Coal mill group control method and system adapting to rapid load change

Abstract

The invention relates to the field of power station boiler coal mills, and provides a coal mill group control method adaptive to rapid load change, which comprises the following steps: acquiring the maximum output and economic output data when each coal mill uses different coal types at present; calculating the actual coal quantity, the coal type and the corresponding heat value of each coal mill under the current load P, and the load P'after the T moment, and establishing a judgment model for the start-stop control of the coal mill unit, so as to obtain the time for controlling the start-stop of the coal mill unit; meanwhile, the change of main indexes influencing the boiler economy is quantified into the influence on the unit power supply coal consumption, a calculation model of the coal consumption change delta b is established, safety and environmental protection indexes are considered, the model is established through a machine learning algorithm, optimization calculation is conducted, and the most economical coal quantity of each coal mill is obtained. The method fully adapts to frequently and rapidly changing loads, and the production efficiency and the equipment safety are improved.

Description

Technical Field

[0001] The invention relates to the field of power station boiler coal mills, and in particular to a coal mill group control method adapting to rapid load changes. Background Art

[0002] At present, with the continuous advancement of China's power market reform, the power spot market is gradually being liberalized. It realizes the instant buying and selling of electricity through bilateral quotations or centralized bidding. It has timeliness, flexibility and randomness, can timely reflect the market supply and demand relationship, and optimize the allocation of power resources. However, for the power generation side, facing the rapid fluctuation and unpredictability of load, it brings a series of difficulties to operation and equipment control. Among them, the coal mill of the coal-fired boiler pulverizing system faces rapid changes in load. Because the total coal volume is positively correlated with the unit's electrical load, the coal volume of each coal mill has an upper and lower limit, so the operator needs to judge in real time whether it is necessary to start a new coal mill or shut down an operating coal mill. The start-up and shutdown steps of each coal mill are relatively cumbersome and time-consuming, and inspection personnel are required to check the equipment on site. Frequent start-up and shutdown bring great difficulties to operators and inspection personnel. At present, there is still no targeted technical solution to optimize the start-up and shutdown timing of coal mills and reduce the workload of operators under the condition of frequent load fluctuations.

[0003] The Chinese invention patent application with publication number CN112619871A, "Automatic preselection module for coal mill start and stop of thermal power unit", determines the coal mill start and stop object based on the analysis and decoupling of the unit's boiler cooling water volume, furnace outlet smoke temperature, and furnace outlet nitrogen oxide content indicators, and comprehensively considers the coal mill economic indicators and operating time, taking into account the safety, economy and environmental protection of the unit operation. The best combination of coal mill start and stop is considered, but the timing of start and stop is not determined based on rapid load changes. The Chinese invention patent application with publication number CN118002296A, "Intelligent control method and device for coal mill suitable for deep peak regulation of power station", combines the boundary conditions such as the dispatching instructions of coal-fired power generation units, coal types, and heat distribution of each heating surface of the boiler, and incorporates the intelligent operation analysis algorithm into it, and finally gives the start and stop equipment planning and start and stop time nodes of the pulverizing system, but does not consider the difference in the maximum output of each coal mill and the impact of changes in coal types. Summary of the invention

[0004] The technical problem to be solved by the present invention is how to perform group control on the coal mill units of power plant boilers to obtain the coal mill start and stop timing and the optimal coal quantity for each coal mill in order to adapt to the rapidly changing load.

[0005] The present invention solves the above technical problems through the following technical means:

[0006] The present invention provides a coal mill group control method adapting to rapid load changes, the method comprising the following steps:

[0007] S1. Obtain the maximum output and economic output data of each coal mill when using different types of coal;

[0008] S2. Obtain the actual coal quantity, coal type and corresponding calorific value of each coal mill under the current load P, and the load P' after time T;

[0009] S3, based on the parameters obtained in step S1 and step S2, calculating and establishing a judgment model for start-stop control of the coal mill unit;

[0010] S4, based on the coal mill start and stop control calculation model obtained in step S3, obtaining the timing of controlling the start and stop of the coal mill;

[0011] S5. Quantify the changes of the main indicators that affect the economic efficiency of the boiler as the impact on the coal consumption of the unit power supply, and establish a calculation model for the coal consumption change Δb;

[0012] S6. Based on the calculation model of the coal consumption change Δb obtained in step S5 and the energy balance formula, and taking into account safety and environmental protection indicators, a model is established using a machine learning algorithm to perform optimization calculations to obtain the most economical coal quantity for each coal mill.

[0013] Furthermore, there are two ways to obtain the maximum output and economic output data in step S1, specifically:

[0014] (1) Regularly obtain the maximum output and economic output data of each coal mill through performance tests;

[0015] (2) By obtaining the historical data of each coal mill, including at least the coal mill differential pressure, coal mill outlet air temperature, coal mill current, coal mill vibration parameters, coal mill power consumption, primary air pressure, and primary fan power consumption; using machine learning algorithm model training and optimization to obtain the current maximum output and economic output data of each coal mill.

[0016] The step S3 comprises the following steps:

[0017] S31. Calculate the sum of heat Q input to the boiler from all coal mills in operation under the current load P now , the sum of the heat that can be input into the boiler when all coal mills are running at maximum output Q max And the sum of the heat that can be input into the boiler when all coal mills are operating at economic output Q eco ;

[0018] S32, calculating the difference ΔQ between the sum of the input heat reversed by the current load P and the sum of the input heat reversed by the load P' at time T;

[0019] S33. Determine the size relationship between P and P'. If P' > P, then ΔQ = P' - P, and proceed to step S34; if P' < P, then ΔQ = P - P', and proceed to step S35;

[0020] S34. Determine the size relationship between ΔQ and Q max -Q now If ΔQ ≤ Q max -Q now , it means that increasing the coal quantity can meet the load increase, and there is no need to start a new coal mill; then skip step S4 and proceed to step S5; if ΔQ > Q max -Q now , it means that the number of currently operating coal mills is no longer sufficient to meet the load increase, and a new coal mill needs to be started, then continue to execute step S4;

[0021] S35. Determine the size relationship between ΔQ and Q now -Q eco If ΔQ ≤ Q now -Q eco , it means that reducing the coal quantity can meet the load decrease and can keep the coal mill operating at the economic output state, and there is no need to shut down the existing coal mills; then skip step S4 and proceed to step S5; if ΔQ > Q now -Q eco , it means that reducing the coal quantity requires reducing the coal output of some coal mills below the economic output state, resulting in a decrease in the stability of the coal mills, and insufficient economy and safety of the unit, and one coal mill needs to be shut down, then continue to execute step S4.

[0022] The specific content of step S4 is as follows:

[0023] When P' > P, the time point T for starting a new coal mill 开启 = T - T 暖磨 -T 启动 -T 升出力 ;

[0024] When P' < P, the time point T for shutting down an existing coal mill 关闭 = T - T 停运 -T 降出力 ;

[0025] Among them, T 暖磨 is the time required for warming up the coal mill before starting, T 启动 is the time required for starting the coal mill, T 升出力 is the time required for increasing the output of the coal mill, T 停运 is the time required for shutting down the coal mill, T 降出力 is the time required for reducing the output of the coal mill.

[0026] The step S5 is specifically as follows:

[0027] The different increase or decrease of coal volume in each pulverizer has different effects on the boiler water-cooled wall temperature, superheater wall temperature, superheated steam temperature and pressure, reheated steam temperature and pressure, desuperheating water volume, nitrogen oxide emissions, and exhaust gas temperature, which in turn affects the boiler's economy, safety, and environmental protection indicators. The main indicators that affect the boiler's economy include superheated steam temperature t 过热 , reheat steam temperature t 再热 , superheated steam pressure p 过热 , reheat steam pressure p 再热 、Superheating and desuperheating water volume m 过热 , Reheating water volume m 再热 , exhaust gas temperature t 排烟 , when the coal output of the pulverizer increases or decreases, the change in the above parameters is Δt 过热 , Δt 再热 , Δp 过热 , Δp 再热 , Δm 过热 , Δm 再热 , Δt 排烟 ;

[0028] The change in the unit economy caused by the unit change of the above parameters is quantified as the impact on the unit power supply coal consumption b. By querying the empirical values ​​of the unit change of the above parameters of different grades of coal-fired units affecting the unit power supply coal consumption, the values ​​of the unit change of the parameters affecting the unit power supply coal consumption are obtained, which are b1, b2, b3, b4, b5, b6, and b7; b1-b7 are positive or negative values ​​according to the parameter characteristics, and the calculation model of the coal consumption change caused by the overall parameter changes after increasing or decreasing the coal volume is Δb as follows:

[0029] Δb=Δt 过热 b1+Δt 再热 b2+Δp 过热 ·b3+Δp 再热 ·b4+Δm 过热 ·b5+Δm 再热 ·b6+Δt 排烟 ·b7(6)

[0030] Wherein, b is the coal consumption for power supply, and the unit of coal consumption for power supply is kg / kwh.

[0031] Preferably, the safety and environmental protection indicators in step S5 include: water-cooled wall temperature, superheater wall temperature, and nitrogen oxide indicators.

[0032] The present invention also provides a coal mill group control system adapting to rapid load changes, the system comprising:

[0033] Parameter collection module, used to obtain the maximum output and economic output data of each coal mill when using different types of coal;

[0034] The working condition acquisition module is used to obtain the actual coal quantity, coal type and corresponding calorific value of each coal mill under the current load P, and the load P' after time T;

[0035] A start-stop judgment model establishment module is used to calculate and establish a judgment model for start-stop control of the coal mill unit based on the parameters obtained by the parameter acquisition module and the operating condition acquisition module;

[0036] The start-stop control module is used to determine the start-stop control calculation model of the coal mill unit obtained by the start-stop judgment model establishment module, and obtain the timing of controlling the start-stop of the coal mill unit;

[0037] The module for establishing the economic coal consumption model is used to quantify the changes in the main indicators that affect the economic efficiency of the boiler as the impact on the coal consumption of the unit power supply, and to establish a calculation model for the coal consumption change Δb;

[0038] The coal quantity control module is used to establish a calculation model for the coal consumption change Δb obtained by the economic coal consumption model establishment module, and the energy balance formula, while taking into account safety and environmental protection indicators. It uses a machine learning algorithm to establish a model and perform optimization calculations to obtain the most economical coal quantity for each coal mill.

[0039] Furthermore, the parameter acquisition module has two modes for acquiring parameters, specifically:

[0040] (1) Regularly obtain the maximum output and economic output data of each coal mill through performance tests;

[0041] (2) By obtaining the historical data of each coal mill, including at least the coal mill differential pressure, coal mill outlet air temperature, coal mill current, coal mill vibration parameters, coal mill power consumption, primary air pressure, and primary fan power consumption; using machine learning algorithm model training and optimization to obtain the current maximum output and economic output data of each coal mill.

[0042] The start-stop judgment model building module includes the following units:

[0043] Heat calculation unit, used to calculate the sum of heat Q input to the boiler from all running coal mills under the current load P now , the sum of the heat that can be input into the boiler when all coal mills are running at maximum output Q max And the sum of the heat that can be input into the boiler when all coal mills are operating at economic output Q eco ;

[0044] A load calculation unit, used to calculate the difference ΔQ between the sum of the input heat reversed by the current load P and the sum of the input heat reversed by the load P' at time T;

[0045] A load increase / decrease judgment unit, which is used to judge the magnitude relationship between P and P'. If P' > P and ΔQ = P' - P, then the start control judgment unit is executed; if P' < P and ΔQ = P - P', then the shutdown control judgment unit is executed.

[0046] The start control judgment unit is used to judge the magnitude relationship between ΔQ and Q max -Q now If ΔQ ≤ Q max -Q now , it means that increasing the coal quantity can meet the load increase and there is no need to start a new coal mill; then skip the start-stop control module and execute the economic coal consumption model establishment module; if ΔQ > Q max -Q now , it means that the number of coal mills currently in operation cannot meet the load increase and a new coal mill needs to be started, then continue to execute the start-stop control module.

[0047] The shutdown control judgment unit is used to judge the magnitude relationship between ΔQ and Q now -Q eco If ΔQ ≤ Q now -Q eco , it means that reducing the coal quantity can meet the load decrease and the coal mill can be kept running at the economic output state, and there is no need to shut down the existing coal mills; then skip the start-stop control module and execute the economic coal consumption model establishment module; if ΔQ > Q now -Q eco , it means that reducing the coal quantity will cause the coal output of some coal mills to drop below the economic output state, resulting in a decrease in the stability of the coal mills, and the economy and safety of the unit are insufficient, and one coal mill needs to be shut down, then continue to execute the start-stop control module.

[0048] The specific execution method of the economic coal consumption model establishment module is as follows:

[0049] Increasing or decreasing the coal quantity of each coal mill has different effects on the wall temperature of the boiler water wall, the wall temperature of the reheater, the superheated steam temperature and pressure, the reheated steam temperature and pressure, the desuperheating water quantity, the nitrogen oxide emission, and the flue gas temperature, and thus affects the economy, safety, and environmental protection indicators of the boiler; the main indicators that affect the economy of the boiler include the superheated steam temperature t 过热 , the reheated steam temperature t 再热 , the superheated steam pressure p 过热 , the reheated steam pressure p 再热 , the superheated desuperheating water quantity m 过热 , the reheated desuperheating water quantity m 再热 , the flue gas temperature t 排烟 . Then, when the coal output of the coal mill increases or decreases, the change amounts of the above parameters are Δt 过热 , Δt 再热, Δp 过热 , Δp 再热 , Δm 过热 , Δm 再热 , Δt 排烟 ;

[0050] The change in the unit economy caused by the unit change of the above parameters is quantified as the impact on the unit power supply coal consumption b. By querying the empirical values ​​of the unit change of the above parameters of different grades of coal-fired units affecting the unit power supply coal consumption, the values ​​of the unit change of the parameters affecting the unit power supply coal consumption are obtained, which are b1, b2, b3, b4, b5, b6, and b7; b1-b7 are positive or negative values ​​according to the parameter characteristics, and the calculation model of the coal consumption change caused by the overall parameter changes after increasing or decreasing the coal volume is Δb as follows:

[0051] Δb=Δt 过热 b1+Δt 再热 b2+Δp 过热 ·b3+Δp 再热 ·b4+Δm 过热 ·b5+Δm 再热 ·b6+Δt 排烟 ·b7(6)

[0052] Wherein, b is the coal consumption for power supply, and the unit of coal consumption for power supply is kg / kwh.

[0053] Based on the frequent changes in actual load in a short period of time in the future under spot electricity trading, the present invention comprehensively considers the actual coal type, coal mill output, unit degradation degree, coal consumption and other data of each coal mill, and combines the corresponding boiler safety indicators and emission environmental protection indicators to perform group control on all coal mills of power station boilers, and accurately control the number of coal mill units started and the output coal of each coal mill. The group control method achieves the following beneficial effects:

[0054] (1) Optimize the start and stop timing of the coal mill unit to avoid equipment wear and tear caused by frequent start and stop and increase the workload of operation and maintenance personnel, improve equipment safety and reliability, and reduce labor costs.

[0055] (2) Optimize the coal output of each coal mill so that it always operates above the economic output state, improve the stability and efficiency of the unit operation, and reduce production costs.

[0056] (3) While adapting to rapidly changing loads and maximizing production efficiency, it also takes into account production safety and the impact of emissions on the environment, conforms to the themes of environmental protection and sustainable development, and has positive social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1This is a flow chart of a group control method for a power station boiler coal mill according to Embodiment 1 of the present invention;

[0058] Figure 2 It is a cross-sectional schematic diagram of the arrangement of a typical power station pulverized coal boiler pulverizing system in Example 1 of the present invention;

[0059] Figure 3 It is a schematic top view of the coal outlet of the F coal mill in the typical power plant pulverized coal boiler pulverizing system layout in Example 1 of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in combination with the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] Example 1

[0062] like Figure 1 As shown, this embodiment is combined with a typical power plant pulverized coal boiler to further illustrate a coal mill group control method adapted to rapid load changes provided by the present invention. The method includes:

[0063] S1. Obtain the maximum output and economic output data of each coal mill when using different types of coal;

[0064] S2. Obtain the actual coal quantity, coal type and corresponding calorific value of each coal mill under the current load P, and the load P' after time T;

[0065] S3, based on the parameters obtained in step S1 and step S2, calculating and establishing a judgment model for start-stop control of the coal mill unit;

[0066] S4, based on the coal mill start and stop control calculation model obtained in step S3, obtaining the timing of controlling the start and stop of the coal mill;

[0067] S5. Quantify the changes of the main indicators that affect the economic efficiency of the boiler as the impact on the coal consumption of the unit power supply, and establish a calculation model for the coal consumption change Δb;

[0068] S6. Based on the calculation model and energy balance formula of the coal consumption change Δb obtained in step S5, and taking into account safety and environmental protection indicators, a model is established using a machine learning algorithm to perform optimization calculations to obtain the most economical coal quantity for each coal mill.

[0069] like Figure 2 and Figure 3As shown, the tangentially fired boiler of this embodiment is equipped with 6 medium-speed coal mills, which are numbered A, B, C, D, E, and F. Due to changes in the coal market and economic efficiency decisions of thermal power plants, there are many types of coal entering the furnace, and the coal types are numbered 1, 2, 3, . . . , n in sequence. In this embodiment, coal mills A, B, C, D, E, and F use coal types 1, 2, 3, 4, 5, and 6, respectively. Due to changes in operating conditions and equipment degradation, the maximum output of each coal mill is m max and economic output eco There are differences.

[0070] The principles for determining the maximum output and economic output of each coal mill refer to DLT469-2019 "Performance Test of Coal Mills and Pulverizing Systems in Power Plants". There are two specific methods. Method 1: Determine through performance tests regularly, with an interval of half a year or one year. Method 2: Obtain historical data of each coal mill, including coal mill differential pressure, coal mill outlet air temperature, coal mill current, coal mill vibration parameters, coal mill power consumption, primary air pressure, primary fan power consumption and other data, and use machine learning algorithm model training and optimization to obtain the current maximum output and economic output of each coal mill.

[0071] In the context of spot trading, based on the power plant's quotation, after the power market is cleared, the grid company sends the power generation unit the grid AGC real-time load curve, which can generally obtain the actual load curve within the T period, and the unit generates electricity according to the load curve. In the context of spot trading, the market is more unpredictable, and T is generally 15-60 minutes. The load after a longer period cannot be accurately predicted.

[0072] The power supply coal consumption b of each unit in the typical load section over a period of time is a fixed value. Based on the principle of conservation of energy, the sum of the heat input to the boiler by all coal mills is equal to the sum of the input heat inferred based on the power supply coal consumption and the power generation.

[0073] m A1 ·q 1 +m B2 ·q 2 +m C3 ·q 3 +m D4 ·q 4 +m E5 ·q 5 +m F6 ·q 6 =Q now (1)

[0074] Where m A1 is the coal quantity of coal mill A under the condition of coal type 1 (kg / h), q 1 is the lower calorific value of No. 1 coal (kJ / kg), Q now is the current total heat input of the boiler (kJ / h), mB2 is the coal quantity of B coal mill under the condition of No. 2 coal (kg / h), q 2 It is the lower calorific value of No. 2 coal (kJ / kg), and so on.

[0075] Assuming that the current unit load is P (kW), and the unit load after time T is P' (kW), then

[0076] b p ·P·Q net =Q now (2)

[0077] Among them, b p Q is the coal consumption for power supply under load P (kW) (kg / kwh). The coal consumption for power supply generally increases as the load of the unit decreases. However, for a fixed load P, this value can be approximately considered as a constant over a long period of time, that is, the coal consumption for power supply under a certain load is a constant. This value is generally determined by regular tests. net The calorific value of standard coal is 29308kJ / kg, which is also a constant.

[0078] Formula (1) and formula (2) are combined to obtain:

[0079] m A1 ·q 1 +m B2 ·q 2 +m C3 ·q 3 +m D4 ·q 4 +m E5 ·q 5 +m F6 ·q 6 =b p ·P·Q net =α P ·P (3)

[0080] Where α P is a constant that only changes with load, then the total heat of each coal mill is proportional to the load.

[0081] In this embodiment, the current unit load is set to P (kW), the unit load after time T is P' (kW), and there are 4 coal mills B, C, D, and E in operation. The coal type of each coal mill is 2, 3, 4, and 5. The coal volume (kg / h) of each coal mill is m B2 、m C3 、m D4 、m E5 The lower calorific value (kJ / kg) of each type of coal is q 2 , 3 4 5

[0082] q, q, q.

[0083] Due to the background of spot trading, the market is more unpredictable. T is generally 15-60 minutes, which is a short time. Based on the regulation characteristics of thermal power units, the load in the short time from the current moment to the moment T generally presents a monotonic function, that is, the load in the T period increases or decreases monotonically.

[0084] When the load increases at time T, that is, P'>P, there are two situations:

[0085] (1) When the following relationship (4) is satisfied

[0086]

[0087] The current four coal mills can meet the load increase by increasing the amount of coal, and there is no need to start a new coal mill. is the maximum output of B coal mill under No. 2 coal type. Similarly, the others are the maximum outputs under the corresponding coal types.

[0088] At this time, the four coal mills increase the coal quantity (kg / h) m according to the load curve at time T. B 、m C 、m D 、m E , based on energy balance, satisfies the following relation (5):

[0089] α P′ ·P′=(m B2 +m B )·q 2 +(m C3 +m C )·q 3 +(m D4 +m D )·q 4 +(m E5 +m E )·q 5 (5)

[0090] Among them, α P’ When the load is P', the corresponding constant is derived from formula (3).

[0091] Due to the change in the heat load of the burner corresponding to different coal mills, that is, the different amount of coal added by each coal mill has different effects on the boiler water-cooled wall temperature, superheater wall temperature, superheated steam temperature and pressure, reheated steam temperature and pressure, desuperheating water volume, nitrogen oxide emissions, and exhaust gas temperature, which in turn affects the boiler's economy, safety, and environmental protection indicators. Among them, the main indicators that affect the boiler's economy include superheated steam temperature t 过热 , reheat steam temperature t 再热 , superheated steam pressure p过热 , reheat steam pressure p 再热 、Superheating and desuperheating water volume m 过热 , Reheating water volume m 再热 , exhaust gas temperature t 排烟 etc., then m B 、m C 、m D 、m E After the increase, the change in each parameter caused is Δt 过热 , Δt 再热 , Δp 过热 , Δp 再热 , Δm 过热 , Δm 再热 , Δt 排烟 .

[0092] The changes in the unit economy caused by the unit changes of the above parameters can be quantified as the impact on the unit's power supply coal consumption. The values ​​of the unit changes of the parameters that affect the unit's power supply coal consumption (kg / kwh) are b1, b2, b3, b4, b5, b6, and b7, respectively. b1-b7 can be positive or negative values ​​according to the parameter characteristics, and different grades of coal-fired units have empirical values ​​that can be queried. The change in coal consumption caused by the overall changes in various parameters after adding coal is Δb.

[0093] Δb=Δt 过热 b1+Δt 再热 b2+Δp 过热 ·b3+Δp 再热 ·b4+Δm 过热 ·b5+Δm 再热 ·b6+Δt 排烟 ·b7(6)

[0094] During the load increase process of the unit, the coal volume of the four coal mills is increased on the basis of satisfying the energy balance of formula (5) while ensuring that the value of the coal consumption change Δb in formula (6) is as small as possible, that is, the economic performance of the unit is the best, while taking into account the water-cooled wall temperature, the superheater wall temperature, and the nitrogen oxides not exceeding the standard. The machine learning algorithm is used to establish a model, perform optimization calculations, and optimize m B 、m C 、m D 、m E The optimal value of can be used to obtain the optimal coal quantity for pulverizers B, C, D, and E.

[0095] (2) When the following relationship (7) is satisfied

[0096]

[0097] If the current 4 coal mills cannot meet the rising load by increasing the coal volume, a new coal mill needs to be started to meet the load requirements of the power grid dispatching. At this time, coal mill A is preferentially started because starting a coal mill requires a warm-up time T 暖磨 , the starting time of the coal mill is T 启动 , the output increase time is T 升出力 , then at time T - T 暖磨 - T 启动 - T 升出力 , coal mill A is started. Assume that coal mill A uses coal type 1, and the lower calorific value (kJ / kg) of the coal type is q 1 . And the output reaches m at time T A1 . At this time, it should satisfy

[0098] α P′ ·P′ = m B2 ·q 2 + m C3 ·q 3 + m D4 ·q 4 + m E5 ·q 5 + m A1 ·q 1 (8)

[0099] On the basis of the 5 coal mills increasing the coal volume to meet the energy balance of formula (8), while ensuring that the value of the coal consumption change Δb in formula (6) is as small as possible, that is, the economic performance of the unit is the best, and at the same time taking into account the wall temperature of the water-cooled wall, the wall temperature of the reheater, and the non-exceedance of nitrogen oxides, a model is established using a machine learning algorithm for optimization calculation to optimize m B2 , m C3 , m D4 , m E5 , m A1 The optimal value of the coal volume, so as to obtain the optimal coal volume of coal mills B, C, D, E, and A.

[0100] When the load rises at time T, that is, P’ < P, there are the following two situations:

[0101] (3) When the following relational formula (9) is satisfied

[0102]

[0103] Then the current 4 coal mills can meet the load drop by reducing the coal volume, and can ensure that the coal volume of several coal mills is maintained above their respective economic outputs, and there is no need to stop the existing coal mills. In the formula

[0104] is the economic output of coal mill B under coal type 2, and the others are similarly known to be the economic outputs under the corresponding coal types. ​

[0105] At this time, the four coal mills reduce the coal quantity (kg / h) m according to the load curve at time T. B 、m C 、m D 、m E , satisfying the following relation (10):

[0106] α P′ ·P′=(m B2 -m B )·q 2 +(m C3 -m C )·q 3 +(m D4 -m D )·q 4 +(m E5 -m E )·q 5 (10)

[0107] Due to the change in the heat load of the burner corresponding to different coal mills, that is, the different coal reduction of each coal mill has different effects on the boiler water-cooled wall temperature, superheater wall temperature, superheated steam temperature and pressure, reheated steam temperature and pressure, desuperheating water volume, nitrogen oxide emissions, and exhaust gas temperature, which in turn affects the boiler's economy, safety, and environmental protection indicators. Among them, the main indicators that affect the boiler's economy include superheated steam temperature t 过热 , reheat steam temperature t 再热 , superheated steam pressure p 过热 , reheat steam pressure p 再热 、Superheating and desuperheating water volume m 过热 , Reheating water volume m 再热 , exhaust gas temperature t 排烟 etc., then m B 、m C 、m D 、m E After the increase, the change in each parameter caused is Δt 过热 , Δt 再热 , Δp 过热 , Δp 再热 , Δm 过热 , Δm 再热 , Δt 排烟 .

[0108] The changes in the unit economy caused by the unit changes of the above parameters can be quantified as the impact on the unit's power supply coal consumption. The values ​​of the unit changes of the parameters that affect the unit's power supply coal consumption (kg / kwh) are b1, b2, b3, b4, b5, b6, and b7, respectively. b1-b7 can be positive or negative values ​​according to the parameter characteristics, and different grades of coal-fired units have empirical values ​​that can be queried. The change in coal consumption caused by the overall changes in various parameters after adding coal is Δb.

[0109] Δb=Δt 过热 b1+Δt 再热 b2+Δp 过热 ·b3+Δp 再热 ·b4+Δm 过热 ·b5+Δm 再热 ·b6+Δt 排烟 ·b7(6)

[0110] During the load reduction process of the unit, the coal volume of the four coal mills is increased on the basis of satisfying the energy balance of formula (10), while ensuring that the value of the coal consumption change Δb in formula (6) is as small as possible, that is, the economic performance of the unit is the best, while taking into account the water-cooled wall temperature, the superheater wall temperature, and the nitrogen oxides not exceeding the standard. The machine learning algorithm is used to establish a model, perform optimization calculations, and optimize m B 、m C 、m D 、m E The optimal value of can be used to obtain the optimal coal quantity for pulverizers B, C, D, and E.

[0111] (4) When the following relationship (11) is satisfied

[0112]

[0113] The current four coal mills cannot meet the load reduction by reducing the coal volume. The coal volume of some coal mills needs to be reduced to below the economic output, resulting in reduced stability of the coal mills, insufficient economic efficiency and safety of the unit. It is necessary to shut down one of the coal mills to meet the load required by the grid dispatch. At this time, the E coal mill should be shut down first, because the shutdown coal mill needs to reduce the output time T 降出力 , shutdown time of coal mill T 停运 , then in TT 停运 -T 降出力 Always be prepared to shut down the E coal mill.

[0114] This should satisfy

[0115] α P′ P′=m B2 ·q 2 +m C3 ·q 3 +m D4 ·q 4 (12)

[0116] The increase in coal volume of the three coal mills satisfies the energy balance of formula (12) and ensures that the value of the coal consumption change Δb in formula (6) is as small as possible, that is, the economic performance of the unit is the best. At the same time, the water-cooled wall temperature, the superheater wall temperature, and the nitrogen oxides do not exceed the standard. The machine learning algorithm is used to establish a model, perform optimization calculations, and optimize mB2 、m C3 、m D4 The optimal value of coal quantity is obtained, thereby obtaining the optimal coal quantity for pulverizers B, C, and D.

[0117] Example 2

[0118] It should be further explained that, based on the same inventive concept, the present invention also provides a group control system for a power plant boiler coal mill, and when the system is running, the method described in Example 1 is executed, including:

[0119] The parameter acquisition module is used to obtain the maximum output and economic output data of each coal mill when using different types of coal.

[0120] The working condition acquisition module is used to obtain the actual coal quantity, coal type and corresponding calorific value of each coal mill under the current load P, and the load P' after time T.

[0121] The start-stop judgment model establishment module is used to calculate and establish a judgment model for the start-stop control of the coal mill unit based on the parameters obtained by the parameter acquisition module and the operating condition acquisition module.

[0122] The start-stop control module is used to determine the start-stop control calculation model of the coal mill unit obtained by the start-stop judgment model establishment module, and obtain the timing of controlling the start-stop of the coal mill unit.

[0123] The economic coal consumption model establishment module is used to quantify the changes in the main indicators that affect the boiler economy as the impact on the unit's power supply coal consumption, and establish a calculation model for the coal consumption change Δb.

[0124] The coal quantity control module is used to establish a calculation model for the coal consumption change Δb obtained by the economic coal consumption model establishment module, and the energy balance formula, while taking into account safety and environmental protection indicators. It uses a machine learning algorithm to establish a model and perform optimization calculations to obtain the most economical coal quantity for each coal mill.

[0125] There are two ways for the parameter acquisition module to collect parameters, specifically:

[0126] (1) Regularly obtain the maximum output and economic output data of each coal mill through performance tests;

[0127] (2) By obtaining the historical data of each coal mill, including at least the coal mill differential pressure, coal mill outlet air temperature, coal mill current, coal mill vibration parameters, coal mill power consumption, primary air pressure, and primary fan power consumption; using machine learning algorithm model training and optimization to obtain the current maximum output and economic output data of each coal mill.

[0128] The start-stop judgment model building module includes the following units:

[0129] A heat calculation unit for calculating the sum Q of the heat input to the boiler by all the operating coal mills under the current load P now , the sum Q of the heat that can be input to the boiler when all the operating coal mills are at maximum output max and the sum Q of the heat that can be input to the boiler when all the operating coal mills are at economic output eco ;

[0130] A load calculation unit for calculating the difference ΔQ between the sum of the input heat deduced from the current load P and the sum of the input heat deduced from the load P' at time T;

[0131] A load increase / decrease judgment unit for judging the magnitude relationship between P and P'. If P'>P and ΔQ = P'-P, then execute the start control judgment unit; if P'<P and ΔQ = P - P', then execute the shutdown control judgment unit;

[0132] A start control judgment unit for judging the magnitude relationship between ΔQ and Q max -Q now . If ΔQ≤Q max -Q now , it means that the load increase can be met by increasing the coal quantity and there is no need to start a new coal mill; then skip the start / stop control module and execute the economic coal consumption model establishment module; if ΔQ>Q max -Q now , it means that the number of currently operating coal mills cannot meet the load increase and a new coal mill needs to be started, then continue to execute the start / stop control module;

[0133] A shutdown control judgment unit for judging the magnitude relationship between ΔQ and Q now -Q eco . If ΔQ≤Q now -Q eco , it means that the load decrease can be met by reducing the coal quantity and the coal mills can be kept operating at economic output, and there is no need to shut down the existing coal mills; then skip the start / stop control module and execute the economic coal consumption model establishment module; if ΔQ>Q now -Q eco , it means that reducing the coal quantity will cause the coal output of some coal mills to drop below the economic output state, resulting in a decrease in the stability of the coal mills, and the economy and safety of the unit are insufficient, and one coal mill needs to be shut down, then continue to execute the start / stop control module.

[0134] The specific execution method of the economic coal consumption model establishment module is as follows:

[0135] The different increase or decrease of coal volume in each pulverizer has different effects on the boiler water-cooled wall temperature, superheater wall temperature, superheated steam temperature and pressure, reheated steam temperature and pressure, desuperheating water volume, nitrogen oxide emissions, and exhaust gas temperature, which in turn affects the boiler's economy, safety, and environmental protection indicators. The main indicators that affect the boiler's economy include superheated steam temperature t 过热 , reheat steam temperature t 再热 , superheated steam pressure p 过热 , reheat steam pressure p 再热 、Superheating and desuperheating water volume m 过热 , Reheating water volume m 再热 , exhaust gas temperature t 排烟 , when the coal output of the pulverizer increases or decreases, the change in the above parameters is Δt 过热 , Δt 再热 , Δp 过热 , Δp 再热 , Δm 过热 , Δm 再热 , Δt 排烟 ;

[0136] The change in the unit economy caused by the unit change of the above parameters is quantified as the impact on the unit power supply coal consumption b. By querying the empirical values ​​of the unit change of the above parameters of different grades of coal-fired units affecting the unit power supply coal consumption, the values ​​of the unit change of the parameters affecting the unit power supply coal consumption are obtained, which are b1, b2, b3, b4, b5, b6, and b7; b1-b7 are positive or negative values ​​according to the parameter characteristics, and the calculation model of the coal consumption change caused by the overall parameter changes after increasing or decreasing the coal volume is Δb as follows:

[0137] Δb=Δt 过热 b1+Δt 再热 b2+Δp 过热 ·b3+Δp 再热 ·b4+Δm 过热 ·b5+Δm 再热 ·b6+Δt 排烟 ·b7(6)

[0138] Wherein, b is the coal consumption for power supply, and the unit of coal consumption for power supply is kg / kwh.

[0139] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A coal mill group control method adapting to rapid load changes, characterized in that: The method includes the following steps: S1. Obtain the maximum output and economic output data of each coal mill when using different coal types; S2. Obtain the actual coal quantity, coal type and corresponding calorific value of each coal mill under the current load P, and the load P' after time T; S3. Based on the parameters obtained in steps S1 and S2, calculate and establish a judgment model for the start-stop control of the coal grinding unit; S4. Based on the judgment model for calculating the start-stop control of the coal grinding unit obtained in step S3, obtain the timing for controlling the start and stop of the coal grinding unit; S5. Quantify the changes in the main indicators affecting the boiler economy into the impact on the unit's power supply coal consumption, and establish a calculation model for the coal consumption change Δb; S6. Based on the calculation model for the coal consumption change Δb obtained in step S5 and the energy balance formula, and taking into account the safety and environmental protection indicators, use a machine learning algorithm to establish a model and perform optimization calculations to obtain the most economic coal quantity for each coal mill.

2. A coal mill group control method adapting to rapid load changes according to claim 1, characterized in that: There are two ways to obtain the maximum output and economic output data described in step S1, specifically: (1) Regularly obtain the maximum output and economic output data of each coal mill through performance tests; (2) By obtaining the historical data of each coal mill, including at least the differential pressure of the coal mill, the outlet air temperature of the coal mill, the current of the coal mill, the vibration parameters of the coal mill, the power consumption of the coal mill, the primary air pressure, and the power consumption of the primary air fan; use a machine learning algorithm model for training and optimization to obtain the maximum output and economic output data of each coal mill at present.

3. A coal mill group control method adapting to rapid load changes according to claim 1, characterized in that: Step S3 includes the following steps: S31. Calculate the sum of heat Q input to the boiler from all coal mills in operation under the current load P now , the sum of the heat that can be input into the boiler when all coal mills are running at maximum output Q max And the sum of the heat that can be input into the boiler when all coal mills are operating at economic output Q eco ; S32. Calculate the difference ΔQ between the sum of the input heat deduced from the current load P and the sum of the input heat deduced from the load P' at time T; S33. Judge the magnitude relationship between P and P'. If P' > P and ΔQ = P' - P, then execute step S34; if P' < P and ΔQ = P - P', then execute step S35; S34. Determine ΔQ and Q max -Q now If ΔQ≤Q max -Q now , it means that the load increase can be met by increasing the amount of coal, and there is no need to start a new coal mill; then skip step S4 and execute step S5; if ΔQ>Q max -Q now , it means that the number of coal mills currently in operation can no longer meet the load increase, and a new coal mill needs to be started, and then continue to execute step S4; S35. Determine ΔQ and Q now -Q eco If ΔQ≤Q now -Q eco , it means that the load reduction can be met by reducing the amount of coal, and the coal mill can be kept running at an economic output state, and there is no need to shut down the existing coal mill; then skip step S4 and execute step S5; if ΔQ>Q now -Q eco , it means that by reducing the amount of coal, the coal output of some coal mills needs to be reduced to below the economic output state, resulting in reduced stability of the coal mills, insufficient economy and safety of the unit, and a coal mill needs to be shut down, then continue to execute step S4.

4. A coal mill group control method adapting to rapid load changes according to claim 1, characterized in that: Step S4 is specifically: When P'>P, the time point T for starting a new coal mill is 开启 =TT 暖磨 -T 启动 -T 升出力 ; When P’ < P, the time point T for shutting down an existing coal mill 关闭 = T - T 停运 - T 降出力 ; Among them, T 暖磨 The time required to warm up the coal mill to start up is T 启动 is the time required for coal mill startup, T 升出力 is the time required for the coal mill to increase its output, T 停运 is the time required for the coal mill to stop operating, T 降出力 The time required for the coal mill to reduce its output.

5. A coal mill group control method adapting to rapid load changes according to claim 1, characterized in that: Step S5 is specifically: The different increase or decrease of coal volume in each pulverizer has different effects on the boiler water-cooled wall temperature, superheater wall temperature, superheated steam temperature and pressure, reheated steam temperature and pressure, desuperheating water volume, nitrogen oxide emissions, and exhaust gas temperature, which in turn affects the boiler's economy, safety, and environmental protection indicators. The main indicators that affect the boiler's economy include superheated steam temperature t 过热 , reheat steam temperature t 再热 , superheated steam pressure p 过热 , reheat steam pressure p 再热 、Superheating and desuperheating water volume m 过热 , Reheating water volume m 再热 , exhaust gas temperature t 排烟 , when the coal output of the pulverizer increases or decreases, the change in the above parameters is Δt 过热 , Δt 再热 , Δp 过热 , Δp 再热 , Δm 过热 , Δm 再热 , Δt 排烟 ; Quantify the changes in the economy of the unit caused by the unit change of each of the above parameters into the impact on the unit's power supply coal consumption b. Obtain the values of the impact of the unit change of these parameters on the unit's power supply coal consumption, which are b1, b2, b3, b4, b5, b6, and b7, by querying the empirical values of the impact of the unit change of the above parameters of different grades of coal-fired units on the unit's power supply coal consumption; b1 - b7 are positive or negative according to the parameter characteristics, then the calculation model for the coal consumption change Δb caused by the overall change of each parameter after increasing or decreasing the coal quantity is as follows: Δb=Δt 过热 ·b1+Δt 再热 ·b2+Δp 过热 ·b3+Δp 再热 ·b4+Δm 过热 ·b5+Δm 再热 ·b6+Δt 排烟 ·b7(6) Among them, b is the power supply coal consumption, and the unit of the power supply coal consumption is kg / kwh.

6. A coal mill group control method adapting to rapid load changes according to claim 1, characterized in that: The consideration of the safety and environmental protection indicators in step S5 includes: the wall temperature of the water wall, the wall temperature of the superheater and reheater, and the nitrogen oxide index.

7. A coal mill group control system adapting to rapid load changes, characterized in that: The system includes: A parameter acquisition module for obtaining the maximum output and economic output data of each coal mill when using different coal types; A working condition acquisition module for obtaining the actual coal quantity, coal type and corresponding calorific value of each coal mill under the current load P, and the load P' after time T; A start-stop judgment model establishment module for calculating and establishing a judgment model for the start-stop control of the coal grinding unit based on the parameters obtained by the parameter acquisition module and the working condition acquisition module; The start-stop control module is used to start and stop the judgment coal mill unit start-stop control calculation model obtained by the start-stop judgment model establishment module, and obtain the timing for controlling the start and stop of the coal mill unit. The economic coal consumption model establishment module is used to quantify the changes in the main indicators affecting the boiler economy into the impact on the unit's power supply coal consumption, and establish a calculation model for the coal consumption change Δb. The coal quantity control module is used to establish a model based on the calculation model of the coal consumption change Δb obtained by the economic coal consumption model establishment module and the energy balance formula, taking into account safety and environmental protection indicators, and using machine learning algorithms to perform optimization calculations to obtain the most economic coal quantity for each coal mill.

8. A coal mill group control system adapting to rapid load changes according to claim 7, characterized in that: There are two ways for the parameter acquisition module to acquire parameters, specifically: (1) Regularly obtain the maximum output and economic output data of each coal mill through performance tests. (2) By obtaining the historical data of each coal mill, including at least the differential pressure of the coal mill, the outlet air temperature of the coal mill, the current of the coal mill, the vibration parameters of the coal mill, the power consumption of the coal mill, the primary air pressure, and the power consumption of the primary air fan; use the machine learning algorithm model to train and optimize to obtain the maximum output and economic output data of each coal mill at present.

9. A coal mill group control system adapting to rapid load changes according to claim 7, characterized in that: The start-stop judgment model establishment module includes the following units: Heat calculation unit, used to calculate the sum of heat Q input to the boiler from all running coal mills under the current load P now , the sum of the heat that can be input into the boiler when all coal mills are running at maximum output Q max And the sum of the heat that can be input into the boiler when all coal mills are operating at economic output Q eco ; The load calculation unit is used to calculate the difference ΔQ between the sum of the input heat inferred from the current load P and the sum of the input heat inferred from the load P' at time T. The load increase and decrease judgment unit is used to judge the magnitude relationship between P and P'. If P'>P and ΔQ = P'-P, then execute the start control judgment unit; if P'<P and ΔQ = P-P', then execute the shutdown control judgment unit. Start control judgment unit, used to judge ΔQ and Q max -Q now If ΔQ≤Q max -Q now , it means that the load increase can be met by increasing the amount of coal, and there is no need to start a new coal mill; the start-stop control module is skipped and the economic coal consumption model establishment module is executed; if ΔQ>Q max -Q now , it means that the number of coal mills currently in operation can no longer meet the load increase, and new coal mills need to be started, so the start-stop control module continues to be executed; The shutdown control judgment unit is used to judge ΔQ and Q now -Q eco If ΔQ≤Q now -Q eco , it means that the load reduction can be met by reducing the amount of coal, and the coal mill can be kept running at an economic output state, and there is no need to shut down the existing coal mill; the start-stop control module is skipped and the economic coal consumption model establishment module is executed; if ΔQ>Q now -Q eco , it means that by reducing the amount of coal, the coal output of some coal mills needs to be reduced to below the economic output state, resulting in a decrease in the stability of the coal mills, insufficient economy and safety of the unit, and a coal mill needs to be shut down, so the start-stop control module will continue to be executed.

10. A coal mill group control system adapting to rapid load changes according to claim 7, characterized in that: The specific execution method of the economic coal consumption model establishment module is as follows: The different increase or decrease of coal volume in each pulverizer has different effects on the boiler water-cooled wall temperature, superheater wall temperature, superheated steam temperature and pressure, reheated steam temperature and pressure, desuperheating water volume, nitrogen oxide emissions, and exhaust gas temperature, which in turn affects the boiler's economy, safety, and environmental protection indicators. The main indicators that affect the boiler's economy include superheated steam temperature t 过热 , reheat steam temperature t 再热 , superheated steam pressure p 过热 , reheat steam pressure p 再热 、Superheating and desuperheating water volume m 过热 , Reheating water volume m 再热 , exhaust gas temperature t 排烟 , when the coal output of the pulverizer increases or decreases, the change in the above parameters is Δt 过热 , Δt 再热 , Δp 过热 , Δp 再热 , Δm 过热 , Δm 再热 , Δt 排烟 ; Quantify the changes in the economy of the unit caused by the unit change of each of the above parameters into the impact on the unit's power supply coal consumption b. Obtain the values of the impact of the unit change of these parameters on the unit's power supply coal consumption as b1, b2, b3, b4, b5, b6, b7 respectively by querying the empirical values of the impact of the unit change of the above parameters on the unit's power supply coal consumption for different grades of coal-fired units; b1-b7 are positive or negative according to the parameter characteristics, then the calculation model for the coal consumption change Δb caused by the overall change of each parameter after increasing or decreasing the coal quantity is as follows: Δb=Δt 过热 ·b1+Δt 再热 ·b2+Δp 过热 ·b3+Δp 再热 ·b4+Δm 过热 ·b5+Δm 再热 ·b6+Δt 排烟 ·b7(6) Among them, b is the power supply coal consumption, and the unit of the power supply coal consumption is kg / kwh.

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