Management system for energy conservation and emission reduction planning based on big data prediction

Abstract

The invention relates to the technical field of energy conservation and emission reduction, in particular to an energy conservation and emission reduction plan management system based on big data prediction. The system comprises an enterprise carbon emission prediction unit, the output end of the enterprise carbon emission prediction unit is connected with an adaptive enterprise determination unit, the output end of the adaptive enterprise determination unit is connected with a conversion cooperation analysis unit, and the output end of the conversion cooperation analysis unit is connected with a regional carbon emission distribution unit. On the basis of carbon emission transactions and enterprise cooperation transactions, it is determined that carbon emission transactions can be met among multiple enterprises, and understanding and cognizing channels are established among the enterprises by achieving the carbon emission transactions among the enterprises, so that the transaction cooperation probability among the enterprises is increased, and transaction cooperation among the enterprises is promoted.

Description

Technical Field

[0001] This invention relates to the field of energy conservation and emission reduction technology, and more specifically, to a management system for energy conservation and emission reduction plans based on big data prediction. Background Technology

[0002] Energy conservation and emission reduction refer to saving material and energy resources and reducing the emission of waste and harmful substances (including solid waste, waste gas, solid waste, and noise); in a narrow sense, energy conservation and emission reduction refer to saving energy and reducing the emission of harmful substances.

[0003] Regarding carbon dioxide emissions (hereinafter referred to as carbon emissions), the current system allocates corresponding carbon emission quotas to enterprises, enabling them to conduct carbon emissions. However, for enterprises, output and carbon emissions are linked; that is, carbon emissions are affected by the enterprise's output. When some enterprises' output is lower or higher than their carbon emissions at a certain time, they can sell or buy corresponding carbon emission quotas from other enterprises to ensure normal production. However, currently, there are no restrictions on the enterprises that enterprises can choose to sell or buy carbon emission quotas from. In other words, it is not possible to find enterprises that are compatible with their own enterprises in the carbon emission trading sector, such as the relationship between manufacturers and raw material suppliers. Therefore, although enterprises currently meet the carbon emission trading requirements, they cannot expand their subsequent revenue benefits because there is no cooperation involved. Thus, it is impossible to improve the carbon emissions of their own enterprises or achieve the planned allocation of carbon emissions among different enterprises through inter-enterprise cooperation. Summary of the Invention

[0004] The purpose of this invention is to provide a management system for energy conservation and emission reduction plans based on big data prediction, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention aims to provide a management system for energy conservation and emission reduction plans based on big data prediction, including an enterprise carbon emission prediction unit. This unit acquires information on the enterprise's business operations and output, predicts the enterprise's carbon emissions based on the output, and designates the enterprise's business operations and carbon emissions as reference enterprise targets. The output of the enterprise carbon emission prediction unit is connected to a matching enterprise determination unit. This unit screens other enterprises that can trade with the reference enterprise targets, designates these other enterprises as trading enterprise targets, and recommends carbon emission trading between the reference enterprise targets and the trading enterprise targets. The output of the matching enterprise determination unit is connected to a conversion and cooperation analysis unit. This unit analyzes the overall trading situation between the reference enterprise targets and the trading enterprise targets. The output of the conversion and cooperation analysis unit is connected to a regional carbon emission allocation unit. This unit determines the growth of enterprise carbon emissions based on the overall trading situation and redistributes the carbon emissions of enterprises in the region.

[0006] As a further improvement to this technical solution, the enterprise carbon emission prediction unit includes an enterprise output data acquisition module. The enterprise output data acquisition module is used to acquire the enterprise's business project information and the estimated output data of the project. The output end of the enterprise output data acquisition module is connected to an enterprise carbon emission analysis module. The enterprise carbon emission analysis module is used to predict the amount of carbon emissions that the enterprise will generate when it completes the project output based on the enterprise's business project information and the estimated output data of the project, and to record the business project information and carbon emissions as the reference enterprise target.

[0007] As a further improvement to this technical solution, the matching enterprise determination unit includes a trading enterprise screening and positioning module. The trading enterprise screening and positioning module is used to receive reference enterprise target information from the enterprise carbon emission analysis module. The trading enterprise screening and positioning module screens other enterprises that can realize carbon emission trading and have cooperation plans with the enterprises in the reference enterprise target based on the reference enterprise target information. The other enterprises after screening are recorded as trading enterprise targets, and the trading enterprise targets are recommended to trade with the reference enterprise targets.

[0008] As a further improvement to this technical solution, the matching enterprise determination unit includes a predetermined target enterprise reservation module. The predetermined target enterprise reservation module is used to set the predetermined other enterprises as predetermined transaction targets when there are predetermined other enterprise choices among the enterprises in the reference enterprise targets. And the predetermined transaction targets here are different from the transaction enterprise targets determined by the reference enterprise targets mentioned above.

[0009] As a further improvement to this technical solution, the conversion cooperation analysis unit includes a carbon emission trading overview analysis module. This module is used to obtain carbon emission trading information between the aforementioned trading enterprise target and the reference enterprise target, and to analyze whether there is any cooperation between the trading enterprise target and the reference enterprise target other than carbon emission trading. The output of the carbon emission trading overview analysis module is connected to a two-way conversion cooperation analysis module. This module is used to analyze the project output of the trading enterprise target and the reference enterprise target themselves when it is determined, based on the analysis overview of the trading enterprise target and the reference enterprise target by the carbon emission trading overview analysis module, that there is any cooperation between the trading enterprise target and the reference enterprise target other than carbon emission trading.

[0010] As a further improvement to this technical solution, the regional carbon emission allocation unit includes a carbon emission growth rate summarization module. This module is used to obtain the carbon emissions of the trading enterprise target and the reference enterprise target caused by changes in their own project output after other trading cooperation, and to estimate the growth rate corresponding to the carbon emission amount. The carbon emission growth rate summarization module also identifies and summarizes some enterprises with the same carbon emission growth rate.

[0011] As a further improvement to this technical solution, the output end of the carbon emission growth rate summarization module is connected to a regional carbon emission allocation improvement module. The regional carbon emission allocation improvement module is used to obtain the locations of enterprises with the same carbon emission growth rate summarized by the carbon emission growth rate summarization module, determine the region where the enterprise is located by the location, and redistribute the carbon emissions of enterprises with low project output and excessively high carbon emission allocation in the region with the carbon emissions of enterprises with current emission growth.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. In this big data-based energy conservation and emission reduction plan management system, carbon emission trading and enterprise cooperation transactions are used as the basis to determine whether multiple enterprises can meet the carbon emission trading requirements. Furthermore, the carbon emission trading between enterprises establishes a channel for understanding and awareness among them, increases the probability of transaction cooperation between enterprises, and promotes transaction cooperation between enterprises.

[0013] 2. In this big data-based energy conservation and emission reduction planning management system, the changes in project output of each enterprise are determined through cooperation in project transactions among multiple enterprises. The growth rate of carbon emissions of enterprises is determined by the changes in project output. Enterprises with the same growth rate of carbon emissions are grouped together, and the corresponding geographical regions of the enterprises are determined. The carbon emissions of enterprises in the region are then redistributed to achieve the optimal allocation and management of carbon emissions in the region. Attached Figure Description

[0014] Fig. 1 This is an overall module block diagram of the present invention; Fig. 2 This is a block diagram of the trading enterprise screening and positioning module and the carbon emission trading overview analysis module of the present invention.

[0015] The meanings of the labels in the diagram are as follows: 1. Enterprise carbon emission prediction unit; 11. Enterprise production data acquisition module; 12. Enterprise carbon emission analysis module; 2. Matching enterprise identification unit; 21. Transaction enterprise screening and positioning module; 22. Pre-defined target enterprise reservation module; 3. Conversion and Cooperation Analysis Unit; 31. Carbon Emission Trading Overview Analysis Module; 32. Two-Way Conversion and Cooperation Analysis Module; 4. Regional carbon emission allocation unit; 41. Carbon emission growth rate summary module; 42. Regional carbon emission allocation improvement module. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1 Please see Figs. 1-2 As shown, this embodiment provides a management system for energy conservation and emission reduction plans based on big data prediction, including an enterprise carbon emission prediction unit 1. This unit 1 is used to acquire the enterprise's business projects and output information, predict the enterprise's carbon emissions based on the output information, and record the enterprise's business projects and carbon emissions as the reference enterprise target. In this solution, the enterprise carbon emission prediction unit 1 acquires the enterprise's business projects and estimated output information, and then predicts how much carbon emissions the enterprise will generate in the current month based on the enterprise's estimated output information. When the enterprise's carbon emissions exceed the carbon emission quota allocated by the state, it means that the enterprise needs to purchase the corresponding carbon emission quota, that is, to engage in carbon emission trading. Enterprises ensure that their carbon emission situation is not affected by completing carbon emission trading, thus enabling continuous production operations. This solution makes the following improvements to the current carbon emission trading between enterprises: The output of Enterprise Carbon Emission Prediction Unit 1 is connected to Matching Enterprise Determination Unit 2. Matching Enterprise Determination Unit 2 is used to screen other enterprises that can trade with the enterprises in the reference enterprise targets, and to designate these other enterprises as trading enterprise targets. It recommends carbon emission trading between the reference enterprise targets and the trading enterprise targets. The output of Matching Enterprise Determination Unit 2 is connected to Conversion and Cooperation Analysis Unit 3. Conversion and Cooperation Analysis Unit 3 is used to analyze the overall trading situation between the reference enterprise targets and the trading enterprise targets. The output of Conversion and Cooperation Analysis Unit 3 is connected to Regional Carbon Emission Allocation Unit 4. Regional Carbon Emission Allocation Unit 4 determines the carbon emission growth of enterprises based on the overall trading situation and redistributes the carbon emissions of enterprises in the region. This is achieved by combining the business projects of the aforementioned enterprises with the estimated... Carbon emission data is recorded as reference enterprise targets. Matching enterprise determination unit 2 uses the data in the reference enterprise targets to identify other enterprises that trade with the enterprises in the reference enterprise targets. These other enterprises are recorded as trading enterprise targets. In other words, by finding other enterprises that have a high probability of cooperating and trading with the enterprises in the reference enterprise targets and can realize carbon emission trading, a basic carbon emission trading can be realized between the reference enterprise targets and the trading enterprise targets. This ensures that the carbon emissions of each enterprise are not affected. Furthermore, based on the realization of carbon emission trading, multiple enterprises can understand and recognize each other through carbon emission trading. This can greatly promote the probability of product and project trading and cooperation among multiple enterprises, achieve mutual benefit among multiple enterprises, and thus improve the output and economic benefits of enterprises.

[0018] Specifically, the transformation and cooperation analysis unit 3 analyzes whether there are other transactional collaborations between the reference enterprise's target and the transaction enterprise's target. When other transactional collaborations are conducted between the reference enterprise's target and the transaction enterprise's target, the output, economic benefits, and carbon emissions of each enterprise can be improved. When the output and economic benefits of an enterprise increase, the GDP support provided by the enterprise to the local area and the country is relatively increased, achieving a maximized overall benefit. Then, the increase in enterprise output will lead to an increase in the enterprise's carbon emissions. The regional carbon emission allocation unit 4, through changes in the enterprise's carbon emissions, reduces the carbon emissions of some low-output, high-carbon-emission enterprises in the region where the enterprise is located, and increases the carbon emissions of enterprises with increased output. This can effectively guarantee the production and development of enterprises, achieve the optimal allocation of carbon emissions in the region, improve the region's energy conservation and emission reduction plan, and improve the region's economic production efficiency and sustainable development.

[0019] A detailed explanation of the above plan is provided below: The enterprise carbon emission prediction unit 1 includes an enterprise output data acquisition module 11, which acquires the enterprise's business project information and estimated project output data. The output of the enterprise output data acquisition module 11 is connected to an enterprise carbon emission analysis module 12. The enterprise carbon emission analysis module 12 predicts the carbon emissions that the enterprise will generate when completing the project output based on the enterprise's business project information and estimated project output data, and records the business project information and carbon emission amount as reference enterprise targets. In this scheme, carbon emissions refer to the amount of carbon dioxide emitted by the enterprise when producing or manufacturing products, that is, the amount of carbon dioxide released into the atmosphere. The enterprise output data acquisition module 11 acquires the enterprise's business target information and the output target data that the enterprise needs to complete in the current month. By determining the output target data to be completed, the enterprise carbon emission analysis module 12 analyzes the carbon emissions generated by the enterprise's past predetermined output, predicts the enterprise's carbon emission data for the current month, and records the output target data and carbon emission data as reference enterprise target data, which facilitates further management of the enterprise's carbon emissions (in this scheme, output and project output refer to the enterprise's product output). Then, the predicted carbon emissions for the aforementioned companies in the current month were calculated and predicted in the following way: By calculating the average carbon emissions, the carbon emissions generated by a company in achieving its product targets for the current month can be predicted, as shown in the following calculation method: The formula for calculating the average carbon emissions is: Average carbon emissions = Past monthly carbon emissions / Past monthly production target; The formula for calculating the carbon emissions for the current month is: Current month carbon emissions = Average carbon emissions * Production target data. Then, the "past month carbon emissions" in the above two formulas refer to the company's past data before the current month, and the time period is one month. This allows for a reasonable and accurate prediction of the company's carbon emissions for the current month.

[0020] The matching enterprise determination unit 2 includes a trading enterprise screening and positioning module 21. This module receives reference enterprise target information from the enterprise carbon emission analysis module 12. Based on this information, it screens other enterprises that can engage in carbon emission trading and have cooperative plans with the enterprises in the reference enterprise targets. These screened enterprises are then recorded as trading enterprise targets, and the module recommends that the trading enterprise targets trade with the reference enterprise targets. In this embodiment, by receiving the reference enterprise target information, the trading enterprise screening and positioning module 21 can use the reference enterprise targets as a base point to determine other enterprises that can engage in carbon emission trading and have cooperative plans with the enterprises in the reference enterprise targets. That is, when the carbon emissions of the enterprises in the reference enterprise targets exceed the nationally allocated carbon emission quota, the trading enterprise screening and positioning module 21 identifies other enterprises that can enable the enterprises in the reference enterprise targets to purchase the corresponding carbon emission quota—that is, enterprises with the excess carbon emission quota. This allows the reference enterprise targets and trading enterprise targets to trade together. Carbon emission trading enables enterprises to conduct normal production. When the trading enterprise screening and positioning module 21 acquires other enterprises, the ability to conduct carbon emission trading is the first factor, and the existence of a cooperation plan is the second factor. The second factor is specifically defined; for example, if the target enterprise manufactures machinery such as pumps and valves, the second factor is identifying enterprises that produce raw materials for pumps and valves. This ensures that, while meeting the carbon emission trading objectives of both the reference enterprise and the trading enterprise, it also fosters understanding between these complementary enterprises, creating opportunities for future cooperation. This prevents some enterprises from having low output due to a lack of access to other resources. By establishing a platform connecting and connecting enterprises, cooperation is promoted, thereby increasing enterprise output and carbon emissions. As carbon emissions continue to change, enterprises can apply for more carbon emission allocations from the government, providing strong economic support for themselves and the nation.

[0021] The conversion cooperation analysis unit 3 includes a carbon emission trading overview analysis module 31. The carbon emission trading overview analysis module 31 is used to obtain carbon emission trading information between the aforementioned trading enterprise target and the reference enterprise target, and to analyze whether there is any cooperation between the trading enterprise target and the reference enterprise target other than carbon emission trading. The output end of the carbon emission trading overview analysis module 31 is connected to a two-way conversion cooperation analysis module 32. The two-way conversion cooperation analysis module 32 is used to analyze the project output of the trading enterprise target and the reference enterprise target themselves when it is determined that there is any cooperation between the trading enterprise target and the reference enterprise target other than carbon emission trading based on the analysis overview of the trading enterprise target and the reference enterprise target by the carbon emission trading overview analysis module 31. It obtains the operation and carbon emission situation of the trading enterprise target and the reference enterprise target through the carbon emission trading overview analysis module 31, and analyzes whether there is carbon emission trading cooperation between the trading enterprise target and the reference enterprise target. That is, one enterprise sells its own carbon emission, and the other enterprise buys the carbon emission sold by the enterprise, so as to achieve normal carbon emission situation of the enterprise and ensure normal production of the enterprise. Then, when there is carbon emission trading between the trading enterprise target and the reference enterprise target, and the analysis is conducted on whether there are other collaborations between the trading enterprise target and the reference enterprise target besides carbon emission trading after the carbon emission trading, if other collaborations are found, it means that both the trading enterprise target and the reference enterprise target have their own project output growth. This means that economic cooperation has been achieved between the trading enterprise target and the reference enterprise target, indicating that there is a certain probability of cooperation driving the above-mentioned recommendation for the trading enterprise target and the reference enterprise target to trade. Furthermore, through the two-way conversion cooperation analysis module 32, the project output of the trading enterprise target and the reference enterprise target are analyzed to obtain the maximum benefit formed by the trading enterprise target and the reference enterprise target after cooperation. In this way, when the trading enterprise target and the reference enterprise target realize carbon emission trading, the expansion of project output improves the profitability of each enterprise, thereby forming a friendly and win-win situation, which also helps the future development of the enterprise and increases the probability of sustainable development of the enterprise.

[0022] Regional carbon emission allocation unit 4 includes a carbon emission growth rate summarization module 41. This module is used to obtain the carbon emissions of the trading enterprise targets and reference enterprise targets due to changes in their own project output after other trading cooperation. It then estimates the corresponding growth rate of carbon emissions based on these changes. Furthermore, the module identifies and summarizes enterprises with the same carbon emission growth rate. In this scheme, the carbon emission growth rate summarization module 41 analyzes the project output of the aforementioned trading enterprise targets and reference enterprise targets after other trading cooperation, thereby aligning with the aforementioned carbon emission targets. The calculation and prediction method predicts the carbon emissions caused by the current project output. This allows for the determination of the changes in carbon emissions of the target trading company and the target reference company after cooperation, thereby inferring the growth rate of carbon emissions and predicting the specific situation of subsequent carbon emission growth. Furthermore, the carbon emission growth rate summarization module 41 will also summarize some companies with the same carbon emission growth rate. Based on the subsequent carbon emission growth of these companies, it is possible to predict the amount of carbon dioxide emitted into the atmosphere by these companies. This facilitates accurate statistical analysis of carbon dioxide content in the atmosphere, enabling the state to make corresponding plans and allocations for the carbon emissions of the aforementioned companies, so as to ensure that the companies can carry out normal production operations.

[0023] Example 2 This embodiment is a further extension of the above solution: The output of the carbon emission growth rate summarization module 41 is connected to the regional carbon emission allocation improvement module 42. The regional carbon emission allocation improvement module 42 is used to obtain the locations of enterprises with the same carbon emission growth rate summarized by the carbon emission growth rate summarization module 41, and determine the region where the enterprise is located based on its location. This is achieved by redistributing the carbon emissions of enterprises with low project output and excessively high carbon emission allocation within that region to enterprises currently experiencing emission growth. The regional carbon emission allocation improvement module 42 obtains the locations of enterprises with the same carbon emission growth rate summarized by the carbon emission growth rate summarization module 41, and determines the region where the enterprise is located based on its location. In other words, the region where each enterprise is located is determined by its coordinates, such as a province. Since carbon emission allocation is usually divided by region, this facilitates the analysis by the regional carbon emission allocation improvement module 42 of enterprises with low project output and excessively high carbon emission allocation within that region. For enterprises with excessively high carbon emission allocations, the reason is usually due to the average allocation of carbon emissions based on the enterprise's production over a certain period. For example, when an enterprise has different production volumes in different months of the year, its carbon emissions will vary accordingly. The regional carbon emission allocation improvement module 42 identifies enterprises with low production and low carbon emissions in recent times. Their carbon emissions can then be reduced and allocated to enterprises with increased carbon emissions within the region. This ensures that enterprises with high carbon emissions have carbon emissions commensurate with their production, facilitating normal production operations within the region. This allows for reasonable carbon emission planning in the region, enabling the implementation of energy conservation and emission reduction projects, enhancing the economic benefits the enterprise can bring to the region, and contributing to the region's future development.

[0024] Example 3 This embodiment is a different implementation method from Embodiment 1 described above: Considering that the companies in the reference enterprise targets have their own partner companies and do not need the companies recommended by this system, the matching enterprise determination unit 2 includes a predetermined target enterprise reservation module 22. The predetermined target enterprise reservation module 22 is used to set the predetermined other companies as predetermined transaction targets when the companies in the reference enterprise targets have predetermined other company selections. The predetermined transaction targets here are different from the transaction enterprise targets determined by the reference enterprise targets mentioned above. By having the companies in the reference enterprise targets provide their predetermined other companies to this system, the predetermined target enterprise reservation module 22 will record the predetermined other companies provided by the companies in the reference enterprise targets as transaction enterprise targets. By trading with the reference enterprise targets, the carbon emission trading needs of the companies themselves can be met, further expanding the actual needs of this system.

[0025] 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 to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended technical solutions and their equivalents.

Claims

1. A management system for energy conservation and emission reduction planning based on big data prediction, comprising an enterprise carbon emission prediction unit (1), wherein the enterprise carbon emission prediction unit (1) is used to obtain the enterprise's business projects and output, predict the enterprise's carbon emissions based on the output, and record the enterprise's business projects and carbon emissions as reference enterprise targets, characterized in that: The output of the enterprise carbon emission prediction unit (1) is connected to the matching enterprise determination unit (2). The matching enterprise determination unit (2) is used to screen other enterprises that can trade with the enterprises in the reference enterprise target based on the reference enterprise target, record the other enterprises as trading enterprise targets, and recommend the reference enterprise target and the trading enterprise target to conduct carbon emission trading. The output of the matching enterprise determination unit (2) is connected to the conversion cooperation analysis unit (3). The conversion cooperation analysis unit (3) is used to analyze the overall trading situation between the reference enterprise target and the trading enterprise target. The output of the conversion cooperation analysis unit (3) is connected to the regional carbon emission allocation unit (4). The regional carbon emission allocation unit (4) determines the carbon emission growth of enterprises based on the overall trading situation and redistributes the carbon emission of enterprises in the region.

2. The energy conservation and emission reduction planning management system based on big data prediction according to claim 1, characterized in that: The enterprise carbon emission prediction unit (1) includes an enterprise output data acquisition module (11), which is used to acquire the enterprise's business project information and the estimated output data of the project. The output end of the enterprise output data acquisition module (11) is connected to an enterprise carbon emission analysis module (12), which is used to predict the amount of carbon emissions that the enterprise will generate when it completes the project output based on the enterprise's business project information and the estimated output data of the project, and to record the business project information and carbon emissions as the reference enterprise target.

3. The energy conservation and emission reduction planning management system based on big data prediction according to claim 1, characterized in that: The matching enterprise determination unit (2) includes a trading enterprise screening and positioning module (21). The trading enterprise screening and positioning module (21) is used to receive reference enterprise target information from the enterprise carbon emission analysis module (12). The trading enterprise screening and positioning module (21) screens other enterprises that can achieve carbon emission trading and have cooperation plans with the enterprises in the reference enterprise target based on the reference enterprise target information. The other enterprises after screening are recorded as trading enterprise targets, and the trading enterprise targets are recommended to trade with the reference enterprise targets.

4. The energy conservation and emission reduction planning management system based on big data prediction according to claim 3, characterized in that: The matching enterprise determination unit (2) includes a predetermined target enterprise reservation module (22). The predetermined target enterprise reservation module (22) is used to set the predetermined other enterprises as predetermined transaction targets when there are predetermined other enterprise choices among the enterprises in the reference enterprise targets. The predetermined transaction targets here are different from the transaction enterprise targets determined by the reference enterprise targets mentioned above.

5. The energy conservation and emission reduction planning management system based on big data prediction according to claim 1, characterized in that: The conversion cooperation analysis unit (3) includes a carbon emission trading overview analysis module (31). The carbon emission trading overview analysis module (31) is used to obtain carbon emission trading information between the above-mentioned trading enterprise target and the reference enterprise target, and to analyze whether there is any cooperation between the trading enterprise target and the reference enterprise target other than carbon emission trading. The output end of the carbon emission trading overview analysis module (31) is connected to a two-way conversion cooperation analysis module (32). The two-way conversion cooperation analysis module (32) is used to analyze the project output of the trading enterprise target and the reference enterprise target when it is determined that there is any cooperation between the trading enterprise target and the reference enterprise target other than carbon emission trading based on the analysis overview between the trading enterprise target and the reference enterprise target by the carbon emission trading overview analysis module (31).

6. The energy conservation and emission reduction planning management system based on big data prediction according to claim 1, characterized in that: The regional carbon emission allocation unit (4) includes a carbon emission growth rate summarization module (41). The carbon emission growth rate summarization module (41) is used to obtain the carbon emissions caused by changes in the output of the trading enterprise target and the reference enterprise target due to their own projects after other trading cooperation. The carbon emission growth rate is estimated based on the carbon emission amount, and the carbon emission growth rate summarization module (41) identifies and summarizes some enterprises with the same carbon emission growth rate.

7. The energy conservation and emission reduction planning management system based on big data prediction according to claim 6, characterized in that: The output of the carbon emission growth rate summarization module (41) is connected to the regional carbon emission allocation improvement module (42). The regional carbon emission allocation improvement module (42) is used to obtain the location of enterprises with the same carbon emission growth rate summarized by the carbon emission growth rate summarization module (41), determine the region where the enterprise is located by the location, and redistribute the carbon emissions of enterprises with low project output and excessive carbon emission allocation in the region with the current emission growth enterprises.

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