Thermal power plant boiler energy-saving control system and method

Abstract

The present invention relates to the technical field of boiler energy conservation, and specifically discloses a thermal power plant boiler energy conservation control system and method, including a prediction module, which is used to predict the current boiler operating efficiency according to the operating condition parameters of the thermal power plant boiler; an optimization module, which is used to optimize the boiler input parameters based on a particle swarm algorithm, determine the optimal operating condition parameter combination according to the optimization result, and set the adjustment step of the optimal operating condition parameter combination according to the operating efficiency prediction value; an emission detection module, which is used to obtain the NOx emission data of the thermal power plant boiler, and calculate the fluctuation degree of NOx emission according to the NOx emission data. A parameter correction module is used to set the emission weight according to the fluctuation degree, and set the correction value of the optimal operating condition parameter combination according to the emission weight; a control module is used to control the thermal power plant boiler according to the correction value of the optimal operating condition parameter combination. Effectively improve the operating efficiency of the boiler and control NOx emissions, so that the boiler can operate efficiently and energy-saving.

Description

Technical Field

[0001] The present application relates to the technical field of boiler energy conservation, and more specifically, to a thermal power plant boiler energy conservation control system and method. Background Art

[0002] The boiler of a thermal power plant is a medium-sized or large boiler that provides a specified amount and quality of steam to the steam turbine in a power plant. It is one of the main thermal equipment in a thermal power plant. It is often matched with a steam turbine generator set of a certain capacity and is mainly used for power generation, but it can also be used for external heat supply in some special occasions. Generally, its evaporation capacity is large, and the steam parameters (steam temperature and steam pressure) are very high. It requires a complete set of auxiliary equipment, and is often equipped with a chamber combustion furnace. It adopts a forced ventilation method and can burn a variety of fuels (coal powder, crude oil or heavy oil, blast furnace gas or coke oven gas). It has a complex structure and a high efficiency, most of which can reach about 85-93%. It has quite high requirements for the operation management level, mechanization degree and automatic control technology.

[0003] Boiler energy-saving standards refer to a series of standard requirements that regulate the energy consumption and thermal efficiency of boilers in various links such as design, manufacturing, installation, and use based on multiple factors such as energy utilization efficiency, thermal efficiency, and environmental protection requirements in order to achieve the goals of saving energy, reducing emissions, and improving performance. However, there is a contradictory relationship between boiler efficiency and NOx emissions. How to adjust the contradictory relationship between boiler efficiency and NOx emissions to achieve the most efficient energy-saving effect of boilers is a technical problem that needs to be solved urgently in this field. Summary of the invention

[0004] The present invention provides a thermal power plant boiler energy-saving control system and method, which is used to solve the problem of low boiler combustion efficiency and ineffective control of NOx emissions in the prior art. It includes:

[0005] The prediction module is used to obtain the operating parameters of the thermal power plant boiler and predict the current boiler operating efficiency based on the operating parameters of the thermal power plant boiler;

[0006] An optimization module is used to optimize boiler input parameters based on a particle swarm algorithm, determine the optimal operating condition parameter combination according to the optimization result, and set the adjustment step length of the optimal operating condition parameter combination according to the predicted value of operating efficiency;

[0007] The emission detection module is used to obtain the NOx emission data of the boiler of the thermal power plant and calculate the fluctuation degree of NOx emission based on the NOx emission data;

[0008] A parameter correction module is used to set emission weights according to the degree of fluctuation and to set correction values ​​of the optimal operating condition parameter combination according to the emission weights;

[0009] The control module is used to control the boiler of the thermal power plant according to the correction value of the optimal operating condition parameter combination.

[0010] Furthermore, the prediction module is also used for:

[0011] Obtain historical operating parameters and boiler operating efficiency of thermal power plant boilers, and pre-process the historical operating parameters and boiler operating efficiency;

[0012] The pre-processed historical operating condition parameters and boiler operating efficiency data are trained to generate a boiler operating efficiency prediction model;

[0013] Obtain the real-time detection values ​​of the operating parameters of the thermal power plant boiler, and predict the boiler operating efficiency under the current operating conditions based on the boiler operating efficiency prediction model.

[0014] Furthermore, the optimization module is also used for:

[0015] Initialize the particle swarm parameters, set the boiler operating efficiency as the fitness function, calculate the fitness value of the particles, and determine the local optimal value and the global optimal value;

[0016] According to the changing trend of the fitness value with the number of iterations, a fitness value change curve of the particle is drawn, and according to the fitness value change curve of the particle, the slope mean of the fitness value within the preset number of iterations is calculated;

[0017] The inertia weight of the particle is updated according to the slope mean of the fitness value within the preset iteration number interval, and the particle is updated according to the updated value of the inertia weight;

[0018] Determine whether the current number of iterations meets the algorithm termination condition. If so, output the operating condition parameter combination of the optimal fitness function according to the global optimal value. If not, continue to iterate.

[0019] Furthermore, the optimization module is also used for:

[0020] The inertia weight of the particle is updated according to the inertia weight update formula, and the inertia weight update formula is specifically:

[0021]

[0022] in, is the inertia weight, is the minimum inertia weight, is the maximum inertia weight, is the mean slope of the fitness value within the preset iteration number interval, is the preset standard slope mean.

[0023] Furthermore, the optimization module is also used for:

[0024] Inputting the operating condition parameter combination of the optimal boiler efficiency into the boiler operating efficiency prediction model, and determining the optimal boiler operating efficiency according to the boiler operating efficiency prediction model;

[0025] Calculate the ratio of the current boiler operating efficiency to the optimal boiler operating efficiency, and calculate the difference between the operating efficiency ratio and the preset allowable ratio;

[0026] If the difference between the operating efficiency ratio and the preset allowable ratio is less than a first preset threshold, the first preset adjustment step is determined as the adjustment step of the optimal operating condition parameter combination;

[0027] If the difference between the operating efficiency ratio and the preset allowable ratio is greater than or equal to the first preset threshold, the second preset adjustment step is determined as the adjustment step of the optimal operating condition parameter combination;

[0028] If the difference between the operating efficiency ratio and the preset allowable ratio is greater than the second preset threshold, the third preset adjustment step is determined as the adjustment step of the optimal operating condition parameter combination.

[0029] Furthermore, the emission detection module is also used for:

[0030] Determine the NOx emission concentration based on the NOx emission data of the thermal power plant boiler, and draw the NOx emission concentration change curve based on the change trend of NOx emission concentration over time;

[0031] Create a number of rolling time windows, set the window size of the rolling time window according to the curve length of the NOx emission concentration change curve, and segment the NOx emission concentration change curve according to the rolling time window;

[0032] Calculate the average value of NOx emission concentration in the rolling time window after segmentation, and draw a NOx emission concentration average value change curve according to the average value of NOx emission concentration in each rolling window;

[0033] Calculate the absolute value of the slope of two adjacent points in the NOx emission concentration average value change curve, and filter out the data whose absolute value of the slope exceeds the first preset threshold; set the proportion of the number of data whose absolute value of the slope exceeds the first preset threshold in the NOx emission concentration average value change curve as the fluctuation degree of NOx emissions.

[0034] Furthermore, the parameter correction module is also used for:

[0035] Calculating the ratio of the fluctuation degree of NOx emissions to the preset allowable fluctuation degree, and normalizing the ratio of the fluctuation degree of NOx emissions to the preset allowable fluctuation degree;

[0036] The ratio of the normalized NOx emission fluctuation degree to the preset allowable fluctuation degree is set as the emission weight, and the emission weight is multiplied by the preset standard correction value to obtain the correction value of the optimal operating condition parameter combination.

[0037] Furthermore, the parameter correction module is also used for:

[0038] Obtain operating condition parameters within a preset period based on historical boiler operating data, and calculate correlation coefficients between each operating condition parameter and NOx emission concentration based on the operating condition parameters within the preset period;

[0039] The correlation coefficient between each operating condition parameter and NOx emission concentration is used as the adjustment coefficient of each operating condition parameter, and the correction value of each operating condition parameter in the optimal operating condition parameter combination is adjusted according to the adjustment coefficient of each operating condition parameter.

[0040] Furthermore, the control module is also used for:

[0041] The correction value of the optimal operating condition parameter combination is multiplied by each parameter in the optimal operating condition parameter combination to obtain the final operating condition parameter;

[0042] The adjustment step of the optimal operating condition parameter combination is set as the current adjustment step, and the final operating condition parameters are used as target values ​​to adjust the current operating condition parameters of the boiler.

[0043] In order to achieve the above object, the present invention also provides a thermal power plant boiler energy-saving control method, comprising:

[0044] Obtain the operating parameters of the thermal power plant boiler, and predict the current boiler operating efficiency based on the operating parameters of the thermal power plant boiler;

[0045] The boiler input parameters are optimized based on the particle swarm algorithm, the optimal operating condition parameter combination is determined according to the optimization results, and the adjustment step length of the optimal operating condition parameter combination is set according to the predicted value of the operating efficiency;

[0046] Obtain NOx emission data from thermal power plant boilers and calculate the fluctuation degree of NOx emissions based on the NOx emission data;

[0047] Set emission weights according to the degree of fluctuation, and set correction values ​​for the optimal operating condition parameter combination according to the emission weights;

[0048] The boiler of a thermal power plant is regulated according to the correction value of the optimal operating condition parameter combination.

[0049] The beneficial effects of the present invention are:

[0050] By applying the above technical scheme, the present invention optimizes the input parameters of the thermal power plant boiler based on the particle swarm algorithm, and converges the algorithm in time according to the changing trend of the fitness value, so as to quickly find the optimal operating condition parameter combination, and greatly improve the operating efficiency of the boiler. At the same time, the adjustment step of the boiler is set in combination with the prediction model, and each parameter is stably adjusted. By adjusting each parameter in the optimal operating condition parameter combination through NOx emission data, NOx emissions can be effectively controlled, so that the boiler can operate efficiently, energy-saving and environmentally friendly. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0052] Figure 1 A schematic diagram of a thermal power plant boiler energy-saving control system proposed in an embodiment of the present invention is shown;

[0053] Figure 2 The figure shows an overall flow chart of a thermal power plant boiler energy-saving control method proposed in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0055] The present application embodiment provides a thermal power plant boiler energy-saving control system, such as Figure 1 As shown, including:

[0056] The prediction module is used to obtain the operating parameters of the boiler in the thermal power plant and predict the current boiler operating efficiency based on the operating parameters of the boiler in the thermal power plant; the optimization module is used to optimize the boiler input parameters based on the particle swarm algorithm, determine the optimal operating parameter combination based on the optimization results, and set the adjustment step of the optimal operating parameter combination according to the predicted value of the operating efficiency; the emission detection module is used to obtain the NOx emission data of the boiler in the thermal power plant and calculate the fluctuation degree of NOx emissions based on the NOx emission data; the parameter correction module is used to set the emission weight according to the fluctuation degree and set the correction value of the optimal operating parameter combination according to the emission weight; the control module is used to control the boiler in the thermal power plant according to the correction value of the optimal operating parameter combination.

[0057] In this embodiment, the operating parameters of the thermal power plant boiler specifically include primary air, secondary air distribution mode, burnout air volume and oxygen content. The NOx emission data of the thermal power plant boiler is monitored in real time by setting up a nitrogen oxide online monitoring system.

[0058] In some embodiments of the present application, the prediction module is also used to: obtain historical operating condition parameters and boiler operating efficiency of the thermal power plant boiler, and preprocess the historical operating condition parameters and boiler operating efficiency; train the preprocessed historical operating condition parameters and boiler operating efficiency data to generate a boiler operating efficiency prediction model; obtain real-time detection values ​​of the operating condition parameters of the thermal power plant boiler, and predict the boiler operating efficiency under the current operating conditions based on the boiler operating efficiency prediction model.

[0059] In this embodiment, the prediction module can construct a boiler operation efficiency prediction model based on a mixture of one or more algorithms such as convolutional neural networks, deep neural networks and genetic algorithms, and obtain a model training sample set and a test sample set by pre-processing historical operating condition parameters and the corresponding boiler operating efficiency such as denoising, de-redundancy and normalization.

[0060] In some embodiments of the present application, the optimization module is also used to: initialize particle swarm parameters, set the boiler operating efficiency as the fitness function, calculate the fitness value of the particles, and determine the local optimal value and the global optimal value; draw a fitness value change curve of the particles according to the changing trend of the fitness value with the number of iterations, and calculate the slope mean of the fitness value within a preset number of iterations according to the fitness value change curve of the particles; update the inertia weight of the particles according to the slope mean of the fitness value within the preset number of iterations, and update the particles according to the updated value of the inertia weight; determine whether the current number of iterations meets the algorithm termination condition. If so, output the operating condition parameter combination of the optimal fitness function according to the global optimal value. If not, continue to iterate.

[0061] In this embodiment, the mean slope of the fitness value within the preset iteration number interval is specifically the average value of the slopes of the two end points of the fitness value within the preset iteration number interval. The size of the mean slope can reflect the speed of growth or decrease of the fitness value.

[0062] In some embodiments of the present application, the optimization module is further used to: update the inertia weight of the particle according to the inertia weight update formula, and the inertia weight update formula is specifically:

[0063]

[0064] in, is the inertia weight, is the minimum inertia weight, is the maximum inertia weight, is the mean slope of the fitness value within the preset iteration number interval, is the preset standard slope mean.

[0065] In this embodiment, Take 0.2, Take 0.7, Set according to the unit operation experience. The faster the fitness value changes, the larger the inertia weight value is, which can improve the global search ability of the algorithm. The slower the fitness value changes, the boiler operating parameters are close to the optimal operating efficiency. Therefore, the inertia weight value is smaller, which improves the local search ability of the algorithm, accelerates the convergence speed, and improves the calculation efficiency.

[0066] In some embodiments of the present application, the optimization module is also used to: input the operating condition parameter combination of the optimal boiler efficiency into the boiler operating efficiency prediction model, and determine the optimal boiler operating efficiency according to the boiler operating efficiency prediction model; calculate the ratio of the current boiler operating efficiency to the optimal boiler operating efficiency, and calculate the difference between the operating efficiency ratio and the preset allowable ratio; if the difference between the operating efficiency ratio and the preset allowable ratio is less than a first preset threshold, then determine the first preset adjustment step as the adjustment step of the optimal operating condition parameter combination; if the difference between the operating efficiency ratio and the preset allowable ratio is greater than or equal to the first preset threshold, then determine the second preset adjustment step as the adjustment step of the optimal operating condition parameter combination; if the difference between the operating efficiency ratio and the preset allowable ratio is greater than the second preset threshold, then determine the third preset adjustment step as the adjustment step of the optimal operating condition parameter combination.

[0067] In this embodiment, the first preset adjustment step, the second preset adjustment step and the third preset adjustment step become larger in sequence. The greater the difference between the optimal boiler operating efficiency and the current boiler operating efficiency, the longer the corresponding adjustment step is set, and the stronger the stability when the boiler is adjusted, preventing the boiler from abnormalities due to excessively fast adjustment speeds.

[0068] In some embodiments of the present application, the emission detection module is also used to: determine the NOx emission concentration based on the NOx emission data of the boiler of the thermal power plant, and draw a NOx emission concentration change curve based on the changing trend of the NOx emission concentration over time; create several rolling time windows, set the window size of the rolling time window according to the curve length of the NOx emission concentration change curve, and segment the NOx emission concentration change curve according to the rolling time window; calculate the average value of the NOx emission concentration in the rolling time window after segmentation, and draw a NOx emission concentration average value change curve based on the average value of the NOx emission concentration in each rolling window; calculate the absolute value of the slope of two adjacent points in the NOx emission concentration average value change curve, and filter out data whose absolute value of the slope exceeds a first preset threshold; set the proportion of the number of data whose absolute value of the slope exceeds the first preset threshold in the NOx emission concentration average value change curve as the degree of fluctuation of NOx emissions.

[0069] In this embodiment, the changing speed of the NOx emission concentration in the rolling window is determined by the slope of the NOx emission concentration average value change curve. The faster the changing speed, the higher the fluctuation degree of the NOx emission concentration. The fluctuation degree of the overall NOx emission is determined by calculating the proportion of the number of data whose absolute value of the slope exceeds the first preset threshold in the NOx emission concentration average value change curve.

[0070] In some embodiments of the present application, the parameter correction module is also used to: calculate the ratio of the fluctuation degree of NOx emissions to a preset allowable fluctuation degree, and normalize the ratio of the fluctuation degree of NOx emissions to the preset allowable fluctuation degree; set the ratio of the fluctuation degree of NOx emissions after normalization to the preset allowable fluctuation degree as the emission weight, multiply the emission weight by the preset standard correction value, and obtain the correction value of the optimal operating condition parameter combination.

[0071] In this embodiment, the normalization processing formula is specifically:

[0072]

[0073] in, is the NOx emission fluctuation degree after normalization, N is the current NOx emission fluctuation degree, is the maximum value of NOx emission fluctuation, It is the minimum fluctuation degree of NOx emissions.

[0074] In some embodiments of the present application, the parameter correction module is also used to: obtain the operating condition parameters within a preset period based on the historical operating data of the boiler, and calculate the correlation coefficient between each operating condition parameter and the NOx emission concentration based on the operating condition parameters within the preset period; use the correlation coefficient between each operating condition parameter and the NOx emission concentration as the adjustment coefficient of each operating condition parameter, and adjust the correction value of each operating condition parameter in the optimal operating condition parameter combination according to the adjustment coefficient of each operating condition parameter.

[0075] In this embodiment, the relationship between the change of the operating condition parameter and the NOx emission concentration is obtained according to the historical operation data of the boiler. Since there are multiple operating condition parameters in the optimal operating condition parameter combination, and the influence efficiency of each parameter on the NOx emission concentration is different, each operating condition parameter is adjusted one by one by calculating the correlation coefficient between the operating condition parameter and the NOx emission concentration. The specific calculation formula of the correlation coefficient between the operating condition parameter and the NOx emission concentration is:

[0076]

[0077] in, is the correlation coefficient, For the i Operating parameters, is the average value of the operating condition parameters, For the i NOx emission concentration, is the average value of NOx emission concentration.

[0078] In some embodiments of the present application, the control module is also used to: multiply the correction value of the optimal operating condition parameter combination by each parameter in the optimal operating condition parameter combination to obtain the final operating condition parameter; set the adjustment step of the optimal operating condition parameter combination as the current adjustment step, and use the final operating condition parameter as the target value to adjust the current operating condition parameter of the boiler.

[0079] In this embodiment, each operating condition parameter is corrected by the correction value of the optimal operating condition parameter combination to obtain the final operating condition parameter, and the boiler is adjusted by adjusting the step size.

[0080] Based on the same technical concept, such as Figure 2 As shown, the present invention also provides a thermal power plant boiler energy-saving control method, comprising:

[0081] S101, obtaining operating condition parameters of the thermal power plant boiler, and predicting the current boiler operating efficiency according to the operating condition parameters of the thermal power plant boiler;

[0082] S102, optimizing the boiler input parameters based on the particle swarm algorithm, determining the optimal operating condition parameter combination according to the optimization result, and setting the adjustment step length of the optimal operating condition parameter combination according to the operating efficiency prediction value;

[0083] S103, obtaining NOx emission data of the boiler of the thermal power plant, and calculating the fluctuation degree of NOx emission according to the NOx emission data;

[0084] S104, setting emission weights according to the degree of fluctuation, and setting correction values ​​of the optimal operating condition parameter combination according to the emission weights;

[0085] S105, regulating the thermal power plant boiler according to the correction value of the optimal operating condition parameter combination.

[0086] By applying the above technical scheme, the present invention obtains the operating condition parameters of the thermal power plant boiler, predicts the current boiler operating efficiency according to the operating condition parameters of the thermal power plant boiler; optimizes the boiler input parameters based on the particle swarm algorithm, determines the optimal operating condition parameter combination according to the optimization result, and sets the adjustment step of the optimal operating condition parameter combination according to the operating efficiency prediction value; obtains the NOx emission data of the thermal power plant boiler, calculates the fluctuation degree of NOx emission according to the NOx emission data; sets the emission weight according to the fluctuation degree, sets the correction value of the optimal operating condition parameter combination according to the emission weight; and regulates the thermal power plant boiler according to the correction value of the optimal operating condition parameter combination. The operating efficiency of the thermal power plant boiler is greatly improved, and energy saving and environmental protection are achieved.

[0087] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present invention can be implemented by hardware, or by software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present invention.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A thermal power plant boiler energy-saving control system, characterized in that: include: The prediction module is used to obtain the operating parameters of the thermal power plant boiler and predict the current boiler operating efficiency based on the operating parameters of the thermal power plant boiler; An optimization module is used to optimize boiler input parameters based on a particle swarm algorithm, determine the optimal operating condition parameter combination according to the optimization result, and set the adjustment step length of the optimal operating condition parameter combination according to the predicted value of operating efficiency; The emission detection module is used to obtain the NOx emission data of the boiler of the thermal power plant and calculate the fluctuation degree of NOx emission based on the NOx emission data; A parameter correction module is used to set emission weights according to the degree of fluctuation and to set correction values ​​of the optimal operating condition parameter combination according to the emission weights; A control module is used to control the boiler of a thermal power plant according to the correction value of the optimal operating condition parameter combination; The emission detection module is also used for: Determine the NOx emission concentration based on the NOx emission data of the thermal power plant boiler, and draw the NOx emission concentration change curve based on the change trend of NOx emission concentration over time; Create a number of rolling time windows, set the window size of the rolling time window according to the curve length of the NOx emission concentration change curve, and segment the NOx emission concentration change curve according to the rolling time window; Calculate the average value of NOx emission concentration in the rolling time window after segmentation, and draw a NOx emission concentration average value change curve according to the average value of NOx emission concentration in each rolling window; Calculate the absolute values ​​of the slopes of two adjacent points in the NOx emission concentration average value change curve, and filter out data whose absolute values ​​of the slopes exceed a first preset threshold value; set the proportion of the number of data whose absolute values ​​of the slopes exceed the first preset threshold value in the NOx emission concentration average value change curve as the degree of fluctuation of NOx emissions; The parameter correction module is also used for: Calculating the ratio of the fluctuation degree of NOx emissions to the preset allowable fluctuation degree, and normalizing the ratio of the fluctuation degree of NOx emissions to the preset allowable fluctuation degree; The ratio of the normalized NOx emission fluctuation degree to the preset allowable fluctuation degree is set as the emission weight, and the emission weight is multiplied by the preset standard correction value to obtain the correction value of the optimal operating condition parameter combination; The parameter correction module is also used for: Obtain operating condition parameters within a preset period based on historical boiler operating data, and calculate correlation coefficients between each operating condition parameter and NOx emission concentration based on the operating condition parameters within the preset period; The correlation coefficient between each operating condition parameter and NOx emission concentration is used as the adjustment coefficient of each operating condition parameter, and the correction value of each operating condition parameter in the optimal operating condition parameter combination is adjusted according to the adjustment coefficient of each operating condition parameter.

2. The thermal power plant boiler energy-saving control system according to claim 1 is characterized in that: The prediction module is also used to: Obtain historical operating parameters and boiler operating efficiency of thermal power plant boilers, and pre-process the historical operating parameters and boiler operating efficiency; The pre-processed historical operating condition parameters and boiler operating efficiency data are trained to generate a boiler operating efficiency prediction model; Obtain the real-time detection values ​​of the operating parameters of the thermal power plant boiler, and predict the boiler operating efficiency under the current operating conditions based on the boiler operating efficiency prediction model.

3. The thermal power plant boiler energy-saving control system according to claim 1 is characterized in that: The optimization module is also used for: Initialize the particle swarm parameters, set the boiler operating efficiency as the fitness function, calculate the fitness value of the particles, and determine the local optimal value and the global optimal value; According to the changing trend of the fitness value with the number of iterations, a fitness value change curve of the particle is drawn, and according to the fitness value change curve of the particle, the slope mean of the fitness value within the preset number of iterations is calculated; The inertia weight of the particle is updated according to the slope mean of the fitness value within the preset iteration number interval, and the particle is updated according to the updated value of the inertia weight; Determine whether the current number of iterations meets the algorithm termination condition. If so, output the operating condition parameter combination of the optimal fitness function according to the global optimal value. If not, continue to iterate.

4. The thermal power plant boiler energy-saving control system according to claim 3 is characterized in that: The optimization module is also used for: The inertia weight of the particle is updated according to the inertia weight update formula, and the inertia weight update formula is specifically: in, is the inertia weight, is the minimum inertia weight, is the maximum inertia weight, is the mean slope of the fitness value within the preset iteration number interval, is the preset standard slope mean.

5. The thermal power plant boiler energy-saving control system according to claim 4 is characterized in that: The optimization module is also used for: Inputting the operating condition parameter combination of the optimal boiler efficiency into the boiler operating efficiency prediction model, and determining the optimal boiler operating efficiency according to the boiler operating efficiency prediction model; Calculate the ratio of the current boiler operating efficiency to the optimal boiler operating efficiency, and calculate the difference between the operating efficiency ratio and the preset allowable ratio; If the difference between the operating efficiency ratio and the preset allowable ratio is less than a first preset threshold, the first preset adjustment step is determined as the adjustment step of the optimal operating condition parameter combination; If the difference between the operating efficiency ratio and the preset allowable ratio is greater than or equal to the first preset threshold, the second preset adjustment step is determined as the adjustment step of the optimal operating condition parameter combination; If the difference between the operating efficiency ratio and the preset allowable ratio is greater than the second preset threshold, the third preset adjustment step is determined as the adjustment step of the optimal operating condition parameter combination.

6. The thermal power plant boiler energy-saving control system according to claim 1, characterized in that: The control module is also used for: The correction value of the optimal operating condition parameter combination is multiplied by each parameter in the optimal operating condition parameter combination to obtain the final operating condition parameter; The adjustment step of the optimal operating condition parameter combination is set as the current adjustment step, and the final operating condition parameters are used as target values ​​to adjust the current operating condition parameters of the boiler.

7. A method for controlling energy conservation of boilers in thermal power plants, characterized in that: The method comprises: Obtain the operating parameters of the thermal power plant boiler, and predict the current boiler operating efficiency based on the operating parameters of the thermal power plant boiler; The boiler input parameters are optimized based on the particle swarm algorithm, the optimal operating condition parameter combination is determined according to the optimization results, and the adjustment step length of the optimal operating condition parameter combination is set according to the predicted value of the operating efficiency; Obtain NOx emission data from thermal power plant boilers and calculate the fluctuation degree of NOx emissions based on the NOx emission data; Set emission weights according to the degree of fluctuation, and set the correction value of the optimal operating condition parameter combination according to the emission weights; Control the boiler of a thermal power plant according to the correction value of the optimal operating condition parameter combination; The calculation of the fluctuation degree of NOx emissions according to the NOx emission data includes: Determine the NOx emission concentration based on the NOx emission data of the thermal power plant boiler, and draw the NOx emission concentration change curve based on the change trend of NOx emission concentration over time; Create a number of rolling time windows, set the window size of the rolling time window according to the curve length of the NOx emission concentration change curve, and segment the NOx emission concentration change curve according to the rolling time window; Calculate the average value of NOx emission concentration in the rolling time window after segmentation, and draw a NOx emission concentration average value change curve according to the average value of NOx emission concentration in each rolling window; Calculate the absolute values ​​of the slopes of two adjacent points in the NOx emission concentration average value change curve, and filter out data whose absolute values ​​of the slopes exceed a first preset threshold value; set the proportion of the number of data whose absolute values ​​of the slopes exceed the first preset threshold value in the NOx emission concentration average value change curve as the degree of fluctuation of NOx emissions; The step of setting the emission weight according to the degree of fluctuation and setting the correction value of the optimal operating condition parameter combination according to the emission weight includes: Calculating the ratio of the fluctuation degree of NOx emissions to the preset allowable fluctuation degree, and normalizing the ratio of the fluctuation degree of NOx emissions to the preset allowable fluctuation degree; The ratio of the normalized NOx emission fluctuation degree to the preset allowable fluctuation degree is set as the emission weight, and the emission weight is multiplied by the preset standard correction value to obtain the correction value of the optimal operating condition parameter combination; After the emission weight is set according to the fluctuation degree and the correction value of the optimal operating condition parameter combination is set according to the emission weight, the method further includes: Obtain operating condition parameters within a preset period based on historical boiler operating data, and calculate correlation coefficients between each operating condition parameter and NOx emission concentration based on the operating condition parameters within the preset period; The correlation coefficient between each operating condition parameter and NOx emission concentration is used as the adjustment coefficient of each operating condition parameter, and the correction value of each operating condition parameter in the optimal operating condition parameter combination is adjusted according to the adjustment coefficient of each operating condition parameter.

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