Photovoltaic direct current arc detection method, device, medium and equipment

Abstract

The invention discloses a photovoltaic direct current arc detection method and device, a medium and equipment, and relates to the technical field of fault diagnosis of a new energy power generation system. The photovoltaic direct current arc detection method comprises the following steps: based on electrical characteristic quantities corresponding to M photovoltaic inverters extracted from a photovoltaic inverter data transmission network, obtaining M first characteristic vectors; according to the M first feature vectors, determining a first reference vector associated with the M photovoltaic inverters; calculating a difference value between the M first feature vectors and the first reference vector; comparing the difference value with a first threshold value to obtain M comparison results associated with the M photovoltaic inverters; and according to the M comparison results, judging whether a photovoltaic inverter in the M photovoltaic inverters generates a direct current arc or not for the first time. According to the scheme, the accuracy of judging whether the photovoltaic inverter generates the direct-current arc or not can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fault diagnosis of new energy power generation systems, and in particular to a photovoltaic direct current arc detection method, device, medium and equipment. Background Art

[0002] At present, solar photovoltaic systems have been widely used due to their advantages of no pollution to the environment, high efficiency of energy conversion and high space utilization.

[0003] However, during the long-term operation of the photovoltaic system, its lines may age due to weathering in the external environment, which may lead to DC arcs. Once a DC arc is generated, it is usually difficult to extinguish naturally, and the temperature generated by the DC arc is enough to ignite surrounding materials, which may further cause failures in the photovoltaic system and cause huge economic losses. Therefore, detecting DC arcs in photovoltaic systems is crucial to preventing fires and protecting the safety of personnel and equipment, and is an important measure to improve the overall reliability and safety of photovoltaic systems.

[0004] In the prior art, the main methods of photovoltaic DC arc detection are divided into two categories: one is to detect DC arc by detecting physical phenomena such as light and heat generated by DC arc, but this method is easily interfered by the external environment, and because it is difficult to predict the location of the fault arc in advance, the sensor installation position is not accurate and the arc detection effect is poor. The other is to extract the time domain and frequency domain characteristics of the current and voltage in the photovoltaic system and use artificial intelligence algorithms to determine the generation of DC arc, but due to the obvious differences in fault feature quantities under different voltages and the influence of noise, this method often has the phenomenon of misjudgment and missed judgment.

[0005] In summary, the existing technology has poor arc detection effect when detecting photovoltaic DC arcs. Summary of the invention

[0006] Based on this, it is necessary to provide a photovoltaic DC arc detection method, device, medium and equipment to address the above technical problems.

[0007] The present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a photovoltaic DC arc detection method, the method comprising:

[0009] Based on the electrical characteristic quantities corresponding to the M photovoltaic inverters extracted from the photovoltaic inverter data transmission network, M first characteristic vectors are obtained;

[0010] Determining a first reference vector associated with the M photovoltaic inverters according to the M first eigenvectors;

[0011] Calculating the difference between the M first eigenvectors and the first reference vector;

[0012] Comparing the difference with a first threshold value to obtain M comparison results associated with the M photovoltaic inverters;

[0013] According to the M comparison results, it is first determined whether any photovoltaic inverter among the M photovoltaic inverters generates a DC arc.

[0014] Furthermore, the electrical characteristic quantities corresponding to the M photovoltaic inverters extracted from the photovoltaic inverter data transmission network are used to obtain M first characteristic vectors, which specifically include:

[0015] Obtaining data types of electrical characteristic quantities corresponding to the M photovoltaic inverters;

[0016] According to the data type, the electrical characteristic quantities corresponding to the M photovoltaic inverters are classified respectively to obtain M groups of standard electrical characteristic quantities;

[0017] The M groups of standard electrical characteristic quantities are respectively implanted into arrays according to the data types to obtain the M first characteristic vectors.

[0018] Furthermore, before obtaining the data types of the electrical characteristic quantities corresponding to the M photovoltaic inverters, the method further includes:

[0019] Collecting electrical characteristic quantities corresponding to the M photovoltaic inverters through a sliding window to obtain electrical characteristic quantities corresponding to the M photovoltaic inverters;

[0020] Based on the number of photovoltaic modules in the photovoltaic array connected to the M photovoltaic inverters, and the series or parallel connection mode, the electrical characteristic quantities corresponding to the M photovoltaic inverters are standardized.

[0021] Further, determining a first reference vector associated with the M photovoltaic inverters according to the M first eigenvectors specifically includes:

[0022] Determine any two first eigenvectors among the M first eigenvectors as initial cluster centroids, and determine the remaining first eigenvectors as first eigenvectors to be clustered;

[0023] Calculating the distance between each of the first feature vectors to be clustered and the centroid of the initial cluster;

[0024] According to the distance, assigning the first feature vector to be clustered to the initial cluster centroid;

[0025] Calculating an average value of the initial cluster centroids, and updating the initial cluster centroids according to the average value of the initial cluster centroids;

[0026] When the number of times the initial cluster centroids are updated reaches a preset number, the segmentation plane between the cluster centroids is determined as the first reference vector.

[0027] Further, the first determining, based on the M comparison results, whether any photovoltaic inverter among the M photovoltaic inverters generates a DC arc specifically includes:

[0028] When a difference corresponding to any one or more comparison results among the M comparison results is greater than the first threshold, determining for the first time that the photovoltaic inverter associated with any one or more comparison results generates a DC arc;

[0029] When the difference corresponding to any one or more comparison results among the M comparison results is not greater than the first threshold, the photovoltaic inverter associated with any one or more comparison results is determined as not generating a DC arc.

[0030] Further, after determining for the first time whether any photovoltaic inverter generates a DC arc among the M photovoltaic inverters according to the M comparison results, the method further includes:

[0031] Sending a first alarm signal through the photovoltaic inverter that is first determined to have generated a DC arc;

[0032] After the time when the photovoltaic inverter that is first determined to generate a DC arc sends out a first alarm signal reaches a preset time, adjusting the power parameters of the photovoltaic inverter that is first determined to generate a DC arc;

[0033] Calculating, based on the power parameter, a second eigenvector associated with the photovoltaic inverter that is first determined to generate a DC arc;

[0034] Based on the second eigenvector, calculating a second reference vector associated with the second eigenvector;

[0035] Based on the second reference vector and a preset threshold, it is determined whether the photovoltaic inverter that is first determined to generate a DC arc generates a DC arc.

[0036] Further, after judging whether the photovoltaic inverter that is first determined to generate a DC arc generates a DC arc according to the second reference vector and a preset threshold, the method further includes:

[0037] In the case where the photovoltaic inverter that is first determined to have generated a DC arc generates a DC arc, a second alarm signal is issued and an arc extinguishing operation is performed;

[0038] In the case that the photovoltaic inverter that is first determined to generate a DC arc does not generate a DC arc, a misjudgment signal is issued.

[0039] In a second aspect, the present invention provides a photovoltaic DC arc detection device, comprising:

[0040] A first determination module is used to obtain M first feature vectors based on electrical feature quantities corresponding to M photovoltaic inverters extracted from a photovoltaic inverter data transmission network;

[0041] A second determination module is used to: determine a first reference vector associated with the M photovoltaic inverters according to the M first characteristic vectors;

[0042] A calculation module, used to: calculate the difference between the M first eigenvectors and the first reference vector;

[0043] A comparison module, used to: compare the difference with a first threshold value to obtain M comparison results associated with the M photovoltaic inverters;

[0044] The judgment module is used to: determine for the first time whether any photovoltaic inverter among the M photovoltaic inverters generates a DC arc according to the M comparison results.

[0045] The present invention provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the photovoltaic DC arc detection method is implemented.

[0046] The present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the photovoltaic DC arc detection method is implemented when the processor executes the program.

[0047] The at least one technical solution adopted by the present invention can achieve the following beneficial effects:

[0048] The present invention first extracts electrical characteristic quantities corresponding to M photovoltaic inverters from a photovoltaic inverter data transmission network to obtain M first characteristic vectors. Then, based on the M first characteristic vectors, a first reference vector associated with the M photovoltaic inverters is determined, and the difference between the M first characteristic vectors and the first reference vector is calculated. Then, the difference is compared with a first threshold value to obtain M comparison results associated with the M photovoltaic inverters. Finally, based on the M comparison results, it is first determined whether any photovoltaic inverter among the M photovoltaic inverters generates a DC arc.

[0049] The present invention detects DC arcs based on the collected electrical characteristic quantities of each photovoltaic inverter, thereby reducing the error of the prior art in DC arc detection of physical phenomena such as light and heat generated by DC arcs by deploying light sensors and heat sensors in the photovoltaic inverter data transmission network, and avoiding the influence of the external environment on the detection of whether the photovoltaic inverter generates a DC arc.

[0050] Since the electrical characteristic quantities of photovoltaic inverters under different operating environments are obviously different, the detection of DC arcs often results in misjudgment and omission. The present invention detects DC arcs based on the electrical characteristic quantities corresponding to multiple photovoltaic inverters collected under the same operating environment, thereby avoiding the error of the electrical characteristic quantities collected under different operating environments of photovoltaic inverters, and improving the accuracy of judging whether multiple photovoltaic inverters generate DC arcs under the same operating environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0052] Figure 1 A schematic diagram of a photovoltaic DC arc detection method provided by the present invention;

[0053] Figure 2 A schematic diagram of a photovoltaic DC arc detection device provided by the present invention;

[0054] Figure 3 A schematic diagram of a computer device for implementing a photovoltaic DC arc detection method provided by the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only 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 ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0056] The server mentioned in the present invention can be a server set on a business platform, or a device such as a desktop computer, a laptop computer, etc. that can execute the solution of the present invention. For the convenience of description, the following description is only based on the server as the execution subject. The following is a detailed description of the technical solutions provided by various embodiments of the present invention in conjunction with the accompanying drawings.

[0057] Figure 1The present invention is a schematic flow chart of a photovoltaic DC arc detection method, which specifically includes the following steps:

[0058] S10: Obtain M first feature vectors based on electrical feature quantities corresponding to M photovoltaic inverters extracted from the photovoltaic inverter data transmission network.

[0059] In this embodiment, the electrical characteristic quantities contained in the M photovoltaic inverters can be extracted through a pre-established photovoltaic inverter data transmission network. The photovoltaic inverter data network is established by, but is not limited to, using the inverter's own communication function to establish a data transmission network or by using an external communication module to establish a data transmission network. The communication methods used include, but are not limited to, optical fiber, 4G, Wireless Fidelity (Wi-Fi), Zigbee (ZigBee technology is a short-distance, low-power wireless communication technology), etc.

[0060] S20: Determine a first reference vector associated with the M photovoltaic inverters according to the M first eigenvectors.

[0061] In this embodiment, the method for determining the first reference vector includes but is not limited to: calculating the average value of the first feature vectors of the M photovoltaic inverters in the first n frames at the time of arc detection, and using the calculation result as the first reference vector.

[0062] S30: Calculate the difference between the M first eigenvectors and the first reference vector.

[0063] In this embodiment, the difference between the M first feature vectors and the first reference vector is calculated by the server.

[0064] S40: Compare the difference with a first threshold value to obtain M comparison results associated with the M photovoltaic inverters.

[0065] In this embodiment, the server is used to compare the difference with the first threshold value to obtain M comparison results associated with the M photovoltaic inverters.

[0066] Optionally, the calculation method of the first threshold includes but is not limited to: taking an average value X% of the M difference vectors as the first threshold, and the specific value of X can be determined based on experience, experiments, etc.

[0067] S50: According to the M comparison results, it is first determined whether any photovoltaic inverter among the M photovoltaic inverters generates a DC arc.

[0068] In this embodiment, the first determination of whether the M photovoltaic inverters generate a DC arc is as follows: if the difference exceeds the first threshold, it is determined that the corresponding photovoltaic inverter is suspected of generating a DC arc.

[0069] based on Figure 1 A photovoltaic DC arc detection method is shown, firstly, electrical characteristic quantities corresponding to M photovoltaic inverters are extracted from a photovoltaic inverter data transmission network to obtain M first characteristic vectors. Then, based on the M first characteristic vectors, a first reference vector associated with the M photovoltaic inverters is determined, and the difference between the M first characteristic vectors and the first reference vector is calculated. Then, the difference is compared with a first threshold value to obtain M comparison results associated with the M photovoltaic inverters, and finally, based on the M comparison results, it is determined for the first time whether there is a photovoltaic inverter generating a DC arc among the M photovoltaic inverters. The present invention avoids the influence of the environment on the DC arc detection by vectorizing the electrical characteristic quantity, and can improve the accuracy of judging whether a photovoltaic inverter generates a DC arc.

[0070] When applying a photovoltaic DC arc detection method provided by the present invention, it is not necessary to Figure 1 The steps are executed in the order shown. The specific execution order of the steps can be determined according to needs, and the present invention does not limit this.

[0071] In addition, in one or more embodiments of the present invention, the obtaining of M first feature vectors based on the extracted electrical feature quantities contained in the M photovoltaic inverters specifically includes:

[0072] S101: Obtain data types of electrical characteristic quantities corresponding to the M photovoltaic inverters.

[0073] Optionally, before obtaining the data type of the electrical characteristic quantities corresponding to the M photovoltaic inverters, the electrical characteristic quantities corresponding to the M photovoltaic inverters are standardized. The method of standardizing the electrical characteristic quantities corresponding to the M photovoltaic inverters includes but is not limited to: comprehensively considering the number of photovoltaic modules in the photovoltaic array connected to the inverter and the series-parallel connection, and standardizing the electrical characteristic quantities. Based on the above method of standardizing the electrical characteristic quantities corresponding to the M photovoltaic inverters, the influence of different combinations of dimensions and photovoltaic modules on the electrical characteristic quantities can be eliminated.

[0074] S102: Classifying the electrical characteristic quantities corresponding to the M photovoltaic inverters according to the data types to obtain M groups of standard electrical characteristic quantities.

[0075] In this embodiment, the data types include but are not limited to: current variance value, current spectrum energy and energy entropy, current wavelet energy entropy, wherein each group of electrical characteristic quantities includes the above data types.

[0076] S103: respectively embedding the M groups of standard electrical characteristic quantities into an array according to the data type to obtain the M first characteristic vectors.

[0077] In this embodiment, the current variance value, the current spectrum energy and energy entropy, and the current wavelet energy entropy are put into an array in order as feature quantities, as the first feature vector in, represents the first eigenvector of the inverter numbered n at time t, t 1n_1 Represents the first component of the first eigenvector of inverter numbered n.

[0078] This embodiment standardizes the electrical characteristic quantities corresponding to the photovoltaic inverter, classifies the electrical characteristic quantities according to different data types, and then sequentially implants the classified electrical characteristic quantities into an array to obtain a first characteristic vector, thereby reducing the calculation errors caused by multiple data types.

[0079] In addition, in one or more embodiments of the present invention, before acquiring the data types of the electrical characteristic quantities corresponding to the M photovoltaic inverters, the method further includes:

[0080] S1011: Collect electrical characteristic quantities corresponding to the M photovoltaic inverters through a sliding window to obtain electrical characteristic quantities corresponding to the M photovoltaic inverters:.

[0081] In this embodiment, a possible solution is to use a 10ms time sliding window to collect the electrical characteristic quantity of the photovoltaic inverter, so that one frame of electrical quantity data can be obtained every 10ms. According to actual needs, the time sliding window can also be changed to other time lengths. In this example, a sliding window is used to collect the current of the photovoltaic inverter. When the sliding window size is set to 10ms and the sampling frequency is 200kHz, each sampling group has a total of 2000 data, recorded as {I n}, n is from 1 to 2000.

[0082] S1012: Based on the number of photovoltaic modules in the photovoltaic array to which the M photovoltaic inverters are connected, and the series or parallel connection mode, the electrical characteristic quantities corresponding to the M photovoltaic inverters are standardized.

[0083] In this embodiment, the electrical characteristic quantities include but are not limited to: time domain, frequency domain, and time-frequency domain characteristic quantities of the current and voltage on the DC side of the photovoltaic inverter. Among them, the time domain characteristic quantities include but are not limited to: effective value, peak value, mean value and other parameters. The frequency domain characteristic quantities include but are not limited to: spectrum energy and spectrum energy entropy. The time-frequency domain characteristic quantities include but are not limited to: wavelet coefficients and wavelet entropy.

[0084] This embodiment collects data by sliding window, and different sliding window widths can be set according to actual needs, which can improve the richness of sampled data. In addition, when standardizing the electrical characteristic quantity, this embodiment takes into account the number of photovoltaic modules in the photovoltaic array and the series or parallel connection mode, which can eliminate the influence of different combinations of dimensions and photovoltaic modules on the electrical characteristic quantity.

[0085] In addition, in one or more embodiments of the present invention, determining the first reference vector associated with the M photovoltaic inverters according to the M first eigenvectors specifically includes:

[0086] S201: Determine any two first eigenvectors among the M first eigenvectors as initial cluster centroids, and determine the remaining first eigenvectors as first eigenvectors to be clustered.

[0087] S202: Calculate the distance between each of the first feature vectors to be clustered and the centroid of the initial cluster.

[0088] S203: Allocating the first feature vector to be clustered to the initial cluster centroid according to the distance.

[0089] S204: Calculate the average value of the initial cluster centroids, and update the initial cluster centroids according to the average value of the initial cluster centroids.

[0090] S205: When the number of times the initial cluster centroids are updated reaches a preset number, a segmentation plane between the cluster centroids is determined as the first reference vector.

[0091] In this embodiment, the K clustering algorithm is used to obtain the data based on multi-machine data. First, the number of cluster centers is determined, which is set to 2 in this method. M first eigenvectors are used as input data. First, two first eigenvectors are randomly selected as the initial cluster centroids, and the distance between each data point and the centroid of each cluster is calculated, and the data point is assigned to the nearest cluster. The average value of the data points of each cluster is calculated, and the cluster centroid is updated. Repeat the above process until the maximum number of iterations is reached. The segmentation planes of different clusters are used as the first reference vectors.

[0092] Optionally, in this embodiment, another method for calculating the first reference vector is: calculating an average value of first feature vectors of first M frames at the arc detection moment of M photovoltaic inverters, and using it as the first reference vector, where M≥1.

[0093] In addition, in one or more embodiments of the present invention, determining whether a photovoltaic inverter among the M photovoltaic inverters generates a DC arc specifically includes:

[0094] S501: When a difference corresponding to any one or more comparison results among the M comparison results is greater than the first threshold, determining for the first time that a photovoltaic inverter associated with the one or more comparison results generates a DC arc.

[0095] In this embodiment, the first determination that a DC arc is generated refers to being determined as suspected that a DC arc is generated.

[0096] S502: When a difference corresponding to any one or more comparison results among the M comparison results is not greater than the first threshold, determine that the photovoltaic inverter associated with any one or more comparison results does not generate a DC arc.

[0097] In this embodiment, the calculation method of the first threshold includes but is not limited to: taking the average value X% of the M difference vectors as the first threshold, and the specific value of X can be determined based on experience, experiments, etc.

[0098] Alternatively, another method for determining whether a PV inverter generates a DC arc is as follows:

[0099] From the M photovoltaic inverters, N photovoltaic inverters that need to be compared with the first characteristic vector are determined to obtain an inverter group, where N is not less than two.

[0100] In this embodiment, a possible photovoltaic inverter grouping scheme is as follows: photovoltaic inverters are grouped according to the similarity of the photovoltaic array operating environments, and N photovoltaic inverters with relatively high operating environment similarity are grouped into one group to obtain the inverter group.

[0101] In the inverter group, each photovoltaic inverter respectively multicasts its associated first characteristic vector to other photovoltaic inverters, so that any photovoltaic inverter in the inverter group obtains N first characteristic vectors associated with different photovoltaic inverters.

[0102] In this embodiment, each photovoltaic inverter does not need to copy multiple first feature vectors for transmission, but only needs to send one first feature vector associated with itself. The multicast network device (network device running the multicast routing protocol) will forward or copy the multicast data according to actual needs, so as to realize on-demand copying and on-demand transmission. In addition, the first feature vector is only sent to the photovoltaic inverters that join the inverter group, and the photovoltaic inverters that do not need the first feature vector will not receive the first feature vector. Through the above scheme, the utilization rate of network resources and the efficiency of each photovoltaic inverter in receiving the first feature vectors of other photovoltaic inverters can be improved.

[0103] Each of the photovoltaic inverters calculates a difference between the N first characteristic vectors associated with different photovoltaic inverters and the first reference vector.

[0104] In this embodiment, each inverter in the group calculates the difference between the N first eigenvectors it receives and the first reference vector. If the difference between the first eigenvector and the first reference vector of a certain inverter exceeds the first threshold, it is determined that the inverter is suspected of generating a DC arc, and the corresponding inverter sends a first alarm signal.

[0105] A possible solution is to calculate the difference between the N first eigenvectors and the first reference vector respectively to obtain N difference vectors. X% of the average value of the N difference vectors is used as the first threshold. If the difference exceeds the first threshold, it is determined that the corresponding inverter is suspected of generating a DC arc, and the corresponding inverter sends a first alarm signal. The specific value of X can be determined based on experience, experiments, etc.

[0106] For example, in this example, N is 3, and the three first eigenvectors and the first reference vector at time t are calculated. The difference of , we get 3 difference vectors, namely 120% of the average value of the three difference vectors is used as the first threshold value. When the difference exceeds 120% of the average value of the three difference vectors, it is determined that the corresponding inverter is suspected of generating a DC arc, and the corresponding inverter sends out a first alarm signal.

[0107] It is determined whether an arc is generated in the photovoltaic inverter according to the difference.

[0108] In this embodiment, each photovoltaic inverter in the group calculates the difference between the N first eigenvectors received by itself and the first reference vector. If the difference between the first eigenvector and the first reference vector of a photovoltaic inverter exceeds the first threshold, it is determined that the photovoltaic inverter is suspected of generating a DC arc.

[0109] The present invention can reduce the range of arc detection on the photovoltaic inverter through the above-mentioned scheme, and improve the efficiency of detecting whether the photovoltaic inverter generates an arc.

[0110] In addition, in one or more embodiments of the present invention, the first determining whether a photovoltaic inverter among the M photovoltaic inverters generates a DC arc according to the M comparison results further includes:

[0111] S601: issuing a first alarm signal through the photovoltaic inverter that is first determined to have generated a DC arc.

[0112] In this embodiment, the types of the alarm signal include but are not limited to: sound signal and optical signal.

[0113] S602: After the time when the photovoltaic inverter that is first determined to generate a DC arc sends out a first alarm signal reaches a preset time, adjust the power parameters of the photovoltaic inverter that is first determined to generate a DC arc.

[0114] S603: Calculate, based on the power parameter, a second eigenvector associated with the photovoltaic inverter that is first determined to generate a DC arc.

[0115] S604: Based on the second characteristic vector and a preset threshold, determine whether the photovoltaic inverter that is first determined to generate a DC arc generates a DC arc.

[0116] In this embodiment, scheme 1: at time t when the first alarm signal is received, the DC voltage of the photovoltaic inverter that is first determined to generate a DC arc is adjusted to change the DC voltage by ΔV. The photovoltaic inverter stores the first feature vector of the frame before and after time t, and records it as the second feature vector. Among them, for the selection of the first feature vector, a possible scheme is to select the variance of the voltage sampling value and the current sampling value as the first feature vector and put it into the second feature vector, and according to the change of the voltage and current variance value before and after the DC arc occurs, reasonably set the second threshold value to determine whether the photovoltaic inverter that is first determined to generate a DC arc generates a DC arc. The second threshold value here can be determined based on the variance value of the voltage and current when the DC arc occurs in the photovoltaic system, and can also be determined based on the second threshold value obtained by the photovoltaic inverter through receiving or storing.

[0117] Exemplarily, in this example, for the current variance value, 120% of the current variance value of the frame before the DC voltage adjustment moment can be selected as its second threshold; for the current spectrum energy and spectrum energy entropy, 130% of the average value of the current spectrum energy entropy of the previous two frames can be selected as its second threshold; for the wavelet energy entropy, 120% of the current spectrum energy entropy of the previous five frames can be selected as its second threshold.

[0118] The current variance calculation formula is as follows:

[0119]

[0120] Among them, σ 2 is the current variance value, n is the total number of current sampling points, I i is each current value sampled, and μ is the average value of the sampled current values.

[0121] Solution 2: At time t when the first alarm signal is received, the DC voltage of the photovoltaic inverter that is first determined to generate a DC arc is adjusted to change the DC voltage by ΔV. The photovoltaic inverter stores the first eigenvector of m frames before and p frames after time t, and records it as the second eigenvector, where m is not less than 2 and p is not less than 1. Among them, for the selection of the first eigenvector, a possible solution is: select the current spectrum energy entropy as the first eigenvector and put it into the second eigenvector, calculate the spectrum energy entropy of the current of m frames before the DC voltage is adjusted and the spectrum energy entropy of the current of m frames after the DC voltage is adjusted, and reasonably set the second threshold value according to the change of the current spectrum energy entropy before and after the DC arc occurs to determine whether the photovoltaic inverter that is first determined to generate a DC arc generates a DC arc. The second threshold value here can be determined based on the spectrum energy entropy of the current when the DC arc occurs in the photovoltaic system, or it can be determined based on the second threshold value obtained by the photovoltaic inverter through receiving or storing.

[0122] In this embodiment, the current variance value, the current spectrum energy and energy entropy, and the current wavelet energy entropy are put into an array in order as feature quantities, as the first feature vector in, represents the first eigenvector of the inverter numbered n at time t, t 1n_1 Represents the first component of the first eigenvector of inverter numbered n.

[0123] Exemplarily, in this example, the first feature vector of the ten frames before the arc detection time t is taken Calculate the average value of the first eigenvector of the first ten frames of the inverter in the group in, The average as the first reference vector.

[0124] Solution 3: At the time t when the first alarm signal is received, the DC voltage of the photovoltaic inverter that is first determined to have a DC arc is adjusted multiple times, so that it changes in sequence according to the time window shift time ΔV1, ΔV2, ..., ΔV n , that is, each time window changes ΔV1, ΔV2, …, ΔV n, where n is the number of times the DC voltage is adjusted, and n is not less than 2. The photovoltaic inverter stores the first eigenvector of the previous frame and the next frame of each DC voltage adjustment, and records it as the second eigenvector, with a total of n+1 second eigenvectors. Among them, for the selection of the first eigenvector, a possible solution is: select the wavelet energy entropy as the first eigenvector and put it into the second eigenvector, and according to the difference in the frequency spectrum changes at different stages of the DC arc (before the occurrence of the DC arc, when the DC arc occurs, and when the DC arc burns), reasonably set the second threshold to determine whether the photovoltaic inverter that is determined to generate the DC arc for the first time generates the DC arc. The second threshold here can be determined based on the frequency spectrum of the DC arc at different stages in the photovoltaic system, or it can be determined based on the second threshold obtained by the photovoltaic inverter through receiving or storing. In addition, different second threshold components need to be set for different second eigenvectors, and the second threshold components are placed in the array in the order of the corresponding second eigenvectors to form the second threshold. In this example, first, according to the number of photovoltaic modules in the photovoltaic array connected to the inverter and the series-parallel situation, the electrical quantity is converted into the photovoltaic array electrical quantity corresponding to the specific number of specific series-parallel situations. Then, Fourier transform is performed and spectrum energy and spectrum energy entropy are calculated. The standardized feature quantities are placed in an array in a certain order to obtain the first feature vector. Among them, the spectrum energy Ef is the current value I n Obtained by Fourier transform.

[0125] to {I n The spectrum amplitude after Fourier transform is recorded as {F k}, k is a positive integer and k Not more than 2000, where the spectrum energy E f The calculation formula is as follows:

[0126]

[0127] Where k2 is the upper frequency of the frequency band The corresponding frequency band number, K1 is the lower frequency of the frequency band F k 1 Corresponding frequency band number, F k is the amplitude of the kth point of the spectrum of the sampling group.

[0128] If the sampling frequency is 200kHz, the corresponding signal frequency upper limit is 100kHz. Each frequency band can be set to 1Hz-10kHz, 10kHz-20kHz, 20kHz-30kHz, 30kHz-40kHz, 40kHz-50kHz, 50kHz-60kHz, 60kHz-70kHz, 70kHz-80kHz, 80kHz-90kHz, 90kHz-100kHz respectively, and the spectrum energy of the 10 frequency bands is used as 10 feature information.

[0129] Spectrum energy entropy H f The definition of is shown in formula (3):

[0130]

[0131] Among them, p fk The calculation method of is shown in formula (4):

[0132]

[0133] Where n is the total number of spectrum points, P fk is the proportion of the kth point in the spectrum in the total energy, E fsum It is the total energy of a sampling group in 1Hz-100kHz. Spectral energy entropy can reflect the complexity and randomness of the signal. The larger the spectrum energy entropy, the more changes the signal spectrum contains.

[0134] The calculation method of wavelet energy entropy is as follows:

[0135] Current sampling signal I n After wavelet decomposition, the coefficient of the j-th subband is c j (k),j=1,2,…,N;k=1,2,…,K。 N is the number of subbands, K is the number of coefficients, then the energy of the j-th subband is as shown in formula (5):

[0136]

[0137] Perform m-layer tree wavelet decomposition on the current signal, let the vector E = (E1, E2, ..., E 2m ) is 2 m The energy of the subband is E sum is the energy E of each subband j The sum of p j =E j / E sum , then the calculation method of wavelet energy entropy H is as shown in formula (6):

[0138]

[0139] Solution 4: At time t when the first alarm signal is received, the DC voltage of all photovoltaic inverters in the inverter group is adjusted to change ΔV. The photovoltaic inverter stores the first feature vector of the next frame after adjusting the DC voltage at time t, and records it as the second feature vector. The communication technology is used to realize the sharing of the second feature vector data within the group, and by comparing the second feature vector received by the photovoltaic inverter, it is realized to judge whether the photovoltaic inverter determined to generate a DC arc for the first time generates a DC arc. Specifically, a possible solution is to calculate the average value of the second feature vector of the photovoltaic inverter in the inverter group after adjusting the DC voltage for one frame, use it as the second reference vector, calculate the difference between each second feature vector and the second reference vector, and judge the photovoltaic inverter determined to generate a DC arc for the first time that exceeds the second threshold as an inverter that generates a DC arc. The second threshold here can be determined based on the second threshold obtained by the photovoltaic inverter through reception or storage.

[0140] Solution 5: At time t when the first alarm signal is received, the DC voltage of all PV inverters in the group is adjusted multiple times so that it changes in sequence according to the time window shift time ΔV1, ΔV2, …, ΔV n , where n is the number of times the DC voltage is adjusted, and n is not less than 2. The photovoltaic inverter stores the first eigenvector of one frame after each adjustment of the DC voltage, and records it as the second eigenvector. The communication technology is used to realize the sharing of the second eigenvector data within the inverter group, and by comparing the second eigenvectors received by the photovoltaic inverter, it is realized to judge whether the photovoltaic inverter determined for the first time to generate a DC arc generates a DC arc. Specifically, a possible solution is: calculate the average value of the second eigenvector of one frame after each adjustment of the DC voltage of the photovoltaic inverter in the inverter group, use it as the second reference vector, calculate the difference between each second eigenvector and the second reference vector, and judge the photovoltaic inverter that exceeds the second threshold as an inverter that generates a DC arc. The second threshold here can be determined based on the second threshold obtained by the photovoltaic inverter through reception or storage.

[0141] Through the above-mentioned embodiments, after comparing the first eigenvectors corresponding to different photovoltaic inverters, the present invention further compares the photovoltaic inverter's own data before and after the DC voltage is adjusted, which can improve the accuracy of detecting whether the photovoltaic inverter generates a DC arc and reduce the misjudgment rate.

[0142] In addition, in one or more embodiments of the present invention, after judging whether the photovoltaic inverter that is first determined to generate a DC arc generates a DC arc according to the second reference vector and a preset threshold, the method further includes:

[0143] S6041: In the case where the photovoltaic inverter that is determined to have generated a DC arc for the first time generates a DC arc, a second alarm signal is issued and an arc extinguishing operation is performed.

[0144] In this embodiment, the second alarm signal refers to an alarm signal for confirming the photovoltaic inverter that is first determined to generate a DC arc as a photovoltaic inverter that generates a DC arc.

[0145] S6042: When the photovoltaic inverter that is first determined to generate a DC arc does not generate a DC arc, a misjudgment signal is issued.

[0146] In this embodiment, the misjudgment signal refers to a signal that confirms that the photovoltaic inverter that is first determined to generate a DC arc is a photovoltaic inverter that does not generate a DC arc.

[0147] Through the above technical solution, this embodiment can further confirm that a photovoltaic inverter suspected of generating a DC arc is a photovoltaic inverter that generates a DC arc or does not generate a DC arc, and can improve the accuracy of DC arc detection on the photovoltaic inverter.

[0148] The above is a photovoltaic DC arc detection method provided by one or more embodiments of the present invention. Based on the same idea, the present invention also provides a corresponding photovoltaic DC arc detection device, such as Figure 2 shown.

[0149] Figure 2 A schematic diagram of a photovoltaic DC arc detection device provided by the present invention includes:

[0150] A first determination module is used to obtain M first feature vectors based on electrical feature quantities corresponding to M photovoltaic inverters extracted from a photovoltaic inverter data transmission network;

[0151] A second determination module is used to: determine a first reference vector associated with the M photovoltaic inverters according to the M first characteristic vectors;

[0152] A calculation module, used to: calculate the difference between the M first eigenvectors and the first reference vector;

[0153] A comparison module, used to: compare the difference with a first threshold value to obtain M comparison results associated with the M photovoltaic inverters;

[0154] The judgment module is used to: determine for the first time whether any photovoltaic inverter among the M photovoltaic inverters generates a DC arc according to the M comparison results.

[0155] For the specific definition of a photovoltaic DC arc detection device, please refer to the definition of a photovoltaic DC arc detection method above, which will not be repeated here. Each module in the photovoltaic DC arc detection device can be implemented in whole or in part by software, hardware and a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0156] The present invention also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the Figure 1 A photovoltaic DC arc detection method is provided.

[0157] The present invention also provides Figure 3 The structural diagram of the computer device shown in FIG. Figure 3 As shown, at the hardware level, the computer device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to implement the Figure 1 A photovoltaic DC arc detection method is provided.

[0158] Those skilled in the art can understand that all or part of the processes in the embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0159] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present invention.

Claims

1. A photovoltaic DC arc detection method, characterized in that: include: Based on the electrical characteristic quantities corresponding to the M photovoltaic inverters extracted from the photovoltaic inverter data transmission network, M first characteristic vectors are obtained; Determining a first reference vector associated with the M photovoltaic inverters according to the M first eigenvectors; Calculating the difference between the M first eigenvectors and the first reference vector; Comparing the difference with a first threshold value to obtain M comparison results associated with the M photovoltaic inverters; According to the M comparison results, it is first determined whether any photovoltaic inverter among the M photovoltaic inverters generates a DC arc.

2. The photovoltaic DC arc detection method according to claim 1, characterized in that: The method of obtaining M first feature vectors based on the electrical feature quantities corresponding to the M photovoltaic inverters extracted from the photovoltaic inverter data transmission network specifically includes: Obtaining data types of electrical characteristic quantities corresponding to the M photovoltaic inverters; According to the data type, the electrical characteristic quantities corresponding to the M photovoltaic inverters are classified respectively to obtain M groups of standard electrical characteristic quantities; The M groups of standard electrical characteristic quantities are respectively implanted into arrays according to the data types to obtain the M first characteristic vectors.

3. The photovoltaic DC arc detection method according to claim 2, characterized in that: Before acquiring the data types of the electrical characteristic quantities corresponding to the M photovoltaic inverters, the method further includes: Collecting electrical characteristic quantities corresponding to the M photovoltaic inverters through a sliding window to obtain electrical characteristic quantities corresponding to the M photovoltaic inverters; Based on the number of photovoltaic modules in the photovoltaic array connected to the M photovoltaic inverters, and the series or parallel connection mode, the electrical characteristic quantities corresponding to the M photovoltaic inverters are standardized.

4. The photovoltaic DC arc detection method according to claim 1, characterized in that: The determining, according to the M first eigenvectors, a first reference vector associated with the M photovoltaic inverters specifically includes: Determine any two first eigenvectors among the M first eigenvectors as initial cluster centroids, and determine the remaining first eigenvectors as first eigenvectors to be clustered; Calculating the distance between each of the first feature vectors to be clustered and the centroid of the initial cluster; According to the distance, assigning the first feature vector to be clustered to the initial cluster centroid; Calculating an average value of the initial cluster centroids, and updating the initial cluster centroids according to the average value of the initial cluster centroids; When the number of times the initial cluster centroids are updated reaches a preset number, the segmentation plane between the cluster centroids is determined as the first reference vector.

5. The photovoltaic DC arc detection method according to claim 1, characterized in that: The first step of determining whether any photovoltaic inverter generates a DC arc among the M photovoltaic inverters according to the M comparison results specifically includes: When a difference corresponding to any one or more comparison results among the M comparison results is greater than the first threshold, determining for the first time that the photovoltaic inverter associated with any one or more comparison results generates a DC arc; When the difference corresponding to any one or more comparison results among the M comparison results is not greater than the first threshold, the photovoltaic inverter associated with any one or more comparison results is determined as not generating a DC arc.

6. The photovoltaic DC arc detection method according to claim 1, characterized in that: After determining for the first time whether any photovoltaic inverter among the M photovoltaic inverters generates a DC arc according to the M comparison results, the method further includes: In the case that there is a photovoltaic inverter that is determined to generate a DC arc for the first time among the M photovoltaic inverters, sending a first alarm signal through the photovoltaic inverter that is determined to generate a DC arc for the first time; After the time when the photovoltaic inverter that is first determined to generate a DC arc sends out a first alarm signal reaches a preset time, adjusting the power parameters of the photovoltaic inverter that is first determined to generate a DC arc; Calculating, based on the power parameter, a second eigenvector associated with the photovoltaic inverter that is first determined to generate a DC arc; Based on the second eigenvector, calculating a second reference vector associated with the second eigenvector; Whether the photovoltaic inverter that is first determined to generate a DC arc generates a DC arc is determined based on the second reference vector and a preset threshold.

7. The photovoltaic DC arc detection method according to claim 6, characterized in that: After judging whether the photovoltaic inverter generating the DC arc generates the DC arc according to the second reference vector and the preset threshold, the method further includes: In the case where the photovoltaic inverter that is first determined to have generated a DC arc generates a DC arc, a second alarm signal is issued and an arc extinguishing operation is performed; In the case that the photovoltaic inverter that is first determined to generate a DC arc does not generate a DC arc, a misjudgment signal is issued.

8. A photovoltaic DC arc detection device, characterized in that: include: A first determination module is used to obtain M first feature vectors based on electrical feature quantities corresponding to M photovoltaic inverters extracted from a photovoltaic inverter data transmission network; A second determination module is used to: determine a first reference vector associated with the M photovoltaic inverters according to the M first characteristic vectors; A calculation module, used to: calculate the difference between the M first eigenvectors and the first reference vector; A comparison module, used to: compare the difference with a first threshold value to obtain M comparison results associated with the M photovoltaic inverters; The judgment module is used to: determine for the first time whether any photovoltaic inverter among the M photovoltaic inverters generates a DC arc according to the M comparison results.

9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the photovoltaic DC arc detection method according to any one of claims 1 to 7 is implemented.

10. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the photovoltaic DC arc detection method according to any one of claims 1 to 7 is implemented.

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