CN-116167562-B - Intelligent optimization method and equipment for open pit coal production and marketing

CN116167562BCN 116167562 BCN116167562 BCN 116167562BCN-116167562-B

Abstract

The invention discloses an intelligent optimization method and equipment for production and marketing of coal in an opencast coal mine, which divide a mining coal seam into a plurality of subareas based on original geological information and establish a coal seam data model, establish a coal washery data model based on the screened coal quantity, the gangue rate and various coal quality test information of a screening workshop of the coal washery, determine the corresponding relation between the coal seam data model and the coal washery data model, determine the screened coal quantity based on a long-term protocol of a power plant and a unit running state, regulate the screening proportion of the screened coal quantity and the lump coal of the refined coal based on the corresponding relation, and establish an optimal sales scheme.

Inventors

WANG YONGLI
LIU HONGYU
SHI XIAODONG
HAN YU
DUAN XIAOLEI
JIANG BO
CHEN JIAN
GAO MIN
WANG JINLONG

Assignees

北方魏家峁煤电有限责任公司

Dates

Publication Date: 20260505
Application Date: 20221205

Claims (6)

1. An intelligent optimization method for coal production and marketing of an opencast coal mine is characterized by comprising the following steps: Dividing the mined coal seam into a plurality of subareas based on the original geological information, and establishing a coal seam data model; Establishing a coal washery data model based on the screened coal quantity, the undersize coal quantity, the gangue rate and the coal quality test information of each coal type in a coal washery screening workshop, and determining the corresponding relation between the coal seam data model and the coal washery data model; Determining the undersize coal quantity based on a power plant long-term protocol and a unit running state, adjusting the screening proportion of the undersize coal quantity and the lump coal size based on the corresponding relation, and making an optimal sales scheme; dividing the mined coal seam into a plurality of subareas based on the original geological information, and establishing a coal seam data model, wherein the method specifically comprises the following steps: performing reconnaissance drilling on the mined coal seam based on the original geological information, and dividing the mined coal seam into a plurality of subareas; Determining a coal pillar structure in each partition, wherein the coal pillar structure comprises a coal calorific value, the hardness of coal and a gangue content; determining the coal bed structure and coal quality information of each partition based on the coal pillar structure, and establishing a coal bed data model; The unit operation state comprises a full load state and a low load state; The undersize coal quantity is determined based on a power plant long-term protocol and a unit running state, and the screening proportion and the clean coal block size of the undersize coal quantity are adjusted based on the corresponding relation, specifically: Respectively determining a first undersize coal quantity of the power plant in a full load state and a second undersize coal quantity of the power plant in a low load state; determining a first on-screen coal amount and a second on-screen coal amount based on the first undersize coal amount and the second under-sun coal amount respectively, wherein the first on-screen coal amount is the on-screen coal amount remained in the coal washing plant in a full load state of the power plant, and the second on-screen coal amount is the on-screen coal amount remained in the coal washing plant in a low load state of the power plant; Adjusting the screening proportion and the lump coal of the first screened coal amount or the second screened coal amount based on the corresponding relation, and determining an optimal sales scheme; The method further comprises the steps of: Determining a mining plan of each partition of the mining coal seam based on the running state and the corresponding relation, and mining coal according to the mining plan; and adjusting the blasting hole network parameters or the charging structure of the mining plan based on the optimal sales scheme so as to realize adjustment of the coal block size.
2. An intelligent optimization device for open pit coal production and marketing, which is used for realizing the intelligent optimization method for open pit coal production and marketing according to claim 1, and is characterized in that the device comprises: the building module is used for dividing the mined coal seam into a plurality of subareas based on the original geological information and building a coal seam data model; The determining module is used for establishing a coal washery data model based on the screened coal quantity, the undersize coal quantity, the gangue rate and the coal quality test information of various coals in a coal washery screening workshop, and determining the corresponding relation between the coal seam data model and the coal washery data model; and the formulating module is used for determining the undersize coal quantity based on a power plant long-term protocol and a unit running state, regulating the screening proportion of the undersize coal quantity and the lump coal size based on the corresponding relation, and formulating an optimal selling scheme.
3. The apparatus of claim 2, wherein the setup module is specifically configured to: performing reconnaissance drilling on the mined coal seam based on the original geological information, and dividing the mined coal seam into a plurality of subareas; Determining a coal pillar structure in each partition, wherein the coal pillar structure comprises a coal calorific value, the hardness of coal and a gangue content; and determining the coal bed structure and coal quality information of each partition based on the coal pillar structure, and establishing a coal bed data model.
4. The apparatus of claim 2, wherein the unit operating conditions include a full load condition and a low load condition.
5. The apparatus of claim 4, wherein the formulation module is specifically configured to: Respectively determining a first undersize coal quantity of the power plant in a full load state and a second undersize coal quantity of the power plant in a low load state; determining a first on-screen coal amount and a second on-screen coal amount based on the first undersize coal amount and the second under-sun coal amount respectively, wherein the first on-screen coal amount is the on-screen coal amount remained in the coal washing plant in a full load state of the power plant, and the second on-screen coal amount is the on-screen coal amount remained in the coal washing plant in a low load state of the power plant; and adjusting the screening proportion and the lump coal of the first screened coal amount or the second screened coal amount based on the corresponding relation, and determining an optimal sales scheme.
6. The apparatus of claim 5, wherein the apparatus is further configured to: Determining a mining plan of each partition of the mining coal seam based on the running state and the corresponding relation, and mining coal according to the mining plan; and adjusting the blasting hole network parameters or the charging structure of the mining plan based on the optimal sales scheme so as to realize adjustment of the coal block size.

Description

Intelligent optimization method and equipment for open pit coal production and marketing Technical Field The application relates to the field of intelligent production of coal, in particular to an intelligent optimization method and equipment for production and marketing of coal in an open pit coal mine. Background The current coal-electricity integrated project production organization process is used for supplying coal basically according to the requirements of a coal flow system and the operation flow of coal mines, coal washery and power plants. The daily coal mining amount of the coal mine site organizes coal feeding according to the actual condition of raw coal storage coal and the coal storage amount of a finished product bin of a coal washing plant, the refined coal sales amount of the coal washing plant adjusts the screening amount according to market demands and the refined coal amount of the finished product bin and experience prediction, and the coal used by a power plant coordinates coal feeding of the coal mine organization according to the specific conditions of the coal storage bins of the coal mine bin and the power plant under the condition of meeting the requirement of unit load. Because the production organization of the coal-electricity integrated project, the clean coal sales and the coal consumption of the power plant only distribute the coal amount according to a single supply-demand relationship. The coal quality information on the production side of the coal mine can be obtained temporarily only by a mode of production along with test, the coal quality information of the mined coal seam can not be obtained in advance, and further the reference proportion of high-quality coal and low-heat value coal can not be determined, and the production organization only considers the supply according to the coal quantity. The coal washery side carries out washing according to the coal loading quantity in the coal mine site, and washing medium and gangue content can not be determined in advance, and the variation range of the clean coal output is great, and the clean coal calorific value can not be predicted in advance according to customer requirements, so that the sales vehicles are scientifically allocated. The coal used in the power plant also lacks a fixed coal supply mode determined according to long-term coordination and high-low load. Coal production, marketing and power generation lack a scientific and intelligent optimization method. Therefore, how to provide an intelligent optimization method for the production and marketing of coal in an opencast coal mine, which is used for realizing the linkage among coal production, sales and power plants and the intelligent management of the whole flow of coal production, becomes a technical problem to be solved in the field. Disclosure of Invention The invention provides an intelligent optimization method for production and marketing of coal in an opencast coal mine, which is used for solving the problem that coal quantity distribution is only carried out according to a single supply-demand relationship among production organizations, clean coal sales and coal used in a power plant in the coal-electricity integrated project in the prior art, and comprises the following steps: Dividing the mined coal seam into a plurality of subareas based on the original geological information, and establishing a coal seam data model; Establishing a coal washery data model based on the screened coal quantity, the undersize coal quantity, the gangue rate and the coal quality test information of each coal type in a coal washery screening workshop, and determining the corresponding relation between the coal seam data model and the coal washery data model; And determining the undersize coal quantity based on a power plant long-term protocol and a unit running state, adjusting the screening proportion of the undersize coal quantity and the lump coal size based on the corresponding relation, and making an optimal sales scheme. In some embodiments of the present application, the mined coal seam is divided into a plurality of sections based on the original geological information, and a coal seam data model is built, specifically: performing reconnaissance drilling on the mined coal seam based on the original geological information, and dividing the mined coal seam into a plurality of subareas; Determining a coal pillar structure in each partition, wherein the coal pillar structure comprises a coal calorific value, the hardness of coal and a gangue content; and determining the coal bed structure and coal quality information of each partition based on the coal pillar structure, and establishing a coal bed data model. In some embodiments of the application, the unit operating conditions include a full load condition and a low load condition. In some embodiments of the present application, the undersize coal amount is determined based on a long-term power plant protocol and