CN116611652A - Carbon emission monitoring and measuring method based on electric power big data - Google Patents
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Abstract
The invention provides a carbon emission monitoring and measuring method based on electric power big data, which comprises the following steps: step one: acquiring declaration carbon emission of a thermal power plant and acquired quota carbon emission; step two: acquiring real-time carbon emission of the thermal power plant, and predicting future carbon emission of the thermal power plant according to the real-time carbon emission; step three: randomly selecting carbon emission in a plurality of time periods from the obtained real-time carbon emission, predicting the future carbon emission of the thermal power plant according to the carbon emission in the plurality of time periods, and comparing and checking with the carbon emission predicted by the real-time carbon emission in the second step; step four: performing difference value according to the predicted carbon emission and the quota carbon emission to obtain a compensation carbon emission, and performing distribution compensation on the compensation carbon emission; the method can conveniently and accurately predict the carbon emission in a period of time in the future of the thermal power plant, ensure the accuracy of prediction and reduce the cost.
Description
Technical Field
The invention relates to the technical field of carbon emission, in particular to a carbon emission monitoring and measuring method based on electric power big data.
Background
Carbon emissions are greenhouse gases, which cause a greenhouse effect and raise the global temperature. The earth absorbs solar radiation and radiates heat to the outer space, and the heat radiation is mainly long-wave infrared rays of 3-30 um. When such long wave radiation enters the atmosphere, it is easily absorbed by certain more polar gas molecules of greater molecular weight. Because the energy of the infrared rays is low enough to cause the breakage of molecular bond energy, no chemical reaction occurs after the gas molecules absorb the infrared radiation, but the heat is only prevented from escaping from the earth outwards, which is equivalent to the function of a heat insulating layer of the earth and the outer space, namely a greenhouse. The phenomenon that some trace components in the atmosphere absorb long-wave radiation of the earth to keep heat near the ground, so that the global air temperature rises is called a greenhouse effect.
As global climate warms, carbon dioxide isothermal chamber gas emissions have attracted widespread attention; the problems of energy consumption and carbon emission become important constraint factors for the development of a thermal power plant, the reduction of carbon emission is a key stress direction, and the realization of accurate measurement and comprehensive monitoring of carbon emission is a primary task of reducing carbon emission. The energy supply side is an important field of carbon emission generation, but the production service is consumption, and the energy consumption side directly or indirectly obtains economic and environmental benefits from high energy consumption and high emission of the energy supply side. Based on this, in order to balance the supply side responsibility and the consumption side responsibility of carbon emissions, to avoid unfair problems caused by carbon emission responsibility transfer, accurate metering and comprehensive monitoring of energy consumption side carbon emissions should be enhanced, providing a trusted data support for the "two carbon" target.
The existing thermal power plant carbon emission accounting report is generally prepared by collecting and summarizing existing emission data, then carrying out carbon emission accounting, finally obtaining carbon emission and carrying out carbon emission reporting. However, the existing thermal power plant carbon emission accounting systems are all accounting systems or methods for thermal power plants in a single industry, at present, the number of types of the systems or methods related to thermal power plant carbon emission accounting in the market is large, the accounting results are uneven, the thermal power plants with requirements are not known to select, the functions of the existing accounting systems or methods are single, only the carbon accounting requirements are provided, the meaning of the carbon accounting is far more than single computing effect at present, early warning and trend prediction of future time of carbon emission can be performed during accounting, carbon transaction can be performed, carbon emission is managed through informatization means, and minimum cost performance is realized.
Disclosure of Invention
Aiming at the technical problems, the invention provides the carbon emission monitoring and measuring method based on the electric power big data, which can conveniently and accurately predict the carbon emission in a period of time in the future of the thermal power plant, ensure the accuracy of prediction and reduce the cost.
In order to achieve the above purpose, the present invention provides the following technical solutions: a carbon emission monitoring and measuring method based on electric power big data comprises the following steps:
step one: acquiring declaration carbon emission of a thermal power plant and acquired quota carbon emission;
step two: acquiring real-time carbon emission of the thermal power plant, and predicting future carbon emission of the thermal power plant according to the real-time carbon emission;
step three: randomly selecting carbon emission in a plurality of time periods from the obtained real-time carbon emission, predicting the future carbon emission of the thermal power plant according to the carbon emission in the plurality of time periods, and comparing and checking with the carbon emission predicted by the real-time carbon emission in the second step;
step four: and carrying out difference value according to the predicted carbon emission and the quota carbon emission to obtain the compensation carbon emission, and carrying out distribution compensation on the compensation carbon emission.
Preferably, the collecting device for collecting the real-time carbon emission in the second step comprises concentration monitoring equipment, flue gas flow monitoring equipment, sampling equipment, a data collecting and controlling system and an automatic data collecting and processing system.
Preferably, the detecting step of the real-time carbon emission amount is as follows:
the first step: detecting the carbon dioxide content in the clean flue gas generated by the thermal power plant by a coarse range detection method;
and a second step of: calculating the concentration of carbon dioxide, wherein the calculation formula of the concentration of carbon dioxide is as follows:
wherein: x-carbon dioxide conversion value (mg/Nm) 3 ) The method comprises the steps of carrying out a first treatment on the surface of the C-carbon dioxide concentration measurements (ppm); molecular mass of M-carbon dioxide; t-clean flue gas temperature (. Degree. C.); p-net flue gas pressure (P a )；
And a third step of: the carbon emission amount is calculated as follows:
wherein: accumulated carbon dioxide emissions (T) over Mc-time T; x-carbon dioxide conversion value (mg/Nm) 3 ) The method comprises the steps of carrying out a first treatment on the surface of the F-clean flue gas flow (Nm) 3 /h)。
Preferably, the calculation formula of the quota carbon emission is as follows:
wherein: AE (AE) tg -counting a target limit value (t) of the emission of carbon from the unit during a time period t; AE (AE) ly -last year unit carbon emission (t); g ly -last annual energy production (MWh); g t -counting the unit plan electrical values (MWh) during a period t; the 0.95-free quota ratio is 95%.
Preferably, the step of predicting the future carbon emission of the thermal power plant by the carbon emission in the plurality of time periods of the real-time carbon emission comprises the following steps:
(1) Dividing the real-time period for acquiring the carbon emission amount into N small periods of the same time length (N 1 、N 2 、N 3 …N n ) And randomly extracts a small time periods (N a1 、N a2 、N a3 …N an )；
(2) Respectively for each extracted small time periodIs subjected to real-time carbon emission detection and calculation to obtain a real-time carbon emission (M) c1 、M c2 、M c3 …M cn )；
(3) Pre-storing the future N by the following formula x Internal carbon emissions M cx ：
Preferably, when the difference between the predicted carbon emission and the quota carbon emission is greater than 0, selling the excessive quota emission; and purchasing the absent quota carbon emission when the difference between the predicted carbon emission and the quota carbon emission is 0, and distributing and compensating the compensating carbon emission.
The invention has the beneficial effects that: the method comprises the steps of obtaining real-time carbon emission of a thermal power plant, predicting future talking emission of the thermal power plant through the real-time carbon emission, dividing the same time period for obtaining the real-time carbon emission into n small time periods, randomly extracting a small time periods in the small time periods, and obtaining corresponding carbon emission in the a small time periods, so that comparison and verification are conveniently carried out on the real-time carbon emission, the prediction accuracy is conveniently improved, the carbon emission supplement is conveniently purchased when the quota carbon emission is small, and the excessive carbon emission is conveniently sold when the quota carbon emission is excessive, so that certain cost is conveniently recovered, the cost is reduced, the carbon emission of the thermal power plant in a future period can be conveniently and accurately predicted, and the prediction accuracy is ensured.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate and together with the embodiments of the invention and do not constitute a limitation to the invention, and in which:
fig. 1 is a schematic diagram of a simple structure of a method for monitoring and measuring carbon emission based on big electric power data according to the present invention.
Detailed Description
In order that the manner in which the above recited features, objects and advantages of the present invention are attained and can be readily understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings, but which are appended drawings. Based on the examples in the embodiments, those skilled in the art can obtain other examples without making any inventive effort, which fall within the scope of the invention.
Referring to fig. 1, a method for monitoring and measuring carbon emission based on big electric power data includes the following steps:
step one: acquiring declaration carbon emission of a thermal power plant and acquired quota carbon emission;
step two: acquiring real-time carbon emission of the thermal power plant, and predicting future carbon emission of the thermal power plant according to the real-time carbon emission;
step three: randomly selecting carbon emission in a plurality of time periods from the obtained real-time carbon emission, predicting the future carbon emission of the thermal power plant according to the carbon emission in the plurality of time periods, and comparing and checking with the carbon emission predicted by the real-time carbon emission in the second step;
step four: and carrying out difference value according to the predicted carbon emission and the quota carbon emission to obtain the compensation carbon emission, and carrying out distribution compensation on the compensation carbon emission.
The acquisition device for acquiring the real-time carbon emission in the second step comprises concentration monitoring equipment, flue gas flow monitoring equipment, sampling equipment, a data acquisition and control system and an automatic data acquisition and processing system.
As shown in fig. 1, the quota carbon emission amount of the thermal power plant is obtained, and then the real-time carbon emission amount of the thermal power plant is obtained, so that whether the quota carbon emission amount is enough or not is conveniently judged, when the quota carbon emission amount is insufficient, the carbon emission amount is purchased through transaction so as to meet basic requirements, and when the quota carbon emission amount is excessive, the quota carbon emission amount is conveniently sold, so that a certain cost is conveniently recovered, and the cost is conveniently reduced; the time for acquiring the real-time carbon emission is divided into a plurality of small time periods, the a small time periods are randomly extracted, the carbon emission corresponding to each time period in the a small time periods is randomly extracted, the future carbon emission of the thermal power plant is conveniently predicted, the accuracy of the carbon emission prediction is conveniently ensured by comparing the carbon emission with the real-time carbon emission, larger fluctuation of each time period in the real-time carbon emission is avoided, the real-time carbon emission in the time period is ensured to be used for predicting experimental data of the future carbon emission of the thermal power plant, the carbon emission in the future time of the thermal power plant can be conveniently and accurately predicted, the prediction accuracy is ensured, and the cost is reduced.
Wherein the carbon emission amount is declared to be 105% of the predicted carbon emission amount, so that it is convenient to ensure that the purchase of the carbon emission amount in the outside is not required even when a small error occurs in the predicted carbon emission amount, so that the cost can be reduced.
The real-time carbon emission detection steps are as follows:
the first step: detecting the carbon dioxide content in the clean flue gas generated by the thermal power plant by a coarse range detection method;
and a second step of: calculating the concentration of carbon dioxide, wherein the calculation formula of the concentration of carbon dioxide is as follows:
wherein: x-carbon dioxide conversion value (mg/Nm) 3 ) The method comprises the steps of carrying out a first treatment on the surface of the C-carbon dioxide concentration measurements (ppm); molecular mass of M-carbon dioxide; t-clean flue gas temperature (. Degree. C.); p-net flue gas pressure (P a )；
And a third step of: the carbon emission amount is calculated as follows:
wherein: accumulated carbon dioxide emissions (T) over Mc-time T; x-carbon dioxide conversion value (mg/Nm) 3 ) The method comprises the steps of carrying out a first treatment on the surface of the F-clean flue gas flow (Nm) 3 /h)。
The calculation formula of the quota carbon emission is as follows:
wherein: AE (AE) tg -counting a target limit value (t) of the emission of carbon from the unit during a time period t; AE (AE) ly -last year unit carbon emission (t); g ly -last annual energy production (MWh); g t -counting the unit plan electrical values (MWh) during a period t; the 0.95-free quota ratio is 95%.
The method for predicting the future carbon emission of the thermal power plant by the carbon emission in a plurality of time periods of the real-time carbon emission comprises the following steps:
(1) Dividing the real-time period for acquiring the carbon emission amount into N small periods of the same time length (N 1 、N 2 、N 3 …N n ) And randomly extracts a small time periods (N a1 、N a2 、N a3 …N an )；
(2) The real-time carbon emission amount (M) is obtained by respectively carrying out real-time carbon emission amount detection calculation on the carbon emission amount in each extracted small period c1 、M c2 、M c3 …M cn )；
(3) Pre-storing the future N by the following formula x Internal carbon emissions M cx ：
The method comprises the steps of randomly extracting a time periods in N small time periods with the same time length, acquiring the corresponding carbon emission in each small time period, calculating and predicting the carbon emission in a future time period of the thermal power plant through a formula (4), performing mutual verification and comparison effects with the real-time carbon emission, and performing prediction calculation and prediction on the future carbon emission of the thermal power plant through the extracted a small time periods, so that the special condition that fluctuation of the carbon emission is overlarge in the small time period in the time period in which the real-time carbon emission is acquired can be effectively avoided, discarding the detection time of the real-time carbon emission in the time period when the condition occurs, and detecting and predicting the carbon emission of the thermal power plant from the time period in which the real-time carbon emission is newly selected.
When the difference result between the predicted carbon emission and the quota carbon emission is larger than 0, selling the excessive quota emission; when the predicted carbon emission and the quota carbon emission are different to be 0, purchasing the lack quota carbon emission, and distributing and compensating the compensating carbon emission.
The method comprises the steps of judging whether the quota carbon emission can meet requirements or not through predicting the carbon emission of a thermal power plant for a period of time in the future, adjusting and compensating the quota carbon emission, supplementing gaps through trading the carbon emission when the quota carbon emission is insufficient, meeting the requirements, selling and trading the excessive carbon emission when the quota carbon emission is met and excessive, and therefore recycling cost is facilitated, and cost is reduced.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present invention, and are not intended to limit the invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. The carbon emission monitoring and measuring method based on the electric power big data is characterized by comprising the following steps of:
step one: acquiring declaration carbon emission of a thermal power plant and acquired quota carbon emission;
step two: acquiring real-time carbon emission of the thermal power plant, and predicting future carbon emission of the thermal power plant according to the real-time carbon emission;
step three: randomly selecting carbon emission in a plurality of time periods from the obtained real-time carbon emission, predicting the future carbon emission of the thermal power plant according to the carbon emission in the plurality of time periods, and comparing and checking with the carbon emission predicted by the real-time carbon emission in the second step;
step four: and carrying out difference value according to the predicted carbon emission and the quota carbon emission to obtain the compensation carbon emission, and carrying out distribution compensation on the compensation carbon emission.
2. The method for monitoring and measuring carbon emission based on electric power big data according to claim 1, wherein the method comprises the following steps: the acquisition device for acquiring the real-time carbon emission in the second step comprises concentration monitoring equipment, smoke flow monitoring equipment, sampling equipment, a data acquisition and control system and an automatic data acquisition and processing system.
3. The method for monitoring and measuring carbon emission based on electric power big data according to claim 2, wherein the method comprises the following steps: the real-time carbon emission detection method comprises the following steps:
the first step: detecting the carbon dioxide content in the clean flue gas generated by the thermal power plant by a coarse range detection method;
and a second step of: calculating the concentration of carbon dioxide, wherein the calculation formula of the concentration of carbon dioxide is as follows:
wherein: x-carbon dioxide conversion value (mg/Nm) 3 ) The method comprises the steps of carrying out a first treatment on the surface of the C-carbon dioxide concentration measurements (ppm); molecular mass of M-carbon dioxide; t-clean flue gas temperature (. Degree. C.); p-net flue gas pressure (P a )；
And a third step of: the carbon emission amount is calculated as follows:
wherein: accumulated carbon dioxide emissions (T) over Mc-time T; x-carbon dioxide conversion value (mg/Nm) 3 ) The method comprises the steps of carrying out a first treatment on the surface of the F-clean flue gas flow (Nm) 3 /h)。
4. A method for monitoring and measuring carbon emissions based on electrical power big data according to claim 3, wherein: the calculation formula of the quota carbon emission is as follows:
wherein: AE (AE) tg -counting a target limit value (t) of the emission of carbon from the unit during a time period t; AE (AE) ly -last year unit carbon emission (t); g ly -last annual energy production (MWh); g t -counting the unit plan electrical values (MWh) during a period t; the 0.95-free quota ratio is 95%.
5. The method for monitoring and measuring carbon emission based on electric power big data according to claim 4, wherein the method comprises the following steps: the method for predicting the future carbon emission of the thermal power plant by the carbon emission in a plurality of time periods of the real-time carbon emission comprises the following steps:
(1) Dividing the real-time period for acquiring the carbon emission amount into N small periods of the same time length (N 1 、N 2 、N 3 …N n ) And randomly extracts a small time periods (N a1 、N a2 、N a3 …N an )；
(2) The real-time carbon emission amount (M) is obtained by respectively carrying out real-time carbon emission amount detection calculation on the carbon emission amount in each extracted small period c1 、M c2 、M c3 …M cn )；
(3) Pre-storing the future N by the following formula x Internal carbon emissions M cx ：
6. The method for monitoring and measuring carbon emission based on electric power big data according to claim 5, wherein the method comprises the following steps: when the difference result between the predicted carbon emission and the quota carbon emission is larger than 0, selling the excessive quota emission; and purchasing the absent quota carbon emission when the difference between the predicted carbon emission and the quota carbon emission is 0, and distributing and compensating the compensating carbon emission.
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| CN116974234A (en) * | 2023-09-22 | 2023-10-31 | 华能山东发电有限公司烟台发电厂 | Monitoring control method and system for thermal power plant carbon asset |
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| CN116974234A (en) * | 2023-09-22 | 2023-10-31 | 华能山东发电有限公司烟台发电厂 | Monitoring control method and system for thermal power plant carbon asset |
| CN116974234B (en) * | 2023-09-22 | 2024-02-20 | 华能山东发电有限公司烟台发电厂 | Monitoring control method and system for thermal power plant carbon asset |
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