Method and system for automatically adjusting sampling precision of photovoltaic inverter

Abstract

The invention discloses a method and system for automatically adjusting the sampling precision of a photovoltaic inverter, and the method comprises the steps: building a first mapping table of temperature values and sampling coefficients, enabling different temperatures to correspond to different sampling coefficients, and correcting a sampling error caused by the temperature change. Technicians can create a first mapping table through experience or pre-collection of data and analysis of the regularity relationship between the temperature and the sampling error. According to the obtained real-time temperature data, namely the first temperature value T1, in the inverter, the corresponding first sampling coefficient K1 is automatically selected based on the mapping rule of the first mapping table, and automatic switching of the first sampling coefficient K1 at different temperatures is achieved. Through data reinspection and deviation multiple calculation, the first mapping table is automatically adjusted, the accuracy of data acquisition is improved, the sampling coefficient switching frequency can be reduced as much as possible, and the stability of a control system is protected.

Description

Technical Field

[0001] The invention belongs to the technical field of photovoltaic power generation, and in particular relates to the technical field of photovoltaic power generation design with an automatic precision adjustment function. Background Art

[0002] The global demand for renewable energy and the improvement of environmental awareness of reducing the use of fossil energy have driven the demand for green energy, among which solar power generation is an important development direction. Photovoltaic power generation systems convert the direct current generated by solar photovoltaic systems into alternating current through their internal photovoltaic inverters and connect them to the power grid, thereby promoting the transformation of energy structure and realizing the sustainable development of economic and social development through solar power generation.

[0003] However, due to the influence of some external factors, the parameters of some analog devices such as resistors, capacitors and op amps in the sampling circuit of the inverter will change, resulting in certain deviations in the instantaneous values ​​of voltage or current sampling, and errors in the sampling of the inverter's control chip DSP. The existence of this error is not conducive to the control of the photovoltaic inverter and thus affects the stability of the entire photovoltaic power generation system, nor is it conducive to improving the power generation efficiency of the photovoltaic inverter. In the prior art, adjustments are made by manually changing the sampling coefficient. However, this method often requires manual adjustments multiple times to find the correct sampling coefficient, which takes a long time and requires skilled personnel to operate, which is very inconvenient. If the setting is incorrect, it will lead to adverse situations such as machine tripping. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention proposes a method and system for automatically adjusting the sampling accuracy of a photovoltaic inverter, which automatically calibrates the sampling error, realizes precise control of the photovoltaic inverter, and improves the power generation efficiency of the photovoltaic power generation system.

[0005] In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical solutions:

[0006] A method for automatically adjusting sampling accuracy of a photovoltaic inverter, characterized by comprising the following steps:

[0007] S1. Mapping table 1 creation

[0008] The mapping table 1 includes a mapping relationship between a first temperature value T1 and a first sampling coefficient k1, wherein the first temperature value T1 is a real-time internal temperature value of the photovoltaic inverter;

[0009] S2. Data Acquisition

[0010] Collect the current first temperature value T1 and the current photovoltaic inverter initial sampling value X 初 ;

[0011] S3. Determination of effective value

[0012] Based on the mapping rule of the mapping table 1 and the first temperature value T1 collected, the first sampling coefficient K1 is determined, and the effective sampling value X is calculated. 有效 , X 有效 =X 初* K1.

[0013] In a photovoltaic power generation system, the inverter is one of the core components, and its control accuracy directly affects the power generation efficiency and stability of the entire system. However, due to the inherent errors of electronic components and the temperature drift caused by temperature changes, errors are inevitable in the sampling process of the inverter control chip DSP. In order to overcome this problem, the technical solution establishes the mapping table 1 of temperature value and sampling coefficient, and different temperatures correspond to different sampling coefficients, which are used to correct the sampling errors caused by temperature changes. Technicians can create the mapping table 1 through experience or by pre-collecting and analyzing the regular relationship between temperature and sampling error. According to the real-time temperature data inside the inverter, that is, the first temperature value T1, based on the mapping rules of the mapping table 1, the corresponding first sampling coefficient K1 is automatically selected to achieve automatic switching of the first sampling coefficient K1 at different temperatures.

[0014] After obtaining the first sampling coefficient K1, the initial sampling value X is obtained through the sampling module inside the inverter. 初 , based on the formula: X 有效 =X 初* K1, determine the effective sampling value X 有效 , so as to calibrate the sampling error of the inverter in real time to reduce the sampling error caused by temperature change. It can realize the precise control of photovoltaic inverter and improve the power generation efficiency of photovoltaic power generation system.

[0015] As a preferred embodiment of the present invention, the mapping table 1 further includes segmentation labels, different segmentation labels correspond to different temperature intervals, and the first sampling coefficients K1 corresponding to the same segmentation labels are the same.

[0016] In a photovoltaic power generation system, if the first sampling coefficient K1 is switched too frequently, it will cause instability in the control system and increase the operating burden of the system. By adding the segmentation label in the mapping table 1, the first sampling coefficient K1 corresponding to the same segmentation label is the same. The technician can directly divide the temperature into several intervals based on experience, and each interval corresponds to a segmentation label with the same first sampling coefficient K1. While ensuring that the sampling error is controlled within the allowable range, the switching frequency of the first sampling coefficient K1 is reduced as much as possible to ensure the stable operation of the system. In addition, the technician can also obtain a temperature-sampling coefficient curve by analyzing and fitting the data samples acquired in advance. Based on the temperature-sampling coefficient curve, the temperature can be divided into different temperature intervals, and each interval corresponds to a segmentation label with the same first sampling coefficient K1. Such a segmentation method can more accurately control the sample error within a preset range.

[0017] As a preferred embodiment of the present invention, the step of creating the mapping table 1 in S1 further includes the following steps:

[0018] Collect the actual sampled value X in the photovoltaic inverter under different first temperature values ​​T1 实际 and the initial sampling value X 初 , calculate and obtain the first sampling coefficient K1 of different first temperature values ​​T1, K1=X 实际 / X 初 , establish a mapping relationship between the first temperature value T1 and the first sampling coefficient K1.

[0019] The actual sampling value X of the photovoltaic inverter 实际 It can be directly measured by using a high-precision test instrument. However, the equipment cost and power consumption of the high-precision measuring instrument are high. If each photovoltaic inverter is equipped with a high-precision measuring instrument for real-time detection, the cost is uncontrollable. Therefore, in the early stage of establishing the mapping table 1, the actual sampling value X in the photovoltaic inverter under different first temperature values ​​T1 is measured. 实际 and the initial sampling value X 初 , and based on the formula: K1=X 实际 / X 初 The mapping relationship between the first temperature value T1 and the first sampling coefficient k1 is obtained. In the subsequent working process of the photovoltaic inverter, the real-time adjustment of the sampling progress can be completed by simply obtaining the first temperature value T1, without the need for each photovoltaic inverter to be equipped with a high-precision measuring instrument for real-time detection. The equipment cost is significantly reduced. For large-scale photovoltaic power generation systems, this can save a lot of initial investment and operation and maintenance costs.

[0020] As a preferred embodiment of the present invention, the photovoltaic inverter sampling accuracy automatic adjustment method further comprises S4, a data rechecking step:

[0021] Collect sampling data of metering chip X 采 , calculate the deviation multiple K 偏， K 偏 =X 采 / X 有效 ,

[0022] Set the deviation threshold range A, if the deviation multiple K 偏 does not fall within the deviation threshold range A, then the valid sampling value X 有效 = Sampling data of the metering chip X 采 , and based on the first sampling coefficient K1 and the deviation multiple K 偏 , calculate the second sampling coefficient k2, K2 = K1 × K 偏 , the first sampling coefficient K1 is replaced by the second sampling coefficient k2.

[0023] In some extreme climates, there are fewer experimental sample data, so the mapping relationship between the first temperature value T1 and the first sampling coefficient k1 may have a large error. Since the performance difference of the metering chip to temperature change is not as large as that of the inverter itself, the sampling data X of the metering chip inside the photovoltaic inverter is collected. 采 , calculate the deviation multiple K 偏， K 偏 =X 采 / X 有效 , recheck the data to determine whether there is a large error in the mapping relationship between the first temperature value T1 and the first sampling coefficient k1.

[0024] If the deviation multiple K 偏 If it falls within the set deviation threshold range A, it is judged that the mapping relationship between the first temperature value T1 and the first sampling coefficient k1 is still accurate, and the error is still within the controllable range. The first sampling coefficient K1 is determined based on the mapping rule of the mapping table 1 and the collected first temperature value T1, and the effective sampling value Xeffective is calculated, where Xeffective=Xinitial*K1.

[0025] If the deviation multiple K 偏 If the first temperature value T1 does not fall within the set deviation threshold range A, it is determined that under this working condition, there is a large error in the mapping relationship between the first temperature value T1 and the first sampling coefficient k1, and the effective sampling value X 有效 = Sampling data of the metering chip X 采 , and based on the first sampling coefficient K1 and the deviation multiple K 偏 , calculate the second sampling coefficient k2, K2 = K1 × K偏 , and the first sampling coefficient K1 is replaced by the second sampling coefficient k2. This technical solution can timely discover and correct the error in the mapping relationship between the first temperature value T1 and the first sampling coefficient k1 caused by extreme climate conditions, so that when the amount of data is small or the environmental conditions are extreme, the mapping table 1 can be adaptively adjusted, so that the photovoltaic inverter can still maintain good performance under adverse conditions, thereby improving the accuracy of the sampling data.

[0026] In addition, too frequent switching of the sampling coefficient will cause instability of the control system and increase the operating burden of the system. Therefore, under normal working conditions, the first sampling coefficient K1 is determined based on the mapping relationship in the pre-created mapping table 1; under special working conditions, the mapping table 1 is automatically adjusted by rechecking the data and calculating the deviation multiple, which improves the accuracy of data collection and minimizes the switching frequency of the sampling coefficient to protect the stability of the control system.

[0027] As a preferred embodiment of the present invention, the step S4, data rechecking, further comprises an alarm determination step:

[0028] Set the normal deviation range B based on the deviation multiple K 偏 and the normal deviation range B to determine whether to alarm: if the deviation multiple K 偏 If it does not fall within the normal deviation range, the photovoltaic inverter stops working and issues an alarm.

[0029] When the internal device of the photovoltaic inverter itself fails, the deviation multiple K 偏 The value will be larger than the normal state. When the deviation coefficient cannot be used for calibration and repair, the staff needs to perform maintenance. Therefore, the normal deviation range B is set. If the deviation multiple K 偏 If it does not fall within the normal deviation range B, it means that there is a fault in the internal components of the photovoltaic inverter. The photovoltaic inverter stops working and promptly alarms to remind the staff to check.

[0030] As a preferred embodiment of the present invention, the alarm determination step further includes a normal deviation range B determination step:

[0031] Collecting a second temperature value T2, where the second temperature value T2 is a real-time temperature value outside the photovoltaic inverter;

[0032] Based on the second temperature value T2 and the first temperature value T1, the internal and external temperature difference ΔT is calculated, ΔT=|T2-T1|,

[0033] Create a mapping table 2, wherein the mapping table 2 includes a mapping relationship between the internal and external temperature difference ΔT and the normal deviation range B;

[0034] The normal deviation range B is determined based on the mapping relationship in the mapping table 2 and the calculated internal and external temperature difference value ΔT.

[0035] The technicians can create the mapping table 2 through experience or by pre-collecting and analyzing the regular relationship between the internal and external temperature difference ΔT and the normal deviation range B. According to the obtained internal and external temperature difference ΔT of the inverter, the corresponding normal deviation range B is automatically selected based on the mapping rules of the mapping table 2. The system can automatically adjust the normal deviation range according to different working conditions, thereby enhancing the system's adaptive ability, improving the accuracy of the system's early warning, and reducing false alarms and missed alarms.

[0036] A photovoltaic inverter sampling precision automatic adjustment system, using a photovoltaic inverter sampling precision automatic adjustment method according to claim 6, comprising a temperature sensor 1, a control module, a sampling module, a power conversion module, a voltage transformer, a current transformer and a metering chip;

[0037] The temperature sensor 1 is used to collect the first temperature value T1 and output it to the control module;

[0038] The sampling module is used to collect the initial sampling value X of the power conversion module. 初 and output it to the control module;

[0039] The current transformer and the voltage transformer respectively collect the current signal and the voltage signal of the power conversion module and transmit them to the metering chip;

[0040] The metering chip receives the current signal and the voltage signal and outputs the sampling data X 采 to the control module;

[0041] The control module is based on the initial sampling value X 初 , the first temperature value T1, the sampling data X 采 Calculate the effective sampling value X 有效 and the deviation multiple K 偏 .

[0042] As a preferred embodiment of the present invention, the photovoltaic inverter sampling accuracy automatic adjustment system further comprises a temperature sensor 2 and an alarm device.

[0043] The second temperature sensor is used to collect the second temperature value T2 and transmit it to the control module.

[0044] The control module is based on the second temperature value T2 and the deviation multiple K 偏 Control the alarm device to sound an alarm.

[0045] In summary, the present invention has the following beneficial effects:

[0046] 1. By establishing the mapping table 1 between temperature value and sampling coefficient, different temperatures correspond to different sampling coefficients, which is used to correct the sampling error caused by temperature changes.

[0047] 2. The error in the mapping relationship between the first temperature value T1 and the first sampling coefficient k1 caused by extreme climatic conditions can be discovered and corrected in time. When the amount of data is small or the environmental conditions are extreme, the mapping table 1 can be adaptively adjusted so that the photovoltaic inverter can still maintain good performance under adverse conditions, thereby improving the accuracy of the sampling data.

[0048] 3. Under normal working conditions, the first sampling coefficient K1 is determined based on the mapping relationship in the pre-created mapping table 1; under special working conditions, the mapping table 1 is automatically adjusted by rechecking the data and calculating the deviation multiple, which improves the accuracy of data collection while minimizing the sampling coefficient switching frequency and protecting the stability of the control system.

[0049] 4. According to the internal and external temperature difference ΔT of the inverter obtained, based on the mapping rules of the mapping table 2, the corresponding normal deviation range B is automatically selected; the system can automatically adjust the normal deviation range according to different working conditions, thereby enhancing the system's adaptability, improving the accuracy of the system's early warning, and reducing false alarms and missed alarms. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 This is a flow chart of the automatic precision adjustment method;

[0052] Figure 2 A flow chart of the data verification steps;

[0053] Figure 3 Schematic diagram of photovoltaic power generation system. DETAILED DESCRIPTION

[0054] The present invention is further described below by specific examples and drawings. The examples of the present invention are intended to enable those skilled in the art to better understand the present invention, and do not limit the present invention in any way.

[0055] like Figure 3As shown, a photovoltaic power generation system with automatic precision adjustment function includes: NTC1 temperature sensor 1, NTC2 temperature sensor 2, MCU control module, sampling module, power conversion module, PT voltage transformer, CT current transformer and metering chip.

[0056] Power conversion module: includes power conversion unit 1, power conversion unit 2 and multiple bus capacitors connected between power conversion unit 1 and power conversion unit 2; converts PV input signal into AC output signal.

[0057] Sampling module: contains sampling module 1 and sampling module 2, which are connected to the input and output of the power conversion module respectively, and are used to collect the initial sampling value X 初 And transmit to the MCU control module, the initial sampling value X 初 Specifically include PV voltage, current sampling values ​​and AC voltage, current sampling values.

[0058] NTC1, namely temperature sensor 1, is used to collect the internal real-time temperature value of the photovoltaic inverter and output the first temperature value T1 to the control module.

[0059] NTC2, namely temperature sensor 2, is used to collect the real-time temperature value outside the photovoltaic inverter and output the second temperature value T1 to the control module.

[0060] PT1 and PT2 are the input voltage transformer and the output voltage transformer, respectively, which are used to collect PV voltage signals and CT voltage signals and output them to the metering chip;

[0061] CT1 and CT2 are the input current transformer and the output current transformer, respectively, which are used to collect PV current signals and CT current signals and output them to the metering chip;

[0062] The current transformer of the metering chip collects the current signal and voltage signal of the power conversion module respectively and transmits them to the metering chip to receive the current signal and voltage signal, and outputs the sampling data X 采 To the control module;

[0063] The control module receives the initial sampling value X 初 , first temperature value T1, sampling data X 采 , calculate the effective sampling value X 有效 and deviation multiple K 偏 , the sampling accuracy of the photovoltaic inverter is automatically adjusted, and the adjustment method is as follows.

[0064] like Figure 2 As shown, a method for automatically adjusting the sampling accuracy of a photovoltaic inverter is specifically as follows:

[0065] S1. Mapping table 1 creation

[0066] Mapping table 1 includes a mapping relationship between a first temperature value T1 and a first sampling coefficient k1, where the first temperature value T1 is the internal real-time temperature value of the photovoltaic inverter; mapping table 1 also includes segmentation labels, where different segmentation labels correspond to different temperature ranges, and the first sampling coefficient K1 corresponding to the same segmentation label is the same.

[0067] The mapping relationship between the first temperature value T1 and the first sampling coefficient k1 is established in the following manner: the actual sampling values ​​X in the photovoltaic inverter under different first temperature values ​​T1 are collected in advance. 实际 and the initial sampling value X 初 , calculate the first sampling coefficient K1 of different first temperature values ​​T1, K1 = X 实际 / X 初 , establish a mapping relationship between the first temperature value T1 and the first sampling coefficient K1.

[0068] The actual sampling value X of the photovoltaic inverter 实际 It can be directly measured by using high-precision test instruments. However, the equipment cost and power consumption of high-precision measuring instruments are high. If each photovoltaic inverter is equipped with a high-precision measuring instrument for real-time detection, the cost is uncontrollable. Therefore, in the early stage of establishing the mapping table 1, the actual sampling value X in the photovoltaic inverter under different first temperature values ​​T1 is measured. 实际 and the initial sampling value X 初 , and based on the formula: K1=X 实际 / X 初 The mapping relationship between the first temperature value T1 and the first sampling coefficient k1 is obtained. In the subsequent working process of the photovoltaic inverter, the real-time adjustment of the sampling progress can be completed by simply obtaining the first temperature value T1, without the need for each photovoltaic inverter to be equipped with a high-precision measuring instrument for real-time detection. The equipment cost is significantly reduced. For large-scale photovoltaic power generation systems, this can save a lot of initial investment and operation and maintenance costs.

[0069] S2. Data Acquisition

[0070] The current first temperature value T1 and the current initial sampling value X of the photovoltaic inverter are collected through NTC1 and the sampling module. 初 ;

[0071] S3. Determination of effective value

[0072] Based on the mapping rule of mapping table 1 and the collected first temperature value T1, the first sampling coefficient K1 is determined, and the effective sampling value X is calculated. 有效 , X 有效 =X 初* K1.

[0073] S4. Data verification steps:

[0074] In some extreme climates, there are fewer experimental sample data, so there will be a large error in the mapping relationship between the first temperature value T1 and the first sampling coefficient k1. Since the performance difference of the metering chip to temperature change is not as large as that of the inverter itself, the sampling data X of the metering chip inside the photovoltaic inverter is collected. 采 , calculate the deviation multiple K 偏， K 偏 =X 采 / X 有效 , recheck the data to determine whether there is a large error in the mapping relationship between the first temperature value T1 and the first sampling coefficient k1. Figure 3 The data verification steps are as follows:

[0075] Collect sampling data of metering chip X 采 , calculate the deviation multiple K 偏， K 偏 =X 采 / X 有效 ,

[0076] Set the deviation threshold range A, if the deviation multiple K 偏 If it falls within the set deviation threshold range A, it is judged that the mapping relationship between the first temperature value T1 and the first sampling coefficient k1 is still accurate, and the error is still within the controllable range. The first sampling coefficient K1 is determined based on the mapping rule of the mapping table 1 and the collected first temperature value T1, and the effective sampling value X is calculated. 有效 , X 有效 =X 初 *K1.

[0077] If the deviation multiple K 偏 If it does not fall within the deviation threshold range A, it is determined that under this condition, there is a large error in the mapping relationship between the first temperature value T1 and the first sampling coefficient k1. Continue to determine whether there is a fault in the internal device of the photovoltaic inverter: set the normal deviation range B, if the deviation multiple K 偏 If it does not fall within the normal deviation range, it means that there is a fault in the internal components of the photovoltaic inverter itself. The photovoltaic inverter stops working and promptly alarms to remind staff to check.

[0078] If the deviation multiple K 偏 If it falls within the normal deviation range B, it is judged that under this working condition, the component itself is not damaged, and the error comes from the large error in the mapping relationship between the first temperature value T1 and the first sampling coefficient k1. 有效 = Sampling data of the metering chip X 采 , and based on the first sampling coefficient K1 and the deviation multiple K 偏 , calculate the second sampling coefficient k2, K2 = K1 × K 偏, the second sampling coefficient k2 replaces the first sampling coefficient K1.

[0079] The steps for determining the normal deviation range B are as follows:

[0080] NTC2 collects the real-time temperature value outside the photovoltaic inverter and outputs a second temperature value T2 to the control module; the control module calculates the internal and external temperature difference ΔT based on the second temperature value T2 and the first temperature value T1, ΔT = |T2-T1|;

[0081] Create a mapping table 2, which contains the mapping relationship between the internal and external temperature difference ΔT and the normal deviation range B;

[0082] Based on the mapping relationship in mapping table 2 and the calculated internal and external temperature difference ΔT, the normal deviation range B is determined.

[0083] The technicians can create mapping table 2 through experience or by pre-collecting and analyzing the regular relationship between the internal and external temperature difference ΔT and the normal deviation range B. According to the obtained internal and external temperature difference ΔT of the inverter, the corresponding normal deviation range B is automatically selected based on the mapping rules of mapping table 2. The system can automatically adjust the normal deviation range according to different working conditions, thereby enhancing the system's adaptive ability, improving the accuracy of system warnings, and reducing false alarms and missed alarms.

[0084] This technical solution can timely discover and correct the error in the mapping relationship between the first temperature value T1 and the first sampling coefficient k1 caused by extreme climatic conditions, so that when the amount of data is small or the environmental conditions are extreme, the mapping table 1 can be adaptively adjusted, so that the photovoltaic inverter can still maintain good performance under unfavorable conditions, thereby improving the accuracy of the sampled data. In addition, too frequent switching of the sampling coefficient will cause instability in the control system and increase the operating burden of the system. Therefore, under normal working conditions, the first sampling coefficient K1 is determined based on the mapping relationship in the pre-created mapping table 1; under special working conditions, the mapping table 1 is automatically adjusted by rechecking the data and calculating the deviation multiple, which improves the accuracy of data collection while minimizing the switching frequency of the sampling coefficient and protecting the stability of the control system.

[0085] It should be noted that the above embodiments are only detailed descriptions of the preferred embodiments and principles of the present invention. For ordinary technicians in this field, there will be changes in the specific implementation methods based on the ideas provided by the present invention, and these changes are also considered to be within the scope of protection of the present invention.

Claims

1. A method for automatically adjusting sampling accuracy of a photovoltaic inverter, characterized in that: The following steps are involved: S1. Mapping table 1 creation The mapping table 1 includes a mapping relationship between a first temperature value T1 and a first sampling coefficient k1, wherein the first temperature value T1 is a real-time internal temperature value of the photovoltaic inverter; S2. Data Acquisition Collect the current first temperature value T1 and the current photovoltaic inverter initial sampling value X 初 ; S3. Determination of effective value Based on the mapping rule of the mapping table 1 and the first temperature value T1 collected, the first sampling coefficient K1 is determined, and the effective sampling value X is calculated. 有效 , X 有效 =X 初* K1.

2. A photovoltaic inverter sampling accuracy automatic adjustment method according to claim 1, characterized in that: The mapping table 1 further includes segmentation labels, different segmentation labels correspond to different temperature ranges, and the first sampling coefficients K1 corresponding to the same segmentation labels are the same.

3. The method for automatically adjusting sampling accuracy of a photovoltaic inverter according to claim 1, characterized in that: The step of creating the mapping table 1 in step S1 also includes the following steps: collecting the actual sampled values ​​X in the photovoltaic inverter under different first temperature values ​​T1; 实际 and the initial sampling value X 初 , calculate and obtain the first sampling coefficient K1 of different first temperature values ​​T1, K1=X 实际 / X 初 , establish a mapping relationship between the first temperature value T1 and the first sampling coefficient K1.

4. A photovoltaic inverter sampling accuracy automatic adjustment method according to claim 1, characterized in that: The photovoltaic inverter sampling accuracy automatic adjustment method further comprises S4, a data rechecking step: Collect sampling data of metering chip X 采 , calculate the deviation multiple K 偏， K 偏 =X 采 / X 有效 , set the deviation threshold range A, if the deviation multiple K 偏 does not fall within the deviation threshold range A, then the valid sampling value X 有效 = Sampling data of the metering chip X 采 , and based on the first sampling coefficient K1 and the deviation multiple K 偏 , calculate the second sampling coefficient k2, K2 = K1 × K 偏 , the first sampling coefficient K1 is replaced by the second sampling coefficient k2.

5. A photovoltaic inverter sampling accuracy automatic adjustment method according to claim 4, characterized in that: The step S4, data re-verification, also includes an alarm determination step: Set the normal deviation range B based on the deviation multiple K 偏 and the normal deviation range B to determine whether to alarm: if the deviation multiple K 偏 If it does not fall within the normal deviation range, the photovoltaic inverter stops working and issues an alarm.

6. A photovoltaic inverter sampling accuracy automatic adjustment method according to claim 5, characterized in that: The alarm determination step also includes a normal deviation range B determination step: Collecting a second temperature value T2, where the second temperature value T2 is a real-time temperature value outside the photovoltaic inverter; Based on the second temperature value T2 and the first temperature value T1, the internal and external temperature difference ΔT is calculated, ΔT=|T2-T1|, Create a mapping table 2, wherein the mapping table 2 includes a mapping relationship between the internal and external temperature difference ΔT and the normal deviation range B; The normal deviation range B is determined based on the mapping relationship in the mapping table 2 and the calculated internal and external temperature difference ΔT.

7. A photovoltaic inverter sampling accuracy automatic adjustment system, used for using the photovoltaic inverter sampling accuracy automatic adjustment method according to claim 6, characterized in that: Contains a temperature sensor, a control module, a sampling module, a power conversion module, a voltage transformer, a current transformer and a metering chip; The temperature sensor 1 is used to collect the first temperature value T1 and output it to the control module; The sampling module is used to collect the initial sampling value X of the power conversion module. 初 and output it to the control module; The current transformer and the voltage transformer respectively collect the current signal and the voltage signal of the power conversion module and transmit them to the metering chip; The metering chip receives the current signal and the voltage signal and outputs the sampling data X 采 to the control module; The control module is based on the initial sampling value X 初 , the first temperature value T1, the sampling data X 采 Calculate the effective sampling value X 有效 and the deviation multiple K 偏 .

8. A photovoltaic inverter sampling accuracy automatic adjustment system according to claim 7, characterized in that: The photovoltaic inverter sampling accuracy automatic adjustment system also includes a second temperature sensor and an alarm device. The second temperature sensor is used to collect the second temperature value T2 and transmit it to the control module. The control module generates an alarm based on the second temperature value T2 and the deviation multiple K. 偏 Control the alarm device to sound an alarm.

Images