Power plant coal yard fuel allocation and transportation method and related device

Abstract

The invention discloses a power plant coal yard fuel allocation and transportation method and a related device, and belongs to the technical field of coal yard fuel allocation and transportation. The method comprises the following steps: acquiring coal transport vehicle data, road weather condition data and power plant coal storage condition data; inputting the vehicle data, the road weather condition data and the power plant coal storage condition data into a pre-established optimal scheduling model based on a multi-objective optimization algorithm, and outputting an optimal driving route of the coal car; obtaining unit daily output demands, and planning an out-of-plant coal transportation vehicle reservation queuing scheme in combination with power plant coal storage condition data; and the transportation path deviation condition and the vehicle performance abnormal condition of the coal transport vehicle are monitored in real time, and the abnormal vehicle is alarmed. According to the method, a data chain between vehicle transportation and in-plant demands is opened, an allocation and transportation scheme adaptive to power plant fire coal control demands can be generated according to real-time road conditions, weather dynamics, in-plant unit load demands and a coal yard stockpiling structure, and the coordination of an allocation and transportation system is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of fuel transportation and dispatching in coal yards, and relates to a method and related device for fuel transportation and dispatching in a power plant coal yard. Background Art

[0002] Under the background of the global energy structure accelerating towards cleaner and lower-carbon transformation, thermal power generation, as an important pillar of traditional energy supply, is facing unprecedented challenges and opportunities. On the one hand, with the gradual increase in the proportion of renewable energy power generation, the power market has put forward higher requirements for the flexibility and response speed of thermal power plants; on the other hand, in order to enhance competitiveness and reduce operating costs, thermal power plants pay more and more attention to the refined management and efficient operation of the fuel supply chain.

[0003] At present, the fuel supply chain of thermal power plants shows significant characteristics of diversified coal source points, which not only increases the complexity of transportation and dispatching management, but also puts forward higher requirements for the timeliness and accuracy of transportation and dispatching. However, the traditional coal transportation and dispatching mode still mainly relies on manual experience and static planning, and it is difficult to adapt to the dynamic market environment and complex transportation conditions, resulting in a series of management problems that need to be solved urgently.

[0004] Specifically, the existing transportation and dispatching system has the following problems: ①Lag in data perception: Key information such as the position, status, and road environment of transportation vehicles lacks real-time collection, resulting in untimely responses of transportation and unloading plans; ②Inefficient collaborative scheduling: The links of vehicle queuing, coal unloading operations, and inventory management are fragmented, the utilization rate of spatio-temporal resources is insufficient, and the efficiency of coal transportation and warehousing is low; ③Passive response to anomalies: There is a lack of effective prediction means for abnormal situations, inventory risks, and supply chain compliance issues during vehicle transportation.

[0005] In summary, the existing transportation and dispatching system has a lag in data perception, low collaborative scheduling efficiency, and a lack of effective prediction and warning means for abnormal situations, which affects the operation and management of power plants. Summary of the Invention

[0006] The purpose of the present invention is to provide a method and related device for fuel transportation and dispatching in a power plant coal yard to solve the technical problem that the collaborative scheduling efficiency of the existing transportation and dispatching system is low and affects the operation and management of power plants.

[0007] To achieve the above object, the present invention adopts the following technical solutions: In the first aspect, the present invention provides a method for fuel transportation and dispatching in a power plant coal yard, including the following steps: Obtain data of coal transportation vehicles, road meteorological conditions, and coal storage conditions in the power plant; Input the vehicle data, road meteorological condition data, and coal storage condition data in the power plant into an optimal scheduling model based on a multi-objective optimization algorithm established in advance, and output the best driving route of the coal transportation vehicle; Obtain the daily output demand of the unit, combine it with the data on the coal storage situation in the power plant, and plan the reservation and queuing scheme for the coal transportation vehicles outside the plant; Real-time monitor the transportation path deviation and abnormal vehicle performance of the coal transportation vehicles, and alarm the abnormal vehicles.

[0008] Furthermore, the data of the coal transportation vehicles includes the positioning of the vehicle's real-time position, the identity of the vehicle and the driver, the vehicle's driving speed, the vehicle's exhaust emissions, and the coal transportation situation; the data of the road meteorological conditions includes the road congestion situation, the construction situation, the likelihood of traffic accidents in each section, the temperature, the precipitation probability, the wind force level, the visibility, and the AQI air quality index; the data of the coal storage situation in the power plant includes the coal stockpile in the coal yard, the coal storage structure, the suppliers in each section of the coal yard, the coal type, the mine type, the stockpile quantity, the stockpile days, and the coal storage temperature.

[0009] Furthermore, the objective function of the optimal scheduling model based on the multi-objective optimization algorithm is a weighted function with the minimum transportation cost, the shortest transportation time, and the minimum calorific value loss; the constraint conditions of the optimal scheduling model based on the multi-objective optimization algorithm include vehicle load, coal yard capacity, and the arrival probability of the vehicle within the expected time period.

[0010] Furthermore, the arrival probability of the vehicle within the expected time period is predicted by an LSTM neural network model, and the input variables of the LSTM neural network model include the departure location, weather forecast, and historical and real-time road conditions.

[0011] Furthermore, the steps of obtaining the daily output demand of the unit, combining it with the data on the coal storage situation in the power plant, and planning the reservation and queuing scheme for the coal transportation vehicles outside the plant specifically include: According to the daily output demand of the unit and the current coal storage structure in the power plant, plan the reservation and queuing system for the coal transportation vehicles outside the plant; according to the weight of the coal type to be transported, assign different queuing priorities, in-plant coal unloading stacking schemes, and in-plant metering and weighing point schemes to the coal transportation vehicles.

[0012] Furthermore, the steps of real-time monitoring the transportation path deviation and abnormal vehicle performance of the coal transportation vehicles, and alarming the abnormal vehicles specifically include: Based on the clustering analysis of SVM, analyze the number of times the vehicle deviates from the planned path, the length of the deviated path, and the characteristics of the deviated route, analyze the overtime transportation duration of the vehicle, the overtime ratio of each section, and the corresponding overtime frequency, and associate the vehicle driver, carrier, supplier, mine site, and coal type information to detect abnormal vehicle lane changes, stops, problematic carriers, and suppliers; Analyze the data of the vehicle engine and exhaust emissions sensors in the vehicle-mounted Internet of Things terminal to detect abnormal vehicle performance, alarm the abnormal vehicles, and stop the dispatching operation.

[0013] Second aspect, the present invention provides a fuel transportation and dispatching system for a power plant coal yard, including: A data acquisition module, configured to acquire data of coal transportation vehicles, road meteorological conditions, and coal storage conditions in the power plant; A route planning module, configured to input the vehicle data, road meteorological condition data, and coal storage condition data in the power plant into an optimal scheduling model based on a multi-objective optimization algorithm established in advance, and output the best driving route of the coal transportation vehicle; A queuing planning module, configured to acquire the daily power generation demand of the unit, and combine with the coal storage condition data in the power plant to plan a reservation queuing scheme for the coal transportation vehicles outside the plant; A monitoring and warning module, configured to monitor in real time the transportation path deviation of the coal transportation vehicle and the abnormal vehicle performance, and give an alarm to the abnormal vehicle.

[0014] Further, the system further includes: An intelligent scheduling and monitoring module, configured to display the real-time road conditions outside the plant, vehicle positions, and meteorological dynamics in the form of a digital map according to the real-time coal storage situation in the coal yard; endow the route planning module with the function of generating and issuing a planned route, and the function of the on-site dispatcher manually setting and issuing a route; endow the on-site dispatcher with the function of real-time communication with the driver through the vehicle-mounted Internet of Things terminal.

[0015] Third aspect, the present invention provides a computer 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, the steps of a fuel transportation and dispatching method for a power plant coal yard as described above are implemented.

[0016] Fourth aspect, the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of a fuel transportation and dispatching method for a power plant coal yard as described above are implemented.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The present invention discloses a fuel transportation method and related devices for a power plant coal yard. By accessing data on coal-carrying vehicles, road weather conditions, and coal storage conditions in power plants, it is possible to capture various key information in the transportation process in real time, providing a solid data foundation for subsequent decision-making analysis, and ensuring real-time perception and accurate grasp of the basic conditions of transportation. By opening up the data chain between vehicle transportation and in-plant demand, the present invention can intelligently generate a set of transportation plans that are highly adapted to the coal management and control needs of power plants through comprehensive analysis of real-time road conditions and weather dynamics, as well as changes in load demand of in-plant units and storage structure characteristics of coal yards. This plan not only takes into account the balance between transportation efficiency and cost-effectiveness, but also fully integrates the actual needs of power plant production and operation, effectively improving the overall coordination and response speed of the transportation system, and ensuring the stability and efficiency of coal supply. At the same time, the transportation data is analyzed, abnormal situations are deeply explored, and the ability to locate and detect abnormalities in the transportation process is strengthened. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 is a flow chart of the method of the present invention; Figure 2 is a schematic diagram of the system of the present invention; Figure 3 It is a schematic diagram of the computer device structure of the present invention. DETAILED DESCRIPTION

[0020] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that, unless there is a conflict, the embodiments and features in the embodiments of the present application can be combined with each other.

[0021] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise indicated, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present invention.

[0022] See also Figure 1 The embodiment of the present invention discloses a fuel transportation method for a power plant coal yard, comprising the following steps: S1, obtain data on coal transport vehicles, road weather conditions, and coal storage status of power plants; In this step, the coal transport vehicle data includes the positioning of the vehicle's real-time location, the identity of the vehicle and the driver, the vehicle's driving speed, the vehicle's exhaust emissions, and the coal transport situation; the road meteorological situation data includes the road congestion situation, the construction situation, the likelihood of traffic accidents in sections, temperature, precipitation probability, wind force level, visibility, and AQI air quality index; the coal storage situation data in the power plant includes the coal stock in the coal yard, the coal storage structure, the suppliers in each section of the coal yard, coal types, mine types, stockpiles, storage days, and the coal storage temperature.

[0023] S2. Input the vehicle data, road meteorological situation data, and coal storage situation data in the power plant into the optimal scheduling model based on the multi-objective optimization algorithm established in advance, and output the best driving route for the coal transport vehicle. In this step, the objective function of the optimal scheduling model based on the multi-objective optimization algorithm is a weighted function with the minimum transportation cost, the shortest transportation time, and the minimum calorific value loss; the constraints of the optimal scheduling model based on the multi-objective optimization algorithm include vehicle load, coal yard capacity, and the arrival probability of the vehicle within the expected time period.

[0024] Preferably, the arrival probability of the vehicle within the expected time period is predicted by the LSTM neural network model, and the input variables of the LSTM neural network model include the departure location, weather forecast, and historical and real-time road conditions.

[0025] S3. Obtain the daily output demand of the unit, and combine it with the coal storage situation data in the power plant to plan the reservation queuing scheme for the coal transport vehicles outside the plant. In this step, according to the daily output demand of the unit and the current coal storage structure in the power plant, plan the reservation queuing system for the coal transport vehicles outside the plant; according to the weight of the coal types transported, assign different queuing priorities, in-plant coal unloading stacking schemes, and in-plant metering weighing point schemes to the coal transport vehicles.

[0026] S4. Real-time monitor the transportation path deviation situation and vehicle performance abnormality situation of the coal transport vehicle, and alarm the abnormal vehicle.

[0027] Based on the clustering analysis of SVM, analyze the number of times the vehicle deviates from the planned path, the deviation path length, and the characteristics of the deviation route, analyze the overtime transportation duration of the vehicle, the overtime ratio of each section, and the corresponding overtime frequency, and associate the information of the vehicle driver, carrier, supplier, mine site, and coal type to realize the detection of abnormal vehicle lane changes, stops, problematic carriers, and suppliers. Analyze the vehicle engine and exhaust emission sensor data in the vehicle-mounted Internet of Things terminal, detect the vehicle performance abnormality situation, alarm the abnormal vehicle, and stop the dispatching operation.

[0028] See Figure 2 , this embodiment of the present invention discloses a fuel dispatching system for a power plant coal yard, including: Data acquisition module, which realizes the real-time perception of coal transportation vehicles, road meteorological conditions, and the coal storage situation in power plants. Among them, for coal transportation vehicles, by installing Internet of Things intelligent terminals, comprehensive data collection is achieved, including the real-time position of the vehicle, the identity of the vehicle and the driver, the vehicle driving speed, exhaust emissions, coal transportation situation, etc.; for road meteorological data, by connecting to the Internet map engine and meteorology, road conditions and meteorological data are extracted in real time, realizing the real-time acquisition of data such as road congestion, construction conditions, whether traffic accidents are prone to occur in sections, temperature, precipitation probability, wind force level, visibility, AQI air quality index, etc.; for the coal storage situation in power plants, by docking with the fuel information system or digital coal yard system on the plant side, the coal stock and storage structure in the coal storage yard are obtained, realizing the acquisition of information such as suppliers, coal types, mine names, stockpiles, stockpile days, coal storage temperature, etc. in each section of the coal yard.

[0029] Route planning module, which uses a multi-objective optimization algorithm. By weighting the transportation cost, transportation time, and calorific value loss, and taking vehicle load, coal yard capacity, the probability of the vehicle arriving within the expected time period, etc. as constraint conditions, optimal scheduling plans with different focuses are generated and the driving routes are issued to the coal transportation vehicles.

[0030] Queue planning module, which coordinates the scheduling inside and outside the coal yard, integrating the expected arrival situation of vehicles, truck scales, the coal yard inventory situation, and the coal blending requirements of the units; among them, the probability of vehicles arriving at different time periods is predicted using an LSTM neural network model, and the input variables include the departure location, weather forecast, historical and real-time road conditions, etc.; in particular, according to the daily unit output requirements and the current coal storage structure in the coal yard, a reservation queuing system for coal transportation vehicles outside the plant is planned, and different vehicle queuing priorities, in-plant coal unloading stacking plans, in-plant weighing and weighing point plans, etc. are assigned according to the weight of the coal types transported.

[0031] Monitoring and warning module, which uses clustering analysis based on SVM to analyze the number of times the vehicle deviates from the planned path, the length of the deviation path, the characteristics of the deviation route, etc., analyzes the vehicle overtime transportation duration, the overtime ratio of each section, and the corresponding overtime frequency, and correlates information such as vehicle drivers, carriers, suppliers, mine sites, coal types, etc. to realize the detection of abnormal vehicle lane changes, stops, and problematic carriers and suppliers. In particular, by analyzing the sensor data of the vehicle engine, exhaust emissions, etc. in the on-vehicle Internet of Things terminal, the abnormal vehicle performance is detected, and an alarm is issued for the abnormal vehicle condition and the dispatching operation is stopped.

[0032] Intelligent scheduling and monitoring module, which uses digital twins to monitor the real-time situation of coal storage in the coal yard, and uses digital maps to display the real-time road conditions outside the plant, vehicle positions, and meteorological dynamics. It is given the function of issuing the planned path generated by the dispatching analysis decision engine, as well as the function of the on-site dispatcher manually setting the path and issuing it. The on-site dispatcher is given the function of real-time communication with the driver through the on-vehicle Internet of Things terminal.

[0033] Embodiment: The fuel transportation method for the coal yard of the power plant in this embodiment includes three major parts: a data perception platform, a transportation analysis and decision-making engine, and abnormal transportation detection; specifically as follows: I. Data perception platform The in-vehicle Internet of Things terminal uses Beidou+GPS dual-mode positioning, collects parameters such as engine speed, fuel consumption, and fault codes through the OBD-II in-vehicle diagnostic system communication protocol, and uses a pressure strain gauge type in-vehicle weighing module to sense vehicle weight data. The positioning data is collected at least once every 10 seconds, and the load data is collected at least once every minute. Abnormal events (such as speeding, sudden braking, mechanical failures, deviation from the planned path), etc., trigger alarms in real time. In particular, the collected data is encrypted using AES symmetric encryption.

[0034] Access the Amap or Baidu Map API to obtain the real-time information of each road section, and collect it at least once every 10 minutes; access the short-term and nowcasting of the Central Meteorological Observatory to obtain meteorological data with a 1km grid accuracy.

[0035] Obtain real-time three-dimensional point cloud data of the coal pile through the OPC protocol with the digital coal yard system, and ensure the data accuracy of ±20cm. According to the matching of the coal batch with the fuel information system on the plant side, obtain the coal storage structure in each coal quality interval in each section.

[0036] II. Transportation analysis and decision-making engine After triggering traffic condition or meteorological alarms, and alarms for the demand of coal quantity and quality for the coal-fired unit load, generate constraint conditions such as vehicle load, coal yard capacity, and the probability of the vehicle arriving within the expected time period, and perform weighted calculation on transportation cost, transportation time, and calorific value loss to obtain the optimal transportation plan. For example, according to the Amap API, if the vehicle congestion index at a certain main road is congested, and the current unit load requires coal with a calorific value of 4000 kCal / kg, and through the analysis of the coal yard structure, it is obtained that the current inventory coal quantity only meets the usage for 8 hours. At this time, the decision weight will be adjusted, reducing the weight of transportation cost and increasing the weights of transportation time and calorific value loss. The sum of the calorific values of the coal carried by vehicles with a probability of arrival above 85% within the next 24 hours is ≥ 12 hours * 1000 tons / hour consumption rate, and the NSGA-II algorithm is used to generate a set of Pareto optimal solutions and output 5 groups of optimal solutions for the dispatcher to choose.

[0037] In particular, use the LSTM neural network to predict the vehicle arrival probability. Input the departure location coordinates, real-time traffic conditions, and vehicle performance parameter records, and output the vehicle arrival probability for each time period within the next several time periods, with a time period resolution of not less than 15 minutes.

[0038] III. Abnormal transportation detection Grab the batches arriving at the factory from a certain supplier in the past 60 days, analyze data such as the carrier and the shipping route in the grabbed batches, including the number of times deviating from the planned route, the deviation distance, the coordinates of the deviation section, the number of mid-course stops, the coordinates of the stop positions, the quality of the coal transported under the contract, and the actual sampled coal quality. Construct a dynamic two-fluctuation index, use SVM to identify data deviating from the normal threshold range, and use a graph neural network to identify the carrier and the supplier.

[0039] In one embodiment of the present invention, refer to Figure 3 , a computer device is provided. The computer device includes a processor and a memory. The memory is used to store a computer program. The computer program includes program instructions. The processor is used to execute the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function. The processor described in the embodiment of the present invention can be used for the operation of a method for fuel transfer in a power plant coal yard.

[0040] The present invention also provides a storage medium, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in a computer device, used to store programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device, and of course can also include the extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, and this storage space stores the operating system of the terminal. And, one or more instructions suitable for being loaded and executed by the processor are stored in this storage space. These instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory, or a non-volatile memory, such as at least one disk memory. One or more instructions stored in the computer-readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the method for fuel transfer in a power plant coal yard in the above embodiment.

[0041] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0042] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0043] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means realizes the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0044] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: still modifications or equivalent replacements can be made to the specific embodiments of the present invention, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. A method for fuel transportation and allocation in a power plant coal yard, characterized in that, It includes the following steps: Obtain the data of coal transport vehicles, road meteorological conditions, and the coal storage situation in the power plant; Input the vehicle data, road meteorological conditions data, and the coal storage situation data in the power plant into the pre-established optimal scheduling model based on the multi-objective optimization algorithm, and output the best driving route of the coal transport vehicle; Obtain the daily output demand of the unit, and combine it with the coal storage situation data in the power plant to plan the reservation queuing scheme for the coal transport vehicles outside the plant; Real-time monitor the transport path deviation situation and vehicle performance abnormality situation of the coal transport vehicle, and give an alarm for the abnormal vehicle.

2. The method for fuel transfer and transportation in a coal yard of a power plant according to claim 1, characterized in that The coal transport vehicle data includes the positioning of the vehicle's real-time position, the identities of the vehicle and the driver, the vehicle's driving speed, the vehicle's exhaust emissions, and the coal transport situation; the road meteorological conditions data includes the road congestion situation, construction situation, whether traffic accidents are likely to occur in the section, temperature, precipitation probability, wind force level, visibility, and AQI air quality index; the coal storage situation data in the power plant includes the coal stock in the coal yard, the coal storage structure, the suppliers in each section of the coal yard, coal types, mine types, stockpiles, stockpiling days, and the coal storage temperature.

3. The method for fuel transportation and transfer in a power plant coal yard according to claim 1, wherein The objective function of the optimal scheduling model based on the multi-objective optimization algorithm is a weighted function with the minimum transport cost, the shortest transport time, and the minimum calorific value loss; the constraint conditions of the optimal scheduling model based on the multi-objective optimization algorithm include vehicle load, coal yard capacity, and the arrival probability of the vehicle within the expected time period.

4. A fuel transfer method for a coal yard in a power plant according to claim 3, characterized in that, The arrival probability of the vehicle within the expected time period is predicted by the LSTM neural network model, and the input variables of the LSTM neural network model include the departure location, weather forecast, and historical and real-time road conditions.

5. A method for fuel transfer and transportation in a power plant coal yard according to claim 1, characterized in that The step of obtaining the daily output demand of the unit, combining it with the coal storage situation data in the power plant, and planning the reservation queuing scheme for the coal transport vehicles outside the plant specifically includes: According to the daily output demand of the unit and the current coal storage structure in the power plant, plan the reservation queuing system for the coal transport vehicles outside the plant; according to the weight of the coal types transported, assign different queuing priorities, in-plant coal unloading stacking schemes, and in-plant metering weighing point schemes to the coal transport vehicles.

6. The method for fuel transfer in a coal yard of a power plant according to claim 1, characterized in that, The step of real-time monitoring the transport path deviation situation and vehicle performance abnormality situation of the coal transport vehicle, and giving an alarm for the abnormal vehicle specifically includes: Based on the clustering analysis of SVM, analyze the number of times the vehicle deviates from the planned path, the length of the deviated path, and the characteristics of the deviated route, analyze the overtime transport duration of the vehicle, the overtime ratio of each section, and the corresponding overtime frequency, and associate the vehicle driver, carrier, supplier, mine site, and coal type information to realize the detection of abnormal vehicle lane changes, stops, problematic carriers, and suppliers; Analyze the vehicle engine and exhaust emission sensor data in the vehicle-mounted Internet of Things terminal, detect the vehicle performance abnormality situation, and give an alarm for the abnormal vehicle and stop the dispatching operation.

7. A fuel transfer and transportation system for a power plant coal yard, characterized in that, It includes: A data acquisition module for obtaining the data of coal transport vehicles, road meteorological conditions, and the coal storage situation in the power plant; A route planning module for inputting the vehicle data, road meteorological conditions data, and the coal storage situation data in the power plant into the pre-established optimal scheduling model based on the multi-objective optimization algorithm, and outputting the best driving route of the coal transport vehicle; A queuing planning module, which is used to obtain the daily output demand of the unit, and combine the data of the coal storage situation in the power plant to plan the appointment queuing scheme for the coal transportation vehicles outside the plant; A monitoring and warning module, which is used to monitor the transportation path deviation and vehicle performance abnormality of the coal transportation vehicle in real time, and warn the abnormal vehicle.

8. The fuel transfer system for a power plant coal yard according to claim 7, wherein It also includes: An intelligent scheduling and monitoring module, which is used to display the real-time road conditions outside the plant, vehicle positions and meteorological dynamics in the form of a digital map according to the real-time coal storage situation in the coal yard; The route planning module is given the function of generating and issuing the planned path, as well as the function of manually setting and issuing the path by the on-site dispatcher; The on-site dispatcher is given the function of communicating with the driver in real time through the vehicle-mounted Internet of Things terminal.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, the steps of a fuel transportation method for a power plant coal yard as described in any one of claims 1-7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, the steps of a fuel transportation method for a power plant coal yard as described in any one of claims 1-7 are implemented.

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