DCS-based biomass boiler intelligent control method and system

Abstract

The invention relates to the technical field of biomass boilers, and discloses a DCS-based biomass boiler intelligent control method and system, and the method comprises the steps: collecting the real-time feature data of a biomass boiler, and determining an initial control strategy; obtaining operation influence factors of the real-time feature data, constructing an operation influence factor set, analyzing the operation influence factor set, and generating an associated operation influence factor set; calculating the associated operation influence factor set according to a first preset calculation mode and a second preset calculation mode, and determining a comprehensive associated influence value of the associated operation influence factor set; the initial control strategy is optimized and adjusted on the basis of the comprehensive correlation influence value, a target control strategy is obtained, the biomass boiler is intelligently controlled according to the target control strategy, intelligent control over the biomass boiler can be achieved, meanwhile, the control strategy is adjusted according to the actual situation, the operation efficiency and the environmental protection performance of the biomass boiler are improved, and the energy consumption is reduced. And the requirement for manual intervention is lowered, and the reducing agent needed by SCR is accurately provided.

Description

Technical Field

[0001] The present invention relates to the technical field of biomass boilers, and in particular to a DCS-based intelligent control method and system for biomass boilers. Background Art

[0002] Biomass boiler is a kind of boiler that uses biomass energy as fuel. It is widely used in industrial and civil heating, steam supply and other fields. Its main features include energy saving, environmental protection and high thermal energy conversion rate. Biomass boilers can be subdivided into many types according to their functions and designs, including vertical and horizontal boilers. As an efficient and environmentally friendly energy conversion equipment, biomass boilers are gradually being widely promoted and used. Its advantages in energy saving, emission reduction and resource recycling make it an important part of future energy solutions.

[0003] Biomass boilers currently use in-furnace SNCR+SCR denitrification technology. It is now necessary to transform the original SNCR system and add a set of supporting systems such as a urea hydrolysis system and an ammonia injection system to provide the reducing agent required by SCR. The DCS system can realize centralized management and decentralized control of the production process, with high flexibility and reliability. However, in terms of traditional intelligent control of biomass boilers, the application of DCS still has certain limitations. For example, existing DCS systems often lack in-depth understanding and adaptability, and cannot automatically adjust control strategies according to changes in actual conditions. Summary of the invention

[0004] The embodiment of the present invention provides a DCS-based intelligent control method and system for a biomass boiler, which is used to solve the technical problem in the prior art that the biomass boiler cannot be intelligently controlled and the control strategy cannot be adjusted according to actual conditions.

[0005] In order to achieve the above object, the present invention provides a DCS-based biomass boiler intelligent control method, comprising:

[0006] Based on a preset collection device, real-time characteristic data of the biomass boiler is collected, and an initial control strategy is determined according to the real-time characteristic data, wherein the real-time characteristic data includes the concentration of the urea solution, the flow rate of the ammonia gas, and the temperature of the hydrolysis reactor;

[0007] Obtaining the operation influencing factors of each real-time feature data, constructing a corresponding operation influencing factor set according to all the operation influencing factors, analyzing each operation influencing factor set, and generating a related operation influencing factor set based on the analysis results;

[0008] Calculating the associated operation influencing factor set according to a first preset calculation method and a second preset calculation method, and determining a comprehensive associated impact value of the associated operation influencing factor set based on the calculation result;

[0009] The initial control strategy is optimized and adjusted based on the comprehensive correlation influence value to obtain a target control strategy, and the biomass boiler is intelligently controlled according to the target control strategy.

[0010] Further, when obtaining the operation influencing factors of each real-time feature data, building a corresponding operation influencing factor set according to all the operation influencing factors, analyzing each operation influencing factor set, and generating a related operation influencing factor set based on the analysis result, it includes:

[0011] A urea operation influencing factor set is constructed according to the concentration of the urea solution, an ammonia operation influencing factor set is constructed according to the flow rate of the ammonia, and a temperature operation influencing factor set is constructed according to the temperature of the hydrolysis reactor;

[0012] Determine the impact evaluation value of the operation influencing factor in each operation influencing factor set;

[0013] The impact evaluation values ​​in each operation influencing factor set are sorted by numerical value to obtain a new urea operation influencing factor set, a new ammonia operation influencing factor set and a new temperature operation influencing factor set;

[0014] Binding each two adjacent impact evaluation values ​​in the new urea operation influencing factor set in pairs, and calculating the impact evaluation difference between each two bound impact evaluation values;

[0015] Obtaining a preset impact evaluation difference value, extracting all two bound impact evaluation values ​​that are greater than or equal to the preset impact evaluation difference value, deleting the latter impact evaluation value of the two bound impact evaluation values, and retaining the former impact evaluation value;

[0016] Constructing a urea operation influencing factor set according to all retained impact evaluation values ​​and all two bound impact evaluation values ​​that are less than the difference of the preset impact evaluation value;

[0017] Binding each two adjacent impact evaluation values ​​in the new ammonia operation influencing factor set in pairs, and constructing an ammonia operation influencing factor set;

[0018] Every two adjacent impact evaluation values ​​in the new temperature operation influencing factor set are bound in pairs, and a temperature operation influencing factor set is constructed.

[0019] Furthermore, when analyzing each set of operation influencing factors and generating a set of associated operation influencing factors based on the analysis results, it includes:

[0020] Extracting a first minimum impact evaluation value from the urea operation influencing factor set, extracting a second maximum impact evaluation value and a third minimum impact evaluation value from the ammonia operation influencing factor set, and extracting a fourth maximum impact evaluation value from the temperature operation influencing factor set;

[0021] Calculating a first correlation factor between the urea operation influencing factor set and the ammonia operation influencing factor set, wherein the first correlation factor is an absolute value of a difference between the first minimum impact evaluation value and the second maximum impact evaluation value;

[0022] Calculating a second correlation factor between the ammonia operation influencing factor set and the temperature operation influencing factor set, wherein the second correlation factor is an absolute value of a difference between the third minimum impact evaluation value and the fourth maximum impact evaluation value;

[0023] Calculate the set association degree according to the first association factor and the second association factor:

[0024]

[0025] Wherein, P is the set association degree, Lmax is the maximum impact evaluation value in the urea operation influencing factor set, n1 is the number of impact evaluation values ​​in the urea operation influencing factor set, Lx is the x-th impact evaluation value in the urea operation influencing factor set, Hx is the weight corresponding to the x-th impact evaluation value, Qmax is the maximum impact evaluation value in the ammonia operation influencing factor set, n2 is the number of impact evaluation values ​​in the ammonia operation influencing factor set, Qy is the y-th impact evaluation value in the ammonia operation influencing factor set, Vy is the weight corresponding to the y-th impact evaluation value, Wmax is the maximum impact evaluation value in the temperature operation influencing factor set, n3 is the number of impact evaluation values ​​in the temperature operation influencing factor set, Wi is the y-th impact evaluation value in the temperature operation influencing factor set, Ki is the weight corresponding to the ith impact evaluation value, e1 is the first association factor, and e2 is the second association factor;

[0026] Acquire a preset set association degree, and when the set association degree is greater than or equal to the preset set association degree, generate a set of associated operation influencing factors according to all the influencing evaluation values;

[0027] When the set association degree is less than the preset set association degree, a set of associated operation influencing factors is generated according to all deleted influence evaluation values.

[0028] Further, when the associated operation influencing factor set is calculated according to the first preset calculation method and the second preset calculation method, and the comprehensive associated impact value of the associated operation influencing factor set is determined based on the calculation result, it includes:

[0029] Calculating a first calculated value of the associated operation influencing factor set based on the first preset calculation method, and calculating a second calculated value of the associated operation influencing factor set based on a second preset calculation method;

[0030] Extracting all impact evaluation values ​​in the associated operation impact factor set that are greater than the first calculated value and greater than the second calculated value, and generating an overvalue mark;

[0031] Extracting all impact evaluation values ​​in the associated operation impact factor set that are equal to the first calculated value and the second calculated value, and generating equal value marks;

[0032] Extracting all impact evaluation values ​​in the associated operation impact factor set that are smaller than the first calculated value and smaller than the second calculated value, and generating an undervalue mark;

[0033] Count the number of overvalue marks for overvalue marks, count the number of equal-value marks for equal-value marks, and count the number of undervalue marks for undervalue marks;

[0034] The comprehensive associated impact value of the associated operation impact factor set is calculated according to the number of overvalue marks, the number of equalvalue marks and the number of undervalue marks.

[0035] Further, when calculating the comprehensive correlation impact value of the set of correlation operation impact factors according to the number of excess value marks, the number of equal value marks, and the number of under value marks, it includes:

[0036] The comprehensive correlation impact value of the set of correlation operation impact factors is calculated according to the following formula:

[0037]

[0038] Among them, B is the comprehensive correlation impact value of the set of correlation operation influencing factors, M1 is the number of undervalue marks, M2 is the number of overvalue marks, and M3 is the number of equal value marks.

[0039] In order to achieve the above object, the present invention also provides a biomass boiler intelligent control system based on DCS, which is characterized by comprising:

[0040] The first module is used to collect real-time characteristic data of the biomass boiler based on a preset collection device, and determine an initial control strategy according to the real-time characteristic data, wherein the real-time characteristic data includes the concentration of the urea solution, the flow rate of the ammonia gas and the temperature of the hydrolysis reactor;

[0041] The second module is used to obtain the operation influencing factors of each real-time feature data, construct a corresponding operation influencing factor set according to all the operation influencing factors, analyze each operation influencing factor set, and generate a related operation influencing factor set based on the analysis result;

[0042] A third module is used to calculate the associated operation influencing factor set according to the first preset calculation method and the second preset calculation method, and determine the comprehensive associated impact value of the associated operation influencing factor set based on the calculation result;

[0043] The fourth module is used to optimize and adjust the initial control strategy based on the comprehensive correlation influence value to obtain a target control strategy, and intelligently control the biomass boiler according to the target control strategy.

[0044] Furthermore, the second module is used for:

[0045] The second module is used to construct a urea operation influencing factor set according to the concentration of the urea solution, to construct an ammonia operation influencing factor set according to the flow rate of the ammonia gas, and to construct a temperature operation influencing factor set according to the temperature of the hydrolysis reactor;

[0046] The second module is used to determine the impact evaluation value of the operation influencing factor in each operation influencing factor set;

[0047] The second module is used to sort the impact evaluation values ​​in each operation influencing factor set by numerical value to obtain a new urea operation influencing factor set, a new ammonia operation influencing factor set and a new temperature operation influencing factor set;

[0048] The second module is used to bind every two adjacent impact evaluation values ​​in the new urea operation influencing factor set in pairs, and calculate the impact evaluation difference between every two bound impact evaluation values;

[0049] The second module is used to obtain a preset impact evaluation difference, extract all two bound impact evaluation values ​​that are greater than or equal to the preset impact evaluation difference, delete the latter impact evaluation value of the two bound impact evaluation values, and retain the former impact evaluation value;

[0050] The second module is used to construct a set of urea operation influencing factors according to all retained impact evaluation values ​​and all two bound impact evaluation values ​​that are less than the difference of the preset impact evaluation value;

[0051] The second module is used to bind every two adjacent impact evaluation values ​​in the new ammonia operation influencing factor set in pairs, and construct the ammonia operation influencing factor set;

[0052] The second module is used to bind every two adjacent impact evaluation values ​​in the new temperature operation influencing factor set in pairs, and construct the temperature operation influencing factor set.

[0053] Furthermore, the second module is used for:

[0054] The second module is used to extract the first minimum impact evaluation value in the urea operation influencing factor set, extract the second maximum impact evaluation value and the third minimum impact evaluation value in the ammonia operation influencing factor set, and extract the fourth maximum impact evaluation value in the temperature operation influencing factor set;

[0055] The second module is used to calculate a first correlation factor between the urea operation influencing factor set and the ammonia operation influencing factor set, wherein the first correlation factor is an absolute value of a difference between the first minimum impact evaluation value and the second maximum impact evaluation value;

[0056] The second module is used to calculate a second correlation factor between the ammonia operation influencing factor set and the temperature operation influencing factor set, wherein the second correlation factor is an absolute value of a difference between the third minimum impact evaluation value and the fourth maximum impact evaluation value;

[0057] The second module is used to calculate the set association degree according to the first association factor and the second association factor:

[0058]

[0059] Wherein, P is the set association degree, Lmax is the maximum impact evaluation value in the urea operation influencing factor set, n1 is the number of impact evaluation values ​​in the urea operation influencing factor set, Lx is the x-th impact evaluation value in the urea operation influencing factor set, Hx is the weight corresponding to the x-th impact evaluation value, Qmax is the maximum impact evaluation value in the ammonia operation influencing factor set, n2 is the number of impact evaluation values ​​in the ammonia operation influencing factor set, Qy is the y-th impact evaluation value in the ammonia operation influencing factor set, Vy is the weight corresponding to the y-th impact evaluation value, Wmax is the maximum impact evaluation value in the temperature operation influencing factor set, n3 is the number of impact evaluation values ​​in the temperature operation influencing factor set, Wi is the y-th impact evaluation value in the temperature operation influencing factor set, Ki is the weight corresponding to the ith impact evaluation value, e1 is the first association factor, and e2 is the second association factor;

[0060] The second module is used to obtain a preset set association degree, and when the set association degree is greater than or equal to the preset set association degree, a set of associated operation influencing factors is generated according to all the influencing evaluation values;

[0061] The second module is used to generate a set of associated operation influencing factors according to all deleted impact evaluation values ​​when the set correlation degree is less than the preset set correlation degree.

[0062] Furthermore, the third module is used for:

[0063] The third module is used to calculate a first calculated value of the associated operation influencing factor set based on the first preset calculation method, and calculate a second calculated value of the associated operation influencing factor set according to a second preset calculation method;

[0064] The third module is used to extract all the impact evaluation values ​​in the associated operation impact factor set that are greater than the first calculated value and greater than the second calculated value, and generate an over-value mark;

[0065] The third module is used to extract all the impact evaluation values ​​in the associated operation impact factor set that are equal to the first calculated value and the second calculated value, and generate equal value marks;

[0066] The third module is used to extract all the impact evaluation values ​​in the associated operation impact factor set that are smaller than the first calculated value and smaller than the second calculated value, and generate an undervalue mark;

[0067] The third module is used to count the number of overvalue marks of overvalue marks, count the number of equal-value marks of equal-value marks, and count the number of undervalue marks of undervalue marks;

[0068] The third module is used to calculate the comprehensive correlation impact value of the set of correlation operation impact factors according to the number of overvalue marks, the number of equalvalue marks and the number of undervalue marks.

[0069] Furthermore, the third module is used for:

[0070] The third module is used to calculate the comprehensive correlation impact value of the set of correlation operation impact factors according to the following formula:

[0071]

[0072] Among them, B is the comprehensive correlation impact value of the set of correlation operation influencing factors, M1 is the number of undervalue marks, M2 is the number of overvalue marks, and M3 is the number of equal value marks.

[0073] Compared with the prior art, the present invention has the following beneficial effects:

[0074] The present invention discloses a biomass boiler intelligent control method and system based on DCS, which collects real-time characteristic data of the biomass boiler to determine the initial control strategy; obtains the operation influencing factors of the real-time characteristic data, constructs an operation influencing factor set, analyzes the operation influencing factor set, and generates a related operation influencing factor set; calculates the related operation influencing factor set according to a first preset calculation method and a second preset calculation method, and determines the comprehensive related influence value of the related operation influencing factor set; optimizes and adjusts the initial control strategy based on the comprehensive related influence value to obtain a target control strategy, and intelligently controls the biomass boiler according to the target control strategy. The biomass boiler can be intelligently controlled, and the control strategy can be adjusted according to actual conditions, thereby improving the operation efficiency and environmental protection performance of the biomass boiler, reducing the need for manual intervention, and accurately providing the reducing agent required by the SCR. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0076] Figure 1 A schematic diagram of a flow chart of a biomass boiler intelligent control method based on DCS in an embodiment of the present invention is shown;

[0077] Figure 2 The schematic diagram of the structure of the biomass boiler intelligent control system based on DCS in the embodiment of the present invention is shown. DETAILED DESCRIPTION

[0078] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0079] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0080] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0081] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0082] The following is a description of preferred embodiments of the present invention with reference to the accompanying drawings.

[0083] like Figure 1 As shown, the embodiment of the present invention discloses a DCS-based intelligent control method for a biomass boiler, comprising:

[0084] S110: collecting real-time characteristic data of the biomass boiler based on a preset collection device, and determining an initial control strategy according to the real-time characteristic data, wherein the real-time characteristic data includes the concentration of the urea solution, the flow rate of the ammonia gas, and the temperature of the hydrolysis reactor;

[0085] In this embodiment, the data collection equipment includes a urea concentration sensor, a turbine flowmeter and a thermocouple, which respectively collect the concentration of the urea solution, the flow rate of the ammonia gas and the temperature of the hydrolysis reactor.

[0086] In this embodiment, the initial control strategy includes setting the flow rate of the urea pump according to the concentration of the urea solution, setting the opening of the ammonia injection valve according to the flow rate of the ammonia, and setting the temperature of the regulating reactor according to the temperature of the hydrolysis reactor.

[0087] S120: Acquire the operation influencing factor of each real-time feature data, construct a corresponding operation influencing factor set according to all the operation influencing factors, analyze each operation influencing factor set, and generate a related operation influencing factor set based on the analysis result;

[0088] In this embodiment, the operational influencing factors of the concentration of the urea solution include metering accuracy control, design and manufacturing technology, driving technology, urea spray characteristics, and urea crystallization control.

[0089] In this embodiment, the operating influencing factors of the opening of the ammonia injection valve include theoretical ammonia injection amount, load change, inlet nitrogen oxide concentration, etc.

[0090] In this embodiment, the operational influencing factors for adjusting the temperature of the reactor include the properties of the raw materials, the operating conditions of the reactor, thermal stability, and heat transfer efficiency.

[0091] In this embodiment, the common operating influencing factors of the above three include catalyst activity, optimized operating parameters, and thermal stability of the system.

[0092] In some embodiments of the present application, when obtaining the operation influencing factor of each real-time feature data, constructing a corresponding operation influencing factor set according to all the operation influencing factors, analyzing each operation influencing factor set, and generating a related operation influencing factor set based on the analysis result, it includes:

[0093] A urea operation influencing factor set is constructed according to the concentration of the urea solution, an ammonia operation influencing factor set is constructed according to the flow rate of the ammonia, and a temperature operation influencing factor set is constructed according to the temperature of the hydrolysis reactor;

[0094] Determine the impact evaluation value of the operation influencing factor in each operation influencing factor set;

[0095] The impact evaluation values ​​in each operation influencing factor set are sorted by numerical value to obtain a new urea operation influencing factor set, a new ammonia operation influencing factor set and a new temperature operation influencing factor set;

[0096] Binding each two adjacent impact evaluation values ​​in the new urea operation influencing factor set in pairs, and calculating the impact evaluation difference between each two bound impact evaluation values;

[0097] Obtaining a preset impact evaluation difference value, extracting all two bound impact evaluation values ​​that are greater than or equal to the preset impact evaluation difference value, deleting the latter impact evaluation value of the two bound impact evaluation values, and retaining the former impact evaluation value;

[0098] Constructing a urea operation influencing factor set according to all retained impact evaluation values ​​and all two bound impact evaluation values ​​that are less than the difference of the preset impact evaluation value;

[0099] Binding each two adjacent impact evaluation values ​​in the new ammonia operation influencing factor set in pairs, and constructing an ammonia operation influencing factor set;

[0100] Every two adjacent impact evaluation values ​​in the new temperature operation influencing factor set are bound in pairs, and a temperature operation influencing factor set is constructed.

[0101] In this embodiment, a corresponding operation influencing factor set is constructed according to the above-mentioned operation influencing factors.

[0102] In this embodiment, the impact evaluation value refers to the effect of the operation influencing factor on the flow rate of the corresponding urea pump, the opening of the ammonia injection valve, and the temperature of the regulating reactor.

[0103] The beneficial effect of the above technical solution is that the present invention can lay a foundation for the optimization and adjustment of the initial control strategy and provide a basis for optimization and adjustment by constructing a set of urea operation influencing factors, ammonia operation influencing factors and temperature operation influencing factors.

[0104] In some embodiments of the present application, when analyzing each set of operation influencing factors and generating a set of associated operation influencing factors based on the analysis results, the following steps are included:

[0105] Extracting a first minimum impact evaluation value from the urea operation influencing factor set, extracting a second maximum impact evaluation value and a third minimum impact evaluation value from the ammonia operation influencing factor set, and extracting a fourth maximum impact evaluation value from the temperature operation influencing factor set;

[0106] Calculating a first correlation factor between the urea operation influencing factor set and the ammonia operation influencing factor set, wherein the first correlation factor is an absolute value of a difference between the first minimum impact evaluation value and the second maximum impact evaluation value;

[0107] Calculating a second correlation factor between the ammonia operation influencing factor set and the temperature operation influencing factor set, wherein the second correlation factor is an absolute value of a difference between the third minimum impact evaluation value and the fourth maximum impact evaluation value;

[0108] Calculate the set association degree according to the first association factor and the second association factor:

[0109]

[0110] Wherein, P is the set association degree, Lmax is the maximum impact evaluation value in the urea operation influencing factor set, n1 is the number of impact evaluation values ​​in the urea operation influencing factor set, Lx is the x-th impact evaluation value in the urea operation influencing factor set, Hx is the weight corresponding to the x-th impact evaluation value, Qmax is the maximum impact evaluation value in the ammonia operation influencing factor set, n2 is the number of impact evaluation values ​​in the ammonia operation influencing factor set, Qy is the y-th impact evaluation value in the ammonia operation influencing factor set, Vy is the weight corresponding to the y-th impact evaluation value, Wmax is the maximum impact evaluation value in the temperature operation influencing factor set, n3 is the number of impact evaluation values ​​in the temperature operation influencing factor set, Wi is the y-th impact evaluation value in the temperature operation influencing factor set, Ki is the weight corresponding to the ith impact evaluation value, e1 is the first association factor, and e2 is the second association factor;

[0111] Acquire a preset set association degree, and when the set association degree is greater than or equal to the preset set association degree, generate a set of associated operation influencing factors according to all the influencing evaluation values;

[0112] When the set association degree is less than the preset set association degree, a set of associated operation influencing factors is generated according to all deleted influence evaluation values.

[0113] In this embodiment, all deleted impact evaluation values ​​refer to the impact evaluation value after deleting the two bound impact evaluation values.

[0114] The beneficial effect of the above technical solution is: the present invention calculates the first correlation factor and the second correlation factor, and then calculates the set correlation degree according to the first correlation factor and the second correlation factor. By calculating the set correlation degree, the three sets of urea operation influencing factor set, ammonia operation influencing factor set and temperature operation influencing factor set can be operated and managed simultaneously.

[0115] S130: Calculate the set of associated operation influencing factors according to a first preset calculation method and a second preset calculation method, and determine a comprehensive associated influence value of the set of associated operation influencing factors based on the calculation result;

[0116] In some embodiments of the present application, when calculating the associated operation influencing factor set according to the first preset calculation method and the second preset calculation method, and determining the comprehensive associated impact value of the associated operation influencing factor set based on the calculation result, it includes:

[0117] Calculating a first calculated value of the associated operation influencing factor set based on the first preset calculation method, and calculating a second calculated value of the associated operation influencing factor set based on a second preset calculation method;

[0118] Extracting all impact evaluation values ​​in the associated operation impact factor set that are greater than the first calculated value and greater than the second calculated value, and generating an overvalue mark;

[0119] Extracting all impact evaluation values ​​in the associated operation impact factor set that are equal to the first calculated value and the second calculated value, and generating equal value marks;

[0120] Extracting all impact evaluation values ​​in the associated operation impact factor set that are smaller than the first calculated value and smaller than the second calculated value, and generating an undervalue mark;

[0121] Count the number of overvalue marks for overvalue marks, count the number of equal-value marks for equal-value marks, and count the number of undervalue marks for undervalue marks;

[0122] The comprehensive associated impact value of the associated operation impact factor set is calculated according to the number of overvalue marks, the number of equalvalue marks and the number of undervalue marks.

[0123] In this embodiment, the first preset calculation method is to calculate the average value of the set of associated operation influencing factors, that is, refers to the first calculated value.

[0124] In this embodiment, the second preset calculation method is to calculate the standard deviation of the set of associated operation influencing factors, which refers to the second calculated value.

[0125] The beneficial effects of the above technical solution are: the present invention counts the number of over-value marks of over-value marks, counts the number of equal-value marks of equal-value marks, and counts the number of under-value marks of under-value marks; calculates the comprehensive associated influence value of the set of associated operation influencing factors according to the number of over-value marks, the number of equal-value marks and the number of under-value marks, thereby realizing accurate calculation of the comprehensive associated influence value, avoiding manual intervention in calculation, reducing calculation errors, and eliminating subjectivity.

[0126] In some embodiments of the present application, when calculating the comprehensive association impact value of the association operation impact factor set according to the number of excess value marks, the number of equal value marks, and the number of undervalue marks, it includes:

[0127] The comprehensive correlation impact value of the set of correlation operation impact factors is calculated according to the following formula:

[0128]

[0129] Among them, B is the comprehensive correlation impact value of the set of correlation operation influencing factors, M1 is the number of undervalue marks, M2 is the number of overvalue marks, and M3 is the number of equal value marks.

[0130] S140: Optimizing and adjusting the initial control strategy based on the comprehensive correlation influence value to obtain a target control strategy, and intelligently controlling the biomass boiler according to the target control strategy.

[0131] The beneficial effect of the above technical solution is that the present invention realizes centralized management and decentralized control of the production process, and has high flexibility and reliability.

[0132] In order to further explain the technical idea of ​​the present invention, the technical solution of the present invention is now described in combination with specific application scenarios.

[0133] Correspondingly, such as Figure 2 As shown, the present application also provides a biomass boiler intelligent control system based on DCS, including:

[0134] The first module is used to collect real-time characteristic data of the biomass boiler based on a preset collection device, and determine an initial control strategy according to the real-time characteristic data, wherein the real-time characteristic data includes the concentration of the urea solution, the flow rate of the ammonia gas and the temperature of the hydrolysis reactor;

[0135] The second module is used to obtain the operation influencing factors of each real-time feature data, construct a corresponding operation influencing factor set according to all the operation influencing factors, analyze each operation influencing factor set, and generate a related operation influencing factor set based on the analysis result;

[0136] A third module is used to calculate the associated operation influencing factor set according to the first preset calculation method and the second preset calculation method, and determine the comprehensive associated impact value of the associated operation influencing factor set based on the calculation result;

[0137] The fourth module is used to optimize and adjust the initial control strategy based on the comprehensive correlation influence value to obtain a target control strategy, and intelligently control the biomass boiler according to the target control strategy.

[0138] In some embodiments of the present application, the second module is used to:

[0139] The second module is used to construct a urea operation influencing factor set according to the concentration of the urea solution, to construct an ammonia operation influencing factor set according to the flow rate of the ammonia gas, and to construct a temperature operation influencing factor set according to the temperature of the hydrolysis reactor;

[0140] The second module is used to determine the impact evaluation value of the operation influencing factor in each operation influencing factor set;

[0141] The second module is used to sort the impact evaluation values ​​in each operation influencing factor set by numerical value to obtain a new urea operation influencing factor set, a new ammonia operation influencing factor set and a new temperature operation influencing factor set;

[0142] The second module is used to bind every two adjacent impact evaluation values ​​in the new urea operation influencing factor set in pairs, and calculate the impact evaluation difference between every two bound impact evaluation values;

[0143] The second module is used to obtain a preset impact evaluation difference, extract all two bound impact evaluation values ​​that are greater than or equal to the preset impact evaluation difference, delete the latter impact evaluation value of the two bound impact evaluation values, and retain the former impact evaluation value;

[0144] The second module is used to construct a set of urea operation influencing factors according to all retained impact evaluation values ​​and all two bound impact evaluation values ​​that are less than the difference of the preset impact evaluation value;

[0145] The second module is used to bind every two adjacent impact evaluation values ​​in the new ammonia operation influencing factor set in pairs, and construct the ammonia operation influencing factor set;

[0146] The second module is used to bind every two adjacent impact evaluation values ​​in the new temperature operation influencing factor set in pairs, and construct the temperature operation influencing factor set.

[0147] In some embodiments of the present application, the second module is used to:

[0148] The second module is used to extract the first minimum impact evaluation value in the urea operation influencing factor set, extract the second maximum impact evaluation value and the third minimum impact evaluation value in the ammonia operation influencing factor set, and extract the fourth maximum impact evaluation value in the temperature operation influencing factor set;

[0149] The second module is used to calculate a first correlation factor between the urea operation influencing factor set and the ammonia operation influencing factor set, wherein the first correlation factor is an absolute value of a difference between the first minimum impact evaluation value and the second maximum impact evaluation value;

[0150] The second module is used to calculate a second correlation factor between the ammonia operation influencing factor set and the temperature operation influencing factor set, wherein the second correlation factor is an absolute value of a difference between the third minimum impact evaluation value and the fourth maximum impact evaluation value;

[0151] The second module is used to calculate the set association degree according to the first association factor and the second association factor:

[0152]

[0153] Wherein, P is the set association degree, Lmax is the maximum impact evaluation value in the urea operation influencing factor set, n1 is the number of impact evaluation values ​​in the urea operation influencing factor set, Lx is the x-th impact evaluation value in the urea operation influencing factor set, Hx is the weight corresponding to the x-th impact evaluation value, Qmax is the maximum impact evaluation value in the ammonia operation influencing factor set, n2 is the number of impact evaluation values ​​in the ammonia operation influencing factor set, Qy is the y-th impact evaluation value in the ammonia operation influencing factor set, Vy is the weight corresponding to the y-th impact evaluation value, Wmax is the maximum impact evaluation value in the temperature operation influencing factor set, n3 is the number of impact evaluation values ​​in the temperature operation influencing factor set, Wi is the y-th impact evaluation value in the temperature operation influencing factor set, Ki is the weight corresponding to the ith impact evaluation value, e1 is the first association factor, and e2 is the second association factor;

[0154] The second module is used to obtain a preset set association degree, and when the set association degree is greater than or equal to the preset set association degree, a set of associated operation influencing factors is generated according to all the influencing evaluation values;

[0155] The second module is used to generate a set of associated operation influencing factors according to all deleted impact evaluation values ​​when the set correlation degree is less than the preset set correlation degree.

[0156] In some embodiments of the present application, the third module is used to:

[0157] The third module is used to calculate a first calculated value of the associated operation influencing factor set based on the first preset calculation method, and calculate a second calculated value of the associated operation influencing factor set according to a second preset calculation method;

[0158] The third module is used to extract all the impact evaluation values ​​in the associated operation impact factor set that are greater than the first calculated value and greater than the second calculated value, and generate an over-value mark;

[0159] The third module is used to extract all the impact evaluation values ​​in the associated operation impact factor set that are equal to the first calculated value and the second calculated value, and generate equal value marks;

[0160] The third module is used to extract all the impact evaluation values ​​in the associated operation impact factor set that are smaller than the first calculated value and smaller than the second calculated value, and generate an undervalue mark;

[0161] The third module is used to count the number of overvalue marks of overvalue marks, count the number of equal-value marks of equal-value marks, and count the number of undervalue marks of undervalue marks;

[0162] The third module is used to calculate the comprehensive correlation impact value of the set of correlation operation impact factors according to the number of overvalue marks, the number of equalvalue marks and the number of undervalue marks.

[0163] In some embodiments of the present application, the third module is used to:

[0164] The third module is used to calculate the comprehensive correlation impact value of the set of correlation operation impact factors according to the following formula:

[0165]

[0166] Among them, B is the comprehensive correlation impact value of the set of correlation operation influencing factors, M1 is the number of undervalue marks, M2 is the number of overvalue marks, and M3 is the number of equal value marks.

[0167] In the description of the above embodiments, specific features, structures, materials or characteristics may be combined in a suitable manner in any one or more embodiments or examples.

[0168] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced with equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed by the present invention may be used in combination with each other in any manner, and the fact that these combinations are not fully described in this specification is only for the sake of omitting space and saving resources.

[0169] Those skilled in the art can understand that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A DCS-based biomass boiler intelligent control method, characterized in that: include: Based on a preset collection device, real-time characteristic data of the biomass boiler is collected, and an initial control strategy is determined according to the real-time characteristic data, wherein the real-time characteristic data includes the concentration of the urea solution, the flow rate of the ammonia gas, and the temperature of the hydrolysis reactor; Obtaining the operation influencing factors of each real-time feature data, constructing a corresponding operation influencing factor set according to all the operation influencing factors, analyzing each operation influencing factor set, and generating a related operation influencing factor set based on the analysis results; Calculating the associated operation influencing factor set according to a first preset calculation method and a second preset calculation method, and determining a comprehensive associated impact value of the associated operation influencing factor set based on the calculation result; The initial control strategy is optimized and adjusted based on the comprehensive correlation influence value to obtain a target control strategy, and the biomass boiler is intelligently controlled according to the target control strategy.

2. The DCS-based intelligent control method for biomass boiler according to claim 1 is characterized in that: When obtaining the operation influencing factors of each real-time feature data, building a corresponding operation influencing factor set according to all the operation influencing factors, analyzing each operation influencing factor set, and generating a related operation influencing factor set based on the analysis result, it includes: A urea operation influencing factor set is constructed according to the concentration of the urea solution, an ammonia operation influencing factor set is constructed according to the flow rate of the ammonia, and a temperature operation influencing factor set is constructed according to the temperature of the hydrolysis reactor; Determine the impact evaluation value of the operation influencing factor in each operation influencing factor set; The impact evaluation values ​​in each operation influencing factor set are sorted by numerical value to obtain a new urea operation influencing factor set, a new ammonia operation influencing factor set and a new temperature operation influencing factor set; Binding each two adjacent impact evaluation values ​​in the new urea operation influencing factor set in pairs, and calculating the impact evaluation difference between each two bound impact evaluation values; Obtaining a preset impact evaluation difference value, extracting all two bound impact evaluation values ​​that are greater than or equal to the preset impact evaluation difference value, deleting the latter impact evaluation value of the two bound impact evaluation values, and retaining the former impact evaluation value; Constructing a urea operation influencing factor set according to all retained impact evaluation values ​​and all two bound impact evaluation values ​​that are less than the difference of the preset impact evaluation value; Binding each two adjacent impact evaluation values ​​in the new ammonia operation influencing factor set in pairs, and constructing an ammonia operation influencing factor set; Every two adjacent impact evaluation values ​​in the new temperature operation influencing factor set are bound in pairs, and a temperature operation influencing factor set is constructed.

3. The DCS-based intelligent control method for biomass boiler according to claim 2 is characterized in that: When analyzing each set of operation influencing factors and generating a set of associated operation influencing factors based on the analysis results, it includes: Extracting a first minimum impact evaluation value from the urea operation influencing factor set, extracting a second maximum impact evaluation value and a third minimum impact evaluation value from the ammonia operation influencing factor set, and extracting a fourth maximum impact evaluation value from the temperature operation influencing factor set; Calculating a first correlation factor between the urea operation influencing factor set and the ammonia operation influencing factor set, wherein the first correlation factor is an absolute value of a difference between the first minimum impact evaluation value and the second maximum impact evaluation value; Calculating a second correlation factor between the ammonia operation influencing factor set and the temperature operation influencing factor set, wherein the second correlation factor is an absolute value of a difference between the third minimum impact evaluation value and the fourth maximum impact evaluation value; Calculate the set association degree according to the first association factor and the second association factor: Wherein, P is the set association degree, Lmax is the maximum impact evaluation value in the urea operation influencing factor set, n1 is the number of impact evaluation values ​​in the urea operation influencing factor set, Lx is the x-th impact evaluation value in the urea operation influencing factor set, Hx is the weight corresponding to the x-th impact evaluation value, Qmax is the maximum impact evaluation value in the ammonia operation influencing factor set, n2 is the number of impact evaluation values ​​in the ammonia operation influencing factor set, Qy is the y-th impact evaluation value in the ammonia operation influencing factor set, Vy is the weight corresponding to the y-th impact evaluation value, Wmax is the maximum impact evaluation value in the temperature operation influencing factor set, n3 is the number of impact evaluation values ​​in the temperature operation influencing factor set, Wi is the y-th impact evaluation value in the temperature operation influencing factor set, Ki is the weight corresponding to the ith impact evaluation value, e1 is the first association factor, and e2 is the second association factor; Acquire a preset set association degree, and when the set association degree is greater than or equal to the preset set association degree, generate a set of associated operation influencing factors according to all the influencing evaluation values; When the set association degree is less than the preset set association degree, a set of associated operation influencing factors is generated according to all deleted influence evaluation values.

4. The DCS-based intelligent control method for biomass boiler according to claim 1 is characterized in that: When the associated operation influencing factor set is calculated according to the first preset calculation method and the second preset calculation method, and the comprehensive associated influence value of the associated operation influencing factor set is determined based on the calculation result, the method includes: Calculating a first calculated value of the associated operation influencing factor set based on the first preset calculation method, and calculating a second calculated value of the associated operation influencing factor set based on a second preset calculation method; Extracting all impact evaluation values ​​in the associated operation impact factor set that are greater than the first calculated value and greater than the second calculated value, and generating an overvalue mark; Extracting all impact evaluation values ​​in the associated operation impact factor set that are equal to the first calculated value and the second calculated value, and generating equal value marks; Extracting all impact evaluation values ​​in the associated operation impact factor set that are smaller than the first calculated value and smaller than the second calculated value, and generating an undervalue mark; Count the number of overvalue marks for overvalue marks, count the number of equal-value marks for equal-value marks, and count the number of undervalue marks for undervalue marks; The comprehensive associated impact value of the associated operation impact factor set is calculated according to the number of overvalue marks, the number of equalvalue marks and the number of undervalue marks.

5. The DCS-based intelligent control method for biomass boiler according to claim 4 is characterized in that: When calculating the comprehensive correlation impact value of the set of correlation operation impact factors according to the number of overvalue marks, the number of equalvalue marks, and the number of undervalue marks, it includes: The comprehensive correlation impact value of the set of correlation operation impact factors is calculated according to the following formula: Among them, B is the comprehensive correlation impact value of the set of correlation operation influencing factors, M1 is the number of undervalue marks, M2 is the number of overvalue marks, and M3 is the number of equal value marks.

6. A biomass boiler intelligent control system based on DCS, characterized in that: include: The first module is used to collect real-time characteristic data of the biomass boiler based on a preset collection device, and determine an initial control strategy according to the real-time characteristic data, wherein the real-time characteristic data includes the concentration of the urea solution, the flow rate of the ammonia gas and the temperature of the hydrolysis reactor; The second module is used to obtain the operation influencing factors of each real-time feature data, construct a corresponding operation influencing factor set according to all the operation influencing factors, analyze each operation influencing factor set, and generate a related operation influencing factor set based on the analysis result; A third module is used to calculate the associated operation influencing factor set according to the first preset calculation method and the second preset calculation method, and determine the comprehensive associated impact value of the associated operation influencing factor set based on the calculation result; The fourth module is used to optimize and adjust the initial control strategy based on the comprehensive correlation influence value to obtain a target control strategy, and intelligently control the biomass boiler according to the target control strategy.

7. The DCS-based intelligent control system for biomass boiler according to claim 6 is characterized in that: The second module is used for: The second module is used to construct a urea operation influencing factor set according to the concentration of the urea solution, to construct an ammonia operation influencing factor set according to the flow rate of the ammonia gas, and to construct a temperature operation influencing factor set according to the temperature of the hydrolysis reactor; The second module is used to determine the impact evaluation value of the operation influencing factor in each operation influencing factor set; The second module is used to sort the impact evaluation values ​​in each operation influencing factor set by numerical value to obtain a new urea operation influencing factor set, a new ammonia operation influencing factor set and a new temperature operation influencing factor set; The second module is used to bind every two adjacent impact evaluation values ​​in the new urea operation influencing factor set in pairs, and calculate the impact evaluation difference between every two bound impact evaluation values; The second module is used to obtain a preset impact evaluation difference, extract all two bound impact evaluation values ​​that are greater than or equal to the preset impact evaluation difference, delete the latter impact evaluation value of the two bound impact evaluation values, and retain the former impact evaluation value; The second module is used to construct a set of urea operation influencing factors according to all retained impact evaluation values ​​and all two bound impact evaluation values ​​that are less than the difference of the preset impact evaluation value; The second module is used to bind every two adjacent impact evaluation values ​​in the new ammonia operation influencing factor set in pairs, and construct the ammonia operation influencing factor set; The second module is used to bind every two adjacent impact evaluation values ​​in the new temperature operation influencing factor set in pairs, and construct the temperature operation influencing factor set.

8. The DCS-based intelligent control system for biomass boiler according to claim 7 is characterized in that: The second module is used for: The second module is used to extract the first minimum impact evaluation value in the urea operation influencing factor set, extract the second maximum impact evaluation value and the third minimum impact evaluation value in the ammonia operation influencing factor set, and extract the fourth maximum impact evaluation value in the temperature operation influencing factor set; The second module is used to calculate a first correlation factor between the urea operation influencing factor set and the ammonia operation influencing factor set, wherein the first correlation factor is an absolute value of a difference between the first minimum impact evaluation value and the second maximum impact evaluation value; The second module is used to calculate a second correlation factor between the ammonia operation influencing factor set and the temperature operation influencing factor set, wherein the second correlation factor is an absolute value of a difference between the third minimum impact evaluation value and the fourth maximum impact evaluation value; The second module is used to calculate the set association degree according to the first association factor and the second association factor: Wherein, P is the set association degree, Lmax is the maximum impact evaluation value in the urea operation influencing factor set, n1 is the number of impact evaluation values ​​in the urea operation influencing factor set, Lx is the x-th impact evaluation value in the urea operation influencing factor set, Hx is the weight corresponding to the x-th impact evaluation value, Qmax is the maximum impact evaluation value in the ammonia operation influencing factor set, n2 is the number of impact evaluation values ​​in the ammonia operation influencing factor set, Qy is the y-th impact evaluation value in the ammonia operation influencing factor set, Vy is the weight corresponding to the y-th impact evaluation value, Wmax is the maximum impact evaluation value in the temperature operation influencing factor set, n3 is the number of impact evaluation values ​​in the temperature operation influencing factor set, Wi is the y-th impact evaluation value in the temperature operation influencing factor set, Ki is the weight corresponding to the ith impact evaluation value, e1 is the first association factor, and e2 is the second association factor; The second module is used to obtain a preset set association degree, and when the set association degree is greater than or equal to the preset set association degree, a set of associated operation influencing factors is generated according to all the influencing evaluation values; The second module is used to generate a set of associated operation influencing factors according to all deleted impact evaluation values ​​when the set correlation degree is less than the preset set correlation degree.

9. The DCS-based intelligent control system for biomass boiler according to claim 6 is characterized in that: The third module is used for: The third module is used to calculate a first calculated value of the associated operation influencing factor set based on the first preset calculation method, and calculate a second calculated value of the associated operation influencing factor set according to a second preset calculation method; The third module is used to extract all the impact evaluation values ​​in the associated operation impact factor set that are greater than the first calculated value and greater than the second calculated value, and generate an over-value mark; The third module is used to extract all the impact evaluation values ​​in the associated operation impact factor set that are equal to the first calculated value and the second calculated value, and generate equal value marks; The third module is used to extract all the impact evaluation values ​​in the associated operation impact factor set that are smaller than the first calculated value and smaller than the second calculated value, and generate an undervalue mark; The third module is used to count the number of overvalue marks of overvalue marks, count the number of equal-value marks of equal-value marks, and count the number of undervalue marks of undervalue marks; The third module is used to calculate the comprehensive correlation impact value of the set of correlation operation impact factors according to the number of overvalue marks, the number of equalvalue marks and the number of undervalue marks.

10. The DCS-based intelligent control system for biomass boiler according to claim 9 is characterized in that: The third module is used for: The third module is used to calculate the comprehensive correlation impact value of the set of correlation operation impact factors according to the following formula: Among them, B is the comprehensive correlation impact value of the set of correlation operation influencing factors, M1 is the number of undervalue marks, M2 is the number of overvalue marks, and M3 is the number of equal value marks.

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