Cooperative pollutant removal operation control method and system for coal-fired power plant

Abstract

The invention discloses a pollutant collaborative removal operation control method and system for a coal-fired power plant. The method comprises the steps of obtaining and preprocessing historical operation data of the coal-fired power plant; the preprocessed historical operation data are analyzed, and influence factors influencing the collaborative removal efficiency of the coal-fired power plant pollutants are determined; constructing a removal efficiency prediction model based on the influence factors, and obtaining removal efficiency prediction data according to prediction of the removal efficiency prediction model; obtaining a removal efficiency requirement, and determining the removal efficiency prediction data and difference characteristics thereof; evaluating the removal condition of the coal-fired power plant based on the characteristics to obtain a removal evaluation value, and determining an operation adjustment coefficient of the coal-fired power plant according to the removal evaluation value; and adjusting the real-time operation data of the coal-fired power plant according to the operation adjustment coefficient, and controlling the cooperative removal of pollutants of the coal-fired power plant according to the adjusted real-time operation data. According to the method, cooperative removal of pollutants can be controlled more efficiently and more accurately, the environmental protection level of the coal-fired power plant is improved, and a more scientific decision basis is provided for operation of the coal-fired power plant.

Description

Technical Field

[0001] The present invention relates to the field of coal-fired power plant control technology, and in particular to a pollutant coordinated removal operation control method and system for a coal-fired power plant. Background Art

[0002] As an important part of energy production, coal-fired power plants emit a large amount of pollutants in their flue gas, including sulfur dioxide, nitrogen oxides and particulate matter, which have serious impacts on the environment and human health. In order to reduce the impact of these harmful emissions on the environment, coal-fired power plants usually adopt pollutant synergistic removal technology. Pollutant synergistic removal refers to the comprehensive treatment of various pollutants generated during the combustion process to achieve the purpose of reducing emission concentrations and improving removal efficiency.

[0003] However, traditional pollutant synergistic removal operation control methods usually adopt static parameter settings and control strategies, which are unable to adjust the operating status and environmental requirements of coal-fired power plants in real time and dynamically, resulting in inflexible and inaccurate control effects. At the same time, traditional methods lack intelligence and adaptability, and are unable to perform intelligent regulation based on the actual operating data of coal-fired power plants, making it difficult to achieve the best pollutant synergistic removal effects. In addition, traditional methods have a low degree of utilization of real-time operating data, and are unable to fully mine the potential information in the data, making it difficult to discover potential problems and room for improvement in operation. Moreover, traditional methods have a slow control response speed and are unable to respond to emergencies and environmental changes in a timely manner, affecting the environmental performance and stability of coal-fired power plants. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a method and system for coordinated pollutant removal operation control of a coal-fired power plant, comprising:

[0005] Obtain historical operation data of coal-fired power plants and pre-process the historical operation data of coal-fired power plants;

[0006] Analyze the historical operation data after pretreatment to determine the factors affecting the efficiency of synergistic removal of pollutants in coal-fired power plants;

[0007] Based on the influencing factors, a removal efficiency prediction model of a coal-fired power plant is constructed, and prediction is performed according to the removal efficiency prediction model of the coal-fired power plant to obtain the removal efficiency prediction data of the coal-fired power plant;

[0008] Obtain the removal efficiency requirements of coal-fired power plants for the coordinated removal of pollutants, and determine the difference characteristics between the removal efficiency prediction data of coal-fired power plants and the removal efficiency requirements;

[0009] Analyze and evaluate the removal status of coal-fired power plants based on the difference characteristics, obtain the removal evaluation value of the coal-fired power plants, and determine the operation adjustment coefficient of the coal-fired power plants according to the removal evaluation value;

[0010] The real-time operation data of the coal-fired power plant is adjusted according to the operation adjustment coefficient, and the coordinated removal of pollutants in the coal-fired power plant is controlled according to the adjusted real-time operation data.

[0011] Furthermore, the preprocessing of the historical operation data of the coal-fired power plant includes:

[0012] The historical operation data of the coal-fired power plant is preprocessed, which includes removing abnormal data and overloaded data in the historical operation data of the coal-fired power plant and filling in missing data, and standardizing the historical operation data of the coal-fired power plant.

[0013] Furthermore, the analysis of the historical operation data after pretreatment to determine the factors affecting the synergistic removal efficiency of pollutants in coal-fired power plants includes:

[0014] Acquire pre-processed historical operation data of the coal-fired power plant, and divide the historical operation data of the coal-fired power plant into several groups of operation parameter data groups according to parameter types;

[0015] Obtain pollutant synergistic removal efficiency data of coal-fired power plants, analyze the correlation between each set of operating parameter data and the pollutant synergistic removal efficiency data, and select the operating parameter data sets whose correlation exceeds a preset threshold;

[0016] The parameter corresponding to the selected operating parameter data group is determined, and the parameter is determined as an influencing factor affecting the removal efficiency of the coal-fired power plant.

[0017] Furthermore, the removal efficiency prediction model of the coal-fired power plant is constructed based on the influencing factors, and the removal efficiency of the coal-fired power plant is predicted according to the removal efficiency prediction model of the coal-fired power plant to obtain the pollutant removal efficiency prediction data of the coal-fired power plant, including:

[0018] A data set is constructed based on the influencing factors, and the data set is input into a preset neural network model to construct an initial model for predicting removal efficiency;

[0019] The data set is divided into a training set and a test set according to a certain ratio, and the training set and the test set are input into the initial model for prediction of removal efficiency;

[0020] The removal efficiency prediction initial model is trained and tested until the removal efficiency prediction initial model meets the preset convergence condition, thereby obtaining the removal efficiency prediction model;

[0021] The pollutant removal efficiency prediction data of coal-fired power plants in the future are predicted based on the obtained removal efficiency prediction model.

[0022] Furthermore, obtaining the removal efficiency requirements of the coal-fired power plant for the coordinated removal of pollutants and determining the difference characteristics between the removal efficiency prediction data of the coal-fired power plant and the removal efficiency requirements include:

[0023] Obtain the removal efficiency requirements of coal-fired power plants for the coordinated removal of pollutants, and perform a difference calculation between each data in the removal efficiency prediction data and the removal efficiency requirements to obtain efficiency deviation data;

[0024] These efficiency deviation data are plotted into an efficiency deviation curve according to the time sequence, and the peak value and the trough value are determined from the efficiency deviation curve;

[0025] Based on the peak value and the trough value, determine the descending curve segment corresponding to each peak value to the trough value and the ascending curve segment corresponding to each trough value to the peak value, and obtain the duration corresponding to the descending curve segment and the ascending curve segment;

[0026] Calculate the slopes of the descending curve segment and the ascending curve segment to obtain the descending slope and the ascending slope respectively;

[0027] The duration corresponding to the descending curve segment and the ascending curve segment as well as the descending slope and the ascending slope are determined as the difference characteristics between the removal efficiency prediction data of the coal-fired power plant and the removal efficiency requirements.

[0028] Furthermore, the removal situation of the coal-fired power plant is analyzed and evaluated based on the difference characteristics to obtain the removal evaluation value of the coal-fired power plant, including:

[0029] Obtain the duration of the efficiency deviation curve, and calculate the ratio between the duration corresponding to the descending curve segment and the ascending curve segment and the duration of the efficiency deviation curve, and use the ratio as the weight of each corresponding curve segment;

[0030] Calculate the average value of the slopes of all curve segments, perform a difference calculation between each curve segment and the average value to obtain a difference value corresponding to each curve segment, and evaluate and value the difference value corresponding to each curve segment to obtain an evaluation value of each curve segment;

[0031] The evaluation value of each curve segment and the weight of each curve segment are weighted and added together to obtain the removal assessment value of the coal-fired power plant.

[0032] Furthermore, determining the operation adjustment coefficient of the coal-fired power plant according to the removal evaluation value includes:

[0033] The operation adjustment coefficient-removal evaluation value interval correspondence relationship is preset, and the operation adjustment coefficient-removal evaluation value interval correspondence relationship is associated with a corresponding operation adjustment coefficient for each removal evaluation value interval;

[0034] A removal evaluation value is obtained, and based on the mapping relationship between the removal evaluation value interval to which the difference belongs and the operation adjustment coefficient corresponding to the removal evaluation value interval, an operation adjustment coefficient corresponding to the removal evaluation value interval is selected.

[0035] The present invention also provides a pollutant collaborative removal operation control system for a coal-fired power plant, comprising:

[0036] An acquisition module is used to acquire historical operation data of the coal-fired power plant and pre-process the historical operation data of the coal-fired power plant;

[0037] The analysis module is used to analyze the historical operation data after pretreatment and determine the factors affecting the efficiency of the synergistic removal of pollutants in coal-fired power plants;

[0038] A prediction module is used to construct a removal efficiency prediction model of a coal-fired power plant based on influencing factors, and to make predictions based on the removal efficiency prediction model of the coal-fired power plant to obtain removal efficiency prediction data of the coal-fired power plant;

[0039] A determination module is used to obtain the removal efficiency requirements of the coal-fired power plant for the coordinated removal of pollutants, and to determine the difference characteristics between the removal efficiency prediction data of the coal-fired power plant and the removal efficiency requirements;

[0040] An evaluation module is used to analyze and evaluate the removal status of the coal-fired power plant based on the difference characteristics, obtain the removal evaluation value of the coal-fired power plant, and determine the operation adjustment coefficient of the coal-fired power plant according to the removal evaluation value;

[0041] The regulation module is used to adjust the real-time operation data of the coal-fired power plant according to the operation regulation coefficient, and control the coordinated removal of pollutants in the coal-fired power plant according to the adjusted real-time operation data.

[0042] Compared with the prior art, the pollutant coordinated removal operation control method and system of a coal-fired power plant in the embodiment of the present invention has the following beneficial effects:

[0043] The present invention can ensure the quality and accuracy of data by cleaning and preprocessing historical operation data, thereby providing a reliable basis for subsequent analysis and modeling;

[0044] By analyzing the influencing factors, the present invention can deeply understand the key influencing factors of the synergistic removal efficiency of pollutants in coal-fired power plants, and provide an important basis for subsequent model construction and optimization;

[0045] The present invention constructs a removal efficiency prediction model to enable coal-fired power plants to predict future removal efficiency based on actual operating conditions, thereby making targeted adjustments and optimizations.

[0046] By comparing the removal efficiency requirements and the predicted data, the present invention can clearly understand the gap between the actual removal efficiency and the standard requirements, providing a basis for subsequent improvements;

[0047] By determining the removal evaluation value and the operation adjustment coefficient, the present invention can enable managers to better understand the removal situation of coal-fired power plants and formulate corresponding control measures;

[0048] The present invention can enable a coal-fired power plant to respond to actual operating conditions more flexibly through the adjustment of real-time operating data, thereby achieving control over the coordinated removal of pollutants. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the flow structure of the pollutant coordinated removal operation control method of a coal-fired power plant in an embodiment of the present invention;

[0050] Figure 2 It is a schematic diagram of the composition of the pollutant coordinated removal operation control system of a coal-fired power plant in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0052] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the platform or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0053] The terms "second" and "second" are used for descriptive purposes only and should not be understood as indicating or implying a relative degree of importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined with "second" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "multiple" means two or more.

[0054] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technical personnel in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0055] like Figure 1 As shown, in an embodiment of the present application, a pollutant collaborative removal operation control method for a coal-fired power plant is provided, comprising: S100: acquiring historical operation data of the coal-fired power plant, and preprocessing the historical operation data of the coal-fired power plant; S200: analyzing the preprocessed historical operation data to determine the influencing factors that affect the efficiency of the collaborative removal of pollutants in the coal-fired power plant; S300: constructing a removal efficiency prediction model for the coal-fired power plant based on the influencing factors, and performing prediction according to the removal efficiency prediction model of the coal-fired power plant to obtain the removal efficiency prediction of the coal-fired power plant. S400: obtaining the removal efficiency requirements of the coal-fired power plant for the coordinated removal of pollutants, and determining the difference characteristics between the removal efficiency prediction data of the coal-fired power plant and the removal efficiency requirements; S500: analyzing and evaluating the removal situation of the coal-fired power plant based on the difference characteristics, obtaining the removal evaluation value of the coal-fired power plant, and determining the operation adjustment coefficient of the coal-fired power plant according to the removal evaluation value; S600: adjusting the real-time operation data of the coal-fired power plant according to the operation adjustment coefficient, and controlling the coordinated removal of pollutants of the coal-fired power plant according to the adjusted real-time operation data.

[0056] Furthermore, the present invention can ensure the quality and accuracy of the data by cleaning and preprocessing the historical operation data, thereby providing a reliable basis for subsequent analysis and modeling; the present invention can deeply understand the key influencing factors of the coordinated removal efficiency of pollutants in coal-fired power plants by analyzing the influencing factors, and provide an important basis for subsequent model construction and optimization; the present invention will enable coal-fired power plants to predict future removal efficiency according to actual operating conditions by constructing a removal efficiency prediction model, so as to make targeted adjustments and optimizations; the present invention can clearly understand the gap between the actual removal efficiency and the standard requirements by comparing the removal efficiency requirements and the predicted data, and provide a basis for subsequent improvements; the present invention can enable managers to better understand the removal situation of coal-fired power plants and formulate corresponding control measures by determining the removal evaluation value and the operation adjustment coefficient; the present invention can enable coal-fired power plants to respond to actual operating conditions more flexibly by adjusting real-time operation data, thereby achieving control over the coordinated removal of pollutants.

[0057] In an embodiment of the present application, a pollutant collaborative removal operation control method for a coal-fired power plant is provided, wherein the preprocessing of historical operation data of the coal-fired power plant comprises: preprocessing the historical operation data of the coal-fired power plant, the preprocessing comprising removing abnormal data and overloaded data in the historical operation data of the coal-fired power plant and filling in missing data, and standardizing the historical operation data of the coal-fired power plant.

[0058] Specifically, the historical operating data of coal-fired power plants are preprocessed, including removing erroneous data points and identifying and removing outliers. Outliers can be identified through statistical methods or by using special anomaly detection algorithms and removed from the data set; missing values ​​can be filled by interpolation or by filling them according to the trend of previous and subsequent values; duplicate data can be removed by setting thresholds or by using anomaly detection algorithms. Duplicate data may be due to problems in the data collection system and require deduplication; data standardization can be performed by performing z-score standardization or minimum-maximum standardization on the data, mapping the data to a standard normal distribution with a mean of 0 and a standard deviation of 1, or mapping it to a range of 0 to 1, so as to eliminate the dimensional effects between different variables and ensure that the data is on a uniform scale.

[0059] In an embodiment of the present application, a method for controlling the coordinated removal of pollutants in a coal-fired power plant is provided, wherein the pre-processed historical operation data is analyzed to determine the influencing factors affecting the coordinated removal efficiency of pollutants in the coal-fired power plant, including: obtaining the pre-processed historical operation data of the coal-fired power plant, and dividing the historical operation data of the coal-fired power plant into several groups of operation parameter data groups according to parameter types; obtaining the coordinated removal efficiency data of pollutants in the coal-fired power plant, analyzing the correlation between each group of operation parameter data groups and the coordinated removal efficiency data of pollutants, and selecting the operation parameter data groups whose correlation exceeds a preset threshold; determining the parameters corresponding to the selected operation parameter data groups, and determining the parameters as the influencing factors affecting the removal efficiency of the coal-fired power plant.

[0060] Specifically, historical operation data of coal-fired power plants are obtained, which may include time series data of multiple parameters such as coal consumption, combustion temperature, flue gas flow rate, flue gas composition, and dust collector efficiency; historical operation data are classified and sorted, and parameter data of similar types are grouped together, such as putting all data related to coal consumption in one group, and data related to flue gas emissions in another group, and so on; pollutant synergistic removal efficiency data of coal-fired power plants are collected; statistical methods or machine learning techniques are used to conduct correlation analysis on each group of operating parameter data and pollutant synergistic removal efficiency data to determine the degree of association between them; by setting a correlation threshold, operating parameter groups with a higher correlation with pollutant synergistic removal efficiency are screened out, and these groups may have a greater impact on the removal efficiency; the parameters corresponding to the selected operating parameter data groups are determined, and the parameters are determined as the influencing factors affecting the removal efficiency of coal-fired power plants, and finally the influencing factors are determined, that is, the specific parameters corresponding to the operating parameter data groups with a higher correlation, and these parameters are considered to have a significant impact on the removal efficiency of coal-fired power plants. Through the above steps, the key parameters and influencing factors in the environmental protection control of coal-fired power plants can be determined, providing important reference for further optimization and improvement.

[0061] In an embodiment of the present application, a pollutant collaborative removal operation control method for a coal-fired power plant is provided, wherein a removal efficiency prediction model of the coal-fired power plant is constructed based on influencing factors, and the removal efficiency of the coal-fired power plant is predicted according to the removal efficiency prediction model of the coal-fired power plant to obtain pollutant removal efficiency prediction data of the coal-fired power plant, including: constructing a data set based on the influencing factors, and inputting the data set into a preset neural network model to construct an initial model for removal efficiency prediction; dividing the data set into a training set and a test set according to a certain ratio, and inputting the training set and the test set into the initial model for removal efficiency prediction; training and testing the initial model for removal efficiency prediction until the initial model for removal efficiency prediction meets the preset convergence conditions to obtain a removal efficiency prediction model; and predicting the pollutant removal efficiency prediction data of the coal-fired power plant in the future period of time according to the obtained removal efficiency prediction model.

[0062] Specifically, a data set is constructed based on the determined influencing factors, and the data set should include the influencing factor parameters and the corresponding pollutant removal efficiency data in the historical operation data; the data set is input into the preset neural network model, the initial model for removal efficiency prediction is constructed, the appropriate neural network structure and parameters are selected, and the constructed data set is input into the neural network model to initialize and construct the model; the data set is divided into a training set and a test set, the training set is used for model training, and the test set is used to evaluate the performance of the model, the divided training set and test set are input into the neural network model, the model is trained and tested, the initial model for removal efficiency prediction is trained and tested, until the preset convergence conditions are met, and the removal efficiency prediction model is obtained; the pollutant removal efficiency prediction data of the coal-fired power plant in the future is predicted based on the obtained removal efficiency prediction model. The above steps can help coal-fired power plants predict the future pollutant removal efficiency and provide an important reference for environmental protection control.

[0063] In an embodiment of the present application, a method for controlling the coordinated removal of pollutants in a coal-fired power plant is provided, wherein the method obtains the removal efficiency requirement of the coal-fired power plant for the coordinated removal of pollutants, and determines the difference characteristics between the removal efficiency prediction data of the coal-fired power plant and the removal efficiency requirement, including: obtaining the removal efficiency requirement of the coal-fired power plant for the coordinated removal of pollutants, and performing a difference calculation between each data in the removal efficiency prediction data and the removal efficiency requirement to obtain efficiency deviation data; plotting the efficiency deviation data into an efficiency deviation curve according to time sequence, and determining the peak value and the trough value from the efficiency deviation curve; determining the descending curve segment corresponding to each peak value to the trough value and the ascending curve segment corresponding to each trough value to the peak value based on the peak value and the trough value, and obtaining the corresponding duration of the descending curve segment and the ascending curve segment; calculating the slopes of the descending curve segment and the ascending curve segment to obtain the descending slope and the ascending slope respectively; determining the corresponding duration of the descending curve segment and the ascending curve segment as well as the descending slope and the ascending slope as the difference characteristics between the removal efficiency prediction data and the removal efficiency requirement of the coal-fired power plant.

[0064] Specifically, the removal efficiency requirements of coal-fired power plants for different pollutants are obtained, and each data in the removal efficiency prediction data is subtracted from the removal efficiency requirements to obtain efficiency deviation data, that is, the difference between the predicted value and the required value; the efficiency deviation data is plotted into an efficiency deviation curve in chronological order to visualize the changing trend, and the peak value and trough value are determined from the efficiency deviation curve. These points represent the maximum and minimum values ​​of the efficiency deviation, that is, the maximum and minimum difference between the predicted value and the required value; based on the peak value and trough value, the descending curve segment corresponding to each peak value to the trough value and each The rising curve segments corresponding to the trough value to the peak value represent the decreasing and increasing process of the efficiency deviation; determine the duration corresponding to each decreasing curve segment and the rising curve segment, that is, the length of time the efficiency deviation lasts after reaching the maximum or minimum value; calculate the slope of the decreasing curve segment and the rising curve segment to determine the rate of change of the efficiency deviation; determine the duration corresponding to the decreasing curve segment and the rising curve segment, as well as the decreasing slope and the increasing slope as the difference characteristics between the removal efficiency prediction data of the coal-fired power plant and the removal efficiency requirements, these characteristics can help understand the difference and change law between the prediction data and the requirements. The above steps can help coal-fired power plants understand the difference between the prediction data and the actual requirements, and provide an important reference for further improvement and optimization.

[0065] In an embodiment of the present application, a method for coordinated pollutant removal operation control of a coal-fired power plant is provided, wherein the removal situation of the coal-fired power plant is analyzed and evaluated based on difference characteristics to obtain a removal evaluation value of the coal-fired power plant, including: obtaining the duration of the efficiency deviation curve, and respectively calculating the ratio between the duration corresponding to the descending curve segment and the ascending curve segment and the duration of the efficiency deviation curve, and using the ratio as the weight of each corresponding curve segment; calculating the average value of the slopes of all curve segments, subtracting each curve segment from the average value to obtain the difference corresponding to each curve segment, and evaluating the difference corresponding to each curve segment to obtain an evaluation value of each curve segment; performing weighted addition calculation on the evaluation value of each curve segment and the weight of each curve segment to obtain the removal evaluation value of the coal-fired power plant.

[0066] Specifically, calculate the duration of each descending curve segment and ascending curve segment, and compare these durations with the duration of the efficiency deviation curve; compare the duration of the descending curve segment and the ascending curve segment with the duration of the entire efficiency deviation curve, and obtain the ratio as the weight of each corresponding curve segment; calculate the slope of all curve segments to obtain the average slope; calculate the difference between the slope of each curve segment and the average slope to obtain the difference corresponding to each curve segment; evaluate and value the difference of each curve segment, and evaluate it according to the size of the difference; multiply the evaluation value of each curve segment by the weight, and then perform weighted addition calculation to obtain the removal evaluation value of the coal-fired power plant. The above steps can help coal-fired power plants to quantitatively evaluate the changes and trends in removal efficiency, and provide important references for improvement and optimization.

[0067] In an embodiment of the present application, a method for coordinated pollutant removal operation control of a coal-fired power plant is provided, wherein the operation adjustment coefficient of the coal-fired power plant is determined according to the removal evaluation value, comprising: presetting an operation adjustment coefficient-removal evaluation value interval correspondence relationship, wherein each removal evaluation value interval is associated with a corresponding operation adjustment coefficient in the operation adjustment coefficient-removal evaluation value interval correspondence relationship; obtaining the removal evaluation value, and selecting the operation adjustment coefficient corresponding to the removal evaluation value interval based on a mapping relationship between the removal evaluation value interval to which the difference belongs within the operation adjustment coefficient-removal evaluation value interval correspondence relationship.

[0068] Specifically, determine the relationship between different removal evaluation value intervals and the corresponding operation adjustment coefficients, which is determined through experience or based on specific engineering models and data analysis; obtain the removal evaluation value based on the previous calculation, which reflects the difference between the removal efficiency of the coal-fired power plant and the requirements; compare the removal evaluation value with the pre-set operation adjustment coefficient-removal evaluation value interval correspondence to determine the interval to which the removal evaluation value belongs, and find the operation adjustment coefficient corresponding to the interval; according to the interval to which the removal evaluation value belongs, select the operation adjustment coefficient corresponding to the interval as the final adjustment value for the actual operation adjustment of the coal-fired power plant. The above steps can help coal-fired power plants to make real-time adjustments according to changes in the removal evaluation value to achieve better removal effects.

[0069] like Figure 2As shown, in an embodiment of the present application, a pollutant collaborative removal operation control system for a coal-fired power plant is provided, including: obtaining and pre-processing historical operation data of the coal-fired power plant; analyzing the pre-processed historical operation data to determine the influencing factors affecting the efficiency of the collaborative removal of pollutants in the coal-fired power plant; constructing a removal efficiency prediction model based on the influencing factors, and obtaining removal efficiency prediction data based on the prediction; obtaining removal efficiency requirements, and determining the difference characteristics between the removal efficiency prediction data and the removal efficiency prediction data; evaluating the removal situation of the coal-fired power plant based on the characteristics, obtaining the removal evaluation value, and determining the operation adjustment coefficient of the coal-fired power plant based on the removal efficiency; adjusting the real-time operation data of the coal-fired power plant according to the operation adjustment coefficient, and controlling the collaborative removal of pollutants in the coal-fired power plant according to the adjusted real-time operation data. The present invention can control the collaborative removal of pollutants more efficiently and accurately, improve the environmental protection level of coal-fired power plants, and provide a more scientific decision-making basis for the operation of coal-fired power plants.

[0070] In summary, the embodiment of the present invention provides a pollutant collaborative removal operation control method and system for a coal-fired power plant, which includes: obtaining and preprocessing the historical operation data of the coal-fired power plant collected by the DCS; analyzing the preprocessed data to determine the factors affecting the removal efficiency of the coal-fired power plant; constructing a removal efficiency prediction model based on the factors to predict the pollutant removal efficiency prediction data; determining the predicted coal supply data according to the pollutant removal efficiency prediction data, obtaining the coal supply demand, and determining the predicted coal supply data and its curve segment; evaluating the curve segment and determining the operation adjustment coefficient according to the result; optimizing and adjusting the removal efficiency according to the operation adjustment coefficient, and controlling the removal efficiency according to the optimized removal efficiency. The present invention obtains the historical operation data of the coal-fired power plant based on the DCS, and performs analysis and modeling. It can predict the coal supply in real time, and determine the operation adjustment coefficient of the coal-fired power plant by evaluating the curve segment, so as to optimize and adjust the coal-fired power plant and improve the working efficiency of the coal-fired power plant.

[0071] Finally, it should be noted that: Obviously, a person skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalent technology, the present invention is also intended to include these modifications and variations.

[0072] The above is only an example of implementation of the present invention, but it cannot be used to limit the scope of the present invention. Any structural changes made according to the present invention, as long as they do not lose the essence of the present invention, should be regarded as falling within the scope of protection of the present invention and being restricted. Technical personnel in the relevant technical field can clearly understand that for the convenience and simplicity of description, the specific working process and related instructions of the platform described above can refer to the corresponding process in the aforementioned platform embodiment, and will not be repeated here.

[0073] The term "comprises" or any other similar term is intended to cover a non-exclusive inclusion such that a process, platform, article, or apparatus / platform that includes a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, platform, article, or apparatus / platform.

[0074] So far, the technical solutions of the present invention have been described in conjunction with the further embodiments shown in the accompanying drawings. However, it is easy for a person skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, a person skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0075] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A method for coordinated pollutant removal operation control of a coal-fired power plant, characterized in that: include: Obtain historical operation data of coal-fired power plants and pre-process the historical operation data of coal-fired power plants; Analyze the historical operation data after pretreatment to determine the factors affecting the efficiency of synergistic removal of pollutants in coal-fired power plants; Based on the influencing factors, a removal efficiency prediction model of a coal-fired power plant is constructed, and prediction is performed according to the removal efficiency prediction model of the coal-fired power plant to obtain the removal efficiency prediction data of the coal-fired power plant; Obtain the removal efficiency requirements of coal-fired power plants for the coordinated removal of pollutants, and determine the difference characteristics between the removal efficiency prediction data of coal-fired power plants and the removal efficiency requirements; Analyze and evaluate the removal status of coal-fired power plants based on the difference characteristics, obtain the removal evaluation value of the coal-fired power plants, and determine the operation adjustment coefficient of the coal-fired power plants according to the removal evaluation value; The real-time operation data of the coal-fired power plant is adjusted according to the operation adjustment coefficient, and the coordinated removal of pollutants in the coal-fired power plant is controlled according to the adjusted real-time operation data.

2. A method for coordinated pollutant removal operation control of a coal-fired power plant according to claim 1, characterized in that: The preprocessing of the historical operation data of the coal-fired power plant includes: The historical operation data of the coal-fired power plant is preprocessed, which includes removing abnormal data and overloaded data in the historical operation data of the coal-fired power plant and filling in missing data, and standardizing the historical operation data of the coal-fired power plant.

3. A method for coordinated pollutant removal operation control of a coal-fired power plant according to claim condition 2, characterized in that: The analysis of the historical operation data after pretreatment to determine the factors affecting the synergistic removal efficiency of pollutants in coal-fired power plants includes: Acquire pre-processed historical operation data of the coal-fired power plant, and divide the historical operation data of the coal-fired power plant into several groups of operation parameter data groups according to parameter types; Obtain pollutant synergistic removal efficiency data of coal-fired power plants, analyze the correlation between each set of operating parameter data and the pollutant synergistic removal efficiency data, and select the operating parameter data sets whose correlation exceeds a preset threshold; The parameter corresponding to the selected operating parameter data group is determined, and the parameter is determined as an influencing factor affecting the removal efficiency of the coal-fired power plant.

4. A method for coordinated pollutant removal operation control of a coal-fired power plant according to claim condition 3, characterized in that: The removal efficiency prediction model of the coal-fired power plant is constructed based on the influencing factors, and the removal efficiency of the coal-fired power plant is predicted according to the removal efficiency prediction model of the coal-fired power plant to obtain the pollutant removal efficiency prediction data of the coal-fired power plant, including: A data set is constructed based on the influencing factors, and the data set is input into a preset neural network model to construct an initial model for predicting removal efficiency; The data set is divided into a training set and a test set according to a certain ratio, and the training set and the test set are input into the initial model for prediction of removal efficiency; The removal efficiency prediction initial model is trained and tested until the removal efficiency prediction initial model meets the preset convergence condition, thereby obtaining the removal efficiency prediction model; The pollutant removal efficiency prediction data of coal-fired power plants in the future are predicted based on the obtained removal efficiency prediction model.

5. A method for coordinated pollutant removal operation control of a coal-fired power plant according to claim 4, characterized in that: The obtaining of the removal efficiency requirements of the coal-fired power plant for the coordinated removal of pollutants and determining the difference characteristics between the removal efficiency prediction data of the coal-fired power plant and the removal efficiency requirements include: Obtain the removal efficiency requirements of coal-fired power plants for the coordinated removal of pollutants, and perform a difference calculation between each data in the removal efficiency prediction data and the removal efficiency requirements to obtain efficiency deviation data; These efficiency deviation data are plotted into an efficiency deviation curve according to the time sequence, and the peak value and the trough value are determined from the efficiency deviation curve; Based on the peak value and the trough value, determine the descending curve segment corresponding to each peak value to the trough value and the ascending curve segment corresponding to each trough value to the peak value, and obtain the duration corresponding to the descending curve segment and the ascending curve segment; Calculate the slopes of the descending curve segment and the ascending curve segment to obtain the descending slope and the ascending slope respectively; The duration corresponding to the descending curve segment and the ascending curve segment as well as the descending slope and the ascending slope are determined as the difference characteristics between the removal efficiency prediction data of the coal-fired power plant and the removal efficiency requirements.

6. A method for coordinated pollutant removal operation control of a coal-fired power plant according to claim 5, characterized in that: The removal situation of the coal-fired power plant is analyzed and evaluated based on the difference characteristics to obtain the removal evaluation value of the coal-fired power plant, including: Obtain the duration of the efficiency deviation curve, and calculate the ratio between the duration corresponding to the descending curve segment and the ascending curve segment and the duration of the efficiency deviation curve, and use the ratio as the weight of each corresponding curve segment; Calculate the average value of the slopes of all curve segments, perform a difference calculation between each curve segment and the average value to obtain a difference value corresponding to each curve segment, and evaluate and value the difference value corresponding to each curve segment to obtain an evaluation value of each curve segment; The evaluation value of each curve segment and the weight of each curve segment are weighted and added together to obtain the removal assessment value of the coal-fired power plant.

7. A method for coordinated pollutant removal operation control of a coal-fired power plant according to claim 6, characterized in that: Determining the operation adjustment coefficient of the coal-fired power plant according to the removal evaluation value includes: The operation adjustment coefficient-removal evaluation value interval correspondence relationship is preset, and the operation adjustment coefficient-removal evaluation value interval correspondence relationship is associated with a corresponding operation adjustment coefficient for each removal evaluation value interval; A removal evaluation value is obtained, and based on the mapping relationship between the removal evaluation value interval to which the difference belongs and the operation adjustment coefficient corresponding to the removal evaluation value interval, an operation adjustment coefficient corresponding to the removal evaluation value interval is selected.

8. A pollutant collaborative removal operation control system for a coal-fired power plant, characterized in that: include: An acquisition module is used to acquire historical operation data of the coal-fired power plant and pre-process the historical operation data of the coal-fired power plant; The analysis module is used to analyze the historical operation data after pretreatment and determine the factors affecting the efficiency of the synergistic removal of pollutants in coal-fired power plants; A prediction module is used to construct a removal efficiency prediction model of a coal-fired power plant based on influencing factors, and to make predictions based on the removal efficiency prediction model of the coal-fired power plant to obtain removal efficiency prediction data of the coal-fired power plant; A determination module is used to obtain the removal efficiency requirements of the coal-fired power plant for the coordinated removal of pollutants, and to determine the difference characteristics between the removal efficiency prediction data of the coal-fired power plant and the removal efficiency requirements; An evaluation module is used to analyze and evaluate the removal status of the coal-fired power plant based on the difference characteristics, obtain the removal evaluation value of the coal-fired power plant, and determine the operation adjustment coefficient of the coal-fired power plant according to the removal evaluation value; The regulation module is used to adjust the real-time operation data of the coal-fired power plant according to the operation regulation coefficient, and control the coordinated removal of pollutants in the coal-fired power plant according to the adjusted real-time operation data.

Images