Coal-fired power plant by-product control method, system, equipment and storage medium

Abstract

The present invention discloses a method, system, equipment and storage medium for controlling byproducts of coal-fired power plants, the method comprising: collecting unit operation data, inventory data and historical production data of byproducts of coal-fired power plants; correcting the yield setting coefficient according to the unit operation data and historical production data to obtain the corrected yield coefficient; predicting the output forecast value of byproducts within a preset time based on the corrected yield coefficient; determining the real-time warehouse output height of byproducts according to the output forecast value and inventory data; when the real-time warehouse output height reaches the preset alarm height, the byproducts are transported through a transportation strategy. Compared with the prior art, the emission management, inventory management and transportation management of byproducts of coal-fired power plants are still in the extensive manual management stage, and the present invention improves the management level of byproducts of power plants by tracking and counting power generation byproducts, thereby ensuring the economic benefits of byproducts of power plants.

Description

Technical Field

[0001] The present invention belongs to the technical field of coal-fired byproduct control, and in particular relates to a method, system, equipment and storage medium for coal-fired power plant byproduct control. Background Art

[0002] Coal-fired thermal power generation is an important part of my country's power security, accounting for about 70%. While ensuring people's livelihood and promoting social development, the by-product emissions of coal-fired power generation enterprises also have an impact on the ecological environment and even power operations.

[0003] The byproducts of coal-fired power plants include ash, slag, and gypsum. For most coal-fired power plants in my country, their emission management, inventory management, and transportation management are still in the stage of extensive manual management, and digital management needs to be strengthened. The byproduct management and control system of existing coal-fired power plants generally focuses on byproduct transportation vehicle management, production statistics management, supplier management, and product category management, but it is basically equivalent to a process management system. There is no actual guidance strategy for the production forecast of coal-fired power plant byproducts and the transportation of ash vehicles. It is an "after-the-fact management" system. Therefore, how to track and count power generation byproducts to improve the level of byproduct management in power plants has become an urgent problem to be solved.

[0004] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of the present invention is to provide a method, system, equipment and storage medium for coal-fired power plant by-product management, aiming to solve the technical problem of how to track and count power generation by-products to improve the level of power plant by-product management.

[0006] To achieve the above object, the present invention provides a method for controlling byproducts of a coal-fired power plant, the method comprising:

[0007] Collect unit operation data, by-product inventory data and historical production data of coal-fired power plants;

[0008] Correcting the yield setting coefficient according to the unit operation data and the historical output data to obtain a corrected yield coefficient;

[0009] Predicting a predicted output value of the by-product within a preset time based on the corrected yield coefficient;

[0010] Determine the real-time warehouse output height of the by-product according to the output forecast value and the inventory data;

[0011] When the real-time output level of the warehouse reaches a preset alarm level, the by-product is transported using a transport strategy.

[0012] Optionally, the step of correcting the yield setting coefficient according to the unit operation data and the historical production data to obtain a corrected yield coefficient includes:

[0013] Determining a yield measurement coefficient according to the unit operation data and the historical production data;

[0014] According to the yield measurement coefficient, the yield setting coefficient is corrected by a coefficient weighting formula to obtain a corrected yield coefficient;

[0015] The coefficient weighting formula is:

[0016] k'=(x×k0+y×k)

[0017] x+y=1

[0018] Wherein, k' is the corrected yield coefficient, k is the yield setting coefficient, k0 is the yield measurement coefficient, x is the weighted coefficient corresponding to the yield measurement coefficient, and y is the weighted coefficient corresponding to the yield setting coefficient.

[0019] Optionally, the step of determining the yield measurement coefficient according to the unit operation data and the historical production data includes:

[0020] Determine the coal consumption and coal quality data of the coal mill in historical unit time according to the unit operation data;

[0021] Determine the actual production data corresponding to the by-product in the historical unit time according to the historical production data;

[0022] Calculate the yield measurement coefficient according to the coal consumption, the coal quality data and the actual output data through a yield measurement formula;

[0023] The yield measurement formula is:

[0024] k0=ΔM R / (ΔM×C)

[0025] In the formula, ΔM R is the actual output data corresponding to the by-product, ΔM is the coal consumption, and C is the coal quality data.

[0026] Optionally, the step of predicting the output forecast value of the by-product within a preset time based on the corrected yield coefficient includes:

[0027] Obtaining a blending scheme for the coal types to be burned by the coal mill within a preset time through a coal blending system;

[0028] Predicting the coal consumption of the coal mill according to the blending scheme through load trend;

[0029] Based on the corrected yield coefficient, the coal quality data and the predicted coal consumption, the predicted output value of the by-product within a preset time is calculated by using a by-product output prediction formula;

[0030] The by-product yield prediction formula is:

[0031] P=Δm×C×k' / Δt

[0032] Where P is the predicted output of by-products, Δm is the predicted coal consumption, and Δt is the preset time.

[0033] Optionally, the step of determining the real-time height of the warehouse output of the by-product according to the output forecast value and the inventory data includes:

[0034] Determine warehouse three-dimensional structure data of the by-product according to the inventory data;

[0035] Determining the warehouse volume change data after the by-product is unloaded according to the warehouse three-dimensional structure data;

[0036] Calculate the measured value of the bulk density of the by-product by using the actual output data corresponding to the by-product and the warehouse volume change data;

[0037] Adjusting the bulk density setting value according to the bulk density measurement value to obtain an adjusted bulk density value;

[0038] The real-time warehouse output height of the by-product is determined according to the adjusted stacking density value and the output forecast value.

[0039] Optionally, the step of adjusting the bulk density setting value according to the bulk density measurement value to obtain an adjusted bulk density value comprises:

[0040] According to the bulk density measurement value, the bulk density setting value is adjusted by a density correction formula to obtain an adjusted bulk density value;

[0041] The density correction formula is:

[0042] ρ'=(a×ρ0+b×ρ)

[0043] a+b=1

[0044] Wherein, ρ' is the adjusted bulk density value, ρ0 is the measured bulk density value, ρ is the set bulk density value, a is the weighting coefficient of the measured bulk density value, and b is the weighting coefficient of the set bulk density value.

[0045] Optionally, the step of determining the real-time height of the warehouse output of the by-product according to the output forecast value and the inventory data includes:

[0046] determining a warehouse radius based on the inventory data;

[0047] Calculate the cross-sectional mass of the by-product according to the warehouse radius and the adjusted stacking density value by using a cross-sectional mass per unit height formula;

[0048] The formula for the mass per unit height cross-sectional area is:

[0049] m h =(πR 2 ×ρ')

[0050] In the formula, m h is the cross-sectional mass of the by-product, and R is the radius of the warehouse;

[0051] Calculate the warehouse height increment of the by-product by using an increment formula according to the cross-sectional mass and the output prediction value;

[0052] The increment formula is:

[0053]

[0054] In the formula, Increase in warehouse height for by-products;

[0055] The real-time warehouse production height of the by-product is determined based on the warehouse height increment and the initial warehouse production height.

[0056] In addition, to achieve the above-mentioned purpose, the present invention also proposes a coal-fired power plant byproduct management and control system, the coal-fired power plant byproduct management and control system comprising:

[0057] The collection module is used to collect the unit operation data, by-product inventory data and historical production data of coal-fired power plants;

[0058] A correction module, used for correcting the yield setting coefficient according to the unit operation data and the historical output data to obtain a corrected yield coefficient;

[0059] A prediction module, used for predicting the output value of the by-product within a preset time based on the corrected yield coefficient;

[0060] A calculation module, used to determine the real-time height of the warehouse output of the by-product according to the output forecast value and the inventory data;

[0061] The transportation module is used to transport the by-products through a transportation strategy when the real-time output level of the warehouse reaches a preset alarm level.

[0062] In addition, to achieve the above-mentioned objectives, the present invention also proposes a coal-fired power plant byproduct control device, the device comprising: a memory, a processor, and a coal-fired power plant byproduct control program stored in the memory and executable on the processor, the coal-fired power plant byproduct control program being configured to implement the steps of the coal-fired power plant byproduct control method as described above.

[0063] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a coal-fired power plant byproduct control program is stored. When the coal-fired power plant byproduct control program is executed by a processor, the steps of the coal-fired power plant byproduct control method as described above are implemented.

[0064] The present invention first collects the unit operation data, by-product inventory data and historical production data of the coal-fired power plant, and then corrects the yield setting coefficient according to the unit operation data and historical production data to obtain the corrected yield coefficient, and then predicts the output forecast value of the by-product within a preset time based on the corrected yield coefficient, and finally determines the real-time warehouse output height of the by-product according to the output forecast value and inventory data. When the real-time warehouse output height reaches the preset alarm height, the by-product is transported through the transportation strategy. Compared with the emission management, inventory management and transportation management of coal-fired power plant by-products in the prior art, which are still in the extensive manual management stage, and have not formed a good by-product output forecast and by-product transportation strategy, the digital management needs to be strengthened. The present invention improves the management level of power plant by-products by tracking and counting power generation by-products, thereby ensuring the economic benefits of power plant by-products. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a structural schematic diagram of a coal-fired power plant byproduct control device in a hardware operating environment involved in an embodiment of the present invention;

[0066] Figure 2 This is a flow chart of a first embodiment of a method for controlling byproducts of a coal-fired power plant according to the present invention;

[0067] Figure 3 This is a schematic diagram of an information maintenance page for ash storage structure data of the first embodiment of the method for controlling byproducts of a coal-fired power plant according to the present invention;

[0068] Figure 4 This is a schematic diagram of a by-product information display page of the first embodiment of the method for controlling by-products in a coal-fired power plant according to the present invention;

[0069] Figure 5 This is a structural block diagram of the first embodiment of the coal-fired power plant byproduct management and control system of the present invention.

[0070] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0071] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0072] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a coal-fired power plant byproduct control equipment in the hardware operating environment involved in the embodiment of the present invention.

[0073] like Figure 1 As shown, the coal-fired power plant byproduct control device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage system independent of the aforementioned processor 1001.

[0074] Those skilled in the art will understand that Figure 1 The structure shown in does not constitute a limitation on the byproduct management equipment of a coal-fired power plant, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0075] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a coal-fired power plant by-product management and control program.

[0076] exist Figure 1In the coal-fired power plant byproduct control device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the coal-fired power plant byproduct control device of the present invention can be set in the coal-fired power plant byproduct control device, and the coal-fired power plant byproduct control device calls the coal-fired power plant byproduct control program stored in the memory 1005 through the processor 1001, and executes the coal-fired power plant byproduct control method provided in the embodiment of the present invention.

[0077] The embodiment of the present invention provides a method for controlling byproducts of a coal-fired power plant, referring to Figure 2 , Figure 2 This is a flow chart of the first embodiment of the method for controlling byproducts of a coal-fired power plant according to the present invention.

[0078] In this embodiment, the method for controlling byproducts of a coal-fired power plant includes the following steps:

[0079] Step S10: Collecting unit operation data, by-product inventory data and historical production data of the coal-fired power plant.

[0080] It is easy to understand that the executor of this embodiment can be a coal-fired power plant byproduct management and control system with functions such as data processing, network communication and program running, or other computer equipment with similar functions, etc., and this embodiment is not limited.

[0081] It should also be noted that the data sources include by-product height measuring devices, coal-fired power plant SIS systems, and coal blending systems or fuel management systems. The by-products of coal-fired power plants include coal ash (ash), coal cinders (cinders), and desulfurization gypsum (gypsum); among them, coal ash is collected by the electrostatic precipitator of the power plant; coal cinders are collected by the boiler ash hopper slag remover, and gypsum is collected by the desulfurization system.

[0082] The unit operation data is the coal feed data (i.e. coal consumption) of the coal mill in the historical unit time of the coal-fired power plant operation unit, the coal quality data (the coal quality data specifically includes the ash content ratio and sulfur content ratio) and the by-product yield coefficient of the corresponding coal type;

[0083] The by-product yield coefficient of the coal type specifically includes the ash output ratio (the quotient of the coal ash output after the unit is burned and operated and the original amount of coal used), the slag output ratio (the quotient of the coal slag output after the unit is burned and operated and the original amount of coal used) and the gypsum yield (the quotient of the gypsum output after the unit is burned and operated and the original amount of coal used).

[0084] It should be understood that the coal feed quantity data is acquired in real time by the power plant SIS system, the coal quality data is acquired in real time by the power plant coal blending system or fuel management system, and the by-product yield coefficient (ash output ratio, slag output ratio and gypsum yield) of the corresponding coal type is automatically calculated and corrected by the system, manually set by the operator or set by default (i.e. initialized and unchanged later).

[0085] The by-product inventory data includes the warehouse three-dimensional structure data of the by-product and the stacking density setting data of the by-product. The warehouse three-dimensional structure data of the by-product includes the bottom shape, size, height and cross-sectional area data along the height, etc., which are manually set by the system operator or set by default (i.e., initialized and unchanged later). The stacking density setting data of the by-product is manually set by the system operator or set by default (i.e., initialized and unchanged later).

[0086] The historical production data includes the actual production data of by-products within a historical unit time, and the actual production data of by-products within a historical unit time is obtained from the weighing system of the by-product transfer vehicle leaving the coal-fired power plant.

[0087] Step S20: Correcting the yield setting coefficient according to the unit operation data and the historical production data to obtain a corrected yield coefficient.

[0088] Furthermore, the coal consumption and coal quality data of the coal mill within the historical unit time are determined based on the unit operation data; the actual output data corresponding to the by-products within the historical unit time are determined based on the historical output data; the yield measurement coefficient is calculated through the yield measurement formula based on the coal consumption, coal quality data and actual output data; the yield setting coefficient is corrected through the coefficient weighting formula based on the yield measurement coefficient to obtain the corrected yield coefficient.

[0089] The yield measurement formula is:

[0090] k0=ΔM R / (ΔM×C)

[0091] Where k0 is the yield measurement coefficient (k0 includes α0, β0 and γ0), ΔM R The actual production data corresponding to the by-product (actual production data ΔM R Including actual ash production data ΔM R1 , the actual production data of slag ΔM R2 And the actual production data of gypsum ΔM R3 ), ΔM is the coal consumption, and C is the coal quality data (the coal quality data C includes ash content A and sulfur content S).

[0092] The coefficient weighting formula is:

[0093] k'=(x×k0+y×k)

[0094] x+y=1

[0095] Wherein, k' is the corrected yield coefficient, k is the yield setting coefficient, x is the weighting coefficient corresponding to the yield measurement coefficient, and y is the weighting coefficient corresponding to the yield setting coefficient.

[0096] In the specific implementation, the actual production data of the by-products in the historical time ΔM is obtained. R , the coal consumption of each coal mill in the historical period ΔM and the coal quality (ash content A, sulfur content S), the ash ratio measurement data in the by-product yield (i.e., the ash yield measurement coefficient) α0 = ΔM R1 / (ΔM×A), slag discharge ratio measurement data (i.e. slag yield measurement coefficient) β0=ΔM R2 / (ΔM×A) and gypsum yield (i.e., gypsum yield measurement coefficient) γ0=ΔM R3 / (ΔM×S).

[0097] Since there are errors in general industrial measurements, the weighting coefficient x of the actual measured value of the by-product yield coefficient and the weighting coefficient y of the given by-product yield coefficient can be adjusted to obtain the corrected data k' of the by-product yield coefficient k as follows: k'=(x×k0+y×k). Where k represents the set ash discharge ratio α, slag discharge ratio β and gypsum yield γ, and the corresponding weighting coefficients x and y are both x+y=1, which can be set manually by the system operator or by the system default setting. If the by-product yield coefficient is set manually by the operator or by default, the ash discharge ratio, slag discharge ratio and gypsum yield will still be α, β and γ.

[0098] In this embodiment, after a certain shift (the unit runs for 8 hours and changes to another shift), the coal consumption ΔM of unit #1 of a coal-fired power plant is 1980 tons, the ash content A of the coal is 20% (A=0.2), the sulfur content S is 0.95% (S=0.095), the given ash discharge ratio α is 0.9, the slag discharge ratio β is 0.1, and it is assumed that the ratio of all sulfur content in the coal is converted into gypsum is 0.9. The gypsum yield γ is the ratio of the molecular weight of calcium sulfate dihydrate (CaSO4·2H2O, the main cost of gypsum) to sulfur multiplied by the above conversion ratio, that is, the given value of gypsum yield γ=0.9×172 / 32=4.838, and the actual ash discharge ΔM R1 The actual slag discharge volume is 369.8t, ΔM R2 The actual gypsum output is 5.72t, ΔM R3 It is 13.04t. For specific parameters, please refer to the following table:

[0099] project symbol unit Numeric Coal consumption ΔM t 1980 Coal ash A ％ 20 Sulfur content of coal S ％ 9.5 Actual ash output <![CDATA[ΔM R1 ]]> t 369.8 Actual slag discharge <![CDATA[ΔM R2 ]]> t 40.4 Actual gypsum production <![CDATA[ΔM R3 ]]> t 92.2 Ash output ratio given value α - 0.9 Slag discharge ratio given value β - 0.1 Gypsum yield given value γ - 4.838

[0100] Then the measured data of ash ratio in by-product yield is:

[0101] α0=ΔM R1 / (ΔM×A)=369.8 / (1980×0.2)=0.934

[0102] The measured data of slag discharge ratio is:

[0103] β0=ΔM R2 / (ΔM×A)=40.4 / (1980×0.2)=0.102

[0104] The measured data of gypsum yield are:

[0105] γ0=ΔM R3 / (ΔM×S)=92.2 / (1980×0.0095)=4.902

[0106] In this embodiment, the by-product yield coefficient adopts the system automatic calculation correction mode, and the weighting coefficient x of the actual measured value of the by-product yield coefficient and the weighting coefficient y of the given by-product yield coefficient can be adjusted specifically as follows: x=y=0.5, then the correction data k' of the by-product yield coefficient k is expressed as follows: k'=(x×k0+y×k)=0.5×(k0+k), and the corresponding correction data of the ash discharge ratio, slag discharge ratio and gypsum yield are respectively:

[0107] α'=0.5×(α0+α)=0.5×(0.934+0.9)=0.917

[0108] β'=0.5×(β0+β)=0.5×(0.102+0.1)=0.101

[0109] γ'=0.5×(γ0+γ)=0.5×(4.902+4.838)=4.885

[0110] Step S30: predicting the output value of the by-product within a preset time based on the corrected yield coefficient.

[0111] By real-time tracking of the types of coal entering the furnace, associating coal quality characteristics with the load forecast for a certain period of time in the future, analyzing the historical statistics of the power plant and big data, the by-product output is predicted by taking the unit load and the type of coal entering the warehouse as input, and the by-product ash, slag and gypsum output as output. The predicted results are compared with the actual results and corrected, and finally a high-precision by-product output prediction model is obtained.

[0112] Furthermore, a coal blending and combustion system is used to obtain a blending and combustion scheme for the coal type to be burned by the coal mill within a preset time; the coal consumption forecast of the coal mill is predicted by load trend according to the blending and combustion scheme; the output forecast value of the by-product within a preset time is calculated by a by-product output prediction formula based on the corrected yield coefficient, coal quality data and the coal consumption forecast;

[0113] The by-product yield prediction formula is:

[0114] P=Δm×C×k' / Δt

[0115] Where P is the predicted output value of by-products (including the predicted output value of ash products per unit time P1, the predicted output value of slag products per unit time P2 and the predicted output value of gypsum per unit time P3), Δm is the predicted coal consumption, and Δt is the preset time.

[0116] In the specific implementation, the blending scheme for the future period is obtained according to the coal blending system, that is, the coal types burned by each coal mill in the unit; the coal consumption Δm of each coal mill in the future period is predicted according to the load trend; according to the coal consumption Δm of each coal mill, ash content, sulfur content, ash output ratio, slag output ratio and gypsum yield, the calculation results are as follows:

[0117] If the by-product yield coefficient adopts the system automatic calculation correction mode, the ash ratio correction value is α', the slag ratio correction value is β' and the gypsum yield correction value is γ', then the by-product output in the future period of time Δt is calculated. The specific calculation method is as follows:

[0118] P1=Δm×A×α' / Δt

[0119] P2=Δm×A×β' / Δt

[0120] P3=Δm×S×γ' / Δt

[0121] If the by-product yield coefficient is set manually by the operator or in the default setting mode, the ash discharge ratio is α, the slag discharge ratio is β, and the gypsum yield is γ, the by-product yield for a period of time Δt in the future is calculated as follows:

[0122] P1=Δm×A×α / Δt

[0123] P2=Δm×A×β / Δt

[0124] P3=Δm×S×γ / Δt

[0125] In this embodiment, it can be predicted that the coal consumption of the #1 unit of a coal-fired power plant in the next day (24 hours) is 4650 tons, the ash content A of the coal is 20%, the sulfur content is 0.95%, and the by-product yield coefficient adopts the system automatic calculation correction mode, Δm=4650t, Δt=24h, then the predicted value of the by-product output per unit time in the next day is as follows:

[0126] P1=Δm×A×α' / Δt=4650×0.2×0.917 / 24=35.5338t / h

[0127] P2=Δm×A×β' / Δt=4650×0.2×0.101 / 24=3.9138t / h

[0128] P3=Δm×S×γ' / Δt=4650×0.0095×4.885 / 25=8.9916t / h

[0129] Step S40: determining the real-time warehouse output height of the by-product according to the output forecast value and the inventory data.

[0130] Furthermore, the three-dimensional structural data of the warehouse of the by-product is determined based on the inventory data; the volume change data of the warehouse after the by-product is unloaded is determined based on the three-dimensional structural data of the warehouse; the stacking density measurement value of the by-product is calculated through the actual output data corresponding to the by-product and the warehouse volume change data; the stacking density set value is adjusted according to the stacking density measurement value to obtain the adjusted stacking density value; the real-time height of the warehouse output of the by-product is determined based on the adjusted stacking density value and the output forecast value.

[0131] In this embodiment, the ash byproduct of a coal-fired power plant is taken as an example. The ash bin is cylindrical. Figure 3 , Figure 3 This is a schematic diagram of the information maintenance page of the ash storage structure data of the first embodiment of the method for controlling byproducts of a coal-fired power plant of the present invention, and the actual output data ΔM of the byproducts in the historical time is obtained. R And the volume change data ΔV after the by-product warehouse is unloaded, then the measured data of the by-product bulk density is the quotient of the actual production data of the by-product in the historical time and the volume change data after the by-product warehouse is unloaded, that is, the bulk density measurement value ρ0=ΔM R / ΔV.

[0132] Since there are errors in general industrial measurements, the weighting coefficient a of the actual measured density ρ0 and the weighting coefficient b of the given by-product bulk density ρ can be adjusted to obtain the by-product bulk density correction data (i.e. the by-product adjusted bulk density value) ρ' expression: ρ'=(a×ρ0+b×ρ)=(a×ΔM R / ΔV+b×ρ). The weight coefficients a and b have the relationship a+b=1, which can be set manually by the system operator or by the system default setting.

[0133] In this example, the density of ash in a coal-fired power plant is given as 0.55×10 3 kg / m 3 , and the byproduct (ash) output of the #1 ash storage was measured at one time, ΔM R1 The ash storage bin No. 1 is cylindrical with a radius of R = 7.85m. The pi is 3.1415. After the ash storage bin No. 1 is unloaded, the height of the storage bin is reduced by Δh to 5.2m.

[0134] The actual volume change data is:

[0135] ΔV=πR 2 ×Δh=3.1415×7.85 2 ×5.2=1006.6528m 3

[0136] The actual measured density is:

[0137] ρ0=ΔM R1 / ΔV=575.8×10 3 kg / 1006.6528m 3 =0.5720×10 3 kg / m 3

[0138] Since there are errors in general industrial measurements, the weighting coefficient a of the actual measured density ρ0 and the weighting coefficient b of the given ash bulk density ρ can be adjusted, specifically a=b=0.5, then the ash bulk density correction data is ρ':

[0139] ρ'=(a×ρ0+b×ρ)=0.5×0.5720×10 3 +0.5×0.55×10 3 =0.5610×10 3 kg / m 3

[0140] Further, the processing method for determining the real-time warehouse output height of the by-product according to the output forecast value and the inventory data is to determine the warehouse radius according to the inventory data; calculate the cross-sectional mass of the by-product according to the warehouse radius and the adjusted stacking density value by using the unit height cross-sectional mass formula; calculate the warehouse height increment of the by-product according to the cross-sectional mass and the output forecast value by using the increment formula;

[0141] The formula for the mass per unit height cross-sectional area is:

[0142] m h =(πR 2 ×ρ')

[0143] In the formula, m h is the cross-sectional mass of the by-product, and R is the radius of the warehouse;

[0144] The increment formula is:

[0145]

[0146] In the formula, Increase in warehouse height for by-products;

[0147] The real-time warehouse production height of the by-product is determined based on the warehouse height increment and the initial warehouse production height.

[0148] In this embodiment, at the initial time t0, the height of the by-product warehouse is h1, and the alarm height is H. The by-product output prediction result is used to calculate the by-product warehouse explosion time ΔT (that is, the height reaches H), and the calculation scheme is:

[0149] If the by-product warehouse is cylindrical (generally speaking, it is a standard cylindrical shape), the variable of warehouse height increase per unit time is the quotient of the predicted value of by-product output per unit time and the mass of the unit height cross-sectional area, and the density is calculated using the corrected value, that is:

[0150]

[0151] The explosion time Δt is the height difference ΔH between the ash bin and the alarm and the height increment of the by-product bin. The quotient of is:

[0152]

[0153] When the by-product warehouse is not a standard cylindrical shape, it is only necessary to integrate the cross section in the height direction to calculate the volume. The system can initialize the warehouse volume shape parameters and then solve them. This embodiment does not elaborate on this aspect.

[0154] In this embodiment, taking the ash byproduct of a coal-fired power plant as an example, the ash product of unit #1 is stored in ash silo #1, which is cylindrical. The parameters are as described above, then:

[0155]

[0156] At the initial time t0, the height of the by-product warehouse is h1 = 4.7m, and the alarm height is H = 8m. The explosion time ΔT of the by-product warehouse is calculated based on the by-product output prediction result:

[0157]

[0158] Step S50: When the real-time output level of the warehouse reaches a preset alarm level, the by-product is transported using a transport strategy.

[0159] According to the above embodiment, it can be known that #1 ash bin has the possibility of bursting in 10 hours, and early warning can be given. When the height of the ash bin reaches 8m, an alarm is issued, an alarm signal is output, and the system generates a transportation strategy for ash trucks.

[0160] It should also be noted that the transportation strategy for by-products is the transportation strategy for the by-product factory transfer vehicle: when the by-product output reaches the alarm value (such as a warehouse overflow), a transportation strategy is generated based on the location of the transfer vehicle and the transportation capacity of the transfer vehicle to reduce manual operation; the by-product transportation strategy is generated based on the principle of "first come, first served".

[0161] In the specific implementation, the arrival time of each transfer vehicle (empty vehicle) is collected, and the first one to arrive at the factory is transferred first. When there is a vehicle failure or other factors, this vehicle is excluded and the subsequent vehicles are transferred in order. The function of manual transfer by personnel is also retained.

[0162] It should be understood that reference Figure 4 , Figure 4 This is a schematic diagram of the by-product information display page of the first embodiment of the coal-fired power plant by-product management and control method of the present invention, which is used to display and output information such as current by-product inventory, by-product output forecast value, by-product transportation strategy and by-product output.

[0163] According to the central adjustment instructions and historical load curve fitting methods, the unit load within a certain period of time is predicted, and combined with the above by-product output prediction results, the output is integrated on the time axis, and the total ash quantity statistics in the future time can be obtained. Combined with the ash storage volume of the current unit ash bin or the ash level line of the ash bin and the ash bin's own characteristics (shape, volume), the ash storage volume-ash level line curve is obtained; the predicted by-product increment is converted into the increment of the bin position line, and the predicted trend of the bin position can be obtained. When the bin position reaches the predetermined alarm line, an alarm is issued in time and a transfer vehicle scheduling strategy is formed to notify the operating personnel to dispatch the ash vehicle, which not only ensures the safe operation of the unit, but also prevents accidents in which the bin position is too high and the load has to be reduced.

[0164] In this embodiment, firstly, the unit operation data, by-product inventory data and historical production data of the coal-fired power plant are collected, and then the yield setting coefficient is corrected according to the unit operation data and the historical production data to obtain the corrected yield coefficient, and then the output forecast value of the by-product within the preset time is predicted based on the corrected yield coefficient, and finally the real-time warehouse output height of the by-product is determined according to the output forecast value and the inventory data, and when the real-time warehouse output height reaches the preset alarm height, the by-product is transported through the transportation strategy. Compared with the emission management, inventory management and transportation management of coal-fired power plant by-products in the prior art, which are still in the stage of extensive manual management, and the actual situation of not forming a good by-product output forecast and by-product transportation strategy, the digital management needs to be strengthened, and this embodiment can further improve the management level of power plant by-products by tracking the emission and transportation of coal-fired power plant by-products in the whole process, reduce manual intervention and reduce the workload of personnel, and further ensure the economic benefits of power plant by-products.

[0165] Reference Figure 5 , Figure 5 This is a structural block diagram of the first embodiment of the coal-fired power plant byproduct management and control system of the present invention.

[0166] like Figure 5 As shown, the coal-fired power plant byproduct management and control system proposed in the embodiment of the present invention includes:

[0167] The collection module 5001 is used to collect the unit operation data, by-product inventory data and historical production data of the coal-fired power plant;

[0168] A correction module 5002, used to correct the yield setting coefficient according to the unit operation data and the historical production data to obtain a corrected yield coefficient;

[0169] Prediction module 5003, used to predict the output value of the by-product within a preset time based on the corrected yield coefficient;

[0170] A calculation module 5004, configured to determine the real-time height of the warehouse output of the by-product according to the output forecast value and the inventory data;

[0171] The transportation module 5005 is used to transport the by-products through a transportation strategy when the real-time output level of the warehouse reaches a preset alarm level.

[0172] Other embodiments or specific implementations of the coal-fired power plant byproduct management and control system of the present invention can refer to the above-mentioned method embodiments, which will not be repeated here.

[0173] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0174] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0175] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory / random access memory, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0176] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for controlling byproducts of a coal-fired power plant, characterized in that: The method for controlling byproducts of a coal-fired power plant comprises the following steps: Collect unit operation data, by-product inventory data and historical production data of coal-fired power plants; Correcting the yield setting coefficient according to the unit operation data and the historical output data to obtain a corrected yield coefficient; Predicting the output value of the by-product within a preset time based on the corrected yield coefficient; Determine the real-time warehouse output height of the by-product according to the output forecast value and the inventory data; When the real-time output level of the warehouse reaches a preset alarm level, the by-product is transported using a transport strategy.

2. The method according to claim 1, characterized in that The step of correcting the yield setting coefficient according to the unit operation data and the historical output data to obtain a corrected yield coefficient comprises: Determining a yield measurement coefficient according to the unit operation data and the historical production data; According to the yield measurement coefficient, the yield setting coefficient is corrected by a coefficient weighting formula to obtain a corrected yield coefficient; The coefficient weighting formula is: k'=(x×k0+y×k) x+y=1 Wherein, k' is the corrected yield coefficient, k is the yield setting coefficient, k0 is the yield measurement coefficient, x is the weighted coefficient corresponding to the yield measurement coefficient, and y is the weighted coefficient corresponding to the yield setting coefficient.

3. The method according to claim 2, characterized in that The step of determining the yield measurement coefficient according to the unit operation data and the historical output data comprises: Determine the coal consumption and coal quality data of the coal mill in historical unit time according to the unit operation data; Determine the actual production data corresponding to the by-product in the historical unit time according to the historical production data; Calculate the yield measurement coefficient according to the coal consumption, the coal quality data and the actual output data through a yield measurement formula; The yield measurement formula is: k0=ΔM R / (ΔM×C) In the formula, ΔM R is the actual output data corresponding to the by-product, ΔM is the coal consumption, and C is the coal quality data.

4. The method according to claim 3, characterized in that The step of predicting the output forecast value of the by-product within a preset time based on the corrected yield coefficient comprises: Obtaining a blending scheme for the coal types to be burned by the coal mill within a preset time through a coal blending system; Predicting the coal consumption of the coal mill according to the blending scheme through load trend; Based on the corrected yield coefficient, the coal quality data and the predicted coal consumption, the predicted output value of the by-product within a preset time is calculated by using a by-product output prediction formula; The by-product yield prediction formula is: P=Δm×C×k' / Δt Where P is the predicted output of by-products, Δm is the predicted coal consumption, and Δt is the preset time.

5. The method according to any one of claims 1 to 4, characterized in that: The step of determining the real-time height of the warehouse output of the by-product according to the output forecast value and the inventory data comprises: Determine warehouse three-dimensional structure data of the by-product according to the inventory data; Determining the warehouse volume change data after the by-product is unloaded according to the warehouse three-dimensional structure data; Calculate the measured value of the bulk density of the by-product by using the actual output data corresponding to the by-product and the warehouse volume change data; Adjusting the bulk density setting value according to the bulk density measurement value to obtain an adjusted bulk density value; The real-time warehouse output height of the by-product is determined according to the adjusted stacking density value and the output forecast value.

6. The method according to claim 5, characterized in that The step of adjusting the bulk density setting value according to the bulk density measurement value to obtain an adjusted bulk density value comprises: According to the bulk density measurement value, the bulk density setting value is adjusted by a density correction formula to obtain an adjusted bulk density value; The density correction formula is: ρ'=(a×ρ0+b×ρ) a+b=1 Wherein, ρ' is the adjusted bulk density value, ρ0 is the measured bulk density value, ρ is the set bulk density value, a is the weighting coefficient of the measured bulk density value, and b is the weighting coefficient of the set bulk density value.

7. The method according to claim 6, characterized in that The step of determining the real-time height of the warehouse output of the by-product according to the output forecast value and the inventory data comprises: determining a warehouse radius based on the inventory data; Calculate the cross-sectional mass of the by-product according to the warehouse radius and the adjusted stacking density value by using a cross-sectional mass per unit height formula; The formula for the mass per unit height cross-sectional area is: m h =(πR 2 ×ρ’) In the formula, m h is the cross-sectional mass of the by-product, and R is the radius of the warehouse; Calculate the warehouse height increment of the by-product by using an increment formula according to the cross-sectional mass and the output prediction value; The increment formula is: In the formula, Increase in warehouse height for by-products; The real-time warehouse production height of the by-product is determined based on the warehouse height increment and the initial warehouse production height.

8. A coal-fired power plant byproduct management and control system, characterized in that: The coal-fired power plant byproduct management and control system includes: The collection module is used to collect the unit operation data, by-product inventory data and historical production data of coal-fired power plants; A correction module, used for correcting the yield setting coefficient according to the unit operation data and the historical output data to obtain a corrected yield coefficient; A prediction module, used for predicting the output value of the by-product within a preset time based on the corrected yield coefficient; A calculation module, used for determining the real-time height of the warehouse output of the by-product according to the output forecast value and the inventory data; The transportation module is used to transport the by-products through a transportation strategy when the real-time output level of the warehouse reaches a preset alarm level.

9. A coal-fired power plant byproduct control device, characterized in that: The device includes: a memory, a processor, and a coal-fired power plant byproduct control program stored in the memory and executable on the processor, wherein the coal-fired power plant byproduct control program is configured to implement the steps of the coal-fired power plant byproduct control method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a coal-fired power plant byproduct control program, and when the coal-fired power plant byproduct control program is executed by the processor, the steps of the coal-fired power plant byproduct control method as described in any one of claims 1 to 7 are implemented.

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