CN113742326B - Power optimizer and power missing value filling method and device thereof - Google Patents
Power optimizer and power missing value filling method and device thereof Download PDFInfo
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Abstract
The invention discloses a power optimizer and a power missing value filling method and device thereof. The method comprises the following steps: acquiring historical irradiation data and historical power data; performing curve fitting based on the historical irradiation data and the historical power data, and determining a power fitting function; acquiring the actually measured irradiation data of a power missing target point of the power optimizer and the power missing target point; and determining a power filling value of the power-missing target point according to the power fitting function and the actually measured irradiation data, and filling the power data of the power-missing target point according to the power filling value. According to the method, the fitting function of the power and the irradiation is established, the power filling value is calculated according to the irradiation data, the power missing data is effectively filled, and the integrity and the accuracy of the power data are improved.
Description
Technical Field
The invention relates to the technical field of power optimization of photovoltaic systems, in particular to a power optimizer and a power missing value filling method and device thereof.
Background
In the distributed photovoltaic system, mismatch of the photovoltaic modules can affect the generated energy, so that a power optimizer needs to be configured to be connected with the photovoltaic modules in series, the maximum power point of the photovoltaic modules is tracked in real time, and the maximum power output and on-line monitoring of the single modules are realized.
Under normal operation condition, the measured data of the photovoltaic module is recorded through the power optimizer, the interval time of the measured data is usually 5 minutes, when the power optimizer is on line again after off line, the phenomenon of power measured data deficiency exists, the power data of the photovoltaic module during off line needs to be supplemented, however, the time interval of supplementing the data is long, for example, the measured data with the interval time of 30 minutes can only be supplemented, the requirement of follow-up power optimization and monitoring cannot be met, and therefore, the deficiency data in the supplementing data needs to be filled.
In the prior art, a common missing data filling method includes: searching a history similar scene through history data, and filling with information auxiliary missing values of the history similar scene; or, adopting historical data to establish a time sequence model, and carrying out interpolation filling based on the time sequence model.
When the existing missing data padding method is applied to a power optimizer, the following problems exist: because the photovoltaic system is greatly influenced by environmental factors, the construction of similar scenes or time sequence models by adopting historical power data can lead to the loss of random fluctuation information of power, namely random fluctuation cannot be reproduced when high-similarity characteristic auxiliary interpolation is not available, and the loss of data at a certain moment represents the loss of random fluctuation information at that moment, so that the filling of data is inaccurate.
Disclosure of Invention
The invention provides a power optimizer and a power missing value filling method and device thereof, which are used for calculating a power filling value through irradiation data with random fluctuation characteristics and filling the power missing data effectively according to the power filling value.
In a first aspect, an embodiment of the present invention provides a power missing value filling method for a power optimizer, where the method includes:
acquiring historical irradiation data and historical power data;
performing curve fitting based on the historical irradiation data and the historical power data, and determining a power fitting function;
acquiring the actually measured irradiation data of a power missing target point of the power optimizer and the power missing target point;
and determining a power filling value of the power-missing target point according to the power fitting function and the actually measured irradiation data, and filling the power data of the power-missing target point according to the power filling value.
In a second aspect, an embodiment of the present invention further provides a power missing value filling apparatus for a power optimizer, including:
the data sampling unit is used for acquiring historical irradiation data and historical power data;
the curve fitting unit is used for performing curve fitting based on the historical irradiation data and the historical power data to determine a power fitting function;
the missing value detection unit is used for acquiring a power missing target point of the power optimizer and actually measured irradiation data of the power missing target point;
the missing value filling unit is used for determining a power filling value of the power missing target point according to the power fitting function and the actually measured irradiation data, and filling the power data of the power missing target point according to the power filling value.
In a third aspect, an embodiment of the present invention further provides a power optimizer, including a power deficiency value filling device for the power optimizer.
The power optimizer and the power missing value filling device provided by the embodiment of the invention execute the power missing value filling method, the method carries out curve fitting through the historical irradiation data and the historical power data, determines the power fitting function, calculates the power filling value of the power missing target point according to the power fitting function and the actually measured irradiation data, and fills the power data of the power missing target point, thereby solving the problem of actually measured power data missing caused by restarting the power optimizer, realizing effective filling of the power missing data according to the irradiation calculation of the power filling value, retaining the random fluctuation characteristic of the filling data, having simple operation and low cost and being beneficial to improving the integrity and the accuracy of the power data.
Drawings
FIG. 1 is a flowchart of a power deficiency value filling method for a power optimizer according to a first embodiment of the present invention;
FIG. 2 is a flow chart of a power-missing-value filling method for a power optimizer according to a second embodiment of the present invention;
FIG. 3 is a flowchart of a power missing value filling method for a power optimizer according to a third embodiment of the present invention;
FIG. 4 is a flowchart of a power deficiency value filling method for a power optimizer according to a fourth embodiment of the present invention;
FIG. 5 is a flowchart of another power deficiency value filling method for a power optimizer according to a fourth embodiment of the present invention;
FIG. 6 is a flowchart of another power deficiency value filling method for a power optimizer according to a fourth embodiment of the present invention;
fig. 7 is a schematic structural diagram of a power-missing-value filling device for a power optimizer according to a fifth embodiment of the present invention;
fig. 8 is a schematic structural diagram of a power optimizer according to a sixth embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Fig. 1 is a flowchart of a power-missing-value filling method for a power optimizer, which is applicable to an application scenario in which power interpolation is assisted by sampling parameters highly related to output power of a photovoltaic module, where the parameters highly related to output power of the photovoltaic module typically include irradiance of the photovoltaic module, and the method may be performed by a power-missing-value filling device in the embodiment of the present invention, and the device may be implemented by software and/or a functional module, and the method specifically includes the following steps:
s110, acquiring historical irradiation data and historical power data.
The historical irradiation data can comprise solar irradiance of the photovoltaic module obtained through actual measurement under the normal operation working condition of the power optimizer, and the historical irradiation data are related to parameters such as movement of a cloud layer, thickness change of the cloud layer, solar angle change, solar intensity change and the like. The historical power data can comprise any one of the output power of the photovoltaic module, the input power of the power optimizer or the output power of the power optimizer, which are obtained through actual measurement under the normal operation condition of the power optimizer, and the historical power data and the historical irradiation data are in one-to-one correspondence, namely, each historical irradiation data corresponds to one historical power data under the normal operation condition of the power optimizer.
In this step, a local server or a cloud server may be used to store the historical irradiation data and the historical power data, which is not limited.
Typically, the time interval between adjacent two historical irradiance data and the time interval between adjacent two historical power data may each be 5 minutes.
S120, performing curve fitting based on the historical irradiation data and the historical power data, and determining a power fitting function.
The curve fitting is to select proper curve types to fit the historical irradiation data and the historical power data, and a function corresponding to each fitted curve is the power fitting function.
In this step, the irradiation can be used as an independent variable of the power fitting function, and the power can be used as an independent variable of the power fitting function, so that the power value can be calculated by substituting the irradiation value into the power fitting function.
S130, acquiring actual measurement irradiation data of a power missing target point of the power optimizer and the power missing target point.
The power missing target point of the power optimizer refers to a sampling point with power data missing, and the sampling point can be set according to actual needs, which is not limited. The measured irradiation data of the power-missing target point refers to the measured irradiation data of the power-missing target point of the power optimizer.
In this step, the power loss target point may be a power data sampling point missing between two adjacent measured power data during the power-on restart or sampling process of the power optimizer, and the measured irradiation data of each sampling point may be obtained by the irradiation detection device.
For example, taking a theoretical time interval of historical power data in the power optimizer as 5 minutes, and a time interval of restarting two adjacent measured power data of the complementary transmission as 30 minutes as an example, if a power failure occurs in the power optimizer between 11:00 and 12:00, and irradiation data is continuously detected during the power failure of the power optimizer, after the power optimizer is powered on and restarted, the power optimizer can only actually obtain the measured power data and the measured irradiation data at three time points of 11:00, 11:30 and 12:00, and then sampling points of the power data corresponding to 11:05, 11:10, 11:15, 11:20, 11:25, 11:35, 11:40, 11:45, 11:50 and 11:55 are power loss target points of the power optimizer, and irradiance of sunlight of the photovoltaic module detected by each power loss target point is the measured irradiation data of the power loss target point.
And S140, determining a power filling value of the power-missing target point according to the power fitting function and the actually measured irradiation data, and filling the power data of the power-missing target point according to the power filling value.
The independent variable of the power fitting function is actually measured irradiation data, the dependent variable of the power fitting function is a power filling value, namely, actually measured irradiation data of any power-missing target point can be substituted into the power fitting function, the power filling value of the power-missing target point is calculated, and the power filling value is used for replacing the power data missing from the corresponding target point.
Specifically, the irradiation and power detection equipment can be used for acquiring the historical irradiation data and the historical power data corresponding to each historical irradiation data during the normal operation of the power optimizer and the photovoltaic module, and the functional relationship between the historical irradiation data and the historical power data, namely the power fitting function, is established through a curve fitting method.
After the power optimizer obtains the power data of the complementary transmission, the power optimizer analyzes the data sampling points based on the actually measured power data of the complementary transmission to obtain at least one power-missing target point, reads actually measured irradiation data of each power-missing target point, substitutes the actually measured irradiation data into a power fitting function, fills the power filling value of the power-missing target point into the power data part of the power-missing target point, and fills the power filling value into the power data part of the power-missing target point to fill the power data missing of the sampling points.
According to the power missing value filling method for the power optimizer, provided by the embodiment of the invention, the historical solar irradiation data and the historical power data of the power optimizer are obtained, the historical irradiation data and the historical power data are subjected to curve fitting to determine the power fitting function, the power missing target point of the power optimizer and the actually measured irradiation data of the power missing target point are obtained, the power filling value of the power missing target point is determined, the power data of the power missing target point is filled, the effective filling of the power missing data is realized, the random fluctuation characteristic of the filling data is reserved, the operation is simple, the cost is low, and the improvement of the integrity and the accuracy of the power data is facilitated.
Optionally, before performing curve fitting based on the historical irradiance data and the historical power data, the power deficiency value filling method further comprises: and performing data cleaning on the historical irradiation data and the historical power data.
Specifically, data cleansing includes screening and deleting outliers and missing values in the historical irradiance data and the historical power data. If abnormal values or missing values exist in the historical irradiation data or the historical power data, deleting a group of historical irradiation data and the historical power data corresponding to the abnormal values or the missing values at the same time, and guaranteeing the consistency of the data.
Illustratively, if the acquired historical irradiance data is negative, it is indicative that the acquired historical irradiance data is outliers, which need to be purged. Normally, the obtained historical power data is the historical power data with an interval of 5 minutes, and if the obtained historical power data is 30 minutes, the obtained historical power data is a missing value and needs to be cleared. By cleaning the data, unnecessary data can be cleaned, and the accuracy and precision of curve fitting of the historical irradiation data and the historical power data can be increased.
Example two
Fig. 2 is a flowchart of a power deficiency value filling method for a power optimizer according to a second embodiment of the present invention, where a specific implementation of curve fitting is shown on the basis of fig. 1 by way of example, and not by way of limitation.
Referring to fig. 2, the step S120 specifically includes the following steps:
s210, determining a curve inflection point of an irradiation power curve according to the historical irradiation data and the historical power data.
The irradiation power curve refers to a function curve for reflecting one-to-one correspondence between historical irradiation data and historical power data, and the historical data has random characteristics, so that different function correspondence can exist in the irradiation power curve at different times, and concave-convex demarcation points of the function curve are curve inflection points.
In this step, the inflection point of the curve can be obtained by identifying the curvature change point of the irradiation power curve through an image analysis technology, or can be obtained by calculating the derivative of the curve at each characteristic point, which is not limited.
For example, a rectangular planar coordinate system may be established, in which the X-axis represents the historical irradiation data and the Y-axis represents the historical power data, points are traced on the coordinate system according to the obtained historical irradiation data and the historical power data, all the traced points are connected, and a curve inflection point is determined according to an irradiation power curve obtained by the connection.
S220, carrying out data segmentation on the historical irradiation data and the historical power data according to curve inflection points to obtain at least one sample interval.
The sample interval is a sample point set of historical irradiation data and historical power data with the same function corresponding relation after data segmentation.
For example, the historical irradiation data and the historical power data may be data segmented according to the number of inflection points, each segment corresponding to one sample interval. For example, if the irradiation power curve has a curve inflection point at a sample point where the historical irradiation data is 200, dividing the data of the historical irradiation data and the historical power data into two sections, wherein the historical irradiation data and the historical power data in the historical irradiation data [0,200) correspond to a sample section; in the historical irradiation data 200, ++ infinity) and history the power data corresponds to another sample interval.
S230, performing polynomial curve fitting on historical irradiation data and historical power data segments in at least one sample interval to obtain at least one segmented power fitting function, wherein the at least one segmented power fitting function corresponds to the at least one sample interval one by one.
The piecewise power fitting function is used for representing the functional correspondence of the power y with respect to the irradiation x in the same sample interval.
Specifically, polynomial curve fitting is carried out on historical irradiation data and historical power data segments in any sample interval, each segment of polynomial curve fitting corresponds to a segment power fitting function, and the segment power fitting functions correspond to the sample intervals one by one.
Alternatively, the piecewise power fitting function may comprise a linear fitting function and/or a binomial curve fitting function.
Specifically, each sample interval corresponds to a fitting function, and the fitting function may be a linear fitting function or a binomial curve fitting function, and the type of the fitting function may be selected according to the curve characteristics of the sample points in the sample interval, so as to fit the historical irradiation data and the historical power data in the sample interval, which is not limited. And finally obtaining a set of all the segmented power fitting functions, namely the power fitting functions which are finally used for data filling.
Illustratively, taking an example that a curve inflection point exists at a sample point with the historical irradiation data of 200 in the irradiation power curve, combining curve characteristics obtained by plotting points, a binomial curve fitting function can be adopted for fitting in the historical irradiation data [0,200), so as to obtain a first piecewise power fitting functionIn the historical irradiation data 200, in +++). The fitting may be performed using a linear fitting function, obtaining a second piecewise power fitting function +.>Where x represents irradiance and y represents power.
According to the power missing value filling method for the power optimizer, historical irradiation data and historical power data are obtained, the curve inflection point of an irradiation power curve is determined, data segmentation is carried out according to the curve inflection point, a sample interval is obtained, polynomial curve fitting is carried out on the historical irradiation data and the historical power data in the sample interval, and a segmented power fitting function is obtained. By means of the data segmentation fitting method, the power fitting precision is improved, and the effective filling of the power missing data is achieved.
Example III
Optionally, fig. 3 is a flowchart of a power deficiency value filling method for a power optimizer according to a third embodiment of the present invention, where, based on the foregoing embodiments, a specific implementation manner of obtaining a power deficiency target point and measured irradiation data of the power deficiency target point is shown by way of example, and not limitation of the method.
Referring to fig. 3, the step S130 specifically includes the following steps:
s310, obtaining actual measurement power data recorded by a power optimizer.
The measured power data recorded by the power optimizer may be power data obtained by sampling the power detection device in a specific period (for example, a power-down period of the power optimizer) and uploaded to the power optimizer.
S320, judging whether the interval time between two adjacent measured power data is larger than a preset time threshold.
The preset time threshold can be set according to a theoretical time interval between historical power data obtained through actual measurement under a normal operation condition of the power optimizer, and specific values of the preset time threshold are not limited.
If the interval time between two adjacent measured power data is greater than the preset time threshold, determining that there is a data loss between the two adjacent measured power data, and executing step S330; otherwise, the process returns to step S310.
S330, determining a power loss target point according to the interval time between two adjacent actually measured power data.
In this step, the interval time between two adjacent measured power data may be divided into points according to a preset time threshold, so as to obtain a power loss target point.
For example, if the theoretical time interval between the historical power data obtained by actually measuring under the normal operating condition of the power optimizer is defined to be 5 minutes, the preset time threshold may be set to be 5 minutes, the interval time between the two adjacent actual power data recorded by the power optimizer after the power optimizer is powered off and restarted is 30 minutes, the interval time between the two adjacent actual power data is greater than the preset time threshold, and one power loss target point may be set every interval preset time threshold (for example, 5 minutes) within the interval time (for example, 30 minutes) between the two actual power data.
S340, inquiring the historical irradiation data according to the power-missing target point, and determining the actual measurement irradiation data of the power-missing target point.
In this step, the historical irradiation data may be the irradiance of sunlight detected by the irradiation detection apparatus at the present time, or may be the irradiance of sunlight detected by the irradiation detection apparatus in the past year or in a time period having the same irradiation intensity, without limitation.
For example, taking a preset time threshold of 5 minutes, taking actually obtained power data of two adjacent actual measurement power data of 11:00 and 11:30 as an example, the interval time of the two adjacent actual measurement power data is 30 minutes, and the power data of 11:05, 11:10, 11:15, 11:20 and 11:25 are power missing target points if the interval time of the two adjacent actual measurement power data is greater than the preset time threshold of 5 minutes, and inquiring the history irradiation data at the same time, for example, the history irradiation data at the same time of the last week or the history irradiation data at the same time of the last month of the last year, and determining the actual measurement irradiation data corresponding to the power missing target points according to the obtained history irradiation data.
Therefore, the power missing value filling method for the power optimizer establishes the power missing target point between two adjacent actually measured power data through the preset time threshold, and determines actually measured irradiation data of the power missing target point through inquiring historical irradiation data, so that effective filling of the actually measured data is realized.
Example IV
Optionally, fig. 4 is a flowchart of a power-missing value filling method for a power optimizer according to a fourth embodiment of the present invention, where the method steps for performing threshold correction on the power-missing value are further added on the basis of the above embodiments.
Referring to fig. 4, after determining the power filling value of the power-loss target point according to the power fitting function and the measured irradiation data, the method further includes the steps of:
s401, determining a power difference threshold according to historical power data, wherein the power difference threshold comprises an upper power difference threshold and a lower power difference threshold.
The power difference threshold is a section of value, is used for correcting the power filling value, can be calculated according to the history power data obtained through actual measurement under the normal operation working condition of the power optimizer, wherein the smallest value in the power difference threshold is a lower limit power difference threshold, the largest value is an upper limit power difference threshold, and the specific value is not limited.
S402, acquiring the previous measured power data and the next measured power data adjacent to the power filling value.
The measured power data are sampled by the power detection device and uploaded to the power optimizer, and the former measured power data and the latter measured power data represent the former measured power data and the latter measured power data adjacent to the power filling value.
For example, taking the case that power values of the power data of the times 11:05, 11:10, 11:15, 11:20 and 11:25 need to be filled, the previous measured power data adjacent to the power filling value is the power data of the time 11:00, for example, 9.9, and the next measured power data is the power data of the time 11:30, for example, 110.
S403, correcting the power filling value according to the previous measured power data, the next measured power data and the power difference threshold value.
Specifically, after the power filling value is obtained through fitting function calculation, the upper limit threshold and the lower limit threshold of the power difference are calculated through historical power data, the previous actual measurement power data and the next actual measurement power data which are adjacent to the power filling value are obtained, whether the fitted power filling value is an available value or not is judged according to the previous actual measurement power data and the next actual measurement power data, if the power filling value is an unavailable value, a corrected filling value is calculated according to the previous actual measurement power data and the next actual measurement power data to replace the unavailable power filling value, fitting data correction is achieved, and data improvement is achieved.
Alternatively, fig. 5 is a flowchart of another power-missing-value filling method for a power optimizer according to the fourth embodiment of the present invention, and fig. 5 illustrates, on the basis of fig. 4, a method for obtaining a power difference threshold, which is not limited to this method.
Referring to fig. 5, determining a power difference threshold according to historical power data specifically includes the following steps:
s4011, a target time period to which the power loss target point belongs is acquired.
Wherein the target time period is a time range having similar irradiation characteristics to the power-deficient target point, and typically, the duration of the target time period may be three days, one week or one month, and the specific data range thereof is not limited.
Illustratively, taking the example that the power loss target point is the power data sampling point lost between the 2021 month 7 and 30 day time 11:00 and 11:30, the power data sampling points at the 2021 month 7 and 30 day time 11:05, 11:10, 11:15, 11:20 and 11:25 are the power loss target points, and the target time period may be a time period of 11:00-12:00 each day between the 2020 month 7 and 28 to the 2020 month 8 and 3 days, and the target time period lasts for 7 days; alternatively, the target time period may also be a period of 11:00-12:00 a day between day 23 of year 2021, 7, and month 29 of year 2021, which lasts for 7 days.
S4012, a power difference sequence is established according to the power difference between two adjacent historical power data in the target time period.
Wherein, the theoretical time interval between two adjacent historical power data in the target time period is 5 minutes.
Taking 11:00-12:00 of the target time period of 2021, 7, 23, and 29 as an example, all the historical power data of 11:00-12:00 of each day in the target time period are obtained, power difference values between two adjacent historical power data in the daily data are sequentially calculated, all the power difference values in the target time period are sequentially ordered, and a power difference value sequence is established.
S4013, calculating an average value and a standard deviation value of the power difference value sequence.
The average value refers to the average value of all power differences in the target time period, and the standard deviation value refers to the standard deviation value of all power differences in the target time period.
S4014, determining an upper power difference threshold and a lower power difference threshold according to the average value and the standard deviation value.
Alternatively, the average value of the power difference sequence may be defined asThe standard deviation is sigma, the power difference threshold may be expressed asWherein->Represents a lower threshold of the power difference,/-)>Indicating the upper power difference threshold.
Exemplary, if an average value is defined500, the standard deviation sigma is 50, and the power difference threshold is (350,650), wherein the power difference lower threshold is 350, and the power difference upper threshold is 650.
Specifically, a power detection device detects a power missing target point, a target time period is determined according to a preset time threshold, historical power data in the target time period is obtained, a power difference sequence is established according to a power difference value between two adjacent historical power data in the target time period, a power difference threshold is further determined by calculating an average value and a standard deviation of the difference sequence, and the power difference threshold can be used for judging whether a power filling value calculated by a fitting function is an available value.
Optionally, fig. 6 is a flowchart of still another power-missing value filling method for a power optimizer according to the fourth embodiment of the present invention, and fig. 6 illustrates, on the basis of fig. 4, a method for correcting a power-missing value, which is not limited to this method.
Referring to fig. 6, the correction of the power filling value according to the previous measured power data, the next measured power data and the power difference threshold value specifically includes the following steps:
s4031, calculating a first power difference value according to the power filling value and the previous measured power data.
S4032, calculating a second power difference value according to the power filling value and the later measured power data.
S4033, judging whether the maximum difference value of the first power difference value and the second power difference value exceeds a power difference threshold value.
Optionally, the maximum difference value of the first power difference value and the second power difference value exceeds the power difference threshold value comprises: the maximum difference value of the first power difference value and the second power difference value is larger than the upper power difference threshold value, or the maximum difference value of the first power difference value and the second power difference value is smaller than the lower power difference threshold value.
S4034, if the maximum difference exceeds the power difference threshold, calculating a linear power filling value according to the previous measured power data and the next measured power data.
The linear power filling value refers to a power filling value calculated by a linear interpolation method.
In this step, the linear interpolation method may be expressed by a function y=k (x1+x2), where y represents power data to be filled, x1 represents the previous measured power data, x2 represents the next measured power data, k is a linear interpolation coefficient, and a specific value of k may be set according to actual needs.
S4035, correcting the power filling value by adopting the linear power filling value.
Specifically, after the power filling value is obtained, judging whether a difference value between the power filling value and the previous measured power data and the next measured power data is within a power difference threshold range, and if the difference value is within the power difference threshold range, judging that the power filling value is available data; if the difference value is not in the power difference threshold range, judging the power filling value as unavailable data, calculating the filling value by a linear difference method, and replacing the power filling value calculated by the original fitting function.
For example, the former measured power data is defined as 9.9, the latter measured power data is defined as 110, the fitted power filling value is 2000, the power difference threshold is (350,650), the calculated first power difference is 1990.1, the second power difference is 1890, the maximum difference between the first power difference and the second power difference is 1990.1, the power difference threshold is exceeded, the linear power filling value is calculated from the former measured power data and the latter measured power data by interpolation calculation, for example, the linear power filling value may be
According to the power missing value filling method for the power optimizer, a power difference sequence between two adjacent historical power data in a target time period is established, the average value and the standard deviation of the difference sequence are calculated to determine a power difference threshold, the relation between the maximum difference value in the first power difference value and the second power difference value and the power difference threshold is judged, if the maximum difference value exceeds the power difference threshold, a linear power filling value is calculated according to the previous actual measurement power data and the next actual measurement power data, and the power filling value is corrected. The error power filling value can be corrected by using the power difference threshold value and the method for judging the maximum difference value and the power difference threshold value in the first power difference value and the second power difference value, so that the accuracy of the power filling value is improved, and the effective filling of the power missing data is realized.
Example five
Fig. 7 is a schematic structural diagram of a power-missing-value filling device for a power optimizer according to a fourth embodiment of the present invention, where the device 81 includes: a data sampling unit 701, a curve fitting unit 702, a missing value detection unit 703, and a missing value filling unit 704.
The data sampling unit 701 is configured to acquire historical irradiation data and historical power data.
And a curve fitting unit 702, configured to perform curve fitting based on the historical irradiation data and the historical power data, and determine a power fitting function.
The missing value detection unit 703 is configured to obtain a power missing target point of the power optimizer and measured irradiation data of the power missing target point.
And the missing value filling unit 704 is configured to determine a power filling value of the power missing target point according to the power fitting function and the actually measured irradiation data, and fill the power data of the power missing target point according to the power filling value.
Optionally, the curve fitting unit 702 is further configured to determine a curve inflection point of the irradiation power curve according to the historical irradiation data and the historical power data; carrying out data segmentation on the historical irradiation data and the historical power data according to the curve inflection points to obtain at least one sample interval; and performing polynomial curve fitting on the historical irradiation data and the historical power data segments in at least one sample interval to obtain at least one segmented power fitting function, wherein the at least one segmented power fitting function corresponds to the at least one sample interval one by one. The piecewise power fitting function includes a linear fitting function and/or a binomial curve fitting function.
Optionally, the missing value detection unit 703 is further configured to obtain measured power data recorded by the power optimizer; judging whether the interval time between two adjacent measured power data is larger than a preset time threshold value or not; if the interval time between two adjacent measured power data is larger than a preset time threshold, determining a power loss target point according to the interval time between the two adjacent measured power data; inquiring historical irradiation data according to the power-missing target point, and determining actual measurement irradiation data of the power-missing target point.
Optionally, the apparatus 81 further includes: the device comprises a power difference threshold determining unit, a power data acquisition unit and a power filling value correction unit.
The power difference threshold determining unit is used for determining a power difference threshold according to the historical power data, wherein the power difference threshold comprises an upper power difference threshold and a lower power difference threshold.
And the power data acquisition unit is used for acquiring the previous measured power data and the next measured power data adjacent to the power filling value.
And the power filling value correction unit is used for correcting the power filling value according to the previous measured power data, the next measured power data and the power difference threshold value.
Optionally, the power difference threshold determining unit is further configured to obtain a target time period to which the power loss target point belongs; establishing a power difference sequence according to the power difference between two adjacent historical power data in the target time period; calculating the average value and standard deviation value of the power difference value sequence; and determining an upper power difference threshold and a lower power difference threshold according to the average value and the standard deviation value.
Optionally, the power filling value correction unit is further configured to calculate a first power difference value according to the power filling value and the previous measured power data; calculating a second power difference value according to the power filling value and the later measured power data; judging whether the maximum difference value of the first power difference value and the second power difference value exceeds a power difference threshold value; if the maximum difference exceeds the power difference threshold, calculating a linear power filling value according to the previous measured power data and the next measured power data.
Optionally, the apparatus 81 further comprises a data cleansing unit for data cleansing the historical irradiation data and the historical power data.
The power missing value filling device for the power optimizer provided by the embodiment of the invention can execute the power missing value filling method for the power optimizer provided by any embodiment of the invention, and has the corresponding functional units and beneficial effects of the execution method.
Example six
Fig. 8 is a schematic structural diagram of a power optimizer provided in a sixth embodiment of the present invention, as shown in fig. 8, the power optimizer includes a power optimizer body 80 and a power missing value filling device 81, where the power missing value filling device 81 has the functional modules and technical effects of any one of the above embodiments.
Alternatively, the power optimizer body 80 may track the maximum power point of the photovoltaic module in real time, and the power optimizer body 80 may be capable of achieving and monitoring the maximum power output of the monolithic module on line. The power missing value filling device 81 is configured in the power optimizer body 80, when the power obtained by the power optimizer body 80 has missing data, the power missing value filling device 81 cannot meet the requirements of subsequent power optimization and monitoring, and at this time, the power missing value filling device 81 performs power missing value filling on the power missing data obtained by the power optimizer body 80 through the data sampling unit, the curve fitting unit, the missing value detecting unit and the missing value filling unit.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (10)
1. A power miss value filling method for a power optimizer, comprising:
acquiring historical irradiation data and historical power data;
performing curve fitting based on the historical irradiation data and the historical power data, and determining a power fitting function;
acquiring the actually measured irradiation data of a power missing target point of the power optimizer and the power missing target point;
determining a power filling value of the power-missing target point according to the power fitting function and the actually measured irradiation data, and filling the power data of the power-missing target point according to the power filling value;
the curve fitting based on the historical irradiation data and the historical power data comprises the following steps:
determining a curve inflection point of an irradiation power curve according to the historical irradiation data and the historical power data;
carrying out data segmentation on the historical irradiation data and the historical power data according to the curve inflection point to obtain at least one sample interval;
and performing polynomial curve fitting on the historical irradiation data and the historical power data segments in the at least one sample interval to obtain at least one segment power fitting function.
2. The power-missing-value filling method for a power optimizer according to claim 1, wherein after determining a power filling value of the power-missing target point according to the power fitting function and the measured irradiation data, further comprising the steps of:
determining a power difference threshold according to the historical power data, wherein the power difference threshold comprises a power difference upper limit threshold and a power difference lower limit threshold;
acquiring the previous measured power data and the next measured power data adjacent to the power filling value;
and correcting the power filling value according to the previous measured power data, the next measured power data and the power difference threshold value.
3. The power loss value filling method for a power optimizer according to claim 2, wherein the power filling value is corrected based on the previous measured power data, the subsequent measured power data and the power difference threshold, comprising the steps of:
calculating a first power difference value according to the power filling value and the previous measured power data;
calculating a second power difference value according to the power filling value and the later measured power data;
judging whether the maximum difference value in the first power difference value and the second power difference value exceeds the power difference threshold value or not;
if the maximum difference value exceeds the power difference threshold value, calculating a linear power filling value according to the previous measured power data and the next measured power data;
and correcting the power filling value by adopting the linear power filling value.
4. The power deficiency value filling method for a power optimizer as claimed in claim 2, wherein said determining a power difference threshold from said historical power data comprises the steps of:
acquiring a target time period to which the power loss target point belongs;
establishing a power difference sequence according to the power difference between two adjacent historical power data in the target time period;
calculating an average value and a standard deviation value of the power difference value sequence;
and determining the power difference upper limit threshold and the power difference lower limit threshold according to the average value and the standard deviation value.
5. The power loss value filling method for a power optimizer according to claim 1, wherein said obtaining the power loss target point of the power optimizer and the actually measured irradiation data of the power loss target point includes the steps of:
obtaining actual measurement power data recorded by the power optimizer;
judging whether the interval time between two adjacent measured power data is larger than a preset time threshold value or not;
if the interval time between the two adjacent measured power data is larger than a preset time threshold, determining a power missing target point according to the interval time between the two adjacent measured power data;
inquiring the historical irradiation data according to the power-missing target point, and determining the actual measurement irradiation data of the power-missing target point.
6. The power deficiency value filling method for a power optimizer as claimed in claim 1, wherein said curve fitting based on said historical irradiance data and said historical power data comprises the steps of:
the at least one piecewise power fitting function is in one-to-one correspondence with the at least one sample interval.
7. The power deficiency value filling method for a power optimizer as claimed in claim 6, wherein the piecewise power fitting function comprises a linear fitting function and/or a binomial curve fitting function.
8. The power deficiency value filling method for a power optimizer as claimed in claim 1, further comprising the steps of, before curve fitting based on said historical irradiance data and said historical power data:
and performing data cleaning on the historical irradiation data and the historical power data.
9. A power deficiency value filling apparatus for a power optimizer, comprising:
the data sampling unit is used for acquiring historical irradiation data and historical power data;
the curve fitting unit is used for performing curve fitting based on the historical irradiation data and the historical power data to determine a power fitting function;
the missing value detection unit is used for acquiring a power missing target point of the power optimizer and actually measured irradiation data of the power missing target point;
the missing value filling unit is used for determining a power filling value of the power missing target point according to the power fitting function and the actually measured irradiation data and filling the power data of the power missing target point according to the power filling value;
the curve fitting unit is also used for determining a curve inflection point of the irradiation power curve according to the historical irradiation data and the historical power data; carrying out data segmentation on the historical irradiation data and the historical power data according to the curve inflection points to obtain at least one sample interval; and performing polynomial curve fitting on the historical irradiation data and the historical power data segments in at least one sample interval to obtain at least one segmented power fitting function.
10. A power optimizer comprising the power deficiency value filling apparatus for a power optimizer of claim 9.
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