Coal electric boiler performance real-time analysis control method, system and equipment and storage medium

Abstract

The invention relates to a coal electric boiler performance real-time analysis control method, system and device and a storage medium. The method comprises the steps that state data of the device during operation are collected from measuring points of a boiler system; obtaining a pre-constructed feature vector model, and performing data analysis on the state data according to the feature vector model to obtain a feature vector; and analyzing the operation state of the equipment according to the feature vector, if the operation state is abnormal, determining an abnormal type, adjusting the equipment according to the abnormal type, and sending an early warning signal. According to the method, the actual operation parameters of the boiler body and the auxiliary machines are obtained in real time, the real-time conditions of the boiler efficiency, the air leakage rate and the auxiliary machine power consumption rate in actual operation are obtained, accordingly, reasons for low boiler efficiency and high auxiliary machine system power consumption rate are known, adjustment is conducted according to proposed targeted suggestions, the energy efficiency of a boiler unit is improved, and the energy efficiency of the boiler unit is improved. And finally, operating parameters of each load section of the boiler are close to design values, and unit coal consumption is reduced.

Description

Technical Field

[0001] The present application relates to the field of boiler control technology, and in particular to a method, system, device and storage medium for real-time analysis and control of coal-fired power boiler performance. Background Art

[0002] The large-scale grid connection of renewable energy has led to the complexity of peak load regulation and frequent changes in load. Due to the need for deep peak load regulation, the actual operating hours of thermal power units have decreased year by year, resulting in the units operating at medium and low loads for a long time. Therefore, the accuracy of the control system needs to be further improved.

[0003] Faced with the characteristics of this type of new power system, the traditional thermal power generation mode has many problems. First, in the face of a large amount of real-time data monitoring and processing, it is very difficult to rely on manual judgment, analysis, intervention and processing; secondly, due to the rapid and sudden load changes and peak-shaving needs of the new power system, it is difficult to meet the real-time requirements of the traditional coordinated control and manual intervention mode, and the rapid response capability is poor; finally, the manual power generation method usually makes decisions based on experience and rules, and there are often great limitations in accuracy and prediction ability, resulting in high energy and material consumption, and increasing operating costs. Therefore, the trend of large-scale renewable energy access has higher requirements for coal-fired power units in terms of safe production, flexibility, efficiency, and green economy, but the current traditional thermal power generation operation mode cannot meet the development needs of the new power system. Summary of the invention

[0004] The embodiments of the present application provide a method, system, device and storage medium for real-time analysis and control of coal-fired power boiler performance, so as to at least solve the problem in the related technology that traditional coordinated control and manual intervention modes are difficult to meet in real time and have poor rapid response capabilities.

[0005] In a first aspect, an embodiment of the present application provides a method for real-time analysis and control of coal-fired power boiler performance, comprising:

[0006] Collect equipment operation status data from the boiler system's measurement points;

[0007] Acquire a pre-built feature vector model, and perform data analysis on the state data according to the feature vector model to obtain a feature vector;

[0008] The operating state of the device is analyzed according to the characteristic vector. If the operating state is abnormal, the abnormality type is determined, the device is adjusted according to the abnormality type, and an early warning signal is issued.

[0009] In one embodiment, the construction of the feature vector model includes:

[0010] Acquiring historical status data of the boiler system and status characteristics of the equipment;

[0011] Analyzing the historical status data according to the status characteristics to identify key factors affecting boiler performance;

[0012] Analyze the historical status data corresponding to the key factors, identify the historical status data that is most sensitive to the change in boiler performance, and record it as a feature vector;

[0013] A mapping relationship is constructed based on the selected feature vector and the corresponding state characteristic to obtain the feature vector model.

[0014] In one embodiment, the historical status data corresponding to the key factors are analyzed to identify the historical status data most sensitive to the boiler performance change, which is recorded as a feature vector, including:

[0015] Preprocessing the historical state data to obtain an initial feature vector, wherein the preprocessing includes cleaning, converting and standardizing the data;

[0016] Extracting new features that can represent data features from the initial feature vector;

[0017] The new features are analyzed by a feature selection algorithm, and the most representative features are selected from the extracted features to obtain the feature vector.

[0018] In one embodiment, analyzing the operating status of the device according to the feature vector includes:

[0019] Obtain energy efficiency index standards for evaluating boiler system performance;

[0020] Calculate the boiler real-time efficiency, boiler-side power consumption rate and air preheater leakage rate of the boiler system in the current state according to the characteristic vector;

[0021] Determine whether the boiler real-time efficiency, boiler-side power consumption rate and air preheater air leakage rate meet the energy efficiency index standard;

[0022] If not, it is determined that the current operating state of the boiler system is abnormal.

[0023] In one embodiment, the state data includes DCS operation parameters, coal quality detection parameters and fly ash / CO detection parameters; the energy efficiency index standard values ​​include boiler efficiency standards, boiler side power consumption rate standards and air preheater leakage rate standards;

[0024] Wherein, determining the abnormality type includes:

[0025] Calculate the power consumption rate of the boiler side and the air preheater leakage rate according to the DCS operation parameters; calculate the real-time efficiency of the boiler according to the DCS operation parameters, coal quality detection parameters and fly ash / CO detection parameters;

[0026] When the real-time efficiency of the boiler does not meet the boiler efficiency standard, the boiler system efficiency is judged to be abnormal; when the boiler side power consumption rate does not meet the boiler side power consumption rate standard, the boiler system power consumption is judged to be abnormal; when the air preheater leakage rate does not meet the air preheater leakage rate standard, the boiler system leakage is judged to be abnormal.

[0027] In one embodiment, the issuing of an early warning signal comprises:

[0028] Calculating the boiler-side power consumption rate and the boiler-side power consumption rate standard, and outputting a first alarm message if the difference between the boiler-side power consumption rate and the boiler-side power consumption rate standard is greater than a first threshold value;

[0029] Calculating the air preheater leakage rate and the air preheater leakage rate standard, and outputting a second alarm message if the difference between the air preheater leakage rate and the air preheater leakage rate standard is greater than a second threshold value;

[0030] The boiler real-time efficiency and the boiler efficiency standard are calculated, and if the difference between the boiler real-time efficiency and the boiler efficiency standard is less than a third threshold, a third alarm message is output.

[0031] In one embodiment, adjusting the device according to the abnormality type includes:

[0032] When the abnormal situation is that the efficiency of the boiler system is abnormal, the air-coal ratio and the furnace negative pressure are adjusted;

[0033] When the abnormal situation is abnormal power consumption of the boiler system, the power consumption of the primary fan, the blower, the induced draft fan, the coal mill or the additional fan is adjusted;

[0034] When the abnormal situation is abnormal air leakage in the boiler system, the inlet and outlet air volumes of the air preheater are adjusted.

[0035] In a second aspect, the embodiment of the present application provides a real-time analysis and control system for performance of a coal-fired power boiler, including:

[0036] A data acquisition module is used to collect status data of equipment when the boiler is running from the measuring points of the boiler system;

[0037] A feature analysis module, used to obtain a pre-built feature vector model, and to perform data analysis and extraction on the state data according to the feature vector model to obtain a feature vector;

[0038] The abnormal warning module is used to analyze the operating status of the device according to the characteristic vector. If the operating status is abnormal, the abnormal situation is analyzed to determine the abnormal type, the device is adjusted according to the abnormal type, and a warning signal is issued.

[0039] In a third aspect, an embodiment of the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the real-time analysis and control method for the performance of a coal-fired power boiler as described in the first aspect above is implemented.

[0040] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the real-time analysis and control method for the performance of a coal-fired power boiler as described in the first aspect above.

[0041] The coal-fired power boiler performance real-time analysis and control method, system, device and storage medium provided by the embodiments of the present application have at least the following technical effects:

[0042] By acquiring the actual operating parameters of the boiler and auxiliary equipment in real time, the real-time status of the boiler efficiency, air leakage rate, and auxiliary equipment power consumption rate in actual operation can be obtained. By comparing the real-time data of boiler efficiency, air leakage rate, and auxiliary equipment power consumption rate with the design values, the reasons for the low boiler efficiency and high power consumption rate of each auxiliary system can be understood, and adjustments can be made based on the targeted suggestions put forward, thereby improving the energy efficiency of the boiler unit. Finally, it is ensured that the operating parameters of each load section of the boiler are close to the design values ​​to reduce the coal consumption of the unit.

[0043] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0045] Figure 1 is a flow chart of a method for real-time analysis and control of coal-fired power boiler performance in one embodiment of the present application;

[0046] Figure 2 It is an analysis logic diagram of a real-time analysis and control method for coal-fired power boiler performance in one embodiment of the present application;

[0047] Figure 3 It is a structural block diagram of an electronic device in one embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0049] Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. In addition, it can also be understood that although the efforts made in this development process may be complicated and lengthy, for ordinary technicians in this field related to the content disclosed in this application, some changes in design, manufacturing or production based on the technical content disclosed in this application are just conventional technical means, and should not be understood as insufficient content disclosed in this application.

[0050] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0051] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0052] At present, coal-fired power units are faced with the challenges of frequent participation in peak load regulation and environmental problems caused by large-scale coal burning, which leads to abnormal energy consumption levels in the actual operation of the units. Parameters such as the calorific value of the coal entering the boiler system, the carbon content of fly ash, and the exhaust enthalpy in the turbine system cannot be measured online due to the limitations of measurement technology. Most of them are analyzed through manual testing, which has a large delay and cannot guide production in a timely manner.

[0053] Based on the above situation, the embodiments of the present application provide a method, system, device and storage medium for real-time analysis and control of coal-fired power boiler performance. The present invention can reflect the operating status and energy efficiency status of boiler equipment in real time online. Through a series of basic research on boiler equipment operating status monitoring, timely monitoring and alarming are performed when boiler energy efficiency abnormalities occur, reducing the probability of equipment failure, maintaining the inherent performance of boiler equipment, and improving the health management level of various systems and equipment on the boiler side.

[0054] In a first aspect, the present application provides a method for real-time analysis and control of coal-fired power boiler performance. Figure 1 is a flow chart, such as Figure 1 As shown, the method is implemented by the following steps.

[0055] Step S1, collecting status data of equipment during operation from measuring points of the boiler system.

[0056] Step S2, obtaining a pre-constructed feature vector model, and performing data analysis on the state data according to the feature vector model to obtain a feature vector.

[0057] Specifically, the historical status data of the boiler system and the status characteristics of the equipment are obtained; the historical status data are analyzed according to the status characteristics to identify the key factors affecting the boiler performance; the historical status data corresponding to the key factors are analyzed to identify the historical status data most sensitive to the change in boiler performance and record them as feature vectors; a mapping relationship is constructed based on the selected feature vectors and the corresponding status characteristics to obtain the feature vector model.

[0058] Among them, the historical status data is preprocessed to obtain an initial feature vector, and the preprocessing includes data cleaning, conversion and standardization; new features that can represent data characteristics are extracted from the initial feature vector; the new features are analyzed by a feature selection algorithm, and the most representative features are selected from the extracted features to obtain the feature vector.

[0059] In one embodiment, the process of selecting a suitable feature vector involves multiple steps, including data preprocessing, feature extraction, and feature selection.

[0060] First, data preprocessing is the premise of feature selection, which includes steps such as data cleaning, conversion and standardization. For example, for numerical data, you can calculate the mean and standard deviation using the formula Convert the original value into an eigenvector, where vi is the converted eigenvector, xi is the original eigenvalue, μ is the mean, and σ is the standard deviation

[0061] Secondly, feature extraction is to extract new features that can represent the data characteristics from the original data, such as temperature, load, pressure and other data.

[0062] Finally, feature selection is to select the most representative feature vectors from the extracted features. This can be achieved by analyzing the relevance and importance of the features or by using some feature selection algorithms. For example, information gain, correlation coefficient or model-based feature selection methods can be used to select the most important feature vectors.

[0063] In addition, for categorical data, feature vectors can be converted through univariate consistency checks and multivariate consistency checks; for string data, string matching and string edit distance calculation can be used for conversion.

[0064] The feature vector model is built by converting the raw data into a vector consisting of a set of features. These features can be numerical, categorical, or other types of data that represent the location of data points in the feature space. The process of building a feature vector involves the following key steps:

[0065] Identify features: You need to determine which features best describe the data points. Features can be numerical (such as temperature, pressure, flow), categorical (such as coal consumption, electricity consumption), or other types of data. These features directly or indirectly describe the data points to facilitate data analysis and machine learning tasks;

[0066] Composing feature vectors: Combine the selected features into a vector, the feature vector. Each element of the feature vector corresponds to the value of a feature, forming a high-dimensional mathematical space whose dimension is equal to the number of features in the feature vector;

[0067] Application data processing and analysis tasks: Feature vectors can be used for various data processing and analysis tasks, such as classification, clustering, dimensionality reduction, etc. For example, in classification tasks, the feature vectors of data points can be mapped to different categories; in clustering tasks, data points can be divided into different groups according to the distance between feature vectors.

[0068] Through the above steps, an effective feature vector model is established to support data analysis and machine learning tasks, improve algorithm performance and promote data understanding and application

[0069] Step S3, analyzing the operating state of the device according to the feature vector, and if the operating state is abnormal, determining the abnormality type, adjusting the device according to the abnormality type, and issuing an early warning signal.

[0070] Specifically, an energy efficiency index standard for evaluating the performance of a boiler system is obtained; the real-time boiler efficiency, boiler-side power consumption rate and air preheater leakage rate of the boiler system in the current state are calculated according to the characteristic vector; it is determined whether the real-time boiler efficiency, boiler-side power consumption rate and air preheater leakage rate meet the energy efficiency index standard; if not, it is determined that the current operating state of the boiler system is abnormal.

[0071] The state data includes DCS operation parameters, coal quality detection parameters and fly ash / CO detection parameters; the energy efficiency index standard value includes boiler efficiency standard, boiler side power consumption rate standard and air preheater leakage rate standard. In the process of determining the abnormality type, the boiler side power consumption rate and air preheater leakage rate are first calculated according to the DCS operation parameters; the real-time efficiency of the boiler is calculated according to the DCS operation parameters, coal quality detection parameters and fly ash / CO detection parameters; when the real-time efficiency of the boiler does not meet the boiler efficiency standard, the efficiency of the boiler system is judged to be abnormal; when the power consumption rate of the boiler side does not meet the power consumption rate standard of the boiler side, the power consumption of the boiler system is judged to be abnormal; when the air preheater leakage rate does not meet the air preheater leakage rate standard, the air leakage of the boiler system is judged to be abnormal.

[0072] The process of issuing the early warning signal includes: calculating the power consumption rate of the boiler side and the power consumption rate standard of the boiler side, and if the difference between the power consumption rate of the boiler side and the power consumption rate standard of the boiler side is greater than a first threshold, outputting a first alarm message; calculating the air preheater leakage rate and the air preheater leakage rate standard, and if the difference between the air preheater leakage rate and the air preheater leakage rate standard is greater than a second threshold, outputting a second alarm message; calculating the real-time efficiency of the boiler and the boiler efficiency standard, and if the difference between the real-time efficiency of the boiler and the boiler efficiency standard is less than a third threshold, outputting a third alarm message.

[0073] Exemplary, reference Figure 2 , first obtain the operation, detection or analysis parameters in the DCS, coal quality online analysis device and fly ash / CO online monitoring device. Among them, the DCS operation parameters include operating parameters such as air temperature / pressure, as well as the power consumption of the forced / induced draft fan, coal mill desulfurization system, air preheater inlet and outlet oxygen, operating oxygen, exhaust gas temperature and other parameters; the coal quality online analysis device can output parameters such as coal moisture, ash content, calorific value, elemental composition, etc.; the fly ash / CO online monitoring device can output parameters such as real-time fly ash carbon content / CO concentration.

[0074] Then, based on the above parameters, the power consumption rate of the boiler auxiliary system, the air preheater leakage rate, the exhaust heat loss, the unburned carbon heat loss and other heat losses are calculated, and then the boiler real-time efficiency is calculated based on the exhaust heat loss, the unburned carbon heat loss and other heat losses. Then, the power consumption rate of the boiler auxiliary system, the air preheater leakage rate and the boiler real-time efficiency are compared with the preset values. When they exceed a certain range, an alarm signal can be output and targeted operation suggestions can be made.

[0075] The adjustment of the equipment according to the abnormality type includes: when the abnormality is abnormal efficiency of the boiler system, adjusting the air-coal ratio and the furnace negative pressure; when the abnormality is abnormal power consumption of the boiler system, adjusting the power consumption of the primary fan, the blower, the induced draft fan, the coal mill or the additional fan; when the abnormality is abnormal air leakage of the boiler system, adjusting the inlet and outlet air volume of the air preheater.

[0076] In summary, the real-time analysis and control method for coal-fired power boiler performance provided in the embodiment of the present application can achieve the development goals of coal-fired power units with higher efficiency, low carbon and environmental protection by adding a real-time analysis and control system for boiler performance. Research is conducted on the performance status monitoring system of coal-fired power units, and a system is developed and manufactured that can be well applied to the operation process of the unit, complete the real-time status identification task, and reduce the supervision work of operators; improve the economy and reliability of the actual operation of the unit, etc., and reduce maintenance costs; through the fusion of data + mechanism model, the operating status of the boiler equipment is judged in real time, and energy efficiency rating is performed, and when the boiler energy efficiency abnormality occurs, timely monitoring and alarm are issued, the probability of equipment failure is reduced, the inherent performance of the boiler equipment is maintained, and the health management level of various systems and equipment on the boiler side is improved.

[0077] On the second aspect, in another embodiment of the present invention, the embodiment of the present application provides a real-time analysis and control system for the performance of a coal-fired power boiler. The system mainly includes three modules: data collection, feature analysis and abnormal warning.

[0078] Specifically, the data acquisition module is used to collect status data of the equipment when the boiler is running from the measuring points of the boiler system; the feature analysis module is used to obtain a pre-constructed feature vector model, perform data analysis and extraction on the status data according to the feature vector model, and obtain a feature vector; the abnormal warning module is used to analyze the operating status of the equipment according to the feature vector, and if the operating status is abnormal, analyze the abnormal situation, determine the abnormal type, adjust the equipment according to the abnormal type, and issue a warning signal.

[0079] The present invention reads various steam-water parameters, exhaust gas temperature, operating oxygen content, fuel consumption and other parameters in the actual operation of the boiler from the system measurement points, obtains signals related to the equipment status, obtains equipment status information, and completes the data acquisition module. By combining the state characteristics of the monitoring system or equipment with the data, the characteristic vector that is most sensitive to the state change is selected, and a characteristic vector model is established to complete the characteristic vector extraction. According to the extracted characteristic vector, the states of different working conditions are classified. The classification is based on normal working condition data such as stable load, load increase, and load decrease. It is judged whether the state is normal, and the abnormal state detected is monitored in time for early warning processing and analysis. The abnormal state mainly includes abnormal boiler energy efficiency state and abnormal auxiliary power consumption rate. It is also possible to predict the change of boiler efficiency after the coal quality changes through the correction curve of the built-in coal quality parameters for the boiler efficiency.

[0080] In the embodiment of the present application, the main energy efficiency indicators for evaluating the boiler system are: boiler efficiency, boiler side power consumption rate, etc. There are two methods for calculating boiler efficiency: positive balance method and negative balance method. The negative balance method is often used in thermal system calculations, and the positive balance method is used for verification. According to the ASME negative balance calculation method, the various heat losses mainly include incomplete combustion heat loss, radiation convection heat loss, dry flue gas heat loss, heat loss caused by fuel moisture, heat loss caused by humidity in the air, and other heat losses.

[0081] In one embodiment, the calculation process of boiler efficiency, boiler-side power consumption rate and air preheater leakage rate is as follows. For example, boiler thermal efficiency refers to the percentage of effective heat utilization of the boiler to the low calorific value of the boiler input fuel, and its calculation formula is as follows:

[0082]

[0083] Where η g is the boiler thermal efficiency; Q ar,net is the low calorific value per kilogram of fuel; Q1 is the effectively utilized part of the low calorific value per kilogram of fuel, which can also be called output heat. The method of directly calculating the thermal efficiency of the boiler using the above formula is called the input-output heat method (also known as the positive balance method).

[0084] In another embodiment, according to the provisions of GB / T 10184 and DL / T 964, in order to more accurately calculate the thermal efficiency of the boiler, the heat loss method (also known as the counter-balance method) can also be used to calculate the thermal efficiency, and the formula is:

[0085]

[0086] In the formula, Q2 is the heat loss of flue gas per kilogram of fuel; Q3 is the heat loss of incomplete combustion of combustible gas per kilogram of fuel; Q4 is the heat loss of incomplete combustion of solid per kilogram of fuel; Q5 is the heat loss of boiler heat dissipation per kilogram of fuel; Q6 is the physical sensible heat loss of ash per kilogram of fuel; Q7 is the heat loss due to limestone pyrolysis and desulfurization per kilogram of fuel, which only exists in boilers with in-furnace desulfurization; q2 is the heat loss of flue gas; q3 is the heat loss of incomplete combustion of combustible gas; q4 is the heat loss caused by incomplete combustion of solid in limestone pyrolysis and desulfurization, which only exists in boilers with in-furnace desulfurization.

[0087] The air preheater leakage rate refers to the ratio of the air mass flow rate leaking into the flue gas side of the air preheater to the flue gas mass flow rate entering the air preheater (%). The air preheater leakage rate in operation can be estimated by the excess air coefficient at the inlet and outlet of the air preheater. The calculation formula is:

[0088]

[0089] Where AL is the air leakage rate of the cavity preheater; α' is the excess air coefficient of the flue gas at the inlet of the air preheater; α" is the excess air coefficient of the flue gas at the outlet of the air preheater.

[0090] Auxiliary machine power consumption rate = power consumption of this type of auxiliary machine or system / power generation during the statistical period, which is the percentage of power consumption of this type of auxiliary machine or system to the power generation during the statistical period.

[0091] According to the equipment function and energy efficiency analysis of the boiler system, when the coal quality and other operating conditions remain unchanged, when the boiler efficiency decreases or the power consumption rate of the boiler system auxiliary equipment increases, it indicates that the operating energy efficiency of the boiler and its auxiliary systems has decreased, and it is necessary to improve the operating status of the boiler system through reasonable operation adjustments. The energy efficiency characteristic indicators of the boiler system are shown in the following table.

[0092] Table 1: Boiler system energy efficiency characteristic indicators

[0093]

[0094] Abnormal boiler energy efficiency status includes low boiler efficiency and high power consumption rate of auxiliary equipment on the boiler side. Abnormal boiler efficiency is a common energy efficiency abnormality event during boiler operation. The boiler efficiency obtained from the thermal test or monthly test after the unit maintenance is compared with the manufacturer's design value. For example, when the boiler efficiency degradation deviation is less than 0.5 percentage points, it is a yellow alarm, 0.5-15 percentage points is an orange alarm, and greater than 1.5 percentage points is a red alarm. Low boiler efficiency is mostly caused by poor coal quality, abnormal combustion adjustment, serious air leakage, etc., which are specifically manifested as excessive boiler exhaust temperature, abnormal exhaust oxygen content, and excessive ash carbon content in the furnace. In this case, the air-coal ratio and furnace negative pressure should be reasonably controlled to keep the flame center in a reasonable position.

[0095] The abnormal power consumption rate of auxiliary equipment in the boiler system is usually caused by excessive air leakage rate of the furnace and air preheater, as shown in Table 2. The deterioration of the coal quality entering the furnace leads to excessive power consumption of the wind and smoke system and the pulverizing system. This requires taking corresponding sealing measures for the furnace and air preheater, including radial, axial and circumferential sealing; controlling the air-coal ratio of the boiler to ensure that the excess air coefficient is within a reasonable range; adjusting the combustion conditions inside the boiler through coal quality analysis feedback. The abnormal power consumption rate of auxiliary equipment in the turbine system is mainly manifested in the excessive power consumption rate of the condensate pump and the circulating water pump. The operation of the condensate pump and the circulating water pump should be closely monitored, the inlet filter should be replaced and cleaned regularly to ensure the filter is clean, and the condenser heat load should be checked.

[0096] Table 2: Boiler system energy efficiency abnormal events table

[0097]

[0098] It should be noted that the real-time analysis and control system for coal-fired power boiler performance provided in this embodiment is used to implement the above-mentioned implementation mode, and the descriptions that have been made will not be repeated. As used above, the terms "module", "unit", "subunit", etc. can implement a combination of software and / or hardware for a predetermined function. Although the device described in the above embodiment is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0099] In a third aspect, an embodiment of the present application provides an electronic device, Figure 3 FIG. 1 is a block diagram of an electronic device according to an exemplary embodiment. Figure 3 As shown, the electronic device may include a processor 11 and a memory 12 storing computer program instructions.

[0100] Specifically, the processor 11 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0101] Among them, the memory 12 may include a large-capacity memory for data or instructions. By way of example and not limitation, the memory 12 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 12 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 12 may be inside or outside a data processing device. In a specific embodiment, the memory 12 is a non-volatile memory. In a specific embodiment, the memory 12 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, PROM for short), an erasable PROM (Erasable ProgrammableRead-Only Memory, EPROM for short), an electrically erasable PROM (Electrically Erasable ProgrammableRead-Only Memory, EEPROM for short), an electrically alterable ROM (Electrically Alterable Read-Only Memory, EAROM for short) or a flash memory (FLASH) or a combination of two or more of these. Under appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), wherein the DRAM can be a fast page mode dynamic random access memory (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0102] The memory 12 may be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 11 .

[0103] The processor 11 reads and executes computer program instructions stored in the memory 12 to implement any one of the coal-fired power boiler performance real-time analysis and control methods in the above embodiments.

[0104] In one embodiment, the electronic device may further include a communication interface 13 and a bus 10. Figure 3 As shown, the processor 11, the memory 12, and the communication interface 13 are connected via a bus 10 and communicate with each other.

[0105] The communication interface 13 is used to realize the communication between the modules, devices, units and / or equipment in the embodiment of the present application. The communication port 13 can also realize data communication with other components such as: external devices, image / data acquisition equipment, databases, external storage and image / data processing workstations.

[0106] The bus 10 includes hardware, software or both, and couples the components of the electronic device to each other. The bus 10 includes but is not limited to at least one of the following: a data bus, an address bus, a control bus, an expansion bus, and a local bus. By way of example and not limitation, bus 10 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, bus 10 may include one or more buses. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.

[0107] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the real-time analysis and control method for the performance of a coal-fired power boiler provided in the first aspect.

[0108] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0109] In a possible implementation, the present invention can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of the real-time analysis and control method of coal-fired boiler performance provided in the first aspect.

[0110] The program code for executing the present invention may be written in any combination of one or more programming languages, and may be executed entirely on a user device, partially on a user device, as an independent software package, partially on a user device and partially on a remote device, or entirely on a remote device.

[0111] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0112] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A real-time analysis and control method for coal-fired power boiler performance, characterized in that: include: Collect equipment operation status data from the boiler system's measurement points; Acquire a pre-built feature vector model, and perform data analysis on the state data according to the feature vector model to obtain a feature vector; The operating state of the device is analyzed according to the characteristic vector. If the operating state is abnormal, the abnormality type is determined, the device is adjusted according to the abnormality type, and an early warning signal is issued.

2. The method for real-time analysis and control of coal-fired power boiler performance according to claim 1, characterized in that: The construction of the feature vector model includes: Acquiring historical status data of the boiler system and status characteristics of the equipment; Analyzing the historical status data according to the status characteristics to identify key factors affecting boiler performance; Analyze the historical status data corresponding to the key factors, identify the historical status data that is most sensitive to the change in boiler performance, and record it as a feature vector; A mapping relationship is constructed based on the selected feature vector and the corresponding state characteristic to obtain the feature vector model.

3. The method for real-time analysis and control of coal-fired power boiler performance according to claim 2 is characterized in that: The historical state data corresponding to the key factors are analyzed to identify the historical state data most sensitive to boiler performance changes, which are recorded as feature vectors, including: Preprocessing the historical state data to obtain an initial feature vector, wherein the preprocessing includes cleaning, converting and standardizing the data; Extracting new features that can represent data features from the initial feature vector; The new features are analyzed by a feature selection algorithm, and the most representative features are selected from the extracted features to obtain the feature vector.

4. The method for real-time analysis and control of coal-fired power boiler performance according to claim 1, characterized in that: The analyzing the operating state of the device according to the feature vector includes: Obtain energy efficiency index standards for evaluating boiler system performance; Calculate the boiler real-time efficiency, boiler-side power consumption rate and air preheater leakage rate of the boiler system in the current state according to the characteristic vector; Determine whether the boiler real-time efficiency, boiler-side power consumption rate and air preheater air leakage rate meet the energy efficiency index standard; If not, it is determined that the current operating state of the boiler system is abnormal.

5. The method for real-time analysis and control of coal-fired power boiler performance according to claim 4 is characterized in that: The state data includes DCS operation parameters, coal quality detection parameters and fly ash / CO detection parameters; the energy efficiency index standard values ​​include boiler efficiency standards, boiler side power consumption rate standards and air preheater leakage rate standards; Wherein, determining the abnormality type includes: Calculate the power consumption rate of the boiler side and the air preheater leakage rate according to the DCS operation parameters; calculate the real-time efficiency of the boiler according to the DCS operation parameters, coal quality detection parameters and fly ash / CO detection parameters; When the real-time efficiency of the boiler does not meet the boiler efficiency standard, it is determined that the boiler system efficiency is abnormal; when the boiler side power consumption rate does not meet the boiler side power consumption rate standard, it is determined that the boiler system power consumption is abnormal; when the air preheater leakage rate does not meet the air preheater leakage rate standard, it is determined that the boiler system leakage is abnormal.

6. The method for real-time analysis and control of coal-fired power boiler performance according to claim 5, characterized in that: The issuing of the early warning signal comprises: Calculating the boiler-side power consumption rate and the boiler-side power consumption rate standard, and outputting a first alarm message if the difference between the boiler-side power consumption rate and the boiler-side power consumption rate standard is greater than a first threshold value; Calculating the air preheater leakage rate and the air preheater leakage rate standard, and outputting a second alarm message if the difference between the air preheater leakage rate and the air preheater leakage rate standard is greater than a second threshold value; The boiler real-time efficiency and the boiler efficiency standard are calculated, and if the difference between the boiler real-time efficiency and the boiler efficiency standard is less than a third threshold, a third alarm message is output.

7. The method for real-time analysis and control of coal-fired power boiler performance according to claim 6, characterized in that: The adjusting the device according to the abnormality type comprises: When the abnormal situation is that the efficiency of the boiler system is abnormal, the air-coal ratio and the furnace negative pressure are adjusted; When the abnormal situation is abnormal power consumption of the boiler system, the power consumption of the primary fan, the blower, the induced draft fan, the coal mill or the additional fan is adjusted; When the abnormal situation is abnormal air leakage in the boiler system, the inlet and outlet air volumes of the air preheater are adjusted.

8. A real-time analysis and control system for coal-fired power boiler performance, characterized in that: include: A data acquisition module is used to collect status data of equipment when the boiler is running from the measuring points of the boiler system; A feature analysis module, used to obtain a pre-built feature vector model, and to perform data analysis and extraction on the state data according to the feature vector model to obtain a feature vector; The abnormal warning module is used to analyze the operating status of the device according to the characteristic vector. If the operating status is abnormal, the abnormal situation is analyzed to determine the abnormal type, the device is adjusted according to the abnormal type, and a warning signal is issued.

9. An electronic device, characterized in that: It comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the real-time analysis and control method for the performance of a coal-fired power boiler as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the real-time analysis and control method for the performance of a coal-fired power boiler according to any one of claims 1 to 7 is implemented.

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