Abnormal Photovoltaic String Branch Identification Method, Device, Electronic Equipment and Storage Medium

Abstract

The present disclosure relates to the technical field of photovoltaic power generation, and provides a method, a device, an electronic device and a storage medium for identifying an abnormal photovoltaic string branch. The method includes: calculating a first discretization rate of each inverter in a photovoltaic system according to a preset calculation period, and screening out abnormal inverters with a first discretization rate greater than a preset discretization threshold; screening each photovoltaic string branch connected to the same abnormal inverter to determine a first photovoltaic string branch with the minimum output power among them; calculating a second discretization rate of the abnormal inverter after removing the first photovoltaic string branch; when the second discretization rate is less than or equal to the preset discretization threshold, determining the first photovoltaic string branch as an abnormal photovoltaic string branch, which can timely and accurately identify abnormal operating photovoltaic string devices in the system, has high identification efficiency, and effectively reduces energy waste caused by photovoltaic string device failures, which is beneficial to improving the power generation revenue of enterprises.

Description

Technical Field

[0001] The present disclosure relates to the technical field of photovoltaic power generation, and in particular, to a method, device, electronic device, and storage medium for identifying an abnormal photovoltaic string branch. Background Art

[0002] A distributed photovoltaic power station refers to a power generation system that utilizes decentralized resources, has a small installed capacity, and is arranged near users. It is a new type of energy utilization method with broad prospects for divergence and comprehensive energy utilization.

[0003] Photovoltaic string equipment is a key device for converting light energy (solar energy) into electrical energy. Whether the photovoltaic string equipment operates normally directly affects whether the distributed photovoltaic system generates electricity normally. Therefore, it is necessary to monitor the operating status of the photovoltaic string equipment in the distributed photovoltaic system in real time to ensure that the system can generate electricity normally.

[0004] Traditional methods for monitoring photovoltaic string equipment collect voltage and current data of the photovoltaic string equipment and rely on manual judgment based on experience to determine the operating status of the photovoltaic string equipment. However, this method not only requires a large amount of manpower and material resources, resulting in high monitoring costs, but also is prone to human factors such as missed inspections and misjudgments, making it difficult to identify abnormal operating photovoltaic string equipment in the system in a timely and accurate manner. As a result, it is easy to cause energy waste due to failures of photovoltaic string equipment and reduce the power generation revenue of enterprises. Summary of the Invention

[0005] In view of this, embodiments of the present disclosure provide a method, device, electronic device, and storage medium for identifying an abnormal photovoltaic string branch, so as to solve the problems in the prior art that manually identifying abnormal photovoltaic string branches in a photovoltaic system is time-consuming, laborious, costly, and prone to human factors such as missed inspections and misjudgments, making it difficult to identify abnormal operating photovoltaic string equipment in the system in a timely and accurate manner, thereby easily causing energy waste due to failures of photovoltaic string equipment and reducing the power generation revenue of enterprises.

[0006] In a first aspect of embodiments of the present disclosure, a method for identifying an abnormal photovoltaic string branch is provided, including:

[0007] Calculating a first discrete rate of each inverter in the photovoltaic system according to a preset calculation period, and screening out abnormal inverters with a first discrete rate greater than a preset discrete threshold;

[0008] Screening each photovoltaic string branch connected to the same abnormal inverter to determine a first photovoltaic string branch with the minimum output power;

[0009] Calculating a second discrete rate of the abnormal inverter after removing the first photovoltaic string branch;

[0010] When the second discrete rate is less than or equal to a preset discrete threshold, it is determined that the first photovoltaic string branch is an abnormal photovoltaic string branch.

[0011] In a second aspect of the embodiments of the present disclosure, there is provided an apparatus for identifying an abnormal photovoltaic string branch, including:

[0012] A first calculation module, configured to calculate a first discrete rate of each inverter in a photovoltaic system according to a preset calculation period, and screen out abnormal inverters with a first discrete rate greater than a preset discrete threshold;

[0013] A screening module, configured to screen each photovoltaic string branch connected to the same abnormal inverter to determine a first photovoltaic string branch with the smallest output power therein;

[0014] A second calculation module, configured to calculate a second discrete rate of the abnormal inverter after removing the first photovoltaic string branch;

[0015] A determination module, configured to determine that the first photovoltaic string branch is an abnormal photovoltaic string branch when the second discrete rate is less than or equal to a preset discrete threshold.

[0016] In a third aspect of the embodiments of the present disclosure, there is provided an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the above method are implemented.

[0017] In a fourth aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0018] The beneficial effects of the embodiments of the present disclosure compared with the prior art at least include: by calculating the first discrete rate of each inverter in the photovoltaic system according to a preset calculation period, and screening out abnormal inverters with a first discrete rate greater than a preset discrete threshold; screening each photovoltaic string branch connected to the same abnormal inverter to determine a first photovoltaic string branch with the smallest output power therein; calculating the second discrete rate of the abnormal inverter after removing the first photovoltaic string branch; when the second discrete rate is less than or equal to a preset discrete threshold, determining that the first photovoltaic string branch is an abnormal photovoltaic string branch, it is possible to identify abnormal operating photovoltaic string devices in the system in a timely and accurate manner, with high identification efficiency, and effectively reduce energy waste caused by photovoltaic string device failures, which is beneficial to improving the power generation income of enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] To more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0020] Figure 1 is a schematic flowchart of a method for identifying an abnormal photovoltaic string branch provided by an embodiment of the present disclosure;

[0021] Figure 2 is a schematic diagram of a photovoltaic system architecture in the method for identifying an abnormal photovoltaic string branch provided by an embodiment of the present disclosure;

[0022] Figure 3 is a schematic structural diagram of an apparatus for identifying an abnormal photovoltaic string branch provided by an embodiment of the present disclosure;

[0023] Figure 4 is a schematic structural diagram of an electronic device provided by an embodiment of the present disclosure. Detailed Embodiments

[0024] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are presented to thoroughly understand the embodiments of the present disclosure. However, those skilled in the art should clearly understand that the present disclosure can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present disclosure.

[0025] The following will detail an abnormal photovoltaic string branch identification method and apparatus according to an embodiment of the present disclosure with reference to the drawings.

[0026] Figure 1 is a schematic flowchart of a method for identifying an abnormal photovoltaic string branch provided by an embodiment of the present disclosure. As Figure 1 shown, the method for identifying an abnormal photovoltaic string branch includes:

[0027] Step S101, calculate the first discrete rate of each inverter in the photovoltaic system according to a preset calculation period, and screen out abnormal inverters with a first discrete rate greater than a preset discrete threshold.

[0028] Exemplarily, in combination with Figure 2 , in the embodiments of the present disclosure, a schematic diagram of the structure of a photovoltaic system is provided. As Figure 2As shown, the photovoltaic system 200 includes: a power generation node 201, (a junction board node), an inverter node 202, a junction box node 203, a box transformer node 204, and a grid-connected node 205 (grid-connected cabinet). Among them, each device node may be connected to one or more subordinate devices. For example, the power generation node 201 can be composed of a plurality of dispersedly installed photovoltaic string clusters; each photovoltaic string cluster includes a plurality of photovoltaic strings, and each photovoltaic string may include a plurality of components connected in series, for example, a photovoltaic string composed of 22 components connected in series. The inverter node 202 includes a plurality of inverters, and usually each inverter is connected to a plurality of photovoltaic strings, and the connection path between each photovoltaic string and the inverter constitutes a photovoltaic string branch. The junction box node 203 includes a plurality of junction boxes, and each junction box is connected to an inverter. The box transformer node 204 includes a plurality of box transformers, and each box transformer is connected to a junction box. Each box transformer can be connected to a grid-connected cabinet.

[0029] An inverter is a device that converts direct current into alternating current.

[0030] The preset calculation period can be flexibly set according to the actual situation, for example, it can be set to 30 minutes / time, 1 hour / time, 1 day / time, etc.

[0031] The preset discrete threshold can be flexibly set according to the actual situation and is usually set to 10%.

[0032] Before calculating the first discrete rate of each inverter, it is necessary to sort out and count the physical connection status of the photovoltaic strings of each inverter under the inverter node 202 in the photovoltaic system. Specifically, the connection status of the photovoltaic strings under each inverter can be recorded according to the following Table 1.

[0033] Table 1 Detailed list of connections of PV strings under inverter

[0034]

[0035]

[0036] When calculating the first discrete rate of each inverter, it is necessary to first exclude the branches of each inverter that are not connected to the photovoltaic strings, and then calculate the first discrete rate of each inverter based on the branches connected to the photovoltaic strings.

[0037] As an example, assume that there are 10 inverters in a photovoltaic system, and each inverter has 8 connection ports numbered from 1# to 8#. First, according to the actual connection conditions of the photovoltaic strings of these 10 inverters, record and count the connection conditions of the photovoltaic strings of each inverter according to Table 1 above. Then, eliminate the branches of each inverter that are not connected to the photovoltaic strings, and calculate the first discrete rate of each inverter based on the relevant parameters (such as output power) of the branches of each inverter that are connected to the photovoltaic strings.

[0038] Exemplarily, assume that Inverter No. 1 has 8 connection ports numbered from 1# to 8#, among which, 1# and 7# are not connected to the photovoltaic strings, and 2# to 6# and 8# are all connected to the photovoltaic strings. Then, when calculating the first discrete rate of Inverter No. 1, it is necessary to eliminate the two branches of 1# and 7#, and then calculate the first discrete rate of Inverter No. 1 based on the relevant equipment parameters of the photovoltaic strings of the branches of 2# to 6# and 8#.

[0039] After calculating the first discrete rates of the 10 inverters, screen out the abnormal inverters (inverters that may have abnormal photovoltaic string branches) whose first discrete rates are greater than a preset discrete threshold (for example, 10%).

[0040] Step S102: Screen each photovoltaic string branch connected to the same abnormal inverter to determine the first photovoltaic string branch with the minimum output power among them.

[0041] As an example, assume that according to the above steps, the abnormal inverters screened out are Inverter No. 1 and Inverter No. 2. Then, screen each photovoltaic string branch connected to Inverter No. 1 and Inverter No. 2 respectively, and find the first photovoltaic string branch with the minimum output power in each inverter.

[0042] As an example, the output power of each photovoltaic string can be further determined by obtaining the readings of the output power meters set at the output ends of each photovoltaic string branch, and by comparing the magnitudes of the output powers of each photovoltaic string, determine the first photovoltaic string branch with the minimum output power among them.

[0043] Step S103: Calculate the second discrete rate of the abnormal inverter after eliminating the first photovoltaic string branch.

[0044] Combined with the above example, assume that the first photovoltaic string branch with the minimum output power in Inverter No. 1 is the branch corresponding to the 2# connection port among them. Then, after eliminating the branch corresponding to the 2# connection port, the interfaces of Inverter No. 1 that are currently connected to the photovoltaic strings are 3# to 6# and 8#. Further, calculate the second discrete rate of Inverter No. 1 based on the relevant parameters (such as output power) of the photovoltaic string branches of 3# to 6# and 8#.

[0045] Step S104: When the second discreteness rate is less than or equal to the preset discreteness threshold, determine the first PV string branch as the abnormal PV string branch.

[0046] Combined with the above example, assume that the second discrete power of the No. 1 inverter calculated through the above steps is 7% (less than the preset discreteness threshold of 10%). Then, the PV string branch corresponding to the 2# connection port can be determined as the abnormal PV string branch, that is, the PV string branch corresponding to the 2# connection port has a fault.

[0047] As an example, assume that the second discreteness rate of the No. 1 inverter calculated through the above steps is 11% (greater than the preset discreteness threshold of 10%). Then, continue to find the branch with the minimum output power among the PV string branches corresponding to the 3#-6# and 8# connection ports. After removing the branch with the minimum output power, calculate the third discreteness rate of the No. 1 inverter according to the relevant parameters (such as output power) of the remaining branches, and repeat the above steps until the discrete power of the No. 1 inverter is less than or equal to the preset discreteness threshold, then all the abnormal PV string branches in the No. 1 inverter can be screened out.

[0048] Similarly, according to the method of checking the abnormal PV string branches of the No. 1 inverter, the PV string branches in the No. 2 inverter can be checked to identify the abnormal string branches among them. The specific checking process will not be elaborated here.

[0049] The technical solution provided by the embodiments of the present disclosure calculates the first discreteness rate of each inverter in the PV system according to a preset calculation period, and screens out the abnormal inverters with the first discreteness rate greater than the preset discreteness threshold; checks each PV string branch connected to the same abnormal inverter to determine the first PV string branch with the minimum output power among them; calculates the second discreteness rate of the abnormal inverter after removing the first PV string branch; when the second discreteness rate is less than or equal to the preset discreteness threshold, determine the first PV string branch as the abnormal PV string branch, which can identify the abnormal operating PV string devices in the system in a timely and accurate manner, with high identification efficiency, and effectively reduce the energy waste caused by the failure of PV string devices, which is beneficial to improving the power generation revenue of enterprises.

[0050] In some embodiments, the above step S104 includes:

[0051] Calculate the first correlation coefficient between every two PV string branches connected to the same abnormal inverter;

[0052] When the second discreteness rate is less than or equal to the preset discreteness threshold, and the first correlation coefficient between every two PV string branches is within the preset correlation coefficient range, determine the first PV string branch as the abnormal PV string branch.

[0053] Among them, the correlation coefficient between the PV string branches refers to the correlation of the real-time power generation of the PV strings under the same inverter, and this correlation coefficient can be specifically set according to the power generation characteristics of different power stations. Generally, the reasonable correlation coefficient between the PV string branches under the same inverter is above 99.2%. That is to say, the preset correlation coefficient range can be set to ≥99.2%.

[0054] The following takes the calculation of the first correlation coefficient between every two PV string branches connected to the Inverter No. 1 as an example for detailed description.

[0055] PV strings are connected to the 2#-6# and 8# of the Inverter No. 1. Calculate the first correlation coefficient between every two PV string branches connected to the Inverter No. 2, specifically: calculate the first correlation coefficient between the PV string branch corresponding to the 2# interface and the PV string branches corresponding to the 3#, 4#, 5#, 6#, and 8# interfaces respectively; the first correlation coefficient between the PV string branch corresponding to the 3# interface and the PV string branches corresponding to the 4#, 5#, 6#, and 8# interfaces respectively; the first correlation coefficient between the PV string branch corresponding to the 4# interface and the PV string branches corresponding to the 5#, 6#, and 8# interfaces respectively; the first correlation coefficient between the PV string branch corresponding to the 5# interface and the PV string branches corresponding to the 6# and 8# interfaces respectively; the first correlation coefficient between the PV string branch corresponding to the 6# interface and the PV string branch corresponding to the 8# interface.

[0056] Assume that according to the above steps, the second discrete rate of the Inverter No. 1 is calculated to be 7% (less than the preset discrete threshold of 10%), and the first correlation coefficient between every two PV string branches connected to the Inverter No. 1 is greater than 99.2% (assuming the preset correlation coefficient range is ≥99.2%), that is, within the preset correlation coefficient range, then the PV string branch corresponding to the 2# connection port can be determined as the abnormal PV string branch.

[0057] The technical solution provided by the embodiments of the present disclosure can effectively improve the recognition accuracy and reliability of the abnormal PV string branch by calculating the discrete rate of each inverter and combining the calculation of the correlation coefficient between every two PV string branches connected to each inverter, which is conducive to subsequent fault detection and repair of the identified abnormal PV string branch, and further reduces the energy waste caused by the PV string equipment failure, and is beneficial to improving the power generation revenue of the enterprise.

[0058] In some embodiments, after calculating the first correlation coefficient between every two PV string branches connected to the same abnormal inverter, it further includes:

[0059] If the first correlation coefficients between the i-th photovoltaic string branch connected to the same abnormal inverter and each of the other photovoltaic string branches are not within the preset correlation coefficient range, then the i-th photovoltaic string branch is determined as an abnormal branch;

[0060] When the second dispersion rate is less than or equal to the preset dispersion threshold and the first photovoltaic string branch includes an abnormal branch, determine that the first photovoltaic string branch is an abnormal photovoltaic string branch.

[0061] Combined with the above example, assume that Inverter No. 1 has a total of 8 connection ports from 1# to 8#, among which, 1# and 7# are not connected to photovoltaic strings, and 2# to 6# and 8# are all connected to photovoltaic strings. Then, the branches corresponding to the connection ports of 2# to 6# and 8# can be set as the 1st to i-th (where i = 6) photovoltaic string branches. Among them, the photovoltaic string branch corresponding to the 2# interface is the 1st photovoltaic string branch, the photovoltaic string branch corresponding to the 3# interface is the 2nd photovoltaic string branch, the photovoltaic string branch corresponding to the 4# interface is the 3rd photovoltaic string branch, and so on. The photovoltaic string branch corresponding to the 8# interface is the 6th photovoltaic string branch.

[0062] Assume that the first correlation coefficients between the 1st photovoltaic string branch and the photovoltaic string branches corresponding to the 3# to 6# and 8# interfaces are all less than 99.2% (assuming the preset correlation coefficient range is ≥99.2%), that is, they are not within the preset correlation coefficient range. Then, the 1st photovoltaic string branch is determined as an abnormal branch. And the first correlation coefficients between the 2nd (3rd, 4th, 5th, 6th) photovoltaic string branches and the photovoltaic string branches corresponding to other interfaces are all greater than 99.2%.

[0063] Combined with the above example, assume that the second dispersion rate of Inverter No. 1 is 7% (less than the preset dispersion threshold of 10%), and according to the above steps, it is determined that the first photovoltaic string branch is the photovoltaic string branch corresponding to the 2# interface, that is, it includes the 1st photovoltaic string branch. Then, at this time, it can be determined that the first photovoltaic string branch is an abnormal photovoltaic string branch.

[0064] In some other embodiments, when the second dispersion rate is less than or equal to the preset dispersion threshold and the first photovoltaic string branch does not include an abnormal branch, calculate the second correlation coefficients between every two branches among the other branches except the i-th photovoltaic string branch; if the second correlation coefficients between every two branches among the other branches are all within the preset correlation coefficient range, then determine the i-th photovoltaic string branch as an abnormal photovoltaic string branch.

[0065] Specifically, in combination with the above example, assume that the second discrete rate of the No. 1 inverter is 7% (less than the preset discrete threshold of 10%), and according to the above steps, it is determined that the first photovoltaic string branch is the photovoltaic string branch corresponding to the 2# interface. And according to the step of calculating the first correlation coefficient between every two photovoltaic string branches connected under the same inverter, it is determined that the first correlation coefficients between the second photovoltaic string branch and the photovoltaic string branches corresponding to the 2#, 4# - 6#, and 8# interfaces are all less than 99.2% (assuming the preset correlation coefficient range is ≥99.2%), that is, they are not within the preset correlation coefficient range. Then, the second photovoltaic string branch is determined as an abnormal branch (i.e., the photovoltaic string branch corresponding to the 3# connection port). And the first correlation coefficients between the first (3, 4, 5, 6) photovoltaic string branches and the photovoltaic string branches corresponding to other interfaces are all greater than 99.2%.

[0066] That is to say, the abnormal photovoltaic string branch screened according to the calculation of the discrete rate of the inverter is the photovoltaic string branch corresponding to the 2# interface (the first photovoltaic string branch); the abnormal photovoltaic string branch determined according to the calculation of the first correlation coefficient between every two photovoltaic string branches connected under the inverter is the photovoltaic string branch corresponding to the 3# interface, that is, the first photovoltaic string branch does not include the photovoltaic string branch corresponding to the 3# interface.

[0067] At this time, the second correlation coefficient between every two of the other photovoltaic string branches except the second photovoltaic string branch (i.e., the photovoltaic string branch corresponding to the 3# connection port) can be further calculated. That is, calculate the second correlation coefficient between the photovoltaic string branch corresponding to the 2# connection port and the photovoltaic string branches corresponding to the 4#, 5#, 6#, and 8# connection ports; the second correlation coefficient between the photovoltaic string branch corresponding to the 4# connection port and the photovoltaic string branches corresponding to the 5#, 6#, and 8# connection ports; the second correlation coefficient between the photovoltaic string branch corresponding to the 5# connection port and the photovoltaic string branches corresponding to the 6# and 8# connection ports; the second correlation coefficient between the photovoltaic string branch corresponding to the 6# connection port and the photovoltaic string branch corresponding to the 8# connection port.

[0068] Exemplarily, assume that the second correlation coefficients between every two of the other branches in the No. 1 inverter except the photovoltaic string branch corresponding to the 2# connection port are all greater than 99.2% (assuming the preset correlation coefficient range is ≥99.2%), that is, they are all within the preset correlation coefficient range. Then, the second photovoltaic string branch can be determined as an abnormal branch (i.e., the photovoltaic string branch corresponding to the 3# connection port).

[0069] In some embodiments, the step of calculating the first discrete rate of each inverter in the photovoltaic system may specifically include:

[0070] Calculate the stable output power of each PV string branch connected to each inverter;

[0071] Determine the average output power and power standard deviation of each inverter according to the stable output power;

[0072] Calculate the first discrete rate of each inverter according to the average output power and power standard deviation.

[0073] As an example, the stable output power of each PV string branch can be calculated through the following steps. Specifically:

[0074] Obtain the historical voltage data and historical current data of each PV string branch connected to each inverter during the calculation period;

[0075] Determine the stable voltage and stable current of each PV string branch during the calculation period according to the historical voltage data and historical current data;

[0076] Calculate the stable output power of each PV string branch according to the stable voltage and stable current.

[0077] As an example, the start-up time and shutdown time of each inverter can be determined according to its output power. The historical voltage data during the above start-up time and shutdown time can be obtained through the voltage meter set at each PV string branch, and the historical current data during the above start-up time and shutdown time can be obtained through the current meter set at each PV string branch.

[0078] Then, within the above time period (assuming 0:00 to 24:00), find the stable voltage and stable current of each PV string branch under each inverter within each calculation period (such as 1 hour). Here, the stable voltage and stable current refer to the time points corresponding to the voltage / current when the voltage / current of the PV string branch is in a stable state within each calculation period, that is, the time points when the voltage / current fluctuation tends to be stable (such as no longer changing). Then, the stable output power of each PV string branch can be calculated according to the calculation formula (1): stable output power = stable current * stable voltage.

[0079] Next, the average output power of each inverter can be calculated according to the following formula (2).

[0080]

[0081] Among them, μ is the average output power of the inverter at a certain moment k; N is the total number of PV strings connected under this inverter; x j is the output power of the jth PV string branch of the inverter at a certain moment k.

[0082] The power standard deviation of each inverter can be calculated according to the following formula (3).

[0083]

[0084] Where σ is the power standard deviation of the inverter at a certain moment k.

[0085] Finally, the first discrete rate of each inverter can be calculated according to the following formula (4).

[0086]

[0087] Where CV is the first discrete rate (i.e., power discrete rate) of a single inverter.

[0088] If the preset calculation period is one day, then it can be obtained by calculating the discrete rate of each hour within one day and then weighted averaging the discrete rates of each hour.

[0089] In some embodiments, before calculating the first correlation coefficient between every two photovoltaic string branches connected to the same abnormal inverter, it further includes:[[]]

[0090] Loading and displaying the preset correlation coefficient range;

[0091] Obtaining the output power of the abnormal photovoltaic string branch;

[0092] When the user applies to adjust the preset correlation coefficient range, adjusting and determining the correlation coefficient range according to the output power.

[0093] As an example, the preset correlation coefficient range can be pre-loaded and displayed on the interface. For example, the preset correlation coefficient range is ≥99.2%.

[0094] As an example, assuming that according to the above steps, the abnormal photovoltaic string branch of the No. 1 inverter is the photovoltaic string branch corresponding to the 2# connection port, then the output power of the photovoltaic string branch corresponding to the 2# connection port can be obtained and fed back to the user, so that the user can understand and determine whether to lower the current correlation coefficient range or raise the current correlation coefficient range.

[0095] Exemplarily, it is assumed that when the user needs to increase the current correlation coefficient range based on the output power of the photovoltaic string branch corresponding to the 2# connection port of the current feedback through empirical judgment, the preset correlation coefficient range displayed on the current interface can be modified and adjusted. When the background detects the modification and adjustment operation of the preset correlation coefficient range on the current interface, for example, changing the original 99.2% to 99.5%, then the preset correlation coefficient range can be modified to ≥99.5%. When calculating the correlation coefficient between every two photovoltaic string branches connected to each inverter subsequently and determining the abnormal branch through the correlation coefficient, the modified correlation coefficient range by the user is used as the screening criterion.

[0096] The technical solution provided by the embodiments of the present disclosure can calculate the discrete rate of the inverter device when it enters the normal operation state. The start and end time points of the calculation are not restricted by seasons and meteorology, and the calculation is convenient and highly flexible. In addition, by calculating the discrete rate of each inverter and combining the calculation of the correlation coefficient between every two photovoltaic string branches connected to each inverter, the recognition accuracy and reliability of abnormal photovoltaic string branches can be effectively improved, which is conducive to subsequent fault detection and repair of the identified abnormal photovoltaic string branches, thereby reducing energy waste caused by photovoltaic string device failures and being beneficial to improving the power generation revenue of enterprises. Moreover, it can realize the calculation of the discrete rate of the inverter per hour, with strong timeliness and effective operation and maintenance value.

[0097] All the above optional technical solutions can be combined arbitrarily to form the optional embodiments of the present application, which will not be elaborated one by one here.

[0098] The following is an embodiment of the device of the present disclosure, which can be used to execute the method embodiment of the present disclosure. For the details not disclosed in the embodiment of the device of the present disclosure, please refer to the method embodiment of the present disclosure.

[0099] Figure 3 It is a schematic diagram of an abnormal photovoltaic string branch recognition device provided by the embodiments of the present disclosure. As Figure 3 shown, the abnormal photovoltaic string branch recognition device includes:

[0100] A first calculation module 301, configured to calculate the first discrete rate of each inverter in the photovoltaic system according to a preset calculation period, and screen out abnormal inverters with a first discrete rate greater than a preset discrete threshold;

[0101] A screening module 302, configured to screen each photovoltaic string branch connected to the same abnormal inverter to determine the first photovoltaic string branch with the minimum output power;

[0102] A second calculation module 303, configured to calculate a second discrete rate of an abnormal inverter after excluding a first photovoltaic string branch;

[0103] A determination module 304, configured to determine that the first photovoltaic string branch is an abnormal photovoltaic string branch when the second discrete rate is less than or equal to a preset discrete threshold.

[0104] The technical solution provided by the embodiments of the present disclosure is as follows: by configuring the first calculation module 301 to calculate the first discrete rate of each inverter in the photovoltaic system according to a preset calculation period, and screening out abnormal inverters with a first discrete rate greater than the preset discrete threshold; configuring the screening module 302 to screen each photovoltaic string branch connected to the same abnormal inverter to determine the first photovoltaic string branch with the minimum output power; configuring the second calculation module 303 to calculate the second discrete rate of the abnormal inverter after excluding the first photovoltaic string branch; configuring the determination module 304 to determine that the first photovoltaic string branch is an abnormal photovoltaic string branch when the second discrete rate is less than or equal to the preset discrete threshold, which can timely and accurately identify the abnormal operating photovoltaic string devices in the system, with high identification efficiency, and effectively reduce the energy waste caused by the failure of photovoltaic string devices, which is beneficial to improving the power generation income of enterprises.

[0105] In some embodiments, the above determination module 304 includes:

[0106] A correlation coefficient calculation unit, configured to calculate a first correlation coefficient between every two photovoltaic string branches connected to the same abnormal inverter;

[0107] A first determination unit, configured to determine that the first photovoltaic string branch is an abnormal photovoltaic string branch when the second discrete rate is less than or equal to the preset discrete threshold and the first correlation coefficient between every two photovoltaic string branches is within the preset correlation coefficient range.

[0108] In some embodiments, the above determination module 304 further includes:

[0109] A second determination unit, configured to determine that the i-th photovoltaic string branch is an abnormal branch if the first correlation coefficient between the i-th photovoltaic string branch and each of the other photovoltaic string branches connected to the same abnormal inverter is not within the preset correlation coefficient range;

[0110] A third determination unit, configured to determine that the first photovoltaic string branch is an abnormal photovoltaic string branch when the second discrete rate is less than or equal to the preset discrete threshold and the first photovoltaic string branch includes an abnormal branch.

[0111] In some embodiments, the above determination module 304 further includes:

[0112] A coefficient calculation unit, configured to calculate a second correlation coefficient between every two branches among the other branches except the i-th photovoltaic string branch when the second dispersion rate is less than or equal to a preset dispersion threshold and the first photovoltaic string branch does not include an abnormal branch;

[0113] A fourth determination unit, configured to determine the i-th photovoltaic string branch as an abnormal photovoltaic string branch if the second correlation coefficients between every two branches among the other branches are all within a preset correlation coefficient range.

[0114] In some embodiments, the above-mentioned first calculation module 301 includes:

[0115] A power calculation unit, configured to calculate the stable output power of each photovoltaic string branch connected to each inverter;

[0116] A determination unit, configured to determine the average output power and power standard deviation of each inverter according to the stable output power;

[0117] A dispersion rate calculation unit, configured to calculate a first dispersion rate of each inverter according to the average output power and the power standard deviation.

[0118] In some embodiments, the above-mentioned power calculation unit may specifically be configured to:

[0119] Obtain historical voltage data and historical current data of each photovoltaic string branch connected to each inverter during a calculation period;

[0120] Determine the stable voltage and stable current of each photovoltaic string branch during the calculation period according to the historical voltage data and the historical current data;

[0121] Calculate the stable output power of each photovoltaic string branch according to the stable voltage and the stable current.

[0122] In some embodiments, the above-mentioned determination module 304 further includes:

[0123] A loading unit, configured to load and display a preset correlation coefficient range;

[0124] An obtaining unit, configured to obtain the output power of the abnormal photovoltaic string branch;

[0125] An adjustment unit, configured to adjust and determine the correlation coefficient range according to the output power when the user applies to adjust the preset correlation coefficient range.

[0126] It should be understood that the magnitudes of the sequence numbers of the above steps in the embodiments do not mean the order of execution is prior or posterior, and the execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present disclosure.

[0127] Figure 4 is a schematic diagram of the electronic device 400 provided by an embodiment of the present disclosure. As Figure 4 shown, the electronic device 400 of this embodiment includes: a processor 401, a memory 402, and a computer program 403 stored in the memory 402 and executable on the processor 401. When the processor 401 executes the computer program 403, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor 401 executes the computer program 403, the functions of each module / unit in the above-mentioned device embodiments are implemented.

[0128] Exemplarily, the computer program 403 can be divided into one or more modules / units. The one or more modules / units are stored in the memory 402 and executed by the processor 401 to complete the present disclosure. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 403 in the electronic device 400.

[0129] The electronic device 400 can be a desktop computer, a notebook, a palm computer, a cloud server, and other electronic devices. The electronic device 400 may include, but is not limited to, the processor 401 and the memory 402. Those skilled in the art can understand that Figure 4 merely examples of the electronic device 400, which do not constitute a limitation on the electronic device 400, may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, the electronic device may further include input / output devices, network access devices, a bus, etc.

[0130] The processor 401 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0131] The memory 402 can be an internal storage unit of the electronic device 400, for example, the hard disk or memory of the electronic device 400. The memory 402 can also be an external storage device of the electronic device 400, for example, a plug-in hard disk equipped on the electronic device 400, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the memory 402 can also include both the internal storage unit of the electronic device 400 and the external storage device. The memory 402 is used to store computer programs and other programs and data required by the electronic device. The memory 402 can also be used to temporarily store the data that has been output or will be output.

[0132] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment and will not be elaborated herein.

[0133] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0134] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this disclosure.

[0135] In the embodiments provided in the present disclosure, it should be understood that the disclosed apparatus / electronic device and method can be implemented in other ways. For example, the apparatus / electronic device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. Multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the apparatus or unit can be in electrical, mechanical or other forms.

[0136] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0137] In addition, each functional unit in various embodiments of the present disclosure can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0138] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above method embodiments of the present disclosure, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above method embodiments can be implemented. The computer program can include computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0139] The above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them; although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present disclosure, and should all be included within the protection scope of the present disclosure.

Claims

1. An abnormal photovoltaic string branch identification method, characterized in that, it includes: Calculating the first discrete rate of each inverter in the photovoltaic system according to a preset calculation period, and screening out abnormal inverters with a first discrete rate greater than a preset discrete threshold; Screening each photovoltaic string branch connected to the same abnormal inverter to determine the first photovoltaic string branch with the minimum output power; Calculating the second discrete rate of the abnormal inverter after removing the first photovoltaic string branch; When the second discrete rate is less than or equal to the preset discrete threshold, determining the first photovoltaic string branch as an abnormal photovoltaic string branch; The step of determining the first photovoltaic string branch as an abnormal photovoltaic string branch when the second discrete rate is less than or equal to the preset discrete threshold includes: Calculating the first correlation coefficient between every two photovoltaic string branches connected to the same abnormal inverter; When the second discrete rate is less than or equal to the preset discrete threshold, and the first correlation coefficient between every two photovoltaic string branches is within the preset correlation coefficient range, determining the first photovoltaic string branch as an abnormal photovoltaic string branch.

2. The method according to claim 1, characterized in that, after calculating the first correlation coefficient between every two photovoltaic string branches connected to the same abnormal inverter, it further includes: If the first correlation coefficient between the i-th photovoltaic string branch connected to the same abnormal inverter and each of the other photovoltaic string branches is not within the preset correlation coefficient range, then determining the i-th photovoltaic string branch as an abnormal branch; When the second discrete rate is less than or equal to the preset discrete threshold, and the first photovoltaic string branch includes the abnormal branch, determining the first photovoltaic string branch as an abnormal photovoltaic string branch.

3. The method according to claim 2, characterized in that, after determining the first photovoltaic string branch as an abnormal photovoltaic string branch when the second discrete rate is less than or equal to the preset discrete threshold, and the first photovoltaic string branch includes the abnormal branch, it further includes: When the second discrete rate is less than or equal to the preset discrete threshold, and the first photovoltaic string branch does not include the abnormal branch, calculating the second correlation coefficient between every two branches among the other branches except the i-th photovoltaic string branch; If the second correlation coefficient between every two branches among the other branches is within the preset correlation coefficient range, then determining the i-th photovoltaic string branch as an abnormal photovoltaic string branch.

4. The method according to claim 1, characterized in that, the step of calculating the first discrete rate of each inverter in the photovoltaic system includes: Calculating the stable output power of each photovoltaic string branch connected to each inverter; Determining the average output power and power standard deviation of each inverter according to the stable output power; Calculating the first discrete rate of each inverter according to the average output power and power standard deviation.

5. The method according to claim 4, characterized in that, Calculating the stable output power of each PV string branch connected to each inverter includes: Obtaining the historical voltage data and historical current data of each PV string branch connected to each inverter within the calculation period; Based on the historical voltage data and historical current data, determining the stable voltage and stable current of each PV string branch within the calculation period; and calculating the stable output power of each PV string branch according to the stable voltage and stable current.

6. The method according to claim 1, wherein, before calculating the first correlation coefficient between every two PV string branches connected to the same abnormal inverter, further includes: Loading and displaying a preset correlation coefficient range; Obtaining the output power of the abnormal PV string branch; When the user applies to adjust the preset correlation coefficient range, adjusting and determining the correlation coefficient range according to the output power.

7. An abnormal PV string branch identification device, wherein, includes: A first calculation module configured to calculate the first discrete rate of each inverter in the PV system according to a preset calculation period, and screen out abnormal inverters with a first discrete rate greater than a preset discrete threshold; A screening module configured to screen each PV string branch connected to the same abnormal inverter to determine the first PV string branch with the minimum output power; A second calculation module configured to calculate the second discrete rate of the abnormal inverter after removing the first PV string branch; A determination module configured to determine the first PV string branch as an abnormal PV string branch when the second discrete rate is less than or equal to the preset discrete threshold; The step of determining the first PV string branch as an abnormal PV string branch when the second discrete rate is less than or equal to the preset discrete threshold includes: calculating the first correlation coefficient between every two PV string branches connected to the same abnormal inverter; When the second discrete rate is less than or equal to the preset discrete threshold and the first correlation coefficient between every two PV string branches is within the preset correlation coefficient range, determining the first PV string branch as an abnormal PV string branch.

8. An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein, when the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium stores a computer program, wherein, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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