CN115935287A - Carbon emission data quality early warning system based on big data - Google Patents
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Abstract
The invention discloses a carbon emission data quality early warning system based on big data, belongs to the field of carbon emission, relates to big data technology, and is used for solving the problem that the quality monitoring of carbon emission data is not accurate due to the fact that early warning and management and control cannot be performed on the carbon emission data of an enterprise in the prior art; the edge processor calculates emission data Spi in combination with the emission parameters, acquires a real-difference rate Sci in combination with the carbon emission data sent by the data acquisition terminal and the emission data Spi obtained by calculation, and sets a real-difference rate threshold Sc0; when the actual difference Sci is larger than the actual difference threshold Sc0, the edge processor sends an abnormal signal to the quality early warning module, and the quality early warning module carries out early warning alarm; the carbon emission monitoring system can be used for timely and accurately monitoring key areas and can be used for macroscopically analyzing, regulating and controlling the whole control area, so that a supervision unit can timely manage and control carbon emission data.
Description
Technical Field
The invention belongs to the field of carbon emission, relates to a big data technology, and particularly relates to a carbon emission data quality early warning system based on big data.
Background
Carbon emission is a general term for greenhouse gas emission, and a large amount of greenhouse gas is generated in the life and production processes; enterprises can generate a large amount of waste gas in the production process, and the waste gas is discharged after being treated, namely the carbon emission process; since carbon emissions have a great influence on the environment, it is very important to accurately monitor and manage the carbon emissions. The data quality is the life line of the carbon market, and is the cornerstone for the stable and effective operation and the continuous development of health of the carbon market. The accurate reliability of carbon emission data diagnosed by technical means is one of core technologies of quality monitoring of carbon emission data.
The invention provides a carbon emission data quality early warning system based on big data, which is used for solving the problems that the existing enterprises are easy to exceed standards and steal in the exhaust emission process, the phenomena can cause the carbon emission to exceed the standards, further the quality monitoring of the carbon emission data is not accurate, the early warning and the control on the carbon emission data of the enterprises cannot be realized, and the early warning and the control on the carbon emission data of the enterprises can be well realized in order to better verify the accuracy of the carbon emission data.
Disclosure of Invention
The utility model aims at providing a carbon emission data quality early warning system based on big data has solved among the prior art and can't carry out early warning and the not accurate problem of carbon emission data quality monitoring that the management and control leads to the carbon emission data of enterprise.
In order to achieve the purpose, the application provides a carbon emission data quality early warning system based on big data, which comprises a plurality of data acquisition terminals, a plurality of information acquisition terminals and an edge processor communicated with and/or electrically connected with the information acquisition terminals;
the data acquisition terminals are used for acquiring carbon emission data of the control panel area and sending the carbon emission data to the edge processor;
the information acquisition terminals are used for acquiring the emission parameters of the control chip area and sending the emission parameters to the edge processor;
the edge processor calculates discharge data Spi by combining the discharge parameters, wherein i represents the number of the control panel area, i is a positive integer, and i =1,2 … … n; n is the total number of the control slice areas;
the edge processor acquires a real-time difference rate Sci by combining carbon emission data sent by the data acquisition terminal and emission data Spi obtained through calculation, and sets a real-time difference rate threshold Sc0;
and when the actual difference Sci is larger than the actual difference threshold Sc0, the edge processor sends an abnormal signal to the quality early warning module, and the quality early warning module carries out early warning and alarming.
Preferably, the emission parameters include activity data of the fossil fuel, a carbon dioxide emission factor of the fossil fuel, a net consumption of the fossil fuel, and a received base site calorific value of the fossil fuel.
Preferably, the emission data Spi is calculated by:
the edge processor marks activity data of the fossil fuel, carbon dioxide emission factors of the fossil fuel, net consumption of the fossil fuel and received base level calorific value of the fossil fuel as ADji, EFji, FCji and NCVji respectively;
wherein j represents the type number of the fossil fuel;
the edge processor calculates the activity data ADji of the fossil fuel by using a calculation formula, wherein the calculation formula is as follows:
ADji＝NCVji×FCji
meanwhile, the edge processor also calculates the calculated emission data Spi of the fossil fuel by using a calculation formula, wherein the calculation formula of the calculated emission data Spi of the fossil fuel is as follows:
wherein alpha is a calculation correction factor, and alpha is more than 0 and less than 1; and m is the total number of types of fossil fuels.
Preferably, the acquisition process of the actual difference ratio Sci is as follows:
the edge processor respectively obtains an actually measured emission value Cpi and calculated emission data Spi, and compares the actually measured emission value Cpi with the calculated emission data Spi to obtain an actual difference ratio Sci, wherein the actual difference ratio Sci is calculated according to the formula:
in this formula, β is the gain factor, β < 1.
Preferably, when the real-to-difference rate Sci is less than or equal to the real-to-difference rate threshold Sc0, the edge processor sends a normal signal to the quality early warning module, and the quality early warning module does not perform early warning and alarming.
Preferably, the method further comprises the steps of acquiring carbon emission data of the control area through a remote sensing technology, and marking the acquired carbon emission data as a carbon emission early warning value;
comparing and analyzing the carbon emission early warning value of the control area with an actually measured emission value Cpi in the control area, and setting a comprehensive early warning signal;
when the actually measured emission value Cpi in the control collection area is larger than or equal to the carbon emission early warning value, the comprehensive early warning signal is an alarm signal, the edge processor sends an abnormal signal to the quality early warning module, and the quality early warning module carries out early warning;
when the actually measured emission value Cpi in the control area is smaller than the carbon emission early warning value, the comprehensive early warning signal is a normal signal, and the quality early warning module does not perform early warning and alarming.
Preferably, the method for acquiring the carbon emission early warning value of the jurisdiction area through the remote sensing technology comprises the following steps:
acquiring a preset evaluation period; wherein the evaluation period comprises one month, one quarter, and one year;
and taking the current moment as a starting point, obtaining the average value of the carbon emission data of the control cluster in the evaluation period, and marking the average value as a carbon emission early warning value.
Preferably, the control hub is composed of several control patch zones.
The carbon emission data quality early warning method based on big data comprises the following steps:
the method comprises the following steps that a plurality of data acquisition terminals acquire carbon emission data of a control area and send the carbon emission data to an edge processor;
the method comprises the following steps that a plurality of information acquisition terminals acquire emission parameters of a control chip area and send the emission parameters to an edge processor;
the edge processor calculates discharge data Spi by combining the discharge parameters, wherein i represents the number of the control panel area, i is a positive integer, and i =1,2 … … n; n is the total number of the control slice areas;
the edge processor acquires a real-time difference rate Sci by combining carbon emission data sent by the data acquisition terminal and emission data Spi obtained through calculation, and sets a real-time difference rate threshold Sc0;
and when the actual difference Sci is larger than the actual difference threshold Sc0, the edge processor sends an abnormal signal to the quality early warning module, and the quality early warning module carries out early warning and alarming.
Compared with the prior art, the invention has the beneficial effects that:
1. the method comprises the steps that carbon emission data in an enterprise are collected through a data collection terminal and an information collection terminal, and carbon emission data of a control area or a control collection area are analyzed and early warned with the assistance of emission parameters; the carbon emission monitoring system can be used for timely and accurately monitoring key areas and can be used for macroscopically analyzing, regulating and controlling the whole control area, so that a supervision unit can timely manage and control carbon emission data.
2. According to the invention, the carbon emission early warning threshold value of the control area is obtained through the remote sensing technology, the remote sensing technology range and the aging advantage are fully utilized, the carbon emission mean value in a certain period of time is obtained, the analysis of the state of the carbon emission data in the current control area is facilitated, the early warning of workers is facilitated, and the carbon emission data can be regulated and controlled as soon as possible.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required in the prior art and the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a block diagram of a carbon emission data quality early warning system based on big data according to the present invention.
Detailed Description
The core of the application is to provide a carbon emission data quality early warning system based on big data.
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all 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 application.
Referring to fig. 1, the carbon emission data quality early warning system based on big data comprises a plurality of data acquisition terminals;
the data acquisition terminals are used for acquiring carbon emission data of the control panel area, and can be one or more of a carbon emission tracker, a fixed source carbon emission online monitoring device and an unorganized carbon emission online monitoring device; the data acquisition terminals are connected with an edge processor;
in this application, a single edge processor is configured to process carbon emission data of a single management and control area, where the management and control area is composed of a plurality of management and control areas, and in one embodiment, the management and control area may be an enterprise, an industrial park, or a designated target area, and the corresponding management and control area may be an industrial park or a larger designated target area;
the edge processor receives carbon emission data sent by the data acquisition terminal, and marks the received carbon emission data as an actually measured emission value Cpi, wherein i represents the number of a control panel area, i is a positive integer, and i =1,2 … … n; n is the total number of the control slice areas;
the carbon emission data quality early warning system based on big data further comprises an information acquisition terminal, wherein the information acquisition terminal is used for acquiring emission parameters of a control area;
it should be noted that the net consumption of fossil fuel is the consumption of a preset evaluation period, which may be one month, one quarter or one year;
the information acquisition terminal sends the acquired emission parameters to the edge processor;
the information acquisition terminal is in communication and/or electrical connection with the edge processor; carrying out information interaction through wireless or electrical connection;
the edge processor receives the emission parameters sent by the information acquisition terminal and performs information processing on the received emission parameters;
in the present application, the information processing process includes preprocessing and calculation processing;
wherein the preprocessing comprises data supplementation and data deduplication; after preprocessing the emission parameters, the edge processor marks the activity data of the fossil fuel, the carbon dioxide emission factor of the fossil fuel, the net consumption of the fossil fuel and the received base calorific value of the fossil fuel as ADji, EFji, FCji and NCVji respectively;
wherein j represents the type number of the fossil fuel;
and the edge processor calculates the activity data ADji of the fossil fuel by using a calculation formula, wherein the calculation formula is as follows:
ADji＝NCVji×FCji
meanwhile, the edge processor also calculates the calculated emission data Spi of the fossil fuel by using a calculation formula, wherein the calculation formula of the calculated emission data Spi of the fossil fuel is as follows:
wherein alpha is a calculation correction factor, and alpha is more than 0 and less than 1; m is the total number of types of fossil fuels;
note that the unit of the calculated emission data Spi in the present application is ton carbon dioxide (tCO) 2 )；
The unit of activity data for fossil fuels is Gigajoules (GJ);
the carbon dioxide emission factor of fossil fuels has the unit of ton carbon dioxide/Ji Jiao (tCO) 2 /GJ)；
The net consumption of fossil fuels is in units of tons (t) or ten thousand standard cubic meters (10) 4 Nm 3 ) (ii) a The unit is tons (t) when the fossil fuel is solid and ten thousand standard cubic meters (10) when the fossil fuel is gaseous 4 Nm 3 )；
The units of calorific value received at the base site of fossil fuels are either gigajoules per ton (GJ/t) or gigajoules per million standard cubic meters (GJ/10) 4 Nm 3 ) (ii) a That is, when the fossil fuel is a solid, it is expressed in units of gigajoules per ton (GJ/t), and when the fossil fuel is a gas, it is expressed in units of gigajoules per thousand standard cubic meters (GJ/10) 4 Nm 3 )；
In this application, the edge processor still is connected with quality early warning module, quality early warning module is used for receiving edge processor's signal to carry out the quality early warning according to edge processor's signal, specifically, the process that edge processor generated the signal includes:
the edge processor respectively obtains an actually measured emission value Cpi and calculated emission data Spi, and compares the actually measured emission value Cpi with the calculated emission data Spi to obtain an actual difference ratio Sci, wherein the actual difference ratio Sci is calculated according to the formula:
in the formula, beta is a gain factor, and beta is less than 1; the edge processor sets a real-difference rate threshold Sc0 and compares the calculated real-difference rate Sci with the real-difference rate threshold Sc0;
when the real difference rate Sci is less than or equal to the real difference rate threshold Sc0, the edge processor sends a normal signal to the quality early warning module, and the quality early warning module does not perform early warning and alarming;
when the actual difference Sci is larger than the actual difference threshold Sc0, the edge processor sends an abnormal signal to the quality early warning module, and the quality early warning module carries out early warning and alarming;
in the application, the carbon emission data quality early warning system based on big data also acquires carbon emission data of a control region through a remote sensing technology, and marks the acquired carbon emission data as a carbon emission early warning value;
comparing and analyzing the carbon emission early warning value of the control area with an actually measured emission value Cpi in the control area, and setting a comprehensive early warning signal;
preferably, when the actually measured emission value Cpi in the control collection area is not less than the carbon emission early warning value, the comprehensive early warning signal is an alarm signal, the edge processor sends an abnormal signal to the quality early warning module, and the quality early warning module gives an early warning;
when the actually measured emission value Cpi in the control area is smaller than the carbon emission early warning value, the comprehensive early warning signal is a normal signal, and the quality early warning module does not perform early warning;
wherein, through the remote sensing technique obtains the carbon emission early warning value in jurisdiction, include:
acquiring a preset evaluation period; wherein the evaluation period comprises one month, one quarter, and one year;
and taking the current moment as a starting point, obtaining the average value of carbon emission data of the control concentrated area in an evaluation period, and marking the average value as a carbon emission early warning value.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
The working principle of the invention is as follows: the data acquisition terminals acquire carbon emission data of the control panel area and send the carbon emission data to the edge processor; the information acquisition terminals acquire the discharge parameters of the control panel area and send the discharge parameters to the edge processor; the edge processor calculates emission data Spi by combining the emission parameters; the edge processor acquires a real-to-differential rate Sci by combining the carbon emission data sent by the data acquisition terminal and the emission data Spi obtained by calculation, and sets a real-to-differential rate threshold Sc0; and when the actual difference Sci is larger than the actual difference threshold Sc0, the edge processor sends an abnormal signal to the quality early warning module, and the quality early warning module carries out early warning and alarming.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. The carbon emission data quality early warning system based on big data is characterized by comprising a plurality of data acquisition terminals, a plurality of information acquisition terminals and an edge processor which is communicated with and/or electrically connected with the information acquisition terminals;
the data acquisition terminals are used for acquiring carbon emission data of the control panel area and sending the carbon emission data to the edge processor;
the information acquisition terminals are used for acquiring the discharge parameters of the control panel area and sending the discharge parameters to the edge processor;
the edge processor calculates discharge data Spi by combining the discharge parameters, wherein i represents the number of the control panel area, i is a positive integer, and i =1,2 … … n; n is the total number of the control slice areas;
the edge processor acquires a real-to-differential rate Sci by combining the carbon emission data sent by the data acquisition terminal and the emission data Spi obtained by calculation, and sets a real-to-differential rate threshold Sc0;
and when the actual difference Sci is larger than the actual difference threshold Sc0, the edge processor sends an abnormal signal to the quality early warning module, and the quality early warning module carries out early warning and alarming.
2. The big-data based carbon emission data quality pre-warning system of claim 1, wherein the emission parameters include activity data of the fossil fuel, a carbon dioxide emission factor of the fossil fuel, a net consumption of the fossil fuel, and a received base bit calorific value of the fossil fuel.
3. The big-data-based carbon emission data quality early warning system according to claim 2, wherein the emission data Spi is calculated by:
the edge processor respectively marks activity data of the fossil fuel, carbon dioxide emission factors of the fossil fuel, net consumption of the fossil fuel and received base level calorific value of the fossil fuel as ADji, EFji, FCji and NCVji;
wherein j represents the type number of the fossil fuel;
the edge processor calculates the activity data ADji of the fossil fuel by using a calculation formula, wherein the calculation formula is as follows:
ADji＝NCVji×FCji
meanwhile, the edge processor calculates the calculated emission data Spi of the fossil fuel by using a calculation formula, wherein the calculation formula of the calculated emission data Spi of the fossil fuel is as follows:
wherein alpha is a calculation correction factor, and alpha is more than 0 and less than 1; and m is the total number of types of fossil fuels.
4. The big-data-based carbon emission data quality early warning system as claimed in claim 3, wherein the real-to-differential ratio Sci is obtained by the following steps:
the edge processor respectively obtains an actually measured emission value Cpi and calculated emission data Spi, and compares the actually measured emission value Cpi with the calculated emission data Spi to obtain an actual difference ratio Sci, wherein the actual difference ratio Sci is calculated according to the formula:
in this formula, β is the gain factor, β < 1.
5. The big-data-based carbon emission data quality early warning system of claim 4, wherein when the real-difference rate Sci is less than or equal to the real-difference rate threshold Sc0, the edge processor sends a normal signal to the quality early warning module, and the quality early warning module does not perform early warning alarm.
6. The big-data-based carbon emission data quality early warning system according to claim 5, further comprising a step of acquiring carbon emission data of a control area by a remote sensing technology, and marking the acquired carbon emission data as a carbon emission early warning value;
comparing and analyzing the carbon emission early warning value of the control area with an actually measured emission value Cpi in the control area, and setting a comprehensive early warning signal;
when the actually measured emission value Cpi in the control collection area is larger than or equal to the carbon emission early warning value, the comprehensive early warning signal is an alarm signal, the edge processor sends an abnormal signal to the quality early warning module, and the quality early warning module carries out early warning;
when the actually measured emission value Cpi in the control area is smaller than the carbon emission early warning value, the comprehensive early warning signal is a normal signal, and the quality early warning module does not perform early warning and alarming.
7. The big-data-based carbon emission data quality early warning system as claimed in claim 6, wherein the obtaining of the carbon emission early warning value of the jurisdiction by the remote sensing technology comprises:
acquiring a preset evaluation period; wherein the evaluation period comprises one month, one quarter, and one year;
and taking the current moment as a starting point, obtaining the average value of the carbon emission data of the control cluster in the evaluation period, and marking the average value as a carbon emission early warning value.
8. The big-data-based carbon emission data quality early warning system according to claim 7, wherein the control concentrated area is composed of a plurality of control areas.
9. The carbon emission data quality early warning method based on big data is applied to the carbon emission data quality early warning system based on big data in any one of claims 1 to 8, and the method comprises the following steps:
the method comprises the following steps that a plurality of data acquisition terminals acquire carbon emission data of a control chip area and send the carbon emission data to an edge processor;
the method comprises the following steps that a plurality of information acquisition terminals acquire emission parameters of a control area and send the emission parameters to an edge processor;
the edge processor calculates discharge data Spi by combining the discharge parameters, wherein i represents the number of the control panel area, i is a positive integer, and i =1,2 … … n; n is the total number of the control slice areas;
the edge processor acquires a real-to-differential rate Sci by combining the carbon emission data sent by the data acquisition terminal and the emission data Spi obtained by calculation, and sets a real-to-differential rate threshold Sc0;
when the actual difference Sci is larger than the actual difference threshold Sc0, the edge processor sends an abnormal signal to the quality early warning module, and the quality early warning module carries out early warning and alarming.
10. A readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the big-data based carbon emission data quality pre-warning method as set forth in claim 9.
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| CN113063898A (en) * | 2021-03-24 | 2021-07-02 | 中国大唐集团科学技术研究院有限公司中南电力试验研究院 | Thermal power station carbon emission monitoring method and system based on block chain |
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| CN114240463A (en) * | 2021-12-21 | 2022-03-25 | 合肥前卫科技有限公司 | Carbon emission monitoring and management system based on big data |
| CN114417435A (en) * | 2022-03-31 | 2022-04-29 | 广东省特种设备检测研究院顺德检测院 | Block chain-based carbon emission data supervision system and method for control and emission enterprises |
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| CN113063898A (en) * | 2021-03-24 | 2021-07-02 | 中国大唐集团科学技术研究院有限公司中南电力试验研究院 | Thermal power station carbon emission monitoring method and system based on block chain |
| CN113281466A (en) * | 2021-05-17 | 2021-08-20 | 吴迅海 | Calibration method and device for carbon emission detection and computer storage medium |
| CN114240463A (en) * | 2021-12-21 | 2022-03-25 | 合肥前卫科技有限公司 | Carbon emission monitoring and management system based on big data |
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