Method and device for determining operating state of photovoltaic power station

Abstract

The application discloses a kind of photovoltaic power station's operating state determination method and device, method includes: obtaining the n historical output data set of n sunny days before photovoltaic power station in current sunny day;According to each historical output data in each historical output data set, determine average output data set;According to each historical output data in each historical output data set and each average output data in average output data set, determine output interval set;Obtain the current output data set of photovoltaic power station in current sunny day;One-to-one correspondingly judge whether each current output data is in each output interval, if each current output data is located in each output interval, then it indicates that photovoltaic power station is in normal operating state.Using the above technical scheme, the operating state of photovoltaic power station can be detected only through the historical output data set of photovoltaic power station, the monitoring problem of the operating state of photovoltaic power station is solved, the development of distributed photovoltaic power station is effectively improved, and the operation and maintenance cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic power plant anomaly sensing technology, and in particular to a method and apparatus for determining the operating status of a photovoltaic power plant. Background Technology

[0002] In recent years, global warming has intensified, making the solution to energy issues more prominent. The development of distributed photovoltaic (PV) systems is a crucial component in building a new energy power system and achieving the "dual carbon" goals of the power industry. Distributed PV offers advantages such as being unrestricted by region or geographical location, having relatively small output power that can be flexibly adjusted, low pollution and significant environmental benefits, and low transmission line losses due to the simultaneous generation and consumption of electricity.

[0003] In recent years, the installed capacity of distributed photovoltaic (PV) power has grown rapidly, and its power generation accounts for an increasingly important proportion of the new energy structure. As the scale of distributed PV expands, accurate perception of the operating status of distributed PV power stations and timely detection of abnormal operating conditions are important means to ensure the safe and economical operation of distributed PV systems. Summary of the Invention

[0004] This invention provides a method and apparatus for determining the operating status of a photovoltaic power station, so as to monitor the operating status of the photovoltaic power station and ensure the normal operation of the photovoltaic system.

[0005] According to one aspect of the present invention, a method for determining the operating status of a photovoltaic power plant is provided, comprising:

[0006] Obtain n historical power output datasets for the photovoltaic power station for n sunny days prior to the current sunny day; each historical power output dataset includes m historical power output data corresponding one-to-one with m preset times in a sunny day; where n and m are both positive integers greater than or equal to 2;

[0007] An average output dataset is determined based on the historical output data in each of the historical output datasets; the average output dataset includes m average output data that correspond one-to-one with m preset time points;

[0008] Based on the historical output data in each of the historical output datasets and the average output data in each of the average output datasets, an output interval set is determined; the output interval set includes m output intervals that correspond one-to-one with m preset times.

[0009] Obtain the current power output dataset of the photovoltaic power station on the current sunny day; the current power output dataset includes m current power output data corresponding one-to-one with m preset times;

[0010] Determine whether each of the current output data is within its respective output range in a one-to-one correspondence;

[0011] If so, the photovoltaic power station is in normal operation.

[0012] Optionally, obtain n historical power output datasets for the photovoltaic power station over the n sunny days prior to the current sunny day, including:

[0013] Obtain n historical output power sets of the photovoltaic power station for n sunny days prior to the current sunny day; each historical output power set includes m historical output powers that correspond one-to-one with m preset times on a sunny day;

[0014] Dimensionless processing is performed on each of the historical output power sets to determine each of the historical output power datasets corresponding to each of the historical output power sets;

[0015] Obtain the current output data set of the photovoltaic power station on the current sunny day, including:

[0016] Obtain the current output power set of the photovoltaic power station on the current sunny day; the current output power set includes m current output powers that correspond one-to-one with m preset times;

[0017] Dimensionless processing is performed on each current output power in the current output power set to determine the current output power dataset corresponding to the current output power set.

[0018] Optionally, the historical output power of each of the historical output power sets is dedimensionalized to determine the historical output power datasets corresponding to each of the historical output power sets, including:

[0019] Based on the historical output power concentrations and the historical output power corresponding to the same time, determine the m minimum historical output power and the m maximum historical output power that correspond one-to-one with the m preset times;

[0020] Based on the minimum historical output power, the maximum historical output power, and the historical output power, determine the historical output data that corresponds one-to-one with each of the historical output powers;

[0021] Each of the historical output data corresponding to the historical output power of the same sunny day is taken as a historical output dataset, so as to determine the n historical output datasets of the photovoltaic power station for n sunny days before the current sunny day in a one-to-one correspondence.

[0022] Dimensionless processing is performed on each current output power in the current output power set to determine the current output power dataset corresponding to the current output power set, including:

[0023] Based on the minimum historical output power, the maximum historical output power, and the current output power, determine the current output data that corresponds one-to-one with each current output power;

[0024] Each of the current output data is used as a single current output dataset to determine the current output dataset of the photovoltaic power station on the current sunny day.

[0025] Optionally, the historical output data P in the historical output data set of the i-th sunny day corresponds to the historical output data P of the j-th preset time. j,i The calculation formula is: P j,i =(Y j,i -min{Y j,1 Y j,2 , ···, Y j,n}) /

[0026] (max{Y j,1 Y j,2 , ···, Y j,n}-minY{Y j,1 Y j,2 , ···, Y j,n});

[0027] The current output data X in the current output data set of the current sunny day that corresponds to the j-th preset time. j The calculation formula is: X j =(Z j -min{Y j,1 Y j,2 , ···, Y j,n}) / (max{Y j,1 Y j,2 , ···, Y j,n}

[0028] -min{Y j,1 Y j,2 , ···, Y j,n});

[0029] Where 1≤i≤n; 1≤j≤m; Y j,i For the historical output data of the i-th sunny day, the historical output power corresponding to the j-th preset time is concentrated; Z j The current output power is the current output power corresponding to the j-th preset time.

[0030] Optionally, the average output data P in the average output data set corresponds to the j-th preset time point. j,mid The calculation formula is:

[0031] Where 1≤i≤n; 1≤j≤m; P j,i The historical output data for the i-th sunny day is combined with the historical output data corresponding to the j-th preset time.

[0032] Optionally, the output range set includes an upper limit dataset and a lower limit dataset;

[0033] The upper limit dataset includes m upper limit data points that correspond one-to-one with the m preset times; the lower limit dataset includes m lower limit data points that correspond one-to-one with the m preset times.

[0034] The output range is the range formed by the upper limit data and the lower limit data corresponding to the same preset time.

[0035] Optionally, based on the historical output data in each of the historical output datasets and the average output data in each of the average output datasets, a set of output intervals is determined, including:

[0036] Based on the historical output data in each of the historical output datasets and the average output data in each of the average output datasets, the standard deviation of each of the historical output data and the average output data is calculated to obtain m standard deviation data that correspond one-to-one with m preset times.

[0037] Based on the standard deviation data and the average output data, the lower limit data and the upper limit data are determined one by one.

[0038] Optionally, the lower limit data P in the lower limit data set corresponds to the j-th preset time. j,dn The calculation formula is: P j,dn =P j,mid -k·σ j ;

[0039] The upper limit data P in the upper limit data set that corresponds to the j-th preset time. j,up The calculation formula is: P j,up =P j,mid +k·σ j ;

[0040] Where 1≤j≤m; k is a positive integer; P j,mid The average output data in the average output data set corresponding to the j-th preset time point; σ j The standard deviation data corresponding to the j-th preset time.

[0041] Optionally, the probability that each of the historical output data points is located within the output interval set is greater than 99% and less than 100%.

[0042] According to another aspect of the present invention, a device for determining the operating status of a photovoltaic power plant is provided, comprising:

[0043] The historical output dataset acquisition module is used to acquire n historical output datasets of the photovoltaic power station for n sunny days prior to the current sunny day; each historical output dataset includes m historical output data corresponding one-to-one with m preset times in a sunny day; where n and m are both positive integers greater than or equal to 2;

[0044] The average output dataset determination module is used to determine the average output dataset based on the historical output data in each of the historical output datasets; the average output dataset includes m average output data that correspond one-to-one with m preset time points;

[0045] The output interval set determination module is used to determine the output interval set based on the historical output data in each of the historical output datasets and the average output data in the average output dataset; the output interval set includes m output intervals that correspond one-to-one with m preset times.

[0046] The current output dataset acquisition module is used to acquire the current output dataset of the photovoltaic power station on the current sunny day; the current output dataset includes m current output data corresponding one-to-one with m preset times;

[0047] The judgment module is used to determine whether each of the current output data is within the respective output range; if so, the photovoltaic power station is in normal operation.

[0048] The technical solution of this invention obtains the output data characteristics of a photovoltaic power station on sunny days by acquiring n historical output datasets from n sunny days prior to the current sunny day. Based on these output data characteristics, the normal output fluctuation range, i.e., the output range set, can be obtained. The operating status of a photovoltaic power station can be detected using only its historical output dataset, solving the problem of monitoring the operating status of photovoltaic power stations that cannot be detected due to insufficient fault features and scarce data. This effectively promotes the development of distributed photovoltaic power stations and reduces operation and maintenance costs.

[0049] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 This is a flowchart of a method for determining the operating status of a photovoltaic power station according to Embodiment 1 of the present invention;

[0052] Figure 2 This is a schematic diagram of an average output data set provided in Embodiment 1 of the present invention;

[0053] Figure 3 This is a schematic diagram of a power output interval set provided in Embodiment 1 of the present invention;

[0054] Figure 4 This is a schematic diagram of a current output data set provided in Embodiment 1 of the present invention;

[0055] Figure 5 This is a flowchart of a method for determining the operating status of a photovoltaic power station according to Embodiment 2 of the present invention;

[0056] Figure 6 This is a schematic diagram of the structure of a photovoltaic power station operation status determination device provided in Embodiment 3 of the present invention. Detailed Implementation

[0057] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0058] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0059] Example 1

[0060] Figure 1 This is a flowchart of a method for determining the operating status of a photovoltaic power station according to Embodiment 1 of the present invention. This embodiment is applicable to monitoring the operating status of a photovoltaic power station under clear weather conditions. The method can be executed by a photovoltaic power station operating status determination device, which can be implemented in hardware and / or software and can be configured in the monitoring system of the photovoltaic power station. Figure 1 As shown, the method includes:

[0061] S1001. Obtain n historical output datasets of the photovoltaic power station for n sunny days prior to the current sunny day; each historical output dataset includes m historical output data corresponding one-to-one with m preset times in a sunny day; where n and m are both positive integers greater than or equal to 2.

[0062] Specifically, the historical output datasets of different sunny days prior to the current sunny day are obtained. The output dataset consists of the historical output data of the current day, and the historical output data of the current day is extracted once at the same time interval.

[0063] For example, from the dates preceding the current sunny day, a power output dataset of 55 sunny days is selected, resulting in 55 historical power output datasets. These 55 sunny days can be non-consecutive. On each sunny day, historical power output data is extracted every 15 minutes between 6:00 AM and 7:00 PM. Each historical power output dataset includes 52 historical power output data points corresponding to 52 preset times. The daily effective power output data of a photovoltaic power station on sunny days is related to the sunrise and sunset times of the geographical location where the photovoltaic array is installed. Differences in geographical location and seasonal timing will cause variations in sunrise and sunset times. For example, there are significant differences between sunrise and sunset times in summer and winter. Except for a few distinctive cities, the basic sunrise time is around 6:00 AM, and the basic sunset time is around 7:00 PM. The output power of the photovoltaic power station is almost zero at night. Selecting the power output dataset from 6:00 AM to 7:00 PM as the effective power output dataset for the photovoltaic power station avoids slight fluctuations in output data caused by excessively low power generation, and eliminates the impact of inconsistent sunrise and sunset times and fluctuating output at night. Furthermore, the time intervals for each preset time point are the same, which does not affect the effectiveness of the output data and the method for determining the operating status of the photovoltaic power station.

[0064] It should be noted that the historical output datasets for the n sunny days prior to the current sunny day were all obtained when the photovoltaic power station was in normal operation.

[0065] Optionally, the historical output data refers to the dimensionless version of the historical power generation data of the photovoltaic power station. Obtaining n historical output datasets for the photovoltaic power station over the n sunny days prior to the current sunny day includes: obtaining n historical output power sets for the photovoltaic power station over the n sunny days prior to the current sunny day; each historical output power set includes m historical output powers corresponding one-to-one with m preset times on a sunny day; and performing dimensionless processing on each historical output power in each historical output power set to determine the corresponding historical output dataset.

[0066] For example, firstly, extract n historical output power sets of the photovoltaic power station for n sunny days prior to the current sunny day. Then, determine the m minimum historical output power and m maximum historical output power corresponding one-to-one with m preset times. Finally, normalize and dedimensionalize each historical output power in the n historical output power sets to obtain the historical output data corresponding to each historical output power. For example, per-unit processing can be used to convert each historical output power into historical output data that are all less than or equal to 1. The historical output data P in the historical output data set of the i-th sunny day corresponds to the historical output data P of the j-th preset time. j,i The formula for per-unit processing is: P j,i =(Y j,i-min{Y j,1 Y j,2 , ···, Y j,n}) / (max{Y j,1 Y j,2 , ···, Y j,n}-minY{Y j,1 Y j,2 , ···, Y j,n}), where Y j,i The historical output power corresponding to the j-th preset time is defined in the historical output data set for the i-th sunny day. The historical output power corresponding to each historical output power on the same sunny day constitutes a historical output data set, thereby obtaining n historical output data sets for the photovoltaic power station for the n sunny days prior to the current sunny day.

[0067] S1002. Determine the average output dataset based on the historical output data in each historical output dataset. The average output dataset includes m average output data that correspond one-to-one with m preset time points.

[0068] The average output dataset consists of the average value of each historical output data corresponding to m preset times. That is, the average output data corresponding to each preset time is the average value of the historical output data corresponding to the same preset time in each historical output dataset.

[0069] For example, the average output data P in the average output data set corresponding to the j-th preset time point. j,mid The calculation formula is: Where 1≤i≤n; 1≤j≤m; P j,i This refers to the historical output data corresponding to the j-th preset time within the historical output dataset of the i-th sunny day. Taking n=55 and m=52 as an example, the historical output data of 55 sunny days is mapped to the 55 historical output data corresponding to the first preset time, yielding the average output data corresponding to the first preset time; the historical output data of 55 sunny days is mapped to the 55 historical output data corresponding to the second preset time, yielding the average output data corresponding to the second preset time, and so on, until the average output data corresponding to the 52nd preset time is obtained. These average output data constitute the average output dataset, such as... Figure 2 As shown.

[0070] S1003. Determine the power output interval set based on the historical power output data in each historical power output dataset and the average power output data in each average power output dataset; the power output interval set includes m power output intervals that correspond one-to-one with m preset times.

[0071] For example, based on multiple historical output data and average output data at various preset times, a reasonable distribution range of the current output data at each preset time on a clear day can be obtained using mathematical distribution, i.e., the output interval corresponding to each preset time. The mathematical distribution includes, but is not limited to, exponential distribution, normal distribution, geometric distribution, etc., and this embodiment of the invention does not limit the specific distribution.

[0072] Optionally, the output interval set includes an upper limit dataset and a lower limit dataset; the upper limit dataset includes m upper limit data corresponding one-to-one with m preset times; the lower limit dataset includes m lower limit data corresponding one-to-one with m preset times; the output interval is the interval formed by the upper limit data and the lower limit data corresponding to the same preset time.

[0073] For example, using mathematical distribution, multiple historical output data and average output data corresponding to each preset time can be used to obtain upper limit data and lower limit data corresponding to each preset time. The upper limit data constitutes an upper limit dataset, and the lower limit data constitutes a lower limit dataset. The upper limit dataset and the lower limit dataset can form a set of output intervals, such as... Figure 3 As shown, the power output interval set can basically cover all historical power output data. For example, it can make the probability that each historical power output data is located in the power output interval set greater than 99% and less than 100%.

[0074] S1004. Obtain the current output data set of the photovoltaic power station on the current sunny day; the current output data set includes m current output data corresponding one-to-one with m preset times.

[0075] For example, with m=52, the current output data is extracted every 15 minutes from 6:00 AM to 7:00 PM on a clear day.

[0076] Optionally, the current output data is the dimensionless data of the current power generation of the photovoltaic power station. Obtaining the current output dataset of the photovoltaic power station on the current sunny day includes: obtaining the current output power set of the photovoltaic power station on the current sunny day; the current output power set includes m current output powers corresponding one-to-one with m preset times; performing dimensionless processing on each current output power in the current output power set to determine the current output dataset corresponding to the current output power set.

[0077] For example, firstly, the current output power set of the photovoltaic power station on the current sunny day is extracted. Then, combining the m minimum historical output power and m maximum historical output power corresponding to m preset times, the m current output power corresponding to the m preset times in the current output power set is normalized and dimensionless to obtain the current output power data corresponding to each current output power. For example, per-unit processing can be used to convert each current output power into current output power data that are all less than or equal to 1. The current output power data X corresponding to the j-th preset time in the current output power set of the current sunny day is... j The calculation formula is: X j =(Z j -min{Y j,1 Y j,2 , ···, Y j,n}) / (max{Y j,1 Y j,2 , ···, Y j,n}-min{Y j,1 Y j,2 , ···, Y j,n}); where 1≤i≤n; 1≤j≤m; Y j,i For the historical output data of the i-th sunny day, the historical output power corresponding to the j-th preset time is concentrated; Z j The current output power is the current output power corresponding to the j-th preset time. All current output data constitute a current output dataset, thus obtaining the current output dataset of the photovoltaic power plant on the current sunny day.

[0078] S1005. Determine whether each current output data is within its respective output range. If yes, proceed to step S1006; otherwise, proceed to step S1007.

[0079] For example, it is determined whether the current output data corresponding to the first preset time is within the output range corresponding to the first preset time, whether the current output data corresponding to the second preset time is within the output range corresponding to the second preset time, and so on, to determine whether the current output data corresponding to the m-th preset time is within the output range corresponding to the m-th preset time.

[0080] S1006. Confirm that the photovoltaic power station is in normal operation.

[0081] S1007. Confirmed that the photovoltaic power station is not in normal operation.

[0082] Specifically, if the current output data for each preset time point is within the output range corresponding to that preset time point, it indicates that the photovoltaic power station is in normal operation; if at least one preset time point has current output data that is not within the output range corresponding to that preset time point, such as... Figure 4 As shown, this indicates that the photovoltaic power station is not in normal operation, is in an abnormal operating state, and the photovoltaic cells may be malfunctioning.

[0083] For example, distributed photovoltaic (PV) power stations have small installed capacities and are widely distributed. Furthermore, their operating environments are often harsher than those of centralized large-scale PV power stations. They lack management and professional maintenance personnel and are not equipped with data acquisition equipment such as small weather stations, making it difficult to obtain more effective information for operational status monitoring. The only data available is the PV power station's power generation data. The most direct impact of abnormal PV power station operation is reduced power output, and different weather conditions directly affect the amount of PV output. The output characteristic curves for sunny and cloudy days differ significantly. The power output data set of PV power stations on sunny days is relatively smooth and stable, with small fluctuations, exhibiting an arch-shaped pattern. Using the characteristics of historical power output data sets from multiple sunny days prior to the current sunny day as a reliable basis for detecting the operational status of PV power stations is therefore quite reliable. First, obtain n historical power output datasets for the photovoltaic power station over n sunny days prior to the current sunny day. The output power curve trend of the photovoltaic power station on sunny days is not directly correlated with the sampling frequency of the data acquisition system. However, excessively long sampling intervals may overlook certain curve feature changes, making it impossible to detect the true power output curve. The preset time interval range is 1-30 minutes, meaning the sampling interval for obtaining the photovoltaic array output time-series power data can be 1 minute, 5 minutes, 15 minutes, 30 minutes, etc. Considering the sampling frequency of the data acquisition system and minimizing its impact on the output waveform, a preset time interval of 15 minutes can be selected, with 4 samples per hour. Based on the data characteristics of each historical power output dataset, an average power output dataset and a power output interval set can be obtained, i.e., a normal power output interval set, which can be used as a fluctuation check standard for the current power output dataset. When the power output data is within the output interval, it indicates that the photovoltaic power station is operating normally; when the power output data exceeds the output interval, it indicates that the photovoltaic power station is operating abnormally, requiring professional maintenance personnel to conduct on-site maintenance and repair.

[0084] In this embodiment of the invention, by acquiring n historical power output datasets from n sunny days prior to the current sunny day, the power output data characteristics of the photovoltaic power station on sunny days can be obtained. Based on the power output data characteristics, the normal power output fluctuation range, i.e., the power output range set, can be obtained. The operating status of the photovoltaic power station can be detected solely through the historical power output dataset, solving the problem of monitoring the operating status of photovoltaic power stations that cannot be detected due to insufficient fault features and scarce data. This effectively promotes the development of distributed photovoltaic power stations and reduces operation and maintenance costs.

[0085] Example 2

[0086] Figure 5 This is a flowchart of a method for determining the operating status of a photovoltaic power station according to Embodiment 2 of the present invention. Compared with the above embodiments, this embodiment adds a step on how to determine the power output interval set. Figure 5 As shown, the method includes:

[0087] S2001. Obtain n historical output datasets of the photovoltaic power station for n sunny days prior to the current sunny day; each historical output dataset includes m historical output data corresponding one-to-one with m preset times in a sunny day; where n and m are both positive integers greater than or equal to 2.

[0088] S2002. Determine the average output dataset based on the historical output data in each historical output dataset. The average output dataset includes m average output data that correspond one-to-one with m preset time points.

[0089] S2003. Based on the historical output data in each historical output dataset and the average output data in each average output dataset, calculate the standard deviation of each historical output data and each average output data to obtain m standard deviation data that correspond one-to-one with m preset times.

[0090] S2004. Based on the standard deviation data and the average output data, determine the lower limit data and the upper limit data one by one.

[0091] S2005. Obtain the current output data set of the photovoltaic power station on the current sunny day; the current output data set includes m current output data corresponding one-to-one with m preset times.

[0092] S2006. Determine whether each current output data is within its respective output range. If yes, proceed to step S2007; otherwise, proceed to step S2008.

[0093] S2007. Confirm that the photovoltaic power station is in normal operation.

[0094] S2008. Confirmed that the photovoltaic power station is not in normal operation.

[0095] For example, the standard deviation output data σ corresponding to the j-th preset time point is... j The calculation formula is: The lower limit data P in the lower limit data set that corresponds to the j-th preset time. j,dn The calculation formula is: P j,dn =P j,mid -k·σ j The upper limit data P in the upper limit data set corresponds to the j-th preset time. j,up The calculation formula is: P j,up =P j,mid +k·σ j Where 1 ≤ j ≤ m; k is a positive integer; P j,i For the historical output data of the i-th sunny day, collect the historical output data corresponding to the j-th preset time; P j,mid The average output data in the average output dataset corresponds to the j-th preset time. The upper limit dataset is obtained by shifting the average output dataset up by k standard deviations, and the lower limit dataset is obtained by shifting the average output dataset up by k standard deviations. Following the normal distribution pattern, when the average output dataset is shifted up or down by one standard deviation, 68.26% of all historical output data is contained within the output interval set; when shifted up or down by two standard deviations, 95.44% of all historical output data is contained within the output interval set; and when shifted up or down by three σ, 99.74% of all data is contained within the range. When k=3, it can basically cover all valid data and the output range.

[0096] In this embodiment of the invention, by using the standard deviation data corresponding to each preset time, the upper limit data of the upper limit dataset and the lower limit data of the lower limit dataset of the power output interval set can be determined, so that the power output interval set can basically cover all historical power output data, thereby improving the accuracy and effectiveness of photovoltaic power plant operation status detection.

[0097] Example 3

[0098] Figure 6 This is a schematic diagram of a photovoltaic power station operation status determination device provided in Embodiment 3 of the present invention. Figure 6 As shown, the device includes:

[0099] The historical output dataset acquisition module 610 is used to acquire n historical output datasets of the photovoltaic power station for n sunny days before the current sunny day; each historical output dataset includes m historical output data corresponding one-to-one with m preset times in a sunny day; where n and m are both positive integers greater than or equal to 2;

[0100] The average output dataset determination module 620 is used to determine the average output dataset based on the historical output data in each historical output dataset; the average output dataset includes m average output data that correspond one-to-one with m preset time points.

[0101] The output interval set determination module 630 is used to determine the output interval set based on the historical output data in each historical output dataset and the average output data in the average output dataset; the output interval set includes m output intervals that correspond one-to-one with m preset times.

[0102] The current output dataset acquisition module 640 is used to acquire the current output dataset of the photovoltaic power station on the current sunny day; the current output dataset includes m current output data corresponding one-to-one with m preset times.

[0103] The judgment module 650 is used to determine whether each current output data is within its respective output range; if so, the photovoltaic power station is in normal operation.

[0104] The photovoltaic power plant operation status determination device provided in this embodiment of the invention can execute the photovoltaic power plant operation status determination method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0105] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0106] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for determining the operating status of a photovoltaic power station, characterized in that, include: Obtain n historical power output datasets for the photovoltaic power station for n sunny days prior to the current sunny day; each historical power output dataset includes m historical power output data corresponding one-to-one with m preset times in a sunny day; where n and m are both positive integers greater than or equal to 2; wherein, whether it is a sunny day is determined based on the power output characteristic curve obtained from the m power output data corresponding one-to-one with the m preset times on the same day. Based on the historical output data in each of the historical output datasets, an average output dataset is determined; the average output dataset includes m average output data that correspond one-to-one with m preset time points. Based on the historical output data in each of the historical output datasets and the average output data in each of the average output datasets, the standard deviation of each of the historical output data and the average output data is calculated to obtain m standard deviation data that correspond one-to-one with m preset times. Based on the standard deviation data and the average output data, each lower limit data and each upper limit data are determined one-to-one; wherein, the upper limit data and the lower limit data corresponding to the same preset time constitute an output interval, and the m output intervals corresponding one-to-one with the m preset times constitute an output interval set; Obtain the current power output dataset of the photovoltaic power station on the current sunny day; the current power output dataset includes m current power output data corresponding one-to-one with m preset times; Determine whether each of the current output data is within its respective output range in a one-to-one correspondence; If so, the photovoltaic power station is in normal operation.

2. The method for determining the operating status of a photovoltaic power station according to claim 1, characterized in that, Obtain the historical power output dataset of the photovoltaic power station for the n sunny days prior to the current sunny day, including: Obtain n historical output power sets of the photovoltaic power station for n sunny days prior to the current sunny day; each historical output power set includes m historical output powers that correspond one-to-one with m preset times on a sunny day; Dimensionless processing is performed on each of the historical output power sets to determine each of the historical output power datasets corresponding to each of the historical output power sets; Obtain the current output data set of the photovoltaic power station on the current sunny day, including: Obtain the current output power set of the photovoltaic power station on the current sunny day; the current output power set includes m current output powers that correspond one-to-one with m preset times; Dimensionless processing is performed on each current output power in the current output power set to determine the current output power dataset corresponding to the current output power set.

3. The method for determining the operating status of a photovoltaic power station according to claim 2, characterized in that, Dimensionless processing is performed on the historical output power of each of the aforementioned historical output power sets to determine the historical output power datasets corresponding to each of the aforementioned historical output power sets, including: Based on the historical output power concentrations and the historical output power corresponding to the same time, determine the m minimum historical output power and the m maximum historical output power that correspond one-to-one with the m preset times; Based on the minimum historical output power, the maximum historical output power, and the historical output power, determine the historical output data that corresponds one-to-one with each of the historical output powers; Each of the historical output data corresponding to the historical output power of the same sunny day is taken as a historical output dataset, so as to determine the n historical output datasets of the photovoltaic power station for n sunny days before the current sunny day in a one-to-one correspondence. Dimensionless processing is performed on each current output power in the current output power set to determine the current output power dataset corresponding to the current output power set, including: Based on the minimum historical output power, the maximum historical output power, and the current output power, determine the current output data that corresponds one-to-one with each current output power; Each of the current output data is used as a single current output dataset to determine the current output dataset of the photovoltaic power station on the current sunny day.

4. The method for determining the operating status of a photovoltaic power station according to claim 3, characterized in that, The historical output data in the historical output data set of the i-th sunny day corresponds to the historical output data of the j-th preset time. The calculation formula is: ； The current output data in the current output data set of the current sunny day that corresponds to the j-th preset time. The calculation formula is: ； Where 1≤i≤n; 1≤j≤m; The historical output power corresponding to the j-th preset time is concentrated in the historical output data of the i-th sunny day; The current output power is the current output power corresponding to the j-th preset time.

5. The method for determining the operating status of a photovoltaic power station according to claim 1, characterized in that, The average output data P in the average output data set corresponding to the j-th preset time point j,mid The calculation formula is: ; Where 1≤i≤n; 1≤j≤m; The historical output data for the i-th sunny day is combined with the historical output data corresponding to the j-th preset time.

6. The method for determining the operating status of a photovoltaic power station according to claim 1, characterized in that, The output range set includes an upper limit dataset and a lower limit dataset; The upper limit dataset includes m upper limit data that correspond one-to-one with the m preset times; The lower limit dataset includes m lower limit data points that correspond one-to-one with the m preset times; The lower limit data in the lower limit data set that corresponds to the j-th preset time. The calculation formula is: ; The upper limit data in the upper limit dataset corresponding to the j-th preset time. The calculation formula is: ; Where 1≤j≤m; k is a positive integer; The average output data in the average output data set corresponding to the j-th preset time; The standard deviation data corresponding to the j-th preset time.

7. The method for determining the operating status of a photovoltaic power station according to claim 1, characterized in that, The probability that each of the historical output data points lies within the output interval set is greater than 99% and less than 100%.

8. A device for determining the operating status of a photovoltaic power station, characterized in that, include: The historical output dataset acquisition module is used to acquire n historical output datasets of the photovoltaic power station for n sunny days prior to the current sunny day; each historical output dataset includes m historical output data corresponding one-to-one with m preset times in a sunny day; where n and m are both positive integers greater than or equal to 2; The average output dataset determination module is used to determine the average output dataset based on the historical output data in each of the historical output datasets; the average output dataset includes m average output data that correspond one-to-one with m preset time points; The power output interval set determination module is used to calculate the standard deviation of each historical power output data and each average power output data based on each historical power output data in each historical power output dataset and each average power output data in each average power output dataset, thereby obtaining m standard deviation data that correspond one-to-one with m preset times. The power output interval set determination module is also used to determine each lower limit data and each upper limit data based on each standard deviation data and each average power output data. The upper limit data and the lower limit data corresponding to the same preset time constitute a power output interval, and the m power output intervals corresponding one-to-one with the m preset times constitute a power output interval set. The current output dataset acquisition module is used to acquire the current output dataset of the photovoltaic power station on the current sunny day; the current output dataset includes m current output data corresponding one-to-one with m preset times; The judgment module is used to determine whether each of the current output data is within the respective output range; if so, the photovoltaic power station is in normal operation.

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