A guidance and control platform for optimizing coal blending and combustion of multiple coal types

Abstract

The present invention provides a guidance and control platform for optimal coal blending and combustion of multiple coal types. It relates to the technical field of coal blending and combustion, and the platform includes: establishing a database of multiple coal types according to the types of coal in stock, and at the same time, obtaining parameter data of the combustion device; taking the quantity of the coal in stock, the combustion characteristic index and the safety of the combustion device as constraints, and taking the efficiency of coal blending and combustion of multiple coal types as the objective function, calculating the optimal coal blending and combustion plan; automatically generating the corresponding optimal coal blending and transportation plan; monitoring the remaining amount of coal in stock, the combustion process and the blending and combustion process; optimizing and adjusting the optimal coal blending and combustion plan; mastering the coal types in the combustion device in real time, improving the combustion safety and combustion efficiency, ensuring that the emission meets the standards, and then ensuring the blending and combustion efficiency, and realizing effective guidance and control.

Description

Technical Field

[0001] The present invention relates to the technical field of coal blending and combustion, and in particular to a guidance and control platform for optimizing coal blending and combustion of multiple coal types. Background Art

[0002] At present, my country's energy structure is mainly based on thermal power generation. In order to ensure electricity production and adapt to the complex and changing coal market, more and more thermal power plants are adopting mixed coal combustion technology; however, when boilers designed based on the designed coal type burn non-designed coal types, problems such as reduced boiler stability, reduced thermal efficiency and excessive pollution emissions appear; and most thermal power plants currently use stratified combustion technology and are equipped with numerous raw coal bunkers, resulting in a time difference from loading coal into the raw coal bunker to stratified combustion, making it impossible to accurately obtain the coal type inside the boiler, resulting in low blending efficiency.

[0003] Therefore, the present invention provides a guidance and control platform for optimizing coal blending and combustion of multiple coal types. Summary of the invention

[0004] The present invention provides a guidance and control platform for optimal coal blending and combustion of multiple coal types, which is used to obtain parameter data of a combustion device by establishing a database of multiple coal types; taking the quantity of the inventory coal, the combustion characteristic index and the safety of the combustion device as constraints, and the coal blending efficiency of multiple coal types as an objective function, to calculate the optimal coal blending and combustion plan; automatically generating a corresponding optimal coal blending and transportation plan; monitoring the remaining amount of inventory coal, the combustion process and the blending process; optimizing and adjusting the optimal coal blending and combustion plan; and understanding the coal type situation in the combustion device in real time, improving combustion safety and combustion efficiency, ensuring that emissions meet standards, and further ensuring blending efficiency, thereby achieving effective guidance and control.

[0005] The present invention provides a multi-coal optimal blending and combustion guidance and control platform, comprising:

[0006] Data collection module: According to the types of coal in stock, obtain the coal quantity, moisture, ash, sulfur and volatile matter of the coal in stock, establish a multi-coal database, and at the same time, obtain the parameter data of the combustion device;

[0007] Coal blending and combustion module: Based on the multi-coal database and the parameter data of the combustion device, with the quantity of the stored coal, the combustion characteristic index and the safety of the combustion device as constraints, and the multi-coal blending and combustion efficiency as the objective function, the optimal coal blending and combustion plan is calculated;

[0008] Transportation module: According to the optimal coal blending and combustion plan and the remaining amount of coal in stock, the corresponding optimal coal blending and transportation plan is automatically generated, and the corresponding proportion of coal is transported to the corresponding combustion device;

[0009] Monitoring and identification module: monitors the remaining amount of coal in stock during the blending and burning of multiple coal types, and monitors the combustion process and blending process in the corresponding combustion device;

[0010] Optimization and update module: Optimize and adjust the best coal blending and combustion plan based on the monitoring results.

[0011] Preferably, the data collection module comprises:

[0012] Coal data collection unit, used to obtain the types of coal in stock;

[0013] According to the types of coal in stock, obtain the storage quantity, moisture, ash, sulfur and volatile matter of each type of coal in stock;

[0014] The database unit is used to sort the various types of inventory coal in descending order according to the volatile matter of coal, and at the same time, establish a database of multiple coal types.

[0015] Preferably, the data collection module comprises:

[0016] The combustion device comprises: a raw coal bunker, a coal mill and a boiler;

[0017] The parameter data of the combustion device include: the total number of raw coal bunkers and the coal storage capacity of each raw coal bunker, the total number of coal mills, the number of combustion layers of the boiler and the safety index of each combustion layer.

[0018] Preferably, the coal blending and combustion module comprises:

[0019] The constraint unit is used to establish the constraint conditions for coal blending based on the database of multiple coal types, combustion characteristic index and the safety of the combustion device;

[0020] The target unit is used to establish the target function of coal blending and combustion according to the efficiency of coal blending and combustion of multiple coal types;

[0021] The coal blending and combustion unit is used to determine the type of coal to be blended and burned according to the constraints and the objective function;

[0022] According to the number of coal types and the coal blending ratio of each coal type, the corresponding coal blending array is obtained, the coal blending ratio is divided into n intervals, and the coal blending scheme is initialized and generated according to the orthogonal design method;

[0023] Construct the fitness function of coal types according to the objective function and calculate the fitness of each initialization coal blending scheme;

[0024] According to the fitness, each initialization coal blending scheme is sorted from large to small, and the first m initialization coal blending schemes are selected and used as the first coal blending scheme;

[0025] Perform crossover and mutation operations on each first coal blending scheme to generate a new coal blending scheme;

[0026] The fitness of each new coal blending scheme is recalculated, and the scheme corresponding to the highest fitness is selected as the optimal coal blending scheme.

[0027] Preferably, the transport module comprises:

[0028] The transport unit is used to transport the required coal types to the corresponding raw coal bunker according to the optimal coal blending and combustion plan;

[0029] When the optimal coal blending and combustion plan is monitored to change, the coal transportation plan is adjusted accordingly;

[0030] When the coal replenishment alarm data from the inventory coal / raw coal bin is received, the corresponding coal replenishment transportation is carried out according to the optimal coal blending and combustion plan.

[0031] Preferably, the monitoring and identification module includes:

[0032] The combustion process monitoring unit is used to monitor the combustion status of each combustion layer of the boiler;

[0033] The wall temperature monitoring unit is used to obtain the wall temperature data of multiple monitoring points in each combustion layer, obtain the average wall temperature data of each combustion layer after analysis and processing, and obtain the overall wall temperature safety of the boiler according to the combustion layer-safety mapping table;

[0034] The combustion efficiency monitoring unit is used to obtain the comprehensive coal quality of the multi-coal blending combustion according to the coal quantity, moisture, ash content, sulfur content and volatile matter of each coal type in the optimal coal blending combustion plan;

[0035] Based on the combustion state monitoring results, the exhaust heat loss, chemical incomplete combustion heat loss, mechanical incomplete combustion heat loss, heat dissipation loss and ash physical heat loss in the combustion process are obtained, and the combustion efficiency of the boiler is calculated;

[0036] The emission monitoring unit is used to obtain the combustion emission parameters and calculate the emission index of the boiler according to the preset emission evaluation index and the weight of each emission parameter;

[0037] Among them, the monitoring results of the combustion process include: overall boiler wall temperature safety, comprehensive coal quality, combustion efficiency and emission index.

[0038] Preferably, the monitoring and identification module includes:

[0039] Inventory coal monitoring unit, used to monitor the remaining inventory coal during the blending and burning of multiple coal types;

[0040] When it is monitored that the remaining amount of a certain stock of coal reaches the preset stock lower limit, if the coal blending plan is changed, a new type of coal will be switched after the blending of the stock of coal is completed;

[0041] Otherwise, coal replenishment alarm data corresponding to the inventory coal is generated, and coal replenishment is carried out in time;

[0042] A raw coal bunker monitoring unit is used to monitor the type of coal loaded into each raw coal bunker at each time, and construct a first coal loading map, wherein the first coal loading map includes: coal loading time points of different types of coal;

[0043] According to the type of coal loaded in the same coal loading time period, the first moisture content of the corresponding coal type is determined from the type-moisture content mapping table;

[0044] The coal mill monitoring unit is used to monitor the coal powder fineness of the coal mill outlet area and the outlet time period consistent with each coal loading time period in the first coal loading diagram according to the coal transmission mechanism between the raw coal bunker and the coal mill and in combination with the pre-deployed infrared sensor in the coal mill outlet area;

[0045] Based on the coal powder fineness, the initial coal powder moisture C0 at each outlet time point is obtained from the original coal fineness-coal powder fineness-moisture mapping table;

[0046] The heat input of the coal mill is obtained according to the temperature sensors pre-deployed at the inlet and outlet of the coal mill;

[0047] q in =G f ×c k ×(t in -t out )

[0048] Among them, q in is the heat input of the coal mill; G f is the hot primary air flow rate of the coal mill; c k is the specific heat capacity of air at the average temperature of the coal mill in operation; t in The hot air temperature measured by the temperature sensor at the coal mill inlet; t out The pulverized coal temperature measured by the temperature sensor at the coal mill outlet;

[0049] Obtain the heat output of the coal mill;

[0050] q out =S f1 +S f2

[0051] Among them, q out is the heat output of the coal mill; S f1 Heat loss of coal mill during coal grinding process; S f2The heat of volatilization of coal moisture during the coal pulverizing process in the coal mill;

[0052] According to the heat balance calculation of the coal mill, the second moisture content of the coal in the coal mill is obtained;

[0053]

[0054] Wherein, C1 represents the second moisture at the corresponding outlet time point; represents the moisture conversion coefficient; Z represents the total energy of the coal mill at the corresponding outlet time point;

[0055] A coal type identification unit, used for drawing a first monitoring diagram according to the first moisture at different coal loading time points obtained by the raw coal bunker unit;

[0056] Draw a second monitoring graph according to the second moisture at different outlet time points obtained by the coal mill monitoring unit;

[0057] Performing alignment processing on the first monitoring graph and the second monitoring graph with consistent time conversion, randomly selecting n1 sequence values ​​from the first alignment graph and the second alignment graph, performing fitting processing on the first alignment graph and the second alignment graph, and selecting fitting values ​​consistent with the time points corresponding to the n1 sequence values;

[0058] At the same time, time points at which the fluctuation difference is greater than a preset difference are selected from the first alignment graph and the second alignment graph, and the data at the selected time points are used as feature data;

[0059] Calculate the fitting degree of the first monitoring graph and the second monitoring graph;

[0060]

[0061] Among them, R 2 is the degree of fit of the first monitoring graph and the second monitoring graph; y1i represents the ith sequence value selected in the first alignment graph; x1i represents the ith fitting value selected in the first alignment graph; y2i represents the ith sequence value selected in the second alignment graph; x2i represents the ith fitting value selected in the second alignment graph; y1p represents the average value of the fitting values ​​selected in the first alignment graph; y2p represents the average value of the fitting values ​​selected in the second alignment graph; y1j represents the sequence value belonging to the first alignment graph in the jth fluctuation pair; y2j represents the sequence value belonging to the second alignment graph in the jth fluctuation pair;

[0062] When the fitting degree of the first monitoring diagram and the second monitoring diagram is greater than the preset fitting degree, it is determined that the coal mill is in a normal operating state;

[0063] Otherwise, adjust the relevant parameters of the coal mill, re-obtain the second moisture content of the coal in the coal mill and perform the fitting calculation.

[0064] Preferably, the optimization and update module includes:

[0065] The optimization unit is used to optimize the type and quantity of purchased coal according to the inventory coal quantity, the historical best coal blending and combustion plan, and the best coal blending plan;

[0066] According to the best coal blending and combustion plan, optimize the monitoring and identification of the raw coal bunker, the relevant parameter settings of the coal mill, and the parameter settings of each combustion layer of the boiler;

[0067] The update unit is used to update the inventory coal data, raw coal bunker coal type data, pulverizer related parameter data, boiler combustion layer combustion data and the best coal blending scheme in real time, and store and record the updated data separately by time.

[0068] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0069] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0071] Figure 1 It is a schematic diagram of a guidance and control platform for optimal coal blending and combustion of multiple coal types in an embodiment of the present invention. DETAILED DESCRIPTION

[0072] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0073] The embodiment of the present invention provides a multi-coal type optimal coal blending guidance and control platform, such as Figure 1 As shown, including:

[0074] Data collection module: According to the types of coal in stock, obtain the coal quantity, moisture, ash, sulfur and volatile matter of the coal in stock, establish a multi-coal database, and at the same time, obtain the parameter data of the combustion device;

[0075] Coal blending and combustion module: Based on the multi-coal database and the parameter data of the combustion device, with the quantity of the stored coal, the combustion characteristic index and the safety of the combustion device as constraints, and the multi-coal blending and combustion efficiency as the objective function, the optimal coal blending and combustion plan is calculated;

[0076] Transportation module: According to the optimal coal blending and combustion plan and the remaining amount of coal in stock, the corresponding optimal coal blending and transportation plan is automatically generated, and the corresponding proportion of coal is transported to the corresponding combustion device;

[0077] Monitoring and identification module: monitors the remaining amount of coal in stock during the blending and burning of multiple coal types, and monitors the combustion process and blending process in the corresponding combustion device;

[0078] Optimization and update module: Optimize and adjust the best coal blending and combustion plan based on the monitoring results.

[0079] In this embodiment, the multi-coal type database refers to a database including the coal type, coal quantity, moisture, ash content, sulfur content and volatile matter of the stored coal.

[0080] In this embodiment, the combustion device refers to a device consisting of a plurality of raw coal bins, a coal pulverizer and a boiler.

[0081] In this embodiment, the optimal coal blending and combustion scheme refers to a coal blending and combustion scheme calculated based on a database of multiple coal types and parameter data of the combustion device, with the quantity of the inventory coal, the combustion characteristic index and the safety of the combustion device as constraints, and the coal blending efficiency of multiple coal types as the objective function. Using this scheme for coal blending and combustion of multiple coal types can achieve the highest combustion efficiency, ensure combustion safety and make the emission index meet the standards.

[0082] In this embodiment, the multi-coal blending and burning is divided into two types: pre-furnace coal blending and burning technology and in-furnace coal blending and burning technology. Compared with in-furnace coal blending and burning, pre-furnace coal blending and burning has high maintenance cost, lacks flexibility and real-time performance. It is easy to cause uneven mixing of multiple coal types, affecting the blending efficiency. Therefore, the in-furnace coal blending and burning technology is selected.

[0083] In this embodiment, the in-furnace coal blending technology refers to transporting different types of coal to different coal mills for grinding, and then sending them into the corresponding boiler combustion layer to provide conditions for sufficient combustion of the coal types.

[0084] In this embodiment, the raw coal bunker refers to a larger capacity coal bunker equipped with the boiler unit, which is used to store corresponding types of coal. The same raw coal bunker can store multiple types of coal according to the optimal coal blending and combustion plan.

[0085] In this embodiment, the coal mill is a machine for crushing coal and grinding it into coal powder, and is an important equipment for assisting the complete combustion of coal.

[0086] In this embodiment, the boiler is a device for blending and burning multiple types of coal and is provided with multiple combustion layers to provide good combustion conditions for the multiple types of coal.

[0087] In this embodiment, the optimal transportation plan refers to a coal transportation plan formulated based on the storage location of the inventory coal, the transportation route, and the optimal coal blending and combustion plan.

[0088] In this embodiment, the combustion process refers to the combustion of multiple types of coal in each combustion layer of the boiler.

[0089] In this embodiment, the blending process refers to the stratification and storage conditions of multiple coal types in the raw coal bin and the conditions in the coal mill.

[0090] The beneficial effects of the above technical solution are: by establishing a database of multiple coal types, parameter data of the combustion device is obtained; taking the quantity of the inventory coal, the combustion characteristic index and the safety of the combustion device as constraints, and the multi-coal blending efficiency as the objective function, the optimal coal blending scheme is calculated; the corresponding optimal coal blending transportation plan is automatically generated; the remaining amount of inventory coal, the combustion process and the blending process are monitored; the optimal coal blending scheme is optimized and adjusted; the coal type situation in the combustion device is mastered in real time, the combustion safety and combustion efficiency are improved, and the emission standards are ensured to be met.

[0091] The embodiment of the present invention provides a multi-coal optimal blending guidance and control platform, a data collection module, including:

[0092] Coal data collection unit, used to obtain the types of coal in stock;

[0093] According to the types of coal in stock, obtain the storage quantity, moisture, ash, sulfur and volatile matter of each type of coal in stock;

[0094] The database unit is used to sort the various types of inventory coal in descending order according to the volatile matter of coal, and at the same time, establish a database of multiple coal types.

[0095] In this embodiment, the coal data is collected in real time, for example, the coal data is collected every hour and updated in a timely manner.

[0096] In this embodiment, when it is monitored that a certain type of coal in stock is completely consumed, the coal type database is promptly removed from the latest multi-coal type database, and at the same time, the moisture, ash, sulfur and volatile matter of the coal type are stored in the historical coal type database.

[0097] In this embodiment, when a new inventory list is monitored, the inventory coal type is obtained, and if the inventory coal type exists in the multi-coal type database or the historical coal type database, the multi-coal type database is updated;

[0098] Otherwise, create new coal type data and update the multi-coal type database.

[0099] The beneficial effects of the above technical solution are: collecting coal data and establishing a database of multiple coal types, which is conducive to the design of the subsequent optimal coal blending and combustion plan. At the same time, the storage quantity, moisture, ash content, sulfur content and volatile matter of various types of inventory coal are obtained and updated in real time to ensure the timely update of the optimal coal blending and combustion plan, and to ensure the efficiency and safety of blending and combustion.

[0100] The embodiment of the present invention provides a multi-coal optimal blending guidance and control platform, a data collection module, including:

[0101] The combustion device comprises: a raw coal bunker, a coal mill and a boiler;

[0102] The parameter data of the combustion device include: the total number of raw coal bunkers and the coal storage capacity of each raw coal bunker, the total number of coal mills, the number of combustion layers of the boiler and the safety index of each combustion layer.

[0103] In this embodiment, in order to ensure the continuous operation of the boiler, multiple raw coal bunkers and multiple coal mills are usually equipped.

[0104] In this embodiment, when the amount of coal stored in the raw coal bin reaches a preset upper limit of coal storage, the co-firing operation of the boiler can be ensured within a certain period of time, for example, the co-firing operation of the boiler can be ensured for about 6 hours.

[0105] In this embodiment, multiple sensors are pre-deployed in each combustion device to monitor and obtain relevant parameter data. For example, an infrared sensor is pre-deployed in the raw coal bin to monitor the coal storage amount in real time; a temperature sensor is pre-deployed in the coal mill to monitor the working status; and temperature sensors are pre-deployed in each combustion layer of the boiler to monitor the co-combustion temperature.

[0106] The beneficial effects of the above technical solution are: obtaining the parameter data of the combustion device, which is convenient for the subsequent design of the optimal coal blending and combustion plan. At the same time, it is conducive to real-time monitoring of the working status of the combustion device, ensuring the working safety of each combustion device, and ensuring the coal blending and combustion work.

[0107] The embodiment of the present invention provides a multi-coal optimal coal blending and combustion guidance and control platform, and a coal blending and combustion module, including:

[0108] The constraint unit is used to establish the constraint conditions for coal blending based on the database of multiple coal types, combustion characteristic index and the safety of the combustion device;

[0109] The target unit is used to establish the target function of coal blending and combustion according to the efficiency of coal blending and combustion of multiple coal types;

[0110] The coal blending and combustion unit is used to determine the type of coal to be blended and burned according to the constraints and the objective function;

[0111] According to the number of coal types and the coal blending ratio of each coal type, the corresponding coal blending array is obtained, the coal blending ratio is divided into n intervals, and the coal blending scheme is initialized and generated according to the orthogonal design method;

[0112] Construct the fitness function of coal types according to the objective function and calculate the fitness of each initialization coal blending scheme;

[0113] According to the fitness, each initialization coal blending scheme is sorted from large to small, and the first m initialization coal blending schemes are selected and used as the first coal blending scheme;

[0114] Perform crossover and mutation operations on each first coal blending scheme to generate a new coal blending scheme;

[0115] The fitness of each new coal blending scheme is recalculated, and the scheme corresponding to the highest fitness is selected as the optimal coal blending scheme.

[0116] In this embodiment, the combustion characteristics refer to the calorific value, ash melting point, combustion rate and burnout temperature of the coal, which are important bases for the combustion device.

[0117] In this embodiment, the constraint condition of coal blending refers to establishing a first constraint condition based on the quantity of inventory coal; establishing a second constraint condition based on the combustion characteristic index of the inventory coal; and establishing a third constraint condition based on the safety of the combustion device.

[0118] In this embodiment, the coal types selected for blending and burning do not appear repeatedly, the number of coal types is not greater than the inventory number, and the total ratio of the coal types is 1. For example, the inventory coal types A1, A2, A3 and A4 are selected for blending and burning, and the blending ratios are 0.5, 0.2 and 0.3 respectively.

[0119] In this embodiment, the calorific value, moisture content, ash content, sulfur content, volatile matter and grindability index of each type of coal used for blending and burning should all meet the parameter requirements of the combustion equipment.

[0120] In this embodiment, the grindability index refers to the difficulty of grinding a type of coal. The larger the grindability index of a type of coal is, the easier it is to grind it in a coal mill.

[0121] In this embodiment, each constraint condition is set with different boundary limits according to the load capacity of the combustion equipment for different constraint conditions, thereby realizing intelligent coal blending and combustion.

[0122] In this embodiment, the objective function of coal blending and combustion refers to establishing an objective function based on the efficiency of coal blending and combustion of multiple coal types.

[0123] In this embodiment, a corresponding coal blending array is obtained according to the types of coal and the blending ratios of each coal type. For example, "A1, A3, A4, 0.5, 0.2, 0.3" means that the coal blending scheme is coal type A1, coal type A3 and coal type A4, and the blending ratios are 0.5, 0.2 and 0.3 respectively.

[0124] In this embodiment, the coal blending ratio is divided into n intervals according to the number of types of coal in stock. For example, if there are 10 types of coal in stock, the coal blending ratio is divided into 10 intervals for subsequent data processing. At the same time, in order to avoid affecting subsequent data processing due to the small number of types of coal in stock, the minimum number of divisions is set to 3.

[0125] In this embodiment, the fitness function is a main indicator used to represent the performance of each type of coal. The various types of coal are screened according to the size of the fitness function; the fitness function is modified according to various constraint conditions.

[0126] The beneficial effect of the above technical solution is: taking the quantity of the inventory coal, the combustion characteristic index and the safety of the combustion device as constraints, and the blending efficiency of multiple coal types as the objective function, the optimal coal blending scheme is calculated, the inventory coal is reasonably utilized, and in theory the combustion efficiency and combustion safety are ensured to the maximum extent.

[0127] The embodiment of the present invention provides a multi-coal optimal blending and combustion guidance and control platform, a transportation module, including:

[0128] The transport unit is used to transport the required coal types to the corresponding raw coal bunker according to the optimal coal blending and combustion plan;

[0129] When the optimal coal blending and combustion plan is monitored to change, the coal transportation plan is adjusted accordingly;

[0130] When the coal replenishment alarm data from the inventory coal / raw coal bin is received, the corresponding coal replenishment transportation is carried out according to the optimal coal blending and combustion plan.

[0131] In this embodiment, according to the optimal coal blending plan, the coal types for blending are determined, and the optimal transportation plan is formulated. For example, the coal type A1 for blending and the raw coal bin C1 are determined, and the inventory coal type A1 is stored at positions B1 and B2. Position B1, which is close to the raw coal bin C1, is selected to transport coal type A1.

[0132] In this embodiment, when the inventory coal replenishment alarm data is received, a replenishment and transportation plan of changing the type of coal or purchasing a new type of coal is selected.

[0133] In this embodiment, after receiving the coal replenishment alarm data of the raw coal bunker, a corresponding amount of coal is transported to the raw coal bunker according to the optimal coal blending and combustion plan.

[0134] The beneficial effect of the above technical solution is: according to the best coal blending and combustion plan, the best transportation plan is formulated, which is conducive to improving the combustion efficiency and ensuring the continuity of the combustion process.

[0135] The embodiment of the present invention provides a multi-coal optimal blending guidance and control platform, a monitoring and identification module, including:

[0136] The combustion process monitoring unit is used to monitor the combustion status of each combustion layer of the boiler;

[0137] The wall temperature monitoring unit is used to obtain the wall temperature data of multiple monitoring points in each combustion layer, obtain the average wall temperature data of each combustion layer after analysis and processing, and obtain the overall wall temperature safety of the boiler according to the combustion layer-safety mapping table;

[0138] The combustion efficiency monitoring unit is used to obtain the comprehensive coal quality of the multi-coal blending combustion according to the coal quantity, moisture, ash content, sulfur content and volatile matter of each coal type in the optimal coal blending combustion plan;

[0139] Based on the combustion state monitoring results, the exhaust heat loss, chemical incomplete combustion heat loss, mechanical incomplete combustion heat loss, heat dissipation loss and ash physical heat loss in the combustion process are obtained, and the combustion efficiency of the boiler is calculated;

[0140] The emission monitoring unit is used to obtain the combustion emission parameters and calculate the emission index of the boiler according to the preset emission evaluation index and the weight of each emission parameter;

[0141] Among them, the monitoring results of the combustion process include: overall boiler wall temperature safety, comprehensive coal quality, combustion efficiency and emission index.

[0142] In this embodiment, the boiler is divided into different combustion layers, and coal is blended and burned in the furnace, so that each type of coal has a higher combustion efficiency.

[0143] In this embodiment, the quantity, moisture, ash, sulfur and volatile matter of each type of coal will affect the heat load capacity of each combustion layer, the slagging capacity of the coal and the combustion safety. Therefore, it is necessary to ensure that the heat load of each combustion layer is uniform.

[0144] In this embodiment, in order to ensure the stability of the co-firing in the furnace, the coal types that are easy to burn and have a high calorific value are set in the lower and middle combustion layers of the boiler, and the coal types that are not easy to burn and have a low calorific value are set in the upper and middle combustion layers of the boiler.

[0145] In this embodiment, multiple monitoring points are provided in each combustion layer to monitor the boiler wall temperature in real time.

[0146] In this embodiment, the safe wall temperature alarm value of each combustion layer is preset according to the combustion layer-safety mapping table. When the wall temperature of a certain combustion layer is monitored to reach the safe wall temperature alarm value, a corresponding alarm is issued to ensure the overall wall temperature safety of the boiler.

[0147] In this embodiment, the best coal blending and combustion scheme is determined based on the overall wall temperature safety of the boiler, the combustion efficiency of the boiler and the emission index of the boiler. That is, the higher the overall wall temperature safety of the boiler, the higher the combustion efficiency of the boiler and the lower the emission index of the boiler, the better the coal blending and combustion scheme.

[0148] The beneficial effect of the above technical solution is: by monitoring the combustion process in each combustion layer of the boiler, the overall wall temperature safety of the boiler, the combustion efficiency of the boiler and the emission index of the boiler can be obtained in real time, which is conducive to intuitive evaluation of the best coal blending and combustion scheme, and data visualization is convenient for real-time processing of various problems generated in the actual combustion process of each combustion layer of the boiler, ensuring the actual combustion efficiency and equipment safety.

[0149] The embodiment of the present invention provides a multi-coal optimal blending guidance and control platform, a monitoring and identification module, including:

[0150] Inventory coal monitoring unit, used to monitor the remaining inventory coal during the blending and burning of multiple coal types;

[0151] When it is monitored that the remaining amount of a certain stock of coal reaches the preset stock lower limit, if the coal blending plan is changed, a new type of coal will be switched after the blending of the stock of coal is completed;

[0152] Otherwise, coal replenishment alarm data corresponding to the inventory coal is generated, and coal replenishment is carried out in time;

[0153] A raw coal bunker monitoring unit is used to monitor the type of coal loaded into each raw coal bunker at each time, and construct a first coal loading map, wherein the first coal loading map includes: coal loading time points of different types of coal;

[0154] According to the type of coal loaded in the same coal loading time period, the first moisture content of the corresponding coal type is determined from the type-moisture content mapping table;

[0155] The coal mill monitoring unit is used to monitor the coal powder fineness of the coal mill outlet area and the outlet time period consistent with each coal loading time period in the first coal loading diagram according to the coal transmission mechanism between the raw coal bunker and the coal mill and in combination with the pre-deployed infrared sensor in the coal mill outlet area;

[0156] Based on the coal powder fineness, the initial coal powder moisture C0 at each outlet time point is obtained from the original coal fineness-coal powder fineness-moisture mapping table;

[0157] The heat input of the coal mill is obtained according to the temperature sensors pre-deployed at the inlet and outlet of the coal mill;

[0158] q in =G f ×c k ×(t in -t out )

[0159] Among them, q in is the heat input of the coal mill; G f is the hot primary air flow rate of the coal mill; c k is the specific heat capacity of air at the average temperature of the coal mill in operation; t in The hot air temperature measured by the temperature sensor at the coal mill inlet; t out The pulverized coal temperature measured by the temperature sensor at the coal mill outlet;

[0160] Obtain the heat output of the coal mill;

[0161] q out =S f1 +S f2

[0162] Among them, q out is the heat output of the coal mill; S f1 Heat loss of coal mill during coal grinding process; S f2 The heat of volatilization of coal moisture during the coal pulverizing process in the coal mill;

[0163] According to the heat balance calculation of the coal mill, the second moisture content of the coal in the coal mill is obtained;

[0164]

[0165] Wherein, C1 represents the second moisture at the corresponding outlet time point; represents the moisture conversion coefficient; Z represents the total energy of the coal mill at the corresponding outlet time point;

[0166] A coal type identification unit, used for drawing a first monitoring diagram according to the first moisture at different coal loading time points obtained by the raw coal bunker unit;

[0167] Draw a second monitoring graph according to the second moisture at different outlet time points obtained by the coal mill monitoring unit;

[0168] Performing alignment processing on the first monitoring graph and the second monitoring graph with consistent time conversion, randomly selecting n1 sequence values ​​from the first alignment graph and the second alignment graph, performing fitting processing on the first alignment graph and the second alignment graph, and selecting fitting values ​​consistent with the time points corresponding to the n1 sequence values;

[0169] At the same time, time points at which the fluctuation difference is greater than a preset difference are selected from the first alignment graph and the second alignment graph, and the data at the selected time points are used as feature data;

[0170] Calculate the fitting degree of the first monitoring graph and the second monitoring graph;

[0171]

[0172] Among them, R 2 is the degree of fit of the first monitoring graph and the second monitoring graph; y1i represents the ith sequence value selected in the first alignment graph; x1i represents the ith fitting value selected in the first alignment graph; y2i represents the ith sequence value selected in the second alignment graph; x2i represents the ith fitting value selected in the second alignment graph; y1p represents the average value of the fitting values ​​selected in the first alignment graph; y2p represents the average value of the fitting values ​​selected in the second alignment graph; y1j represents the sequence value belonging to the first alignment graph in the jth fluctuation pair; y2j represents the sequence value belonging to the second alignment graph in the jth fluctuation pair;

[0173] When the fitting degree of the first monitoring diagram and the second monitoring diagram is greater than the preset fitting degree, it is determined that the coal mill is in a normal operating state;

[0174] Otherwise, adjust the relevant parameters of the coal mill, re-obtain the second moisture content of the coal in the coal mill and perform the fitting calculation.

[0175] In this embodiment, in order to ensure the stability of coal supply and combustion, the boiler is equipped with a raw coal bunker with a large capacity. Therefore, there will be a certain time error from the loading of coal from the raw coal bunker to the actual combustion of each combustion layer of the boiler, which may lead to differences between the type of coal loaded and the type of coal actually burned.

[0176] In this embodiment, the type of coal entering the coal mill is regarded as the type of coal actually burned in each combustion layer of the boiler and is processed.

[0177] In this embodiment, the remaining amount of coal in stock during the process of blending and burning multiple coal types is monitored. For example, when it is monitored that the remaining amount of coal type A1 reaches the preset inventory lower limit of 10t, if the optimal coal blending and burning scheme changes at this time, the coal type is switched according to the new optimal coal blending and burning scheme after the inventory coal type A1 is burned; otherwise, coal replenishment alarm data for the inventory coal type A1 is generated, and coal replenishment is completed before the inventory coal type A1 is burned.

[0178] In this embodiment, when it is monitored that the optimal coal blending and combustion scheme has changed and the remaining amount of coal in stock has not reached the preset inventory lower limit, for example, when it is monitored that the optimal coal blending and combustion scheme has changed from coal types A1, A3 and A4 to coal types A2 and A4, and it is monitored that the remaining amount of coal type A1 has reached the preset inventory lower limit, and the remaining amount of coal type A3 is 15t, then when coal type A1 is burned, the coal type is switched. At this moment, the inventory of coal type A1 is 0, and the inventory of coal type A3 is 5t.

[0179] In this embodiment, a preset coal storage range of the raw coal bin is obtained, for example, a preset upper limit of the coal storage is 15t, and a preset lower limit of the coal storage is 3t.

[0180] In this embodiment, when it is monitored that the amount of coal stored in the raw coal bin reaches the preset coal storage lower limit, coal replenishment is performed;

[0181] When it is detected that a raw coal bunker starts to be replenished with coal, the coal storage position of the existing coal types in the raw coal bunker is obtained according to the infrared sensor pre-deployed in the raw coal bunker. At the same time, according to the optimal coal blending and combustion plan, the coal types in the raw coal bunker are obtained. For example, the raw coal bunker already has 2t of coal type A1 and 3t of coal type A3, and the order of coal loading is coal type A1 first and coal type A3 later.

[0182] If the supplementary coal type is the same as the top layer coal type in the original coal bunker, the coal types will be merged. For example, if the original coal bunker already has coal types A1 and A3, the top layer coal type is A3, and the supplementary coal type is A3, then coal type A3 will be merged;

[0183] Otherwise, the coal quantity of the existing coal types is obtained, and the coal loading time of the existing coal types is obtained according to the design output of the raw coal bunker. For example, the coal loading time of coal type A1 is 10 minutes, and the coal loading time of coal type A3 is 5 minutes;

[0184] When it is detected that the amount of coal stored in the raw coal bunker reaches the preset upper limit, the coal replenishment is stopped;

[0185] In this embodiment, the first coal loading map refers to a map of the types and time of loading coal from the raw coal bin to the coal mill. For example, coal A1 is loaded at the current moment, and the estimated loading time is 10 minutes. When the loading of coal type A1 is completed, coal A3 begins to be loaded, and the estimated loading time is 5 minutes.

[0186] In this embodiment, the first moisture content of the coal type refers to the moisture content of the coal type identified by monitoring the raw coal bin.

[0187] In this embodiment, the second moisture content of the coal refers to the moisture content of the coal calculated in the coal mill.

[0188] In this embodiment, when the type of coal in the coal mill changes, the calculated second moisture content will also change accordingly. Therefore, the type of coal in the coal mill can be determined by the second moisture content.

[0189] In this embodiment, there will be a mixture of coal types during the switching process in the raw coal bin, and there will be a certain error in the first moisture content of the coal types. When the moisture content of the switched coal types does not change much, it is difficult to determine the coal type in the coal mill with the second moisture content of the coal types. Therefore, the monitoring results of the raw coal bin are combined with the monitoring results of the coal mill to perform online identification of the coal types.

[0190] In this embodiment, the heat input refers to the heat provided by the hot primary air for drying the coal mill and conveying the coal powder.

[0191] In this embodiment, the heat output is the sum of the heat lost by the coal mill during the coal grinding process and the heat volatilized by the moisture in the coal during the coal grinding process.

[0192] In this embodiment, the first monitoring diagram of the moisture content of the coal type refers to a monitoring diagram of the first moisture content at different coal loading time points obtained from the raw coal bin unit.

[0193] In this embodiment, the second monitoring diagram of the moisture content of the coal type refers to a monitoring diagram of the second moisture content at different outlet time points obtained by the coal mill monitoring unit.

[0194] In this embodiment, when it is determined that the coal mill is in a normal operating state, it is considered that the online identification of the coal type is achieved at this moment.

[0195] The beneficial effect of the above technical solution is: by combining raw coal bin monitoring with pulverizer monitoring, it effectively realizes the online real-time identification of coal types in the actual combustion process, and can predict whether the coal type will be switched and the coal type switching time period, ensuring the safety and efficiency of the blending process.

[0196] The embodiment of the present invention provides a multi-coal optimal blending guidance and control platform, an optimization and update module, including:

[0197] The optimization unit is used to optimize the type and quantity of purchased coal according to the inventory coal quantity, the historical best coal blending and combustion plan, and the best coal blending plan;

[0198] According to the best coal blending and combustion plan, optimize the monitoring and identification of the raw coal bunker, the relevant parameter settings of the coal mill, and the parameter settings of each combustion layer of the boiler;

[0199] The update unit is used to update the inventory coal data, raw coal bunker coal type data, pulverizer related parameter data, boiler combustion layer combustion data and the best coal blending scheme in real time, and store and record the updated data separately by time.

[0200] In this embodiment, the type and quantity of purchased coal are optimized. For example, according to the monitoring results, the coal blending effect of coal type A1, which is the best coal blending scheme, is better, the coal blending effect of coal type A2 is average, and the coal blending effect of coal type A3 is poor. In this way, the purchase amount of coal type A1 is increased, the purchase amount of coal type A2 is reduced, and the purchase of coal type A3 is stopped.

[0201] In this embodiment, when it is monitored that the blending efficiency of the current best coal blending scheme is lower than the overall blending effect of a certain historical best coal blending scheme, if all the coal types of the corresponding historical best coal blending scheme can be purchased, the best coal blending scheme is optimized and updated.

[0202] In this embodiment, the update data is stored and recorded separately by time. When the best coal blending and combustion scheme needs to be optimized and updated, the relevant data basis can be obtained from the historical storage data for design, which simplifies the design difficulty.

[0203] The beneficial effects of the above technical solution are: based on the monitoring results, the best coal blending and combustion scheme is optimized and updated, ensuring the best combustion efficiency in each operating stage of the combustion equipment and maximizing combustion safety; updating and storing relevant data is conducive to later data viewing and optimizing and adjusting the best coal blending and combustion scheme based on historical data.

[0204] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A multi-coal blending guidance and control platform, characterized in that: include: Data collection module: According to the types of coal in stock, obtain the coal quantity, moisture, ash, sulfur and volatile matter of the coal in stock, establish a multi-coal database, and at the same time, obtain the parameter data of the combustion device; Coal blending and combustion module: Based on the multi-coal database and the parameter data of the combustion device, with the quantity of the stored coal, the combustion characteristic index and the safety of the combustion device as constraints, and the multi-coal blending and combustion efficiency as the objective function, the optimal coal blending and combustion plan is calculated; Transportation module: According to the optimal coal blending and combustion plan and the remaining amount of coal in stock, the corresponding optimal coal blending and transportation plan is automatically generated, and the corresponding proportion of coal is transported to the corresponding combustion device; Monitoring and identification module: monitors the remaining amount of coal in stock during the blending and burning of multiple coal types, and monitors the combustion process and blending process in the corresponding combustion device; Optimization and update module: optimize and adjust the best coal blending and combustion scheme according to the monitoring results; Among them, the monitoring and identification module includes: Inventory coal monitoring unit, used to monitor the remaining inventory coal during the blending and burning of multiple coal types; When it is monitored that the remaining amount of a certain stock of coal reaches the preset stock lower limit, if the coal blending plan is changed, a new type of coal will be switched after the blending of the stock of coal is completed; Otherwise, coal replenishment alarm data corresponding to the inventory coal is generated, and coal replenishment is carried out in time; A raw coal bunker monitoring unit is used to monitor the type of coal loaded into each raw coal bunker at each time, and construct a first coal loading map, wherein the first coal loading map includes: coal loading time points of different types of coal; According to the type of coal loaded in the same coal loading time period, the first moisture content of the corresponding coal type is determined from the type-moisture content mapping table; The coal mill monitoring unit is used to monitor the coal powder fineness of the coal mill outlet area and the outlet time period consistent with each coal loading time period in the first coal loading diagram according to the coal transmission mechanism between the raw coal bunker and the coal mill and in combination with the pre-deployed infrared sensor in the coal mill outlet area; Based on the coal powder fineness, the initial coal powder moisture C0 at each outlet time point is obtained from the original coal fineness-coal powder fineness-moisture mapping table; The heat input of the coal mill is obtained according to the temperature sensors pre-deployed at the inlet and outlet of the coal mill; in, is the heat input of the coal mill; is the hot primary air flow rate of the coal mill; is the specific heat capacity of air at the average temperature of the coal mill in operation; The hot air temperature is measured by the temperature sensor at the coal mill inlet; The pulverized coal temperature measured by the temperature sensor at the coal mill outlet; Obtain the heat output of the coal mill; in, is the heat output of the coal mill; Heat loss in the coal mill during the coal grinding process; The heat of volatilization of coal moisture during the coal pulverizing process in the coal mill; According to the heat balance calculation of the coal mill, the second moisture content of the coal in the coal mill is obtained; Wherein, C1 represents the second moisture at the corresponding outlet time point; represents the moisture conversion coefficient; It represents the total energy of the coal mill at the corresponding outlet time point; A coal type identification unit, used for drawing a first monitoring diagram according to the first moisture at different coal loading time points obtained by the raw coal bunker unit; Draw a second monitoring graph according to the second moisture at different outlet time points obtained by the coal mill monitoring unit; Performing alignment processing on the first monitoring graph and the second monitoring graph with consistent time conversion, randomly selecting n1 sequence values ​​from the first alignment graph and the second alignment graph, performing fitting processing on the first alignment graph and the second alignment graph, and selecting fitting values ​​consistent with the time points corresponding to the n1 sequence values; Calculate the fitting degree of the first monitoring graph and the second monitoring graph; in, is the degree of fit of the first monitoring graph and the second monitoring graph; y1i represents the ith sequence value selected in the first alignment graph; x1i represents the ith fitting value selected in the first alignment graph; y2i represents the ith sequence value selected in the second alignment graph; x2i represents the ith fitting value selected in the second alignment graph; y1p represents the average value of the fitting values ​​selected in the first alignment graph; y2p represents the average value of the fitting values ​​selected in the second alignment graph; y1j represents the sequence value belonging to the first alignment graph in the jth fluctuation pair; y2j represents the sequence value belonging to the second alignment graph in the jth fluctuation pair; When the fitting degree of the first monitoring diagram and the second monitoring diagram is greater than the preset fitting degree, it is determined that the coal mill is in a normal operating state; Otherwise, adjust the relevant parameters of the coal mill, re-obtain the second moisture content of the coal in the coal mill and perform the fitting calculation.

2. A multi-coal blending guidance and control platform as claimed in claim 1, characterized in that: Data collection module, including: Coal data collection unit, used to obtain the types of coal in stock; According to the types of coal in stock, obtain the storage quantity, moisture, ash, sulfur and volatile matter of each type of coal in stock; The database unit is used to sort the various types of inventory coal in descending order according to the volatile matter of coal, and at the same time, establish a database of multiple coal types.

3. A multi-coal blending guidance and control platform as claimed in claim 1, characterized in that: Data collection module, including: The combustion device comprises: a raw coal bunker, a coal mill and a boiler; The parameter data of the combustion device include: the total number of raw coal bunkers and the coal storage capacity of each raw coal bunker, the total number of coal mills, the number of combustion layers of the boiler and the safety index of each combustion layer.

4. A multi-coal blending guidance and control platform as claimed in claim 1, characterized in that: Coal blending module, including: The constraint unit is used to establish the constraint conditions for coal blending based on the database of multiple coal types, combustion characteristic index and the safety of the combustion device; The target unit is used to establish the target function of coal blending and combustion according to the efficiency of coal blending and combustion of multiple coal types; The coal blending and combustion unit is used to determine the type of coal to be blended and burned according to the constraints and the objective function; According to the number of coal types and the coal blending ratio of each coal type, the corresponding coal blending array is obtained, the coal blending ratio is divided into n intervals, and the coal blending scheme is initialized and generated according to the orthogonal design method; Construct the fitness function of coal types according to the objective function and calculate the fitness of each initialization coal blending scheme; According to the fitness, each initialization coal blending scheme is sorted from large to small, and the first m initialization coal blending schemes are selected and used as the first coal blending scheme; Perform crossover and mutation operations on each first coal blending scheme to generate a new coal blending scheme; The fitness of each new coal blending scheme is recalculated, and the scheme corresponding to the highest fitness is selected as the optimal coal blending scheme.

5. A multi-coal optimal blending and combustion guidance and control platform as claimed in claim 1, characterized in that: Shipping module, including: The transport unit is used to transport the required coal types to the corresponding raw coal bunker according to the optimal coal blending and combustion plan; When the optimal coal blending and combustion plan is monitored to change, the coal transportation plan is adjusted accordingly; When the coal replenishment alarm data from the inventory coal / raw coal bin is received, the corresponding coal replenishment transportation is carried out according to the optimal coal blending and combustion plan.

6. A multi-coal optimal blending guidance and control platform as claimed in claim 1, characterized in that: Monitoring and identification module, including: The combustion process monitoring unit is used to monitor the combustion status of each combustion layer of the boiler; The wall temperature monitoring unit is used to obtain the wall temperature data of multiple monitoring points in each combustion layer, obtain the average wall temperature data of each combustion layer after analysis and processing, and obtain the overall wall temperature safety of the boiler according to the combustion layer-safety mapping table; The combustion efficiency monitoring unit is used to obtain the comprehensive coal quality of the multi-coal blending combustion according to the coal quantity, moisture, ash content, sulfur content and volatile matter of each coal type in the optimal coal blending combustion plan; Based on the combustion state monitoring results, the exhaust heat loss, chemical incomplete combustion heat loss, mechanical incomplete combustion heat loss, heat dissipation loss and ash physical heat loss in the combustion process are obtained, and the combustion efficiency of the boiler is calculated; The emission monitoring unit is used to obtain the combustion emission parameters and calculate the emission index of the boiler according to the preset emission evaluation index and the weight of each emission parameter; Among them, the monitoring results of the combustion process include: overall boiler wall temperature safety, comprehensive coal quality, combustion efficiency and emission index.

7. A multi-coal optimal blending and combustion guidance and control platform as claimed in claim 1, characterized in that: Optimized update modules, including: The optimization unit is used to optimize the type and quantity of purchased coal according to the inventory coal quantity, the historical best coal blending and combustion plan, and the best coal blending plan; According to the best coal blending and combustion plan, optimize the monitoring and identification of the raw coal bunker, the relevant parameter settings of the coal mill, and the parameter settings of each combustion layer of the boiler; The update unit is used to update the inventory coal data, raw coal bunker coal type data, pulverizer related parameter data, boiler combustion layer combustion data and the best coal blending scheme in real time, and store and record the updated data separately by time.

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