CN115309129A - SCR denitration efficiency automatic optimization regulation and control method and system - Google Patents
SCR denitration efficiency automatic optimization regulation and control method and system Download PDFInfo
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- G05B19/00—Programme-control systems
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- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
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- B01D53/00—Separation of gases or vapours; Recovering vapours of volatile solvents from gases; Chemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases, aerosols
- B01D53/34—Chemical or biological purification of waste gases
- B01D53/74—General processes for purification of waste gases; Apparatus or devices specially adapted therefor
- B01D53/86—Catalytic processes
- B01D53/8621—Removing nitrogen compounds
- B01D53/8625—Nitrogen oxides
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- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
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Abstract
The application relates to an automatic optimizing regulation and control method and system for SCR denitration efficiency, wherein the method comprises the following steps: acquiring historical data, and dividing the historical data based on working condition division points to obtain data of a plurality of working condition intervals; based on the data of the working condition interval, constructing an automatic optimization model for regulating and controlling the generation concentration of NOx; in actual operation, matching according to the current value of the working condition index in the actual data to obtain a corresponding working condition interval; respectively sequencing the data values of all working condition indexes in the working condition interval according to a preset sequence through an automatic optimization model; and according to the sequencing result, calculating the optimal value of each working condition index through an automatic optimization searching model. Through the method and the device, the problem of how to compromise the operating efficiency of the boiler and the operating cost of SCR denitration is solved, the optimal value of each working condition index in the boiler unit is calculated based on the optimizing model, and the generation concentration of NOx in the boiler is effectively regulated and controlled so as to compromise the efficiency and the cost.
Description
Technical Field
The application relates to the technical field of industrial waste gas purification, in particular to an automatic optimizing and regulating method and system for SCR denitration efficiency.
Background
SCR (Selective Catalytic Reduction) denitration is also called a Selective Catalytic Reduction method, and is currently the most internationally applied flue gas denitration technology, and ammonia (NH 3) is generally used as a reducing agent to selectively reduce generated NOx to N2. The device has the advantages of no by-product, no secondary pollution, simple structure, high separation efficiency (up to more than 90%), reliable operation, convenient maintenance and the like. The low-nitrogen combustion and SCR flue gas denitration technology is a mainstream technology for coal-fired boiler denitration ultra-low emission, the combustion in the boiler is difficult to control and low in boiler efficiency under the large situation of deep peak regulation, and an SCR denitration system is faced with a series of problems of air preheater blockage, high operation cost and the like.
The NOx concentration generation is reduced by adjusting the low-nitrogen operation mode, so that the cost of a denitration system is reduced, the boiler efficiency is correspondingly sacrificed, and the operation cost of the boiler side is improved; on the contrary, the sacrifice of boiler efficiency can be avoided in the formation of NOx in the high-concentration boiler, but the cost of a denitration system can be increased, and the technical problem that how to give consideration to the combustion formation of low-nitrogen NOx and the optimal economic operation of SCR denitration operation cost is urgently needed to be solved in the current electric power environmental protection field is solved. With the trend of intellectualization of coal-fired power plants, the existing optimization and adjustment mode still cannot effectively solve the outstanding contradiction between high-efficiency combustion and low NOx emission of the existing coal-fired boiler.
At present, an effective solution is not provided aiming at the problem of how to consider the operation efficiency of the boiler and the operation cost of SCR denitration in the related technology.
Disclosure of Invention
The embodiment of the application provides an automatic optimizing and regulating method and system for SCR denitration efficiency, and the method and system at least solve the problem that how to consider the boiler operation efficiency and the SCR denitration operation cost in the related technology.
In a first aspect, an embodiment of the present application provides an automatic optimization regulation and control method for SCR denitration efficiency, where the method includes:
acquiring historical data, and dividing the historical data based on working condition division points to obtain data of a plurality of working condition intervals;
constructing an automatic optimizing model for regulating and controlling the generation concentration of NOx based on the data of the working condition interval;
in actual operation, according to the current value of the working condition index in the actual data, matching to obtain a corresponding working condition interval;
respectively sequencing the data values of all the working condition indexes in the working condition interval according to a preset sequence through the automatic optimization searching model;
and according to the sequencing result, calculating the optimal value of each working condition index through the automatic optimizing model.
In some embodiments, obtaining historical data, and dividing the historical data based on the operating condition dividing points to obtain data of a plurality of operating condition intervals includes:
acquiring historical data;
setting the division number, and averagely dividing the historical data according to the (upper limit value of the working condition division point-lower limit value of the working condition division point)/the division number to obtain data of a plurality of working condition intervals, wherein the working condition division point comprises main steam flow and unit load.
In some embodiments, in the actual operation, matching to obtain the corresponding operating condition interval according to the current value of the operating condition index in the actual data includes:
in actual operation, the formula is used
Calculating Euclidean distance between the actual data and each working condition interval, and matching to obtain the working condition interval with the minimum Euclidean distance, wherein,x i as an index of working conditions in actual dataiThe current value of (a) is,y i is an index of the working conditions in the working condition intervaliThe center value of (c).
In some embodiments, the sorting, by the automatic optimization model, the data values of the operating condition indexes in the operating condition interval according to a preset sequence includes:
configuring the index value of the working condition index in the working condition interval through the automatic optimization searching model;
if the index value is larger and the data value corresponding to the working condition index is more optimal, sorting the data values of the working condition indexes respectively according to the sequence of the index values from large to small;
and if the smaller the index value is, the better the data value corresponding to the working condition index is, sorting the data values of the working condition indexes respectively according to the sequence from small to large of the index value.
In some embodiments, calculating, by the automatic optimization model according to the sorted result, an optimal value of each condition index includes:
and removing data outside the standard deviation range of +/-3 times of the average value of each working condition index through the automatic optimization searching model, and taking the average value of 10% -15% of the data before the sorting as the optimal value of each working condition index.
In a second aspect, an embodiment of the present application provides an SCR denitration efficiency automatic optimization regulation and control system, which includes a data processing module, a model building module, a matching module, a sorting module, and an optimization module;
the data processing module is used for acquiring historical data and dividing the historical data based on working condition dividing points to obtain data of a plurality of working condition intervals;
the model building module is used for building an automatic optimization model for regulating and controlling the generation concentration of NOx based on the data of the working condition interval;
the matching module is used for matching to obtain a corresponding working condition interval according to the current value of the working condition index in the actual data in the actual operation;
the sequencing module is used for sequencing the data values of the working condition indexes in the working condition interval according to a preset sequence through the automatic optimization searching model;
and the optimizing module is used for calculating the optimal value of each working condition index through the automatic optimizing model according to the sorted data.
In some embodiments, the data processing module is further configured to obtain historical data; setting the division number, and averagely dividing the historical data according to the (upper limit value of the working condition division point-lower limit value of the working condition division point)/the division number to obtain data of a plurality of working condition intervals, wherein the working condition division point comprises main steam flow and unit load.
In some embodiments, the matching module is further configured to use a formula in an actual operation
Calculating Euclidean distance between the actual data and each working condition interval, and matching to obtain the working condition interval with the minimum Euclidean distance, wherein,x i as the operating condition index in actual dataiThe current value of (a) is,y i is an index of the working conditions in the working condition intervaliThe center value of (c).
In some embodiments, the ranking module is further configured to configure, through the automatic optimization model, an index value of an operating condition index in the operating condition interval; if the index value is larger and the data value corresponding to the working condition index is more optimal, sorting the data values of the working condition indexes respectively according to the sequence of the index values from large to small; and if the smaller the index value is, the better the data value corresponding to the working condition index is, sorting the data values of the working condition indexes respectively according to the sequence from small to large of the index value.
In some embodiments, the optimizing module is further configured to remove, through the automatic optimizing model, data outside a standard deviation range of ± 3 times of the average value of each operating condition index, and take the average value of the top 10% to 15% of the data in the sequence as the optimal value of each operating condition index.
Compared with the prior art, the SCR denitration efficiency automatic optimization regulation and control method and system provided by the embodiment of the application have the advantages that historical data are obtained, and are divided based on the working condition dividing points, so that data of a plurality of working condition intervals are obtained; based on the data of the working condition interval, constructing an automatic optimization model for regulating and controlling the generation concentration of NOx; in actual operation, matching according to the current value of the working condition index in the actual data to obtain a corresponding working condition interval; respectively sequencing the data values of all working condition indexes in the working condition interval according to a preset sequence through an automatic optimization model; according to the sequencing result, the optimal value of each working condition index is calculated through the automatic optimization searching model, the problem of how to consider the operation efficiency of the boiler and the operation cost of SCR denitration is solved, the optimal value of each working condition index in the boiler unit is calculated based on the optimization searching model, the generation concentration of NOx in the boiler is effectively regulated and controlled, and the operation efficiency of the boiler and the operation cost of SCR denitration are effectively considered.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a flow chart illustrating steps of a method for automatically optimizing and controlling SCR denitration efficiency according to an embodiment of the present disclosure;
FIG. 2 is a block diagram of an SCR denitration efficiency automatic optimization regulation system according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of an internal structure of an electronic device according to an embodiment of the present application.
Description of the drawings: 21. a data processing module; 22. a model building module; 23. a matching module; 24. a sorting module; 25. and an optimizing module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments provided in the present application without any inventive step are within the scope of protection of the present application.
It is obvious that the drawings in the following description are only examples or embodiments of the present application, and that it is also possible for a person skilled in the art to apply the present application to other similar contexts on the basis of these drawings without inventive effort. Moreover, it should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of ordinary skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.
Unless otherwise defined, technical or scientific terms referred to herein should have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar words throughout this application are not to be construed as limiting in number, and may refer to the singular or the plural. The present application is directed to the use of the terms "including," "comprising," "having," and any variations thereof, which are intended to cover non-exclusive inclusions; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to the listed steps or elements, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. Reference to "connected," "coupled," and the like in this application is not intended to be limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The term "plurality" as referred to herein means two or more. "and/or" describes an association relationship of associated objects, meaning that three relationships may exist, for example, "A and/or B" may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. Reference herein to the terms "first," "second," "third," and the like, are merely to distinguish similar objects and do not denote a particular ordering for the objects.
An embodiment of the present application provides an SCR denitration efficiency automatic optimization control method, and fig. 1 is a flowchart of steps of the SCR denitration efficiency automatic optimization control method according to the embodiment of the present application, and as shown in fig. 1, the method includes the following steps:
step S102, obtaining historical data, and dividing the historical data based on working condition dividing points to obtain data of a plurality of working condition intervals;
specifically, historical data is obtained, the number of divisions is set, and the historical data is divided averagely according to the (upper limit value of the working condition division point-lower limit value of the working condition division point)/the number of divisions to obtain data of a plurality of working condition intervals, wherein the working condition division point comprises main steam flow and unit load.
Preferably, the type of the working condition indexes (such as SCR ammonia gas supply flow, SCR ammonia supply pressure, SCR inlet flue gas flow, SOF wind ratio and the like) is a numerical type, the dividing number of the working condition indexes is a mandatory item, 1 is filled at the minimum, the upper limit and the lower limit can be empty when the working condition indexes are divided into 1 working condition interval, and the upper limit and the lower limit are required to be filled when the working condition indexes are divided into a plurality of working conditions; when the division is carried out on a plurality of working conditions, the working condition indexes are averagely divided according to the division number (the upper limit value-the lower limit value of the working condition division point). For example, if the operating condition division point is the unit load, and for a 300MW unit, the division number is 5, that is, (300 MW-0 MW)/5 =60mw, and the load module is set to 20% (corresponding to 60 MW), 0-20% (corresponding to 0-60 MW) is an operating condition interval, 20-40% (corresponding to 60-120 MW) is an operating condition interval, 40-60 (corresponding to 120-180 MW) is an operating condition interval, 60-80% (corresponding to 180-240 MW) is an operating condition interval, and 80-100% (corresponding to 240-300 MW) is an operating condition interval.
Step S104, constructing an automatic optimization model for regulating and controlling the generation concentration of NOx based on the data of the working condition interval;
specifically, based on data of a working condition interval, configuring an index for automatically optimizing SCR denitration efficiency as a denitration inlet NOx concentration value, and constructing an automatic optimization model for associating the working condition index in the working condition interval with the denitration inlet NOx concentration value, wherein the model is used for calculating an optimal value of the working condition index in the working condition interval so as to regulate and control the generation concentration of NOx in the boiler (namely the denitration inlet NOx concentration value).
Note that NOx is a generic term of nitrogen oxides, and generally includes NO, NO2, and the like. Besides nitrogen dioxide, other nitrogen oxides are extremely unstable, and change into nitrogen dioxide and nitric oxide when exposed to light, humidity and heat, the nitric oxide is changed into the nitrogen dioxide, such as nitrous oxide (N2O), nitric oxide (NO 2), nitrous oxide (N2O 3), dinitrogen tetroxide (N2O 4) and the like, in addition, one boiler unit device can correspond to multiple types of automatic optimization models, each type can create an in-use model and a standby model, the in-use model is not modifiable, and the standby model can be modified and started.
Step S106, in actual operation, according to the current value of the working condition index in the actual data, matching to obtain a corresponding working condition interval;
specifically, in actual operation, the formula is used
Calculating Euclidean distance between the actual data and each working condition interval, and matching to obtain the working condition interval with the minimum Euclidean distance, wherein,x i as an index of working conditions in actual dataiThe current value of (a) is,y i is an index of the working conditions in the working condition intervaliThe center value of (c).
Step S108, the data values of all the working condition indexes in the working condition interval are respectively sequenced according to a preset sequence through an automatic optimization model;
specifically, index values of working condition indexes in the working condition interval are configured through an automatic optimization model; if the index value is larger, the data value corresponding to the working condition index is more optimal (big optimal), and the data values of all the working condition indexes are respectively sequenced according to the sequence from big index value to small index value; and if the smaller the index value is, the better the data value corresponding to the working condition index is (smaller is better), sorting the data values of the working condition indexes respectively according to the sequence from smaller index values to larger index values.
And step S110, calculating the optimal value of each working condition index through an automatic optimizing model according to the sequencing result.
Specifically, data outside a standard deviation range of +/-3 times of the average value of each working condition index is removed through an automatic optimization model, and the average value of 10% -15% of the data at the top of the sequence is taken as the optimal value of each working condition index.
Further, step S106 to step S110 are executed in a loop according to a preset period, and the optimal value of the operating condition index obtained in each execution is stored in the database for subsequent big data analysis, wherein the preset period can be set according to requirements, for example, one minute, that is, step S106 to step S110 are executed once every minute, and the optimal value of the operating condition index is obtained once every minute.
Through the steps S102 to S110 in the embodiment of the application, the problem of how to consider both the boiler operation efficiency and the SCR denitration operation cost is solved, the optimal values of all working condition indexes in a boiler unit are calculated based on an optimization model, the generation concentration of NOx in the boiler is effectively regulated and controlled, and the boiler operation efficiency and the SCR denitration operation cost are effectively considered; the method is characterized in that the optimal point of the working condition index under different loads is calculated based on historical data and a big-optimal and small-optimal iteration mode, and is used as the optimal value of operation real-time adjustment, and then real-time analysis and optimization regulation and control are carried out according to the optimal value in the operation adjustment.
It should be noted that the steps illustrated in the above-described flow diagrams or in the flow diagrams of the figures may be performed in a computer system, such as a set of computer-executable instructions, and that, although a logical order is illustrated in the flow diagrams, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
An embodiment of the present application provides an SCR denitration efficiency automatic optimization regulation and control system, fig. 2 is a structural block diagram of the SCR denitration efficiency automatic optimization regulation and control system according to the embodiment of the present application, and as shown in fig. 2, the system includes a data processing module 21, a model construction module 22, a matching module 23, a sorting module 24, and an optimization module 25;
the data processing module 21 is configured to acquire historical data, and divide the historical data based on the working condition division points to obtain data of a plurality of working condition intervals;
the model building module 22 is used for building an automatic optimization model for regulating and controlling the generation concentration of NOx based on the data of the working condition interval;
the matching module 23 is used for matching to obtain a corresponding working condition interval according to the current value of the working condition index in the actual data in the actual operation;
the sorting module 24 is configured to sort the data values of the working condition indexes in the working condition interval according to a preset sequence through an automatic optimization model;
and the optimizing module 25 is configured to calculate an optimal value of each working condition index through an automatic optimizing model according to the sorted data.
In some embodiments, the data processing module 21 is further configured to obtain historical data; setting the division number, and averagely dividing the historical data according to the (upper limit value of the working condition division point-lower limit value of the working condition division point)/the division number to obtain data of a plurality of working condition intervals, wherein the working condition division point comprises main steam flow and unit load.
In some of these embodiments, the matching module 23 is also used for the actual operation through the formula
Calculating Euclidean distance between the actual data and each working condition interval, and matching to obtain the working condition interval with the minimum Euclidean distance, wherein,x i as an index of working conditions in actual dataiThe current value of (a) is,y i is the working condition in the working condition intervalIndex (I)iThe center value of (c).
In some embodiments, the sorting module 24 is further configured to configure an index value of the condition index in the condition interval through an automatic optimization model; if the index value is larger and the data value corresponding to the working condition index is more optimal, sorting the data values of the working condition indexes respectively according to the sequence of the index values from large to small; and if the smaller the index value is, the better the data value corresponding to the working condition index is, sorting the data values of the working condition indexes respectively according to the sequence from small to large of the index value.
In some embodiments, the optimizing module 25 is further configured to remove, through the automatic optimizing model, data outside a standard deviation range of ± 3 times of the average value of each operating condition index, and take the average value of the top 10% to 15% of the data in the sequence as the optimal value of each operating condition index.
The above modules may be functional modules or program modules, and may be implemented by software or hardware. For a module implemented by hardware, the modules may be located in the same processor; or the modules can be respectively positioned in different processors in any combination.
The present embodiment also provides an electronic device comprising a memory having a computer program stored therein and a processor configured to execute the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
It should be noted that, for specific examples in this embodiment, reference may be made to examples described in the foregoing embodiments and optional implementations, and details of this embodiment are not described herein again.
In addition, by combining the SCR denitration efficiency automatic optimization control method in the above embodiments, the embodiments of the present application can provide a storage medium to implement. The storage medium having stored thereon a computer program; when executed by a processor, the computer program implements any one of the above-described automatic optimization control methods for SCR denitration efficiency.
In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to realize an automatic optimization regulation and control method for SCR denitration efficiency. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
In one embodiment, fig. 3 is a schematic diagram of an internal structure of an electronic device according to an embodiment of the present application, and as shown in fig. 3, there is provided an electronic device, which may be a server, and its internal structure diagram may be as shown in fig. 3. The electronic device comprises a processor, a network interface, an internal memory and a non-volatile memory connected by an internal bus, wherein the non-volatile memory stores an operating system, a computer program and a database. The processor is used for providing calculation and control capability, the network interface is used for being connected and communicated with an external terminal through a network, the internal memory is used for providing an environment for an operating system and the running of a computer program, the computer program is executed by the processor to realize the SCR denitration efficiency automatic optimization regulation and control method, and the database is used for storing data.
Those skilled in the art will appreciate that the architecture shown in fig. 3 is a block diagram of only a portion of the architecture associated with the subject application, and does not constitute a limitation on the electronic devices to which the subject application may be applied, and that a particular electronic device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It should be understood by those skilled in the art that various features of the above-described embodiments can be combined in any combination, and for the sake of brevity, all possible combinations of features in the above-described embodiments are not described in detail, but rather, all combinations of features which are not inconsistent with each other should be construed as being within the scope of the present disclosure.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent application shall be subject to the appended claims.
Claims (10)
1. An automatic optimizing and regulating method for SCR denitration efficiency is characterized by comprising the following steps:
acquiring historical data, and dividing the historical data based on working condition division points to obtain data of a plurality of working condition intervals;
constructing an automatic optimizing model for regulating and controlling the generation concentration of NOx based on the data of the working condition interval;
in actual operation, matching according to the current value of the working condition index in the actual data to obtain a corresponding working condition interval;
respectively sequencing the data values of all working condition indexes in the working condition interval according to a preset sequence through the automatic optimization searching model;
and according to the sequencing result, calculating the optimal value of each working condition index through the automatic optimization searching model.
2. The method of claim 1, wherein obtaining historical data, and dividing the historical data based on operating condition division points to obtain data for a plurality of operating condition intervals comprises:
acquiring historical data;
setting the division number, and averagely dividing the historical data according to the (upper limit value of the working condition division point-lower limit value of the working condition division point)/the division number to obtain data of a plurality of working condition intervals, wherein the working condition division point comprises main steam flow and unit load.
3. The method of claim 1, wherein in actual operation, obtaining the corresponding operating condition interval by matching according to the current value of the operating condition index in the actual data comprises:
in actual operation, the formula is used
Calculating Euclidean distance between the actual data and each working condition interval, and matching to obtain the working condition interval with the minimum Euclidean distance, wherein,x i as an index of working conditions in actual dataiThe current value of (a) is,y i is the index of the working condition in the working condition intervaliThe center value of (c).
4. The method of claim 1, wherein the step of sorting the data values of the operating condition indexes in the operating condition interval according to a preset sequence by the automatic optimization model comprises the steps of:
configuring the index value of the working condition index in the working condition interval through the automatic optimization searching model;
if the index value is larger and the data value corresponding to the working condition index is more optimal, sorting the data values of the working condition indexes respectively according to the sequence of the index values from large to small;
and if the smaller the index value is, the better the data value corresponding to the working condition index is, sorting the data values of the working condition indexes respectively according to the sequence from small to large of the index value.
5. The method of claim 1, wherein calculating optimal values of the various condition indicators according to the sorted results through the automatic optimization model comprises:
and removing data outside the standard deviation range of +/-3 times of the average value of each working condition index through the automatic optimization searching model, and taking the average value of 10% -15% of the data before the sorting as the optimal value of each working condition index.
6. An automatic optimizing regulation and control system for SCR denitration efficiency is characterized by comprising a data processing module, a model building module, a matching module, a sequencing module and an optimizing module;
the data processing module is used for acquiring historical data and dividing the historical data based on working condition dividing points to obtain data of a plurality of working condition intervals;
the model building module is used for building an automatic optimization model for regulating and controlling the generation concentration of NOx based on the data of the working condition interval;
the matching module is used for matching to obtain a corresponding working condition interval according to the current value of the working condition index in the actual data in the actual operation;
the sequencing module is used for sequencing the data values of all the working condition indexes in the working condition interval according to a preset sequence through the automatic optimization searching model;
and the optimizing module is used for calculating the optimal value of each working condition index through the automatic optimizing model according to the sorted data.
7. The system of claim 6, wherein the data processing module is further configured to obtain historical data; setting the division number, and averagely dividing the historical data according to the (upper limit value of the working condition division point-lower limit value of the working condition division point)/the division number to obtain data of a plurality of working condition intervals, wherein the working condition division point comprises a main steam flow and a unit load.
8. The system of claim 6, wherein the matching module is further configured to formulate the matching in real-world operations
Calculating Euclidean distance between the actual data and each working condition interval, and matching to obtain the working condition interval with the minimum Euclidean distance, wherein,x i as an index of working conditions in actual dataiThe current value of (a) is,y i is an index of the working conditions in the working condition intervaliThe center value of (c).
9. The system of claim 6, wherein the ranking module is further configured to configure an index value of the condition index in the condition interval through the automatic optimization model; if the index value is larger and the data value corresponding to the working condition index is more optimal, sorting the data values of the working condition indexes respectively according to the sequence of the index values from large to small; and if the smaller the index value is, the better the data value corresponding to the working condition index is, sorting the data values of the working condition indexes respectively according to the sequence from small to large of the index value.
10. The system of claim 6, wherein the optimizing module is further configured to remove data outside a standard deviation range of ± 3 times of the average value of each condition index through the automatic optimizing model, and take the average value of the top 10% -15% of the data as the optimal value of each condition index.
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| CN202211240566.2A CN115309129A (en) | 2022-10-11 | 2022-10-11 | SCR denitration efficiency automatic optimization regulation and control method and system |
| JP2023562475A JP2024522428A (en) | 2022-10-11 | 2022-11-24 | Automatic optimization adjustment control method and system for SCR denitration efficiency |
| PCT/CN2022/133901 WO2023221446A1 (en) | 2022-10-11 | 2022-11-24 | Scr denitrification efficiency automatic optimization regulation and control method and system |
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| WO2023221446A1 (en) * | 2022-10-11 | 2023-11-23 | 华电电力科学研究院有限公司 | Scr denitrification efficiency automatic optimization regulation and control method and system |
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