Photovoltaic inverter wide voltage input range adaptive adjustment method and system

Abstract

The application discloses a photovoltaic inverter wide-voltage input range adaptive adjustment method and system, relates to the wide-voltage input range adjustment technical field, and comprises the following steps: collecting the voltage of a photovoltaic module output to a photovoltaic inverter in each period, collecting the average temperature and average irradiance in each period, obtaining input voltage sample data and related weather sample data; and performing period similarity analysis, screening a reference period of the period, and obtaining reference period information; using the input voltage sample data of the reference period to perform input range analysis, obtaining wide-voltage input range information; and adaptively adjusting the wide-voltage input range of the photovoltaic inverter; the application is used to solve the problem that the existing wide-voltage input range adjustment technology cannot adaptively adjust the wide-voltage input range of the photovoltaic inverter according to historical input voltage conditions and in combination with temperature and irradiance when adjusting the wide-voltage input range of the photovoltaic inverter.

Description

Technical Field

[0001] This invention relates to the field of wide voltage input range adjustment technology, specifically to a method and system for adaptive adjustment of wide voltage input range in photovoltaic inverters. Background Technology

[0002] Wide voltage input range adjustment technology for photovoltaic inverters refers to an intelligent technology that dynamically optimizes the actual operating voltage range of the inverter within the fixed maximum input voltage limit and minimum start-up voltage threshold of the inverter hardware through multi-source data sensing, adaptive algorithm decision-making, and real-time control execution.

[0003] Existing wide voltage input range adjustment technologies for photovoltaic inverters often preset one or more fixed ranges and then switch them according to the season or time of day. However, these fixed ranges are often preset based on experience, aiming for wide coverage but lacking adaptability and unable to cope with dynamic operating conditions and individual differences. For example, different weather conditions in the same season can cause significant fluctuations in string voltage, but the fixed range cannot be adjusted in real time, easily leading to problems such as voltage exceeding the range or the range being too wide. If the wide voltage input range of the photovoltaic inverter is too large, it will increase the difficulty of MPPT search and adjustment, and reduce the response speed. The current wide voltage input range adjustment technology is slow and difficult to accurately lock the maximum power point, resulting in reduced power generation efficiency. An excessively large range may also include inefficient intervals, leading to a decline in overall conversion efficiency. If the range is too small, it will cause the inverter to start and stop frequently, reducing power generation time. Under high temperature and low light conditions, the module output voltage will decrease, and if it falls below the set lower limit, the inverter will shut down. Too small a range may also miss some high-efficiency intervals, resulting in low power generation efficiency. Therefore, the existing wide voltage input range adjustment technology cannot adaptively adjust the wide voltage input range of photovoltaic inverters based on historical input voltage conditions, combined with temperature and irradiance. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art. It collects the voltage output from the photovoltaic module to the photovoltaic inverter for each time period, along with the average temperature and average irradiance for each time period. By performing time period similarity analysis and filtering reference time periods, reference time period information is obtained. Based on this reference time period information, input range analysis is performed to obtain wide voltage input range information. The wide voltage input range of the photovoltaic inverter is then adaptively adjusted. This addresses the problem that existing wide voltage input range adjustment technologies cannot adaptively adjust the wide voltage input range of the photovoltaic inverter based on historical input voltage data, combined with temperature and irradiance.

[0005] To achieve the above objectives, this application provides a wide voltage input range adaptive adjustment method for photovoltaic inverters, comprising the following steps: Collect the voltage output from the photovoltaic modules to the photovoltaic inverter for each time period, and collect the average temperature and average irradiance for each time period to obtain input voltage sample data and relevant weather sample data; Based on relevant weather sample data, time period similarity analysis is performed to filter reference time periods and obtain reference time period information; Based on the reference time period information, the input range analysis is performed using the input voltage sample data of the reference time period to obtain wide voltage input range information; The wide voltage input range of the photovoltaic inverter is adaptively adjusted based on the wide voltage input range information.

[0006] Furthermore, the voltage output from the photovoltaic modules to the photovoltaic inverter is collected for each time period, and the average temperature and average irradiance for each time period are also collected to obtain input voltage sample data and relevant weather sample data, including the following sub-steps: For any type of photovoltaic inverter, denoted as the first inverter, the photovoltaic module connected to the first inverter is denoted as the first photovoltaic module, and the voltage output by the first photovoltaic module to the first inverter is denoted as the input voltage of the first inverter. The normal operating time of the first inverter is divided into multiple time periods of duration T0, denoted as time periods, and any one of these time periods is designated as the first time period; where T0 is the set duration.

[0007] Furthermore, the voltage output from the photovoltaic modules to the photovoltaic inverter is collected for each time period, and the average temperature and average irradiance for each time period are also collected to obtain input voltage sample data and relevant weather sample data, including the following sub-steps: In the first time period, the input voltage of the first inverter is collected at the first time interval and recorded as the input voltage information of the first time period; the input voltage information of each time period is collected repeatedly every day and sorted by date and recorded as input voltage sample data, where the first time interval is t1; In the first time period, the average temperature of the environment where the first photovoltaic module is located is collected, and the average irradiance of the environment where the first photovoltaic module is located is collected in the first time period. These are recorded as the relevant weather information for the first time period. The relevant weather information for each time period is collected repeatedly every day and sorted by date, and recorded as the relevant weather sample data.

[0008] Furthermore, based on relevant weather sample data, a time-period similarity analysis is performed to filter reference time periods, obtaining reference time period information, including the following sub-steps: The next time period after the current time period is designated as the first future time period. The average temperature and average irradiance of the predicted first future time period are obtained and designated as AT and AI in order. The k1 dates closest to the date of the first future time period are designated as reference dates, where k1 is the number of reference dates. For the average irradiance, multiple continuous irradiance intervals with a width of k2 are set, and all time periods of all reference dates are assigned to each irradiance interval according to the average irradiance; any irradiance interval is denoted as the first interval; where k2 is the set interval size.

[0009] Furthermore, based on relevant weather sample data, time-period similarity analysis is performed to filter reference time periods and obtain reference time period information. This process also includes the following sub-steps: Obtain the average irradiance of the time period within the first interval, denoted as the first average irradiance set; obtain the absolute difference between the maximum and minimum values ​​in the first average irradiance set, denoted as the irradiance range IC; obtain the average of the average irradiance of all time periods across all reference dates, denoted as the time period irradiance mean PI. Based on the input voltage sample data, calculate the average input voltage of the input voltage information for each time period in each reference date, and calculate the average value of the average input voltage for all time periods, denoted as the time period voltage mean PV; And obtain the average input voltage of the first interval, denoted as the first average voltage set, and obtain the absolute difference between the maximum and minimum values ​​in the first average voltage set, denoted as the voltage range VC; Calculate (IC / PI) / (VC / PV), and denote it as the irradiance sensitivity coefficient corresponding to the first interval. Repeatedly obtain the average value of the irradiance sensitivity coefficients corresponding to all irradiance intervals, and denote it as the sensitivity corresponding to the average irradiance, labeled as irradiance sensitivity IM; repeatedly obtain the sensitivity corresponding to the average temperature, labeled as temperature sensitivity TM.

[0010] Furthermore, based on relevant weather sample data, time-period similarity analysis is performed to filter reference time periods and obtain reference time period information. This process also includes the following sub-steps: Calculate TM / (IM+TM) and IM / (IM+TM) respectively, and denote them as temperature weight TQ and irradiance weight IQ in order; denote any time period in the reference date as the sample time period; denote the average temperature and average irradiance of the sample time period as YT and YI in order; Calculate the relative temperature deviation DT and the relative irradiance deviation DI, respectively, where DT = |AT - YT| / AT and DI = |AI - YI| / AI; and calculate the similarity score GS between the first future time period and the sample time period, where GS = TQ × DT + IQ × ​​DI; Repeatedly obtain the similarity scores between the first future time period and all time periods in the reference date, and take the smallest k3% similarity score. Record the corresponding time period as the reference time period of the first future time period, and mark it as the reference time period information of the first future time period, where k3% is the set percentage.

[0011] Furthermore, based on the reference time period information, the input range analysis is performed using the input voltage sample data of the reference time period to obtain wide voltage input range information, including the following sub-steps: For the input voltage information of each reference time period in the first future time period, the outliers corresponding to each input voltage information are removed by using the 3σ principle, and the remaining input voltage information of each reference time period is merged and denoted as the first voltage set. Calculate the average value PU and standard deviation BU of the first voltage set. Calculate PU-k4×BU and PU+k4×BU, which are denoted as the initial lower limit XU and the initial upper limit SU, respectively, where k4 is the set scaling factor.

[0012] Furthermore, based on the reference time period information, the input range analysis using the input voltage sample data of the reference time period to obtain wide voltage input range information also includes the following sub-steps: Calculate the mean values ​​of irradiance IM (IPM) and temperature sensitivity TM (TPM) for all reference periods; calculate the mean values ​​of average irradiance (HI) and average temperature (HT) for all reference periods. Calculate AT-HT and AI-HI, denoted as temperature difference RT and illuminance difference RI, respectively; and calculate temperature correction WT and illuminance correction WI, where WT=RT×TPM and WI=RI×IPM; and denote WT+WI as the total correction WTI. Calculate the lower limit XEU and the upper limit SEU, and record them as the wide voltage input range information for the first future time period, where XEU=XU+WTI and SEU=SU+WTI.

[0013] Furthermore, adaptively adjusting the wide voltage input range of the photovoltaic inverter based on the wide voltage input range information includes the following sub-steps: Based on the lower limit XEU and the upper limit SEU, [k5×XEU, k6×SEU] is denoted as the pre-adjusted voltage range, and the wide voltage input range of the first inverter is adjusted to the pre-adjusted voltage range in the first future time period, where k5 and k6 are set proportional coefficients, k5<1, k6>1; The wide voltage input range of the first inverter in the next time period is adjusted in sequence.

[0014] Secondly, this application provides a wide voltage input range adaptive adjustment system for photovoltaic inverters, including a sample collection module, a time period screening module, a voltage analysis module, and a range adjustment module; The sample collection module includes a voltage acquisition unit and a weather acquisition unit. The voltage acquisition unit is used to collect the voltage output by the photovoltaic module to the photovoltaic inverter at each time period to obtain input voltage sample data. The weather acquisition unit is used to collect the average temperature and average irradiance at each time period to obtain relevant weather sample data. The time period filtering module performs time period similarity analysis based on relevant weather sample data, filters reference time periods, and obtains reference time period information; The voltage analysis module performs input range analysis based on the reference time period information and the input voltage sample data of the reference time period to obtain wide voltage input range information; The range adjustment module adaptively adjusts the wide voltage input range of the photovoltaic inverter based on the wide voltage input range information.

[0015] The beneficial effects of this invention are as follows: This invention collects the voltage output from the photovoltaic module to the photovoltaic inverter at each time period, and collects the average temperature and average irradiance at each time period to obtain input voltage sample data and related weather sample data; it performs time period similarity analysis based on the related weather sample data to filter reference time periods and obtain reference time period information; based on the reference time period information, it uses the input voltage sample data of the reference time period to perform input range analysis to obtain wide voltage input range information; it adaptively adjusts the wide voltage input range of the photovoltaic inverter according to the wide voltage input range information; when adjusting the wide voltage input range of the photovoltaic inverter, it is not possible to adaptively adjust the wide voltage input range of the photovoltaic inverter based on historical input voltage conditions, while also considering temperature and irradiance, thus improving the adaptability of the input range; This invention compares predicted temperature and irradiance for future periods with actual temperature and irradiance for historical periods, and calculates a similarity score with the weights of temperature and irradiance to select the historical period closest to the future weather as a reference. This selected reference period better represents the statistical characteristics of future input voltage, reducing the bias of directly using all historical data. By calculating irradiance sensitivity and temperature sensitivity, and using sensitivity to determine the weights of temperature and irradiance in the similarity score, higher weights can be assigned to factors with a greater impact on voltage, thereby improving the relevance and reliability of the selected reference period. The average sensitivity of the reference period is calculated and compared with the historical average. Then, corrections are calculated based on the predicted temperature and irradiance differences to adjust the initial upper and lower limits, ensuring that the final input range is based on both historical conditions and short-term weather changes, thus improving the accuracy of the input range. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the system of the present invention; Figure 2 This is a flowchart illustrating the steps of the method of the present invention; Figure 3This is a flowchart of the process for obtaining the irradiation sensitivity coefficient according to the present invention; Figure 4 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1, please refer to Figure 1 As shown, this application provides a wide voltage input range adaptive adjustment system for photovoltaic inverters, including a sample collection module, a time period screening module, a voltage analysis module, and a range adjustment module; The sample collection module includes a voltage acquisition unit and a weather acquisition unit. The voltage acquisition unit is used to collect the voltage output from the photovoltaic module to the photovoltaic inverter at each time period to obtain input voltage sample data. The weather acquisition unit is used to collect the average temperature and average irradiance at each time period to obtain relevant weather sample data. The voltage acquisition unit is configured with a voltage acquisition strategy, which includes: for any photovoltaic inverter, referred to as the first inverter, the photovoltaic module connected to the first inverter is referred to as the first photovoltaic module, and the voltage output by the first photovoltaic module to the first inverter is referred to as the input voltage of the first inverter. The normal operating time of the first inverter is divided into multiple time periods of duration T0, denoted as time periods, and any one of these time periods is designated as the first time period; where T0 is the set duration; in this embodiment, T0 = 1 hour, that is, 1 hour is one time period, for example, 8:00 to 9:00 is one time period, and 9:00 to 10:00 is the next time period; T0 can be flexibly set according to the actual application scenario; dividing the time period can provide basic units for subsequent analysis and processing, and reduce the amount of data and computational burden. Processing and aggregating data by time period is more efficient than processing each piece of raw data; In the first period, the input voltage of the first inverter is collected at a first time interval and recorded as the input voltage information of the first period; the input voltage information of each period is collected repeatedly every day and sorted by date and recorded as input voltage sample data, wherein the first time interval is t1. In this embodiment, the first time interval is 0.1 seconds and can be flexibly set.

[0019] The weather data acquisition unit is configured with a weather data acquisition strategy, which includes: during the first time period, acquiring the average temperature of the environment where the first photovoltaic module is located, in °C, and acquiring the average irradiance of the environment where the first photovoltaic module is located, in W / m². 2 This is recorded as the relevant weather information for the first time period; relevant weather information for each time period is collected repeatedly every day and sorted by date, and recorded as relevant weather sample data; In practical implementation, temperature and irradiance are the core factors affecting the voltage output of the photovoltaic string to the inverter. Temperature and voltage are inversely related; low temperatures will cause the voltage to rise significantly, while high temperatures will cause the voltage to drop, directly determining the voltage fluctuation boundary. Irradiance and voltage are positively related; under weak light, the voltage rises rapidly with irradiance and tends to stabilize under strong light, and sudden changes will cause instantaneous voltage fluctuations. Under the combined effect of the two, temperature dominates the extreme voltage values, while irradiance determines the voltage start-up threshold and stable range, jointly affecting the inverter's operating range adaptability and power generation efficiency.

[0020] The time period filtering module performs time period similarity analysis based on relevant weather sample data, filters reference time periods, and obtains reference time period information; The time period filtering module is configured with a time period filtering strategy, which includes: designating the next time period after the current time period as the first future time period; obtaining the predicted average temperature and average irradiance of the first future time period, and designating them as AT and AI in sequence; designating the k1 dates closest to the date of the first future time period as reference dates; where k1 is the set number; in this embodiment, k1=30, generally 15 to 40, and can be flexibly set; the average temperature of the first future time period can be obtained from relevant weather forecasts or predicted manually; and the average irradiance of the first future time period can be obtained using relevant prediction models, or it can be obtained by multiplying the average irradiance of the current time period by a certain variation coefficient. For the average irradiance, multiple continuous irradiance intervals with a width of k2 are set, and all time periods of all reference dates are allocated to each irradiance interval according to the average irradiance; any one of the irradiance intervals is denoted as the first interval; where k2 is the set interval size. In this embodiment, the width of the irradiance interval k2 = 50 W / m 2 The width of the subsequent temperature range is 1℃, which can be set flexibly, but should not be too large. Because it is difficult to find periods in historical data where the temperature remains constant while the illuminance changes, or where the irradiance remains constant while the temperature changes, we divide the data into intervals. We find time periods where the illuminance remains almost constant and calculate the temperature sensitivity; we find time periods where the temperature remains almost constant and calculate the illuminance sensitivity. This eliminates cross-influences, making the subsequent sensitivity more accurate and the weighting more reliable.

[0021] The average irradiance for the time period within the first interval is obtained and denoted as the first average irradiance set. The absolute difference between the maximum and minimum values ​​in the first average irradiance set is obtained and denoted as the irradiance range IC. The average irradiance for all time periods across all reference dates is obtained and denoted as the time period mean irradiance PI. IC represents the irradiance fluctuation range between different samples within the irradiance interval, while the temperature corresponding to the irradiance interval remains almost constant, and voltage fluctuations are mainly caused by irradiance fluctuations. PI is a normalized benchmark. Based on the input voltage sample data, calculate the average input voltage for each time period in each reference date, and calculate the average value of the average input voltage for all time periods, denoted as the time period voltage mean PV; PV is a normalized benchmark. The average input voltage for the first interval is obtained and denoted as the first average voltage set. The absolute difference between the maximum and minimum values ​​in the first average voltage set is obtained and denoted as the voltage range VC. IC represents the voltage fluctuation amplitude between different samples within the irradiation interval. Calculate (IC / PI) / (VC / PV), and record it as the irradiance sensitivity coefficient corresponding to the first interval. Repeatedly obtain the average value of the irradiance sensitivity coefficients corresponding to all irradiance intervals, and record it as the sensitivity corresponding to the average irradiance, marked as irradiance sensitivity IM. Repeatedly obtain the sensitivity corresponding to the average temperature, and mark it as temperature sensitivity TM. The acquisition process is the same as the acquisition process of irradiance sensitivity IM. Irradiance sensitivity IM represents the percentage change in voltage for every 1% change in irradiance; temperature sensitivity TM represents the percentage change in voltage for every 1% change in temperature; for example, the average irradiance over several time periods within the first interval is [420, 450, 470, 430, 460], in W / m². 2 If IC = 470 - 420 = 50, then the average input voltage in the first interval is [250, 275, 301, 320, 314], in V. Then VC = 320 - 250 = 70. Assuming PI = 550 and PV = 320, then (IC / PI) / (VC / PV) = (50 / 550) / (70 / 320) = 0.416.

[0022] Calculate TM / (IM+TM) and IM / (IM+TM) respectively, and denote them as temperature weight TQ and irradiance weight IQ in order; denote any time period in the reference date as the sample period; denote the average temperature and average irradiance of the sample period as YT and YI in order; for TM and IM, if TM is larger than IM, then TQ is larger, which indicates that temperature has a more important influence on voltage, and the similarity comparison will be more biased towards the matching temperature; the opposite is also true. The relative temperature deviation DT and the relative irradiance deviation DI are calculated separately, where DT = |AT - YT| / AT and DI = |AI - YI| / AI; and the similarity score GS between the first future time period and the sample time period is calculated, where GS = TQ × DT + IQ × ​​DI; DT and DI convert the difference into a relative difference to eliminate the bias caused by the absolute scale. The similarity scores between the first future time period and all time periods in the reference date are repeatedly obtained, and the minimum similarity score of k3% is taken. The corresponding time period is recorded as the reference time period of the first future time period and marked as the reference time period information of the first future time period, where k3% is a set percentage; in this embodiment, k3%=8%, which can be set flexibly. In practice, GS combines the relative deviations of temperature and irradiance into a single similarity score based on weights. The smaller the GS value, the closer the historical period is to the first future period in terms of both temperature and irradiance. Through GS, similar historical periods can be uniformly sorted and selected under the conditions of temperature and irradiance, i.e., reference periods.

[0023] The voltage analysis module analyzes the input range based on the reference time period information and the input voltage sample data of the reference time period to obtain wide voltage input range information; The voltage analysis module is configured with a voltage analysis strategy, which includes: for the input voltage information of each reference time period in the first future time period, outliers corresponding to each input voltage information are removed using the 3σ principle, that is, the average value P0 and standard deviation B0 of the input voltage information in each reference time period are calculated, and those not located in [P0-3×B0, P0+3×B0] are regarded as outliers and removed; the remaining input voltage information in each reference time period is merged and recorded as the first voltage set; outliers in each reference time period are removed first to avoid these outliers affecting subsequent calculations; Calculate the average value PU and standard deviation BU of the first voltage set. Calculate PU-k4×BU and PU+k4×BU, which are denoted as the initial lower limit XU and the initial upper limit SU, respectively. Here, k4 is a set scaling factor. In this embodiment, k4=3, which can be flexibly set. The average value PU and standard deviation BU are estimates of the center and dispersion of the future input voltage distribution. For example, if PU=320.0V, BU=3.0V, and k4=3, then the initial lower limit XU=320-9=311V and the initial upper limit SU=320+9=329V.

[0024] Calculate the mean values ​​of irradiance IM (IPM) and temperature sensitivity TM (TPM) for all reference periods; calculate the mean values ​​of average irradiance (HI) and average temperature (HT) for all reference periods. Calculate AT-HT and AI-HI, denoted as temperature difference RT and illuminance difference RI, respectively; and calculate temperature correction WT and illuminance correction WI, where WT=RT×TPM and WI=RI×IPM; and denote WT+WI as the total correction WTI. Calculate the lower limit XEU and the upper limit SEU, and record them as the wide voltage input range information for the first future time period, where XEU=XU+WTI and SEU=SU+WTI; For example, IPM=0.0002, TPM=-0.25, HT=25.0℃, HI=550 W / m2, AT=27.0℃, AI=600W / m 2 Therefore, RT = 27 - 25 = 2.0℃, RI = 600 - 550 = 50 W / m 2 ;WT=RT×TPM=2.0×(-0.25)=-0.50V; WI=RI×IPM=50×0.0002=0.010V; WTI=WT+WI=-0.50 +0.01=-0.49V; XU=311V, SU=329V, then XEU=311-0.49=310.51V, SEU=329-0.49=328.51V; In practice, IPM and TPM are used to convert weather forecast deviations into voltage corrections; HI and HT are the average weather levels for the reference period, serving as benchmarks for comparison with the predicted AI and AT.

[0025] The range adjustment module adaptively adjusts the wide voltage input range of the photovoltaic inverter based on wide voltage input range information; The range adjustment module is configured with a module adjustment strategy, which includes: based on the lower limit XEU and the upper limit SEU, [k5×XEU, k6×SEU] is recorded as the pre-adjusted voltage range, and the wide voltage input range of the first inverter is adjusted to the pre-adjusted voltage range in the first future time period, where k5 and k6 are set proportional coefficients, k5<1, k6>1; in this embodiment, k5=0.9, k6=1.1, which can be flexibly set according to the actual application scenario. k5 and k6 are used to appropriately widen the lower limit and upper limit to avoid the photovoltaic inverter from operating at the edge of the upper or lower limit for a long time, so as to ensure equipment safety. The wide voltage input range of the first inverter in the next time period is adjusted sequentially and repeatedly. In practice, the wide voltage input range for multiple future time periods can be obtained simultaneously based on the actual application scenario, and then adjusted sequentially.

[0026] Example 2, please refer to Figure 2As shown, this application provides a wide voltage input range adaptive adjustment method for photovoltaic inverters, including the following steps: Step S1 involves collecting the voltage output from the photovoltaic modules to the photovoltaic inverter for each time period, and acquiring the average temperature and average irradiance for each time period to obtain input voltage sample data and relevant weather sample data. Step S1 includes the following sub-steps: Step S101: For any type of photovoltaic inverter, denoted as the first inverter, the photovoltaic module connected to the first inverter is denoted as the first photovoltaic module, and the voltage output by the first photovoltaic module to the first inverter is denoted as the input voltage of the first inverter. Step S102: Divide the normal operating time of the first inverter into multiple time periods of duration T0, denoted as time periods, and denot any one of these time periods as the first time period; where T0 is the set duration.

[0027] Step S103: In the first time period, the input voltage of the first inverter is collected at a first time interval and recorded as the input voltage information of the first time period; the input voltage information of each time period is collected repeatedly every day and sorted by date and recorded as input voltage sample data, wherein the first time interval is t1; Step S104: In the first time period, the average temperature of the environment where the first photovoltaic module is located is collected, and the average irradiance of the environment where the first photovoltaic module is located is collected in the first time period, and recorded as the relevant weather information for the first time period; the relevant weather information for each time period is collected repeatedly every day, and sorted by date, and recorded as relevant weather sample data.

[0028] Step S2 involves performing time-period similarity analysis based on relevant weather sample data to filter reference time periods and obtain reference time period information. Step S2 includes the following sub-steps: Step S201: The next time period after the current time period is designated as the first future time period. The average temperature and average irradiance of the predicted first future time period are obtained and designated as AT and AI in order. The k1 dates closest to the date of the first future time period are designated as reference dates. Here, k1 is the number of reference dates. Step S202: For the average irradiance, set multiple continuous irradiance intervals with a width of k2, and allocate all time periods of all reference dates to each irradiance interval according to the average irradiance; denot any one of the irradiance intervals as the first interval; where k2 is the set interval size.

[0029] Step S203: Obtain the average irradiance of the time period located in the first interval, denoted as the first average irradiance set; obtain the absolute difference between the maximum and minimum values ​​in the first average irradiance set, denoted as the irradiance range IC; obtain the average of the average irradiance of all time periods in all reference dates, denoted as the time period irradiance mean PI. Step S204: Based on the input voltage sample data, calculate the average input voltage of the input voltage information for each time period in each reference date, and calculate the average value of the average input voltage for all time periods, denoted as the average voltage PV for each time period; Step S205, and obtain the average input voltage of the time period in the first interval, denoted as the first average voltage set, and obtain the absolute difference between the maximum and minimum values ​​in the first average voltage set, denoted as the voltage range VC; Step S206: Calculate (IC / PI) / (VC / PV), and record it as the irradiance sensitivity coefficient corresponding to the first interval. Repeatedly obtain the average value of the irradiance sensitivity coefficients corresponding to all irradiance intervals, and record it as the sensitivity corresponding to the average irradiance, labeled as irradiance sensitivity IM; Repeatedly obtain the sensitivity corresponding to the average temperature, labeled as temperature sensitivity TM.

[0030] Step S207: Calculate TM / (IM+TM) and IM / (IM+TM) respectively, and record them as temperature weight TQ and irradiance weight IQ in order; record any time period in the reference date as the sample time period; record the average temperature and average irradiance of the sample time period as YT and YI in order. Step S208: Calculate the relative temperature deviation DT and the relative irradiance deviation DI, where DT = |AT - YT| / AT and DI = |AI - YI| / AI; and calculate the similarity score GS between the first future time period and the sample time period, where GS = TQ × DT + IQ × ​​DI. Step S209: Repeatedly obtain the similarity scores of all time periods in the first future time period and the reference date, and take the smallest k3% similarity score. Record the corresponding time period as the reference time period of the first future time period and mark it as the reference time period information of the first future time period, where k3% is the set percentage.

[0031] Step S3: Based on the reference time period information, perform input range analysis using the input voltage sample data of the reference time period to obtain wide voltage input range information; Step S3 includes the following sub-steps: Step S301: For the input voltage information of each reference time period in the first future time period, the outlier value corresponding to each input voltage information is removed by using the 3σ principle, and the remaining input voltage information of each reference time period is merged and recorded as the first voltage set. Step S302: Calculate the average value PU and standard deviation BU of the first voltage set, and calculate PU-k4×BU and PU+k4×BU, which are denoted as the initial lower limit XU and the initial upper limit SU, respectively, where k4 is the set scaling factor.

[0032] Step S303: Calculate the mean value of irradiance IM (IPM) and the mean value of temperature sensitivity TM (TPM) for all reference periods; calculate the mean value of average irradiance (HI) and the mean value of average temperature (HT) for all reference periods. Step S304: Calculate AT-HT and AI-HI, denoted as temperature difference RT and illuminance difference RI, respectively; and calculate temperature correction amount WT and illuminance correction amount WI, where WT=RT×TPM and WI=RI×IPM; and WT+WI is denoted as total correction amount WTI. Step S305: Calculate the lower limit XEU and the upper limit SEU, and record them as the wide voltage input range information for the first future time period, where XEU=XU+WTI and SEU=SU+WTI.

[0033] Step S4: Adaptively adjust the wide voltage input range of the photovoltaic inverter based on the wide voltage input range information; Step S4 includes the following sub-steps: Step S401: Based on the lower limit XEU and the upper limit SEU, [k5×XEU, k6×SEU] is recorded as the pre-adjusted voltage range, and the wide voltage input range of the first inverter is adjusted to the pre-adjusted voltage range in the first future time period, where k5 and k6 are set proportional coefficients, k5<1, k6>1; Step S402: Repeat the adjustment of the wide voltage input range of the first inverter for the next time period of the current time period.

[0034] Example 3, please refer to Figure 4 As shown, Figure 4 A schematic diagram of an electronic device is provided, which may include a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The memory stores computer-readable instructions, and the processor can call these instructions. When the processor executes a computer-readable instruction, it performs steps such as those in the adaptive adjustment method for a wide voltage input range of a photovoltaic inverter to achieve the following functions: collecting the voltage output from the photovoltaic modules to the photovoltaic inverter for each time period, and collecting the average temperature and average irradiance for each time period to obtain input voltage sample data and relevant weather sample data; performing time period similarity analysis based on the relevant weather sample data to filter reference time periods and obtain reference time period information; performing input range analysis using the input voltage sample data of the reference time periods based on the reference time period information to obtain wide voltage input range information; and adaptively adjusting the wide voltage input range of the photovoltaic inverter according to the wide voltage input range information.

[0035] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0036] Example 4: This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program performs steps such as those in the photovoltaic inverter wide voltage input range adaptive adjustment method to achieve the following functions: collecting the voltage output from the photovoltaic module to the photovoltaic inverter for each time period, and collecting the average temperature and average irradiance for each time period to obtain input voltage sample data and related weather sample data; performing time period similarity analysis based on the related weather sample data to filter reference time periods and obtain reference time period information; performing input range analysis using the input voltage sample data of the reference time periods based on the reference time period information to obtain wide voltage input range information; and adaptively adjusting the wide voltage input range of the photovoltaic inverter according to the wide voltage input range information.

[0037] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0038] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0039] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for adaptive adjustment of a photovoltaic inverter with a wide voltage input range, characterized in that, Includes the following steps: The voltage output from the photovoltaic modules to the photovoltaic inverter is collected for each time period, and the average temperature and average irradiance for each time period are collected to obtain input voltage sample data and relevant weather sample data. Based on relevant weather sample data, time period similarity analysis is performed to filter reference time periods and obtain reference time period information; Based on the reference time period information, the input range analysis is performed using the input voltage sample data of the reference time period to obtain wide voltage input range information; The wide voltage input range of the photovoltaic inverter is adaptively adjusted based on the wide voltage input range information. Based on relevant weather sample data, a time-period similarity analysis is performed to filter reference time periods. The reference time period information includes the following sub-steps: The next time period after the current time period is designated as the first future time period. The average temperature and average irradiance of the predicted first future time period are obtained and designated as AT and AI in order. The k1 dates closest to the date of the first future time period are designated as reference dates, where k1 is the number of reference dates. For the average irradiance, multiple continuous irradiance intervals with a width of k2 are set, and all time periods of all reference dates are assigned to each irradiance interval according to the average irradiance; any irradiance interval is denoted as the first interval. Where k2 is the set interval size; Obtain the average irradiance of the time period located in the first interval, denoted as the first average irradiance set; obtain the absolute difference between the maximum and minimum values ​​in the first average irradiance set, denoted as the irradiance range IC. The average irradiance for all time periods across all reference dates is obtained and denoted as the time period mean irradiance PI. Based on the input voltage sample data, calculate the average input voltage of the input voltage information for each time period in each reference date, and calculate the average value of the average input voltage for all time periods, denoted as the time period voltage mean PV; And obtain the average input voltage of the first interval, denoted as the first average voltage set, and obtain the absolute difference between the maximum and minimum values ​​in the first average voltage set, denoted as the voltage range VC; Calculate (IC / PI) / (VC / PV), and denote it as the irradiance sensitivity coefficient corresponding to the first interval. Repeatedly obtain the average value of the irradiance sensitivity coefficients corresponding to all irradiance intervals, and denote it as the sensitivity corresponding to the average irradiance, labeled as irradiance sensitivity IM; repeatedly obtain the sensitivity corresponding to the average temperature, and label it as temperature sensitivity TM. Calculate TM / (IM+TM) and IM / (IM+TM) respectively, and denote them as temperature weight TQ and irradiance weight IQ in order; denote any time period in the reference date as the sample time period; denote the average temperature and average irradiance of the sample time period as YT and YI in order; Calculate the relative temperature deviation DT and the relative irradiance deviation DI, respectively, where DT = |AT - YT| / AT and DI = |AI - YI| / AI; and calculate the similarity score GS between the first future time period and the sample time period, where GS = TQ × DT + IQ × ​​DI; Repeatedly obtain the similarity scores between the first future time period and all time periods in the reference date, and take the smallest k3% similarity score. Record the corresponding time period as the reference time period of the first future time period, and mark it as the reference time period information of the first future time period, where k3% is the set percentage.

2. Based on reference time period information, input range analysis is performed using input voltage sample data from the reference time period to obtain wide voltage input range information, including the following sub-steps: For the input voltage information of each reference time period in the first future time period, the outliers corresponding to each input voltage information are removed by using the 3σ principle, and the remaining input voltage information of each reference time period is merged and denoted as the first voltage set. Calculate the average value PU and standard deviation BU of the first voltage set, and calculate PU-k4×BU and PU+k4×BU, which are denoted as the initial lower limit XU and the initial upper limit SU, respectively, where k4 is the set scaling factor; Calculate the mean values ​​of irradiance IM (IPM) and temperature sensitivity TM (TPM) for all reference periods; calculate the mean values ​​of average irradiance (HI) and average temperature (HT) for all reference periods. Calculate AT-HT and AI-HI, denoted as temperature difference RT and illuminance difference RI, respectively; and calculate temperature correction WT and illuminance correction WI, where WT=RT×TPM and WI=RI×IPM; and denote WT+WI as the total correction WTI. Calculate the lower limit XEU and the upper limit SEU, and record them as the wide voltage input range information for the first future time period, where XEU = XU + WTI and SEU = SU + WTI.

3. The adaptive adjustment method for a wide voltage input range photovoltaic inverter according to claim 1, characterized in that, Collect the voltage output from the photovoltaic modules to the photovoltaic inverter for each time period, and collect the average temperature and average irradiance for each time period to obtain input voltage sample data and relevant weather sample data, including the following sub-steps: For any type of photovoltaic inverter, denoted as the first inverter, the photovoltaic module connected to the first inverter is denoted as the first photovoltaic module, and the voltage output by the first photovoltaic module to the first inverter is denoted as the input voltage of the first inverter. The normal operating time of the first inverter is divided into multiple time periods of duration T0, denoted as time periods, and any one of these time periods is designated as the first time period; where T0 is the set duration.

4. The adaptive adjustment method for a wide voltage input range photovoltaic inverter according to claim 2, characterized in that, Collect the voltage output from the photovoltaic modules to the photovoltaic inverter for each time period, and collect the average temperature and average irradiance for each time period to obtain input voltage sample data and relevant weather sample data, including the following sub-steps: In the first time period, the input voltage of the first inverter is collected at the first time interval and recorded as the input voltage information of the first time period; the input voltage information of each time period is collected repeatedly every day and sorted by date and recorded as input voltage sample data, where the first time interval is t1; In the first time period, the average temperature of the environment where the first photovoltaic module is located is collected, and the average irradiance of the environment where the first photovoltaic module is located is collected in the first time period. These are recorded as the relevant weather information for the first time period. The relevant weather information for each time period is collected repeatedly every day and sorted by date, and recorded as the relevant weather sample data.

5. The adaptive adjustment method for a wide voltage input range photovoltaic inverter according to claim 3, characterized in that, Adaptive adjustment of the wide voltage input range of the photovoltaic inverter based on wide voltage input range information includes the following sub-steps: Based on the lower limit XEU and the upper limit SEU, [k5×XEU, k6×SEU] is denoted as the pre-adjusted voltage range, and the wide voltage input range of the first inverter is adjusted to the pre-adjusted voltage range in the first future time period, where k5 and k6 are set proportional coefficients, k5<1, k6>1; The wide voltage input range of the first inverter in the next time period is adjusted in sequence.

6. A photovoltaic inverter wide voltage input range adaptive adjustment system, applicable to the photovoltaic inverter wide voltage input range adaptive adjustment method according to any one of claims 1-4, characterized in that, It includes a sample collection module, a time period screening module, a voltage analysis module, and a range adjustment module; The sample collection module includes a voltage acquisition unit and a weather acquisition unit. The voltage acquisition unit is used to collect the voltage output by the photovoltaic module to the photovoltaic inverter at each time period to obtain input voltage sample data. The weather acquisition unit is used to collect the average temperature and average irradiance at each time period to obtain relevant weather sample data. The time period filtering module performs time period similarity analysis based on relevant weather sample data, filters reference time periods, and obtains reference time period information; The voltage analysis module performs input range analysis based on reference time period information and uses input voltage sample data from the reference time period to obtain wide voltage input range information; The range adjustment module adaptively adjusts the wide voltage input range of the photovoltaic inverter based on the wide voltage input range information.

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