Power distribution methods, devices, and pulverizing systems in coal-fired power plants

Abstract

This invention provides a method, apparatus, and pulverizing system for power output allocation in a coal-fired power plant pulverizing system, belonging to the field of coal-fired unit pulverizing technology. The method for power output allocation in a coal-fired power plant pulverizing system includes: obtaining the pulverizing unit consumption characteristics of each coal mill in the thermal power unit, multiple objective functions for power output allocation in the pulverizing system, and multiple constraints for power output allocation in the pulverizing system; constructing a multi-objective optimization model based on the pulverizing unit consumption characteristics of each coal mill, the multiple objective functions for power output allocation in the pulverizing system, and the multiple constraints for power output allocation in the pulverizing system; solving for the optimal value of the objective function in the multi-objective optimization model under multiple constraints to obtain a set of power output allocation strategies for the pulverizing system; wherein the set of power output allocation strategies for the pulverizing system includes multiple power output allocation strategies for the pulverizing system; obtaining the optimal power output allocation strategy for the pulverizing system from the set of power output allocation strategies for the pulverizing system; and controlling the output of the coal mills according to the optimal power output allocation strategy for the pulverizing system.

Description

Technical Field

[0001] This invention relates to the field of coal-fired power plant pulverizing technology, specifically to a method for distributing the output of a coal-fired power plant pulverizing system, a device for distributing the output of a coal-fired power plant pulverizing system, and a coal-fired power plant pulverizing system. Background Technology

[0002] The pulverizing system is an important auxiliary system for coal-fired power units. Its function is to grind qualified pulverized coal to ensure the combustion needs of the boiler.

[0003] Currently, existing technologies establish multi-objective optimization models based on multiple objective functions, and obtain the output allocation strategy of the pulverizing system by solving these models. However, existing technologies have two problems: First, because the pulverizing consumption characteristics of each coal mill are different, they cannot adapt to the output allocation of coal mills under different characteristics, which can easily lead to problems such as increased plant power consumption, unstable combustion conditions, increased energy loss, and pollutant emissions. Second, traditional mathematical programming methods for solving multi-objective optimization problems mostly adopt weighted methods, which obtain the Pareto front of the multi-objective optimization by adjusting the weights of various indicators, and then make decisions. This method itself is prone to generating local optima and may cause difficulties in solving the problem. Summary of the Invention

[0004] The purpose of this invention is to provide a method, apparatus, and pulverizing system for distributing output in a coal-fired power plant pulverizing system, so as to at least solve the above-mentioned problems.

[0005] To achieve the above objectives, a first aspect of the present invention provides a method for output distribution in a pulverizing system of a coal-fired power plant, the method comprising:

[0006] The unit consumption characteristics of each coal mill in a thermal power unit, multiple objective functions of the output allocation of the pulverizing system, and multiple constraints of the output allocation of the pulverizing system are obtained.

[0007] A multi-objective optimization model is constructed based on the pulverizing unit consumption characteristics of each coal mill, multiple objective functions of the pulverizing system output allocation, and multiple constraints of the pulverizing system output allocation.

[0008] The optimal value of the objective function in the multi-objective optimization model is obtained by solving under multiple constraints, thereby obtaining a set of power allocation strategies for the pulverizing system; wherein, the set of power allocation strategies for the pulverizing system includes multiple power allocation strategies for the pulverizing system.

[0009] Obtain the optimal power allocation strategy for the pulverizing system from the set of power allocation strategies for the pulverizing system;

[0010] The output of the coal mill is controlled according to the optimal power distribution strategy of the pulverizing system.

[0011] In this embodiment of the invention, obtaining the pulverizing unit consumption characteristics of each coal mill in a thermal power unit includes:

[0012] Obtain historical operating data and historical output allocation strategies for each coal mill;

[0013] Based on the historical operating data and historical power allocation strategy, the relationship between coal feed and power consumption of each coal mill is analyzed to obtain the pulverizing unit consumption characteristics of each coal mill.

[0014] In this embodiment of the invention, solving for the optimal value of the objective function in the multi-objective optimization model under multiple constraints includes:

[0015] The ε-constraint method is used to determine one of the multiple objective functions in the multi-objective optimization model as the reference objective function, and to convert the other objective functions into constraint conditions with an upper limit of ε.

[0016] Adjust the value of ε and calculate the optimal value of the reference objective function for different values ​​of ε.

[0017] In this embodiment of the invention, the multiple objective functions for the output allocation of the pulverizing system include a minimum power consumption objective function and a minimum start-up and shutdown cost objective function; wherein:

[0018] The objective function for minimizing power consumption is:

[0019] ;

[0020] The objective function for minimizing start-up and shutdown costs is:

[0021] ;

[0022] in, The objective function is to minimize power consumption. The objective function is to minimize start-up and shutdown costs. For the first The power consumption of a coal mill. For the first The coal feed rate of the coal mill. For time sets, For the first Start-up cost of a coal mill For the first The downtime cost of a coal mill. For the first Taiwan coal mill The device's current startup status. For the first Taiwan coal mill The system is in a constant state of shutdown.

[0023] In this embodiment of the invention, the multiple constraints on the output distribution of the pulverizing system include equality constraints, upper and lower limit constraints, start-stop constraints, and ramping constraints; wherein:

[0024] The equality constraints are:

[0025] ;

[0026] The upper and lower limit constraints are:

[0027] ;

[0028] The start / stop constraints are:

[0029] when hour, ;

[0030] The climbing constraint is:

[0031] ;

[0032] in, For the first The coal feed rate of the coal mill. This is the coal feed instruction for the coal mill. This represents the lower limit of the coal mill's pulverizing output. This is the upper limit of the coal mill's pulverizing output. For the first The power consumption of a coal mill. This represents the lower limit of the coal mill's pulverizing output ramp-up. To increase the maximum output of the coal mill, For the first Taiwan coal mill Coal feed rate at any given time For the first Taiwan coal mill The amount of coal fed at any given time.

[0033] In this embodiment of the invention, the multi-objective optimization model constructed based on the pulverizing unit consumption characteristics of each coal mill, multiple objective functions of the pulverizing system output allocation, and multiple constraints of the pulverizing system output allocation is specifically as follows:

[0034] ;

[0035] in, The objective function is to minimize power consumption. The objective function is to minimize start-up and shutdown costs. These are equality constraints. These are inequality constraints.

[0036] In this embodiment of the invention, the ε-constraint method is used to determine one of the multiple objective functions in the multi-objective optimization model as the reference objective function, and the other objective functions are converted into constraints with an upper limit of ε. The converted model is as follows:

[0037] ;

[0038] The strategy for choosing the value of ε is:

[0039] ;

[0040] in, The objective function is to minimize power consumption. The objective function is to minimize start-up and shutdown costs. These are equality constraints. These are inequality constraints. This is the upper bound of the objective function that minimizes start-up and shutdown costs. To determine the number of solutions, This is the maximum number of solutions set. Let the minimum value of the objective function for minimizing start-up and shutdown costs be found. This represents the maximum value of the objective function that minimizes start-up and shutdown costs.

[0041] In this embodiment of the invention, obtaining the optimal power allocation strategy for the pulverizing system from the set of power allocation strategies for the pulverizing system includes:

[0042] The power allocation strategy that maximizes the objective function in the set of power allocation strategies for the pulverizing system is identified as a non-ideal power allocation strategy for the pulverizing system; the power allocation strategy that minimizes the objective function in the set of power allocation strategies for the pulverizing system is identified as a rational power allocation strategy for the pulverizing system.

[0043] Calculate the distance between each power allocation strategy of the pulverizing system and the power allocation strategy of the non-ideal pulverizing system, and the distance between each power allocation strategy of the pulverizing system and the power allocation strategy of the ideal pulverizing system, respectively.

[0044] Multiple evaluation values ​​are calculated based on the distance between the output allocation strategies of each pulverizing system and the non-ideal pulverizing system output allocation strategies, as well as the distance between the output allocation strategies of each pulverizing system and the ideal pulverizing system output allocation strategies. The pulverizing system output allocation strategy with the largest evaluation value is selected as the optimal pulverizing system output allocation strategy.

[0045] In this embodiment, the optimal power allocation strategy for the pulverizing system is obtained from the set of power allocation strategies using the superior-inferior solution distance method. The superior-inferior solution distance method is a ranking method that approximates the ideal solution. It ranks the evaluation objects by detecting the distance between the evaluation objects and the optimal and worst solutions. If the evaluation object is closest to the optimal solution and furthest from the worst solution, it is the best; otherwise, it is not the best.

[0046] In this embodiment of the invention, the distance between the output allocation strategy of the pulverizing system and the output allocation strategy of the non-ideal pulverizing system is calculated as follows:

[0047] ;

[0048] The distance between the output allocation strategy of the pulverizing system and the ideal output allocation strategy of the pulverizing system is calculated as follows:

[0049]

[0050] The formula for calculating the evaluation value is:

[0051] ;

[0052] in, For the first Calculation of the distance between the output allocation strategy of an ideal pulverizing system and the output allocation strategy of a non-ideal pulverizing system. For the first The distance between the output allocation strategy of the individual pulverizing system and the ideal output allocation strategy of the pulverizing system. j For the first j One objective function, Power allocation strategy for the pulverizing system For non-ideal pulverizing systems, the power allocation strategy A power allocation strategy for an ideal milling system. For the first Evaluation value of the output allocation strategy of a powder-making system.

[0053] A second aspect of the present invention provides a power distribution device for a pulverizing system in a coal-fired power plant, comprising:

[0054] The parameter acquisition unit is used to acquire the pulverizing unit consumption characteristics of each coal mill in the thermal power unit, multiple objective functions of the pulverizing system output allocation, and multiple constraints of the pulverizing system output allocation.

[0055] The multi-objective optimization model construction unit is used to construct a multi-objective optimization model based on the pulverizing unit consumption characteristics of each coal mill, multiple objective functions of the pulverizing system output allocation, and multiple constraints of the pulverizing system output allocation.

[0056] The solving unit is used to solve for the optimal value of the objective function in the multi-objective optimization model under multiple constraints, and obtain a set of power allocation strategies for the pulverizing system; wherein, the set of power allocation strategies for the pulverizing system includes multiple power allocation strategies for the pulverizing system.

[0057] The optimal power allocation strategy acquisition unit for the pulverizing system is used to acquire the optimal power allocation strategy for the pulverizing system from the set of power allocation strategies for the pulverizing system.

[0058] The control unit is used to control the output of the coal mill according to the optimal power distribution strategy of the pulverizing system.

[0059] A third aspect of the present invention provides a coal-fired power plant pulverizing system, comprising: an output distribution device, a coal feeder, and a coal mill, wherein the output distribution device is connected to the coal feeder and the coal mill respectively, and is used to obtain the coal feed rate of the coal mill through the coal feeder and the power consumption of the coal mill through the coal mill; the output distribution device is the output distribution device of the coal-fired power plant pulverizing system as described above.

[0060] This invention establishes a multi-objective optimization model based on the pulverizing unit consumption characteristics of coal mills, enabling the allocation of power output at coal mills with different characteristics, resulting in a more accurate allocation method. By solving the multi-objective optimization model using the ε-constraint method, which converts redundant objective functions into constraints, the Pareto optimality of power output allocation for multiple coal mills can be obtained, significantly reducing the energy consumption of coal mills.

[0061] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0062] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0063] Figure 1 This is a flowchart of a method for distributing the output of a coal-fired power plant pulverizing system according to one embodiment of the present invention;

[0064] Figure 2 This is a structural block diagram of an output distribution device for a coal-fired power plant pulverizing system according to one embodiment of the present invention;

[0065] Figure 3 This is a structural block diagram of a coal-fired power plant pulverizing system provided in one embodiment of the present invention.

[0066] Explanation of reference numerals in the attached figures

[0067] 1-Boiler furnace, 2-Air preheater, 3-Blower, 4-Coal feeder, 5-Coal mill, 6-Coarse powder separator, 7-Primary air fan, 8-Sealing fan, 9-Burner. Detailed Implementation

[0068] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0069] As described in the background section, in existing technologies, a multi-objective optimization model is established based on multiple objective functions, and the output allocation strategy of the pulverizing system is obtained by solving the multi-objective optimization model. However, existing technologies have two problems: First, because the pulverizing consumption characteristics of each coal mill are different, they cannot adapt to the output allocation of coal mills under different characteristics, which easily leads to problems such as increased plant power consumption, unstable combustion conditions, increased energy loss, and pollutant emissions; Second, traditional mathematical programming methods for solving multi-objective optimization mostly adopt weighted methods, which obtain the Pareto front of multi-objective optimization by adjusting the weights of various indicators, and then make decisions. This method itself has the problem of easily generating local optima and potentially being difficult to solve.

[0070] This invention provides a method for power allocation in a pulverizing system of a coal-fired power plant. The method includes: acquiring the pulverizing unit consumption characteristics of each coal mill in the thermal power unit, multiple objective functions for power allocation in the pulverizing system, and multiple constraints for power allocation in the pulverizing system; constructing a multi-objective optimization model based on the pulverizing unit consumption characteristics of each coal mill, the multiple objective functions for power allocation in the pulverizing system, and the multiple constraints for power allocation in the pulverizing system; solving for the optimal value of the objective function in the multi-objective optimization model under multiple constraints to obtain a set of power allocation strategies for the pulverizing system; wherein the set of power allocation strategies for the pulverizing system includes multiple power allocation strategies for the pulverizing system; obtaining the optimal power allocation strategy for the pulverizing system from the set of power allocation strategies for the pulverizing system; and controlling the output of the coal mills according to the optimal power allocation strategy for the pulverizing system. This invention establishes a multi-objective optimization model based on the pulverizing unit consumption characteristics of coal mills, which can allocate the output of coal mills under different characteristics, and the allocation method is more accurate. The redundant objective functions are converted into constraints to deal with them. By solving the established multi-objective programming, the Pareto optimality of the output allocation of multiple coal mills can be obtained, which greatly reduces the energy consumption of coal mills.

[0071] Figure 1 This is a flowchart illustrating a method for distributing the output of a pulverizing system in a coal-fired power plant, according to one embodiment of the present invention. Figure 1 As shown, an embodiment of the present invention provides a method for power output distribution in a coal-fired power plant pulverizing system, the method comprising:

[0072] S1. Obtain the pulverizing unit consumption characteristics of each coal mill in the thermal power unit, multiple objective functions of the pulverizing system output allocation, and multiple constraints of the pulverizing system output allocation.

[0073] S2. Construct a multi-objective optimization model based on the pulverizing unit consumption characteristics of each coal mill, multiple objective functions of the pulverizing system output allocation, and multiple constraints of the pulverizing system output allocation;

[0074] S3. Solve for the optimal value of the objective function in the multi-objective optimization model under multiple constraints to obtain a set of power allocation strategies for the pulverizing system; wherein, the set of power allocation strategies for the pulverizing system includes multiple power allocation strategies for the pulverizing system;

[0075] S4. Obtain the optimal power allocation strategy for the pulverizing system from the set of power allocation strategies for the pulverizing system.

[0076] S5. Control the output of the coal mill according to the optimal power distribution strategy of the pulverizing system.

[0077] In step S1 above, obtaining the pulverizing unit consumption characteristics of each coal mill in the thermal power unit includes: acquiring historical operating data and historical output allocation strategies for each coal mill; analyzing the relationship between coal feed and power consumption for each coal mill based on the historical operating data and historical output allocation strategies to obtain the pulverizing unit consumption characteristics of each coal mill. Specifically, historical operating data for each coal mill is acquired from the DCS (Distributed Control System), and the output allocation method of each coal mill under different unit loads is obtained to determine the historical output allocation strategy under the original control logic. Correlation analysis is used to perform characteristic analysis on each coal mill to determine the pulverizing unit consumption characteristics of each coal mill under the control of coal feed and drying output regulation.

[0078] Furthermore, the relationship between power consumption and coal feed rate in a pulverizing system is complex and difficult to calculate based on the system's mechanism. It can only be analyzed using historical data from the field. Many factors influence power consumption, including the matching of operating parameters and the start-up and shutdown of the coal mills, indirectly affecting the system's power consumption. This invention expresses the power consumption characteristics of each coal mill using the following formula:

[0079] ;in The power consumption for coal grinding is expressed in KW. This is the coal feed instruction for the coal mill, in units of... .

[0080] Based on historical data on the pulverizing power consumption and coal feed rate of each coal mill, the determined functional form is a quadratic equation in one variable, as shown below:

[0081] ;in, For the first Electricity consumption of a coal mill in Taiwan, in KW; For the first Coal feed instructions for the coal mill, in units of ; All are coefficients of a quadratic function.

[0082] In step S1 above, the multiple objective functions for the output allocation of the pulverizing system include a minimum power consumption objective function and a minimum start-up and shutdown cost objective function; wherein:

[0083] The objective function for minimizing power consumption is:

[0084] ;

[0085] The objective function for minimizing start-up and shutdown costs is:

[0086] ;

[0087] in, The objective function is to minimize power consumption. The objective function is to minimize start-up and shutdown costs. For the first The power consumption of a coal mill. For the first The coal feed rate of the coal mill. For time sets, For the first Start-up cost of a coal mill For the first The downtime cost of a coal mill. For the first Taiwan coal mill The device's current startup status. For the first Taiwan coal mill The system is in a constant state of shutdown.

[0088] In this embodiment, .

[0089] In step S1 above, the multiple constraints on the output distribution of the pulverizing system include equality constraints, upper and lower limit constraints, start-stop constraints, and ramping constraints; wherein:

[0090] The equality constraints are:

[0091] ;

[0092] The upper and lower limit constraints are:

[0093] ;

[0094] The start / stop constraints are:

[0095] when hour, ;

[0096] The climbing constraint is:

[0097] ;

[0098] in, For the first The coal feed rate of the coal mill. This is the coal feed instruction for the coal mill. This represents the lower limit of the coal mill's pulverizing output. This is the upper limit of the coal mill's pulverizing output. For the first The power consumption of a coal mill. This represents the lower limit of the coal mill's pulverizing output ramp-up. To increase the maximum output of the coal mill, For the first Taiwan coal mill Coal feed rate at any given time For the first Taiwan coal mill The amount of coal fed at any given time.

[0099] In step S2 above, the multi-objective optimization model constructed based on the pulverizing unit consumption characteristics of each coal mill, multiple objective functions for the output allocation of the pulverizing system, and multiple constraints for the output allocation of the pulverizing system is specifically described as follows:

[0100] ;

[0101] in, The objective function is to minimize power consumption. The objective function is to minimize start-up and shutdown costs. These are equality constraints. These are inequality constraints.

[0102] In step S3 above, solving for the optimal value of the objective function in the multi-objective optimization model under multiple constraints includes: using the ε-constraint method to determine one of the multiple objective functions in the multi-objective optimization model as the reference objective function, converting the other objective functions into constraints with an upper limit of ε; adjusting the value of ε, and calculating the optimal value of the reference objective function under different ε values.

[0103] In step S3 above, the ε-constraint method is used to determine one of the multiple objective functions in the multi-objective optimization model as the reference objective function, and the other objective functions are converted into constraints with an upper limit of ε. The converted model is as follows:

[0104] ;

[0105] By adjusting the ε value, the power allocation strategy of the pulverizing system under different ε values ​​is solved to obtain the set of power allocation strategies for the pulverizing system.

[0106] Traditional mathematical programming methods for solving multi-objective optimization problems mostly employ weighted methods. By adjusting the weights of various indicators, the Pareto front of the multi-objective optimization is obtained before making a decision. This method is inherently prone to generating local optima and can be difficult to solve. This invention uses the ε-constraint method, which transforms redundant objective functions into constraints to solve the established multi-objective programming problem.

[0107] The strategy for choosing the value of ε is as follows:

[0108] ;

[0109] in, The objective function is to minimize power consumption. The objective function is to minimize start-up and shutdown costs. These are equality constraints. These are inequality constraints. This is the upper bound of the objective function that minimizes start-up and shutdown costs. To determine the number of solutions, This is the maximum number of solutions set. Let the minimum value of the objective function for minimizing start-up and shutdown costs be found. This represents the maximum value of the objective function that minimizes start-up and shutdown costs.

[0110] Specifically, by performing single-objective optimization with the goal of minimizing power consumption in the model, the maximum value of the objective function that minimizes start-stop costs is obtained. .

[0111] Specifically, the solution model is as follows:

[0112] ;

[0113] get Because the single-objective optimization solution with minimum power consumption as the objective function yields the maximum value of the start-stop cost objective function, therefore, when the minimum power consumption objective function value is... At that time, the objective function value that minimizes start-up and shutdown costs reaches its maximum value. That is, when the solution is obtained... At that time, it can obtain the corresponding information. .

[0114] Similarly, solve the model:

[0115]

[0116] get A single-objective optimization is performed with the goal of minimizing start-up and shutdown costs, and the solution is obtained. hour.

[0117] In step S4 above, obtaining the optimal power allocation strategy for the pulverizing system from the set of power allocation strategies includes: obtaining the power allocation strategy that maximizes the objective function from the set of power allocation strategies for the pulverizing system, and determining it to be a non-ideal power allocation strategy for the pulverizing system; obtaining the power allocation strategy that minimizes the objective function from the set of power allocation strategies for the pulverizing system, and determining it to be a rational power allocation strategy for the pulverizing system; calculating the distance between each power allocation strategy for the pulverizing system and the non-ideal power allocation strategy, and the distance between each power allocation strategy for the pulverizing system and the ideal power allocation strategy, respectively; calculating multiple evaluation values ​​based on the distances between each power allocation strategy for the pulverizing system and the non-ideal power allocation strategy, and the distance between each power allocation strategy for the pulverizing system and the ideal power allocation strategy, and selecting the power allocation strategy for the pulverizing system with the largest evaluation value as the optimal power allocation strategy for the pulverizing system.

[0118] In this embodiment, the distance between the output allocation strategy of the pulverizing system and the output allocation strategy of the non-ideal pulverizing system is calculated as follows:

[0119] ;

[0120] The distance between the output allocation strategy of the pulverizing system and the ideal output allocation strategy of the pulverizing system is calculated as follows:

[0121]

[0122] The formula for calculating the evaluation value is:

[0123] ;

[0124] in, For the first Calculation of the distance between the output allocation strategy of an ideal pulverizing system and the output allocation strategy of a non-ideal pulverizing system. For the first The distance between the output allocation strategy of the individual pulverizing system and the ideal output allocation strategy of the pulverizing system. j For the first j One objective function, Power allocation strategy for the pulverizing system For non-ideal pulverizing systems, the power allocation strategy A power allocation strategy for an ideal milling system. For the first Evaluation value of the output allocation strategy of a powder-making system.

[0125] Figure 2 This is a structural block diagram of an output distribution device for a coal-fired power plant pulverizing system according to one embodiment of the present invention. Figure 2 As shown, this invention provides a power distribution device for a pulverizing system in a coal-fired power plant, comprising: a parameter acquisition unit, a multi-objective optimization model construction unit, a solution unit, an optimal pulverizing system power distribution strategy acquisition unit, and a control unit. The parameter acquisition unit is used to acquire the pulverizing unit consumption characteristics of each coal mill in the thermal power unit, multiple objective functions for pulverizing system power distribution, and multiple constraints for pulverizing system power distribution. The multi-objective optimization model construction unit is used to construct a multi-objective optimization model based on the pulverizing unit consumption characteristics of each coal mill, the multiple objective functions for pulverizing system power distribution, and the multiple constraints for pulverizing system power distribution. The solution unit is used to solve for the optimal value of the objective function in the multi-objective optimization model under multiple constraints, obtaining a set of pulverizing system power distribution strategies; wherein the set of pulverizing system power distribution strategies includes multiple pulverizing system power distribution strategies. The optimal pulverizing system power distribution strategy acquisition unit is used to acquire the optimal pulverizing system power distribution strategy from the set of pulverizing system power distribution strategies. The control unit is used to control the output of the coal mills according to the optimal pulverizing system power distribution strategy.

[0126] The power distribution device for the pulverizing system of a coal-fired power plant provided in this embodiment mainly implements the following methods:

[0127] The process involves obtaining the pulverizing unit consumption characteristics of each coal mill in a thermal power unit, multiple objective functions for pulverizing system output allocation, and multiple constraints for pulverizing system output allocation. A multi-objective optimization model is constructed based on these characteristics. The optimal value of the objective function in the multi-objective optimization model is solved under multiple constraints to obtain a set of pulverizing system output allocation strategies. This set includes multiple pulverizing system output allocation strategies. The optimal pulverizing system output allocation strategy is then obtained from this set. Finally, the output of the coal mills is controlled according to the optimal pulverizing system output allocation strategy.

[0128] In the above steps, obtaining the pulverizing unit consumption characteristics of each coal mill in a thermal power unit includes: obtaining historical operating data and historical output allocation strategies for each coal mill; analyzing the relationship between coal feed and power consumption for each coal mill based on the historical operating data and historical output allocation strategies to obtain the pulverizing unit consumption characteristics of each coal mill.

[0129] Specifically, historical operating data for each coal mill is obtained from the DCS system, along with the output distribution methods of each mill under different unit loads, to determine the historical output distribution strategy under the original control logic. Correlation analysis is used to perform characteristic analysis on each coal mill, determining the pulverizing system output and the pulverizing unit consumption characteristics of each mill under the control of coal feed rate and drying output regulation.

[0130] Furthermore, the relationship between power consumption and coal feed rate in a pulverizing system is complex and difficult to calculate based on the system's mechanism. It can only be analyzed using historical data from the field. Many factors influence power consumption, including the matching of operating parameters and the start-up and shutdown of the coal mills, indirectly affecting the system's power consumption. This invention expresses the power consumption characteristics of each coal mill using the following formula:

[0131] ;in The power consumption for coal grinding is expressed in KW. This is the coal feed instruction for the coal mill, in units of... .

[0132] Based on historical data on the pulverizing power consumption and coal feed rate of each coal mill, the determined functional form is a quadratic equation in one variable, as shown below:

[0133] ;in, For the first Electricity consumption of a coal mill in Taiwan, in KW; For the first Coal feed instructions for the coal mill, in units of ; All are coefficients of a quadratic function.

[0134] In step S1 above, the multiple objective functions for the output allocation of the pulverizing system include a minimum power consumption objective function and a minimum start-up and shutdown cost objective function; wherein:

[0135] The objective function for minimizing power consumption is:

[0136] ;

[0137] The objective function for minimizing start-up and shutdown costs is:

[0138] ;

[0139] in, The objective function is to minimize power consumption. The objective function is to minimize start-up and shutdown costs. For the first The power consumption of a coal mill. For the first The coal feed rate of the coal mill. For time sets, For the first Start-up cost of a coal mill For the first The downtime cost of a coal mill. For the first Taiwan coal mill The device's current startup status. For the first Taiwan coal mill The system is in a constant state of shutdown.

[0140] In this embodiment, .

[0141] In the above steps, the multiple constraints on the output distribution of the pulverizing system include equality constraints, upper and lower limit constraints, start-stop constraints, and ramping constraints; wherein:

[0142] The equality constraints are:

[0143] ;

[0144] The upper and lower limit constraints are:

[0145] ;

[0146] The start / stop constraints are:

[0147] when hour, ;

[0148] The climbing constraint is:

[0149] ;

[0150] in, For the first The coal feed rate of the coal mill. This is the coal feed instruction for the coal mill. This represents the lower limit of coal mill pulverizing output. This is the upper limit of the coal mill's pulverizing output. For the first The power consumption of the coal mill. This represents the lower limit of the coal mill's pulverizing output ramp-up. To increase the maximum output of the coal mill, For the first Taiwan coal mill Coal feed rate at any given time For the first Taiwan coal mill The amount of coal fed at any given time.

[0151] In the above steps, the multi-objective optimization model constructed based on the pulverizing unit consumption characteristics of each coal mill, multiple objective functions for the output allocation of the pulverizing system, and multiple constraints for the output allocation of the pulverizing system is specifically described as follows:

[0152] ;

[0153] in, The objective function is to minimize power consumption. The objective function is to minimize start-up and shutdown costs. These are equality constraints. These are inequality constraints.

[0154] In the above steps, solving for the optimal value of the objective function in the multi-objective optimization model under multiple constraints includes: using the ε-constraint method to determine one of the multiple objective functions in the multi-objective optimization model as the reference objective function, converting the other objective functions into constraints with an upper limit of ε; adjusting the value of ε, and calculating the optimal value of the reference objective function under different ε values.

[0155] In step S3 above, the ε-constraint method is used to determine one of the multiple objective functions in the multi-objective optimization model as the reference objective function, and the other objective functions are converted into constraints with an upper limit of ε. The converted model is as follows:

[0156] ;

[0157] By adjusting the ε value, the power allocation strategy of the pulverizing system under different ε values ​​is solved to obtain the set of power allocation strategies for the pulverizing system.

[0158] Traditional mathematical programming methods for solving multi-objective optimization problems mostly employ weighted methods. By adjusting the weights of various indicators, the Pareto front of the multi-objective optimization is obtained before making a decision. This method itself suffers from the problems of easily generating local optima and potentially being difficult to solve. This invention adopts... - The constraint method involves converting redundant objective functions into constraints to solve the established multi-objective programming problem.

[0159] The strategy for choosing the value of ε is as follows:

[0160] ;

[0161] in, The objective function is to minimize power consumption. The objective function is to minimize start-up and shutdown costs. These are equality constraints. These are inequality constraints. This is the upper bound of the objective function that minimizes start-up and shutdown costs. To determine the number of solutions, This is the maximum number of solutions set. Let the minimum value of the objective function for minimizing start-up and shutdown costs be found. This represents the maximum value of the objective function that minimizes start-up and shutdown costs.

[0162] Specifically, this is achieved by solving the objective function that minimizes power consumption in the model. The minimum value is obtained to obtain the maximum value of the objective function that minimizes start-up and shutdown costs. .

[0163] Specifically, the solution model is as follows:

[0164] ;

[0165] get Because the objective function value for minimizing power consumption corresponds to the objective function value for minimizing start-up and shutdown costs, therefore, when the objective function value for minimizing power consumption is... At that time, the objective function value that minimizes start-up and shutdown costs reaches its maximum value. That is, when the solution is obtained... At that time, it can obtain the corresponding information. .

[0166] Similarly, solve the model:

[0167]

[0168] get Because the objective function value for minimizing power consumption corresponds to the objective function value for minimizing start-stop cost, therefore, when the objective function value for minimizing start-stop cost is... When the power consumption is minimized, the objective function value is maximized. That is, when the solution is obtained... At that time, it can obtain the corresponding information. .

[0169] In the above steps, obtaining the optimal power allocation strategy for the pulverizing system from the set of power allocation strategies for the pulverizing system includes:

[0170] The power allocation strategy that maximizes the objective function in the set of power allocation strategies for the pulverizing system is identified as a non-ideal power allocation strategy for the pulverizing system; the power allocation strategy that minimizes the objective function in the set of power allocation strategies for the pulverizing system is identified as a rational power allocation strategy for the pulverizing system.

[0171] Calculate the distance between each power allocation strategy of the pulverizing system and the power allocation strategy of the non-ideal pulverizing system, and the distance between each power allocation strategy of the pulverizing system and the power allocation strategy of the ideal pulverizing system, respectively.

[0172] Multiple evaluation values ​​are calculated based on the distance between the output allocation strategies of each pulverizing system and the non-ideal pulverizing system output allocation strategies, as well as the distance between the output allocation strategies of each pulverizing system and the ideal pulverizing system output allocation strategies. The pulverizing system output allocation strategy with the largest evaluation value is selected as the optimal pulverizing system output allocation strategy.

[0173] In this embodiment, the distance between the output allocation strategy of the pulverizing system and the output allocation strategy of the non-ideal pulverizing system is calculated as follows:

[0174] ;

[0175] The distance between the output allocation strategy of the pulverizing system and the ideal output allocation strategy of the pulverizing system is calculated as follows:

[0176]

[0177] The formula for calculating the evaluation value is:

[0178] ;

[0179] in, For the first Calculation of the distance between the output allocation strategy of an ideal pulverizing system and the output allocation strategy of a non-ideal pulverizing system. For the first The distance between the output allocation strategy of the individual pulverizing system and the ideal output allocation strategy of the pulverizing system. j For the first j One objective function, Power allocation strategy for the pulverizing system For non-ideal pulverizing systems, the power allocation strategy A power allocation strategy for an ideal milling system. For the first Evaluation value of the output allocation strategy of a powder-making system.

[0180] The present invention also provides a pulverizing system for a coal-fired power plant, such as... Figure 3 As shown, a specific embodiment of a coal-fired power plant pulverizing system includes: an output distribution device, a coal feeder 4, and a coal mill 5. The output distribution device is connected to both the coal feeder 4 and the coal mill 5, and is used to obtain the coal feed rate of the coal mill 5 through the coal feeder 4 and the power consumption of the coal mill 5 through the coal mill 5. The output distribution device is the output distribution device of the coal-fired power plant pulverizing system described above. The coal-fired power plant pulverizing system also includes: a boiler furnace 1, an air preheater 2, a blower 3, a coarse powder separator 6, a primary air fan 7, a sealing fan 8, and a burner 9.

[0181] Specifically, the output distribution device is used to obtain the amount of coal fed from the coal feeder to the coal mill, and to obtain the power consumption of the coal mill, thereby obtaining the pulverizing unit consumption characteristics of each coal mill.

[0182] Furthermore, the power distribution device constructs a multi-objective optimization model based on the pulverizing unit consumption characteristics of each coal mill, solves the multi-objective optimization model, and thus obtains the optimal power distribution strategy for the pulverizing system.

[0183] Furthermore, the output distribution device controls the output of each coal mill according to the optimal pulverizing system output distribution strategy.

[0184] Furthermore, the output distribution device is also used to obtain the start-up and shutdown costs of each coal mill, and to construct an objective function that minimizes the start-up and shutdown costs.

[0185] This invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the power output distribution method of the coal-fired power plant pulverizing system as described above.

[0186] The present invention also provides a machine-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the above-described power distribution method for a coal-fired power plant pulverizing system.

[0187] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0188] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details described above. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe the various possible combinations.

[0189] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the embodiments of the present invention, they should also be regarded as the content disclosed by the embodiments of the present invention.

Claims

1. A method for distributing the output of a coal pulverizing system of a coal-fired power plant, characterized in that, The method comprises: acquiring a pulverizing unit consumption characteristic of each coal mill of a thermal power unit, a plurality of objective functions of output distribution of a pulverizing system, and a plurality of constraint conditions of output distribution of the pulverizing system; wherein the pulverizing unit consumption characteristic of each coal mill is determined by analyzing a relationship between a coal supply amount and an electricity consumption amount of each coal mill according to historical operation data and a historical output distribution strategy of each coal mill; the plurality of objective functions comprises a minimum electricity consumption objective function and a minimum start-stop cost objective function; and the plurality of constraint conditions comprises an equality constraint condition, an upper and lower limit constraint condition, a start-stop constraint condition, and a climbing constraint condition; A multi-objective optimization model is constructed according to the coal pulverizing specific energy consumption characteristics of each coal mill, a plurality of target functions of the output distribution of the coal pulverizing system and a plurality of constraint conditions of the output distribution of the coal pulverizing system; wherein the multi-objective optimization model is specifically: Wherein, is a minimum power consumption target function, is a minimum start-stop cost target function, is an equality constraint condition, is an inequality constraint condition; solving optimal values of the objective functions in the multi-objective optimization model under the plurality of constraint conditions to obtain a set of output distribution strategies of the pulverizing system; wherein the set of output distribution strategies of the pulverizing system comprises a plurality of output distribution strategies of the pulverizing system; and the solving of the optimal values of the objective functions in the multi-objective optimization model under the plurality of constraint conditions comprises: using an ε-constraint method to determine one of the plurality of objective functions in the multi-objective optimization model as a reference objective function, and converting other objective functions in the plurality of objective functions into constraint conditions with an upper limit of ε; and adjusting a value of ε to calculate optimal values of the reference objective function under different values of ε; acquiring an optimal output distribution strategy of the pulverizing system from the set of output distribution strategies of the pulverizing system, comprising: acquiring an output distribution strategy of the pulverizing system in the set of output distribution strategies of the pulverizing system that maximizes the objective functions, and determining the output distribution strategy of the pulverizing system as a non-ideal output distribution strategy of the pulverizing system; acquiring an output distribution strategy of the pulverizing system in the set of output distribution strategies of the pulverizing system that minimizes the objective functions, and determining the output distribution strategy of the pulverizing system as an ideal output distribution strategy of the pulverizing system; calculating distances between each output distribution strategy of the pulverizing system in the set of output distribution strategies of the pulverizing system and the non-ideal output distribution strategy of the pulverizing system, and distances between each output distribution strategy of the pulverizing system in the set of output distribution strategies of the pulverizing system and the ideal output distribution strategy of the pulverizing system; calculating a plurality of evaluation values according to the distances between each output distribution strategy of the pulverizing system and the non-ideal output distribution strategy of the pulverizing system, and the distances between each output distribution strategy of the pulverizing system and the ideal output distribution strategy of the pulverizing system; and selecting an output distribution strategy of the pulverizing system with a maximum evaluation value as the optimal output distribution strategy of the pulverizing system; controlling a coal mill output according to the optimal output distribution strategy of the pulverizing system.

2. The coal-fired power plant pulverizing system output distribution method of claim 1, wherein, The acquiring of the pulverizing unit consumption characteristic of each coal mill comprises: acquiring historical operation data and a historical output distribution strategy of each coal mill; analyzing a relationship between a coal supply amount and an electricity consumption amount of each coal mill according to the historical operation data and the historical output distribution strategy to obtain the pulverizing unit consumption characteristic of each coal mill.

3. The coal-fired power plant pulverizing system output distribution method according to claim 1, wherein the minimum electricity consumption objective function is: the minimum start-stop cost objective function is: ； the equality constraint condition is: ； in, The objective function is to minimize power consumption. The objective function is to minimize start-up and shutdown costs. For the first The power consumption of a coal mill. For the first The coal feed rate of the coal mill. For time sets, For the first Start-up cost of a coal mill For the first The downtime cost of a coal mill. For the first Taiwan coal mill The device's current startup status. For the first Taiwan coal mill The system is in a constant state of shutdown. the upper and lower limit constraint condition is: ； the start-stop constraint condition is: ； the climbing constraint condition is: When time, ; 5. The coal-fired power plant pulverizing system output distribution method according to claim 1, wherein ； wherein, is the coal supply amount of the nth coal mill, is a coal supply amount command of the coal mill, is a lower limit of the coal mill pulverizing output, is an upper limit of the coal mill pulverizing output, is the power consumption of the nth coal mill, is a lower limit of the coal mill pulverizing output ramp, is an upper limit of the coal mill pulverizing output ramp, is the coal supply amount of the nth coal mill at the time t, is the coal supply amount of the nth coal mill at the time t.

4. The coal-fired power plant pulverizing system output distribution method of claim 1, wherein, The method comprises the following steps: adopting the ε-constraint method, determining one of the multiple objective functions in the multi-objective optimization model as a reference objective function, converting other objective functions in the multiple objective functions into constraint conditions with an upper limit of ε, and converting the model into ; The value strategy is: ； wherein, is a minimum power consumption objective function, is a minimum start-stop cost objective function, is an equality constraint condition, is an inequality constraint condition, is an upper bound of the minimum start-stop cost objective function, is a number of solutions, is a maximum value of the number of solutions, is a minimum value of the minimum start-stop cost objective function, is a maximum value of the minimum start-stop cost objective function. ​ The distance between the pulverizing system output distribution strategy and the non-ideal pulverizing system output distribution strategy is calculated as: ； The distance between the pulverizing system output distribution strategy and the ideal pulverizing system output distribution strategy is calculated as: The calculation formula of the evaluation value is: ； wherein, is a distance between the i-th mill system output distribution policy and the non-ideal mill system output distribution policy, is a distance between the i-th mill system output distribution policy and the ideal mill system output distribution policy, is a distance between the i-th mill system output distribution policy and the non-ideal mill system output distribution policy, is a distance between the i-th mill system output distribution policy and the ideal mill system output distribution policy, j is a distance between the i-th mill system output distribution policy and the non-ideal mill system output distribution policy, j is a distance between the i-th mill system output distribution policy and the ideal mill system output distribution policy, is a mill system output distribution policy, is a non-ideal mill system output distribution policy, is an ideal mill system output distribution policy, is a distance between the i-th mill system output distribution policy and the non-ideal mill system output distribution policy, is a distance between the i-th mill system output distribution policy and the ideal mill system output distribution policy.

6. A coal pulverizing system output distribution device for a coal-fired power plant, characterized by comprising: The method comprises the following steps: The parameter acquisition unit is configured to acquire the pulverizing unit consumption characteristics of each coal mill of the thermal power generating unit, a plurality of objective functions of the pulverizing system output distribution, and a plurality of constraint conditions of the pulverizing system output distribution; wherein the pulverizing unit consumption characteristics of each coal mill are determined by analyzing the relationship between the coal supply amount and the power consumption of each coal mill according to the historical operation data and the historical output distribution strategy of each coal mill; the plurality of objective functions comprise a minimum power consumption objective function and a minimum start-stop cost objective function; and the plurality of constraint conditions comprise an equality constraint condition, an upper and lower limit constraint condition, a start-stop constraint condition, and a climbing constraint condition. The multi-objective optimization model construction unit is configured to construct a multi-objective optimization model according to the power consumption characteristics of each coal mill, a plurality of objective functions of the output distribution of the coal pulverizing system, and a plurality of constraint conditions of the output distribution of the coal pulverizing system. wherein, is a minimum power consumption objective function, is a minimum start-stop cost objective function, is an equality constraint condition, is an inequality constraint condition. The solving unit is configured to solve the optimal value of the objective function in the multi-objective optimization model under the plurality of constraint conditions to obtain a set of pulverizing system output distribution strategies; wherein the set of pulverizing system output distribution strategies comprises a plurality of pulverizing system output distribution strategies; and the solving of the optimal value of the objective function in the multi-objective optimization model under the plurality of constraint conditions comprises: using an ε-constraint method to determine one of the plurality of objective functions in the multi-objective optimization model as a reference objective function, and converting the other objective functions into constraint conditions with an upper limit of ε; and adjusting the value of ε to calculate the optimal value of the reference objective function under different ε values. The optimal pulverizing system output distribution strategy acquisition unit is configured to acquire an optimal pulverizing system output distribution strategy from the set of pulverizing system output distribution strategies, comprising: acquiring a pulverizing system output distribution strategy in the set of pulverizing system output distribution strategies that maximizes the objective function, and determining it as a non-ideal pulverizing system output distribution strategy; acquiring a pulverizing system output distribution strategy in the set of pulverizing system output distribution strategies that minimizes the objective function, and determining it as a rational pulverizing system output distribution strategy; calculating the distance between each pulverizing system output distribution strategy in the set of pulverizing system output distribution strategies and the non-ideal pulverizing system output distribution strategy, and the distance between each pulverizing system output distribution strategy and the ideal pulverizing system output distribution strategy, respectively; calculating a plurality of evaluation values according to the distance between each pulverizing system output distribution strategy and the non-ideal pulverizing system output distribution strategy, and the distance between each pulverizing system output distribution strategy and the ideal pulverizing system output distribution strategy; and selecting the pulverizing system output distribution strategy with the maximum evaluation value as the optimal pulverizing system output distribution strategy. The control unit is configured to control the coal mill output according to the optimal pulverizing system output distribution strategy.

7. A coal pulverizing system for a coal-fired power plant, characterized by, The method comprises the following steps: The output distribution device, the coal feeder, and the coal mill are connected, and the output distribution device is configured to acquire the coal supply amount of the coal mill through the coal feeder and the power consumption of the coal mill through the coal mill. The output distribution device is the coal-fired power plant pulverizing system output distribution device of claim 6.

Images