Visual monthly report emission progress management method and system

Abstract

The invention discloses a visual emission monthly report progress management method and system, and relates to the technical field of energy management, and the method comprises the steps: building a visual platform, obtaining the energy consumption and operation log data of target plant equipment, calculating the emission progress and generating trend prediction data according to the energy consumption and operation log data, making a control strategy through combining with a preset emission target, and carrying out the prediction of the trend prediction data. And adjusting the equipment operation parameters to obtain an optimal value, displaying the emission progress and the equipment parameters through a platform, and generating a management report based on a preset target completion rate. The technical problem that in the prior art, emission management is lack of intuition, scientificity and dynamic adjustment capacity is solved, and the technical effects of intuitively, scientifically and dynamically managing emission of target plant equipment and improving energy consumption management of enterprises are achieved by establishing a visual platform and dynamically adjusting equipment operation parameters.

Description

Technical Field

[0001] The present application relates to the field of energy management technology, and in particular to a visualized emission monthly report progress management method and system. Background Art

[0002] In the context of enterprise emission management, emission issues in enterprise production activities have received increasing attention, and the contradiction between environmental protection requirements and efficient operation of enterprises has become more prominent. Achieving efficient emission management and ensuring efficient operation of enterprises while meeting environmental protection requirements has become a vital link in enterprise development. Traditional enterprise emission management is often extensive and lacks systematicity. It only relies on simple emission monitoring equipment or irregular inspections, and has insufficient control over the overall emission situation of the enterprise. It lacks in-depth analysis and utilization of equipment energy consumption data and operation log data, making it difficult to comprehensively and accurately evaluate the emission progress and trends of the enterprise. There are unreasonable situations in the formulation of emission control strategies, resulting in waste of resources or excessive emissions. The adjustment of equipment operating parameters is relatively arbitrary and lacks scientificity, and cannot cope well with the ever-changing production situation of the enterprise.

[0003] At the current stage, relevant technologies have technical problems such as the lack of intuitiveness, scientificity and dynamic adjustment capabilities of emission management. Summary of the invention

[0004] The present application provides a visualized emission monthly progress management method and system, establishes a visualization platform, obtains the energy consumption and operation log data of the target plant equipment, calculates the emission progress and generates trend forecast data based on this, formulates a control strategy based on the preset emission target, adjusts the equipment operation parameters to obtain the optimal value, displays the emission progress and equipment parameters through the platform, and generates a management report based on the preset target completion rate. By establishing a visualization platform, the equipment operation parameters are dynamically adjusted, thereby achieving intuitive, scientific and dynamic management of the emissions of the target plant equipment and improving the technical effect of the enterprise energy consumption management.

[0005] This application provides a visual emission monthly report progress management method, including:

[0006] Establish a visualization platform to obtain the actual energy consumption data and operation log data of the target plant equipment; calculate the current emission progress based on the actual energy consumption data and the operation log data, and generate emission trend forecast data; obtain the preset emission target, and formulate an emission control strategy based on the preset emission target and the emission trend forecast data; adjust the operating parameters of the target plant equipment based on the emission control strategy to obtain the optimal operating parameters; display the real-time emission progress, predicted emission progress, and equipment operating parameters of the target plant equipment through the visualization platform; generate an emission management report based on the completion rate of the preset emission target.

[0007] This application also provides a visual emission monthly report progress management system, including:

[0008] A visualization platform establishment module, the visualization platform establishment module is used to establish a visualization platform and obtain the actual energy consumption data and operation log data of the target plant equipment; an emission trend prediction data generation module, the emission trend prediction data generation module is used to calculate the current emission progress based on the actual energy consumption data and the operation log data, and generate emission trend prediction data; an emission control strategy formulation module, the emission control strategy formulation module is used to obtain a preset emission target, and formulate an emission control strategy based on the preset emission target and the emission trend prediction data; an optimal operating parameter acquisition module, the optimal operating parameter acquisition module is used to adjust the operating parameters of the target plant equipment based on the emission control strategy, and obtain the optimal operating parameters; a visualization platform display module, the visualization platform display module is used to display the real-time emission progress, predicted emission progress, and equipment operating parameters of the target plant equipment through the visualization platform; an emission management report generation module, the emission management report generation module is used to generate an emission management report based on the completion rate of the preset emission target.

[0009] A visualized emission monthly progress management method and system is proposed in this application. First, a visualization platform is established to obtain the energy consumption and operation log data of the target plant equipment, based on which the emission progress is calculated and trend forecast data is generated. A control strategy is formulated in combination with the preset emission targets, and the equipment operating parameters are adjusted to obtain the optimal values. The emission progress and equipment parameters are displayed on the platform, and a management report is generated based on the preset target completion rate. By establishing a visualization platform and dynamically adjusting the equipment operating parameters, the intuitive, scientific and dynamic management of the emissions of the target plant equipment is achieved, thereby improving the technical effect of the enterprise's energy consumption management. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0011] Figure 1 A flow chart of a visualized emission monthly report progress management method provided in an embodiment of the present application;

[0012] Figure 2 A structural schematic diagram of a visual emission monthly report progress management system provided in an embodiment of the present application.

[0013] Explanation of the accompanying drawings: visualization platform establishment module 10, emission trend prediction data generation module 20, emission control strategy formulation module 30, optimal operating parameter acquisition module 40, visualization platform display module 50, emission management report generation module 60. DETAILED DESCRIPTION

[0014] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0015] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0016] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0017] The present application embodiment provides a visual emission monthly report progress management method, such as Figure 1 As shown, the method includes:

[0018] Step S100, establish a visualization platform to obtain the actual energy consumption data and operation log data of the target plant equipment. Specifically, to establish a visualization platform for the management of the monthly emission report progress, it is necessary to first clarify its functional requirements and user groups, and to select technology and design the architecture. In terms of obtaining the actual energy consumption data of the target plant equipment, it is necessary to determine the data source, such as the communication interface of the energy metering device and the intelligent device. Considering the diversity of the device Internet of Things protocol, the corresponding communication protocol can be used for different devices for data collection. For example, for devices using the Modbus protocol, the energy consumption data can be read through the Modbus communication module; for devices supporting the ZigBee protocol, the ZigBee gateway can be used for data collection, and the data collection device can be used to transmit data in a combination of real-time and periodic collection, and the collected data can be verified and cleaned. For obtaining the operation log data, it is necessary to find the device control system or monitoring system to determine the data source. Similarly, data collection can be performed according to the communication protocols of different devices, such as the device control system communication to read the operation log data, organize it into a unified format and store it in the data storage layer of the visualization platform, and provide basic data support for the monthly emission report progress management together with the energy consumption data.

[0019] In a possible implementation, a visualization platform is established to obtain actual energy consumption data and operation log data of target plant equipment, and step S100 further includes step S110, configuring a visualization data conversion layer format based on the communication transmission format of the target plant equipment. Specifically, we need to have an in-depth understanding of the communication transmission format of the target plant equipment. Different devices use different communication protocols, data encoding methods and transmission rates. For example, some devices may use the Modbus protocol for communication, while other devices may use protocols such as Profibus. We need to configure the visualization data conversion layer format. By analyzing the communication transmission format of the equipment, we need to analyze the communication protocol of the target plant equipment in detail, understand its data structure, command format and communication process, etc., determine how to convert data in different formats into a format that the visualization platform can understand and process, and select appropriate data conversion technology. According to the characteristics of the equipment communication transmission format, we need to select appropriate data conversion technology. For example, we can use tools such as protocol converters, data parsers or middleware to convert data of different protocols into a unified format. We need to configure the data conversion layer parameters. According to the specific needs of the equipment, we need to configure the parameters of the data conversion layer, including setting the communication port, data format conversion rules, data filtering conditions, etc. By configuring the parameters reasonably, we can ensure the accuracy and efficiency of data conversion, provide a unified data interface for the visualization platform, so that the equipment data in different communication transmission formats can be correctly identified and processed by the platform, thereby improving the equipment compatibility of the platform.

[0020] Step S120, through the visualization data conversion layer, the actual energy consumption data and operation log data of the target plant equipment are obtained. Specifically, the visualization data conversion layer format is configured, and the actual energy consumption data and operation log data of the target plant equipment are obtained through the conversion layer, and a data connection is established. The visualization platform establishes a connection with the target plant equipment through the data conversion layer, which is achieved through a network connection, a serial port connection or other communication methods to ensure the stability and reliability of the connection so that the equipment data can be obtained in real time. The function of the data conversion layer is used to collect the actual energy consumption data and operation log data from the target plant equipment, which involves sending specific commands or requests to obtain the status information, energy consumption data and operation log of the equipment, etc., and data transmission and processing. The collected data is transmitted to the visualization platform through the data conversion layer. During the transmission process, data encryption, compression or other processing is required to ensure the security and integrity of the data. After receiving the data, the visualization platform performs further processing and analysis, such as storing data, calculating energy consumption indicators, generating reports, etc., to achieve real-time acquisition and processing of target plant equipment data, and provide accurate data support for the progress management of the monthly emission report.

[0021] Step S130, based on the business type, the actual energy consumption data and the operation log data are classified and stored. Specifically, the actual energy consumption data and the operation log data are classified and stored according to the business type, and the business type is determined. Different business types are determined according to the use scenarios and business needs of the target plant equipment. For example, the equipment can be divided into different types such as production equipment, auxiliary equipment, energy equipment, etc., or classified according to different production processes, workshops, etc., and a data storage structure is designed. According to the determined business type, a corresponding data storage structure is designed, and storage technologies such as databases, file systems or data warehouses are used to classify and store data according to business types. For example, a database table or folder is created for each business type, and the relevant data is stored therein. Data is stored and managed, and the actual energy consumption data and the operation log data are stored in the corresponding storage structure according to the business type. At the same time, it is necessary to establish a data management mechanism to ensure data security, backup and recovery, etc., use the database management system's permission management, data backup strategy and other functions to ensure data security and reliability, improve data management efficiency and query performance, facilitate subsequent data analysis and processing, and also help to better understand the energy consumption and operation of equipment of different business types, and provide a basis for formulating more scientific and reasonable emission control strategies. By configuring the visualization data conversion layer format based on the target plant equipment communication transmission format, obtaining equipment data through the conversion layer, and classifying and storing based on business type, the problems of low compatibility and few supported devices of the visualization platform can be effectively solved, so as to achieve the technical effect of improving the compatibility of platform equipment and better supporting more equipment, and provide strong support for the progress management of monthly emission reports.

[0022] In one possible implementation, based on the communication transmission format of the target factory equipment, the visualization data conversion layer format is configured, and step S110 further includes step S111, configuring the data format configuration plug-in corresponding to the target factory equipment on the visualization platform based on the Internet of Things communication protocol of the target factory equipment.Specifically, various devices in the target factory are investigated to obtain the IoT communication protocols used. Different devices use different protocols, and the common ones are MQTT, CoAP, HTTP, etc. The specific communication protocol of each device is determined by communicating with the device manufacturer, consulting the device documentation, or conducting actual network monitoring. After the communication protocol is determined, the characteristics of the protocol are analyzed, including the message format, data encoding method, transmission method, etc. For example, the MQTT protocol is a lightweight communication protocol based on the publish / subscribe mode. The message format is relatively simple, and messages are usually distributed based on topics. The CoAP protocol is a protocol designed specifically for constrained devices with low power consumption. , low bandwidth occupancy, etc. By analyzing the characteristics of the communication protocol, the structural and format characteristics of the data sent by the device are obtained, which provides a basis for the design of the subsequent data format configuration plug-in. According to the technical architecture and requirements of the visualization platform, the appropriate plug-in development technology is selected, and the programming language and development tools compatible with the visualization platform are selected to develop the data format configuration plug-in. Before developing the plug-in, it is necessary to design the structure of the plug-in, including determining the input interface and output interface of the plug-in, as well as the internal data processing flow. The input interface of the plug-in should be able to receive the original data from the target plant equipment. The data is usually encoded according to a specific Internet of Things communication protocol, and the output interface should process the processed data in a visual format. The data is output in a format that can be understood by the visualization platform. The internal data processing process may include data parsing, format conversion, data verification and other links. The data parsing link is responsible for parsing the original data according to the format of the communication protocol and extracting useful information. The format conversion link converts the parsed data into the format required by the visualization platform. The data verification link is responsible for checking whether the converted data meets the requirements of the visualization platform. According to the IoT communication protocol of the target plant equipment, code is written to implement the data parsing function. It is necessary to use a specific protocol parsing library or manually write the parsing code. According to the needs of the visualization platform, data format conversion rules are designed. The rules can be fixed conversion formulas or can be based on specific conditions. Perform dynamic conversion. According to the designed format conversion rules, write code to implement the data format conversion function. It is necessary to use the built-in functions of the programming language or call external libraries to write code to implement the data verification function. Check whether the converted data meets the requirements of the visualization platform. Use regular expressions, data range checks and other methods to verify the data. When the data format configuration plug-in is developed, it needs to be integrated into the visualization platform. It is necessary to make corresponding settings in the configuration file of the visualization platform to specify the location and parameters of the plug-in. The visualization platform needs to be tested to ensure that the plug-in can work properly and will not affect other functions of the platform. If problems are found, they need to be adjusted and optimized in a timely manner.

[0023] Step S112, based on the data format of the target plant equipment, configure the field mapping plug-in of the data format configuration plug-in on the visualization platform. Specifically, the data format of the target plant equipment can be analyzed by consulting technical documents, communicating with manufacturers or obtaining information through actual sampling and analysis, understanding the data structure, field meaning, type and length, etc., clarifying the data requirements of the visualization platform, including the expected data format, field name, type and display method, designing field mapping rules according to the equipment data format and platform requirements, which may include one-to-one, many-to-one or one-to-many mapping, and considering data type conversion, unit conversion and cleaning preprocessing. After selecting a development technology compatible with the visualization platform, develop a field mapping plug-in to implement field parsing, design mapping functions, perform data cleaning preprocessing and continuously test and optimize, and finally integrate the plug-in into the visualization platform, set and test it in the configuration file to ensure that it works normally and does not affect other functions of the platform, improve the compatibility and processing capabilities of the visualization platform for different equipment data, and provide accurate and effective data support for the progress management of the monthly emission report.

[0024] Step S113, through the visualization platform, the data format configuration plug-in and the field mapping plug-in are combined to obtain the data conversion layer format. Specifically, the functions of the data format configuration plug-in and the field mapping plug-in are understood. The former performs preliminary format conversion on the data according to the IoT communication protocol of the target plant equipment, and the latter performs accurate field mapping and conversion based on the equipment data format and visualization platform requirements. The combination method and order are determined. Usually, the data format configuration plug-in is used for preliminary processing and then further converted by the field mapping plug-in. The data flow is established in the visualization platform, the plug-in parameters are configured, and data transmission is realized. The actual equipment data is used for testing, the processing flow is optimized, and continuous monitoring and improvement are carried out to ensure that the combined plug-in can accurately obtain the data conversion layer format that meets the requirements, and provide support for the efficient operation of the visualization platform and the progress management of the monthly emission report.

[0025] In one possible implementation, based on the IoT communication protocol of the target factory equipment, a data format configuration plug-in corresponding to the target factory equipment on the visualization platform is configured, and step S111 further includes step S1111, pre-configuring the data format configuration plug-in on the visualization platform, and the data format configuration plug-in is obtained by parsing multiple IoT communication protocols. Specifically, we first investigate and analyze the IoT communication protocols that may be used in the target plant to determine their specific types, such as MQTT, CoAP, HTTP, AMQP, etc. We select development technologies with good scalability and compatibility to build data format configuration plug-ins, such as using some open source frameworks or libraries to design plug-in architecture and interfaces. We use a layered design including a protocol parsing layer, a data conversion layer, and an interface layer to ensure easy integration with the visualization platform and the ability to flexibly handle different protocols. We develop corresponding protocol parsing modules for each determined protocol to implement data extraction and conversion, and perform integration and testing. We pre-configure the developed plug-in on the visualization platform, specify the location and parameters in the configuration file, select the supported protocol and set the corresponding parameters based on the actual equipment situation, and we can also make customized settings to meet platform-specific requirements, so that the plug-in can obtain target plant equipment data by parsing multiple IoT communication protocols, providing support for the management of the monthly emission report progress.

[0026] Step S200, based on the actual energy consumption data and the operation log data, calculate the current emission progress and generate emission trend prediction data. Specifically, first collect the actual energy consumption data and operation log data of the target plant equipment, organize and pre-process them, remove outliers, fill in missing values ​​and sort them by time series, determine the appropriate emission calculation model according to the equipment type and energy consumption characteristics, such as for the equipment that mainly consumes electricity, calculate the emission amount by combining power, operation time and emission factor, the emission factor can be obtained by consulting materials or consulting the energy supply department, use the emission calculation model, substitute the actual energy consumption data into the calculation of the current actual emission amount, calculate the current emission progress in combination with the preset emission target, collect the actual energy consumption and emission data of the equipment in the past for historical data analysis, find out the trend law and select the appropriate prediction model, train the model with historical data, and then input the current actual energy consumption and operation log data into the trained model to generate future emission trend prediction data, and provide reference information for the emission management of the target plant equipment.

[0027] In a possible implementation, based on the actual energy consumption data and the operation log data, the current emission progress is calculated to generate emission trend prediction data. Step S200 further includes step S210, based on the historical emission data, calculating the emission progress difference between the actual emission data of the target plant equipment and the emission trend prediction data. Specifically, the actual emission data of the target plant equipment over a period of time in the past are collected. The data can be obtained from the operation log, energy consumption record and environmental monitoring system of the equipment. The historical emission data should cover different operating conditions and time periods to ensure sufficient representativeness. The emission trend prediction data can be generated by existing prediction methods or models. For example, the historical emission data can be modeled using time series analysis, regression analysis and other methods to obtain future emission trend prediction values. For the actual emission data and the emission trend prediction data, the emission progress relative to the preset emission target in a specific time period is calculated respectively. The emission progress can be expressed by the ratio of the actual emission amount or the predicted emission amount to the preset emission target. The emission progress of the actual emission data is compared with the emission progress of the emission trend prediction data, and the difference between the two is calculated. The difference can be expressed in absolute value or percentage, depending on actual needs.

[0028] Step S220, based on the emission progress difference, an emission trend prediction model is generated. Specifically, the calculated emission progress difference is deeply analyzed to study the size of the difference, the trend of change and the possible reasons, to help determine the factors that affect the accuracy of emission trend prediction, and to provide a basis for improving the prediction model. According to the characteristics of the emission progress difference and the analysis results, a suitable modeling method is selected to generate a new emission trend prediction model. Machine learning algorithms such as neural networks and support vector machines are used. The algorithms can automatically learn patterns and relationships in the data, thereby improving the accuracy of the prediction. The historical emission data and emission progress difference are used as training data to train the selected modeling method. By adjusting the parameters of the model, the model can better fit the data and reduce the emission progress difference. The trained model is verified, and the performance of the model is evaluated using independent test data. If the performance of the model does not meet the requirements, further optimization can be performed, such as adjusting the model structure and increasing the training data.

[0029] Step S230, based on the emission trend prediction model and the current emission progress, generate emission trend prediction data. Specifically, the emission progress of the current target plant equipment is used as input data and provided to the generated emission trend prediction model. The current emission progress can be obtained through actual monitoring or calculation, reflecting the emission situation of the equipment at the current moment. The emission trend prediction model is used to process the input current emission progress to generate future emission trend prediction data. The prediction data may include emission volume prediction values ​​and emission progress prediction values ​​for different time periods in the future. The generated emission trend prediction data is analyzed to evaluate its reliability and accuracy. According to the prediction data, the enterprise can formulate corresponding emission control strategies and adjust the operating parameters of the equipment to achieve the goal of energy conservation and emission reduction. The actual emission situation is continuously monitored and compared with the prediction data, and the emission trend prediction model is continuously improved and optimized. By calculating the emission progress difference based on historical emission data, an emission trend prediction model is generated, and the emission trend prediction data is generated by combining the model with the current emission progress, which can provide a scientific basis and decision support for the emission management of the target plant equipment.

[0030] Step S300, obtain the preset emission target, and formulate an emission control strategy based on the preset emission target and the emission trend forecast data. Specifically, obtaining the preset emission target requires clear regulatory requirements, understanding the environmental protection regulations and emission standards of the national and local governments for the industry to which the target plant belongs to determine the bottom line requirements, and considering the company's own goals, such as sustainable development strategies and other factors to set stricter goals, and then determine the specific preset emission target value and time range, analyze the emission trend forecast data, understand its meaning, including the predicted emission volume, trend speed, peak and trough time, etc., evaluate uncertainty, and then compare it with the preset emission target to determine whether the target can be achieved, and formulate an emission control strategy, including equipment optimization, such as upgrading equipment energy efficiency, improving production processes, etc.; operation management, strengthening equipment operation efficiency, formulating reasonable operation plans, etc.; energy management, optimizing energy use, adopting energy-saving technologies, etc.; monitoring and feedback, establishing and improving emission monitoring systems and adjusting strategies based on results, and establishing feedback mechanisms; emergency measures, formulating emergency plans to deal with emergencies, so that enterprises can effectively manage the emissions of target plant equipment and achieve sustainable development goals.

[0031] In one possible implementation, a preset emission target is obtained, and an emission control strategy is formulated based on the preset emission target and the emission trend prediction data. Step S300 further includes step S310, step a: based on the emission control strategy, adjusting the operating parameters of the target plant equipment. Specifically, first, review and clarify the emission control strategies that have been formulated. The strategies may include measures in equipment optimization, operation management, energy management, etc. For example, equipment optimization strategies may involve upgrading the energy efficiency of equipment and installing emission reduction equipment; operation management strategies may include formulating reasonable equipment operation plans and optimizing equipment start and stop times; energy management strategies may include adopting energy-saving technologies and optimizing energy procurement strategies. Determine the adjustable operating parameters. According to the emission control strategy, determine the adjustable operating parameters of the target plant equipment. The parameters include equipment power, speed, temperature, pressure, etc. Different types of equipment may have different adjustable parameters, which need to be determined in combination with the characteristics and functions of the specific equipment. According to the requirements of the emission control strategy, adjust the operating parameters of the target plant equipment. The parameters can be adjusted through the equipment control system, manual adjustment device or automatic control system. During the adjustment process, attention should be paid to the adjustment range and speed of the parameters to avoid adverse effects on the normal operation of the equipment.

[0032] Step S320, step b: obtaining the emission data of the target plant equipment after adjustment in real time through the visualization platform, and performing emission performance evaluation based on the emission data to obtain emission evaluation parameters. Specifically, the emission data of the target plant equipment after adjustment is obtained in real time by using the monitoring function of the visualization platform. The visualization platform can collect the emission data of the equipment in real time by communicating with the equipment, such as emission volume, emission concentration, emission rate, etc. Based on the acquired emission data, the emission performance of the target plant equipment is evaluated. The evaluation can be carried out in a variety of ways, such as comparing the gap between the emission data and the preset emission target, calculating the emission reduction rate, analyzing the change trend of the emission data, etc. Through the evaluation, it can be understood whether the emission of the equipment has been improved after adjusting the operating parameters. According to the results of the emission performance evaluation, the emission evaluation parameters are determined. The emission evaluation parameters can be a specific value or an indicator system for measuring the emission performance of the equipment. For example, the ratio of the emission volume to the preset emission target, the emission reduction rate, the emission compliance rate, etc. can be used as emission evaluation parameters.

[0033] Step S330, step c: if the emission assessment parameters reach the preset emission targets, confirm that the operating parameters of the target plant equipment are optimal operating parameters. Specifically, the emission assessment parameters are compared with the preset emission targets, and the obtained emission assessment parameters are compared with the preset emission targets. If the emission assessment parameters reach or exceed the preset emission targets, it means that the equipment can meet the emission requirements under the current operating parameters. If the emission assessment parameters reach the preset emission targets, the current operating parameters of the target plant equipment are confirmed to be the optimal operating parameters. The parameters can be used as the standard operating parameters of the equipment and continue to be used in future production processes. The optimal operating parameters are recorded for reference and adjustment when necessary. Even if the optimal operating parameters are confirmed, it is necessary to continuously monitor the emissions of the target plant equipment. With the use time of the equipment, changes in production conditions and technological advances, it may be necessary to further optimize and adjust the operating parameters, regularly evaluate the emission performance of the equipment, and adjust the operating parameters in a timely manner according to the evaluation results to ensure that the equipment always maintains the optimal emission state. Through step a, the operating parameters of the target plant equipment are adjusted based on the emission control strategy, step b, obtaining emission data in real time through the visualization platform and evaluating the emission performance to obtain emission assessment parameters, and step c, confirming the optimal operating parameters when the emission assessment parameters reach the preset emission targets, the enterprise can effectively optimize the emission performance of the target plant equipment and achieve the goal of energy conservation and emission reduction.

[0034] In a possible implementation, step c: if the emission assessment parameter reaches the preset emission target, confirm that the operating parameter of the target plant equipment is the optimal operating parameter, step S330 further includes step S331, if the emission assessment parameter does not reach the preset emission target, adjust the operating parameter based on the acquired emission data, and repeat step b to step c. Specifically, if the emission assessment parameter does not reach the preset emission target, first analyze the emission data obtained through the visualization platform to determine the adjustment direction of the operating parameter. For example, if the emission volume is too high, the parameters such as equipment power can be reduced, and a step-by-step adjustment method is adopted and it is noted that the amplitude should not be too large, then repeat step b, obtain the adjusted emission data in real time through the visualization platform and perform emission performance evaluation to obtain new emission assessment parameters, and then repeat step c, compare the new parameters with the preset emission target, if the target is reached, confirm that the current operating parameters are optimal, if not, continue to adjust the operating parameters based on the emission data and repeat the above process, which needs to be repeated many times, and make more accurate adjustments based on experience and lessons to improve the efficiency of reaching the preset target, so as to continuously optimize the target plant equipment operating parameters to achieve energy conservation and emission reduction goals.

[0035] Step S400, based on the emission control strategy, adjust the operating parameters of the target plant equipment to obtain the optimal operating parameters. Specifically, first clarify the emission control strategy, which is usually formulated based on preset emission targets, equipment characteristics and regulatory requirements, covering equipment optimization, operation management, energy management and other aspects, determine the adjustable operating parameters of the target plant equipment, and combine technical documents, operation manuals and practical experience to find out the parameters that have a greater impact on emissions, such as power, speed, temperature, etc. Then adjust the parameters based on the emission control strategy, first make preliminary adjustments and then monitor the emission data through the visualization platform, analyze the data to evaluate the impact of parameter adjustments on emissions, and then further adjust and pay attention to the equipment operation status, and repeat the adjustment and monitoring process until the emission evaluation parameters reach the preset emission targets, confirm that the current operating parameters are the optimal operating parameters, and record and share these parameters to achieve energy conservation and emission reduction goals.

[0036] Step S500, through the visualization platform, the real-time emission progress, predicted emission progress, and equipment operating parameters of the target plant equipment are displayed. Specifically, the real-time emission data is collected through sensors connected to the target plant equipment, and the real-time emission progress is calculated. At the same time, the predicted emission progress is obtained using the emission trend prediction model, and the equipment operating parameters are collected. Then the data is integrated into a unified data set. The display content and form of the visualization platform are determined according to the needs of the enterprise and user habits, the interface layout is designed, and the functions are developed using visualization tools and technologies. Various forms of display can be used and interactive functions can be added to ensure that the visualization platform can update data in real time, conduct accuracy checks regularly, and regularly maintain and upgrade the platform to meet the needs of the enterprise, so as to display the real-time emission progress, predicted emission progress, and equipment operating parameters of the target plant equipment on the visualization platform, and provide strong support for the emission management and decision-making of the enterprise.

[0037] Step S600, based on the completion rate of the preset emission target, an emission management report is generated. Specifically, the preset emission targets of the target plant equipment are clarified, actual emission data is collected through monitoring means, the completion rate of the preset emission targets is calculated, emission management related information is collected, including the implementation of emission control strategies, equipment operating parameter adjustment records, abnormal situations and treatment measures, the emission management report structure is designed, and specific content is written. The introduction part introduces the background and purpose, the target completion part explains the completion rate and gap analysis, the emission control strategy implementation status explains the implementation effect and problems, the equipment operating parameter adjustment record shows the process and impact, the abnormal situation and treatment measures record the occurrence and treatment process, the conclusion and prospect part summarizes the results and proposes improvement directions, and adopts data visualization methods. After review, the report is issued to the company management and other relevant personnel to provide the company with a comprehensive and systematic emission management summary, helping the company to improve measures to achieve sustainable development goals.

[0038] The embodiment of the present application adopts the method of establishing a visualization platform to obtain the energy consumption and operation log data of the target plant equipment, calculate the emission progress and generate trend forecast data based on this, formulate a control strategy in combination with the preset emission targets, adjust the equipment operation parameters to obtain the optimal value, display the emission progress and equipment parameters through the platform, and generate a management report based on the preset target completion rate. By establishing a visualization platform and dynamically adjusting the equipment operation parameters, it is achieved to achieve intuitive, scientific and dynamic management of the emissions of the target plant equipment and improve the technical effect of enterprise energy consumption management.

[0039] In the above, refer to Figure 1 A visual emission monthly report progress management method according to an embodiment of the present invention is described in detail. Figure 2 A visual emission monthly report progress management system according to an embodiment of the present invention is described.

[0040] A visualized emission monthly report progress management system according to an embodiment of the present invention is used to solve the technical problem that emission management in the prior art lacks intuitiveness, scientificity and dynamic adjustment capabilities. By establishing a visualization platform and dynamically adjusting equipment operating parameters, it achieves the technical effect of achieving intuitive, scientific and dynamic management of target plant equipment emissions and improving enterprise energy consumption management. A visualized emission monthly report progress management system includes: a visualization platform establishment module 10, an emission trend prediction data generation module 20, an emission control strategy formulation module 30, an optimal operating parameter acquisition module 40, a visualization platform display module 50, and an emission management report generation module 60.

[0041] The visualization platform establishment module 10 is used to establish a visualization platform to obtain the actual energy consumption data and operation log data of the target plant equipment.

[0042] The emission trend prediction data generation module 20 is used to calculate the current emission progress based on the actual energy consumption data and the operation log data, and generate emission trend prediction data.

[0043] The emission control strategy formulation module 30 is used to obtain a preset emission target and formulate an emission control strategy based on the preset emission target and the emission trend prediction data.

[0044] The optimal operating parameter acquisition module 40 is used to adjust the operating parameters of the target plant equipment based on the emission control strategy to obtain the optimal operating parameters.

[0045] The visualization platform display module 50 is used to display the real-time emission progress, predicted emission progress, and equipment operating parameters of the target plant equipment through the visualization platform.

[0046] The emission management report generating module 60 is used to generate an emission management report based on the completion rate of the preset emission target.

[0047] The specific configuration of the visualization platform establishment module 10 will be described in detail below. As described above, a visualization platform is established to obtain the actual energy consumption data and operation log data of the target plant equipment. The visualization platform establishment module 10 further includes: a format configuration unit, which is used to configure the visualization data conversion layer format based on the target plant equipment communication transmission format; a data acquisition unit, which is used to obtain the actual energy consumption data and operation log data of the target plant equipment through the visualization data conversion layer; and a classification storage unit, which is used to classify and store the actual energy consumption data and the operation log data based on the business type.

[0048] Among them, based on the communication transmission format of the target factory equipment, the visualization data conversion layer format is configured, and the format configuration unit further includes: a data format configuration plug-in configuration subunit, the data format configuration plug-in configuration subunit is used for the data format configuration plug-in to configure the data format configuration plug-in corresponding to the target factory equipment on the visualization platform based on the Internet of Things communication protocol of the target factory equipment; a field mapping plug-in configuration subunit, the field mapping plug-in configuration subunit is used to configure the field mapping plug-in of the data format configuration plug-in on the visualization platform based on the data format of the target factory equipment; a plug-in combination subunit, the plug-in combination subunit is used to combine the data format configuration plug-in and the field mapping plug-in through the visualization platform to obtain the data conversion layer format.

[0049] Among them, the data format configuration plug-in configures the data format configuration plug-in corresponding to the target factory equipment on the visualization platform based on the Internet of Things communication protocol of the target factory equipment, and the data format configuration plug-in configuration subunit further includes: a data format configuration plug-in pre-configuration micro-unit, and the data format configuration plug-in pre-configuration micro-unit is used to pre-configure the data format configuration plug-in on the visualization platform, and the data format configuration plug-in is obtained by parsing multiple Internet of Things communication protocols.

[0050] The specific configuration of the emission trend prediction data generation module 20 will be described in detail below. As described above, based on the actual energy consumption data and the operation log data, the current emission progress is calculated to generate emission trend prediction data. The emission trend prediction data generation module 20 further includes: an emission progress difference calculation unit, the emission progress difference calculation unit is used to calculate the emission progress difference between the actual emission data of the target plant equipment and the emission trend prediction data based on historical emission data; an emission trend prediction model generation unit, the emission trend prediction model generation unit is used to generate an emission trend prediction model based on the emission progress difference; an emission trend prediction data generation unit, the emission trend prediction data generation unit is used to generate emission trend prediction data based on the emission trend prediction model and the current emission progress.

[0051] The specific configuration of the emission control strategy formulation module 30 will be described in detail below. As described above, a preset emission target is obtained, and an emission control strategy is formulated based on the preset emission target and the emission trend prediction data. The emission control strategy formulation module 30 further includes: an operating parameter adjustment unit, which is used in step a: adjusting the operating parameters of the target plant equipment based on the emission control strategy; an emission evaluation parameter acquisition unit, which is used in step b: obtaining the emission data of the adjusted target plant equipment in real time through the visualization platform, and performing emission performance evaluation based on the emission data to obtain emission evaluation parameters; an optimal operating parameter determination unit, which is used in step c: if the emission evaluation parameters reach the preset emission target, confirming that the operating parameters of the target plant equipment are the optimal operating parameters.

[0052] Among them, step c: if the emission assessment parameters reach the preset emission targets, confirm that the operating parameters of the target plant equipment are the optimal operating parameters, and the optimal operating parameter determination unit further includes: an operating parameter feedback adjustment subunit, and the operating parameter feedback adjustment subunit is used to adjust the operating parameters based on the acquired emission data if the emission assessment parameters do not reach the preset emission targets, and repeat steps b to c.

[0053] A visualized monthly emission report progress management system provided by an embodiment of the present invention can execute a visualized monthly emission report progress management method provided by any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0054] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0055] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A visual emission monthly report progress management method, characterized in that: include: Establish a visualization platform to obtain the actual energy consumption data and operation log data of the target plant equipment; Based on the actual energy consumption data and the operation log data, calculate the current emission progress and generate emission trend prediction data; Obtaining a preset emission target, and formulating an emission control strategy based on the preset emission target and the emission trend forecast data; Based on the emission control strategy, adjust the operating parameters of the target plant equipment to obtain the optimal operating parameters; The real-time emission progress, predicted emission progress, and equipment operating parameters of the target plant equipment are displayed through the visualization platform; Based on the completion rate of the preset emission target, an emission management report is generated.

2. A visual emission monthly report progress management method according to claim 1, characterized in that: Obtain the actual energy consumption data and operation log data of the target plant equipment, including: Configure the visual data conversion layer format based on the target plant equipment communication transmission format; The actual energy consumption data and operation log data of the target plant equipment are obtained through the visual data conversion layer; Based on the business type, the actual energy consumption data and the operation log data are classified and stored.

3. A visual emission monthly report progress management method according to claim 2, characterized in that: Configure the visualization data conversion layer format, including: Based on the Internet of Things communication protocol of the target plant equipment, configure a data format configuration plug-in corresponding to the target plant equipment on the visualization platform; Based on the data format of the target plant equipment, configure the field mapping plug-in of the data format configuration plug-in on the visualization platform; The data format configuration plug-in and the field mapping plug-in are combined through the visualization platform to obtain the data conversion layer format.

4. A visual emission monthly report progress management method according to claim 3, characterized in that: The data format configuration plug-in is pre-configured on the visualization platform, and the data format configuration plug-in is obtained by parsing multiple Internet of Things communication protocols.

5. A visual emission monthly report progress management method according to claim 1, characterized in that: Generate emission trend forecast data, including: Based on the historical emission data, calculate the emission progress difference between the actual emission data of the target plant equipment and the emission trend forecast data; generating an emission trend prediction model based on the emission progress differences; Based on the emission trend prediction model and the current emission progress, emission trend prediction data is generated.

6. A visual emission monthly report progress management method according to claim 1, characterized in that: Obtain optimal operating parameters, including: Step a: Based on the emission control strategy, adjusting the operating parameters of the target plant equipment; Step b: acquiring the adjusted emission data of the target plant equipment in real time through the visualization platform, and performing emission performance evaluation based on the emission data to obtain emission evaluation parameters; Step c: If the emission assessment parameters reach the preset emission targets, confirm that the operating parameters of the target plant equipment are optimal operating parameters.

7. A visual emission monthly report progress management method according to claim 6, characterized in that: If the emission assessment parameter does not reach the preset emission target, the operating parameter is adjusted based on the acquired emission data, and steps b to c are repeated.

8. A visual emission monthly report progress management system, characterized in that: The system is used to implement a visualized emission monthly report progress management method according to any one of claims 1 to 7, and the system comprises: A visualization platform establishment module, which is used to establish a visualization platform to obtain actual energy consumption data and operation log data of target plant equipment; An emission trend prediction data generation module, the emission trend prediction data generation module is used to calculate the current emission progress based on the actual energy consumption data and the operation log data, and generate emission trend prediction data; An emission control strategy formulation module, the emission control strategy formulation module is used to obtain a preset emission target and formulate an emission control strategy based on the preset emission target and the emission trend prediction data; An optimal operating parameter acquisition module, which is used to adjust the operating parameters of the target plant equipment based on the emission control strategy to obtain the optimal operating parameters; A visualization platform display module, which is used to display the real-time emission progress, predicted emission progress, and equipment operating parameters of the target plant equipment through the visualization platform; An emission management report generation module is used to generate an emission management report based on the completion rate of the preset emission target.

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