Self-adaptive identification method and system for inclination angle orientation of photovoltaic string

Abstract

The invention relates to the technical field of intelligent operation and maintenance of a photovoltaic power station, and discloses a self-adaptive identification method and system for the inclination angle orientation of a photovoltaic string, and the method comprises the steps: obtaining the historical data of all photovoltaic strings, connected to various types of inverters, of the photovoltaic power station, and the metadata of the design of the photovoltaic power station; the metadata comprises longitude and latitude information of the photovoltaic power station and all tilt angle orientation combinations registered by the photovoltaic power station, and the historical data comprises historical current and voltage data; based on the historical data, screening out the photovoltaic string in normal operation, and calculating the power generation capacity of each photovoltaic string; calculating the theoretical irradiation potential of all inclination angle orientation combinations; and matching the power generation capacity of each photovoltaic string with the theoretical irradiation potential to obtain a photovoltaic string inclination angle orientation identification result. According to the method, the existing historical data and the power station metadata are utilized, accurate recognition of the inclination angle orientation of the photovoltaic string is achieved through automatic matching, and important basic data support is provided for follow-up implementation of refined operation, maintenance and analysis of the string level.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent operation and maintenance of photovoltaic power stations, and in particular to a method and system for adaptively identifying the inclination angle orientation of a photovoltaic string. Background Art

[0002] At present, there are two main methods for determining the tilt angle and direction in distributed photovoltaic scenarios: the first method is that the operation and maintenance personnel go to a specific site and use measuring equipment to manually determine the tilt angle and direction of the string. However, for a large number of photovoltaic power stations that are widely distributed, this method is not only costly, but also inefficient, and is not suitable for online management platforms that integrate a large number of photovoltaic power stations. The second method is to use a scanning device to obtain the point cloud model and orthophoto of the site, use the image detection model to determine the position of the image, and then determine the tilt angle and direction of each photovoltaic string in the image. This method makes full use of intelligent means for measurement, but the equipment cost is high and there is a certain false detection rate. Both of the above solutions require staff to go to the site and use the equipment to collect data while ignoring the data generated when the inverter is running. For a large number of distributed power stations, the results obtained by analyzing the data generated by the operation of the equipment are more economical and convenient.

[0003] Usually, when a photovoltaic power station is built, the existing tilt angle combination of the power station is recorded, and the information is registered as one of the power station metadata when the power station is connected to the management system. However, a distributed power station may have multiple inverters, each inverter is connected to multiple strings. A current technical challenge is how to accurately allocate the tilt angle through intelligent algorithms based on the recorded historical current and voltage data of the strings, so as to ensure that all strings can be assigned a clear and accurate tilt angle. Summary of the invention

[0004] In view of this, the present invention provides a method and system for adaptively identifying the inclination direction of a photovoltaic string, so as to solve the problem of how to determine the inclination direction of a photovoltaic string without actual on-site measurement.

[0005] In a first aspect, the present invention provides a method for adaptively identifying the inclination direction of a photovoltaic string, the method comprising:

[0006] Obtain the historical data of all photovoltaic strings connected to various types of inverters in the photovoltaic power station, as well as the metadata of the photovoltaic power station design; wherein the metadata includes: inverter model, longitude and latitude information of the photovoltaic power station, and all tilt angle and orientation combinations registered by the photovoltaic power station; the historical data includes: historical current data and historical voltage data;

[0007] Filter out the PV strings that are in normal operation based on historical data, and calculate the power generation capacity of each PV string;

[0008] Calculate the theoretical irradiation potential for all combinations of inclination angles in the metadata;

[0009] The power generation capacity of each photovoltaic string is matched with the theoretical irradiation potential to obtain the photovoltaic string inclination direction identification result.

[0010] The method for adaptively identifying the inclination direction of photovoltaic strings provided in the embodiment of the present invention obtains historical data of all photovoltaic strings of various types of inverters connected to the photovoltaic power station and metadata of the photovoltaic power station design, and comprehensively analyzes various key information, so that the final identification result can be based on a more comprehensive data foundation, which helps to improve the accuracy of inclination direction identification and accurately identify the inclination direction of photovoltaic strings. It can help operation and maintenance personnel to better understand whether the actual layout of various parts of the power station is consistent with the optimal light receiving conditions, and then can make targeted adjustments and optimizations to unreasonable inclination directions, thereby improving the power generation efficiency of the entire photovoltaic power station and providing a strong basis for decision-making on long-term stable and efficient operation of the power station.

[0011] In an optional implementation, the process of calculating the power generation capacity of each photovoltaic string includes:

[0012] Based on the historical data of PV strings connected to the same type of inverters and operating normally, the average power of each PV string connected to the same type of inverter is calculated, and the power generation capacity of each PV string is calculated based on the average power of each PV string;

[0013] The power generation capacity data of all photovoltaic strings connected to different types of inverters are divided into multiple power generation capacity intervals according to the power generation capacity, and the number of divided intervals is the same as the number of inclination angle direction combinations.

[0014] The embodiment of the present invention calculates the average power size based on the historical data of the normal operation of photovoltaic strings connected to the same type of inverters, and then obtains the power generation capacity. This grouping calculation according to the inverter type can eliminate the interference factors caused by different inverters, so that the calculated average power and power generation capacity of each photovoltaic string can more truly reflect the power generation characteristics of the string itself, improve the reliability of the data, and the reasonably divided power generation capacity interval corresponds to the number of inclination direction combinations. When the power generation capacity is subsequently matched with the theoretical irradiation potential, the power generation capacity range corresponding to each inclination direction combination can be found more carefully and accurately, thereby improving the accuracy of the overall matching, thereby more reliably obtaining the recognition result of the inclination direction of the photovoltaic string, and optimizing the accuracy of the entire recognition process.

[0015] In an optional implementation, the historical data further includes: historical irradiance data;

[0016] The method calculates the average power of each photovoltaic string connected to the same type of inverter based on the historical data of the photovoltaic strings connected to the same type of inverter in normal operation, and calculates the power generation capacity of each photovoltaic string based on the average power of each photovoltaic string, including:

[0017] Calculate the power value of each photovoltaic string connected to each type of inverter;

[0018] For PV strings with historical irradiance data or numerical weather forecast irradiance, the calculated power values ​​are used to obtain the average power for all days;

[0019] For PV strings that lack historical irradiance data and numerical weather forecast irradiance, the irradiance value under theoretical sunny conditions is calculated based on the timestamp information corresponding to the historical current data and historical voltage data. The number of sunny days is determined by judging the peak power and power fluctuation of a day in the historical data, and the average power of sunny days is calculated.

[0020] Arrange the calculated average power of each PV string by numerical value, and take the PV string with the largest average power connected to the same inverter model as the benchmark string;

[0021] The power generation capacity is represented by the ratio of the average power of other PV strings connected to the same model of inverter to the corresponding benchmark string.

[0022] For photovoltaic strings that lack historical irradiance data and numerical weather forecast irradiance, the embodiment of the present invention can calculate the irradiance value under theoretical sunny conditions based on the timestamp information corresponding to the historical current and voltage data, and further determine the number of sunny days by judging the peak power and power volatility, and finally calculate the average power of sunny days. This method embodies strong flexibility, so that even in the unfavorable situation of missing irradiance data, the power generation capacity of the corresponding photovoltaic strings can still be calculated relatively scientifically, ensuring that the entire calculation process can cover all photovoltaic strings without missing due to data shortcomings. The photovoltaic string with the largest average power connected to the same model inverter is used as the benchmark string, and then the average power of other photovoltaic strings of the same model inverter is used to characterize the power generation capacity. Through this method of setting up benchmarks and calculating ratios, a relatively standardized measurement scale is provided for the power generation capacity of different photovoltaic strings, which is convenient for intuitively comparing the relative power generation capacity of each string under the same inverter type.

[0023] In an optional implementation manner, determining the number of sunny days by judging the peak power and power fluctuation of a day in historical data includes:

[0024] Get the peak power on day d And judge Is it greater than the maximum power value in the preset historical time period with a preset multiple? If so, the power peak value on the dth day meets the requirement;

[0025] Get the mean of the absolute value of the first-order difference of power on day d And judge whether it is less than the average of the absolute values ​​of the first-order differences of the minimum power in the preset historical time period with a preset multiple; if so, it is determined that the power volatility of the dth day meets the requirements;

[0026] The number of days that meet both the power peak and power fluctuation requirements is obtained as the number of sunny days.

[0027] The embodiment of the present invention comprehensively considers two important dimensions: peak power and power volatility during the day. On sunny days, the solar radiation is usually relatively stable and sufficient, which will make the power of the photovoltaic strings show a higher peak and relatively stable change characteristics. Judging from these two aspects, it is more logically reasonable and rigorous to fit the actual performance of the photovoltaic string power generation on sunny days, and can more accurately select the days that meet the characteristics of sunny days.

[0028] In an optional implementation, the calculating of the theoretical irradiance potential of all inclination angle combinations in the metadata includes:

[0029] Calculate the extraterrestrial irradiance based on the longitude and latitude information of the photovoltaic power station, and calculate the sun's position based on the longitude and latitude information of the photovoltaic power station;

[0030] For PV strings with historical irradiance data or numerical weather forecast irradiance, the total irradiance on the inclined surface is calculated based on the historical irradiance data and time of the PV strings;

[0031] For PV strings that lack historical irradiance data and numerical weather forecast irradiance, calculate the theoretical clear sky irradiance for the time period corresponding to historical sunny days;

[0032] Based on irradiance data, extraterrestrial irradiance, solar position, time, and inclination direction, the total irradiance of the inclined surface for each inclination direction combination is obtained;

[0033] The irradiation potentials corresponding to all tilt angle combinations are sorted according to numerical values, and the sorting method is the same as the sorting method of the average power of the photovoltaic strings.

[0034] The embodiment of the present invention comprehensively considers the latitude and longitude information, sun position, irradiance data, tilt direction, time and other factors of the photovoltaic power station. These factors are interrelated and have a key impact on the irradiation received by the photovoltaic strings. By fully incorporating and calculating, the total irradiance of the inclined surface of each tilt direction combination finally obtained can more scientifically and accurately reflect the actual theoretical irradiation potential, laying a solid foundation for subsequent precise matching and tilt direction identification; the irradiation potential corresponding to all tilt direction combinations is sorted according to the numerical value, and the sorting method is the same as the way the average power of the photovoltaic strings is sorted. When the power generation capacity of the photovoltaic strings is subsequently matched with the theoretical irradiation potential, the same sorting method enables the two to correspond more conveniently and intuitively, making it easy to quickly and accurately find the tilt direction combination that best matches the power generation capacity of each photovoltaic string, which helps to improve the efficiency and accuracy of the entire tilt direction identification process.

[0035] In an optional implementation, matching the power generation capacity of each photovoltaic string with the theoretical irradiation potential to obtain the photovoltaic string inclination direction identification result includes:

[0036] Sorting the power generation capacity of each photovoltaic string, and matching each photovoltaic string with a tilt angle orientation combination having the same ranking of irradiation potential according to the sorting order;

[0037] After the matching is completed, all photovoltaic strings connected to all types of inverters in the photovoltaic power station correspond to a tilt angle direction value, and the photovoltaic string tilt angle direction identification result is obtained.

[0038] The matching method adopted in the embodiment of the present invention utilizes the basis of sorting the power generation capacity and irradiation potential respectively, so that the two can be associated in an orderly and corresponding manner. Since the sorting process itself is based on the scientific analysis and arrangement of relevant data, through such sorting and matching, the photovoltaic strings can be accurately associated with the inclination direction combination that best matches their power generation performance, which greatly improves the accuracy of matching and reduces the occurrence of mismatches, thereby providing a strong guarantee for obtaining reliable inclination direction identification results.

[0039] In a second aspect, the present invention provides an adaptive identification system for the inclination angle of a photovoltaic string, comprising:

[0040] A data acquisition module is used to acquire the historical data of all photovoltaic strings connected to various types of inverters in the photovoltaic power station, as well as metadata of the photovoltaic power station design; wherein the metadata includes: inverter model, longitude and latitude information of the photovoltaic power station, and all tilt angle and orientation combinations registered by the photovoltaic power station; the historical data includes: historical current data and historical voltage data;

[0041] A power generation capacity calculation module is used to select photovoltaic strings in normal operation based on historical data and calculate the power generation capacity of each photovoltaic string;

[0042] Irradiation data acquisition module, used to calculate the theoretical irradiation potential of all inclination angle combinations in metadata;

[0043] The inclination direction recognition module is used to match the power generation capacity of each photovoltaic string with the theoretical irradiation potential to obtain the inclination direction recognition result of the photovoltaic string.

[0044] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for adaptively identifying the inclination orientation of a photovoltaic string according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0045] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for adaptively identifying the inclination orientation of a photovoltaic string according to the first aspect or any corresponding embodiment thereof.

[0046] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the method for adaptively identifying the inclination orientation of a photovoltaic string according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1 A schematic diagram of a flow chart of a method for adaptively identifying the inclination orientation of a photovoltaic string according to an embodiment of the present invention;

[0049] Figure 2 A schematic diagram of the average total irradiance of the inclined surface in one day with different inclination angle combinations according to an embodiment of the present invention;

[0050] Figure 3 A schematic flow chart of a method for adaptively identifying the inclination orientation of a photovoltaic string according to a specific example of an embodiment of the present invention;

[0051] Figure 4A structural block diagram of a photovoltaic string tilt orientation adaptive recognition system according to an embodiment of the present invention;

[0052] Figure 5 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0054] Usually, when a photovoltaic power station is built, the existing tilt angle combination of the power station is recorded, and the information is registered as one of the power station metadata when the power station is connected to the management system. However, a distributed power station may have multiple inverters, each inverter is connected to multiple strings. A current technical challenge is how to accurately allocate the tilt angle through intelligent algorithms based on the recorded historical current and voltage data of the strings, so as to ensure that all strings can be assigned a clear and accurate tilt angle.

[0055] Taking into account that after a large number of photovoltaic power stations are connected to the operation and management platform, it is necessary to determine the inclination direction of each photovoltaic string of each inverter. In this embodiment, an adaptive identification method for the inclination direction of photovoltaic strings is provided. By processing and analyzing the historical data collected from the photovoltaic strings and matching them with the existing inclination direction combinations, the problem of determining the inclination direction of distributed photovoltaic strings is solved. Figure 1 is a flow chart of a method for adaptively identifying the inclination angle of a photovoltaic string according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0056] S101, obtaining historical data of all photovoltaic strings of various types of inverters connected to the photovoltaic power station, as well as metadata of the photovoltaic power station design; wherein the metadata includes: inverter model, longitude and latitude information of the photovoltaic power station, all tilt angle and orientation combinations registered for the photovoltaic power station, and historical data, including: historical current data, historical voltage data.

[0057] Specifically, a distributed photovoltaic power station is usually equipped with multiple inverters, each of which is connected to multiple photovoltaic strings. A photovoltaic string is a circuit unit formed by connecting photovoltaic components (solar panels) in series. In the embodiment of the present invention, the photovoltaic power station includes M types of inverters, and the i-th type of inverter has N i The number of strings of each inverter of the i-th type is S i, the length of the sequence collected by each photovoltaic string is the same and is set to T. Then the sequence of current and voltage of the kth string of the jth inverter of the i-th type with a step length of T can be expressed as:

[0058] I i,j,k = {I i,j,k (1),…,I i,j,k (T)};

[0059] V i,j,k = {V i,j,k (1),…,V i,j,k (T)};

[0060] Where i represents the inverter type, i = {1, 2, ..., M}, with a total of M types; j represents the jth inverter, j = {1, 2, ..., N i}, N represents the number of inverters; k represents the kth photovoltaic string, k={1,2,…,S i}, S represents the number of PV strings; T represents the length of the sequence.

[0061] The longitude and latitude information of the photovoltaic power station in the metadata of the embodiment of the present invention is represented by (lon, lat), and all the tilt angle combinations registered by the photovoltaic power station are represented by {(A i ,B i )|1≤i≤G}, where A i and B i They represent the inclination angle and direction of the i-th combination respectively, and the number of combinations of all inclination angles and directions is G.

[0062] S102, selecting photovoltaic strings in normal operation based on historical data, and calculating the power generation capacity of each photovoltaic string.

[0063] In order to accurately match the tilt angle, the embodiment of the present invention must use a fault detection algorithm based on historical data to ensure that the strings used are fault-free. No calculation is performed for faulty inverters. The fault detection algorithm is a relatively mature algorithm and no specific limit is imposed here. The process of calculating the power generation capacity of each photovoltaic string includes:

[0064] S1021, based on historical data of photovoltaic strings connected to inverters of the same type and operating normally, calculate the average power of each photovoltaic string connected to the inverter of the same type, and calculate the power generation capacity of each photovoltaic string based on the average power of each photovoltaic string;

[0065] Specifically, first calculate the power value of each photovoltaic string connected to each type of inverter. There are N inverters of type i. i There are N corresponding photovoltaic strings. i ×S iSelect the strings with actual current and calculate the point-by-point power value of each photovoltaic string. For the kth string of the jth inverter, the corresponding power is: P i,j,k =I i,j,k V i,j,k There are two cases for calculating the average power of photovoltaic strings:

[0066] ① When the power station has historical measured irradiance or numerical weather forecast irradiance (including direct irradiance, diffuse irradiance and horizontal total irradiance), the corresponding historical current and voltage data can be used directly. At this time, the average power of the string data on all days can be directly calculated:

[0067] ② In the absence of historical measured irradiance and numerical weather forecast irradiance at the power station, the irradiance value under theoretical clear sky conditions can be calculated based on the timestamp information corresponding to the historical current and voltage data. In order to achieve a higher degree of matching, only the data under clear sky conditions are used as a reference in the calculation process instead of the data under all meteorological conditions.

[0068] For photovoltaic strings that lack historical irradiance data and numerical weather forecast irradiance, the embodiments of the present invention can calculate the irradiance value under theoretical sunny conditions based on the timestamp information corresponding to the historical current and voltage data, and further determine the number of sunny days by judging the peak power and power volatility, and finally calculate the average power of sunny days. This method embodies strong flexibility, so that even in the unfavorable situation of missing irradiance data, the power generation capacity of the corresponding photovoltaic strings can still be calculated relatively scientifically, ensuring that the entire calculation process can cover all photovoltaic strings without omissions due to data shortcomings.

[0069] The embodiment of the present invention selects sunny day data by judging two indicators, namely, peak power and power volatility of a day in historical data, and the process is as follows:

[0070] 1. Get the peak power on day d And judge Is it greater than the maximum power value in the preset historical time period with a preset multiple? If so, the power peak value on the dth day meets the requirement;

[0071] 2. Get the mean of the absolute value of the first-order difference of power on day d And judge whether it is less than the average of the absolute values ​​of the first-order differences of the minimum power in the preset historical time period with a preset multiple; if so, it is determined that the power volatility of the dth day meets the requirements;

[0072] 3. The number of days that meet both the power peak and power fluctuation requirements is obtained as the number of sunny days.

[0073] The embodiment of the present invention comprehensively considers two important dimensions: peak power and power volatility during the day. On sunny days, solar radiation is usually relatively stable and sufficient, which will make the power of the photovoltaic strings show a higher peak and relatively stable change characteristics. Judging from these two aspects, it is more logically reasonable and rigorous to fit the actual performance of the photovoltaic string power generation on sunny days, and can more accurately select the days that meet the characteristics of sunny days. In a specific embodiment, the specific process is as follows:

[0074] 1) Determine the peak power of the day

[0075] For example, determine the peak power on day d Is it greater than 0.8P? max , where P max is the maximum power value in the preset historical time period; if yes, the power peak value on the dth day meets the requirement. Assuming there are C data in one day, the data set can be calculated for T time steps to contain T / C days. The maximum power value on the d∈[1,T / C]th day is calculated as: The maximum power of the entire data set is Pmax = maxPi,j,k1,…,Pi,j,kT. Determine the peak power on day d Is it true? If so, the power peak value of this day meets the requirements, and we continue to judge the volatility of the power sequence of this day.

[0076] 2) Determine the volatility of the day

[0077] For example, using the mean of the absolute values ​​of the first-order differences of power on day d To measure the fluctuation of meteorological factors on that day, the greater the fluctuation of power due to meteorological factors, the greater the value. The calculation is: By judging Whether it is established is used to determine the volatility of power on that day.

[0078] Furthermore, the inverter model is i and the corresponding string has N i ×S i According to the power average of each photovoltaic string calculated in the previous step, these strings can be arranged in ascending order (or in descending order. In the embodiment of the present invention, the power average of each photovoltaic string is arranged in ascending order from small to large as an example). Then, the benchmark string of the inverter of this model is the photovoltaic string with the largest average power, which is calculated as follows:

[0079] The benchmark string has the strongest power generation capacity. The power generation capacity of other strings can be measured by dividing by the average power of the benchmark string. For the kth string of the jth inverter, its power generation capacity is calculated as:

[0080]

[0081] In the embodiment of the present invention, the photovoltaic string with the largest average power connected to each type of inverter is used as the benchmark string, and then the average power of other photovoltaic strings of the same type of inverter is compared with the corresponding benchmark string to characterize the power generation capacity. By setting up benchmarks and calculating ratios in this way, a relatively standardized measurement scale is provided for the power generation capacity of different photovoltaic strings, which facilitates intuitive comparison of the relative power generation capacity of each string under the same inverter type.

[0082] S1022, dividing the power generation capacity data of all photovoltaic strings connected to different types of inverters into a plurality of power generation capacity intervals according to the power generation capacity, and the number of the divided intervals is the same as the number of the inclination angle direction combinations.

[0083] The embodiment of the present invention calculates the power generation capacity of each photovoltaic string of the same type of inverter. For an inverter of model i, the power generation capacity of all its strings is expressed as: The power generation capacity of all strings of different types of inverters in a power station is expressed as:

[0084]

[0085] Arrange the photovoltaic strings connected to all inverters in the power station in ascending order according to their power generation capacity. The total number of photovoltaic strings in the power station is All the strings after arrangement can be expressed as:

[0086] Q o = sort(Q) = {q1,…,q H};

[0087] Among them, sort() represents the ascending order operation, q1 and q H They are respectively the strings with the smallest and largest generating capacities in the power station.

[0088] The number of intervals is the same as the number of inclination angle combinations, which is G. The length of each interval of power generation capacity is: The data range of the g∈[1,G]th interval can be expressed as [q1+(g-1)L,q1+gL], and the power generation capacity of all the arranged strings is divided into different intervals according to their size: {[q1+(g-1L,q1+gL|1≤g≤G}.

[0089] S103, calculating the theoretical irradiation potential of all inclination angle combinations in the metadata.

[0090] Specifically, different tilt angle combinations correspond to different placement methods of photovoltaic panels. This difference will directly affect the irradiance received by the photovoltaic panels. Figure 2 As shown, the change of theoretical total irradiance at different inclination angles under the same meteorological conditions on a certain day is shown. The irradiance in meteorology is usually calculated for horizontal ground, and a conversion model is required to convert the irradiance of the horizontal ground to the total irradiance of the inclined surface. Therefore, the embodiment of the present invention calculates the theoretical irradiation potential of all inclination angle combinations through the location and meteorological data of the photovoltaic power station. Specifically:

[0091] 1) Calculate extraterrestrial irradiance: Extraterrestrial irradiance reflects the energy from the sun that reaches the earth's surface without the influence of the atmosphere. Use the Spencer model of the pvlib library to calculate the extraterrestrial irradiance at a specified location for a period of time.

[0092] 2) Calculate the sun's position: Use the Solar Position Algorithm (SPA) to input the longitude and latitude loc (Lon, lat) and the corresponding time t to calculate the solar zenith angle Z and solar azimuth angle A at time t: [Z, A] = SPA (loc (Lon, lat), t).

[0093] 3) Calculate the total irradiance of the inclined surface, divided into two scenarios:

[0094] ① For the case of existing measured irradiance of power stations or numerical weather forecast (NWP) irradiance, the existing irradiance can be directly input into the conversion model to calculate the total irradiance of the inclined surface.

[0095] ② In the absence of historical irradiance data and numerical weather forecast (NWP) irradiance, the Ineichen clear sky irradiance model of the pvlib library is used (the pvlib library is a Python library for photovoltaic system analysis, in which the Ineichen clear sky irradiance model is a model for calculating solar irradiance under clear sky conditions) to calculate the theoretical clear sky irradiance for the time period corresponding to the historical sunny days (the number of sunny days obtained in step a1).

[0096] The irradiance data, extraterrestrial irradiance, solar position, time, inclination, and orientation are further input into the Perez model of the pvlib library (the pvlib library is a Python library for photovoltaic system analysis, in which the Perez model is mainly used to calculate the anisotropic diffuse component of solar radiation, which can more accurately estimate the amount of solar radiation received on the inclined plane) to calculate the total irradiance of the inclined plane for each inclination angle and orientation combination (Plane of Array Irradiance). Taking the existing irradiance as an example, the total irradiance of the inclined plane is calculated:

[0097]

[0098] The embodiment of the present invention comprehensively considers the latitude and longitude information of the photovoltaic power station, the position of the sun, the irradiance data, the tilt direction, time and other factors. These factors are interrelated and have a key impact on the irradiation received by the photovoltaic string. By fully incorporating and calculating them, the total irradiance of the inclined surface of each tilt direction combination finally obtained can more scientifically and accurately reflect the actual theoretical irradiation potential, laying a solid foundation for subsequent precise matching and tilt direction identification.

[0099] Furthermore, the irradiation potential corresponding to all inclination angle combinations is Sort them in ascending order (the sorting method is the same as the sorting method of the average power of the photovoltaic strings), and the sorted sequence is: F o ={f1,…,f G}, where f1,f G Represent the minimum and maximum irradiation potentials respectively, and their corresponding inclination angles θ and τ can be expressed as: {(θ1,τ1),…,(θ G ,τ G )}.

[0100] The embodiment of the present invention sorts the irradiation potentials corresponding to all inclination orientation combinations according to numerical values, and the sorting method is the same as the method of sorting the average power of photovoltaic strings. When the power generation capacity of the photovoltaic strings is subsequently matched with the theoretical irradiation potential, the same sorting method enables the two to be more conveniently and intuitively matched, making it easy to quickly and accurately find the inclination orientation combination that best matches the power generation capacity of each photovoltaic string, which helps to improve the efficiency and accuracy of the entire inclination orientation identification process.

[0101] S104, matching the power generation capacity of each photovoltaic string with the theoretical irradiation potential to obtain a photovoltaic string inclination direction identification result.

[0102] Specifically, under the same hardware conditions, a string with stronger power generation capacity corresponds to a greater irradiance. The magnitude of the irradiance depends on the inclination and orientation of the string installation. The optimal inclination and orientation correspond to the maximum irradiance. The embodiment of the present invention sorts the power generation capacity of each photovoltaic string, and matches each photovoltaic string with the inclination orientation combination with the same irradiation potential ranking in the sorting order; after the matching is completed, all photovoltaic strings connected to all models of inverters in the photovoltaic power station correspond to a inclination orientation value, and the photovoltaic string inclination orientation recognition result is obtained.

[0103] Specifically, it will be in the g range of power generation capacity ranking [q G +(g-1)L,q G +gL] and the combination of the inclination angle with the highest irradiation potential (θ g ,τg ) for matching, where g∈[1,G]. All intervals are matched with corresponding inclination directions in order. After the matching is completed, all strings of all inverter models in the power station correspond to a inclination direction value (θ g ,τ g ), g∈[1,G], realizing the automatic allocation of the inclination angles of all strings.

[0104] The matching method adopted in the embodiment of the present invention utilizes the basis of sorting the power generation capacity and irradiation potential respectively, so that the two can be associated in an orderly and corresponding manner. Since the sorting process itself is based on the scientific analysis and arrangement of relevant data, through such sorting and matching, the photovoltaic strings can be accurately associated with the inclination direction combination that best matches their power generation performance, which greatly improves the accuracy of matching and reduces the occurrence of mismatches, thereby providing a strong guarantee for obtaining reliable inclination direction identification results.

[0105] In a specific embodiment, the embodiment of the present invention provides a method for adaptively identifying the inclination angle of a photovoltaic string, such as Figure 3 As shown in the figure, by obtaining the historical data of all photovoltaic strings connected to various types of inverters in the photovoltaic power station and the metadata of the photovoltaic power station design, comprehensive analysis is carried out on various key information, so that the final identification result can be based on a more comprehensive data foundation, which is helpful to improve the accuracy of the inclination direction identification. Accurately identifying the inclination direction of the photovoltaic strings can help the operation and maintenance personnel to better understand whether the actual layout of each part of the power station is consistent with the optimal light receiving conditions, and then they can make targeted adjustments and optimizations to the unreasonable inclination direction, thereby improving the power generation efficiency of the entire photovoltaic power station and providing a strong basis for the decision-making of the long-term stable and efficient operation of the power station.

[0106] In this embodiment, a photovoltaic string tilt direction adaptive identification system is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be repeated hereafter. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the system described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0107] This embodiment provides an adaptive identification system for the inclination angle of a photovoltaic string. Figure 4 As shown, including:

[0108] The data acquisition module 401 is used to acquire the historical data of all photovoltaic strings connected to various types of inverters in the photovoltaic power station, as well as the metadata of the photovoltaic power station design; wherein the metadata includes: the longitude and latitude information of the photovoltaic power station, all the tilt angle and orientation combinations registered by the photovoltaic power station, and the historical data, including: historical current data and historical voltage data;

[0109] The power generation capacity calculation module 402 is used to select the photovoltaic strings in normal operation based on the historical data and calculate the power generation capacity of each photovoltaic string;

[0110] The irradiation data acquisition module 403 is used to calculate the theoretical irradiation potential of all inclination angle combinations in the metadata;

[0111] The inclination direction identification module 404 is used to match the power generation capacity of each photovoltaic string with the theoretical irradiation potential to obtain the photovoltaic string inclination direction identification result.

[0112] In some optional implementations, the power generation capacity calculation module 402 includes:

[0113] A power generation capacity calculation unit, used to calculate the average power size of each photovoltaic string connected to the same type of inverter based on historical data of photovoltaic strings connected to the same type of inverter in normal operation, and calculate the power generation capacity of each photovoltaic string based on the average power size of each photovoltaic string;

[0114] The power generation capacity interval division unit is used to divide the power generation capacity data of all photovoltaic strings connected to different types of inverters into multiple power generation capacity intervals according to the power generation capacity, and the number of divided intervals is the same as the number of inclination angle direction combinations.

[0115] In some optional implementations, the historical data further includes: historical irradiance data; a power generation capacity interval division unit, including:

[0116] The power calculation subunit is used to calculate the power value of each photovoltaic string connected to each type of inverter;

[0117] A first average power calculation subunit is used to obtain the average power of all days using the calculated power value for the photovoltaic strings with historical irradiance data or numerical weather forecast irradiance;

[0118] The second average power calculation subunit, for photovoltaic strings lacking historical irradiance data and numerical weather forecast irradiance, calculates the irradiance value under theoretical sunny conditions based on the timestamp information corresponding to the historical current data and the historical voltage data, determines the number of sunny days by judging the peak power and power fluctuation of one day in the historical data, and calculates the average power of sunny days;

[0119] The benchmark string acquisition subunit is used to arrange the calculated average power of each photovoltaic string according to the numerical value, and take the photovoltaic string with the largest average power connected to the same model inverter as the benchmark string;

[0120] The power generation capacity calculation unit is used to represent the power generation capacity by the ratio of the average power of other photovoltaic strings connected to the same type of inverter to the corresponding benchmark string.

[0121] In some optional implementations, determining the number of sunny days by judging the peak power and power fluctuation of a day in historical data includes:

[0122] Get the peak power on day d And judge Is it greater than the maximum power value in the preset historical time period with a preset multiple? If so, the power peak value on the dth day meets the requirement;

[0123] Get the mean of the absolute value of the first-order difference of power on day d And judge whether it is less than the average of the absolute values ​​of the first-order differences of the minimum power in the preset historical time period with a preset multiple; if so, it is determined that the power volatility of the dth day meets the requirements;

[0124] The number of days that meet both the power peak and power fluctuation requirements is obtained as the number of sunny days.

[0125] In some optional implementations, the irradiation data acquisition module 403 includes:

[0126] A first calculation unit, used to calculate the extraterrestrial irradiance based on the longitude and latitude information of the photovoltaic power station, and calculate the sun's position based on the longitude and latitude information of the photovoltaic power station;

[0127] A second calculation unit is used to calculate the total irradiance of the inclined surface based on the historical irradiance data and time of the photovoltaic string for which the historical irradiance data or numerical weather forecast irradiance is available;

[0128] The third calculation unit is used to calculate the theoretical clear sky irradiance in the time period corresponding to the historical sunny day for the photovoltaic string that lacks the historical irradiance data and the numerical weather forecast irradiance;

[0129] A fourth calculation unit is used to obtain the total irradiance of the inclined surface for each inclination angle combination based on the irradiance data, the extraterrestrial irradiance, the sun's position, the time, and the inclination angle;

[0130] The irradiation potential sorting unit is used to sort the irradiation potential corresponding to all inclination angle combinations according to the numerical value, and the sorting method is the same as the sorting method of the average power of the photovoltaic strings.

[0131] In some optional implementations, the inclination direction identification module includes:

[0132] A matching unit, used to sort the power generation capacity of each photovoltaic string, and match each photovoltaic string with a tilt angle orientation combination with the same irradiation potential ranking according to the sorting order;

[0133] The identification unit is used to match all photovoltaic strings connected to all types of inverters in the photovoltaic power station to a corresponding tilt angle direction value after the matching is completed, and obtain the photovoltaic string tilt angle direction identification result.

[0134] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0135] The adaptive identification system for the inclination direction of the photovoltaic string in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0136] The embodiment of the present invention also provides a computer device having the above Figure 4 An adaptive identification system for the inclination orientation of a photovoltaic string is shown.

[0137] See also Figure 5 , Figure 5 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 5 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 5 A processor 10 is taken as an example.

[0138] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0139] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0140] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0141] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0142] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0143] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor central control system or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0144] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0145] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for adaptively identifying the inclination angle of a photovoltaic string, characterized in that: include: Obtain the historical data of all photovoltaic strings connected to various types of inverters in the photovoltaic power station, as well as the metadata of the photovoltaic power station design; wherein the metadata includes: inverter model, longitude and latitude information of the photovoltaic power station, and all tilt angle and orientation combinations registered by the photovoltaic power station; the historical data includes: historical current data and historical voltage data; Filter out the PV strings that are in normal operation based on historical data, and calculate the power generation capacity of each PV string; Calculate the theoretical irradiation potential for all combinations of inclination angles in the metadata; The power generation capacity of each photovoltaic string is matched with the theoretical irradiation potential to obtain the photovoltaic string inclination direction identification result.

2. The method according to claim 1, characterized in that The process of calculating the power generation capacity of each photovoltaic string includes: Based on the historical data of PV strings connected to the same type of inverters and operating normally, the average power of each PV string connected to the same type of inverter is calculated, and the power generation capacity of each PV string is calculated based on the average power of each PV string; The power generation capacity data of all photovoltaic strings connected to different types of inverters are divided into multiple power generation capacity intervals according to the power generation capacity, and the number of divided intervals is the same as the number of inclination angle direction combinations.

3. The method according to claim 2, characterized in that The historical data also includes: historical irradiance data; The method calculates the average power of each photovoltaic string connected to the same type of inverter based on the historical data of the photovoltaic strings connected to the same type of inverter in normal operation, and calculates the power generation capacity of each photovoltaic string based on the average power of each photovoltaic string, including: Calculate the power value of each photovoltaic string connected to each type of inverter; For PV strings with historical irradiance data or numerical weather forecast irradiance, the calculated power values ​​are used to obtain the average power for all days; For PV strings that lack historical irradiance data and numerical weather forecast irradiance, the irradiance value under theoretical sunny conditions is calculated based on the timestamp information corresponding to the historical current data and historical voltage data. The number of sunny days is determined by judging the peak power and power fluctuation of a day in the historical data, and the average power of sunny days is calculated. Arrange the calculated average power of each PV string by numerical value, and take the PV string with the largest average power connected to the same inverter model as the benchmark string; The power generation capacity is represented by the ratio of the average power of other PV strings connected to the same model of inverter to the corresponding benchmark string.

4. The method according to claim 3, characterized in that The method of determining the number of sunny days by judging the peak power and power fluctuation of a day in historical data includes: Get the peak power on day d And judge Is it greater than the maximum power value in the preset historical time period with a preset multiple? If so, the power peak value on the dth day meets the requirement; Get the mean of the absolute value of the first-order difference of power on day d And judge whether it is less than the average of the absolute values ​​of the first-order differences of the minimum power in the preset historical time period with a preset multiple; if so, it is determined that the power volatility of the dth day meets the requirements; The number of days that meet both the power peak and power fluctuation requirements is obtained as the number of sunny days.

5. The method according to claim 3, characterized in that: The theoretical irradiance potential for all combinations of inclination angles in the calculation metadata includes: Calculate the extraterrestrial irradiance based on the longitude and latitude information of the photovoltaic power station, and calculate the sun's position based on the longitude and latitude information of the photovoltaic power station; For PV strings with historical irradiance data or numerical weather forecast irradiance, the total irradiance on the inclined surface is calculated based on the historical irradiance data and time of the PV strings; For PV strings that lack historical irradiance data and numerical weather forecast irradiance, calculate the theoretical clear sky irradiance for the time period corresponding to historical sunny days; Based on irradiance data, extraterrestrial irradiance, solar position, time, and inclination direction, the total irradiance of the inclined surface for each inclination direction combination is obtained; The irradiation potentials corresponding to all tilt angle combinations are sorted according to numerical values, and the sorting method is the same as the sorting method of the average power of the photovoltaic strings.

6. The method according to claim 5, characterized in that The power generation capacity of each photovoltaic string is matched with the theoretical irradiation potential to obtain the photovoltaic string inclination direction identification result, including: Sorting the power generation capacity of each photovoltaic string, and matching each photovoltaic string with a tilt angle orientation combination having the same ranking of irradiation potential according to the sorting order; After the matching is completed, all photovoltaic strings connected to all types of inverters in the photovoltaic power station correspond to a tilt angle direction value, and the photovoltaic string tilt angle direction identification result is obtained.

7. An adaptive identification system for the inclination angle of a photovoltaic string, characterized in that: include: A data acquisition module is used to acquire the historical data of all photovoltaic strings connected to various types of inverters in the photovoltaic power station, as well as metadata of the photovoltaic power station design; wherein the metadata includes: inverter model, longitude and latitude information of the photovoltaic power station, and all tilt angle and orientation combinations registered by the photovoltaic power station; the historical data includes: historical current data and historical voltage data; A power generation capacity calculation module is used to select photovoltaic strings in normal operation based on historical data and calculate the power generation capacity of each photovoltaic string; Irradiation data acquisition module, used to calculate the theoretical irradiation potential of all inclination angle combinations in metadata; The inclination direction recognition module is used to match the power generation capacity of each photovoltaic string with the theoretical irradiation potential to obtain the inclination direction recognition result of the photovoltaic string.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for adaptively identifying the inclination orientation of a photovoltaic string according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for adaptively identifying the inclination angle orientation of a photovoltaic string according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises computer instructions, wherein the computer instructions are used to enable a computer to execute the method for adaptively identifying the inclination angle orientation of a photovoltaic string according to any one of claims 1 to 6.

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