Time-sharing metering method, system and equipment for enterprise carbon emission and storage medium

Abstract

The invention relates to the technical field of carbon emission metering, and discloses a time-sharing metering method, system and equipment for enterprise carbon emission and a storage medium, and the method comprises the steps: constructing a time-sharing carbon flow accounting model, and determining a carbon flow calculation boundary of an enterprise; whether monitoring equipment exists in each target area or not is judged, if yes, data collection is carried out through the monitoring equipment to obtain first time sequence energy consumption data, and if not, data collection is carried out through image sensing equipment, and the collected image data and sensing data are input into a pre-constructed energy consumption estimation model to obtain second time sequence energy consumption data; adding the first time sequence energy consumption data and the second time sequence energy consumption data to obtain time sequence energy consumption data; and inputting the time sequence energy consumption data into the time-sharing carbon flow accounting model to obtain the time-sharing carbon emission. Through the time-sharing metering technology, the precision of enterprise carbon emission metering is improved, the actual condition of enterprise carbon emission is accurately reflected, and a scientific basis is provided for enterprise carbon emission management.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission measurement, and in particular to a time-sharing measurement method, system, device and storage medium for enterprise carbon emission. Background Art

[0002] As global climate change becomes increasingly severe, accurate measurement and monitoring of carbon emissions have become a common focus of concern for governments and enterprises around the world. As one of the main sources of carbon emissions, accurate measurement of carbon emissions from high-energy-consuming enterprises is of great significance for formulating effective emission reduction strategies. At present, although there are some carbon emission measurement methods for high-energy-consuming enterprises, these methods still have certain limitations: first, the measurement accuracy is not high and cannot accurately reflect the actual situation of carbon emissions of enterprises; second, there is a lack of time-sharing measurement function and it is impossible to provide carbon emission data for different time periods, making it difficult to formulate effective emission reduction strategies; third, the calculation process is complicated and requires a lot of manpower and material resources. Since most of the existing carbon emission measurement methods are based on overall or average calculations, they cannot accurately reflect the carbon emissions of enterprises in different time periods, making it difficult for enterprises to formulate more targeted emission reduction measures. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides a time-sharing measurement method, system, equipment and storage medium for enterprise carbon emissions, so as to solve the problem that the existing carbon emission measurement method cannot accurately reflect the carbon emissions of the enterprise in different time periods, thereby achieving the effect of improving the measurement accuracy of the enterprise's carbon emissions.

[0004] In a first aspect, the present invention provides a time-sharing measurement method for enterprise carbon emissions, the method comprising:

[0005] Based on energy consumption and production consumption, a time-sharing carbon flow accounting model is constructed, and the production process of the enterprise is analyzed to determine the carbon flow calculation boundary of the enterprise, which includes the production activity boundary and production process boundary that generate carbon flow;

[0006] Determine whether there is a monitoring device in each target area corresponding to the carbon flow calculation boundary. If so, use the monitoring device to collect data to obtain first time series energy consumption data. If not, use an image sensor device to collect data, and input the collected image data and sensor data into a pre-built energy consumption estimation model to obtain second time series energy consumption data.

[0007] Adding the first time series energy consumption data and the second time series energy consumption data to obtain time series energy consumption data, and extracting a corresponding carbon emission factor from a preset carbon flow database according to the time series energy consumption data;

[0008] The time-series energy consumption data and the corresponding carbon emission factors are input into the time-sharing carbon flow accounting model to obtain the time-sharing carbon emissions of the enterprise, and the production process of the enterprise is regulated and optimized according to the time-sharing carbon emissions.

[0009] Furthermore, the step of constructing a time-sharing carbon flow accounting model based on energy consumption and production consumption includes:

[0010] According to the company's electric energy carbon emissions and non-electric energy carbon emissions, a time-sharing energy carbon flow accounting model is constructed;

[0011] According to the carbon emissions of raw materials, carbon absorption of products and carbon emissions of production process in enterprise production consumption, a time-sharing production carbon flow accounting model is constructed;

[0012] According to the time-sharing energy carbon flow accounting model and the time-sharing production carbon flow accounting model, a time-sharing carbon flow accounting model is obtained.

[0013] Furthermore, the step of analyzing the production process of the enterprise and determining the carbon flow calculation boundary of the enterprise includes:

[0014] According to the production process and scope of activities of the enterprise, the area and production stage where the carbon flow is generated are determined, and the production stage where the carbon flow is generated is analyzed to determine the production process that generates the carbon flow.

[0015] Furthermore, the step of collecting data through an image sensor device and inputting the collected image data and sensor data into a pre-built energy consumption estimation model to obtain time series energy consumption data includes:

[0016] Acquire peripheral sensor data of the target area through a sensor device, extract peripheral feature data from the peripheral sensor data through a principal component analysis method, and input the peripheral feature data into a pre-constructed first energy consumption estimation model to obtain first energy consumption data;

[0017] Acquire image data of the target area through an image acquisition device, input the image data into a pre-built second energy consumption estimation model to obtain energy consumption information, and convert the energy consumption information into second energy consumption data;

[0018] The first energy consumption data and the second energy consumption data are processed to obtain second time series energy consumption data.

[0019] Furthermore, after the step of obtaining the time series energy consumption data, the method further includes:

[0020] Define the state space according to the environmental state of the target area, define the action space according to the data collection frequency and data transmission strategy, define the reward function according to the data accuracy and resource consumption, and use the reinforcement learning algorithm for training to obtain the optimal data collection frequency;

[0021] According to the optimal data collection frequency, the data collection frequency is adjusted.

[0022] Furthermore, the following formula is used to express the carbon emissions of electric energy:

[0023]

[0024] In the formula, in the formula, represents the carbon emissions generated by electric energy in period t, Pelectricity(t) represents the average electric power in period t, EF electricity represents the carbon emission factor of electricity, Δt represents the time interval;

[0025] The following formula is used to express non-electric energy carbon emissions:

[0026]

[0027] In the formula, in the formula, represents the carbon emissions from non-electric energy during period t, Q other (t) represents the non-electric energy consumption during period t, EF other represents the carbon emission factor of non-electric energy, C carbon-other Indicates the carbon content of non-electric energy;

[0028] The following formula is used to express the time-sharing energy carbon flow accounting model:

[0029] E CO2-energy (t) = E CO2-electricity (t)+E CO2-other (t)

[0030] In the formula, E CO2-energy (t) represents the carbon emissions generated by the total energy in period t;

[0031] The following formula is used to express the carbon emissions of raw materials:

[0032]

[0033] In the formula, E CO2-raw (t) represents the carbon emission of raw materials put into production in period t, M raw-i (t) represents the input amount of the i-th raw material in period t, C carbon-raw-i represents the carbon content of the i-th raw material;

[0034] The product carbon absorption is expressed using the following formula:

[0035]

[0036] In the formula, represents the carbon absorption of the product during period t, M product-j (t) represents the output of the jth product in period t, C carbon-product-j represents the carbon absorption of the jth product;

[0037] The following formula is used to express the carbon emissions during the production process:

[0038] E CO2-process (t) = Y product (t)*EF process

[0039] In the formula, E CO2-process (t) represents the carbon emissions generated by the production process during period t, Y product (t) represents the product output in period t, EF process represents the carbon emission factor of the production process;

[0040] The following formula is used to express the time-sharing production carbon flow accounting model:

[0041] E CO2-activity (t) = E CO2-raw (t)—E CO2-product (t)+E CO2-process (t)

[0042] In the formula, E CO2-activity (t) represents the carbon emissions generated by total production activities during period t;

[0043] The following formula is used to express the time-sharing carbon flow accounting model:

[0044] E CO2-total (t) = E CO2-energy (t)+E CO2-activity (t)

[0045] In the formula, E CO2-total (t) represents the total carbon emissions of the enterprise in period t.

[0046] Furthermore, the first energy consumption estimation model is constructed based on a support vector machine;

[0047] The second energy consumption estimation model is constructed based on a target recognition model and a convolutional neural network. The target recognition model is used to extract energy consumption related images from image data, and the convolutional neural network model is used to extract energy consumption information from the energy consumption related images.

[0048] In a second aspect, the present invention provides a time-sharing measurement system for enterprise carbon emissions, the system comprising:

[0049] A model building module is used to build a time-sharing carbon flow accounting model based on energy consumption and production consumption, and analyze the production process of the enterprise to determine the carbon flow calculation boundary of the enterprise, which includes the production activity boundary and production process boundary that generate carbon flow;

[0050] An energy consumption data estimation module is used to determine whether there is a monitoring device in each target area corresponding to the carbon flow calculation boundary. If so, the monitoring device is used to collect data to obtain first time series energy consumption data. If not, the image sensor device is used to collect data, and the collected image data and sensor data are input into a pre-built energy consumption estimation model to obtain second time series energy consumption data.

[0051] Adding the first time series energy consumption data and the second time series energy consumption data to obtain time series energy consumption data, and extracting a corresponding carbon emission factor from a preset carbon flow database according to the time series energy consumption data;

[0052] The carbon emission calculation module is used to input the time-series energy consumption data and the corresponding carbon emission factor into the time-sharing carbon flow accounting model to obtain the time-sharing carbon emissions of the enterprise, and regulate and optimize the production process of the enterprise according to the time-sharing carbon emissions.

[0053] In a third aspect, an embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0054] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0055] The present invention provides a time-sharing measurement method, system, device and storage medium for enterprise carbon emissions. The present invention can accurately reflect the carbon emissions in different time periods through time-sharing measurement technology, and provide a scientific basis for the carbon emission management of enterprises by analyzing the time distribution characteristics of enterprise carbon emissions, providing strong support for the refined management and energy conservation and emission reduction of enterprises, and helping enterprises to formulate more effective time-sharing emission reduction strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a flow chart of a time-sharing measurement method for enterprise carbon emissions in an embodiment of the present invention;

[0057] Figure 2 It is a structural schematic diagram of a time-sharing measurement system for enterprise carbon emissions in an embodiment of the present invention;

[0058] Figure 3It is a diagram of the internal structure of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] See also Figure 1 The first embodiment of the present invention provides a time-sharing measurement method for enterprise carbon emissions, which includes steps S10 to S40:

[0061] Step S10, based on energy consumption and production consumption, construct a time-sharing carbon flow accounting model, analyze the production process of the enterprise, and determine the carbon flow calculation boundary of the enterprise, wherein the carbon flow calculation boundary includes the production activity boundary and the production process boundary that generate the carbon flow;

[0062] Step S20, determining whether there is a monitoring device in each target area corresponding to the carbon flow calculation boundary, if yes, using the monitoring device to collect data to obtain first time series energy consumption data, if no, using an image sensor device to collect data, and inputting the collected image data and sensor data into a pre-built energy consumption estimation model to obtain second time series energy consumption data;

[0063] Step S30, adding the first time series energy consumption data and the second time series energy consumption data to obtain time series energy consumption data, and extracting a corresponding carbon emission factor from a preset carbon flow database according to the time series energy consumption data;

[0064] Step S40, inputting the time-series energy consumption data and the corresponding carbon emission factor into the time-sharing carbon flow accounting model to obtain the time-sharing carbon emissions of the enterprise, and regulating and optimizing the production process of the enterprise according to the time-sharing carbon emissions.

[0065] The present invention proposes a time-sharing carbon emission measurement method for high-energy-consuming enterprises. First, a time-sharing carbon flow accounting model is constructed based on energy consumption and production consumption. The specific construction steps include:

[0066] According to the company's electric energy carbon emissions and non-electric energy carbon emissions, a time-sharing energy carbon flow accounting model is constructed;

[0067] According to the carbon emissions of raw materials, carbon absorption of products and carbon emissions of production process in enterprise production consumption, a time-sharing production carbon flow accounting model is constructed;

[0068] According to the time-sharing energy carbon flow accounting model and the time-sharing production carbon flow accounting model, a time-sharing carbon flow accounting model is obtained.

[0069] In this embodiment, the calculation of time-sharing carbon flow includes the carbon flow generated by energy consumption and the carbon flow generated by production consumption. For each time period, a carbon flow accounting model based on energy flow and carbon emission factors is constructed, which includes a time-sharing energy carbon flow accounting model and a time-sharing production carbon flow accounting model.

[0070] The time-sharing energy carbon flow accounting model includes the calculation of electric energy carbon emissions and non-electric energy, i.e. other energy carbon emissions, and combines them to obtain the total energy carbon emissions. Specifically, the following formula is used to represent electric energy carbon emissions:

[0071] E CO2-electricity (t)=Pelectricity(t)*EF electricity *Δt

[0072] In the formula, represents the carbon emissions of electricity energy in period t, Pelectricity(t) represents the average power in period t, EF electricity represents the carbon emission factor of electricity, and Δt represents the time interval between period t and the previous period.

[0073] The following formula is used to express non-electric energy carbon emissions:

[0074]

[0075] In the formula, represents the carbon emissions of non-electric energy in period t, Q other (t) represents the non-electric energy consumption during period t, EF other represents the carbon emission factor of non-electric energy, C carbon-other Indicates the carbon content in non-electric energy.

[0076] The following formula is used to express the time-sharing energy carbon flow accounting model:

[0077] E CO2-energy (t) = E CO2-electricity (t)+E CO2-other (t)

[0078] In the formula, E CO2-energy (t) represents the energy carbon emissions in period t.

[0079] In the time-sharing production carbon flow accounting model, carbon emissions are divided into carbon emissions generated by raw materials, carbon absorption of products and carbon emissions in the production process. The reason for carbon absorption is that in some production processes, such as the production of carbon-cured materials, products may absorb a certain amount of carbon. Therefore, it is also necessary to include it in the calculation of the carbon emissions of production activities. Specifically, the following formula is used to represent the carbon emissions of raw materials:

[0080]

[0081] In the formula, E CO2-raw (t) represents the carbon emission of raw materials put into production in period t, M raw-i (t) represents the input amount of the i-th raw material in period t, C carbon-raw-i represents the carbon content of the i-th raw material;

[0082] The product carbon absorption is expressed using the following formula:

[0083]

[0084] In the formula, E CO2-product (t) represents the carbon absorption of the product during period t, M product-j (t) represents the output of the jth product in period t, C carbon-product-j represents the carbon absorption of the jth product;

[0085] The following formula is used to express the carbon emissions during the production process:

[0086] E CO2-process (t) = Y product (t)*EF process

[0087] In the formula, E CO2-process (t) represents the carbon emissions generated by the production process during period t, Y product (t) represents the product output in period t, EF process represents the carbon emission factor of the production process;

[0088] The following formula is used to express the time-sharing production carbon flow accounting model:

[0089] E CO2-activity (t) = E CO2-raw (t)—E CO2-product (t)+E CO2-process (t)

[0090] In the formula, E CO2-activity (t) represents the carbon emissions generated by total production activities during period t.

[0091] The following formula is used to express the time-sharing carbon flow accounting model:

[0092] E CO2-total (t) = E CO2-energy (t)+E CO2-activity (t)

[0093] In the formula, E CO2-total (t) represents the total carbon emissions of the enterprise in period t.

[0094] Based on the above-mentioned time-sharing carbon flow accounting model, the production process of high-energy-consuming enterprises is analyzed to determine the carbon flow calculation boundary. The specific steps include:

[0095] According to the production process and scope of activities of the enterprise, the area and production stage where the carbon flow is generated are determined, and the production stage where the carbon flow is generated is analyzed to determine the production process that generates the carbon flow.

[0096] In this embodiment, the overall scope of high-energy-consuming enterprises for calculating carbon flow is first clarified, including all production workshops, auxiliary facilities (such as boiler rooms, power distribution rooms, etc.) and office areas related to production. Determine which activities and processes are included in the carbon flow calculation model. For example, for a steel company, it is necessary to cover the entire production chain from iron ore procurement, sintering, ironmaking, steelmaking to steel rolling. At the same time, the carbon flow involved in auxiliary links such as internal transportation and lighting in the enterprise cannot be ignored. On this basis, each major production process is analyzed to further determine the boundaries of the process flow. Taking the synthesis reaction in chemical production as an example, the scope of carbon flow calculation in the process from the reactant entering the reaction system to the product leaving the system is clarified, including the changes in carbon content in the raw materials, intermediate products, catalysts and other substances involved in the reaction, as well as the carbon emissions generated by the energy consumed in the reaction process (such as the energy required for heating, stirring, etc.).

[0097] By analyzing the company's production areas and each stage of the production process, we can determine the specific energy consumption and the specific stage of carbon flow generation. After clarifying the carbon flow calculation boundary, we collect relevant data on energy consumption and production consumption in the corresponding target area, thereby improving the data accuracy and efficiency of data collection.

[0098] In this embodiment, data collection is divided into two ways, one is to collect energy consumption data through energy consumption monitoring equipment, and the other is to estimate energy consumption data through image sensing equipment. Specifically, for energy consumption units such as production lines, office areas, and public areas of high-energy-consuming enterprises that are easy to install or have already installed monitoring equipment, energy consumption data is collected through installed smart meters, smart measuring instruments, smart water meters, flow meters and other high-precision collection equipment. For example, the collection frequency is one period every 15 minutes, and a total of 96 periods a day to obtain the corresponding time series energy consumption data, and then the data is transmitted to the back end through integrated Internet of Things technology, wireless communication technology and other technologies for subsequent carbon emissions calculation. For some areas where monitoring equipment cannot be installed or energy consumption data cannot be directly collected through monitoring equipment, image data and sensor data can be obtained through image sensing equipment, and data processing is performed through models to estimate energy consumption data. The specific steps include:

[0099] Acquire peripheral sensor data of the target area through a sensor device, extract peripheral feature data from the peripheral sensor data through a principal component analysis method, and input the peripheral feature data into a pre-constructed first energy consumption estimation model to obtain first energy consumption data;

[0100] Acquire image data of the target area through an image acquisition device, input the image data into a pre-built second energy consumption estimation model to obtain energy consumption information, and convert the energy consumption information into second energy consumption data;

[0101] The first energy consumption data and the second energy consumption data are processed to obtain second time series energy consumption data.

[0102] In this embodiment, sensor devices and image acquisition devices cooperate with each other to collect data from areas where energy consumption data cannot be directly obtained. Specifically, sensor devices are installed to collect production-related peripheral sensor data from the target area. For example, in the workshop area, data such as the overall energy consumption of the workshop, equipment operating status, ambient temperature and humidity, etc. can be obtained. For example, in the ventilation equipment area, sensors are used to collect the operating status of the ventilation equipment such as the rotation speed and ventilation volume. Then, the principal component analysis method is used to extract features from the peripheral sensor data. At the same time, a supervised learning algorithm such as a support vector machine is used to construct a first energy consumption estimation model. The first energy consumption estimation model is trained with known energy consumption distribution conditions in historical data as labels, and is optimized through cross-validation, etc., and then the extracted peripheral feature data is input into the trained energy consumption estimation model to obtain the first energy consumption data. It should be noted that the first energy consumption estimation model here is constructed based on different target areas. For different enterprises, there may be one or more first energy consumption estimation models.

[0103] For relevant areas where sensor equipment cannot be installed or cannot be collected by sensor equipment, in order to improve the calculation accuracy of enterprise carbon emissions, this embodiment also provides image recognition based on deep learning to assist data collection, by installing an image acquisition device, such as a high-definition camera or a high-definition camera, in the target area where no relevant equipment including monitoring equipment and sensor equipment is installed, and collecting images of the production process through the image acquisition device, and then the image is pre-processed by cropping, scaling, graying, etc., and then input into a pre-constructed second energy consumption estimation model to extract energy consumption information, wherein the second energy consumption estimation model is constructed by a target recognition model such as a YOLO model and a convolutional neural network model, the target recognition model can identify areas related to energy consumption from the collected image, and the convolutional neural network model can extract energy consumption information from the identified area, and finally the energy consumption information is converted by formulas and processed by data to obtain second energy consumption data. Then the first energy consumption data and the second energy consumption data are integrated and time-series divided to obtain second time-series energy consumption data. It should be noted here that different carbon flow calculation boundaries will exist depending on the type of enterprise, so their time series energy consumption data and the energy and production energy consumption data specifically included in the time series energy consumption data will also be different. The specific energy consumption calculation steps can be calculated according to the above steps based on the actual situation of the enterprise, and will not be repeated here.

[0104] The collected data is transmitted wirelessly or wired, for example, through an existing power line network or an enterprise's automated management system. In addition, the collected data also needs to be pre-processed such as data cleaning and format conversion to ensure the accuracy, consistency and rationality of the data.

[0105] Furthermore, in order to improve the quality and efficiency of data collection, in a preferred embodiment, the present invention also provides a method for optimizing the collection frequency, and the specific steps thereof include:

[0106] Define the state space according to the environmental state of the target area, define the action space according to the data collection frequency and data transmission strategy, define the reward function according to the data accuracy and resource consumption, and use the reinforcement learning algorithm for training to obtain the optimal data collection frequency;

[0107] According to the optimal data collection frequency, the data collection frequency is adjusted.

[0108] In this embodiment, the environmental state of the target area is defined as a state space, and the environmental state includes equipment operation status, personnel flow status, and network communication quality. The data collection frequency and data upload strategy are used as the action space. The reward function is designed according to the data accuracy and communication resource consumption. Reinforcement learning is used for training. Through simulation or small-scale actual test environment training and continuous fine-tuning, the optimal data collection frequency and upload strategy under the current state are obtained to optimize the data collection and upload process and ensure that the carbon flow accounting model can obtain data in a timely and accurate manner. The upload strategy here includes the upload time interval, data volume and other transmission parameters related to data transmission. The specific parameters can be flexibly set according to the actual situation, and no excessive restrictions are made here.

[0109] Based on the above-mentioned time-sharing carbon flow accounting model, it can be known that a carbon emission factor is required when calculating carbon emissions. In this embodiment, a carbon flow database is pre-built based on the carbon emission factor, and the carbon emission factor used by the enterprise in the carbon flow calculation process is stored in the carbon flow database. In the process of building the database, the specific value of the carbon emission factor needs to be determined.

[0110] The determination of carbon emission factors requires a combination of multiple approaches. For energy carbon emission factors, on the one hand, they can be based on scientific research and stoichiometric calculations, such as the chemical composition of fossil fuels and the combustion reaction equation. For example, the stoichiometric relationship of natural gas combustion can calculate the amount of carbon dioxide produced per unit mass of combustion; on the other hand, it is necessary to refer to the data of relevant authoritative organizations, such as the National Greenhouse Gas Inventory Guidelines issued by the IPCC, and the energy statistics of the IEA, as well as the data released by the energy management departments of various countries in combination with their own energy structures and the data obtained by local environmental protection departments based on local industry surveys and monitoring. In addition, energy companies themselves can also determine it through long-term data statistics or experimental research on special energy utilization methods.

[0111] For non-energy related carbon emission factors (i.e. industrial production processes), one is to base the calculation on industry standards and guidelines. The standards formulated by different industry associations specify the calculation methods for carbon emission factors of production processes and products. The second is to analyze the company's specific production process data and combine it with energy consumption calculations through mass balance principles. The third is to rely on experimental research and monitoring data, which can be determined in laboratory simulations or by using the company's continuous emission monitoring system combined with production data.

[0112] After obtaining the time series energy consumption data based on the above steps, the corresponding carbon emission factors can be extracted from the carbon flow database according to the specific energy consumption data. At the same time, for the product parameters involved in the time-sharing carbon flow accounting model, the specific product types, output and carbon content can be determined through production statistics and product analysis, and then substituted into the time-sharing carbon flow accounting model to calculate the total carbon emissions of the enterprise during the target period.

[0113] After obtaining the carbon emissions of the enterprise in each time period, a carbon emission curve is established based on the time-sharing carbon emissions, and the carbon emissions of the enterprise are analyzed, so as to achieve precise control and optimization of the production process. The specific optimization steps will not be repeated here one by one.

[0114] This embodiment provides a time-sharing measurement method for enterprise carbon emissions. The present invention uses time-sharing measurement technology to accurately reflect the carbon emissions in different time periods, improve the accuracy of carbon emission measurement for high-energy-consuming enterprises, simplify the carbon emission calculation process, reduce calculation costs, and improve calculation efficiency. The present invention provides a scientific basis for the carbon emission management of enterprises by analyzing the time distribution characteristics of enterprise carbon emissions, provides strong support for the refined management and energy conservation and emission reduction of enterprises, and helps enterprises to formulate more effective time-sharing emission reduction strategies. The time-sharing measurement method provided by the present invention can be adjusted and optimized according to the actual needs of the enterprise, is suitable for different types of high-energy-consuming enterprises, and has extremely high flexibility and scalability.

[0115] See also Figure 2 Based on the same inventive concept, a time-sharing measurement system for enterprise carbon emissions proposed in the second embodiment of the present invention includes:

[0116] The model building module 10 is used to build a time-sharing carbon flow accounting model based on energy consumption and production consumption, and analyze the production process of the enterprise to determine the carbon flow calculation boundary of the enterprise, wherein the carbon flow calculation boundary includes the production activity boundary and the production process boundary that generate the carbon flow;

[0117] The energy consumption data estimation module 20 is used to determine whether there is a monitoring device in each target area corresponding to the carbon flow calculation boundary. If so, the monitoring device is used to collect data to obtain the first time series energy consumption data. If not, the image sensor device is used to collect data, and the collected image data and sensor data are input into a pre-built energy consumption estimation model to obtain the second time series energy consumption data.

[0118] Adding the first time series energy consumption data and the second time series energy consumption data to obtain time series energy consumption data, and extracting a corresponding carbon emission factor from a preset carbon flow database according to the time series energy consumption data;

[0119] The carbon emission calculation module 30 is used to input the time-series energy consumption data and the corresponding carbon emission factor into the time-sharing carbon flow accounting model to obtain the time-sharing carbon emissions of the enterprise, and regulate and optimize the production process of the enterprise according to the time-sharing carbon emissions.

[0120] The technical features and technical effects of the time-sharing metering system for corporate carbon emissions proposed in the embodiment of the present invention are the same as the method proposed in the embodiment of the present invention, and will not be repeated here. Each module in the above-mentioned time-sharing metering system for corporate carbon emissions can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0121] In addition, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0122] See also Figure 3 , an internal structure diagram of a computer device in an embodiment, the computer device can specifically be a terminal or a server. The computer device includes a processor, a memory, a network interface, a display and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a time-sharing metering method for corporate carbon emissions is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0123] It can be understood by those skilled in the art that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computing device may include more or fewer components than shown in the figure, or combine certain components, or have the same component arrangement.

[0124] In addition, an embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0125] In summary, the embodiments of the present invention propose a time-sharing measurement method, system, device and storage medium for enterprise carbon emissions. The method constructs a time-sharing carbon flow accounting model based on energy consumption and production consumption, analyzes the production process of the enterprise, and determines the carbon flow calculation boundary of the enterprise, wherein the carbon flow calculation boundary includes the production activity boundary and the production process boundary that generate the carbon flow; determines whether there is a monitoring device in each target area corresponding to the carbon flow calculation boundary, and if so, uses the monitoring device to collect data to obtain first time series energy consumption data; if not, collects data through an image sensing device, and inputs the collected image data and sensor data into a pre-constructed energy consumption estimation model to obtain second time series energy consumption data; adds the first time series energy consumption data and the second time series energy consumption data to obtain time series energy consumption data, and extracts the corresponding carbon emission factor from a preset carbon flow database according to the time series energy consumption data; inputs the time series energy consumption data and the corresponding carbon emission factor into the time-sharing carbon flow accounting model to obtain the time-sharing carbon emissions of the enterprise, and regulates and optimizes the production process of the enterprise according to the time-sharing carbon emissions. The present invention uses time-sharing metering technology to accurately reflect the carbon emissions in different time periods, improves the accuracy of carbon emission measurement of high-energy-consuming enterprises, simplifies the carbon emission calculation process, reduces calculation costs, and improves calculation efficiency. The present invention provides a scientific basis for the carbon emission management of enterprises by analyzing the time distribution characteristics of enterprise carbon emissions, provides strong support for the refined management and energy conservation and emission reduction of enterprises, and helps enterprises to formulate more effective time-sharing emission reduction strategies. The time-sharing metering method provided by the present invention can be adjusted and optimized according to the actual needs of the enterprise, is suitable for different types of high-energy-consuming enterprises, and has extremely high flexibility and scalability.

[0126] Each embodiment in this specification is described in a progressive manner, and the same or similar parts of each embodiment can be directly referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. It should be noted that the technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above-mentioned embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0127] The above-mentioned embodiments only express several preferred implementation modes of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in the technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be regarded as the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be based on the protection scope of the claims.

Claims

1. A time-sharing measurement method for enterprise carbon emissions, characterized in that: include: Based on energy consumption and production consumption, a time-sharing carbon flow accounting model is constructed, and the production process of the enterprise is analyzed to determine the carbon flow calculation boundary of the enterprise, which includes the production activity boundary and production process boundary that generate carbon flow; Determine whether there is a monitoring device in each target area corresponding to the carbon flow calculation boundary. If so, use the monitoring device to collect data to obtain first time series energy consumption data. If not, use an image sensor device to collect data, and input the collected image data and sensor data into a pre-built energy consumption estimation model to obtain second time series energy consumption data. Adding the first time series energy consumption data and the second time series energy consumption data to obtain time series energy consumption data, and extracting a corresponding carbon emission factor from a preset carbon flow database according to the time series energy consumption data; The time-series energy consumption data and the corresponding carbon emission factors are input into the time-sharing carbon flow accounting model to obtain the time-sharing carbon emissions of the enterprise, and the production process of the enterprise is regulated and optimized according to the time-sharing carbon emissions.

2. The time-sharing measurement method for enterprise carbon emissions according to claim 1 is characterized in that: The steps of constructing a time-sharing carbon flow accounting model based on energy consumption and production consumption include: According to the company's electric energy carbon emissions and non-electric energy carbon emissions, a time-sharing energy carbon flow accounting model is constructed; According to the carbon emissions of raw materials, carbon absorption of products and carbon emissions of production process in enterprise production consumption, a time-sharing production carbon flow accounting model is constructed; According to the time-sharing energy carbon flow accounting model and the time-sharing production carbon flow accounting model, a time-sharing carbon flow accounting model is obtained.

3. The time-sharing measurement method for enterprise carbon emissions according to claim 1 is characterized in that: The steps of analyzing the production process of the enterprise and determining the carbon flow calculation boundary of the enterprise include: According to the production process and scope of activities of the enterprise, the area and production stage where the carbon flow is generated are determined, and the production stage where the carbon flow is generated is analyzed to determine the production process that generates the carbon flow.

4. The time-sharing measurement method for enterprise carbon emissions according to claim 1 is characterized in that: The step of collecting data through an image sensor device and inputting the collected image data and sensor data into a pre-built energy consumption estimation model to obtain time series energy consumption data includes: Acquire peripheral sensor data of the target area through a sensor device, extract peripheral feature data from the peripheral sensor data through a principal component analysis method, and input the peripheral feature data into a pre-constructed first energy consumption estimation model to obtain first energy consumption data; Acquire image data of the target area through an image acquisition device, input the image data into a pre-built second energy consumption estimation model to obtain energy consumption information, and convert the energy consumption information into second energy consumption data; The first energy consumption data and the second energy consumption data are processed to obtain second time series energy consumption data.

5. The time-sharing measurement method for enterprise carbon emissions according to claim 4 is characterized in that: After the step of obtaining the time series energy consumption data, the method further includes: Define the state space according to the environmental state of the target area, define the action space according to the data collection frequency and data transmission strategy, define the reward function according to the data accuracy and resource consumption, and use the reinforcement learning algorithm for training to obtain the optimal data collection frequency; According to the optimal data collection frequency, the data collection frequency is adjusted.

6. The time-sharing measurement method for enterprise carbon emissions according to claim 2 is characterized in that: The following formula is used to express the carbon emissions of electric energy: In the formula, in the formula, represents the carbon emissions generated by electric energy in period t, Pelectricity(t) represents the average electric power in period t, EF electricity represents the carbon emission factor of electricity, Δt represents the time interval; The following formula is used to express non-electric energy carbon emissions: In the formula, in the formula, represents the carbon emissions from non-electric energy during period t, Q other (t) represents the non-electric energy consumption during period t, EF other represents the carbon emission factor of non-electric energy, C carbon-other Indicates the carbon content of non-electric energy; The following formula is used to express the time-sharing energy carbon flow accounting model: E CO2-energy (t)=E CO2-electricity (t)+E CO2-other (t) In the formula, E CO2-energy (t) represents the carbon emissions generated by the total energy in period t; The following formula is used to express the carbon emissions of raw materials: In the formula, E CO2-raw (t) represents the carbon emission of raw materials put into production in period t, M raw-i (t) represents the input amount of the i-th raw material in period t, C carbon-raw-i represents the carbon content of the i-th raw material; The product carbon absorption is expressed using the following formula: In the formula, E CO2-product (t) represents the carbon absorption of the product during period t, M product-j (t) represents the output of the jth product in period t, C carbon-product-j represents the carbon absorption of the jth product; The following formula is used to express the carbon emissions during the production process: E CO2-process (t)=Y product (t)*EF process In the formula, E CO2-process (t) represents the carbon emissions generated by the production process during period t, Y product (t) represents the product output in period t, EF process represents the carbon emission factor of the production process; The following formula is used to express the time-sharing production carbon flow accounting model: E CO2-activity (t)=E CO2-raw (t)—E CO2-product (t)+E CO2-process (t) In the formula, E CO2-activity (t) represents the carbon emissions generated by total production activities during period t; The following formula is used to express the time-sharing carbon flow accounting model: E CO2-total (t)=E CO2-energy (t)+E CO2-activity (t) In the formula, E CO2-total (t) represents the total carbon emissions of the enterprise in period t.

7. The time-sharing measurement method for enterprise carbon emissions according to claim 4 is characterized in that: The first energy consumption estimation model is constructed based on a support vector machine; The second energy consumption estimation model is constructed based on a target recognition model and a convolutional neural network. The target recognition model is used to extract energy consumption related images from image data, and the convolutional neural network model is used to extract energy consumption information from the energy consumption related images.

8. A time-sharing measurement system for enterprise carbon emissions, characterized in that: include: A model building module is used to build a time-sharing carbon flow accounting model based on energy consumption and production consumption, and analyze the production process of the enterprise to determine the carbon flow calculation boundary of the enterprise, which includes the production activity boundary and production process boundary that generate carbon flow; An energy consumption data estimation module is used to determine whether there is a monitoring device in each target area corresponding to the carbon flow calculation boundary. If so, the monitoring device is used to collect data to obtain first time series energy consumption data. If not, the image sensor device is used to collect data, and the collected image data and sensor data are input into a pre-built energy consumption estimation model to obtain second time series energy consumption data. Adding the first time series energy consumption data and the second time series energy consumption data to obtain time series energy consumption data, and extracting a corresponding carbon emission factor from a preset carbon flow database according to the time series energy consumption data; The carbon emission calculation module is used to input the time-series energy consumption data and the corresponding carbon emission factor into the time-sharing carbon flow accounting model to obtain the time-sharing carbon emissions of the enterprise, and regulate and optimize the production process of the enterprise according to the time-sharing carbon emissions.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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