Green light and green certificate scene analysis method and device based on big data technology, medium and product

Abstract

The invention provides a green light and green certificate scene analysis method and device based on a big data technology, a medium and a product. The method comprises the following steps: obtaining green light and green certificate service data from an original service system; and processing the green-light green-certificate service data: directly storing the green-light green-certificate service data through a source pasting layer, constructing and storing a wide table and a star model according to a dimension modeling mode based on the data of the source pasting layer through a detail layer, and performing unit summarization and storage according to an index modeling mode based on the data of the detail layer through a summarization layer, forming corresponding index data according to the set business scene through the mart layer based on the data of the summary layer, and storing the index data; obtaining a green light and green evidence analysis instruction; and in combination with the data of the market layer, responding to the green light and green evidence analysis instruction, and displaying an analysis result through a visual interface. According to the method, the green light and green certificate service data are integrated, the visual analysis result is given according to different green light and green certificate analysis instructions, and the effect and efficiency of green light and green certificate service data analysis are improved.

Description

Technical Field

[0001] This invention relates to the field of green electricity and green certificate analysis technology, specifically to a method, device, medium, and product for green electricity and green certificate scenario analysis based on big data technology. Background Technology

[0002] Green electricity, or green power, refers to electricity produced through renewable energy technologies. A green certificate, or green electricity certificate, is the sole proof of the environmental attributes of renewable energy electricity in China. It serves as proof of consuming green electricity and supporting its development. Each certificate has a unique code; only by obtaining a green certificate can power generation companies and electricity users prove that they generate and use green electricity.

[0003] In power grid companies, renewable energy development plays a crucial role. However, with the government's promotion of green electricity and green certificates, the continuous expansion of enterprise scale, and the increasing complexity of business, the analysis of green certificates has become increasingly difficult. For example, the data on green electricity and green certificates is scattered, has inconsistent formats, and is difficult to integrate; the analysis of green electricity and green certificates is not intuitive enough.

[0004] An existing carbon emission monitoring and management system collects carbon emission data, processes and analyzes it, and then visualizes the carbon emission data. However, this approach collects data from various business databases, such as the national statistical yearbook database for prefecture-level cities and the national enterprise pollution discharge database. Without further processing of the business data, it is difficult to directly support data-driven decision-making and apply it directly to the analysis of green electricity and green certificates. Summary of the Invention

[0005] The primary objective of this invention is to provide a method for analyzing green electricity and green certificates based on big data technology, which can provide multi-dimensional visualization analysis of green electricity and green certificate scenarios and improve the management level of green electricity and green certificates.

[0006] The second objective of this invention is to provide a computer device for implementing the above-mentioned green electricity and green certificate scenario analysis method based on big data technology.

[0007] A third objective of this invention is to provide a computer-readable storage medium for implementing the above-mentioned green electricity and green certificate scenario analysis method based on big data technology.

[0008] The fourth objective of this invention is to provide a computer program product that implements the above-mentioned green electricity and green certificate scenario analysis method based on big data technology.

[0009] To achieve the aforementioned primary objective, this invention provides a method for analyzing green electricity and green certificates based on big data technology, comprising the following steps: obtaining green electricity and green certificate business data from the original business system; processing the green electricity and green certificate business data, including: directly storing the green electricity and green certificate business data through the source layer; constructing and storing wide tables and star schemas based on the source layer data using a dimensional modeling approach through the detail layer; performing unit aggregation and storing based on the detail layer data using an indicator modeling approach through the summary layer; forming and storing corresponding indicator data based on the summary layer data according to the set business scenarios through the marketplace layer; obtaining green electricity and green certificate analysis instructions; responding to the green electricity and green certificate analysis instructions using the data from the marketplace layer; and displaying the analysis results through a visual interface.

[0010] As can be seen from the above scheme, this invention processes green electricity and green certificate business data by setting up a source layer, a detail layer, a summary layer, and a marketplace layer. It integrates green electricity and green certificate business data and forms corresponding indicator data according to business scenarios. After obtaining green electricity and green certificate analysis instructions, it provides visualized analysis results based on the stored indicator data, improving the effectiveness and efficiency of green electricity and green certificate business data analysis. This invention obtains various green electricity and green certificate analysis instructions and displays them in the form of indicators, maps, and various charts, enabling visualized analysis of green electricity and green certificates from multiple dimensions, such as units and time, for trend analysis and distribution. This meets the needs of full-level and security management of green electricity and green certificates, effectively improving the lean management level of green electricity and green certificates.

[0011] A further proposed solution is that the green electricity and green certificate analysis instructions include a first green electricity key indicator analysis instruction and a second green electricity key indicator analysis instruction. The first green electricity key indicator analysis instruction is used to obtain the analysis results of the green electricity key indicators corresponding to all units under the first-level region; the second green electricity key indicator analysis instruction is used to obtain the analysis results of the green electricity key indicators corresponding to all units under the second-level region, where the first-level region includes the second-level region.

[0012] This demonstrates that maps can be used to perform layer-by-layer analysis of data at lower levels, while key indicators can be linked to the map for intuitive data visualization. This allows businesses to visually represent the spatial distribution of data, deeply explore the information behind data at each level, and provide comprehensive and accurate geospatial data support for business decision-making.

[0013] A further proposal is that key indicators for green electricity should include at least one of the following types of data: average transaction price of green electricity, cumulative transaction volume of green electricity, cumulative premium income of green electricity, number of green certificates held with subsidies, average transaction price of green certificates, cumulative transaction volume of green certificates, cumulative transaction income of green certificates, and number of green certificates held that will mature within 3 months.

[0014] A further proposal is that the green electricity and green certificate analysis instructions include green electricity trading trend analysis instructions; the green electricity and green certificate analysis instructions include green certificate trading trend analysis instructions.

[0015] This demonstrates that the system can present the price fluctuations, transaction volume, and profitability of the green electricity market in an intuitive and easy-to-understand way, providing a basis for market participants to make decisions.

[0016] A further proposal is that the green electricity and green certificate analysis instructions include instructions for analyzing the distribution of energy types in green electricity trading; the green electricity and green certificate analysis instructions include instructions for analyzing the distribution of energy types in green certificate trading.

[0017] Therefore, analyzing the energy type distribution in green electricity trading can clearly present the trading prices and overall financing cost rates of different green energy sources. This helps policymakers optimize the energy structure, investors identify the right direction, and enterprises adjust their procurement strategies, jointly promoting the healthy development of the green electricity market. Analyzing the trading volume and premium returns of green certificate trading based on energy type distribution provides a clear understanding of the performance of different energy types in the green certificate market, offering a direct view of the market share and profitability of each energy type. This helps investors accurately grasp investment directions, assists enterprises in optimizing energy procurement strategies, and provides strong data support for government departments to formulate scientific and reasonable energy policies, promoting the healthy and orderly development of the green certificate market and the renewable energy industry.

[0018] A further proposal is that the green electricity and green certificate analysis instructions include instructions for analyzing the distribution of energy types held in green certificates, and instructions for analyzing the distribution of the remaining term of green certificates held in green certificates.

[0019] Therefore, analyzing the number and proportion of subsidized green certificates held by each energy type in the distribution of green energy holdings provides data support, intuitively demonstrating the scale differences of different green energy sources under subsidy support. This helps energy companies understand the development trends of each energy type, optimize investment and operation strategies, and provides government departments with information for adjusting subsidy policies, rationally allocating resources, and promoting the balanced and efficient development of the green energy industry. Analyzing the number and proportion of subsidized green certificates with different remaining maturities provides intuitive data for energy companies to rationally allocate funds and production plans, for government departments to optimize subsidy policies, and for investors to assess investment risks and returns.

[0020] A further approach is to verify the data at the aggregation layer and the marketplace layer based on the green electricity and green certificate business data before obtaining the green electricity and green certificate analysis instructions.

[0021] This demonstrates that it can improve data accuracy.

[0022] To achieve the second objective mentioned above, the present invention provides a computer device, including a processor and a memory, wherein: the memory stores a computer program, and when the computer program is executed by the processor, it implements the above-mentioned green electricity and green certificate scenario analysis method based on big data technology.

[0023] To achieve the third objective mentioned above, the present invention provides a computer-readable storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the aforementioned green electricity and green certificate scenario analysis method based on big data technology.

[0024] To achieve the fourth objective mentioned above, the present invention provides a computer program product, including computer instructions, wherein: when the computer instructions are executed by a processor, they implement the above-mentioned green electricity and green certificate scenario analysis method based on big data technology. Attached Figure Description

[0025] Figure 1 This is a system framework diagram of the green electricity and green certificate system based on big data technology in the embodiment of the green electricity and green certificate scenario analysis method based on big data technology of the present invention.

[0026] Figure 2 This is a flowchart of an embodiment of the green electricity and green certificate scenario analysis method based on big data technology of the present invention.

[0027] Figure 3 This is the visualization interface corresponding to the first green electricity key indicator analysis command in the embodiment of the green electricity and green certificate scenario analysis method based on big data technology of the present invention.

[0028] Figure 4 This is the visualization interface corresponding to the second key green electricity indicator analysis command in the embodiment of the green electricity and green certificate scenario analysis method based on big data technology of the present invention.

[0029] Figure 5 This is the visualization interface corresponding to the green electricity transaction trend analysis command in the embodiment of the green electricity and green certificate scenario analysis method based on big data technology of the present invention.

[0030] Figure 6 This is a visualization interface corresponding to the distribution instructions for green electricity trading energy types in the embodiments of the green electricity and green certificate scenario analysis method based on big data technology of the present invention.

[0031] Figure 7 This is the visualization interface corresponding to the green certificate trading trend analysis instruction in the embodiment of the green electricity and green certificate scenario analysis method based on big data technology of the present invention.

[0032] Figure 8 This is the visualization interface corresponding to the green certificate trading energy type distribution analysis instruction in the embodiment of the green electricity and green certificate scenario analysis method based on big data technology of the present invention.

[0033] Figure 9 This is the visualization interface corresponding to the command for analyzing the distribution of energy types holding green certificates in the embodiment of the green electricity and green certificate scenario analysis method based on big data technology of the present invention.

[0034] Figure 10 This is the visualization interface corresponding to the instruction for analyzing the distribution of remaining green certificate terms in the green electricity and green certificate scenario analysis method embodiment based on big data technology of the present invention.

[0035] The present invention will be further described below with reference to the accompanying drawings and embodiments. Detailed Implementation

[0036] Example of a method for analyzing green electricity and green certificate scenarios based on big data technology: See Figure 1 The green electricity and green certificate system based on big data technology in this embodiment includes a data warehouse layering module 11, a data link setting module 12, and a visualization module 13.

[0037] The data warehouse layering module 11 is used to obtain green electricity and green certificate business data from the original business system in real time, and to process and store the green electricity and green certificate business data. Specifically, it includes the source layer (ODS), detail layer (DWD), summary layer (TWC), and marketplace layer (DM).

[0038] The source layer is used to store green electricity and green certificate business data obtained from the original business system and retain the original structure of the green electricity and green certificate business data, thereby providing a unified data source for the detail layer and avoiding impact on the original business system, while facilitating problem backtracking.

[0039] The data for green electricity and green certificates includes project information tables, project subsidy information tables, and special financing information tables collected from the reporting details table.

[0040] The report detail table is the underlying data table used to generate reports in the original business system. It typically contains complete records of business operations, such as full project information, subsidy disbursement details, and financing contract details. The project information table can originate from the project management module of the original business system, recording all project attributes, such as project ID, project name, project initiation time, affiliated unit, energy type, and other fields and their contents. The project subsidy information table can originate from the financial management module of the original business system, recording project subsidy details, such as subsidy amount and disbursement time, and other fields and their contents. The special financing information table originates from the financing management module of the original business system, recording project financing details, such as financing cost and loan disbursement time, and other fields and their contents.

[0041] Optionally, the original business system can be the financial control system of each company within the group.

[0042] The detail layer is used to construct and store wide tables and star schemas based on the data from the source layer using dimensional modeling. The detail layer employs dimensional modeling to create wide tables and star schemas for project scale, project subsidies, and special financing. Specifically, the detail layer cleanses and standardizes the data from the source layer, resolving issues such as duplication and inconsistent formats. Then, it establishes wide tables and star schemas for project scale, project subsidies, and special financing, respectively. The star schema consists of fact tables and dimension tables, providing a flexible foundation for multidimensional analysis. The wide tables integrate fields from the fact and dimension tables, reducing multi-table joins during queries.

[0043] For example, the fact table fields of the star schema corresponding to project subsidies may include subsidy ID, project ID, subsidy amount, disbursement time, etc., while the dimension table may include fields such as the name of the green energy type for the subsidy. The wide table fields corresponding to special financing may include project ID, project name, affiliated unit name, unit level, financing type, financing cost, green energy type, etc.

[0044] The summary layer aggregates and stores data from the detail layer according to unit dimension. The summarized unit data at each level can be used to meet the need to display data from all units across all levels. For example, the granularity of the summarized units can cover multiple levels such as headquarters, provincial companies, and municipal companies.

[0045] The marketplace layer, based on the data from the aggregation layer, generates and stores corresponding indicator data according to the set business scenarios, thus providing indicator results data directly for front-end display. For example, if the business scenario is set as the annual average transaction price of green certificates, the marketplace layer will calculate the average annual transaction price of green certificates for all units in the current year based on the data from the aggregation layer. Alternatively, if the business scenario is the annual average transaction price of green certificates in a specific prefecture-level city, the marketplace layer will calculate the average annual transaction price of green certificates for all units within that prefecture-level city based on the data from the aggregation layer, and then calculate the average annual transaction price of green certificates for that prefecture-level city.

[0046] The data link setting module 12 ensures timely and accurate daily data updates. It designs a complete data link dependency relationship and configures reasonable scheduling tasks. The link order is set as source layer → detail layer → summary layer → marketplace layer. The scheduling strategy is to set dependencies for tasks at each layer, and trigger the next layer after the previous layer is completed. It also sets a reasonable running window (e.g., triggering the update in the early morning to avoid affecting online business).

[0047] The visualization module 15 visualizes the key green energy indicators required based on the data from the marketplace layer, specifically in the form of indicator cards.

[0048] In addition, data from green electricity and green certificates can be used to verify the data at the aggregation and marketplace layers, thereby promptly identifying any potential errors in the data at the aggregation and marketplace layers.

[0049] Therefore, the green electricity and green certificate scenario analysis system based on big data technology described above can be used to analyze different green electricity and green certificate scenarios. The following section will combine... Figure 2 The specific steps are explained in detail.

[0050] First, step S1 is executed to obtain green electricity and green certificate business data from the original business system in real time and process the data. Specifically, the data is processed through the aforementioned source layer, detail layer, summary layer, and marketplace layer, forming indicator data which is stored in the marketplace layer.

[0051] Then, step S2 is executed to obtain the first green energy key indicator analysis instruction and display the visualization interface corresponding to the first green energy key indicator analysis instruction.

[0052] The first green energy key indicator analysis command is used to obtain the analysis results of green energy key indicators for all units within a first-level region. In this embodiment, the first-level region is a provincial-level region, and the first green energy key indicator analysis command obtains the analysis results of green energy key indicators for all units within a specific provincial-level region. See also... Figure 3 The first key indicator analysis command for green energy is to obtain the analysis results of the key indicators for green energy of all units under the Guangxi Zhuang Autonomous Region. The system uses... Figure 3 The visualization interface displays the analysis results. At the top of the visualization interface, the overall key green energy indicators and their corresponding specific data for all units under the Guangxi Zhuang Autonomous Region are displayed.

[0053] See also Figure 3 In the map, number 101 displays a map showing multiple provincial and autonomous region levels, specifically including Yunnan, Guizhou, Guangxi, Guangdong, and Hainan. The method for obtaining the first key green energy indicator analysis command can be by retrieving the location clicked on the map. For example, if a user clicks on the location of Guangdong Province on the map corresponding to number 101, the system will confirm receipt of a first key green energy indicator analysis command. This command is used to obtain the analysis results of the overall key green energy indicators for all units under Guangdong Province.

[0054] Key indicators for green electricity include at least one of the following: average green electricity trading price, cumulative green electricity trading volume, cumulative green electricity premium gain, number of green certificate holding subsidies, average green certificate trading price, cumulative green certificate trading volume, cumulative green certificate trading profit, and number of green certificates maturing within 3 months. Some key indicators for green electricity can be displayed according to a set time span, such as by year or by month, or by year or by reading to display the cumulative green certificate trading volume.

[0055] Then, step S3 is executed to obtain the second key indicator analysis command for green electricity and display the visualization interface corresponding to the second key indicator analysis command for green electricity.

[0056] The second green energy key indicator analysis command is used to obtain the analysis results of green energy key indicators for all units under the secondary region. The primary region contains the secondary region. In this embodiment, the primary region is the provincial-level region, and the secondary region is a prefecture-level city region under the provincial-level region.

[0057] See also Figure 4 , Figure 4 The label 201 in the image represents a map of Guangdong Province, showing the locations of various prefecture-level cities. The second key indicator analysis command for green electricity in this embodiment is to obtain the annual average transaction price for all units under Guangzhou City. The corresponding visualization interface displays the overall annual average transaction price for all units under Guangzhou City and its specific data, namely 34.56 fen / kWh.

[0058] In addition, the system supports map penetration to display data of lower-level units, which can be achieved directly by double-clicking. For example, in... Figure 3 By clicking on the location of Guangzhou on the map, the system receives a second key indicator analysis command for green electricity. This command retrieves the annual average transaction price of all units within Guangzhou, and the system then provides the corresponding data. Figure 4 A visual interface.

[0059] Optionally, a third key indicator analysis command can also be obtained, which is used to obtain the analysis results of green energy key indicators corresponding to a specified unit.

[0060] Then, execute step S4 to obtain the green electricity trading trend analysis instruction and display the corresponding visualization interface of the green electricity trading trend analysis instruction.

[0061] The Green Electricity Trading Trend Analysis command is used to obtain the analysis results of green electricity trading trends. Specifically, it can obtain the green electricity trading trends of all units in a specified region, or it can obtain the green electricity trading trends of a specific unit. Green electricity trading trends can be trading trends of trading price, trading volume, and premium gains, and are displayed according to a yearly or monthly time dimension.

[0062] The analysis results of green electricity trading trends are displayed through a visual interface. In this embodiment, see... Figure 5 This allows for the display of green electricity transactions from annual / monthly average transaction prices, transaction volumes, and premium returns in a trend chart format. This provides an intuitive and easy-to-understand representation of price fluctuations, transaction scale, and profitability in the green electricity market, offering decision-making support for market participants.

[0063] Then, execute step S5 to obtain the green electricity trading energy type distribution analysis instruction and display the corresponding visualization interface for the green electricity trading energy type distribution instruction.

[0064] The Green Electricity Trading Energy Type Distribution Analysis command is used to obtain the analysis results of the energy type distribution in green electricity trading. This analysis clearly presents the trading prices and overall financing cost rates of different green electricity sources, helping policymakers optimize the energy structure, investors identify the right direction, and enterprises adjust their procurement strategies, thus jointly promoting the healthy development of the green electricity market.

[0065] The analysis results of the energy type distribution in green electricity trading are displayed through a visualization interface. In this embodiment, see [link to documentation]. Figure 6 The distribution analysis of energy types for green electricity trading is presented in a bar chart, which specifically shows the annual average transaction price and comprehensive financing cost rate for each energy type.

[0066] Then, execute step S6 to obtain the green certificate trading trend analysis instruction and display the corresponding visualization interface of the green certificate trading trend analysis instruction.

[0067] The Green Certificate Trading Trend Analysis command is used to obtain the analysis results of green certificate trading trends. Green certificate trading trends can analyze average trading prices, trading volumes, and premium gains within a set time range and display them as trend charts. This provides an intuitive and easy-to-understand representation of price fluctuations, trading volume, and profitability in the green certificate market, offering decision-making support for market participants.

[0068] The analysis results of green certificate trading trends are displayed through a visual interface. In this embodiment, see [link to documentation]. Figure 7 The analysis of green certificate trading trends examines the trading price, trading volume, and premium gains for each year and month, specifically showing the changes in the average annual trading price over the past five years.

[0069] Then, execute step S7 to obtain the green certificate trading energy type distribution analysis instruction and display the corresponding visualization interface of the green certificate trading energy type distribution analysis instruction.

[0070] The Green Certificate Trading Energy Type Distribution Analysis command is used to obtain the analysis results of the energy type distribution in green certificate trading. Analyzing the trading volume and premium returns of different energy types in the green certificate market provides a clear understanding of their performance, market share, and profitability. This helps investors accurately grasp investment directions, assists companies in optimizing their energy procurement strategies, and provides strong data support for government departments to formulate scientific and reasonable energy policies, thus promoting the healthy and orderly development of the green certificate market and the renewable energy industry.

[0071] The analysis results of the energy type distribution in green certificate trading are displayed through a visualization interface. In this embodiment, see... Figure 8 The pie chart displays the trading volume and percentage of green certificates corresponding to each energy type.

[0072] Then, step S8 is executed to obtain the green certificate energy type distribution analysis instruction and display the corresponding visualization interface.

[0073] The command to analyze the distribution of green certificate holdings by energy type is used to obtain the analysis results. The analysis primarily focuses on the number and proportion of subsidized holdings of each energy type within the green energy holding distribution. This provides a clear picture of the scale differences in different green energy sources under subsidy support, helping energy companies understand the development trends of various energy sources and optimize investment and operational strategies. It also provides data support for government departments to adjust subsidy policies, rationally allocate resources, and promote the balanced and efficient development of the green energy industry. Furthermore, it helps investors accurately grasp investment directions, mitigate risks, and increase returns.

[0074] The analysis results of the distribution of energy types held by green certificate holders are displayed through a visualization interface. In this embodiment, see [link to example]. Figure 9 The distribution of energy types holding green certificates can be clearly shown through bar charts, which can clearly present the number and proportion of subsidies for different green energy types.

[0075] Then, execute step S9 to obtain the green certificate remaining term distribution analysis instruction and display the corresponding visualization interface of the green certificate remaining term distribution analysis instruction.

[0076] The command to analyze the remaining maturity distribution of green certificates held is used to obtain the analysis results of the remaining maturity distribution of green certificates held. The analysis of the remaining maturity distribution of green certificates held mainly analyzes the number and proportion of subsidized green certificates with different remaining maturities, which can provide intuitive data basis for energy companies to rationally allocate funds and production plans, government departments to optimize subsidy policies, and investors to assess investment risks and returns.

[0077] The analysis results of the distribution of remaining green certificate terms are displayed through a visualization interface. In this embodiment, see [link to documentation]. Figure 10 The pie chart displays the distribution of remaining green certificates, which helps companies clearly understand the distribution of the number of green certificates with different remaining terms, providing a strong basis for green certificate trading decisions, revenue forecasting and related business planning.

[0078] In summary, this invention integrates green electricity and green certificate business data, providing visualized analysis results based on different green electricity and green certificate analysis commands, thereby improving the effectiveness and efficiency of green electricity and green certificate business data analysis. By acquiring various green electricity and green certificate analysis commands and displaying them in the form of indicators, maps, and various charts, this invention enables visualized analysis of green electricity and green certificates across multiple dimensions, such as units and time periods, focusing on trend analysis and distribution. This meets the needs of comprehensive and secure management of green electricity and green certificates, effectively improving the level of lean management of green electricity and green certificates.

[0079] Computer device embodiment: The computer device in this embodiment includes a processor and a memory. The memory stores a computer program, and when the processor executes the computer program, it implements the above-described embodiment of the green electricity and green certificate scenario analysis method based on big data technology.

[0080] A computer device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that a computer device may include more or fewer components, or a combination of certain components, or different components; for example, a computer device may also include input / output devices, network access devices, buses, etc.

[0081] For example, a processor can be a Central Processing Unit (CPU), or 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. A general-purpose processor can be a microcontroller or any conventional processor. The processor is the control center of a computer device, connecting all parts of the computer device through various interfaces and lines.

[0082] The memory can be used to store computer programs and / or modules. The controller implements various functions of the computer device by running or executing the computer programs and / or modules stored in the memory, and by accessing data stored in the memory. For example, the memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (e.g., sound receiving function, sound-to-text function, etc.), etc.; the data storage area may store data created based on the use of the mobile phone (e.g., audio data, text data, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0083] Examples of computer-readable storage media: If the modules integrated into the computer device in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes of the embodiments of the green electricity and green certificate scenario analysis method based on big data technology can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a controller, it can implement the steps of the above embodiments of the green electricity and green certificate scenario analysis method based on big data technology. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The storage medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content contained in computer-readable media may be appropriately added to or subtracted from the requirements of legislation and patent practice in a jurisdiction. For example, in some jurisdictions, computer-readable media may not include electrical carrier signals and telecommunication signals, in accordance with legislation and patent practice.

[0084] Example of a computer program product: The computer program product of this embodiment includes computer instructions stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the various steps of the above-described embodiment of the green electricity and green certificate scenario analysis method based on big data technology.

[0085] Finally, it should be emphasized that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for analyzing green electricity and green certificate scenarios based on big data technology, characterized in that, Includes the following steps: Obtain green electricity and green certificate business data from the original business system; The green electricity and green certificate business data is processed as follows: the green electricity and green certificate business data is directly stored through the source layer; the detailed layer constructs and stores a wide table and a star schema based on the data of the source layer according to the dimensional modeling method; the summary layer performs unit summary and stores based on the data of the detailed layer according to the indicator modeling method; and the marketplace layer forms and stores corresponding indicator data based on the data of the summary layer according to the set business scenarios. Obtain green electricity and green certificate analysis instructions; The system combines the data from the marketplace layer to respond to the green electricity and green certificate analysis commands and displays the analysis results in a visual interface.

2. The green electricity and green certificate scenario analysis method based on big data technology as described in claim 1, characterized in that: The green electricity and green certificate analysis instructions include a first green electricity key indicator analysis instruction and a second green electricity key indicator analysis instruction. The first green electricity key indicator analysis instruction is used to obtain the analysis results of the green electricity key indicators corresponding to all units under the first-level region. The second green electricity key indicator analysis instruction is used to obtain the analysis results of the green electricity key indicators corresponding to all units under the second-level region. The first-level region includes the second-level region.

3. The green electricity and green certificate scenario analysis method based on big data technology as described in claim 2, characterized in that: The key indicators for green electricity include at least one of the following types of data: average transaction price of green electricity, cumulative transaction volume of green electricity, cumulative premium income of green electricity, number of green certificate holding subsidies, average transaction price of green certificates, cumulative transaction volume of green certificates, cumulative transaction income of green certificates, and number of green certificates held for maturity within 3 months.

4. The green electricity and green certificate scenario analysis method based on big data technology as described in claim 1, characterized in that: The green electricity and green certificate analysis instructions include green electricity transaction trend analysis instructions; The green electricity and green certificate analysis instructions include green certificate trading trend analysis instructions.

5. The green electricity and green certificate scenario analysis method based on big data technology as described in claim 1, characterized in that: The green electricity and green certificate analysis instructions include instructions for analyzing the distribution of energy types in green electricity transactions. The green electricity and green certificate analysis instructions include instructions for analyzing the distribution of energy types in green certificate trading.

6. The green electricity and green certificate scenario analysis method based on big data technology as described in claim 1, characterized in that: The green electricity and green certificate analysis instructions include instructions for analyzing the distribution of energy types held by green certificate holders. The green electricity and green certificate analysis instructions include instructions for analyzing the distribution of remaining terms of held green certificates.

7. The method for analyzing green electricity and green certificates based on big data technology as described in any one of claims 1 to 6, characterized in that: Before obtaining the green electricity and green certificate analysis instruction, the data of the summary layer and the marketplace layer are checked based on the green electricity and green certificate business data.

8. A computer device comprising a processor and a memory, characterized in that: The memory stores a computer program, which, when executed by the processor, implements the green electricity and green certificate scenario analysis method based on big data technology as described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the green electricity and green certificate scenario analysis method based on big data technology as described in any one of claims 1 to 7.

10. A computer program product comprising computer instructions, characterized in that: When the computer instructions are executed by the processor, they implement the green electricity and green certificate scenario analysis method based on big data technology as described in any one of claims 1 to 7.

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