invention, the economic evaluation subsystem obtains the project data corresponding to the project to be evaluated and predicted through the financial budget statement and the power big data platform, and preprocesses the data through the index system preprocessing management system and the data parameter preprocessing management system.

[0017] As a further solution of the present invention, the preprocessed data is calculated through the single-factor uncertainty analysis and prediction system, the multi-factor uncertainty analysis and prediction system, the trial calculation system, the early warning system and the calculation engine, and the incremental income and operation and maintenance costs after the production of the project to be evaluated are calculated. The cost allocated after the production of the project is calculated by using the value chain analysis tool and the financial calculation model, and the project capital cost of the project to be evaluated and predicted is calculated in combination with the capital cost rate.

[0018] As a further solution of the present invention, based on the incremental income after production, the operation and maintenance cost after production, the allocated cost after production, and the project capital cost calculated for the project to be evaluated and predicted, the economic feasibility of the project to be evaluated is analyzed through the cloud computing platform in combination with the calculation engine and the economic evaluation model, and the calculated values are all saved in the economic evaluation database.

[0019] As a further solution of the present invention, the economic evaluation calculates the operation model by inputting basic parameters, and then generates graphs, reports and evaluation reports through the sensitivity analysis of the input parameters. The investment judgment evaluation reads the project information database, conducts control during the evaluation process, and then conducts statistical analysis and message reminders.

[0020] As a further solution of the present invention, the data saved in the economic evaluation database obtained through the economic evaluation subsystem is exported, and in combination with the data such as the information of the operating generating units, the information of the generating units under construction, the regional new energy consumption level, the regional electricity demand level, the photovoltaic resource data, the regional power grid capacity, and the regional wind resource capacity saved in the economic evaluation database, in-depth analysis is carried out by using the benchmarking and competitiveness analysis tool and the energy and policy research tool.

[0021] As a further solution of the present invention, for the visual decision support, benchmarking decisions are made on the indicators and parameters in the project based on the analysis results of the competitiveness map subsystem, and the analysis results are compared with the average level and the leading level in the industry, and a decision analysis report is generated accordingly.

[0022] As a further solution of the present invention, the economic evaluation database includes industry numerical control, competitor data, economic indicator library, policy data and regional data.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] 1. In the traditional power plant construction project investment decision - making analysis system, the data cited is relatively scarce. This system cites more data, including industry data, competitor data, economic indicator databases, policy data, and regional data. The data sources mainly include economic evaluation tools, manual input, web crawler import, connection with third - party platforms, and provision by relevant authoritative institutions. The diversity of data sources makes the analysis results more accurate, and the authority of data sources further improves the accuracy of the analysis results.

[0025] 2. The current economic evaluation systems only conduct evaluation and analysis by inputting data and are not linked to investment decisions, resulting in an inflexible analysis process and results that do not conform to the actual situation. This system adds a visual decision - making support subsystem, makes benchmark decisions on the indicators and parameters in the project based on the analysis results of the competitiveness map subsystem, and compares the analysis results with the average and leading levels in the industry to generate a decision - making analysis report, making the analysis results more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the overall system structure of the present invention;

[0027] Figure 2 It is a first - structure schematic diagram of the economic evaluation subsystem of the present invention;

[0028] Figure 3 It is a second - structure schematic diagram of the economic evaluation subsystem of the present invention;

[0029] Figure 4 It is a schematic diagram of the economic evaluation structure of the present invention;

[0030] Figure 5 It is a schematic diagram of the investment judgment evaluation structure of the present invention;

[0031] Figure 6 It is a schematic diagram of the structure of the competition evaluation map subsystem of the present invention;

[0032] Figure 7 It is a schematic diagram of the competitiveness analysis structure of the present invention;

[0033] Figure 8 It is a schematic diagram of the intelligence map structure of the present invention;

[0034] Figure 9 It is a schematic diagram of the structure of the visual decision - making support subsystem of the present invention;

[0035] Figure 10 It is a schematic diagram of the composition structure of the economic evaluation database of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0036] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0037] Please refer to Figures 1 - 10 , the present invention provides a method for investment decision-making analysis of a power plant construction project based on power big data, including the following steps:

[0038] S1: Data collection: Obtain the project data corresponding to the project to be evaluated and predicted through the financial budget statement and the power big data platform;

[0039] S2: Data processing:

[0040] Primary processing: First, preprocess the collected data through the preprocessing system, then calculate the preprocessed data to obtain the incremental revenue and operation and maintenance costs after the project to be evaluated and predicted is put into production, and use the value chain analysis tool and the financial calculation model to calculate the allocated costs after the project is put into production, and combine the capital cost rate to calculate the project capital cost of the project to be evaluated and predicted. Then, based on the incremental revenue after the project to be evaluated and predicted is put into production, the operation and maintenance costs after the project is put into production, the allocated costs after the project is put into production, and the project capital cost calculated above, combined with the calculation engine and the economic evaluation model, analyze the economic feasibility of the project to be evaluated through the cloud computing platform, and save all the calculated values into the database;

[0041] Secondary processing: Deeply analyze the data in the database in combination with the information of the already commissioned generating units, the generating units under construction, the regional new energy consumption level, the regional electricity demand level, the photovoltaic resource data, the regional power grid capacity, the regional wind resource capacity, etc. in the economic evaluation database by using the benchmarking and competitiveness analysis tool and the energy and policy research tool;

[0042] S3: Generate a report: Make a benchmarking decision on the key indicators and parameters of the project based on the analysis structure of the secondary processing, and compare the analysis results with the average level and the leading level in the industry, and generate a decision-making analysis report accordingly.

[0043] Specifically, as Figure 1 shown, the method for investment decision-making analysis of a power plant construction project based on power big data is applied to the investment decision-making analysis system of a power plant construction project based on power big data. The investment decision-making analysis system of a power plant construction project based on power big data includes an economic evaluation subsystem, a visual decision support subsystem, a competition evaluation map subsystem, an economic evaluation database, a cloud computing platform, and a cloud storage platform.

[0044] Specifically, as Figure 2 and Figure 3 shown, the economic evaluation subsystem includes an index system preprocessing management system, a data parameter preprocessing management system, a single-factor uncertainty analysis and prediction system, a multi-factor uncertainty analysis and prediction system, a trial calculation system, an early warning system, and a calculation engine. The evaluation is divided into economic evaluation and investment judgment evaluation.

[0045] Specifically, as Figure 2 shown, the economic evaluation subsystem obtains the project data corresponding to the project to be evaluated and predicted through the financial budget statement and the power big data platform, and preprocesses the data through the index system preprocessing management system and the data parameter preprocessing management system.

[0046] Specifically, as Figure 2 shown, the preprocessed data is calculated through the single-factor uncertainty analysis and prediction system, the multi-factor uncertainty analysis and prediction system, the trial calculation system, the early warning system, and the calculation engine. The incremental revenue and operation and maintenance costs after the project to be evaluated is put into production are calculated, and the allocated costs after the project is put into production are calculated using the value chain analysis tool and the financial calculation model. The project capital cost of the project to be evaluated and predicted is calculated in combination with the capital cost rate.

[0047] Specifically, as Figure 2 shown, according to the incremental revenue after the project to be evaluated and predicted is put into production, the operation and maintenance costs after the project is put into production, the allocated costs after the project is put into production, and the project capital cost, the economic feasibility of the project to be evaluated is analyzed through the cloud computing platform in combination with the calculation engine and the economic evaluation model. The calculated values are all saved in the economic evaluation database.

[0048] Specifically, as Figure 4 and Figure 5 shown, the economic evaluation calculates the operation model by inputting basic parameters, and then generates graphs, reports, and evaluation reports through the sensitivity analysis of the input parameters. The investment judgment evaluation reads the project information database, conducts control during the evaluation process, and then conducts statistical analysis and message reminders.

[0049] Specifically, as Figure 8 shown, the data saved in the economic evaluation database obtained through the economic evaluation subsystem is exported, and in-depth analysis is carried out using the benchmarking and competitiveness analysis tool and the energy and policy research tool in combination with the data such as the information of the already-operated generating units, the information of the generating units under construction, the regional new energy consumption level, the regional electricity demand level, the photovoltaic resource data, the regional power grid capacity, and the regional wind resource capacity saved in the economic evaluation database.

[0050] Specifically, as Figures 6 - 9As shown, for visual decision support, benchmarking decisions are made on the indicators and parameters in the project based on the analysis results of the competitiveness map subsystem, and the analysis results are compared with the industry average level and leading level, and a decision analysis report is generated accordingly.

[0051] Specifically, as Figure 10 shown, the economic evaluation database includes industry numerical control, competitor data, economic indicator library, policy data, and regional data.

[0052] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only to illustrate the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements fall within the scope of the present invention claimed. The scope of the present invention claimed is defined by the appended claims and their equivalents.

Claims

1. A method for investment decision-making analysis of power plant construction projects based on power big data, characterized in that: It includes the following steps: S1: Data collection: Obtain the project data corresponding to the project to be evaluated and predicted through the financial budget statement and the power big data platform; S2: Data processing: Primary processing: First, preprocess the collected data through the preprocessing system, then calculate the preprocessed data to obtain the incremental revenue and operation and maintenance costs after the project to be evaluated and predicted is put into production, and use the value chain analysis tool and the financial calculation model to calculate the allocated costs after the project is put into production, and calculate the project capital cost of the project to be evaluated and predicted in combination with the capital cost rate. Then, based on the incremental revenue after production, operation and maintenance costs after production, allocated costs after production, and project capital cost calculated for the project to be evaluated and predicted above, analyze the economic feasibility of the project to be evaluated through the cloud computing platform in combination with the calculation engine and the economic evaluation model, and save the calculated values to the database; Secondary processing: Deeply analyze the data in the database in combination with the information of the operating generating units, under-construction generating units, regional new energy consumption level, regional power demand level, photovoltaic resource data, regional power grid capacity, and regional wind resource capacity data in the economic evaluation database by using the benchmarking and competitiveness analysis tool and the energy and policy research tool; S3: Report generation: Make a benchmarking decision on the key indicators and parameters of the project based on the analysis structure of the secondary processing, and compare the analysis results with the industry average level and leading level, and generate a decision analysis report accordingly.

2. A power plant construction project investment decision-making analysis system based on power big data, characterized in that: Apply the power big data-based investment decision analysis method for power plant construction projects described in claim 1 to the power big data-based investment decision analysis system for power plant construction projects. The power big data-based investment decision analysis system for power plant construction projects includes an economic evaluation subsystem, a visual decision support subsystem, a competition evaluation map subsystem, an economic evaluation database, a cloud computing platform, and a cloud storage platform.

3. The investment decision-making analysis system for power plant construction projects based on power big data according to claim 2, wherein: The economic evaluation subsystem includes an index system preprocessing management system, a data parameter preprocessing management system, a single-factor uncertainty analysis and prediction system, a multi-factor uncertainty analysis and prediction system, a trial calculation system, an early warning system, and a calculation engine, where the evaluation is divided into economic evaluation and investment judgment evaluation.

4. The investment decision-making analysis system for power plant construction projects based on power big data according to claim 3, wherein: The economic evaluation subsystem obtains the project data corresponding to the project to be evaluated and predicted through the financial budget statement and the power big data platform, and preprocesses the data through the index system preprocessing management system and the data parameter preprocessing management system.

5. The investment decision-making analysis system for power plant construction projects based on power big data according to claim 3, characterized in that: The preprocessed data is calculated through the single-factor uncertainty analysis and prediction system, the multi-factor uncertainty analysis and prediction system, the trial calculation system, the early warning system, and the calculation engine to obtain the incremental revenue and operation and maintenance costs after the project to be evaluated is put into production, and use the value chain analysis tool and the financial calculation model to calculate the allocated costs after the project is put into production, and calculate the project capital cost of the project to be evaluated and predicted in combination with the capital cost rate.

6. The investment decision-making analysis system for power plant construction projects based on power big data according to claim 5, wherein: The incremental revenue after production, operation and maintenance costs after production, allocated costs after production, and project capital costs calculated based on the projects to be evaluated and predicted are combined with the calculation engine and economic evaluation model to analyze the economic feasibility of the projects to be evaluated through the cloud computing platform. The calculated values are all saved in the economic evaluation database.

7. The investment decision-making analysis system for power plant construction projects based on power big data according to claim 3, wherein: The economic evaluation generates graphs, reports, and evaluation reports through inputting basic parameters, calculating the operation model, and then performing sensitivity analysis on the input parameters. The investment judgment evaluation reads the project information database, conducts control during the evaluation process, and then performs statistical analysis and sends message reminders.

8. The investment decision-making analysis system for power plant construction projects based on power big data according to claim 6, wherein: Export the data saved in the economic evaluation database obtained through the economic evaluation subsystem, and conduct in-depth analysis by combining the information of the already commissioned generator sets, generator sets under construction, regional new energy consumption level, regional electricity demand level, photovoltaic resource data, regional power grid capacity, and regional wind resource capacity data saved in the economic evaluation database using the benchmarking and competitiveness analysis tool and the energy and policy research tool.

9. The investment decision-making analysis system for power plant construction projects based on power big data according to claim 2, wherein: The visual decision support makes benchmarking decisions on the indicators and parameters in the project based on the analysis results of the competitiveness map subsystem, compares the analysis results with the industry average level and leading level, and generates a decision analysis report accordingly.

10. The investment decision-making analysis system for power plant construction projects based on power big data according to claim 2, characterized in that: The economic evaluation database includes industry numerical control, competitor data, economic indicator library, policy data, and regional data.

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