CN115330081A - Carbon trading market intelligent analysis and prediction method and system based on big data - Google Patents
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Abstract
The invention discloses a big data-based intelligent analysis and prediction method and system for a carbon trading market, which relate to the technical field of carbon trading, and a predictor comprises the following analysis steps: s101, collecting multi-dimensional enterprise carbon emission data of a plurality of emission control enterprises, obtaining actual emission reduction values of the emission control enterprises based on a preset emission reduction reference value calculation formula, and obtaining a basic big data set; s102, based on the obtained basic big data set, carrying out detailed analysis on market price trends of the controlled and ranked enterprises to obtain an analysis result set, wherein the analysis result set is the regional support degree of the controlled and ranked enterprises; s103, comparing an analysis result set with a preset carbon trading market expectation condition set, wherein the preset carbon trading market expectation condition set is a comprehensive region support degree QZ, and judging whether the analysis result set meets the expectation condition set or not; and S104, if the analysis result set meets the expected condition set, outputting an analysis result and predicting the carbon emission trading market.
Description
Technical Field
The invention relates to the technical field of carbon trading, in particular to a carbon trading market intelligent analysis and prediction method and system based on big data.
Background
The consequences of climate change are becoming serious and serious threats to human sustainable development, and with the improvement of science and technology and the improvement of living standard of people, the emission of carbon dioxide is getting higher and higher, and further, the issues related to climate warming and carbon emission caused by too high emission of carbon dioxide are getting more and more attention. In order to promote global greenhouse gas emission reduction and reduce global carbon dioxide emission, a form of trading carbon emission rights as commodities is formed, and the form is called carbon trading. The ultimate goal of carbon trading is to promote the reduction of greenhouse gas emissions by energy savings and process improvement measures, i.e., to optimize carbon emissions by market mechanisms.
In the existing carbon transaction management system, an optimization technology for configuring carbon assets and carbon transactions without consideration or rationality is lacked, so that an energy transaction mechanism, an energy producer and consumer and an auxiliary service transaction mechanism and a carbon transaction mechanism between carbon transaction suppliers and consumers are not clear, carbon emission information of related areas and related enterprises cannot be supervised and tracked according to carbon transactions and quotas, transaction service management is carried out, and certain safety risk exists in the carbon transaction process.
Disclosure of Invention
The invention aims to provide a carbon trading market intelligent analysis and prediction method and system based on big data, and the following technical problems are solved:
the carbon emission information of related areas and related enterprises cannot be supervised and tracked according to carbon trading and quotas, and trading service management is carried out, so that certain safety risk exists in the carbon trading process.
The purpose of the invention can be realized by the following technical scheme:
a carbon trading market intelligent analysis and prediction method based on big data comprises the following analysis steps:
s101, collecting multi-dimensional enterprise carbon emission data of a plurality of emission control enterprises, obtaining actual emission reduction values of the emission control enterprises based on a preset emission reduction reference value calculation formula, and obtaining a basic big data set;
s102, based on the obtained basic big data set, carrying out detailed analysis on market price trends of the control and arrangement enterprises to obtain an analysis result set, wherein the analysis result set is the regional support degree of the control and arrangement enterprises;
s103, comparing an analysis result set with a preset carbon trading market expectation condition set which is a comprehensive region support degree QZ, and judging whether the analysis result set meets the expectation condition set or not;
and S104, if the analysis result set meets the expected condition set, outputting an analysis result and predicting the carbon emission trading market.
Preferably, in step S101, the emission reduction reference value calculation formula is:
wherein, the index is the sustainable development index of the enterprise; w1, W2 and W3 are weights, a, b and c are influence factors, X is an uncontrollable factor, a, b and c are positive values when the influence factors are positive, and a, b and c are negative values when the influence factors are negative.
Preferably, the step S102 further includes the steps of:
s1021, obtaining carbon trading market data of any control enterprise, wherein the market data comprise selling unit price Di and selling amount;
s1021, acquiring a sales rate value Si of the control and emission enterprise, wherein Si represents the sales rate of the carbon transaction i of the enterprise;
step S1022: degree of zone support
(ii) a Qi is the total profit of the carbon transaction i in T days, and Li is the average value of the selling unit price of other emission control enterprises in the region;
wherein, X1 is a preset value, and 0.6, 0.5 and 0.01 are preset weights;
all values are calculated after removing the steel.
Preferably, the step S103 further includes the steps of:
s1031, obtaining market data corresponding to the carbon trading market in the region, wherein the market data comprise selling unit price and selling amount;
s1032, acquiring a selling unit price mean Dt of all carbon trades in the region from the current season to the current season based on the market data;
s1033, acquiring the total sale quantity Mt of all agricultural products in the region from the current season to the current season based on the market data;
marking the total days from the season to the present as Tt,3030 ≦ T ≦ 90;
the comprehensive area support degree is as follows:
；
wherein, 0.6 and 0.2 are preset weights.
Preferably, if the analysis result does not satisfy the expected condition set, the analysis result set is optimized based on the expected condition set to obtain an optimized result set and an optimized analysis result set.
Preferably, for the set of analysis results that do not satisfy the expected condition, the analysis results are used as temporary optimization results according to a probability formula, and the summaryThe rate formula is:
(ii) a Wherein e is a natural logarithm;
and stopping optimization until the difference value of the multiple temporary optimization results is smaller than a preset value, and taking all temporary optimization results as the analysis result set.
The utility model provides a carbon trading market intelligence analysis prediction system based on big data, includes data acquisition unit, first analysis unit, second analysis unit and prediction unit.
Preferably, the data acquisition unit is used for acquiring multi-dimensional enterprise carbon emission data of a plurality of emission control enterprises, obtaining an actual emission reduction value of each emission control enterprise based on a preset emission reduction reference value calculation formula, and obtaining a basic big data set;
the first analysis unit is used for carrying out detailed analysis on the market price trend of the controlled and released enterprises according to the obtained basic big data set to obtain an analysis result set;
the second analysis unit is used for comparing an analysis result set with a preset carbon trading market expectation condition set, wherein the preset carbon trading market expectation condition set is a comprehensive region support degree QZ, and judging whether the analysis result set meets the expectation condition set or not;
the prediction unit is used for predicting the carbon emission trading market according to the analysis result.
Preferably, the system further comprises a data storage module for storing a program which, when executed by the processor, causes the system to perform the steps of the method.
Preferably, the data storage means has stored thereon a computer program which, when being executed by a processor, carries out the steps of the method.
The invention has the beneficial effects that:
1) Acquiring multi-dimensional enterprise carbon emission data of a plurality of emission control enterprises, and obtaining actual emission reduction values of the emission control enterprises based on a preset emission reduction reference value calculation formula to obtain a basic big data set; based on the obtained basic big data set, carrying out detailed analysis on the market price trend of the control and arrangement enterprises to obtain an analysis result set, wherein the analysis result set is the regional support degree of the control and arrangement enterprises; comparing an analysis result set with a preset carbon trading market expectation condition set, wherein the preset carbon trading market expectation condition set is a comprehensive regional support degree QZ, and judging whether the analysis result set meets the expectation condition set or not; if the analysis result set meets the expected condition set, outputting an analysis result and predicting the carbon emission trading market;
2) The method comprises the steps of obtaining enterprise carbon emission data declared by a plurality of control and emission enterprises, and performing quota distribution on the enterprise carbon emission data to obtain an initial carbon quota which is used as a voucher and a carrier of carbon emission rights in a carbon market.
Drawings
The invention will be further described with reference to the accompanying drawings.
Fig. 1 is a flow chart of an intelligent analysis and prediction method for a carbon trading market based on big data according to the invention.
Fig. 2 is a schematic diagram of a big data-based intelligent analysis and prediction system for a carbon trading market according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Referring to fig. 1, the present invention relates to a method for intelligently analyzing and predicting a carbon trading market based on big data, which comprises the following analysis steps:
s101, collecting multi-dimensional enterprise carbon emission data of a plurality of emission control enterprises, obtaining actual emission reduction values of the emission control enterprises based on a preset emission reduction reference value calculation formula, and obtaining a basic big data set;
in step S101, the emission reduction reference value calculation formula is:
wherein, the index is the sustainable development index of the enterprise; w1, W2 and W3 are weights, a, b and c are influence factors, X is an uncontrollable factor, when the influence factors are positive, a, b and c are positive values, and when the influence factors are negative, a, b and c are negative values;
drawing a market sustainability development prediction index of the carbon emission of the enterprise according to the change of the value with time, wherein the starting point is the actual emission reduction value of the emission control enterprise;
participants of each link in the carbon market comprise a carbon checking unit, a trading mechanism, an intermediary mechanism, a control and emission enterprise, a third-party management mechanism and the like, wherein the fairness and reasonability of the carbon market trading can be guaranteed only by ensuring the accuracy of carbon emission data of the control and emission enterprise, so that enterprise carbon emission data declared by a plurality of control and emission enterprises need to be obtained, quota distribution is carried out on the enterprise carbon emission data, and the obtained initial carbon quota is used as a certificate and a carrier of carbon emission rights in the carbon market;
specifically, the carbon emission data of the emission control enterprise can be acquired by collecting the checking units, the transaction institutions, the intermediary institutions, the emission control enterprise, the third-party management institutions and the like of the emission control enterprise in the carbon market; for example, in a power generation system that accounts for carbon trading, if the actual carbon dioxide emissions of a power plant exceed the system allocation limits, the power plant must purchase a carbon emission differential; if the actual carbon dioxide emissions from a power plant are less than the allocated limits, the power plant may sell the remaining carbon emissions, at which point the carbon trading cost may be considered negative.
S102, based on the obtained basic big data set, carrying out detailed analysis on market price trends of the controlled and ranked enterprises to obtain an analysis result set, wherein the analysis result set is the regional support degree of the controlled and ranked enterprises;
s1021, acquiring carbon trading market data of any emission control enterprise, wherein the market data comprises sale unit price Di and sale amount;
s1021, acquiring a sales speed value Si of the controlled enterprise, wherein Si represents the sales speed of the carbon transaction i of the enterprise;
step S1022: degree of zone support
(ii) a Qi is the total profit of the carbon transaction i in T days, and Li is the average value of the selling unit price of other emission control enterprises in the region;
wherein, X1 is a preset value, and 0.6, 0.5 and 0.01 are preset weights;
all numerical values are calculated after the rigidity is removed;
in step S102, based on the analysis result set, if the carbon emission amount of the emission control enterprise is smaller than the upper limit of the carbon emission amount of this year, it is proved that the carbon emission right of the emission control enterprise has a surplus carbon emission amount, and the surplus carbon emission amount can be traded in the block chain;
if the carbon emission is greater than the upper limit of carbon emission in this year, it proves that the company violates the regulation of the Clean Development Mechanism (CDM), and corresponding carbon emission rights need to be purchased from other companies in the block chain, so as to increase the total allowed carbon emission and achieve the purpose of meeting the standard regulated by the Clean Development Mechanism (CDM);
and the emission reduction calculation intelligent contract is pre-deployed in the block chain and used for realizing the conversion between the low-carbon behavior data and the carbon emission reduction amount of the emission control enterprise and storing the converted result.
In this embodiment, the emission reduction calculation may submit a transaction request for emission reduction recording in the block chain network, and the block chain node receives the transaction request for emission reduction recording, may run the intelligent contract for emission reduction calculation, determines the carbon emission reduction amount of the controlled and ventilated enterprise according to the read low-carbon traffic behavior data of the controlled and ventilated enterprise and the carbon emission reduction calculation rule, and performs chain storage. In addition, in the embodiment, while the carbon emission reduction amount is determined, the low carbon behavior data of the emission control enterprise can be audited, the reasonability of the audit is audited, and the carbon emission reduction amount is calculated after the audit is passed;
s103, comparing an analysis result set with a preset carbon trading market expectation condition set, wherein the preset carbon trading market expectation condition set is a comprehensive region support degree QZ, and judging whether the analysis result set meets the expectation condition set or not;
s1031, obtaining market data corresponding to the carbon trading market in the region, wherein the market data comprise selling unit price and selling amount;
s1032, acquiring a selling unit price mean Dt of all carbon transactions in the region from the current season to the current season based on the market data;
s1033, acquiring the total sale quantity Mt of all agricultural products in the region from the current season to the current season based on the market data;
marking the total days from the current quarter to the current quarter as Tt, wherein T is more than or equal to 3030 and less than or equal to 90;
the comprehensive area support degree is as follows:
；
wherein, 0.6 and 0.2 are preset weights;
s104, if the analysis result set meets the expected condition set, outputting an analysis result and predicting a carbon emission trading market; and if the analysis result does not meet the expected condition set, optimizing the analysis result set based on the expected condition set to obtain an optimized result set and an optimized analysis result set.
Preferably, for the analysis result not meeting the expected condition set, the analysis result is used as a temporary optimization result according to a probability formula, where the probability formula is:
(ii) a Wherein e is a natural logarithm;
stopping optimization until the difference value of the multiple temporary optimization results is smaller than a preset value, and taking all temporary optimization results as the analysis result set;
in step S104, the prediction set is established based on the relevant data characteristics after the relevant data characteristics are extracted from the carbon emission data of the emission control enterprise, and the prediction set makes full use of the carbon emission data information of the emission control enterprise, so that the reliability and accuracy of a prediction result can be improved by using the prediction set for market prediction, and the technical problem that the prediction result is inaccurate due to the fact that the actual emission reduction value of the emission control enterprise cannot be accurately obtained by using the method in the prior art is solved;
example 2
The utility model provides a carbon trading market intelligence analysis prediction system based on big data, includes data acquisition unit, first analysis unit, second analysis unit and prediction unit.
The data acquisition unit is used for acquiring multi-dimensional enterprise carbon emission data of a plurality of emission control enterprises, obtaining actual emission reduction values of the emission control enterprises based on a preset emission reduction reference value calculation formula and obtaining a basic big data set;
the first analysis unit is used for carrying out detailed analysis on market price trends of the controlled and released enterprises according to the obtained basic big data set to obtain an analysis result set;
the second analysis unit is used for comparing an analysis result set with a preset carbon trading market expectation condition set, wherein the preset carbon trading market expectation condition set is a comprehensive region support degree QZ, and judging whether the analysis result set meets the expectation condition set or not;
the prediction unit is used for predicting the carbon emission trading market according to the analysis result.
Further comprising a data storage module for storing a program which, when executed by the processor, causes a system to perform the steps of the method.
The data storage module has stored thereon a computer program which, when executed by a processor, carries out the steps of the method.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and the like are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
While one embodiment of the present invention has been described in detail, the description is only a preferred embodiment of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (10)
1. The intelligent analysis and prediction method for the carbon trading market based on big data is characterized by comprising the following analysis steps:
s101, collecting multi-dimensional enterprise carbon emission data of a plurality of emission control enterprises, obtaining actual emission reduction values of the emission control enterprises based on a preset emission reduction reference value calculation formula, and obtaining a basic big data set;
s102, based on the obtained basic big data set, carrying out detailed analysis on market price trends of the controlled and ranked enterprises to obtain an analysis result set, wherein the analysis result set is the regional support degree of the controlled and ranked enterprises;
s103, comparing an analysis result set with a preset carbon trading market expectation condition set, wherein the preset carbon trading market expectation condition set is a comprehensive region support degree QZ, and judging whether the analysis result set meets the expectation condition set or not;
and S104, if the analysis result set meets the expected condition set, outputting an analysis result and predicting the carbon emission trading market.
2. The big-data-based intelligent analysis and prediction method for the carbon trading market according to claim 1, wherein in step S101, the emission reduction reference value calculation formula is as follows:
wherein, the index is the sustainable development index of the enterprise; w1, W2 and W3 are weights, a, b and c are influence factors, X is an uncontrollable factor, a, b and c are positive values when the influence factors are positive, and a, b and c are negative values when the influence factors are negative.
3. The big-data-based intelligent analysis and prediction method for the carbon trading market according to claim 2, wherein the step S102 further comprises the steps of:
s1021, obtaining carbon trading market data of any control enterprise, wherein the market data comprise selling unit price Di and selling amount;
s1021, acquiring a sales speed value Si of the controlled enterprise, wherein Si represents the sales speed of the carbon transaction i of the enterprise;
step S1022: degree of zone support
(ii) a Qi is the total profit of the carbon transaction i in T days, and Li is the average value of the selling unit price of other emission control enterprises in the region;
wherein, X1 is a preset value, and 0.6, 0.5 and 0.01 are preset weights;
all values are calculated after removing the steel.
4. The intelligent analysis and prediction method for the carbon trading market based on big data according to claim 3, wherein the step S103 further comprises the steps of:
s1031, obtaining market data corresponding to the carbon trading market in the region, wherein the market data comprise selling unit price and selling amount;
s1032, acquiring a selling unit price mean Dt of all carbon transactions in the region from the current season to the current season based on the market data;
s1033, acquiring the total sale quantity Mt of all agricultural products in the region from the current season to the current season based on the market data;
marking the total days from the season to the present as Tt,3030 ≦ T ≦ 90;
degree of support of the integrated area
；
Wherein 0.6 and 0.2 are preset weights.
5. The big-data-based intelligent analysis and prediction method for the carbon trading market according to claim 4, wherein if the analysis result does not satisfy the expected condition set, the analysis result set is optimized based on the expected condition set to obtain an optimized result set and an optimized analysis result set.
6. The big-data-based intelligent analysis and prediction method for the carbon trading market according to claim 5, wherein for the analysis result not meeting the set of expected conditions, the analysis result is used as a temporary optimization result according to a probability formula
(ii) a Wherein e is a natural logarithm;
and stopping optimization until the difference value of the multiple temporary optimization results is smaller than a preset value, and taking all temporary optimization results as the analysis result set.
7. The big-data-based intelligent analysis and prediction system for the carbon trading market according to any one of claims 1 to 6, comprising a data acquisition unit, a first analysis unit, a second analysis unit and a prediction unit.
8. The intelligent analysis and prediction system for the carbon trading market based on the big data as claimed in claim 7, wherein the data acquisition unit is used for acquiring multi-dimensional enterprise carbon emission data of a plurality of emission control enterprises, obtaining actual emission reduction values of each emission control enterprise based on a preset emission reduction reference value calculation formula, and obtaining a basic big data set;
the first analysis unit is used for carrying out detailed analysis on the market price trend of the controlled and released enterprises according to the obtained basic big data set to obtain an analysis result set;
the second analysis unit is used for comparing an analysis result set with a preset carbon trading market expectation condition set, wherein the preset carbon trading market expectation condition set is a comprehensive regional support degree QZ and judging whether the analysis result set meets the expectation condition set or not;
the prediction unit is used for predicting the carbon emission trading market according to the analysis result.
9. A big-data based carbon trading market intelligent analysis prediction system according to claim 8, further comprising a data storage module for storing a program that, when executed by the processor, causes the system to perform the steps of the method of any one of claims 1 to 6.
10. A big data based carbon trading market intelligent analysis prediction system according to claim 9, wherein the data storage module has stored thereon a computer program that, when executed by a processor, performs the steps of the method of any one of claims 1 to 6.
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| CN114723503A (en) * | 2022-06-08 | 2022-07-08 | 深圳传世智慧科技有限公司 | Market analysis method and system based on industrial chain data |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111369100A (en) * | 2020-01-07 | 2020-07-03 | 广州绿石碳科技股份有限公司 | Construction method of power transmission enterprise carbon asset assessment model |
| CN113139284A (en) * | 2021-04-16 | 2021-07-20 | 北京航空航天大学 | Carbon emission strategy optimization method and system |
| CN113393277A (en) * | 2021-07-01 | 2021-09-14 | 安徽洲弋电子商务有限公司 | Agricultural product market data analysis system based on big data |
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