A data screening method and a nominal operating temperature measurement method

Abstract

The present invention provides a data screening method and a nominal operating temperature measurement method, the data screening method comprising the following steps: S1: screening the irradiation intensity data to obtain valid irradiation intensity data that meets the screening conditions; S2: screening the ambient wind speed data to obtain valid ambient wind speed data that meets the screening conditions; S3: if the irradiation intensity and ambient wind speed collected at the i-th moment meet the screening conditions, the meteorological data collected at the i-th moment are all valid data; otherwise, the meteorological data collected at the i-th moment are all invalid data. Compared with the prior art, the data screening method of the present invention can quickly and accurately remove unstable irradiation intensity or ambient wind speed data from the collected data, thereby improving the accuracy of the calculated NMOT value.

Description

Technical Field

[0001] The invention relates to a data screening method and a nominal operating temperature measuring method. Background Art

[0002] Photovoltaic power generation system is a power generation system that uses the photovoltaic effect to convert solar energy into electrical energy. It has the characteristics of high reliability, long service life, environmental protection, independent power generation and grid-connected operation, etc. It is deeply favored by enterprises and organizations in various countries and has broad development prospects. In the actual use of photovoltaic power generation system, the power generation of photovoltaic modules is greatly affected by the working temperature of photovoltaic cells, and ambient temperature, radiation intensity and ambient wind speed are the main factors affecting the working temperature of photovoltaic cells.

[0003] According to the IEC61215 standard "Crystalline Silicon Photovoltaic Modules for Terrestrial Use - Design Qualification and Finalization", the standard reference environment for the nominal operating temperature (NMOT value) of photovoltaic modules is: the module installation angle is 37°±5°, the overall irradiance is 800W / m 2 , the ambient temperature is 20℃, the wind speed is 1m / s, and the electronic load is connected to make the photovoltaic module work near the maximum power point (MPPT). Under this specific environmental condition, the temperature value of the photovoltaic cell in the photovoltaic module is the NMOT value of the photovoltaic module. The NMOT value can be used as a reference temperature for photovoltaic modules when working on site, and it is a very useful parameter for photovoltaic module finalization and system design. However, the existing method for measuring the NMOT value is not only complicated, but also requires a lot of manpower, which pushes up the production cost of photovoltaic modules. Secondly, the accuracy of the NMOT value measured by the existing measurement method is low, which is not conducive to the finalization of photovoltaic modules and system design; this is because there is currently a lack of effective means to eliminate unstable irradiation intensity or ambient wind speed data from the collected data, thereby interfering with the accurate calculation of the NMOT value.

[0004] In view of the above problems, it is necessary to provide a data screening method and a nominal operating temperature measurement method to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a data screening method and a nominal operating temperature measurement method. The nominal operating temperature measurement method not only has a simple process but also has high measurement accuracy, which is beneficial to photovoltaic module finalization and system design.

[0006] To achieve the above object, the present invention provides a data screening method for screening out valid data for calculating the nominal operating temperature of photovoltaic modules from meteorological data collected in chronological order, wherein the meteorological data includes irradiation intensity, ambient temperature and ambient wind speed data, and comprises the following steps:

[0007] S1: Screening the irradiance intensity data to obtain valid irradiance intensity data that meets the screening conditions, specifically including the following steps:

[0008] S11: Calculate the previous T including the i-th moment 11 The maximum value P of the irradiance intensity data of all collected time points within a certain period of time imax And the minimum value P imin ;

[0009] S12: Calculate the radiation intensity P at the i-th moment i With P imax , P imin The ratio of k imax =P i / P imin , k imin =P i / Pimax ;

[0010] S13: If k imin ≤K 1 or k imax ≥K 2 , then the subsequent T including the i-th moment 12 The irradiance intensity data of all acquisition time points within the time period are invalid data; otherwise, jump to step S14;

[0011] S14: If P i >P 0 , then the radiation intensity P at the i-th moment i is valid data; otherwise, the irradiance intensity P at the i-th moment i is invalid data;

[0012] S2: Screening the ambient wind speed data to obtain valid ambient wind speed data that meets the screening conditions;

[0013] S3: If the irradiation intensity and ambient wind speed at the i-th moment meet the screening conditions, the meteorological data collected at the i-th moment are all valid data; otherwise, the meteorological data collected at the i-th moment are all invalid data.

[0014] As a further improvement of the present invention, the environmental wind speed data screening includes the following steps:

[0015] S21: Calculate the previous T including the i-th moment 21 The average value of the ambient wind speed data at all collection time points within a period of time W iavg ;

[0016] S22: Calculate the ambient wind speed data W at the i-th moment i With W iavg The ratio of W iratio =Wi / W iavg ;

[0017] S23: If W i ≤W 0 or W iratio ≥W R , then the subsequent T including the i-th moment 22 The ambient wind speed data of all collected time points within the time period are invalid data and are deleted; otherwise, jump to step S24;

[0018] S24: If W min <W iavg <W max , then the ambient wind speed data W at the i-th moment i is valid data and is retained; otherwise, the ambient wind speed data W at the i-th moment i It is considered invalid data and will be deleted.

[0019] As a further improvement of the present invention, the time interval between adjacent acquisition time points is 5 seconds; 11 , T 12 Equally, 10 minutes.

[0020] As a further improvement of the present invention, the K 1 is 0.9, the K 2 is 1.1, the P 0 400w / m 2 .

[0021] As a further improvement of the present invention, the time interval between adjacent acquisition time points is 5 seconds. 21 For 5 minutes, the T 22 For 10 minutes.

[0022] As a further improvement of the present invention, the W 0 is 0.25m / s, the W R is 200%, the W min is 1m / s, the W max 8m / s.

[0023] As a further improvement of the present invention, there are at least N effective data collected every day. 1 One is before 12 o'clock true solar time, at least N 2 The first one is after 12 o'clock true solar time; otherwise, all the valid collected data of the day will be deemed invalid data.

[0024] As a further improvement of the present invention, the N 1 is 10, N 2 is 10.

[0025] The present invention also discloses a nominal operating temperature measurement method, comprising the following steps:

[0026] Acquire meteorological data of a photovoltaic module work site and a module temperature of the photovoltaic module over a period of time, wherein the meteorological data includes radiation intensity, ambient temperature, and ambient wind speed data;

[0027] The meteorological data are screened using the aforementioned data screening method, and valid data that meets the screening conditions is retained;

[0028] Perform linear regression analysis and fitting on the data that meet the screening conditions to obtain the heat loss coefficient U of the photovoltaic module. 0 and U 1 ;

[0029] Reference formula T mod =P / (U 0 +U 1 *W)+T amb , using the heat loss coefficient U 0 and U 1 Calculate the nominal operating temperature of the PV module; where T mod is the component temperature, P is the irradiation intensity, W is the ambient wind speed, T amb is the ambient temperature.

[0030] As a further improvement of the present invention, the valid data for linear regression analysis and fitting must come from data collected over a period of at least 10 days.

[0031] The beneficial effect of the present invention is that the data screening method of the present invention can quickly and accurately remove unstable irradiation intensity or ambient wind speed data from the collected data, thereby improving the accuracy of the calculated NMOT value. Secondly, the nominal operating temperature measurement method of the present invention is not only simple in process, but also has high measurement accuracy, which is beneficial to photovoltaic module finalization and system design. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of the data screening method of the present invention.

[0033] Figure 2 It is a flow chart of the steps for screening irradiance intensity data.

[0034] Figure 3 It is a flow chart of the environmental wind speed data screening steps.

[0035] Figure 4 It is a flow chart of the nominal operating temperature measurement method.

[0036] Figure 5 It is a block diagram of the nominal operating temperature measurement system. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0038] See also Figure 1 As shown, the present invention discloses a data screening method for screening out effective data for calculating the nominal operating temperature of photovoltaic modules from meteorological data collected in chronological order, wherein the meteorological data includes irradiation intensity, ambient temperature and ambient wind speed data. The data screening method comprises the following steps:

[0039] S1: Screening the irradiation intensity data to obtain effective irradiation intensity data that meets the screening conditions;

[0040] S2: Screening the ambient wind speed data to obtain valid ambient wind speed data that meets the screening conditions;

[0041] S3: If the irradiation intensity and ambient wind speed collected at the i-th moment meet the screening conditions, the meteorological data collected at the i-th moment are all valid data; otherwise, the meteorological data collected at the i-th moment are all invalid data.

[0042] Specifically, see Figure 2 As shown, the irradiance intensity data screening step in step S1 includes the following steps:

[0043] S11: Calculate the previous T including the i-th moment 11 The maximum value P of the irradiance intensity data of all collected time points within a certain period of time imax And the minimum value P imin ;

[0044] S12: Calculate the radiation intensity P at the i-th moment i With P imax , P imin The ratio of k imax =P i / P imin , k imin =P i / Pimax ;

[0045] S13: If k imin ≤K 1 or k imax ≥K 2 , then the subsequent T including the i-th moment 12 The irradiance intensity data of all collected time points within the time period are invalid data and are deleted; otherwise, jump to step S14;

[0046] S14: If P i>P 0 , then the radiation intensity P at the i-th moment i is valid data and is retained; otherwise, the irradiation intensity P at the i-th moment i It is invalid data and will be deleted;

[0047] In this embodiment, the time interval between adjacent acquisition time points is 5 seconds; 11 , T 12 equal, for 10 minutes; the K 1 is 0.9, the K 2 is 1.1, the P 0 400w / m 2 Of course, it can be understood that in other embodiments, the time interval between adjacent acquisition time points, T 11 , T 12 , K 1 , K 2 , P 0 It can also be set up as needed.

[0048] Preferably, the step S11 further includes step S110: determining the previous T including the i-th moment 11 Is the number of collected data within a certain time equal to N? 1 =((T 11 / adjacent collection time interval) + 1); if the previous T including the i-th moment 11 The number of collected data in time is equal to N 1 , then calculate the previous T including the i-th moment 11 The maximum value P of the irradiance intensity data of all collected time points within a certain period of time imax And the minimum value P imin .

[0049] See also Figure 3 As shown, the environmental wind speed data screening in step S2 includes the following steps:

[0050] S21: Calculate the previous T including the i-th moment 21 The average value of the ambient wind speed data at all collection time points within a period of time W iavg ;

[0051] S22: Calculate the ambient wind speed data W at the i-th moment i With W iavg The ratio of W iratio =W i / W iavg ;

[0052] S23: If W i ≤W 0 or W iratio ≥WR , then the subsequent T including the i-th moment 22 The ambient wind speed data of all collected time points within the time period are invalid data and are deleted; otherwise, jump to step S24;

[0053] S24: If W min <W iavg <W max , then the ambient wind speed data W at the i-th moment i is valid data and is retained; otherwise, the ambient wind speed data W at the i-th moment i It is considered invalid data and will be deleted.

[0054] In this embodiment, the T 21 For 5 minutes, the T 22 For 10 minutes, the W 0 is 0.25m / s, the W R is 200%, the W min is 1m / s, the W max Of course, it can be understood that in other embodiments, the T 21 、T 22 , W 0 , W R , W min , W max It can also be set up as needed.

[0055] Preferably, the step S21 further includes step S210: determining the previous T including the i-th moment 21 Whether the number of ambient wind speed data at all collected time points in the time period is equal to N 2 =((T 21 / adjacent collection time interval) + 1); if the previous T including the i-th moment 21 The number of ambient wind speed data collected at all time points in time is equal to N 2 , then calculate the previous T including the i-th moment 21 The average value of the ambient wind speed data at all collection time points within a period of time W iavg .

[0056] Compared with the prior art, the data screening method disclosed in the present invention can quickly and accurately remove unstable radiation intensity or ambient wind speed data from the collected data, thereby improving the accuracy of the calculated NMOT value.

[0057] See also Figure 4 As shown, the present invention also discloses a nominal operating temperature measurement method, comprising the following steps:

[0058] S01: Acquire meteorological data of a photovoltaic module work site and a component temperature of the photovoltaic module within a period of time, wherein the meteorological data includes radiation intensity, ambient temperature, and ambient wind speed data;

[0059] S02: Filter the meteorological data using the aforementioned data screening method, and retain valid data that meets the screening conditions;

[0060] Furthermore, the step S02 further includes: when the irradiance P at the i-th moment i , Ambient wind speed W i When both are selected, the irradiation intensity P at the i-th moment i , Ambient wind speed W i 、Ambient temperature T iamb and the component temperature T imod At the same time, they are valid data, otherwise they are invalid data.

[0061] S03: Perform linear regression analysis and fitting on the data that meet the screening conditions to obtain the heat loss coefficient U of the photovoltaic module 0 and U 1 ;

[0062] Preferably, the valid data for linear regression analysis and fitting must come from data collected over at least 10 days. Preferably, the valid data collected each day has at least N 1 One is before 12 o'clock true solar time, at least N 2 is after 12 o'clock of the true solar time; otherwise, all the valid collected data of the day are deemed invalid data. 1 、N 2 The value of N is 10, but in practical applications, 1 、N 2 The value can be set as needed.

[0063] S04: Reference formula T mod =P / (U 0 +U 1 *W)+T amb , using the heat loss coefficient U 0 and U 1 Calculate the nominal operating temperature of the PV module; where T mod is the component temperature, P is the irradiation intensity, W is the ambient wind speed, T amb is the ambient temperature.

[0064] Specifically, P = 800 W / m 2 、T amb =20℃, W=1m / s, heat loss coefficient U 0 and U 1Substitute into the formula T mod =P / (U 0 +U 1 *W)+T amb , and thus calculate the nominal operating temperature T of the photovoltaic module mod .

[0065] Compared with the prior art, the nominal operating temperature measurement method disclosed in the present invention not only has a simple process but also has high measurement accuracy, which is beneficial to photovoltaic module finalization and system design.

[0066] See also Figure 5 As shown, the present invention also discloses a nominal operating temperature measurement system, comprising a meteorological acquisition module 10 for acquiring meteorological data of a photovoltaic module work site, a temperature acquisition module 20 for acquiring the component temperature of the photovoltaic module, and a control module 30. The control module 30 is in communication connection with the meteorological acquisition module 10 and the temperature acquisition module 20, and calculates the nominal operating temperature through the nominal operating temperature measurement method.

[0067] The weather acquisition module 10 includes a thermometer 11 for collecting ambient temperature, a radiometer 12 for collecting irradiation intensity, and an anemometer 13 for collecting wind speed, and the thermometer 11, the radiometer 12, and the anemometer 13 are all connected to the control module 30. Specifically, the temperature acquisition module 20, the thermometer 11, the radiometer 12, and the anemometer 13 are connected to the control module 30 by wireless or wired connection, preferably by wireless connection such as Bluetooth, network, NFC, etc., so that remote measurement can be performed.

[0068] Compared with the prior art, the nominal operating temperature measurement method of the present invention is not only simple in process, but also has high measurement accuracy, which is beneficial to photovoltaic module finalization and system design, etc. In addition, the data screening logic flow and processing flow in steps S2, S3, and S4 can be implemented through Python programming, so that the data can be processed quickly and accurate NMOT values ​​can be obtained, so as to provide an evaluation basis for the outdoor power generation performance collection of photovoltaic modules.

[0069] The above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A data screening method for screening out valid data for calculating the nominal operating temperature of a photovoltaic module from meteorological data collected in chronological order, wherein the meteorological data includes irradiation intensity, ambient temperature and ambient wind speed data, characterized in that: The steps include: S1: Screening the irradiance intensity data to obtain valid irradiance intensity data that meets the screening conditions, specifically including the following steps: S11: Calculate the previous T including the i-th moment 11 The maximum value P of the irradiance intensity data of all collected time points within a certain period of time imax And the minimum value P imin ; S12: Calculate the radiation intensity P at the i-th moment i With P imax , P imin The ratio of k imax =P i / P imin , k imin =P i / P imax ; S13: If k imin ≤K1 or k imax ≥K2, then the subsequent T including the i-th moment 12 The irradiance intensity data of all acquisition time points within the time period are invalid data; otherwise, jump to step S14; S14: If P i >P0, then the radiation intensity at the i-th moment is P i is valid data; otherwise, the irradiance intensity P at the i-th moment i Invalid data; K1 is 0.9, K2 is 1.1, P0 is 400w / m 2 ; S2: Screening the ambient wind speed data to obtain valid ambient wind speed data that meets the screening conditions; the ambient wind speed data screening includes the following steps: S21: Calculate the previous T including the i-th moment 21 The average value of the ambient wind speed data at all collection time points within a period of time W iavg ; S22: Calculate the ambient wind speed data W at the i-th moment i With W iavg The ratio of W iratio =W i / W iavg ; S23: If W i ≤W0 or W iratio ≥W R , then the subsequent T including the i-th moment 22 The ambient wind speed data at all acquisition time points within the time period are invalid data; otherwise, jump to step S24; S24: If W min <W iavg <W max , then the ambient wind speed data W at the i-th moment i is valid data; otherwise, the ambient wind speed data W at the i-th moment i is invalid data; W0 is 0.25m / s, W R is 200%, the W min is 1m / s, the W max 8m / s; S3: If the irradiation intensity and ambient wind speed at the i-th moment meet the screening conditions, the meteorological data collected at the i-th moment are all valid data; otherwise, the meteorological data collected at the i-th moment are all invalid data.

2. The data screening method according to claim 1, characterized in that: The time interval between adjacent acquisition time points is 5 seconds; 11 、T 12 Equally, 10 minutes.

3. The data screening method according to claim 1, characterized in that: The time interval between adjacent acquisition time points is 5 seconds. 21 For 5 minutes, the T 22 For 10 minutes.

4. The data screening method according to any one of claims 1 to 3, characterized in that: At least N1 of the valid collected data for each day are before 12:00 true solar time, and at least N2 of them are after 12:00 true solar time; otherwise, all the valid collected data for that day will be deemed invalid data.

5. The data screening method according to claim 4, characterized in that: The N1 is 10, and the N2 is 10.

6. A method for measuring nominal operating temperature, characterized in that: The steps include: Acquire meteorological data of a photovoltaic module work site and a module temperature of the photovoltaic module over a period of time, wherein the meteorological data includes radiation intensity, ambient temperature, and ambient wind speed data; Filtering the meteorological data using the data screening method described in any one of claims 1 to 5 to obtain valid data that meets the screening conditions; Perform linear regression analysis and fitting on the valid data that meet the screening conditions to obtain the heat loss coefficients U0 and U1 of the photovoltaic modules; Reference formula T mod =P / (U0+U1*W)+T amb , using the heat loss coefficients U0 and U1 to calculate the nominal operating temperature of the PV module; where T mod is the component temperature, P is the irradiation intensity, W is the ambient wind speed, T amb is the ambient temperature.

7. The nominal operating temperature measurement method according to claim 6, characterized in that: Valid data for linear regression analysis and fitting must come from data collected over a period of at least 10 days.

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