Method for evaluating product carbon footprint in use stage of intelligent electric meter

Abstract

The invention relates to a product carbon footprint evaluation method in the use stage of an intelligent electric meter. Carrying out an aging test, and obtaining the output loss of each measurement point in the aging test process, the output failure moment and the measurement moment corresponding to each loss data; averaging the measured loss data of all the test samples, and fitting by applying a least square method to obtain a loss-use time curve y = f1 (t) of the product; after an intelligent electric meter is put into use, a power grid carbon emission factor curve p = f2 (t) is obtained according to time-sharing and zoning power grid carbon emission factors issued by a regional government or a power grid enterprise; and evaluating the product carbon footprint in the use stage of the intelligent electric meter according to the obtained curve. According to the method, the product carbon footprint change rule of the intelligent electric meter in the use stage can be further summarized, the intelligent electric meter replacement strategy of basic product carbon footprint data can be conveniently formulated under the carbon emission double-control target step-by-step promotion requirement, and the power grid carbon emission is further reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of electric power calculation, and in particular to a method for evaluating the carbon footprint of a smart meter product during its use phase. Background Art

[0002] Smart meters are one of the basic equipment for data collection in smart grids. They undertake the tasks of collecting, measuring and transmitting electric energy data, and are the basis for accurate accounting of carbon emissions in the production, consumption and transmission of electric energy. In the context of the country's promotion of the construction of a standard measurement system for carbon peak and carbon neutrality, it is necessary to accurately calculate the carbon footprint of smart meters throughout their life cycle. In the life cycle of smart meters, the sources of carbon emission accounting data in the stages of raw material acquisition, product manufacturing, and product transportation are relatively broad, and the data is relatively sufficient, so they can be accurately calculated; while for the use stage, the traditional emission factor method is usually used, using the maximum loss of the smart meter and multiplying it by the carbon emission factor of the power grid to obtain it. This method is relatively conservative and may cause a large deviation in the calculation results of the carbon footprint of the product, which will have a negative impact on the accurate calculation of the carbon footprint of smart meter products and the comparison of different types of products. However, since smart meters consume less energy during the use stage and have a long operating time, generally not less than 10 years, the use of higher-precision metering devices to carry out actual data monitoring requires a lot of manpower and material resources, which is less economical, and even limited by on-site conditions such as live electricity and small installation space during the use stage, monitoring is impossible. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and propose a method for evaluating the carbon footprint of smart meters in the use stage. The method can further summarize the changing rules of the carbon footprint of smart meters in the use stage. Under the requirement of gradually advancing the dual control targets of carbon emissions, it is convenient to formulate a smart meter replacement strategy based on product carbon footprint data, so as to further reduce the carbon emissions of the power grid.

[0004] The present invention solves the technical problem by adopting the following technical solutions:

[0005] A method for evaluating the carbon footprint of a smart meter product during its use phase comprises the following steps:

[0006] Step 1: Select samples;

[0007] Step 2: Perform an aging test on the selected samples and determine whether the sample error after aging is greater than the 1.5 limit error. If so, the experiment ends and proceeds to step 4; otherwise, proceeds to step 3.

[0008] Step 3: Calculate the acceleration factor of the sample through the aging test data, obtain the simulated actual use time, and proceed to step 5;

[0009] Step 4, obtaining the loss of each measurement point during the aging test, the output failure time and the measurement time corresponding to each loss data;

[0010] Step 5: average the loss data of all test samples and fit them using the least square method to obtain the product loss-use time curve y=f1(t);

[0011] Step 6: After the smart meter is put into use, the grid carbon emission factor curve p = f2(t) is obtained according to the time-sharing and zone-based grid carbon emission factors issued by the local government or grid company;

[0012] Step 7: Evaluate the carbon footprint of the smart meter product during its use phase based on the curves in steps 5 and 6.

[0013] Moreover, the specific implementation method of step 1 is: select multiple batches of products, each batch has no less than 77 samples, and the test interval between each batch is no less than 15 days.

[0014] Moreover, the specific implementation method of step 2 is: the aging test temperature is the upper limit of the product operating temperature range, the aging test humidity is 25% RH, the aging test voltage is 1.1 times the rated voltage, and the aging test current is the maximum working current; at the same time, during the aging test, the smart meter loss data is read and recorded every 8 hours, the test is suspended every 48 hours, and the smart meter error is measured after the test sample returns to normal temperature. When the error exceeds 50% of the limit value specified in the table below, the smart meter is determined to have aged and failed.

[0015] Moreover, the specific implementation method of step 3 is:

[0016] t u =t s *AF

[0017]

[0018] Among them, t u To simulate the actual usage time; t s is the loss measurement time during the test; AF is the acceleration factor; RH is the s Relative humidity during the test; RH u is the relative humidity value under normal use conditions; n is the humidity acceleration constant; Ea is the activation energy; K is the Boltzmann constant; T u is the ambient temperature for normal use, T s is the ambient temperature during the test; β is the voltage acceleration constant; V s is the voltage during the test; V u This is the normal operating voltage.

[0019] Moreover, the specific implementation method of step 7 is:

[0020]

[0021] Among them, C is the carbon footprint assessment result of the smart meter product during the use phase, and p is the carbon emission factor curve of the power grid.

[0022] The advantages and positive effects of the present invention are:

[0023] The present invention selects samples; performs an aging test on the selected samples, and determines whether the sample error after aging is greater than 1.5 limit errors, and obtains the loss of each measurement point output during the aging test, as well as the output failure time and the measurement time corresponding to each loss data; averages the loss data measured by all test samples, and applies the least squares method to fit, so as to obtain the product loss-use time curve y=f1(t); after the smart meter is put into use, according to the time-sharing and zoned power grid carbon emission factors issued by the local government or power grid company, a power grid carbon emission factor curve p=f2(t) is obtained; and the carbon footprint of the smart meter product during the use stage is evaluated according to the obtained curve. The present invention proposes for the first time a method for evaluating the carbon footprint of smart meters in the use stage based on aging test data and carbon emission factor data of the time-sharing and zoned power grid in the region. Compared with the traditional emission factor method, the method of using the maximum loss of the smart meter multiplied by the carbon emission factor of the power grid to calculate the carbon footprint of the product in the use stage is closer to the actual level; at the same time, it overcomes the inconvenience of installing higher-precision metering devices and conducting long-term monitoring in a small energized space on site, avoids the influence of other factors on site, and is conducive to improving the efficiency of product carbon footprint calculation; it can further summarize the change law of the carbon footprint of smart meters in the use stage, and under the requirement of gradually advancing the dual control targets of carbon emissions, it is convenient to formulate a smart meter replacement strategy based on product carbon footprint data, so as to further reduce carbon emissions from the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0025] The present invention is further described in detail below with reference to the accompanying drawings.

[0026] A method for evaluating the carbon footprint of smart meter products during their use phase, such as Figure 1 As shown, the following steps are included:

[0027] Step 1: Select samples.

[0028] The specific implementation method of step 1 is: select three batches of products, each batch has no less than 77 samples, and the test interval between each batch is no less than 15 days.

[0029] Step 2: Perform an aging test on the selected samples and determine whether the sample error after aging is greater than the 1.5 limit error. If so, the experiment ends and proceeds to step 4; otherwise, proceed to step 3.

[0030] The specific implementation method of step 2 is as follows: the aging test temperature is the upper limit of the product operating temperature range, the aging test humidity is 25% RH, the aging test voltage is 1.1 times the rated voltage, and the aging test current is the maximum working current; at the same time, during the aging test, the smart meter loss data is read and recorded every 8 hours, the test is suspended every 48 hours, and the smart meter error is measured after the test sample returns to normal temperature. Figure 1 As shown in the table below, when the error exceeds 50% of the limit value specified in the table below, the smart meter is determined to be aged and failed.

[0031] Table 1 Smart meter accuracy levels and their percentage error change limits

[0032]

[0033] Step 3: Calculate the acceleration factor of the sample through the aging test data, obtain the simulated actual use time, and proceed to step 5.

[0034] The specific implementation method of step 3 is:

[0035] t u =t s *AF Formula 1

[0036]

[0037] Among them, t u To simulate the actual usage time; t s is the loss measurement time during the test; AF is the acceleration factor; RH is the s Relative humidity during the test; RH u is the relative humidity value under normal use conditions; n is the humidity acceleration rate constant, between 2 and 3; Ea is the activation energy, between 0.3eV and 1.2eV; K is the Boltzmann constant; T u is the ambient temperature for normal use, T s is the ambient temperature during the test; β is the voltage acceleration constant, between 0.5 and 1.0; V s is the voltage during the test; V u This is the normal operating voltage.

[0038] Step 4: Obtain the output loss of each measurement point during the aging test, the output failure time, and the measurement time corresponding to each loss data.

[0039] Step 5: average the loss data of all test samples and fit them using the least squares method to obtain the product loss-usage time curve y=f1(t).

[0040] Step 6: After the smart meter is put into use, the grid carbon emission factor curve p=f2(t) is obtained according to the time-sharing and zoned grid carbon emission factors issued by the local government or grid company.

[0041] Step 7: Evaluate the carbon footprint of the smart meter product during its use phase based on the curves in steps 5 and 6.

[0042] The specific implementation method of step 7 is:

[0043]

[0044] Among them, C is the carbon footprint assessment result of the smart meter product during the use phase, and p is the carbon emission factor curve of the power grid.

[0045] It should be emphasized that the embodiments described in the present invention are illustrative rather than restrictive. Therefore, the present invention includes but is not limited to the embodiments described in the specific implementation manner. Any other implementation manners derived by those skilled in the art based on the technical solution of the present invention also fall within the scope of protection of the present invention.

Claims

1. A method for evaluating the carbon footprint of smart meter products during their use phase, characterized by: The following steps are involved: Step 1: Select samples; Step 2: Perform an aging test on the selected samples and determine whether the sample error after aging is greater than the 1.5 limit error. If so, the experiment ends and proceeds to step 4; otherwise, proceeds to step 3. Step 3: Calculate the acceleration factor of the sample through the aging test data, obtain the simulated actual use time, and proceed to step 5; Step 4, obtaining the loss of each measurement point during the aging test, the output failure time and the measurement time corresponding to each loss data; Step 5: average the loss data of all test samples and fit them using the least square method to obtain the product loss-use time curve y=f1(t); Step 6: After the smart meter is put into use, the grid carbon emission factor curve p = f2(t) is obtained according to the time-sharing and zone-based grid carbon emission factors issued by the local government or grid company; Step 7: Evaluate the carbon footprint of the smart meter product during its use phase based on the curves in steps 5 and 6.

2. The method for evaluating the carbon footprint of smart meter products during the use phase according to claim 1, characterized in that: The specific implementation method of step 1 is: select multiple batches of products, each batch has no less than 77 samples, and the test interval between each batch is no less than 15 days.

3. The method for evaluating the carbon footprint of smart meter products during the use phase according to claim 2, characterized in that: The specific implementation method of step 2 is as follows: the aging test temperature is the upper limit of the product operating temperature range, the aging test humidity is 25% RH, the aging test voltage is 1.1 times the rated voltage, and the aging test current is the maximum operating current; at the same time, during the aging test, the smart meter loss data is read and recorded every 8 hours, the test is suspended every 48 hours, and the smart meter error is measured after the test sample returns to normal temperature. When the error exceeds 50% of the limit value specified in the table below, the smart meter is determined to have aged and failed.

4. The method for evaluating the carbon footprint of smart meter products during the use phase according to claim 3, characterized in that: The specific implementation method of step 3 is: t u =t s *OF Among them, t u To simulate the actual usage time; t s is the loss measurement time during the test; AF is the acceleration factor; RH is the s Relative humidity during the test; RH u is the relative humidity value under normal use conditions; n is the humidity acceleration constant; Ea is the activation energy; K is the Boltzmann constant; T u is the ambient temperature for normal use, T s is the ambient temperature during the test; β is the voltage acceleration constant; V s is the voltage during the test; V u This is the normal operating voltage.

5. The method for evaluating the carbon footprint of smart meter products during the use phase according to claim 4, characterized in that: The specific implementation method of step 7 is: Among them, C is the carbon footprint assessment result of the smart meter product during the use phase, and p is the carbon emission factor curve of the power grid.

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