Carbon emission optimization method and system

Abstract

The invention discloses a carbon emission optimization method and system, and relates to the technical field of carbon emission optimization management. The carbon emission optimization method comprises the following steps: evaluating the sensitivity of a sensor; building equipment carbon emission evaluation; and evaluating the energy consumption of the building equipment. According to the invention, sensor sensitivity evaluation is carried out through the obtained monitoring related data to obtain the sensor monitoring sensitivity coefficient, and whether monitoring sensitivity optimization is carried out or not is judged based on the sensor monitoring sensitivity coefficient. Then obtaining a building equipment carbon emission evaluation coefficient according to the obtained qualified sensor monitoring sensitivity coefficient and the obtained building carbon emission monitoring related data, judging whether to carry out carbon emission optimization evaluation, and finally judging whether to carry out carbon emission optimization according to the obtained building equipment energy consumption evaluation coefficient. The effect of improving the carbon emission optimization sufficiency is achieved, and the problem that in the prior art, optimization data is low in accuracy in the carbon emission optimization process is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission optimization management, and in particular to a carbon emission optimization method and system. Background Art

[0002] Carbon emission optimization will promote the high-end, intelligent and green development of traditional industries and promote the optimization and upgrading of the entire industrial chain. Smart grids can help reduce carbon emissions by optimizing energy distribution and use. Smart grids can monitor grid load and power supply in real time, dynamically adjust power supply according to demand, and reduce energy waste. At the same time, smart grids also support the access and management of distributed energy, such as renewable energy such as solar and wind power, thereby reducing dependence on fossil fuels and carbon emissions. Smart grids can be combined with smart building systems to achieve intelligent management of building energy.

[0003] Existing carbon emission optimization methods mainly monitor the energy consumption of buildings in real time. Smart grids can automatically adjust the building's heating, cooling, lighting and other systems to achieve optimal energy utilization efficiency, thereby effectively reducing energy waste.

[0004] For example, the invention patent announcement with announcement number: CN114330826B announces a carbon emission prediction and optimization method, including: S1. Obtaining the comprehensive energy consumption data of various types of designated energy in the park within a preset historical time period and determining whether there is an energy conversion enterprise in the park. If so, analyzing and processing the data of the energy conversion enterprise; if not, proceeding to the next step; S2. Distinguishing between energy production data, primary energy consumption data and secondary energy consumption data in the comprehensive energy consumption data and analyzing the changing patterns within a preset time period; S3. Determining whether it is necessary to conduct carbon emission prediction and analysis on the park. If so, establishing a park carbon emission prediction model based on the changing patterns to predict the park's carbon emissions, and conducting carbon emission optimization analysis on the park; if not, directly conducting carbon emission optimization analysis on the park.

[0005] For example, the carbon emission optimization method and related equipment disclosed in the invention patent application with publication number: CN115713142A include: responding to a carbon footprint analysis request for a target product, calculating the carbon emissions of the target product at multiple stages in its life cycle; calculating the total emissions of the target product based on the carbon emissions at multiple stages; if the total emissions of the target product are greater than a preset threshold, obtaining the optimization level and optimization strategy corresponding to each stage of the target product in its life cycle; and determining a management and control strategy for optimizing the carbon emissions of the target product based on the optimization level and optimization strategy.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the prior art, the real-time monitoring of a building's energy consumption is affected by environmental factors. For example, extreme weather (high temperature or lightning) may cause the sensor's carbon emission performance in monitoring building equipment to deteriorate, resulting in inaccurate carbon emission data during carbon emission optimization, leading to the problem of low accuracy of optimization data during carbon emission optimization. Summary of the invention

[0008] The embodiments of the present application provide a carbon emission optimization method and system, thereby solving the problem of low accuracy of optimization data in the carbon emission optimization process in the prior art and improving the adequacy of carbon emission optimization.

[0009] An embodiment of the present application provides a carbon emission optimization method, comprising the following steps: S1, performing sensor sensitivity evaluation through acquired monitoring-related data to obtain a sensor monitoring sensitivity coefficient, and judging whether to perform monitoring sensitivity optimization based on the sensor monitoring sensitivity coefficient, wherein the sensor monitoring sensitivity coefficient is used to evaluate the monitoring sensitivity of a preset sensor in monitoring carbon emissions of building equipment; S2, obtaining a building equipment carbon emission evaluation coefficient based on acquired qualified sensor monitoring sensitivity coefficients and acquired building carbon emission monitoring-related data, wherein the building equipment carbon emission evaluation coefficient is used to evaluate changes in carbon emissions during the building equipment carbon emission process; S3, judging whether to perform a carbon emission optimization evaluation based on the building equipment carbon emission evaluation coefficient, obtaining a building equipment energy consumption evaluation coefficient based on acquired unqualified building equipment carbon emission evaluation coefficients and acquired average power of building equipment, and judging whether to perform carbon emission optimization based on the building equipment energy consumption evaluation coefficient, wherein the building equipment energy consumption evaluation coefficient is used to evaluate energy consumption during the building equipment carbon emission process.

[0010] Furthermore, the monitoring-related data include output current signal change, initial current output signal, temperature change, output signal frequency and transmission conductivity; the output current signal change represents the average change in output current of a preset monitoring sensor within a preset monitoring area; the temperature change represents the average change in ambient temperature within a preset monitoring area; the output signal frequency represents the average frequency corresponding to the output current of building equipment within a preset monitoring area; the building carbon emission monitoring-related data include the average operating time of building equipment and the average usage frequency of building equipment.

[0011] Furthermore, the sensor monitoring sensitivity coefficient is obtained by processing the temperature coefficient interference ratio and the signal attenuation interference ratio; the specific acquisition process of the temperature coefficient interference ratio is as follows: the initial temperature coefficient value is obtained by performing a ratio operation on the output current signal change and the product of the initial current output signal and the temperature change; the temperature coefficient interference ratio is obtained by performing a ratio operation on the initial temperature coefficient value and the preset temperature coefficient average value obtained from the database; the temperature coefficient interference ratio is used to describe the temperature coefficient interference situation of the preset monitoring sensor in the preset monitoring area; the specific acquisition process of the signal attenuation interference ratio is as follows: the initial signal attenuation value is obtained by performing an operation on the output signal frequency, the transmission conductivity and the speed of light obtained from the database; the signal attenuation interference ratio is obtained by performing a ratio operation on the initial signal attenuation value and the preset signal attenuation average value obtained from the database; the signal attenuation interference ratio is used to describe the interference situation of the current signal attenuation of the preset monitoring sensor in the preset monitoring area.

[0012] Furthermore, the specific process of judging whether to perform monitoring sensitivity optimization based on the sensor monitoring sensitivity coefficient is as follows: judging whether the sensor monitoring sensitivity coefficient is not lower than the reference monitoring sensor sensitivity threshold, if so, marking the sensor monitoring sensitivity coefficient that is not lower than the reference monitoring sensor sensitivity threshold as a qualified sensor monitoring sensitivity coefficient, otherwise performing monitoring sensitivity optimization; the specific steps of the monitoring sensitivity optimization are: step one, performing data filtering, when the monitored sensor monitoring sensitivity coefficient is not lower than the reference monitoring sensor sensitivity threshold, stopping step one, otherwise executing step two; step two, sending a prompt to a preset personnel to amplify the output signal, when the monitored sensor monitoring sensitivity coefficient is not lower than the reference monitoring sensor sensitivity threshold, stopping step two, otherwise sending a monitoring abnormality prompt to the preset personnel.

[0013] Furthermore, the carbon emission assessment coefficient of the building equipment is obtained by processing the operating time compliance ratio, the usage frequency compliance ratio and the qualified sensor monitoring sensitivity coefficient; the operating time compliance ratio is represented by the result of the ratio operation between the average operating time of the building equipment and the preset operating time maximum value obtained from the database; the usage frequency compliance ratio is represented by the result of the ratio operation between the average usage frequency of the building equipment and the preset usage frequency maximum value obtained from the database.

[0014] Furthermore, the specific acquisition process of judging whether to conduct carbon emission optimization assessment based on the building equipment carbon emission assessment coefficient is as follows: judging whether the building equipment carbon emission assessment coefficient is not lower than the reference carbon emission average value: if so, the building equipment carbon emission assessment coefficient corresponding to the building equipment carbon emission assessment coefficient that is not lower than the reference carbon emission average value obtained from the database is marked as an unqualified building equipment carbon emission assessment coefficient, and the carbon emission optimization assessment is conducted; if not, the carbon emission optimization assessment is not conducted.

[0015] Furthermore, the specific process of obtaining the building equipment energy consumption assessment coefficient based on the obtained unqualified building equipment carbon emission assessment coefficient and the obtained average power of the building equipment is as follows: the initial equipment energy consumption value is obtained by multiplying the average operation time of the building equipment corresponding to the unqualified building equipment carbon emission assessment coefficient and the average power of the building equipment; the equipment energy consumption compliance ratio is obtained by ratio calculation of the initial equipment energy consumption value and the preset maximum value of the building equipment energy consumption obtained from the database; the building equipment energy consumption assessment coefficient is obtained by combining the equipment energy consumption compliance ratio and the unqualified building equipment carbon emission assessment coefficient; the equipment energy consumption compliance ratio is used to describe the energy consumption compliance of the building equipment in the preset monitoring area.

[0016] Furthermore, the specific process of judging whether to perform carbon emission optimization based on the energy consumption assessment coefficient of building equipment is as follows: judging whether the energy consumption assessment coefficient of building equipment is not lower than the maximum reference energy consumption obtained from the database, if not, it indicates that the energy consumption of the building equipment is qualified and carbon emission optimization is not performed; otherwise, carbon emission optimization is performed, and the steps of carbon emission optimization are: the first step is to perform gain adjustment. When the monitored energy consumption assessment coefficient of the building equipment is lower than the maximum reference energy consumption, the first step is stopped, otherwise the second step is performed; the second step is to send a prompt to the preset personnel to change the position of the building equipment air outlet. When the monitored energy consumption assessment coefficient of the building equipment is lower than the maximum reference energy consumption, the second step is stopped, otherwise a carbon emission abnormality prompt is sent to the preset personnel.

[0017] Furthermore, the limiting expression of the sensor monitoring sensitivity coefficient is as follows:

[0018]

[0019] In the formula, represents the sensor monitoring sensitivity coefficient of the preset monitoring sensor in the x-th preset time period, x=1,2,...,k, x represents the number of the preset time period, k represents the total number of preset time periods, Indicates the temperature coefficient interference ratio of the preset monitoring sensor in the xth preset time period, It represents the signal attenuation-interference ratio of the preset monitoring sensor in the x-th preset time period, and e represents a natural constant.

[0020] The embodiment of the present application provides a carbon emission optimization system, including a sensor sensitivity evaluation module, a building equipment carbon emission evaluation module and a building equipment energy consumption evaluation module: wherein the sensor sensitivity evaluation module is used to perform sensor sensitivity evaluation through acquired monitoring-related data to obtain a sensor monitoring sensitivity coefficient, and judge whether to perform monitoring sensitivity optimization based on the sensor monitoring sensitivity coefficient, and the sensor monitoring sensitivity coefficient is used to evaluate the monitoring sensitivity of the preset sensor in the process of monitoring the carbon emission of building equipment; the building equipment carbon emission evaluation module is used to obtain a building equipment carbon emission evaluation coefficient based on the acquired qualified sensor monitoring sensitivity coefficient and the acquired building carbon emission monitoring-related data, and the building equipment carbon emission evaluation coefficient is used to evaluate the change in carbon emissions during the carbon emission process of building equipment; the building equipment energy consumption evaluation module is used to judge whether to perform a carbon emission optimization evaluation based on the building equipment carbon emission evaluation coefficient, and obtain a building equipment energy consumption evaluation coefficient based on the acquired unqualified building equipment carbon emission evaluation coefficient and the acquired average power of the building equipment, and judge whether to perform carbon emission optimization based on the building equipment energy consumption evaluation coefficient, and the building equipment energy consumption evaluation coefficient is used to evaluate the energy consumption of the building equipment in the carbon emission process.

[0021] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0022] 1. By monitoring relevant data, the sensor sensitivity evaluation is performed to obtain the sensor monitoring sensitivity coefficient and determine whether to optimize the monitoring sensitivity. Then, based on the obtained carbon emission evaluation coefficient of the building equipment, it is determined whether to perform carbon emission optimization evaluation. Finally, based on the obtained building equipment energy consumption evaluation coefficient, it is determined whether to perform carbon emission optimization. This improves the reliability of the optimization data in the carbon emission optimization process, and further improves the adequacy of the carbon emission optimization, effectively solving the problem of low accuracy of the optimization data in the carbon emission optimization process in the prior art.

[0023] 2. The sensor monitoring sensitivity coefficient is obtained by processing the temperature coefficient interference ratio and the signal attenuation interference ratio, and then the building equipment carbon emission assessment coefficient is obtained by processing the operating time compliance ratio, the use frequency compliance ratio and the qualified sensor monitoring sensitivity coefficient. Finally, the building equipment energy consumption assessment coefficient is calculated by combining the equipment energy consumption compliance ratio and the unqualified building equipment carbon emission assessment coefficient, thereby achieving the improvement of the accuracy of obtaining carbon emission optimization related data, and then achieving the improvement of the effectiveness of carbon emission optimization.

[0024] 3. By judging whether the sensor monitoring sensitivity coefficient is not lower than the sensitivity threshold of the reference monitoring sensor, if so, the sensor monitoring sensitivity coefficient that is not lower than the sensitivity threshold of the reference monitoring sensor is marked as a qualified sensor monitoring sensitivity coefficient, otherwise data filtering and output signal amplification are performed, thereby achieving the improvement of the sensitivity of the preset sensor in monitoring carbon emissions, and then achieving the accurate quantification of the monitoring sensitivity of the preset sensor in monitoring carbon emissions of construction equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A flow chart of a carbon emission optimization method provided in an embodiment of the present application;

[0026] Figure 2 A statistical diagram showing the change in the average operation time of the construction equipment provided in the embodiment of the present application - the operation time compliance ratio;

[0027] Figure 3 A structural schematic diagram of a carbon emission optimization system provided in an embodiment of the present application;

[0028] Figure 4 An overall flow chart provided for an embodiment of the present application. DETAILED DESCRIPTION

[0029] The embodiments of the present application solve the problem of low accuracy of optimization data in the carbon emission optimization process in the prior art by providing a carbon emission optimization method and system. The sensor sensitivity is evaluated by using the acquired monitoring-related data to obtain the sensor monitoring sensitivity coefficient. Based on the sensor monitoring sensitivity coefficient, it is determined whether to perform monitoring sensitivity optimization. Then, the building equipment carbon emission assessment coefficient is obtained according to the acquired qualified sensor monitoring sensitivity coefficient and the acquired building carbon emission monitoring-related data. Then, based on the building equipment carbon emission assessment coefficient, it is determined whether to perform carbon emission optimization evaluation. Then, based on the acquired unqualified building equipment carbon emission assessment coefficient and the acquired average power of the building equipment, the building equipment energy consumption assessment coefficient is obtained. Finally, based on the building equipment energy consumption assessment coefficient, it is determined whether to perform carbon emission optimization, thereby improving the adequacy of carbon emission optimization.

[0030] The technical solution in the embodiment of the present application is to solve the problem of low accuracy of optimization data in the above carbon emission optimization process. The overall idea is as follows:

[0031] By monitoring relevant data to evaluate the sensor sensitivity, we obtain the sensor monitoring sensitivity coefficient and determine whether to optimize the monitoring sensitivity. Then, we determine whether to optimize the carbon emission based on the obtained carbon emission assessment coefficient of the building equipment. Finally, we determine whether to optimize the carbon emission based on the obtained energy consumption assessment coefficient of the building equipment, thereby achieving the effect of improving the adequacy of carbon emission optimization.

[0032] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0033] like Figure 1 As shown, it is a flow chart of a carbon emission optimization method provided by an embodiment of the present application, and the method includes the following steps: S1, sensor sensitivity evaluation: sensor sensitivity evaluation is performed through the acquired monitoring related data to obtain the sensor monitoring sensitivity coefficient, and whether to perform monitoring sensitivity optimization is determined based on the sensor monitoring sensitivity coefficient. The monitoring sensitivity optimization is used to improve the sensitivity of the preset sensor in the process of monitoring the carbon emission of building equipment, and the sensor monitoring sensitivity coefficient is used to evaluate the monitoring sensitivity of the preset sensor in the process of monitoring the carbon emission of building equipment; S2, building equipment carbon emission evaluation: according to the acquired qualified sensor monitoring sensitivity coefficient and the acquired building The carbon emission monitoring related data obtains the building equipment carbon emission assessment coefficient, which is used to evaluate the changes in carbon emissions during the carbon emission process of building equipment; S3, building equipment energy consumption assessment: based on the building equipment carbon emission assessment coefficient, determine whether to conduct carbon emission optimization assessment, and obtain the building equipment energy consumption assessment coefficient based on the obtained unqualified building equipment carbon emission assessment coefficient and the obtained average power of the building equipment. Based on the building equipment energy consumption assessment coefficient, determine whether to conduct carbon emission optimization. Carbon emission optimization is used to reduce energy consumption in the carbon emission process of building equipment. The building equipment energy consumption assessment coefficient is used to evaluate the energy consumption of building equipment in the carbon emission process.

[0034] It should be added that the monitoring-related data include the output current signal change, the initial current output signal, the temperature change, the output signal frequency and the transmission conductivity; the output current signal change represents the average change in the output current of the preset monitoring sensor in the preset monitoring area; the temperature change represents the average change in the ambient temperature in the preset monitoring area; the output signal frequency represents the average frequency corresponding to the output current of the building equipment in the preset monitoring area; the transmission conductivity represents the conductivity of the preset transmission medium in the preset monitoring area.

[0035] The relevant data for building carbon emission monitoring include the average operating time of building equipment and the average frequency of use of building equipment; the average operating time of building equipment indicates the average operating time of building equipment in the preset monitoring area; the average frequency of use of building equipment indicates the average frequency of use of building equipment in the preset monitoring area; the average power of building equipment indicates the average power of building equipment in the preset monitoring area.

[0036] It needs to be explained that the output current signal change within the preset time period and the initial current output signal at the beginning of the preset time period are measured by the current sensor, the temperature change within the preset time period is measured by the temperature sensor, the output signal frequency of the building equipment within the preset time period is measured by the spectrum analyzer, the conductivity of the preset transmission medium (cable, etc.) within the preset time period is measured by the electrical conductivity sensor, the average operation time of the building equipment within the preset time period is measured by the timer, the average usage frequency of the building equipment within the preset time period is measured by the frequency counter, and the average power of the building equipment within the preset time period is measured by the power sensor. The preset monitoring sensors include current sensors, temperature sensors, electrical conductivity sensors and power sensors. The building equipment includes lighting fixtures, boilers and radiators. The sensor monitoring sensitivity coefficient and the corresponding monitoring-related data are analyzed for a single preset monitoring sensor. When a single preset monitoring sensor is lower than the sensitivity threshold of the reference monitoring sensor, the monitoring sensitivity is optimized. The building equipment carbon emission assessment coefficient, the building equipment energy consumption assessment coefficient and the corresponding building carbon emission monitoring-related data and the average power of the building equipment are analyzed and calculated based on the average values ​​of all preset monitoring sensors.

[0037] In this embodiment, there is a close mutual influence relationship between the sensor monitoring sensitivity coefficient, the building equipment carbon emission assessment coefficient and the building equipment energy consumption assessment coefficient. The sensor monitoring sensitivity coefficient is the basis, which determines the accuracy and reliability of the carbon emission monitoring data, and thus affects the accuracy of the building equipment carbon emission assessment coefficient and the building equipment energy consumption assessment coefficient. The higher the sensor monitoring sensitivity coefficient, the more accurately it can capture the carbon emission changes of the building equipment, thereby providing a more accurate building equipment carbon emission assessment coefficient and a building equipment energy consumption assessment coefficient. The lower the sensor monitoring sensitivity coefficient, the more likely it is to cause distortion of the monitoring data, thereby affecting the accuracy of the building equipment carbon emission assessment coefficient and the building equipment energy consumption assessment coefficient. When the monitored sensor monitoring sensitivity coefficient is lower than the reference monitoring sensor sensitivity threshold, the monitoring sensitivity optimization is performed. When the building equipment carbon emission assessment coefficient is not lower than the reference carbon emission average value, the building equipment carbon emission assessment coefficient corresponding to the building equipment carbon emission assessment coefficient that is not lower than the reference carbon emission average value is marked as an unqualified building equipment carbon emission assessment coefficient, and a carbon emission optimization assessment is performed. When the building equipment energy consumption assessment coefficient is lower than the reference energy consumption maximum value, carbon emission optimization is performed. For example, in the process of optimizing and monitoring the carbon emissions of lighting fixtures, the higher the sensor monitoring sensitivity coefficient, the more accurately it can capture the on / off status, brightness changes, and energy consumption of the lighting fixtures, thereby providing accurate carbon emissions and energy consumption data. Carbon emissions and energy consumption data help to achieve intelligent control of lighting fixtures, further reduce energy consumption and carbon emissions, and achieve an improvement in the adequacy of carbon emissions optimization.

[0038] Furthermore, the sensor monitoring sensitivity coefficient is calculated by the temperature coefficient interference ratio (i.e., the limiting expression of the sensor monitoring sensitivity coefficient). ) and the signal attenuation interference ratio (i.e., the limiting expression of the sensor monitoring sensitivity coefficient ) is processed to obtain; the specific acquisition process of the temperature coefficient interference ratio is as follows: the initial temperature coefficient value is obtained by ratio calculation by multiplying the output current signal change with the product of the initial current output signal and the temperature change; the temperature coefficient interference ratio is obtained by ratio calculation by the initial temperature coefficient value and the preset temperature coefficient average value obtained from the database; the temperature coefficient interference ratio is used to describe the temperature coefficient interference of the preset monitoring sensor in the preset monitoring area; the specific acquisition process of the signal attenuation interference ratio is as follows: the initial signal attenuation value is obtained by calculation through the output signal frequency, the transmission conductivity and the speed of light obtained from the database; the signal attenuation interference ratio is obtained by ratio calculation by the initial signal attenuation value and the preset signal attenuation average value obtained from the database; the signal attenuation interference ratio is used to describe the interference of the current signal attenuation of the preset monitoring sensor in the preset monitoring area.

[0039] Among them, the limiting expression of the sensor monitoring sensitivity coefficient is as follows:

[0040]

[0041] In the formula, represents the sensor monitoring sensitivity coefficient of the preset monitoring sensor in the x-th preset time period, x=1,2,...,k, x represents the number of the preset time period, k represents the total number of preset time periods, Indicates the temperature coefficient interference ratio of the preset monitoring sensor in the xth preset time period, It represents the signal attenuation interference ratio of the preset monitoring sensor in the xth preset time period, Indicates the output current signal change of the preset monitoring sensor in the xth preset time period, Indicates the initial current output signal of the preset monitoring sensor in the xth preset time period, ΔT x1 Indicates the temperature change of the preset monitoring sensor in the xth preset time period, Indicates the output signal frequency of the monitoring sensor is preset in the xth preset time period, Indicates the transmission conductivity of the preset monitoring sensor in the xth preset time period, TC 0 Indicates the preset temperature coefficient average value, SJ 0 represents the preset signal attenuation average value, c represents the speed of light, and e represents a natural constant.

[0042] In this embodiment, the aforementioned database is a database for storing various types of setting data established before the design of a carbon emission optimization method provided in an embodiment of the present application. The database includes but is not limited to conductivity, signal frequency, temperature coefficient, etc., and the various numerical values ​​therein are directly set by technical personnel. For example, the preset temperature coefficient average value is represented by the average value of the temperature coefficient corresponding to the preset monitoring sensor in the historical time period in the database, and the preset signal attenuation average value is represented by the average value of the attenuation of the output current signal of the monitoring sensor in the historical time period in the database.

[0043] It should be understood that the algorithm of this embodiment combines the monitoring-related data analysis to obtain the sensor monitoring sensitivity coefficient. The monitoring-related data in the algorithm of this embodiment does not exist independently, but has mutual correlation. The greater the temperature change and the larger the initial current output signal, it does not mean that the sensor monitoring sensitivity coefficient will definitely increase. The influence of the output current signal change, the output signal frequency and the transmission conductivity should also be considered comprehensively. The higher the output signal frequency, the faster the sensor can respond to environmental changes, making the output signal more accurate. The higher the transmission conductivity means that the current transmission is more efficient, but it may also cause the signal received by the sensor to weaken. The increase in temperature may cause the chemical reaction rate to increase, thereby affecting the output current signal change. When the initial current output signal increases, the sensor may be more likely to detect small current changes, thereby improving sensitivity, resulting in an increase in the sensor monitoring sensitivity coefficient. The parameters of the algorithm of this embodiment need to consider the impact on the results together.

[0044] Specifically, assuming that the temperature coefficient interference ratio The range is 0.1-1, signal attenuation interference ratio The range is 0.1-0.6, as shown in Table 1, which is a statistical table of changes in the sensor monitoring sensitivity coefficient provided in the embodiment of the present application:

[0045] Table 1 Statistics of changes in sensor monitoring sensitivity coefficient

[0046]

[0047] It can be seen from the above table that as the temperature coefficient interference ratio and the signal attenuation interference ratio gradually increase, the sensor monitoring sensitivity coefficient gradually decreases, which means that the monitoring sensitivity of the preset sensor in monitoring the carbon emissions of building equipment gradually decreases. For example, the decrease in the sensor monitoring sensitivity coefficient means that the accuracy of the sensor in monitoring the carbon emissions of lighting fixtures decreases, which realizes the quantitative evaluation of the monitoring sensitivity of the preset sensor in monitoring the carbon emissions of building equipment, and realizes the improvement of the accuracy of obtaining monitoring sensitivity related data, thereby realizing the improvement of the adequacy of carbon emission optimization.

[0048] Furthermore, the specific process of judging whether to perform monitoring sensitivity optimization based on the sensor monitoring sensitivity coefficient is as follows: judging whether the sensor monitoring sensitivity coefficient is not lower than the reference monitoring sensor sensitivity threshold, if so, marking the sensor monitoring sensitivity coefficient that is not lower than the reference monitoring sensor sensitivity threshold as a qualified sensor monitoring sensitivity coefficient, otherwise performing monitoring sensitivity optimization; the specific steps of monitoring sensitivity optimization are: step one, performing data filtering, when the monitored sensor monitoring sensitivity coefficient is not lower than the reference monitoring sensor sensitivity threshold, stop performing step one, otherwise perform step two, data filtering means reducing the noise and interference of the sensor output under high temperature environment by using the Kalman filtering method; step two, sending a prompt to the preset personnel to amplify the output signal, when the monitored sensor monitoring sensitivity coefficient is not lower than the reference monitoring sensor sensitivity threshold, stop performing step two, otherwise send a monitoring abnormality prompt to the preset personnel, output signal amplification means reducing the distortion of the output signal by using a negative feedback circuit.

[0049] In this embodiment, the sensitivity threshold of the monitoring sensor is represented by the average value of the sensor monitoring sensitivity coefficient corresponding to the preset monitoring sensor in the historical time period in the database. In a high temperature environment, the preset monitoring sensor may be affected by various noises and interferences, resulting in inaccurate output data. The output data can be corrected and updated in real time through Kalman filtering, which can effectively reduce the noise and interference of the sensor output in a high temperature environment and improve the accuracy and reliability of the monitoring sensitivity related data. The negative feedback circuit reduces the distortion and fluctuation of the output signal by feeding back part of the output signal to the input end. The negative feedback circuit can reduce the fluctuation of the output signal, make the output signal more stable, and achieve the improvement of the adequacy of carbon emission optimization.

[0050] Furthermore, the building equipment carbon emission assessment coefficient is calculated by the operating time compliance ratio (i.e., the constraint expression of the building equipment carbon emission assessment coefficient). ), the frequency of use compliance ratio (i.e. the limit expression of the building equipment carbon emission assessment coefficient ) and the qualified sensor monitoring sensitivity coefficient are processed; the operating time compliance ratio is used to describe the compliance of the operating time of the building equipment in the preset monitoring area; the operating time compliance ratio is expressed by the result of the ratio operation between the average operating time of the building equipment and the preset operating time maximum value obtained from the database; the qualified sensor monitoring sensitivity coefficient is expressed as not less than the reference monitoring sensor sensitivity threshold obtained from the database; the usage frequency compliance ratio is used to describe the compliance of the usage frequency of the building equipment in the preset monitoring area; the usage frequency compliance ratio is expressed by the result of the ratio operation between the average usage frequency of the building equipment and the preset usage frequency maximum value obtained from the database.

[0051] Among them, the carbon emission assessment coefficient of building equipment is obtained by the following method:

[0052]

[0053] In the formula, represents the building equipment carbon emission assessment coefficient of the building equipment in the x-th preset time period, x=1,2,...,k, x represents the number of the preset time period, k represents the total number of preset time periods, It indicates the operation time of the building equipment in the x-th preset time period. Indicates the usage frequency of building equipment in the xth preset time period, YT x It represents the average operation time of the building equipment in the x-th preset time period, YP x represents the average usage frequency of construction equipment in the x-th preset time period, Indicates the qualified sensor monitoring sensitivity coefficient corresponding to the building equipment in the xth preset time period, YT 0 Indicates the maximum preset running time, YP 0 It indicates the maximum preset frequency of use, and e indicates a natural constant.

[0054] It should be added that the specific acquisition process of judging whether to conduct carbon emission optimization assessment based on the building equipment carbon emission assessment coefficient is as follows: judge whether the building equipment carbon emission assessment coefficient is not lower than the reference carbon emission average value: if so, the building equipment carbon emission assessment coefficient corresponding to the building equipment carbon emission assessment coefficient that is not lower than the reference carbon emission average value obtained from the database is marked as an unqualified building equipment carbon emission assessment coefficient, and a carbon emission optimization assessment is conducted. The unqualified building equipment carbon emission assessment coefficient indicates a building equipment carbon emission assessment coefficient that is not lower than the reference carbon emission average value; if not, it indicates that the carbon emissions are qualified and no carbon emission optimization assessment is conducted (carbon emission optimization assessment refers to obtaining the building equipment energy consumption assessment coefficient).

[0055] In this embodiment, the preset maximum operating time is represented by the maximum operating time of the construction equipment in the historical time period in the database, the preset maximum usage frequency is represented by the maximum usage frequency of the construction equipment in the historical time period in the database, and the reference carbon emission average value is represented by the average value of the carbon emission assessment coefficient of the construction equipment in the historical time period in the database.

[0056] It should be understood that the algorithm of this embodiment combines the building carbon emission monitoring related data and the sensor monitoring sensitivity coefficient analysis to obtain the building equipment carbon emission assessment coefficient. In the algorithm of this embodiment, the building carbon emission monitoring related data and the sensor monitoring sensitivity coefficient are not independent, but have mutual correlation. The longer the average operation time of the building equipment does not necessarily mean that the building equipment carbon emission assessment coefficient will increase. The comprehensive influence of the average use frequency of the building equipment and the qualified sensor monitoring sensitivity coefficient should also be considered comprehensively. The higher the qualified sensor monitoring sensitivity coefficient, the more accurately it can capture the equipment operation status and energy consumption changes, thereby providing more accurate carbon emission data. The longer the operation time but the lower the frequency of use of the building equipment, the carbon emissions may increase due to equipment aging, wear or inefficient operation, thereby increasing the building equipment carbon emission assessment coefficient. The building equipment with higher frequency of use but shorter operation time, if the equipment energy efficiency is higher, the carbon emissions may be relatively lower, thereby reducing the building equipment carbon emission assessment coefficient. The parameters of the algorithm of this embodiment need to consider the impact on the results together.

[0057] Specifically, assuming that the average operating time of construction equipment is YT x The range is 6-12 (hours), and the maximum preset running time is YT 0 Fixed to 12 (hours), such as Figure 2 As shown, it is a statistical diagram of the change of the average operation time of the construction equipment provided in the embodiment of the present application - the operation time compliance ratio, which is composed of Figure 2 It can be seen that as the average operating time of building equipment gradually increases, the carbon emission assessment coefficient of building equipment gradually increases, which means that the carbon emissions in the process of building equipment carbon emission gradually increase. For example, when the operating time of lighting fixtures increases, the electric energy consumed will also increase accordingly, and the carbon emission assessment coefficient of building equipment will also gradually increase. The carbon emission situation in the process of building equipment carbon emission is quantitatively assessed, thereby achieving the improvement of carbon emission optimization adequacy.

[0058] Furthermore, the specific process of obtaining the building equipment energy consumption assessment coefficient according to the obtained unqualified building equipment carbon emission assessment coefficient and the obtained building equipment average power is as follows: the initial equipment energy consumption value is obtained by multiplying the average operation time of the building equipment corresponding to the unqualified building equipment carbon emission assessment coefficient and the average power of the building equipment; the equipment energy consumption compliance ratio (i.e., the maximum value of the building equipment energy consumption in the restriction expression of the building equipment energy consumption assessment coefficient) is obtained by performing a ratio operation between the initial equipment energy consumption value and the preset maximum value of the building equipment energy consumption obtained from the database. ); the building equipment energy consumption assessment coefficient is obtained by combining the equipment energy consumption compliance ratio and the unqualified building equipment carbon emission assessment coefficient; the equipment energy consumption compliance ratio is used to describe the energy consumption compliance of building equipment in the preset monitoring area.

[0059] Among them, the building equipment energy consumption assessment coefficient is obtained by the following method:

[0060]

[0061] In the formula, represents the building equipment energy consumption assessment coefficient corresponding to the unqualified building equipment carbon emission assessment coefficient in the zth unqualified preset time period, z=1,2,...d, z represents the number of the unqualified preset time period, d represents the total number of unqualified preset time periods, z is less than or equal to x, and the unqualified preset time period represents the preset time period corresponding to the unqualified building equipment carbon emission assessment coefficient, It indicates the equipment energy consumption compliance ratio corresponding to the carbon emission assessment coefficient of the unqualified building equipment in the zth unqualified preset time period, Denotes the unqualified building equipment carbon emission assessment coefficient of the building equipment in the zth unqualified preset time period, YT z ′ represents the average operation time of the building equipment corresponding to the carbon emission assessment coefficient of the unqualified building equipment in the zth unqualified preset time period, represents the average power of building equipment corresponding to the carbon emission assessment coefficient of unqualified building equipment in the zth unqualified preset time period, NH 0 It represents the preset maximum energy consumption of building equipment, and e represents the natural constant.

[0062] In this embodiment, the preset maximum value of building equipment energy consumption is represented by the maximum value of building equipment energy consumption of building equipment in a historical time period in the database.

[0063] It should be understood that the algorithm of this embodiment combines the carbon emission assessment coefficient of building equipment and the average power analysis of building equipment to obtain the energy consumption assessment coefficient of building equipment. In the algorithm of this embodiment, the carbon emission assessment coefficient of building equipment and the average power of building equipment are not independent, but have mutual correlation. The longer the average operation time of building equipment, it does not mean that the energy consumption assessment coefficient of building equipment is larger. The influence of the carbon emission assessment coefficient of building equipment should also be considered comprehensively. The higher the average power of building equipment, the more energy the building equipment will consume in the same operation time, which will lead to an increase in the energy consumption assessment coefficient of building equipment. However, in the case of higher energy efficiency of building equipment, the longer the operation time of building equipment, the carbon emission assessment coefficient of building equipment may decrease, which may lead to a decrease in the energy consumption assessment coefficient of building equipment. The parameters of the algorithm of this embodiment need to consider the impact on the results together. For example, if the average power of lighting fixtures is higher, but the energy efficiency is lower, then the lighting fixtures will consume more electricity in the same operation time. This will lead to an increase in the energy consumption assessment coefficient of building equipment, and the carbon emissions will also increase accordingly, so that the carbon emission assessment coefficient of building equipment will also increase. The energy consumption in the process of carbon emission of building equipment is quantitatively evaluated, and the adequacy of carbon emission optimization is improved.

[0064] Furthermore, the specific process of judging whether to perform carbon emission optimization based on the energy consumption assessment coefficient of building equipment is as follows: judging whether the energy consumption assessment coefficient of building equipment is not lower than the maximum reference energy consumption obtained from the database, if not, it indicates that the energy consumption of building equipment is qualified and carbon emission optimization is not performed; otherwise, it indicates that the energy consumption of building equipment is high and carbon emission optimization is performed. The steps of carbon emission optimization are: the first step is to perform gain adjustment. When the monitored energy consumption assessment coefficient of building equipment is lower than the maximum reference energy consumption, the first step is stopped, otherwise the second step is performed. Gain adjustment means that temperature compensation is performed through the gain adjustment PID control algorithm to reduce the energy consumption of building equipment; the second step is to send a prompt to the preset personnel to change the position of the building equipment air outlet. When the monitored energy consumption assessment coefficient of building equipment is lower than the maximum reference energy consumption, the second step is stopped, otherwise a carbon emission abnormality prompt is sent to the preset personnel, and the position of the building equipment air outlet is changed to reduce the energy consumption of mechanical ventilation.

[0065] In this embodiment, the reference maximum energy consumption is represented by the average value of the building equipment energy consumption assessment coefficient of the historical time period in the database. The PID (Proportion Integration Differentiation) control algorithm achieves precise control of the system output by adjusting the three parameters of proportional gain (P), integral time constant (I) and differential time constant (D). The proportional term produces an output value proportional to the current error value, the integral term is proportional to the size of the error and the duration of the error, and the differential term provides a prediction of future errors based on the current rate of change. By changing the position of the air outlet, the airflow distribution in the building can be optimized to make the air flow more evenly, which helps to reduce energy consumption and improve the adequacy of carbon emission optimization.

[0066] like Figure 3As shown, it is a structural schematic diagram of a carbon emission optimization system provided in an embodiment of the present application. A carbon emission optimization system provided in an embodiment of the present application includes a sensor sensitivity evaluation module, a building equipment carbon emission evaluation module and a building equipment energy consumption evaluation module: wherein the sensor sensitivity evaluation module is used to perform sensor sensitivity evaluation through the acquired monitoring-related data to obtain the sensor monitoring sensitivity coefficient, and judge whether to perform monitoring sensitivity optimization based on the sensor monitoring sensitivity coefficient. The monitoring sensitivity optimization is used to improve the sensitivity of the preset sensor in the process of monitoring the carbon emission of the building equipment. The sensor monitoring sensitivity coefficient is used to evaluate the monitoring sensitivity of the preset sensor in the process of monitoring the carbon emission of the building equipment; the building equipment carbon emission evaluation module is used The carbon emission assessment coefficient of building equipment is obtained according to the obtained qualified sensor monitoring sensitivity coefficient and the obtained building carbon emission monitoring related data. The carbon emission assessment coefficient of building equipment is used to evaluate the change of carbon emissions in the carbon emission process of building equipment; the building equipment energy consumption assessment module is used to determine whether to perform carbon emission optimization assessment based on the building equipment carbon emission assessment coefficient. The building equipment energy consumption assessment coefficient is obtained according to the obtained unqualified building equipment carbon emission assessment coefficient and the obtained average power of building equipment. It is determined whether to perform carbon emission optimization based on the building equipment energy consumption assessment coefficient. Carbon emission optimization is used to reduce energy consumption in the carbon emission process of building equipment. The building equipment energy consumption assessment coefficient is used to evaluate the energy consumption of building equipment in the carbon emission process.

[0067] like Figure 4 As shown, it is the overall flow chart provided in the embodiment of the present application. The sensor sensitivity evaluation module, the building equipment carbon emission evaluation module and the building equipment energy consumption evaluation module together constitute a system for monitoring, evaluating and optimizing the carbon emissions and energy consumption of building equipment. By performing monitoring sensitivity optimization and carbon emission optimization, the energy efficiency of building equipment is improved. For example, by real-time monitoring of the status of lighting fixtures and collecting energy consumption and carbon emission data, the system can perform monitoring sensitivity optimization and carbon emission optimization, thereby optimizing the energy consumption and carbon emission performance of the lamps and achieving an improvement in the adequacy of carbon emission optimization.

[0068] To summarize, the embodiment of the present application performs sensor sensitivity evaluation by monitoring relevant data to obtain the sensor monitoring sensitivity coefficient and determines whether to perform monitoring sensitivity optimization, then determines whether to perform carbon emission optimization evaluation based on the obtained building equipment carbon emission evaluation coefficient, and finally determines whether to perform carbon emission optimization based on the obtained building equipment energy consumption evaluation coefficient, thereby achieving an improvement in the reliability of carbon emission optimization, and then achieving an improvement in the adequacy of carbon emission optimization, effectively solving the problem of low accuracy of optimization data in the carbon emission optimization process in the prior art.

[0069] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0070] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0071] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0072] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0073] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0074] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A carbon emission optimization method, characterized in that: The following steps are involved: S1, evaluating the sensitivity of the sensor by acquiring the monitoring-related data to obtain the sensor monitoring sensitivity coefficient, and judging whether to perform monitoring sensitivity optimization based on the sensor monitoring sensitivity coefficient, wherein the sensor monitoring sensitivity coefficient is used to evaluate the monitoring sensitivity of the preset sensor in the process of monitoring the carbon emission of the building equipment; S2, obtaining a building equipment carbon emission assessment coefficient based on the acquired qualified sensor monitoring sensitivity coefficient and the acquired building carbon emission monitoring related data, wherein the building equipment carbon emission assessment coefficient is used to assess the change of carbon emission amount during the building equipment carbon emission process; S3, based on the carbon emission assessment coefficient of the building equipment, determine whether to conduct a carbon emission optimization assessment, obtain the building equipment energy consumption assessment coefficient according to the obtained carbon emission assessment coefficient of the unqualified building equipment and the obtained average power of the building equipment, and determine whether to conduct carbon emission optimization based on the building equipment energy consumption assessment coefficient. The building equipment energy consumption assessment coefficient is used to evaluate the energy consumption of the building equipment during the carbon emission process.

2. A carbon emission optimization method as claimed in claim 1, characterized in that: The monitoring related data include output current signal change, initial current output signal, temperature change, output signal frequency and transmission conductivity; The output current signal variation represents the average variation of the output current of the preset monitoring sensor in the preset monitoring area; The temperature change represents the average change of the ambient temperature in the preset monitoring area; The output signal frequency represents the average frequency corresponding to the output current of the building equipment in the preset monitoring area; The building carbon emission monitoring related data include the average operation time of building equipment and the average usage frequency of building equipment.

3. A carbon emission optimization method as claimed in claim 2, characterized in that: The sensor monitoring sensitivity coefficient is obtained by processing the temperature coefficient interference ratio and the signal attenuation interference ratio; The specific acquisition process of the temperature coefficient interference ratio is as follows: The initial temperature coefficient value is obtained by performing a ratio operation on the output current signal change amount and the product of the initial current output signal and the temperature change amount; The temperature coefficient interference ratio is obtained by performing a ratio operation between the initial temperature coefficient value and the preset temperature coefficient average value obtained from the database; The temperature coefficient interference ratio is used to describe the temperature coefficient interference of a preset monitoring sensor in a preset monitoring area; The specific process of obtaining the signal attenuation-to-interference ratio is as follows: The initial signal attenuation value is obtained by calculating the output signal frequency, the transmission conductivity and the light speed obtained from the database; The signal attenuation-to-interference ratio is obtained by performing a ratio operation between the initial signal attenuation value and the preset signal attenuation average value obtained from the database; The signal attenuation interference ratio is used to describe the interference situation of the current signal attenuation of the preset monitoring sensor in the preset monitoring area.

4. A carbon emission optimization method as claimed in claim 3, characterized in that: The specific process of judging whether to optimize the monitoring sensitivity based on the sensor monitoring sensitivity coefficient is as follows: Determine whether the sensor monitoring sensitivity coefficient is not lower than the reference monitoring sensor sensitivity threshold, if so, mark the sensor monitoring sensitivity coefficient that is not lower than the reference monitoring sensor sensitivity threshold as a qualified sensor monitoring sensitivity coefficient, otherwise perform monitoring sensitivity optimization; The specific steps of optimizing the monitoring sensitivity are: Step 1: perform data filtering. When the monitoring sensitivity coefficient of the monitored sensor is not lower than the sensitivity threshold of the reference monitoring sensor, stop performing step 1. Otherwise, perform step 2. Step 2, sending a prompt to the preset personnel to amplify the output signal. When the monitoring sensitivity coefficient of the monitored sensor is not lower than the sensitivity threshold of the reference monitoring sensor, stop step 2. Otherwise, send a monitoring abnormality prompt to the preset personnel.

5. A carbon emission optimization method as claimed in claim 2, characterized in that: The building equipment carbon emission assessment coefficient is obtained by processing the operation time compliance ratio, the use frequency compliance ratio and the qualified sensor monitoring sensitivity coefficient; The running time compliance ratio is represented by the result of calculating the ratio between the average running time of the construction equipment and the maximum value of the preset running time obtained from the database; The usage frequency compliance ratio is represented by a result of a ratio calculation between an average usage frequency of the construction equipment and a preset maximum usage frequency value obtained from a database.

6. A carbon emission optimization method as claimed in claim 1, characterized in that: The specific acquisition process of judging whether to perform carbon emission optimization assessment based on the building equipment carbon emission assessment coefficient is as follows: Determine whether the carbon emission assessment coefficient of building equipment is not lower than the reference carbon emission average value: If so, the building equipment carbon emission assessment coefficient corresponding to the building equipment carbon emission assessment coefficient that is not less than the reference carbon emission average value obtained from the database is marked as an unqualified building equipment carbon emission assessment coefficient, and a carbon emission optimization assessment is performed; If not, no carbon emission optimization assessment will be conducted.

7. A carbon emission optimization method as claimed in claim 1, characterized in that: The specific process of obtaining the building equipment energy consumption assessment coefficient based on the obtained unqualified building equipment carbon emission assessment coefficient and the obtained building equipment average power is as follows: The initial equipment energy consumption value is obtained by multiplying the average operation time of the building equipment corresponding to the carbon emission assessment coefficient of the unqualified building equipment and the average power of the building equipment; The equipment energy consumption compliance ratio is obtained by performing a ratio calculation between the initial equipment energy consumption value and the preset maximum building equipment energy consumption value obtained from the database; The building equipment energy consumption assessment coefficient is calculated by combining the equipment energy consumption compliance ratio and the unqualified building equipment carbon emission assessment coefficient; The equipment energy consumption compliance ratio is used to describe the energy consumption compliance of building equipment in a preset monitoring area.

8. A carbon emission optimization method as claimed in claim 7, characterized in that: The specific process of judging whether to optimize carbon emissions based on the building equipment energy consumption assessment coefficient is as follows: Determine whether the energy consumption assessment coefficient of building equipment is not lower than the maximum reference energy consumption value obtained from the database. If not, it means that the energy consumption of building equipment is qualified and carbon emission optimization is not performed; Otherwise, carbon emission optimization is performed, and the steps of carbon emission optimization are: The first step is to perform gain adjustment. When the energy consumption evaluation coefficient of the monitored building equipment is lower than the maximum reference energy consumption, the first step is stopped, otherwise the second step is performed; The second step is to send a reminder to the preset personnel to change the location of the building equipment air outlet. When the monitored building equipment energy consumption assessment coefficient is lower than the reference energy consumption maximum value, the second step is stopped. Otherwise, a carbon emission abnormality reminder is sent to the preset personnel.

9. A carbon emission optimization method as claimed in claim 3, characterized in that: The limiting expression of the sensor monitoring sensitivity coefficient is as follows: In the formula, represents the sensor monitoring sensitivity coefficient of the preset monitoring sensor in the x-th preset time period, x=1,2,...,k, x represents the number of the preset time period, k represents the total number of preset time periods, Indicates the temperature coefficient interference ratio of the preset monitoring sensor in the xth preset time period, It represents the signal attenuation-interference ratio of the preset monitoring sensor in the x-th preset time period, and e represents a natural constant.

10. A carbon emission optimization system, characterized in that: Including sensor sensitivity assessment module, building equipment carbon emission assessment module and building equipment energy consumption assessment module: The sensor sensitivity evaluation module is used to evaluate the sensor sensitivity through the acquired monitoring related data to obtain the sensor monitoring sensitivity coefficient, and determine whether to optimize the monitoring sensitivity based on the sensor monitoring sensitivity coefficient. The sensor monitoring sensitivity coefficient is used to evaluate the monitoring sensitivity of the preset sensor in the process of monitoring the carbon emissions of building equipment; The building equipment carbon emission assessment module is used to obtain a building equipment carbon emission assessment coefficient based on the acquired qualified sensor monitoring sensitivity coefficient and the acquired building carbon emission monitoring related data, and the building equipment carbon emission assessment coefficient is used to assess the change of carbon emissions during the building equipment carbon emission process; The building equipment energy consumption assessment module is used to determine whether to perform a carbon emission optimization assessment based on the building equipment carbon emission assessment coefficient. The building equipment energy consumption assessment coefficient is obtained according to the obtained unqualified building equipment carbon emission assessment coefficient and the obtained average power of the building equipment. Based on the building equipment energy consumption assessment coefficient, it is determined whether to perform carbon emission optimization. The building equipment energy consumption assessment coefficient is used to evaluate the energy consumption of the building equipment during the carbon emission process.

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