CN116974234A - Monitoring control method and system for thermal power plant carbon asset - Google Patents
Monitoring control method and system for thermal power plant carbon asset Download PDFInfo
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- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 title claims abstract description 433
- 229910052799 carbon Inorganic materials 0.000 title claims abstract description 433
- 238000012544 monitoring process Methods 0.000 title claims abstract description 190
- 238000000034 method Methods 0.000 title claims abstract description 35
- 239000003245 coal Substances 0.000 claims abstract description 56
- 238000013213 extrapolation Methods 0.000 claims description 14
- 238000012935 Averaging Methods 0.000 claims description 6
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- 238000004088 simulation Methods 0.000 claims description 3
- 230000002194 synthesizing effect Effects 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 description 9
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000010248 power generation Methods 0.000 description 3
- 238000007605 air drying Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 229910002092 carbon dioxide Inorganic materials 0.000 description 2
- 239000001569 carbon dioxide Substances 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005265 energy consumption Methods 0.000 description 2
- 238000002309 gasification Methods 0.000 description 2
- 239000005431 greenhouse gas Substances 0.000 description 2
- 239000007788 liquid Substances 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 238000013211 curve analysis Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 230000007257 malfunction Effects 0.000 description 1
- 238000007789 sealing Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The invention provides a method and a system for monitoring and controlling carbon assets of a thermal power plant. Belongs to the technical field of data monitoring, and comprises: acquiring all carbon emission types and real-time carbon emission parameters of a target thermal power plant, and determining the real-time carbon emission amount; constructing a carbon emission prediction model based on real-time coal parameters and real-time equipment parameters to obtain predicted carbon emission, and acquiring matched standard carbon emission based on the real-time equipment parameters; respectively comparing the predicted carbon emission amount, the real-time carbon emission amount and the standard carbon emission amount to obtain an initial monitoring result, and adjusting to obtain a comprehensive monitoring result; and judging the carbon emission result based on the comprehensive monitoring result, and determining equipment to be controlled based on the original carbon asset distribution to realize equipment control. The real-time carbon emission of the thermal power plant is predicted and compared, and the thermal power plant is monitored and adjusted by combining the original carbon asset, so that the monitoring of the carbon asset of the thermal power plant can be more accurate.
Description
Technical Field
The invention relates to the field of data monitoring control, in particular to a method and a system for monitoring and controlling carbon assets of a thermal power plant.
Background
At present, along with the high-speed development of the Internet of things technology, the Internet of things technology is more and more applied to the industrial field, particularly to the monitoring control of industrial equipment of a thermal power plant, a large amount of human resources can be liberated, and meanwhile equipment monitoring is more timely.
However, in the existing monitoring technology, the monitoring result is inaccurate due to less monitoring data and single monitoring method, so that the service life of the equipment is influenced.
Therefore, the invention provides a method and a system for monitoring and controlling carbon assets of a thermal power plant.
Disclosure of Invention
The invention provides a method and a system for monitoring and controlling carbon assets of a thermal power plant, which are used for predicting and comparing real-time carbon emission of the thermal power plant, and monitoring and adjusting the thermal power plant by combining a comparison result with an original carbon asset, so that the monitoring of the carbon asset of the thermal power plant can be more timely and accurate, and equipment emission problems can be found more timely and timely adjusted.
The invention provides a monitoring control method of a thermal power plant carbon asset, which comprises the following steps:
step 1: acquiring all carbon emission types of the target thermal power plant, acquiring corresponding real-time carbon emission parameters based on the carbon emission types, and determining the real-time carbon emission amount of the target thermal power plant;
Step 2: constructing a carbon emission prediction model based on real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain predicted carbon emission, and acquiring standard carbon emission matched with the target thermal power plant equipment based on the real-time equipment parameters;
step 3: first comparing the predicted carbon emission with the standard carbon emission, and second comparing the real-time carbon emission with the standard carbon emission;
step 4: obtaining an initial monitoring result of the target thermal power plant based on the second comparison result, and adjusting the initial monitoring result based on the first comparison result to obtain a comprehensive monitoring result;
step 5: and judging the carbon emission result of the target thermal power plant based on the comprehensive monitoring result, and determining thermal power plant equipment and equipment control parameters required to be controlled based on the original carbon asset distribution to realize equipment control.
In one possible implementation manner, obtaining all carbon emission types of the target thermal power plant, and obtaining corresponding real-time carbon emission parameters based on the carbon emission types, determining the real-time carbon emission amount of the target thermal power plant includes:
acquiring power plant equipment parameters of a target thermal power plant, and determining all carbon emission types contained in the target thermal power plant based on the parameter types;
Matching corresponding type equipment sensors based on the carbon emission type, and acquiring real-time carbon emission parameters based on the corresponding equipment sensors;
and carrying out parameter processing on the real-time carbon emission parameters, and obtaining the real-time carbon emission of all outlets of the target thermal power plant based on the parameter processing result.
In one possible implementation, constructing a carbon emission prediction model based on real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain a predicted carbon emission, and obtaining a standard carbon emission matched with the target thermal power plant based on the real-time equipment parameters, including:
extracting core data of real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain first coal parameters and first equipment parameters;
obtaining a corresponding first data fitting curve based on the first coal parameters, and performing curve trend extrapolation according to the curve trend of the first data fitting curve to obtain a second curve;
obtaining a corresponding first equipment fitting curve based on the first equipment parameters;
locking equipment to be analyzed based on data of a non-overlapping part of the second curve and the first data fitting curve and real-time equipment parameters of the target thermal power plant;
performing trend extrapolation on the first equipment fitting curve based on the real-time equipment parameters of the equipment to be analyzed to obtain a third curve;
Adjusting the second curve based on the curve trend of the third curve to obtain a second adjustment curve, and performing first prediction of carbon emission on the target thermal power plant based on curve parameters of the second adjustment curve;
acquiring a first preset weight as a fixed parameter of an initial carbon emission prediction model, and inputting a first coal parameter into the initial carbon emission prediction model to perform carbon emission prediction;
comparing the historical carbon emission of the target thermal power plant with a carbon emission prediction result, calculating a prediction error, and adjusting a first preset weight according to the prediction error to reduce the error;
determining the optimal preset weight as a standard fixed parameter of a carbon emission prediction model through multiple prediction adjustment;
predicting carbon emission based on the standard fixed parameters and the first coal parameters to obtain a second initial prediction result;
adjusting the second initial prediction result by combining the real-time equipment parameters of the target thermal power plant to obtain a second prediction result;
based on the first prediction result and the second prediction result, carrying out simulation, and judging the feasibility of the first prediction result and the second prediction result in practical application;
if the first prediction result and the second prediction result are in the application feasibility range, integrating the first prediction result and the second prediction result to obtain predicted carbon emission;
And simultaneously, acquiring the standard carbon emission matched with the target thermal power plant equipment from a standard database based on the real-time equipment parameters.
In one possible implementation, a first comparison of the predicted carbon emissions with the standard carbon emissions, and a second comparison of the real-time carbon emissions with the standard carbon emissions, includes:
comparing the predicted carbon emission amount with a carbon emission maximum threshold value and a carbon emission minimum threshold value of the target thermal power plant in real time;
if the predicted carbon emission is outside the range of the carbon emission maximum threshold and the carbon emission minimum threshold, the carbon emission is predicted again;
if the real-time carbon emission is out of the range of the carbon emission maximum threshold and the carbon emission minimum threshold, judging that equipment of the current target thermal power plant fails and carrying out early warning;
if the predicted and real-time carbon emissions are between the carbon emission maximum and minimum thresholds, the predicted and standard carbon emissions are first compared and the real-time and standard carbon emissions are second compared.
In one possible implementation manner, obtaining an initial monitoring result of the target thermal power plant based on the second comparison result, and adjusting the initial monitoring result based on the first comparison result to obtain a comprehensive monitoring result, including:
Inputting a second comparison result of the real-time carbon emission and the standard carbon emission into a comparison monitoring data table, and classifying according to the comparison result of the real-time carbon emission and the standard carbon emission;
if the real-time carbon emission is larger than the standard carbon emission, extracting a corresponding comparison result to obtain a first monitoring data table;
otherwise, extracting a corresponding comparison result to obtain a second monitoring data table;
synthesizing based on the comparison result values of the first monitoring data table and the second monitoring data table and the influence weights of the corresponding data to obtain an initial monitoring result of the target thermal power plant;
obtaining a third monitoring data table and a fourth monitoring data table based on the first comparison result;
respectively performing third comparison and fourth comparison on the data characteristics and the data values of the first monitoring data table and the third monitoring data table, and the second monitoring data table and the fourth monitoring data table;
and adjusting the initial monitoring result based on the results of the third comparison and the fourth comparison to obtain the comprehensive monitoring result of the target thermal power plant.
In one possible implementation, the third comparing the data characteristics and the data values of the first monitoring data table and the third monitoring data table includes:
Acquiring data characteristics of monitoring data in the first monitoring data table and the third monitoring data table, and corresponding the monitoring data in the first monitoring data table and the third monitoring data table one by one based on the data characteristics;
and comparing the data errors of the corresponding monitoring data based on the corresponding results one by one to obtain a third comparison result.
In one possible implementation manner, the method for determining the carbon emission result of the target thermal power plant based on the comprehensive monitoring result, and determining the thermal power plant equipment and equipment control parameters to be controlled based on the original carbon asset distribution, to implement equipment control includes:
judging a carbon emission result of the target thermal power plant based on the comprehensive monitoring result, and determining a carbon emission level of the target thermal power plant based on the judging result;
comprehensively determining the coal resource utilization condition of the target thermal power plant based on the carbon emission level and the carbon assets of the corresponding part;
determining equipment numbers and positions of the target thermal power plant, which need to control the carbon assets, based on the original carbon asset distribution and the coal resource utilization condition, and determining equipment control conditions of corresponding equipment;
and determining equipment control parameters of corresponding equipment based on the equipment control conditions, and controlling the corresponding equipment based on the equipment control parameters, so as to realize carbon asset monitoring control of the target thermal power plant.
The invention provides a monitoring control system of thermal power plant carbon assets, comprising:
emission determination module: the method comprises the steps of acquiring all carbon emission types of a target thermal power plant, acquiring corresponding real-time coal parameters based on the carbon emission types, and determining the real-time carbon emission amount of the target thermal power plant;
emission prediction module: the method comprises the steps of constructing a carbon emission prediction model based on real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain predicted carbon emission, and obtaining standard carbon emission matched with the target thermal power plant based on the real-time equipment parameters;
emission comparison module: for first comparing the predicted carbon emission with the standard carbon emission and second comparing the real-time carbon emission with the standard carbon emission;
and the comprehensive monitoring module is used for: the method comprises the steps of obtaining an initial monitoring result of a target thermal power plant based on a second comparison result, and adjusting the initial monitoring result based on a first comparison result to obtain a comprehensive monitoring result;
and the monitoring control module: and the device is used for judging the carbon emission result of the target thermal power plant based on the comprehensive monitoring result, determining the thermal power plant equipment and equipment control parameters required to be controlled based on the original carbon asset distribution, and realizing equipment control.
Compared with the prior art, the application has the following beneficial effects:
the real-time carbon emission of the thermal power plant is predicted and compared, and the comparison result is combined with the original carbon asset to monitor and adjust the thermal power plant, so that the monitoring of the carbon asset of the thermal power plant is more timely and accurate, and the equipment emission problem can be found more timely and timely adjusted.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the application is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate the application and together with the embodiments of the application, serve to explain the application. In the drawings:
FIG. 1 is a flow chart of a method for monitoring and controlling carbon assets of a thermal power plant in an embodiment of the application;
FIG. 2 is a flowchart of obtaining a comprehensive monitoring result in an embodiment of the present application;
FIG. 3 is a block diagram of a thermal power plant carbon asset monitoring control system in accordance with an embodiment of the present invention;
fig. 4 is a block diagram of a line segment extension in an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Example 1:
the embodiment of the invention provides a method for monitoring and controlling carbon assets of a thermal power plant, which is shown in fig. 1 and comprises the following steps:
step 1: acquiring all carbon emission types of the target thermal power plant, acquiring corresponding real-time carbon emission parameters based on the carbon emission types, and determining the real-time carbon emission amount of the target thermal power plant;
step 2: constructing a carbon emission prediction model based on real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain predicted carbon emission, and acquiring standard carbon emission matched with the target thermal power plant equipment based on the real-time equipment parameters;
step 3: first comparing the predicted carbon emission with the standard carbon emission, and second comparing the real-time carbon emission with the standard carbon emission;
step 4: obtaining an initial monitoring result of the target thermal power plant based on the second comparison result, and adjusting the initial monitoring result based on the first comparison result to obtain a comprehensive monitoring result;
Step 5: and judging the carbon emission result of the target thermal power plant based on the comprehensive monitoring result, and determining thermal power plant equipment and equipment control parameters required to be controlled based on the original carbon asset distribution to realize equipment control.
In this embodiment, the carbon emission type refers to a type of carbon emission performed by a thermal power plant, and for example, the carbon emission type includes direct carbon emission, indirect carbon emission, wherein the indirect carbon emission includes electric power consumption of equipment, production energy consumption, line power consumption, and the like.
In this embodiment, the real-time carbon emission parameters refer to emission parameters of carbon emission of the target thermal power plant, wherein the real-time carbon emission parameters include carbon dioxide emission amount, greenhouse gas emission ratio, carbon emission intensity, and equipment average emission amount.
In this embodiment, the real-time carbon emission amount refers to a carbon emission amount obtained by classifying according to the corresponding carbon emission type according to the acquired real-time carbon emission parameter.
In this embodiment, the real-time coal parameters refer to real-time coal consumption parameters of equipment of the target thermal power plant, for example, the real-time coal parameters include coal calorific value, ash, air drying-based gasification amount, and the like.
In this embodiment, the real-time equipment parameter refers to equipment parameters of the target thermal power plant when the equipment performs normal power generation operation, such as real-time voltage, power consumption, rotation speed, frequency, and the like of the equipment.
In this embodiment, the carbon emission prediction model is a carbon emission prediction model obtained by constructing an initial carbon emission model according to real-time coal parameters input by each device in the target thermal power plant and real-time device parameters of the corresponding device and adjusting the initial carbon emission model.
In this embodiment, predicting the carbon emission amount refers to obtaining the carbon emission amount of each device based on the carbon emission model, thereby predicting the carbon emission amount of the target thermal power plant.
In this embodiment, the standard carbon emission amount refers to a carbon emission maximum threshold and a carbon emission minimum threshold corresponding to the equipment of the target thermal power plant.
In this embodiment, the first comparison refers to comparing the predicted carbon emission amount with the standard carbon emission amount, and the second comparison refers to comparing the real-time carbon emission amount with the standard carbon emission amount.
In this embodiment, the initial monitoring result refers to a carbon emission monitoring result of the target thermal power plant obtained based on the comparison result of the second comparison.
In this embodiment, the comprehensive monitoring result refers to a monitoring result obtained after the initial monitoring result is adjusted according to the comparison result of the first comparison.
In this embodiment, the raw carbon asset distribution refers to the distribution of all carbon assets in the target thermal power plant at each facility.
In this embodiment, the device control parameters refer to parameters for controlling and adjusting the device, where the device control parameters include a temperature control parameter, a pressure control parameter, a flow control parameter, a liquid level control parameter, a speed control parameter, and the like.
The beneficial effects of the technical scheme are as follows: the real-time carbon emission of the thermal power plant is predicted and compared, and the comparison result is combined with the original carbon asset to monitor and adjust the thermal power plant, so that the monitoring of the carbon asset of the thermal power plant is more timely and accurate, and the equipment emission problem can be found more timely and timely adjusted.
Example 2:
based on the embodiment 1, all carbon emission types of the target thermal power plant are obtained, and corresponding real-time carbon emission parameters are obtained based on the carbon emission types, and the real-time carbon emission amount of the target thermal power plant is determined, including:
acquiring power plant equipment parameters of a target thermal power plant, and determining all carbon emission types contained in the target thermal power plant based on the parameter types;
matching corresponding type equipment sensors based on the carbon emission type, and acquiring real-time carbon emission parameters based on the corresponding equipment sensors;
and carrying out parameter processing on the real-time carbon emission parameters, and obtaining the real-time carbon emission of all outlets of the target thermal power plant based on the parameter processing result.
In this embodiment, the device parameters refer to device parameters when the device of the target thermal power plant performs normal power generation operation, such as real-time voltage, power consumption, rotation speed, frequency, and the like of the device.
In this embodiment, the carbon emission type refers to a type of carbon emission performed by a thermal power plant, and for example, the carbon emission type includes direct carbon emission, indirect carbon emission, wherein the indirect carbon emission includes electric power consumption of equipment, production energy consumption, line power consumption, and the like.
In this embodiment, the plant sensor means a sensor capable of monitoring parameters such as a temperature of the plant, a gas discharge amount, a solid discharge amount, and the like.
In this embodiment, the real-time carbon emission parameters refer to emission parameters of carbon emission of the target thermal power plant, wherein the real-time carbon emission parameters include carbon dioxide emission amount, greenhouse gas emission ratio, carbon emission intensity, and equipment average emission amount.
In this embodiment, the real-time carbon emission amount refers to a carbon emission amount obtained by classifying according to the corresponding carbon emission type according to the acquired real-time carbon emission parameter.
The beneficial effects of the technical scheme are as follows: the real-time carbon emission of the thermal power plant is determined, so that the real-time carbon emission of the thermal power plant is predicted and compared, and the thermal power plant is monitored and adjusted by combining the comparison result with the original carbon asset, so that the monitoring of the carbon asset of the thermal power plant is more timely and accurate, and the equipment emission problem can be found more timely and adjusted in time.
Example 3:
based on the embodiment 2, a carbon emission prediction model is constructed based on real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain predicted carbon emission, and a standard carbon emission matched with the target thermal power plant equipment is obtained based on the real-time equipment parameters, and the method comprises the following steps:
extracting core data of real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain first coal parameters and first equipment parameters;
obtaining a corresponding first data fitting curve based on the first coal parameters, and performing curve trend extrapolation according to the curve trend of the first data fitting curve to obtain a second curve;
obtaining a corresponding first equipment fitting curve based on the first equipment parameters;
locking equipment to be analyzed based on data of a non-overlapping part of the second curve and the first data fitting curve and real-time equipment parameters of the target thermal power plant;
performing trend extrapolation on the first equipment fitting curve based on the real-time equipment parameters of the equipment to be analyzed to obtain a third curve;
adjusting the second curve based on the curve trend of the third curve to obtain a second adjustment curve, and performing first prediction of carbon emission on the target thermal power plant based on curve parameters of the second adjustment curve;
Acquiring a first preset weight as a fixed parameter of an initial carbon emission prediction model, and inputting a first coal parameter into the initial carbon emission prediction model to perform carbon emission prediction;
comparing the historical carbon emission of the target thermal power plant with a carbon emission prediction result, calculating a prediction error, and adjusting a first preset weight according to the prediction error to reduce the error;
determining the optimal preset weight as a standard fixed parameter of a carbon emission prediction model through multiple prediction adjustment;
predicting carbon emission based on the standard fixed parameters and the first coal parameters to obtain a second initial prediction result;
adjusting the second initial prediction result by combining the real-time equipment parameters of the target thermal power plant to obtain a second prediction result;
based on the first prediction result and the second prediction result, carrying out simulation, and judging the feasibility of the first prediction result and the second prediction result in practical application;
if the first prediction result and the second prediction result are in the application feasibility range, integrating the first prediction result and the second prediction result to obtain predicted carbon emission;
and simultaneously, acquiring the standard carbon emission matched with the target thermal power plant equipment from a standard database based on the real-time equipment parameters.
In this embodiment, the real-time coal parameters refer to real-time coal consumption parameters of equipment of the target thermal power plant, for example, the real-time coal parameters include coal calorific value, ash, air drying-based gasification amount, and the like.
In this embodiment, the real-time equipment parameter refers to equipment parameters of the target thermal power plant when the equipment performs normal power generation operation, such as real-time voltage, power consumption, rotation speed, frequency, and the like of the equipment.
In this embodiment, the core data refers to data that may have an impact on plant carbon emission monitoring.
In this embodiment, the first coal parameter refers to a parameter obtained by extracting core data of a real-time coal parameter.
In this embodiment, the first device parameter refers to a parameter obtained by extracting core data from a real-time device parameter.
In this embodiment, the first data fitting curve is a curve obtained by performing data fitting according to a first coal parameter, wherein the horizontal axis of the first data fitting curve represents the equipment numbers corresponding to different equipment of the target thermal power plant, and the vertical axis represents the numerical value of the same coal parameter in different equipment of the same equipment working type.
In this embodiment, the second curve is a curve obtained by performing trend extrapolation on two sides of the curve according to the first data fitting curve, wherein a horizontal axis of the second curve represents equipment numbers corresponding to different equipment of the target thermal power plant, and a vertical axis of the second curve represents values of the same coal parameter in different equipment of the same equipment working type, and a non-overlapping portion of the second curve and the first data fitting curve is a portion of the curve obtained by performing trend extrapolation on the first data fitting curve.
In this embodiment, the first device fitting curve refers to a curve obtained after fitting according to the first device parameter.
In this embodiment, the device to be analyzed refers to a device determined by combining data of a portion where the first data fitting curve and the second curve do not overlap with real-time device parameters of the thermal power plant.
In this embodiment, the trend extrapolation refers to extending to two sides of an original curve according to a trend of the curve, determining a curve fixing parameter of the existing curve when extending, and extending the curve according to the curve fixing parameter, where the trend extrapolation is performed on a first equipment fitting curve based on a real-time equipment parameter of the equipment to be analyzed to obtain a third curve, and specifically includes the following steps:
extracting the valley point fitting value and the peak point fitting value of the first equipment fitting curve, averaging to construct a middle horizontal line, averaging according to the valley point fitting value of the first equipment fitting curve to construct a bottom horizontal line, averaging according to the peak point fitting value of the first equipment fitting curve, and constructing a top horizontal line;
obtaining a minimum fitting value in a fitting curve of the first equipment, constructing a first reference horizontal line, obtaining a maximum fitting value in the fitting curve of the first equipment, and constructing a second reference horizontal line;
Calculating the head-tail interception length of the fitting curve of the first equipment according to the number of the valley point fitting values and the number of the peak point fitting values;
the method comprises the steps of carrying out a first treatment on the surface of the Wherein J1 represents a head-to-tail interception length; />Representing the length of a curve segment between two adjacent points; />Representing the total number of peak points and valley points; />Representing the total curve segment number of a first equipment fitting curve formed by two adjacent points; />Indicating all->The length of the longest curve segment;
according to the head intercepting length, intercepting head and tail line segments of a first equipment fitting line, and according to the position connecting sequences of the intercepted line segments and a top horizontal line, a middle horizontal line, a bottom horizontal line, a first reference horizontal line and a second reference horizontal line;
when a connection relation exists, setting the sequence value of the corresponding horizontal line and the intercepted line segment to be 1, otherwise, setting the sequence value to be 0;
according to the position connection sequence, locking the horizontal line with the sequence value of 1 to obtain a locking point corresponding to the intercepted line segment, regarding the position extension length based on the distance between the central point of a closed area surrounded by the tangent line of each locking point and the corresponding outermost locking point, and according to the rule of the line segment corresponding to the intercepted line segment, performing curve change on the position extension length to realize the head-tail curve extension of the fitting curve of the first equipment.
As shown in fig. 4, for example, a01, a02, a03, a04 and a05 respectively represent a top horizontal line, a middle horizontal line, a bottom horizontal line, a first reference horizontal line and a second reference horizontal line, taking a first line segment as an example of a cut line segment, and r01 as a first line segment, at this time, three locking points 01, 02 and 03 respectively exist, and when the surrounding area is r02, if other conditions exist, for example, the tangential lines corresponding to the three points are not on one horizontal line, at this time, the horizontal lines corresponding to the three points are closed in a closed loop in the vertical direction, so that a closed area can be obtained, and the closed loop seal is obtained by sealing based on the two outermost locking points as a vertical line.
In this embodiment, there are 5 elements in the position-join sequence, such as: {0 1 1 1 0}.
In this embodiment, the respective outermost locking point refers to: when the intercepted line is the first line, the outermost locking point is the leftmost locking point; when the intercepted line segment is a tail line segment, the outermost locking point is the rightmost locking point.
In the embodiment, the curve change is obtained by inputting a rule of a line segment into a curve analysis model for analysis and finally obtaining a changed curve, wherein the model is trained in advance and can be directly obtained by analysis.
In this embodiment, the third curve refers to a curve obtained by performing trend extrapolation on the first device fitting curve based on the real-time device parameters of the device to be analyzed.
In this embodiment, the second adjustment curve refers to a curve obtained by adjusting the second curve according to a curve trend of the third curve.
In this embodiment, the first prediction refers to predicting the carbon emission of the target thermal power plant based on each curve parameter on the second adjustment curve.
In this embodiment, the curve parameter refers to a parameter value corresponding to each first coal parameter corresponding to the parameter type on the second adjustment curve.
In this embodiment, the first preset weight is determined according to the influence weight of the carbon emission amount of the different equipment carbon emission amounts and the carbon emission amounts of the different carbon emission types required for constructing the initial carbon emission model on the carbon emission amount of the target thermal power plant.
In this embodiment, the initial carbon emission prediction model refers to a carbon emission prediction model obtained based on a first preset weight as a fixed parameter of the carbon emission medical model.
In this embodiment, the historical carbon emission amount refers to the carbon emission amount generated during the historical operation of the target thermal power plant.
In this embodiment, the prediction error refers to an error between each of the historical carbon emissions and the corresponding carbon emission prediction result.
In this embodiment, the optimal preset weight is a weight with the highest matching degree with the carbon emission prediction model obtained by continuously adjusting the first preset weight.
In this embodiment, the standard fixed parameter refers to the optimal preset weight as the fixed parameter of the carbon emission prediction model.
In this embodiment, the second initial prediction result refers to a standard fixed parameter as a fixed parameter of the carbon emission prediction model, and the first coal parameter is input into the carbon emission prediction model to predict the carbon emission amount.
In this embodiment, the second prediction result refers to a prediction result obtained by adjusting the second initial prediction result according to the historical carbon emission amount of the target thermal power plant.
In this embodiment, the application feasibility refers to that the first prediction result and the second prediction result are respectively simulated, and the feasibility of the first prediction result and the second prediction result in actual work is determined.
In this embodiment, predicting the carbon emission amount means obtaining the carbon emission amount of each device based on the carbon emission model, thereby predicting the carbon emission amount of the target thermal power plant.
In this embodiment, the standard carbon emission amount refers to a carbon emission maximum threshold and a carbon emission minimum threshold corresponding to the equipment of the target thermal power plant.
The beneficial effects of the technical scheme are as follows: the carbon emission of the thermal power plant is predicted in various modes, and the carbon emission of the thermal power plant is compared according to the prediction results, so that the monitoring of the carbon asset of the thermal power plant can be more timely and accurate.
Example 4:
based on the example 3, a first comparison of the predicted carbon emission amount with the standard carbon emission amount, and a second comparison of the real-time carbon emission amount with the standard carbon emission amount, comprising:
comparing the predicted carbon emission amount with a carbon emission maximum threshold value and a carbon emission minimum threshold value of the target thermal power plant in real time;
if the predicted carbon emission is outside the range of the carbon emission maximum threshold and the carbon emission minimum threshold, the carbon emission is predicted again;
if the real-time carbon emission is out of the range of the carbon emission maximum threshold and the carbon emission minimum threshold, judging that equipment of the current target thermal power plant fails and carrying out early warning;
if the predicted and real-time carbon emissions are between the carbon emission maximum and minimum thresholds, the predicted and standard carbon emissions are first compared and the real-time and standard carbon emissions are second compared.
In this embodiment, predicting the carbon emission amount refers to obtaining the carbon emission amount of each device based on the carbon emission model, thereby predicting the carbon emission amount of the target thermal power plant.
In this embodiment, the real-time carbon emission amount refers to a carbon emission amount obtained by classifying according to the corresponding carbon emission type according to the acquired real-time carbon emission parameter.
In this embodiment, the highest carbon emission threshold refers to the highest value of carbon emission by the current plant, and the lowest carbon emission threshold refers to the lowest value of carbon emission by the current plant, wherein the highest and lowest carbon emission thresholds include the carbon emission amount of the direct plant and the indirect carbon emission amount.
In this embodiment, the first comparison refers to comparing the predicted carbon emission amount with the standard carbon emission amount, and the second comparison refers to comparing the real-time carbon emission amount with the standard carbon emission amount.
The beneficial effects of the technical scheme are as follows: the real-time carbon emission of the thermal power plant is compared, so that the comparison result is combined with the original carbon asset to monitor and adjust the thermal power plant, and the monitoring of the carbon asset of the thermal power plant can be more timely and accurate.
Example 5:
based on the embodiment 4, an initial monitoring result of the target thermal power plant is obtained based on the second comparison result, and the initial monitoring result is adjusted based on the first comparison result, so as to obtain a comprehensive monitoring result, as shown in fig. 2, including:
Inputting a second comparison result of the real-time carbon emission and the standard carbon emission into a comparison monitoring data table, and classifying according to the comparison result of the real-time carbon emission and the standard carbon emission;
if the real-time carbon emission is larger than the standard carbon emission, extracting a corresponding comparison result to obtain a first monitoring data table;
otherwise, extracting a corresponding comparison result to obtain a second monitoring data table;
synthesizing based on the comparison result values of the first monitoring data table and the second monitoring data table and the influence weights of the corresponding data to obtain an initial monitoring result of the target thermal power plant;
obtaining a third monitoring data table and a fourth monitoring data table based on the first comparison result;
respectively performing third comparison and fourth comparison on the data characteristics and the data values of the first monitoring data table and the third monitoring data table, and the second monitoring data table and the fourth monitoring data table;
and adjusting the initial monitoring result based on the results of the third comparison and the fourth comparison to obtain the comprehensive monitoring result of the target thermal power plant.
In this embodiment, the comparison monitoring data table refers to a data table including the real-time carbon emission amount, the standard carbon emission amount, and the comparison result of the real-time carbon emission amount and the standard carbon emission amount, wherein the comparison result of the standard carbon emission amount and the real-time carbon emission amount may be negative or positive, and the comparison results should be uniform, for example, the standard carbon emission amount minus the real-time carbon emission amount.
In this embodiment, the first monitoring data table refers to a data table obtained by extracting a comparison result corresponding to a real-time carbon emission amount greater than a standard carbon emission amount from comparison results of the comparison monitoring data table. The second monitoring data table is a data table obtained by extracting a comparison result corresponding to the comparison result that the real-time carbon emission is not more than the standard carbon emission in the comparison result of the comparison monitoring data table.
In this embodiment, the initial monitoring result is a monitoring result obtained by integrating the impact weight of the corresponding data on the equipment monitoring based on the result value of the comparison result of the first monitoring data table and the second monitoring data table.
In this embodiment, the third monitoring data table refers to a data table obtained by comparing the predicted carbon emission amount with the standard carbon emission amount, and extracting the comparison result in which the predicted carbon emission amount is larger than the standard carbon emission amount from the comparison result. The fourth monitoring data table is a data table obtained by comparing the predicted carbon emission amount with the standard carbon emission amount, and extracting the comparison result that the predicted carbon emission amount is not more than the standard carbon emission amount from the comparison result.
In this embodiment, the third comparison is to compare the corresponding data values in the first and third tables, and the fourth comparison is to compare the corresponding data values in the second and fourth tables.
In this embodiment, the integrated monitoring result refers to a monitoring result obtained by replacing or adjusting a data value in the corresponding initial monitoring result according to a data value in which an error exceeds a preset error in the comparison result of the third comparison and the fourth comparison.
The beneficial effects of the technical scheme are as follows: through adjusting the monitoring comparison result, the monitoring of the carbon asset of the thermal power plant can be more timely and accurate, and the equipment emission problem can be found more timely and timely adjusted.
Example 6:
based on embodiment 5, a third comparison of the data characteristics and the data values of the first and third monitoring data tables includes:
acquiring data characteristics of monitoring data in the first monitoring data table and the third monitoring data table, and corresponding the monitoring data in the first monitoring data table and the third monitoring data table one by one based on the data characteristics;
and comparing the data errors of the corresponding monitoring data based on the corresponding results one by one to obtain a third comparison result.
In this embodiment, the data characteristics of the monitoring data refer to the data type and data capacity of each monitoring data in the first monitoring data table and the third monitoring data table.
In this embodiment, the third comparison result is a comparison result obtained by comparing the corresponding data values in the first monitoring data table and the third monitoring data table.
The beneficial effects of the technical scheme are as follows: the real-time carbon emission, the predicted carbon emission and the standard carbon emission of the thermal power plant are compared, so that the comparison result is combined with the original carbon asset to monitor and adjust the thermal power plant, and the monitoring of the thermal power plant carbon asset can be more timely and accurate.
Example 7:
based on embodiment 5, the carbon emission result of the target thermal power plant is determined based on the comprehensive monitoring result, and the thermal power plant equipment and equipment control parameters to be controlled are determined based on the original carbon asset distribution, so as to realize equipment control, including:
judging a carbon emission result of the target thermal power plant based on the comprehensive monitoring result, and determining a carbon emission level of the target thermal power plant based on the judging result;
comprehensively determining the coal resource utilization condition of the target thermal power plant based on the carbon emission level and the carbon assets of the corresponding part;
determining equipment numbers and positions of the target thermal power plant, which need to control the carbon assets, based on the original carbon asset distribution and the coal resource utilization condition, and determining equipment control conditions of corresponding equipment;
And determining equipment control parameters of corresponding equipment based on the equipment control conditions, and controlling the corresponding equipment based on the equipment control parameters, so as to realize carbon asset monitoring control of the target thermal power plant.
In this embodiment, the carbon emission level refers to the level of direct and indirect carbon emission of the device, and the higher the level, the higher the corresponding direct and indirect carbon emission levels, which indicates that the device may malfunction or have a problem of excessively consuming energy.
In this embodiment, the carbon asset refers to the input carbon quantity of the device.
In this embodiment, the coal resource utilization is determined based on the ratio of the target plant input carbon quantity to the carbon emission quantity.
In this embodiment, the device control condition refers to a critical condition under which the device performs control adjustment.
In this embodiment, the device control parameters refer to parameters for controlling and adjusting the device, where the device control parameters include a temperature control parameter, a pressure control parameter, a flow control parameter, a liquid level control parameter, a speed control parameter, and the like.
The beneficial effects of the technical scheme are as follows: the carbon emission of the thermal power plant is predicted and compared, and the comparison result is combined with the original carbon asset to monitor and adjust the thermal power plant, so that the monitoring of the carbon asset of the thermal power plant is more timely and accurate.
Example 8:
the embodiment of the invention provides a monitoring and controlling system for carbon assets of a thermal power plant, as shown in fig. 3, comprising:
emission determination module: the method comprises the steps of acquiring all carbon emission types of a target thermal power plant, acquiring corresponding real-time coal parameters based on the carbon emission types, and determining the real-time carbon emission amount of the target thermal power plant;
emission prediction module: the method comprises the steps of constructing a carbon emission prediction model based on real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain predicted carbon emission, and obtaining standard carbon emission matched with the target thermal power plant based on the real-time equipment parameters;
emission comparison module: for first comparing the predicted carbon emission with the standard carbon emission and second comparing the real-time carbon emission with the standard carbon emission;
and the comprehensive monitoring module is used for: the method comprises the steps of obtaining an initial monitoring result of a target thermal power plant based on a second comparison result, and adjusting the initial monitoring result based on a first comparison result to obtain a comprehensive monitoring result;
and the monitoring control module: and the device is used for judging the carbon emission result of the target thermal power plant based on the comprehensive monitoring result, determining the thermal power plant equipment and equipment control parameters required to be controlled based on the original carbon asset distribution, and realizing equipment control.
The beneficial effects of the technical scheme are as follows: the real-time carbon emission of the thermal power plant is predicted and compared, and the comparison result is combined with the original carbon asset to monitor and adjust the thermal power plant, so that the monitoring of the carbon asset of the thermal power plant is more timely and accurate, and the equipment emission problem can be found more timely and timely adjusted.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A method for monitoring and controlling carbon assets of a thermal power plant, comprising the steps of:
step 1: acquiring all carbon emission types of the target thermal power plant, acquiring corresponding real-time carbon emission parameters based on the carbon emission types, and determining the real-time carbon emission amount of the target thermal power plant;
step 2: constructing a carbon emission prediction model based on real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain predicted carbon emission, and acquiring standard carbon emission matched with the target thermal power plant equipment based on the real-time equipment parameters;
Step 3: first comparing the predicted carbon emission with the standard carbon emission, and second comparing the real-time carbon emission with the standard carbon emission;
step 4: obtaining an initial monitoring result of the target thermal power plant based on the second comparison result, and adjusting the initial monitoring result based on the first comparison result to obtain a comprehensive monitoring result;
step 5: judging a carbon emission result of the target thermal power plant based on the comprehensive monitoring result, and determining thermal power plant equipment and equipment control parameters to be controlled based on the original carbon asset distribution to realize equipment control;
wherein, step 2 includes:
extracting core data of real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain first coal parameters and first equipment parameters;
obtaining a corresponding first data fitting curve based on the first coal parameters, and performing curve trend extrapolation according to the curve trend of the first data fitting curve to obtain a second curve;
obtaining a corresponding first equipment fitting curve based on the first equipment parameters;
locking equipment to be analyzed based on data of a non-overlapping part of the second curve and the first data fitting curve and real-time equipment parameters of the target thermal power plant;
Performing trend extrapolation on the first equipment fitting curve based on the real-time equipment parameters of the equipment to be analyzed to obtain a third curve;
adjusting the second curve based on the curve trend of the third curve to obtain a second adjustment curve, and performing first prediction of carbon emission on the target thermal power plant based on curve parameters of the second adjustment curve;
predicting carbon emission according to the standard fixed parameters of the carbon emission prediction model and the first coal parameters, and adjusting by combining with real-time equipment parameters of the target thermal power plant to obtain a second prediction result;
integrating the first prediction result and the second prediction result to obtain predicted carbon emission;
and simultaneously, acquiring the standard carbon emission matched with the target thermal power plant equipment from a standard database based on the real-time equipment parameters.
2. The method for monitoring and controlling carbon assets of a thermal power plant according to claim 1, wherein obtaining all carbon emission types of the target thermal power plant, and obtaining corresponding real-time carbon emission parameters based on the carbon emission types, determining the real-time carbon emission amount of the target thermal power plant, comprises:
acquiring power plant equipment parameters of a target thermal power plant, and determining all carbon emission types contained in the target thermal power plant based on the parameter types;
Matching corresponding type equipment sensors based on the carbon emission type, and acquiring real-time carbon emission parameters based on the corresponding equipment sensors;
and carrying out parameter processing on the real-time carbon emission parameters, and obtaining the real-time carbon emission of all outlets of the target thermal power plant based on the parameter processing result.
3. A method of monitoring and controlling a thermal power plant carbon asset according to claim 2, wherein the first comparing the predicted carbon emission with the standard carbon emission and the second comparing the real-time carbon emission with the standard carbon emission comprises:
comparing the predicted carbon emission amount with a carbon emission maximum threshold value and a carbon emission minimum threshold value of the target thermal power plant in real time;
if the predicted carbon emission is outside the range of the carbon emission maximum threshold and the carbon emission minimum threshold, the carbon emission is predicted again;
if the real-time carbon emission is out of the range of the carbon emission maximum threshold and the carbon emission minimum threshold, judging that equipment of the current target thermal power plant fails and carrying out early warning;
if the predicted and real-time carbon emissions are between the carbon emission maximum and minimum thresholds, the predicted and standard carbon emissions are first compared and the real-time and standard carbon emissions are second compared.
4. A method for monitoring and controlling carbon assets in a thermal power plant according to claim 3, wherein obtaining an initial monitoring result of a target thermal power plant based on the second comparison result, and adjusting the initial monitoring result based on the first comparison result to obtain a comprehensive monitoring result, comprises:
inputting a second comparison result of the real-time carbon emission and the standard carbon emission into a comparison monitoring data table, and classifying according to the comparison result of the real-time carbon emission and the standard carbon emission;
if the real-time carbon emission is larger than the standard carbon emission, extracting a corresponding comparison result to obtain a first monitoring data table;
otherwise, extracting a corresponding comparison result to obtain a second monitoring data table;
synthesizing based on the comparison result values of the first monitoring data table and the second monitoring data table and the influence weights of the corresponding data to obtain an initial monitoring result of the target thermal power plant;
obtaining a third monitoring data table and a fourth monitoring data table based on the first comparison result;
respectively performing third comparison and fourth comparison on the data characteristics and the data values of the first monitoring data table and the third monitoring data table, and the second monitoring data table and the fourth monitoring data table;
And adjusting the initial monitoring result based on the results of the third comparison and the fourth comparison to obtain the comprehensive monitoring result of the target thermal power plant.
5. The method for monitoring and controlling carbon assets of a thermal power plant according to claim 4, wherein the third comparison of the data characteristics and the data values of the first and third monitoring data tables includes:
acquiring data characteristics of monitoring data in the first monitoring data table and the third monitoring data table, and corresponding the monitoring data in the first monitoring data table and the third monitoring data table one by one based on the data characteristics;
and comparing the data errors of the corresponding monitoring data based on the corresponding results one by one to obtain a third comparison result.
6. The method for monitoring and controlling carbon assets in a thermal power plant according to claim 4, wherein the method for determining carbon emission results of a target thermal power plant based on comprehensive monitoring results and determining thermal power plant equipment and equipment control parameters to be controlled based on original carbon asset distribution to realize equipment control comprises the following steps:
judging a carbon emission result of the target thermal power plant based on the comprehensive monitoring result, and determining a carbon emission level of the target thermal power plant based on the judging result;
Comprehensively determining the coal resource utilization condition of the target thermal power plant based on the carbon emission level and the carbon assets of the corresponding part;
determining equipment numbers and positions of the target thermal power plant, which need to control the carbon assets, based on the original carbon asset distribution and the coal resource utilization condition, and determining equipment control conditions of corresponding equipment;
and determining equipment control parameters of corresponding equipment based on the equipment control conditions, and controlling the corresponding equipment based on the equipment control parameters, so as to realize carbon asset monitoring control of the target thermal power plant.
7. The method for monitoring and controlling carbon assets in a thermal power plant according to claim 1, wherein predicting carbon emissions according to standard fixed parameters of a carbon emission prediction model and first coal parameters, and adjusting in combination with real-time equipment parameters of a target thermal power plant, to obtain a second prediction result, comprises:
acquiring a first preset weight as a fixed parameter of an initial carbon emission prediction model, and inputting a first coal parameter into the initial carbon emission prediction model to perform carbon emission prediction;
comparing the historical carbon emission of the target thermal power plant with a carbon emission prediction result, calculating a prediction error, and adjusting a first preset weight according to the prediction error to reduce the error;
Determining the optimal preset weight as a standard fixed parameter of a carbon emission prediction model through multiple prediction adjustment;
predicting carbon emission based on the standard fixed parameters and the first coal parameters to obtain a second initial prediction result;
and adjusting the second initial prediction result by combining the real-time equipment parameters of the target thermal power plant to obtain a second prediction result.
8. The method for monitoring and controlling carbon asset in thermal power plant according to claim 7, wherein before integrating the first prediction result and the second prediction result, the method comprises:
based on the first prediction result and the second prediction result, carrying out simulation, and judging the feasibility of the first prediction result and the second prediction result in practical application;
and if the first prediction result and the second prediction result are in the application feasibility range, integrating the first prediction result and the second prediction result.
9. The method for monitoring and controlling carbon assets in a thermal power plant according to claim 1, wherein trend extrapolation is performed on the first equipment fitting curve based on the real-time equipment parameters of the equipment to be analyzed to obtain a third curve, including:
extracting the valley point fitting value and the peak point fitting value of the first equipment fitting curve, averaging to construct a middle horizontal line, averaging according to the valley point fitting value of the first equipment fitting curve to construct a bottom horizontal line, averaging according to the peak point fitting value of the first equipment fitting curve, and constructing a top horizontal line;
Obtaining a minimum fitting value in a fitting curve of the first equipment, constructing a first reference horizontal line, obtaining a maximum fitting value in the fitting curve of the first equipment, and constructing a second reference horizontal line;
calculating the head-tail interception length of the fitting curve of the first equipment according to the number of the valley point fitting values and the number of the peak point fitting values;
the method comprises the steps of carrying out a first treatment on the surface of the Wherein J1 represents a head-to-tail interception length; />Representing the length of a curve segment between two adjacent points; />Representing the total number of peak points and valley points; />Representing the total curve segment number of a first equipment fitting curve formed by two adjacent points; />Indicating all->The length of the longest curve segment;
according to the head intercepting length, intercepting head and tail line segments of a first equipment fitting line, and according to the position connecting sequences of the intercepted line segments and a top horizontal line, a middle horizontal line, a bottom horizontal line, a first reference horizontal line and a second reference horizontal line;
when a connection relation exists, setting the sequence value of the corresponding horizontal line and the intercepted line segment to be 1, otherwise, setting the sequence value to be 0;
according to the position connection sequence, locking the horizontal line with the sequence value of 1 to obtain a locking point corresponding to the intercepted line segment, regarding the position extension length based on the distance between the central point of a closed area surrounded by the tangent line of each locking point and the corresponding outermost locking point, and according to the rule of the line segment corresponding to the intercepted line segment, performing curve change on the position extension length to realize the head-tail curve extension of the fitting curve of the first equipment.
10. A monitoring control system for a thermal power plant carbon asset, comprising:
emission determination module: the method comprises the steps of acquiring all carbon emission types of a target thermal power plant, acquiring corresponding real-time coal parameters based on the carbon emission types, and determining the real-time carbon emission amount of the target thermal power plant;
emission prediction module: the method comprises the steps of constructing a carbon emission prediction model based on real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain predicted carbon emission, and obtaining standard carbon emission matched with the target thermal power plant based on the real-time equipment parameters;
emission comparison module: for first comparing the predicted carbon emission with the standard carbon emission and second comparing the real-time carbon emission with the standard carbon emission;
and the comprehensive monitoring module is used for: the method comprises the steps of obtaining an initial monitoring result of a target thermal power plant based on a second comparison result, and adjusting the initial monitoring result based on a first comparison result to obtain a comprehensive monitoring result;
and the monitoring control module: the method is used for judging the carbon emission result of the target thermal power plant based on the comprehensive monitoring result, determining thermal power plant equipment and equipment control parameters required to be controlled based on the original carbon asset distribution, and realizing equipment control;
Wherein, emission prediction module is used for:
extracting core data of real-time coal parameters and real-time equipment parameters of a target thermal power plant to obtain first coal parameters and first equipment parameters;
obtaining a corresponding first data fitting curve based on the first coal parameters, and performing curve trend extrapolation according to the curve trend of the first data fitting curve to obtain a second curve;
obtaining a corresponding first equipment fitting curve based on the first equipment parameters;
locking equipment to be analyzed based on data of a non-overlapping part of the second curve and the first data fitting curve and real-time equipment parameters of the target thermal power plant;
performing trend extrapolation on the first equipment fitting curve based on the real-time equipment parameters of the equipment to be analyzed to obtain a third curve;
adjusting the second curve based on the curve trend of the third curve to obtain a second adjustment curve, and performing first prediction of carbon emission on the target thermal power plant based on curve parameters of the second adjustment curve;
predicting carbon emission according to the standard fixed parameters of the carbon emission prediction model and the first coal parameters, and adjusting by combining with real-time equipment parameters of the target thermal power plant to obtain a second prediction result;
Integrating the first prediction result and the second prediction result to obtain predicted carbon emission;
and simultaneously, acquiring the standard carbon emission matched with the target thermal power plant equipment from a standard database based on the real-time equipment parameters.
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