Distributed-based Total Atmospheric Pollution Emission Calculation Method and System for Industrial Parks

Abstract

The present invention provides a method and system for calculating the total amount of atmospheric pollution emissions in an industrial park based on a distributed architecture, which solves the problems of existing total amount simulation technologies that can only conduct accounting for a single target, have low accounting efficiency, and cannot perform large-scale dynamic accounting. The method steps include: S1. Based on the basic information and data of the industrial park, configure and form a standard configuration file in JSON format and output it; S2. Deploy simulation inversion software to conduct total accounting of the pollution emission intensity in the park according to the standardized configuration file; S3. Construct a distributed computing cluster with a master-slave structure; for each slave node, deploy N independent simulation inversion software and at least one monitoring software, and accelerate the completion of tasks with higher priorities through an intelligent scheduling algorithm; for the master node, it is necessary to receive the information reported by the slave nodes at intervals of t moments and maintain the status of the slave nodes; S4. Deploy an operation and maintenance module to analyze and give early warnings on the running status of the distributed computing cluster.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring and protection, and particularly to a method and system for calculating the total amount of atmospheric pollution emissions in industrial parks based on a distributed system. Background Art

[0002] The total amount of atmospheric pollution emissions is an important basis for the control of the atmospheric environment. Previously, the total amount accounting mainly fell into three categories of methods: the measurement method, which calculates the total emissions through on-line monitoring instruments or manual sampling and monitoring. This method can only calculate the pollutants emitted in an organized manner through the discharge ports; the coefficient method, which calculates the emissions of enterprises through production capacity conversion or production and pollution discharge coefficients. This type of method requires professional personnel to check the data, and the accounting period is usually in years; the model method, which inversely calculates the total emissions through environmental monitoring data. Currently, dynamic accounting of organized and unorganized emissions can be carried out. However, due to differences in model selection, parameter settings, etc., it is difficult to conduct large-scale accounting, and the accounting results of different industrial parks are difficult to compare horizontally.

[0003] The above methods still have the following limitations:

[0004] 1. The existing total amount simulation technology can only conduct accounting for a single target and cannot perform large-scale dynamic accounting;

[0005] 2. The existing technology adopts different configuration schemes for different industrial parks, lacks standards, and the results are difficult to compare horizontally;

[0006] 3. The calculation resource allocation efficiency in the existing target accounting process is low, and the task scheduling synchronization is poor, making it difficult to achieve efficient accounting of multiple pollution sources in large-scale industrial parks.

[0007] Therefore, we propose a method and system for calculating the total amount of atmospheric pollution emissions in industrial parks based on a distributed system to solve the above problems. Summary of the Invention

[0008] The technical problem to be solved by the present invention is to overcome the defects existing in the prior art. The present invention proposes a method and system for calculating the total amount of atmospheric pollution emissions in industrial parks based on a distributed system, which can achieve large-scale synchronous dynamic accounting of the total amount of atmospheric pollution emissions in industrial parks.

[0009] To solve the above technical problems, the technical solution adopted by the present invention is: a method for calculating the total amount of atmospheric pollution emissions in industrial parks based on a distributed system, including the following steps:

[0010] S1. Based on the basic information and data of the industrial park, configure and form a standard configuration file in JSON format and output it;

[0011] S2. Deploy simulation inversion software to conduct accounting of the total amount of pollution emission intensity in the park according to the standardized configuration file;

[0012] S3. Build a distributed computing cluster with a master-slave structure;

[0013] For each slave node, deploy N independent simulation inversion software and at least one monitoring software. The monitoring software regularly sends the computing resource status of the slave node to the master node. When the computing resources are limited, the intelligent scheduling algorithm is used to accelerate the completion of high-priority tasks. The specific steps are as follows: For the calculation of a certain pollution factor in a certain park, the priority aims to achieve synchronous real-time calculation, assisted by a correction factor, and the synchronization is optimized through an evolutionary algorithm to select the individual with the maximum fitness as the current task allocation scheme;

[0014] For the master node, it is necessary to receive the information reported by the slave node at intervals of t moments, maintain the status of the slave node, and determine that the slave node is offline when no information is received for 2t consecutive times;

[0015] S4. Deploy an operation and maintenance module to analyze and warn the running status of the distributed computing cluster.

[0016] Furthermore, the standard configuration file in step S1 includes park simulation area information, monitoring point information, and pollution point information.

[0017] Furthermore, the specific steps for configuring the standard configuration file are as follows:

[0018] Collect basic information and data of the industrial park, including the regional scope, regional pollution source information, ground monitoring point information, and other pollution source point information around the park;

[0019] According to the collected information, calculate the simulated longitude and latitude range of the park. The minimum longitude of the simulation range is the minimum longitude of all points minus offset, the maximum longitude is the maximum longitude of all points plus offset, the minimum latitude is the minimum latitude of all points minus offset, and the maximum latitude is the maximum latitude of all points plus offset. Offset is set to 0.005;

[0020] Divide the simulation grid according to the grid resolution or the number of grids;

[0021] Mark the interference points outside the park, set the pollution source points outside the park, and at the same time mark whether each point belongs to the inside of the park. In the simulation and inversion of pollution diffusion, consider the pollution sources inside and outside the park. When calculating the total emission, only calculate the pollution sources inside the park;

[0022] Output a standard configuration file in JSON format.

[0023] Further, the park simulation area information includes the longitude and latitude of the southwest corner and the northeast corner of the simulation grid, the XY grid resolution, and the number of grids in the XY direction, where the X direction is the longitude change direction and the Y direction is the latitude change direction; the monitoring point information includes the point name, point code, point longitude and latitude, and point height; the pollution source point information includes the pollution source point name, point longitude and latitude, emission height, temperature, flow rate, discharge port diameter, and whether it belongs to the park interior.

[0024] Further, the specific steps of the total amount accounting in step S2 are as follows: obtain the real-time data corresponding to each monitoring point from the database, synchronously calculate the contribution degree of the pollution point to the diffusion process of the monitoring point, invert the pollution source emission intensity according to the real-time detection concentration, and sum up the emission intensities of all points marked as park points to obtain the overall emission intensity of the park.

[0025] Further, in the distributed computing cluster of step S3, assign an independent code SID and M park accounting tasks to each simulation inversion software, assign an independent code PID to each park accounting task, and the master node synchronously maintains the correspondence table between the park accounting task PID and the simulation inversion software instance SID.

[0026] Further, the specific calculation method of the intelligent scheduling algorithm in step S3 is

[0027]

[0028] where is the correction factor for task i; is the hour difference between the current time and the time when the park has completed the accounting;

[0029] Define the accounting computing power requirement for a single park and a single factor as a constant. Then, for computing server j, its total computing power can be set as , indicating that instances can be calculated simultaneously.

[0030] Further, when M parks and factors are calculated by N node servers, the specific calculation steps of the evolutionary algorithm are as follows:

[0031] Initialize the DNA as , where represents the first base of the k-th individual in the 0-th generation, represents that computing task 1 is computed on the node server numbered ;

[0032] Calculate the fitness of the k-th individual in the 0-th generation,

[0033]

[0034]

[0035] Select the top 10% of individuals with the highest fitness in the 0th generation according to the genetic algorithm, and generate offspring through base interaction and mutation;

[0036] Repeat the above steps until the maximum fitness of the population has not improved for 3 consecutive rounds;

[0037] Select the DNA of the individual with the maximum fitness as the current task allocation scheme.

[0038] Furthermore, in the step S4, the specific deployment steps of the operation and maintenance module are as follows

[0039] Park accounting warning: Analyze the park accounting time delay according to the calculation result database, and form an accounting warning when the delay is more than T hours;

[0040] Operation instance warning: Analyze the instance SID corresponding to the park PID with the accounting warning, calculate the number of warning PIDs corresponding to all SIDs and divide it by M as the warning rate. When the warning rate of the same SID exceeds the threshold, give a warning to this instance;

[0041] Operation node warning: Give a warning to the offline slave nodes maintained by the master node, and give a warning to the slave nodes whose disk occupancy exceeds the threshold.

[0042] Construct a system according to the above-mentioned distributed-based total air pollution emission calculation method for industrial parks, including:

[0043] Configuration module, used to configure and form a standard configuration file in JSON format and output it based on the basic information and data of the industrial park;

[0044] Total amount accounting module, deployed with simulation inversion software to conduct park total amount accounting according to the standardized configuration file output by the configuration module;

[0045] Distributed computing module, constructed according to the master-slave node structure, and synchronously and intelligently schedules high-priority tasks according to the computing resource situation of the slave nodes to speed up the completion. The master node is responsible for maintaining the status of the slave nodes;

[0046] Operation and maintenance module, used to analyze and warn the running status of the distributed computing cluster.

[0047] Compared with the prior art, the beneficial effects of the present invention include:

[0048] 1. The present invention provides a large-scale synchronous dynamic accounting technology for the total air pollution emissions in industrial parks, solves the problems of computing power allocation and efficient operation and maintenance. It has been verified that the system can support synchronous accounting of hundreds of industrial parks at the provincial level;

[0049] 2. By standardizing the park configuration file and the model configuration file, the present invention standardizes the setting of model operation parameters, making the accounting results of different parks horizontally comparable and providing support for management. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The disclosure of the present invention will be described with reference to the accompanying drawings. It should be understood that the drawings are only for illustrative purposes and are not intended to limit the scope of protection of the present invention. In the drawings, the same reference numerals are used to refer to the same components. Among them:

[0051] Figure 1 Schematically shows a schematic flowchart of a calculation method proposed according to an embodiment of the present invention;

[0052] Figure 2 Schematically shows an effect diagram of the park system configuration proposed according to an embodiment of the present invention;

[0053] Figure 3 Schematically shows a table diagram of the simulation inversion software configuration items proposed according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0054] It is easy to understand that according to the technical solution of the present invention, without changing the essence of the present invention, those of ordinary skill in the art can propose various structural ways and implementation ways that can be mutually replaced. Therefore, the following detailed embodiments and the accompanying drawings are only exemplary descriptions of the technical solution of the present invention, and should not be regarded as all of the present invention or as a limitation or restriction on the technical solution of the present invention.

[0055] According to an embodiment of the present invention in combination with Figures 1 - 3 shown.

[0056] As Figure 1 shown, in this embodiment, for the calculation method flow of the total amount of air pollution emissions in an industrial park based on distribution, the specific steps can be summarized as follows:

[0057] S1. Based on the basic information and data of the industrial park, configure and form a standard configuration file in JSON format and output it;

[0058] S2. Deploy simulation inversion software to perform total amount accounting according to the standardized configuration file;

[0059] S3. Build a distributed computing cluster with a master-slave structure;

[0060] For each slave node, deploy N independent simulation inversion software and at least one monitoring software. The monitoring software regularly sends the computing resource status of the slave node to the master node. When the computing resources are limited, the intelligent scheduling algorithm is used to accelerate the completion of high-priority tasks. The specific steps are as follows: for the calculation of a certain pollution factor in a certain park, the priority aims to achieve synchronous real-time calculation, supplemented by a correction factor, and the synchronization is optimized through an evolutionary algorithm to select the individual with the maximum fitness as the current task allocation scheme;

[0061] For the master node, it is necessary to receive the information reported by the slave node at intervals of t moments, maintain the status of the slave node, and determine that the slave node is offline when no information is received for 2t consecutive times;

[0062] S4. Deploy an operation and maintenance module to analyze and warn the running status of the distributed computing cluster.

[0063] Similarly, the system constructed according to the above calculation method is also within the protection scope of the present invention. The following further describes in combination with the above method and the actual system module composition:

[0064] 1. Configuration module

[0065] 1.1 Collection of basic park information

[0066] Collect the basic information and data of the application area, including the area range, information on area pollution sources (including the longitude and latitude of pollution source points, pollutant emission intensity, discharge port height, discharge port temperature, discharge port flow rate, discharge port diameter, etc.), information on ground monitoring points, including the longitude and latitude of the points, height and ground meteorological monitoring data (atmospheric pressure, temperature, humidity, wind speed, wind direction), information on other pollution source points around the park, etc.

[0067] 1.2 Construction of standardized configuration

[0068] According to the collected information, calculate the simulated longitude and latitude range of the park. The minimum longitude of the simulation range is the minimum longitude of all points (including pollution sources and monitoring stations) minus offset, and the offset is set to 0.005; the maximum longitude is the maximum longitude of all points (including pollution sources and monitoring stations) plus offset; the minimum latitude is the minimum latitude of all points (including pollution sources and monitoring stations) minus offset, and the offset is set to 0.005; the maximum latitude is the maximum latitude of all points (including pollution sources and monitoring stations) plus offset.

[0069] Divide the simulation grid, which can be divided according to the grid resolution or the number of grids. The grid resolution is generally set to 100 meters, and the number of grids is evenly divided according to the number of grids input by the user in the longitude and latitude directions.

[0070] Mark the interference points outside the park, set the pollution source points including those outside the park, and at the same time mark whether each point belongs to the inside of the park. In the pollution diffusion simulation and inversion, consider the pollution sources inside and outside the park. When calculating the total emissions, only calculate the pollution sources inside the park.

[0071] Output the standard configuration file. The configuration file is in a certain format and contains the following content:

[0072] 1) Information on the simulation area of the park: The longitude and latitude of the southwest and northeast corners of the simulation grid, the XY grid resolution, and the number of grids in the XY directions (the X direction is the direction of longitude change, and the Y direction is the direction of latitude change);

[0073] 2) Information on the monitoring points: including the point name, point code (corresponding to the database), point longitude and latitude, and point height H;

[0074] 3) Information on the pollution source points: including the pollution source point name, point longitude and latitude, emission height H, temperature, flow rate, outlet diameter, and whether it belongs to the inside of the park.

[0075] 2. Total amount accounting module

[0076] 2.1 Simulation and inversion software

[0077] The simulation and inversion software conducts total amount accounting according to the standardized configuration file. The specific steps are as follows:

[0078] 1) Read the information in the park configuration JSON file, standardize the location information, and convert the longitude and latitude in the JSON file into X and Y coordinates in the local coordinate system, with the unit of meters, taking the southwest corner of the simulation grid as the origin of the rectangular coordinate system;

[0079] 2) According to the simulation range information, read the satellite elevation DEM data, calculate the ground height h of each monitoring point and the location of the pollution source, and the final height h0 input into the model for the monitoring and pollution source points is h + H;

[0080] 3) Obtain the real-time data from the database through the numbers of the monitoring points, including the pollution concentration data, temperature, air pressure, humidity, wind speed, and wind direction of the points;

[0081] 4) Calculate the diffusion process from the pollution source to the monitoring station to obtain the contribution degree c, with the unit of mg·S / Kg·m3, indicating that when the emission intensity is 1 kg / s, the pollutant concentration at the monitoring point is c mg / m3;

[0082] 5) Invert the emission intensity of the pollution source according to the actual monitored concentration;

[0083] 6) Add up the emission intensities of all points marked as inside the park to obtain the overall emission intensity of the park.

[0084] The simulation inversion software can be configured with unified parameters to ensure the comparability of accounting results for different parks. The configuration items can refer to Figure 3 the table shown and will not be elaborated here.

[0085] For the specific calculation steps of the above contribution degree c, point emission intensity, and overall park emission intensity, reference can be made to the Chinese invention patent with the publication number CN118643299B, titled "An Atmospheric Pollution Real-time Tracing and Visualization Analysis Method and System", which has detailedly disclosed the corresponding formulas and calculation processes in the specification [0054 - 0068], and will not be elaborated here.

[0086] 3. Distributed Computing Module

[0087] The computing cluster adopts a master-slave structure, divided into a master node and slave nodes.

[0088] For each slave node, N independent simulation inversion software and 1 monitoring software are deployed. Among them, the monitoring software regularly sends operation status information to the master node. The operation status information includes: the computing resource situation of the slave node, including CPU occupancy, RAM occupancy, and disk occupancy. Each simulation inversion software is assigned an independent encoding SID and M park accounting tasks, and each park accounting task is assigned an independent encoding PID. Generally, N takes the value of 10 and M takes the value of 8.

[0089] For the master node, it is necessary to receive the information reported by the slave nodes at interval t, maintain the status of the slave nodes, and when no information is received for 2t consecutive time, it is judged that the slave node is offline, and t takes the value of 10 minutes. The master node also maintains a correspondence table between the park accounting task PID and the simulation inversion software instance SID.

[0090] When the computing resources of the aforementioned cluster are limited, that is, when there are many computing tasks, it is necessary to accelerate the completion of tasks with higher priorities through an intelligent scheduling algorithm.

[0091] For the calculation of a certain pollution factor in a certain park, the priority aims to achieve synchronous real-time calculation, supplemented by a correction factor, and the calculation method is:

[0092]

[0093] where is the correction factor of task i, with a default value of 1.0, which is adjusted according to business requirements; is the hour difference between the current time and the time when the park has completed accounting.

[0094] If the computing power requirement for the accounting of a single park and a single factor can be considered a constant, then for computing server j, its total computing power can be set as , indicating that instances can be calculated simultaneously.

[0095] Intelligent optimization is performed using an evolutionary algorithm. When M parks and factors are calculated by N node servers, optimization is carried out according to the following method.

[0096] 1) Initialize the DNA as , where represents the first base of the k-th individual in the 0-th generation, and represents the operation of calculation task 1 on the node server numbered .

[0097] 2) Calculate the fitness of the k-th individual in the 0-th generation:

[0098]

[0099]

[0100] 3) Select the top 10% individuals with the highest fitness in the 0-th generation according to the genetic algorithm, and generate offspring through base crossover and mutation;

[0101] 4) Repeat steps 1 - 3 until the maximum fitness of the population has not increased for three consecutive rounds;

[0102] 5) Select the DNA of the individual with the highest fitness as the current task allocation scheme.

[0103] 4. Operation and Maintenance Module

[0104] The operation and maintenance module mainly realizes the analysis of the running state of the distributed high-performance cluster to achieve efficient operation and maintenance of large-scale accounting. The operation and maintenance module mainly links the cluster master node and the calculation result database, specifically including:

[0105] Park accounting warning. Analyze the park accounting time delay based on the calculation result database. An accounting warning is formed when the delay is more than T hours. T is set to 24 hours;

[0106] Operation instance warning. Analyze the instance SID corresponding to the park PID with accounting warning, calculate the number of warning PIDs corresponding to all SIDs and divide it by M as the warning rate. When the warning rate of the same SID exceeds the threshold, a warning is issued for this instance. The threshold is set to 60%;

[0107] Operation node warning. Issue a warning for the offline slave nodes maintained by the master node and those with disk occupancy exceeding the threshold. The threshold is set to 80%.

[0108] In addition, the above method steps and system can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0109] The technical scope of the present invention is not limited to the content described in the above description. Those skilled in the art can make various deformations and modifications to the above embodiments without departing from the technical idea of the present invention, and these deformations and modifications should all fall within the protection scope of the present invention.

Claims

1. A distributed method for calculating the total amount of atmospheric pollution emissions from industrial parks, characterized in that: The steps include: S1. Based on the basic information and data of the industrial park, a standard configuration file in JSON format is configured and output; S2. Deploy simulation inversion software to calculate the total amount of pollution emission intensity in the park according to the standardized configuration file. The specific steps of the total amount calculation are to obtain the real-time data of each monitoring point from the standard configuration file, synchronously calculate the contribution of the diffusion process from the pollution point to the monitoring point, reversely calculate the emission intensity of the pollution source according to the real-time detection concentration, and add up the emission intensity of all the points marked as the park to obtain the overall pollution emission intensity of the park; S3, build a distributed computing cluster with a master-slave structure; For each slave node, deploy N independent simulation inversion software and at least one monitoring software, where the monitoring software regularly sends the computing resource status of the slave node to the master node. When computing resources are limited, the intelligent scheduling algorithm is used to speed up the completion of high-priority tasks. The specific steps are as follows: for the calculation of a pollution factor in a certain park, the priority is to achieve synchronous real-time calculation, assisted by correction factors, and synchronously optimized through evolutionary algorithms to select the individual with the maximum fitness as the current task allocation plan; For the master node, it needs to receive information reported by the slave node at intervals of t and maintain the status of the slave node. If no information is received for 2t consecutive times, it is considered that the slave node is offline; S4. Deploy the operation and maintenance module to analyze and warn the running status of the distributed computing cluster. The specific deployment steps of the operation and maintenance module are: Park accounting warning: analyze the delay of park accounting time according to the calculation result database, and generate accounting warning if the delay exceeds T hours; Calculate the instance warning, analyze the instance SID corresponding to the accounting warning park PID, calculate the number of warning PIDs corresponding to all SIDs and divide it by M as the warning rate. When the warning rate of the same SID exceeds the threshold, issue a warning for the instance; Early warning for computing nodes, early warning for offline slave nodes that are under maintenance of the master node, and early warning for slave node disk usage that exceeds the threshold.

2. The distributed industrial park air pollution emission calculation method according to claim 1 is characterized by: The standard configuration file in step S1 includes park simulation area information, monitoring point information and pollution point information.

3. The distributed method for calculating the total amount of atmospheric pollution emissions from industrial parks according to claim 2 is characterized in that: The specific steps for configuring the standard configuration file are as follows: Collect basic information and data of the industrial park, including regional scope, regional pollution source information, ground monitoring point information, and other pollution source point information around the park; According to the collected information, calculate the simulated longitude and latitude range of the park, where the minimum longitude of the simulation range is the minimum longitude of all points minus the offset, the maximum longitude is the maximum longitude of all points plus the offset, the minimum latitude is the minimum latitude of all points minus the offset, and the maximum latitude is the maximum latitude of all points plus the offset. The offset is set to 0.005; Divide the simulation grid according to the grid resolution or the number of grids; Mark the interference points outside the park, set the pollution source points outside the park, and mark whether each point belongs to the inside of the park. In the simulation and inversion of pollution diffusion, consider the pollution sources inside and outside the park. When calculating the total emissions, only the pollution sources inside the park are calculated; Outputs a standard configuration file in JSON format.

4. The distributed method for calculating the total amount of atmospheric pollution emissions from industrial parks according to claim 2 is characterized in that: The park simulation area information includes the longitude and latitude of the southwest corner and northeast corner of the simulation grid, the XY grid resolution, and the number of grids in the XY direction, where the X direction is the direction of longitude change and the Y direction is the direction of latitude change; the monitoring point information includes the point name, point code, point longitude and latitude, and point height; the pollution source point information includes the pollution source point name, point longitude and latitude, emission height, temperature, flow rate, outlet diameter, and whether it belongs to the interior of the park.

5. The distributed method for calculating the total amount of atmospheric pollution emissions from industrial parks according to claim 1 is characterized in that: In the distributed computing cluster of step S3, an independent coded SID and M park accounting tasks are allocated to each simulation inversion software, and an independent coded PID is allocated to each park accounting task. The master node synchronously maintains a correspondence table between the park accounting task PID and the simulation inversion software instance SID.

6. The distributed method for calculating the total amount of air pollution emissions from industrial parks according to claim 1 is characterized in that: The specific calculation method of the intelligent scheduling algorithm in step S3 is: ； in is the correction factor of task i; The hour difference between the current time and the time the park has completed accounting; Define the computing power requirements of a single park and a single factor as constants, then the total computing power of computing server j can be set to , indicating that it can be performed simultaneously Calculation of an instance.

7. The distributed industrial park air pollution emission calculation method according to claim 1 is characterized in that: When M parks and pollution factors are calculated by N node servers, the specific calculation steps of the evolutionary algorithm are as follows: Initialize DNA to ,in represents the first base of the k-th individual in generation 0, Indicates that computing task 1 is numbered Node server computing; Calculate the fitness of individual k in generation 0, ； ； According to the genetic algorithm, the 10% individuals with the highest fitness in the 0th generation are selected to generate offspring through base interaction and mutation; Repeat the above steps until the maximum fitness of the group does not increase for three consecutive rounds; The individual DNA with the largest fitness is selected as the current task allocation scheme.

8. A system constructed based on a distributed method for calculating the total amount of atmospheric pollution emissions from industrial parks according to any one of claims 1 to 7, characterized in that: include: Configuration module, which is used to configure and output standard configuration files in JSON format based on the basic information and data of the industrial park; The total volume accounting module is equipped with simulation inversion software to perform total volume accounting of the park based on the standardized configuration files output by the configuration module; The distributed computing module is built based on the master-slave node structure, and intelligently schedules high-priority tasks to speed up completion based on the computing resources of the slave nodes. The master node is responsible for maintaining the status of the slave nodes. The operation and maintenance module is used to analyze and warn the operating status of the distributed computing cluster.

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