CN113541600B - Method, system, equipment and storage medium for judging branch fault of photovoltaic power station - Google Patents
Method, system, equipment and storage medium for judging branch fault of photovoltaic power station Download PDFInfo
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- H—ELECTRICITY
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- H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
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Abstract
The invention belongs to the field of photovoltaic power generation, and discloses a method, a system, equipment and a storage medium for judging branch faults of a photovoltaic power station, wherein the method comprises the following steps: acquiring current data of each photovoltaic branch in each photovoltaic branch subset in a preset time period; obtaining an average value of current values of all photovoltaic branches in the photovoltaic branch subsets at each sampling time according to current data of each photovoltaic branch in a preset time period; when the average value is larger than the preset average value, the current sampling time is an effective time point, and the number of all effective time points in the preset time period is counted to obtain the number of the counted effective time points; when the number of the counted effective time points is larger than the number of the preset effective time points, counting the number of zero currents and/or the number of low currents of each photovoltaic branch at the effective time points; when the number of the zero currents is larger than the preset zero times, the current zero fault exists, and when the number of the low currents is larger than the preset low times, the current low fault exists. The accuracy of photovoltaic power plant branch road fault diagnosis has effectively been promoted.
Description
Technical Field
The invention belongs to the field of photovoltaic power generation, and relates to a method, a system, equipment and a storage medium for judging branch faults of a photovoltaic power station.
Background
With the vigorous development of the global photovoltaic industry, the overall installed capacity is increased year by year, and how to reduce the failure loss by an effective means becomes a problem of increasing concern. In a photovoltaic power station, photovoltaic branches are the most important and most central devices, and are the links which are most prone to failure and cause electric quantity loss.
At present, each enterprise mainly judges the trouble branch road through monitored control system in carrying out the power station operation and maintenance in-process, but because of the reasons such as the on-the-spot cluster of power station, branch road quantity is many, and data refresh frequency is fast, and the communication is unstable, leads to photovoltaic power station branch road fault judgment's accuracy lower, and then leads to more erroneous judgement, finally leads to the operation and maintenance personnel to give charge no charge to the trouble branch road of judgement, causes great electric quantity loss.
Disclosure of Invention
The invention aims to overcome the defect of low accuracy of judging the branch fault of the photovoltaic power station in the prior art, and provides a method, a system, equipment and a storage medium for judging the branch fault of the photovoltaic power station.
In order to achieve the purpose, the invention adopts the following technical scheme to realize the purpose:
in a first aspect of the present invention, a method for judging a branch fault of a photovoltaic power station includes the following steps:
dividing all photovoltaic branches in a photovoltaic power station into a plurality of photovoltaic branch subsets;
acquiring current data of each photovoltaic branch in each photovoltaic branch subset within a preset time period; the current data comprise a plurality of sampling times and current values which correspond to the sampling times one by one;
obtaining the average value of the current values of all photovoltaic branches in the photovoltaic branch subsets at each sampling time according to the current data of each photovoltaic branch in a preset time period;
when the average value is larger than the preset average value, the current sampling time is an effective time point, and the number of all effective time points in a preset time period is counted to obtain the number of the counted effective time points;
and when the number of the statistical effective time points is larger than the number of the preset effective time points, performing the step A and/or the step B:
step A: counting the number of the current values of the photovoltaic branches at the effective time points to be zero to obtain the number of the zero currents of the photovoltaic branches; when the number of zero currents of the photovoltaic branch circuits is larger than the preset zero times, the current photovoltaic branch circuit has a current zero fault;
and B: counting the number of the current values of the photovoltaic branches at the effective time points, which are smaller than the preset low current value, to obtain the low current number of the photovoltaic branches; when the number of the low currents of the photovoltaic branch circuits is larger than the preset low times, the current of the photovoltaic branch circuit has a low current fault.
The method for judging the branch fault of the photovoltaic power station is further improved as follows:
and when the current data of each photovoltaic branch in each photovoltaic branch subset in the preset time period is obtained, the current data of each photovoltaic branch in each photovoltaic branch subset in the preset time period is obtained at regular time according to the preset obtaining time.
The preset acquisition time is a plurality of fixed moments every day; after the plurality of fixed moments are arranged according to the time sequence, the preset time period of the first fixed moment is from the initial working moment of the photovoltaic power station to the first fixed moment on the same day, and the preset time periods of the rest of the fixed moments are from the last fixed moment to the current fixed moment.
The preset time period is the time period of the installed capacity of the photovoltaic power station with the current photovoltaic power station real-time power larger than the preset proportion.
The specific method for obtaining the average value of the current values of all the photovoltaic branches in the photovoltaic branch subset at each sampling time according to the current data of each photovoltaic branch in the preset time period is as follows: according to the current data of each photovoltaic branch in a preset time period, current values of all photovoltaic branches in the photovoltaic branch subset at each sampling time are obtained, current values which are larger than a maximum current preset value and smaller than a minimum current preset value are filtered out, and then the average value of the current values of all photovoltaic branches in the photovoltaic branch subset at each sampling time is calculated.
The preset zero times and the preset lower times are 0.5-0.8 times of the number of the statistical valid time points; the preset low current value is a preset multiple of the average value of the current values of all the photovoltaic branches in the photovoltaic branch subset at the current effective time point.
The specific method for dividing all photovoltaic branches in the photovoltaic power station into a plurality of photovoltaic branch subsets comprises the following steps: acquiring all branch father equipment in the photovoltaic power station, and dividing all photovoltaic branches connected with the same branch father equipment into a photovoltaic branch subset.
In a second aspect of the present invention, a system for determining a branch fault of a photovoltaic power station includes:
the dividing module is used for dividing all photovoltaic branches in the photovoltaic power station into a plurality of photovoltaic branch subsets;
the acquisition module is used for acquiring current data of each photovoltaic branch in each photovoltaic branch subset within a preset time period; the current data comprise a plurality of sampling times and current values which correspond to the sampling times one by one;
the average value calculation module is used for obtaining the average value of the current values of all the photovoltaic branches in the photovoltaic branch subsets at each sampling time according to the current data of each photovoltaic branch in the preset time period;
the effective point counting module is used for counting the number of all effective time points in a preset time period to obtain the number of counted effective time points when the average value is larger than a preset average value and the current sampling time is an effective time point;
the fault judgment module is used for counting the number of current values of each photovoltaic branch at the effective time points to be zero when the number of the counted effective time points is larger than the number of the preset effective time points, so as to obtain the number of zero currents of each photovoltaic branch; when the number of the zero currents of the photovoltaic branch circuits is larger than the preset zero times, the current zero fault exists in the current photovoltaic branch circuit.
In a third aspect of the present invention, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method for judging the branch fault of the photovoltaic power station when executing the computer program.
In a fourth aspect of the present invention, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the method for judging the branch fault of the photovoltaic power station.
Compared with the prior art, the invention has the following beneficial effects:
the method for judging the branch faults of the photovoltaic power station obtains the current data of each photovoltaic branch in each photovoltaic branch subset in the preset time period, obtains the average value of the current values of all the photovoltaic branches in each photovoltaic branch subset at each sampling time according to the current data of each photovoltaic branch in the preset time period, then obtains the number of statistical effective time points according to the average value, further judges whether the photovoltaic branches have current zero faults or current low faults based on the number of the statistical effective time points, realizes a method for judging whether the current of the photovoltaic branches such as assemblies, strings and the like is zero or low faults, and provides a scheme and a method for realizing the intelligent monitoring of equipment. The method is wide in application, can be applied to photovoltaic branch fault monitoring of an intelligent combiner box, a string inverter and the like, and provides a feasible and practical scheme and method for intelligent fault diagnosis. And the accurate judgment that the current of the serial branch of the photovoltaic power station group is zero is realized, the misjudgment is avoided, the loss under the fault condition that the current of the branch is zero can be accurately calculated, and a basis is provided for the efficiency loss evaluation of the photovoltaic branch under the fault condition. By combining the actual situation of the photovoltaic station, a professional analysis method is provided from the two aspects of accurate positioning of the branch for the zero-group string and electric quantity loss caused by the fault branch, the accurate judgment of the current zero fault of the photovoltaic branch of the photovoltaic power station is improved, and the operation and maintenance evaluation capability of the station is improved.
Furthermore, when the average value of the current values of all the photovoltaic branches in the set is calculated, the current values which are larger than the maximum current preset value and smaller than the minimum current preset value in the current values of all the photovoltaic branches are filtered out, so that the influence of obvious error data is avoided.
Furthermore, the number of the preset zero times and the number of the preset low times are 0.5-0.8 times of the number of the statistical effective time points, the size of the preset zero times and the size of the preset low times are determined on the basis of counting the number of the effective time points, misjudgment is effectively prevented, and the accuracy of judgment is improved.
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FIG. 1 is a flow chart of a method for judging a branch fault of a photovoltaic power station according to the present invention;
FIG. 2 is a partial current data diagram of an embodiment of the present invention;
fig. 3 is a schematic diagram of a determination result of a plurality of photovoltaic branches according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The invention is described in further detail below with reference to the accompanying drawings:
referring to fig. 1, in an embodiment of the present invention, a method for judging a branch fault of a photovoltaic power station is provided, which mainly relates to judging an abnormal current fault of a branch of a photovoltaic power station.
Specifically, the method for judging the branch fault of the photovoltaic power station comprises the following steps:
s1: all photovoltaic branches in the photovoltaic power station are divided into a plurality of photovoltaic branch subsets.
Specifically, all branch father devices in the photovoltaic power station are obtained, and all photovoltaic branches connected with the same branch father device are divided into a photovoltaic branch subset. The branch parent equipment is different in type according to different application scenes, and when the photovoltaic power station adopts a centralized inverter, the branch parent equipment is a combiner box; when the photovoltaic power station adopts the group-string inverter, the branch father device is the group-string inverter.
S2: acquiring current data of each photovoltaic branch in each photovoltaic branch subset within a preset time period; the current data comprise a plurality of sampling times and current values which correspond to the sampling times one by one.
Specifically, current values of all photovoltaic branches are inquired according to a preset time period, if the collected data are not null, the operation is continued, and otherwise, the fault judgment method cannot be realized. The preset time period may be one fixed time period, a plurality of fixed time periods, or one dynamic time period, and when the preset time period is a plurality of fixed time periods, the following operations are performed in each fixed time period.
The dynamic time period is a time period within which the real-time power of the photovoltaic power station is greater than the installed capacity of the photovoltaic power station in a preset proportion, the preset proportion can be 5% -10%, the preset proportion is 5% in the embodiment, and the influence of invalid data can be reduced as much as possible while the validity of the data is guaranteed.
Preferably, when current data of each photovoltaic branch in each photovoltaic branch subset within a preset time period is obtained, current data of each photovoltaic branch in each photovoltaic branch subset within the preset time period is obtained at regular time according to preset obtaining time. The preset acquisition time is a plurality of fixed moments every day; after the plurality of fixed moments are arranged according to the time sequence, the preset time period of the first fixed moment is from the initial working moment of the photovoltaic power station to the first fixed moment on the same day, and the preset time periods of the rest of the fixed moments are from the last fixed moment to the current fixed moment. The preset acquisition time needs to be set after the photovoltaic power station generates electricity, and the preset time period is selected to sample photovoltaic branch current data to judge whether abnormal photovoltaic branches exist in the normal working time period of the photovoltaic power station. And each photovoltaic power station can automatically set the starting time of a preset fixed time period according to different regions. A plurality of fixed moments can be set, so that a plurality of preset time periods are generated, and the plurality of preset time periods are used for judging the conditions of each photovoltaic branch in a segmented and repeated manner as soon as possible. The judgment is carried out on the basis of historical data of a preset time period, if the preset time period is 4 hours, the judgment is carried out once in 4 hours, and the abnormality can be diagnosed after the photovoltaic power station is connected to the grid for 4 hours; if the preset time period is 8 hours, the diagnosis is performed once in 8 hours, and the abnormality can be diagnosed only after the photovoltaic power station is connected to the grid for 8 hours.
Specifically, in this embodiment, the preset acquisition time is verified once or twice a day, and the verification times can be determined according to the shift. The photovoltaic power station starting working time is set to be 8 points on the same day, and when the photovoltaic power station starting working time is set once a day, the preset obtaining time is 22:00 a day, so that the fault judgment method is started at a fixed time of 22:00 a day, and the corresponding preset time period is 8: 00-22: 00; twice daily, the preset acquisition times are 14:00 and 22:00, thus timing daily 14:00 and 22:00 start-up failure determination, 14:00, corresponding to a preset time period of 8:00 to 14:00, 22:00 is started, and the corresponding preset time period is 14:00 to 22: 00.
S3: and obtaining the average value of the current values of all the photovoltaic branches in the photovoltaic branch subsets at each sampling time according to the current data of each photovoltaic branch in the preset time period.
Specifically, in this embodiment, firstly, data is reconstructed according to current data of each photovoltaic branch in a preset time period, the data is divided according to a matrix type structure, a time node is defined to be a horizontal direction, a sequence of each photovoltaic branch under one set is defined to be a vertical direction, and a current value of each branch and sampling time form a matrix structure. Then, on each horizontal sampling time node, calculating the average value of the current values of each longitudinal photovoltaic branch in one set to obtain the average value of the current values of all photovoltaic branches in the photovoltaic branch subset at each sampling time.
Preferably, when the average value of the current values of the photovoltaic branches in the set is calculated, the current values of all the photovoltaic branches in the photovoltaic branch subset at each sampling time are obtained according to the current data of each photovoltaic branch in a preset time period, then the current values which are greater than the maximum current preset value and smaller than the minimum current preset value in the current values are filtered, and the average value of the current values of all the photovoltaic branches in the photovoltaic branch subset at each sampling time is calculated after filtering is completed. In this embodiment, the maximum current preset value is 15A, and the minimum current preset value is 0A, so as to avoid the influence of obvious error data.
Preferably, the plurality of sampling times are evenly distributed within a preset time period. Specifically, when the current value of the photovoltaic branch is sampled, the current value is sampled uninterruptedly at a preset time interval, wherein in this embodiment, the preset time interval is 5 minutes.
S4: and when the average value is larger than the preset average value, the current sampling time is an effective time point, and the number of all effective time points in the preset time period is counted to obtain the number of the counted effective time points.
Specifically, a preset average value is formulated according to historical experience and actual conditions of the photovoltaic power station, and the preset average value supports modification. And judging whether the average value is larger than a preset average value, wherein the preset average value can be 1-2A, in the embodiment, the preset average value is 2A, and if the calculated average value of the current values of the photovoltaic branches at the current sampling time is larger than 2A, counting the current sampling time as an effective time point.
And then, traversing the average value of the current values of the photovoltaic branches at all the sampling time to obtain whether the sampling time is an effective time point, and counting the number of the effective time points to obtain the number of the counted effective time points.
S5: when the number of the counted effective time points is larger than the preset number of the effective time points, performing the step A and/or the step B; step A: counting the number of the current values of the photovoltaic branches at the effective time points to be zero to obtain the number of the zero currents of the photovoltaic branches; when the number of zero currents of the photovoltaic branches is larger than the preset zero times, a current zero fault exists in the current photovoltaic branch; and B: counting the number of the current values of the photovoltaic branches at the effective time points, which are smaller than the preset low current value, to obtain the low current number of the photovoltaic branches; when the number of the low currents of the photovoltaic branch circuits is larger than the preset low times, the current of the photovoltaic branch circuit has a low current fault.
Specifically, the preset number of valid time points is related to the duration and time interval of current data sampling, and when the time interval of sampling is 5 minutes, the duration of sampling is 30 minutes, and preferably, the preset number of valid time points is set to 6 times. In this embodiment, the number of valid time points is preset to be 6, that is, when the number of valid time points is greater than 6, the number of the photovoltaic branches at the valid time points, the current value of which is zero, and the number of the photovoltaic branches at which the current value of which is less than the preset low current value are counted to obtain the zero current number and the low current number of each photovoltaic branch, and then the current zero fault and the current low fault are determined based on the zero current number of each photovoltaic branch.
Specifically, when the number of zero currents of the photovoltaic branch circuits is larger than the preset zero times, the current zero fault of the photovoltaic branch circuit exists, the photovoltaic branch circuit is recorded as the zero fault, and warning information is generated and fault early warning is started. When the number of the low currents of the photovoltaic branch circuits is larger than the preset low frequency, the current photovoltaic branch circuits have low current faults, alarm information is generated, and fault early warning is started.
Preferably, the number of the preset zero times and the number of the preset low times are 0.5-0.8 times of the number of the statistical effective time points, the size of the preset zero times and the size of the preset low times are determined on the basis of counting the number of the effective time points, and the accuracy of a judgment result is improved.
The preset low current value is a preset multiple of the average value of the current values of all the photovoltaic branches in the photovoltaic branch subset of the current effective time point. In this embodiment, the preset multiple is preferably 0.5.
Referring to fig. 2, a partial current data actually acquired in an embodiment of the present invention is shown. Referring to fig. 3, a judgment result of a plurality of photovoltaic branches in the embodiment of the present invention is shown.
The performance of the photovoltaic branch directly determines the performance of the whole photovoltaic power station, but in the aspect of evaluation of the photovoltaic power station, the whole power station is used as an evaluation object, and the efficiency of the photovoltaic power station is evaluated by the system efficiency PR value. The evaluation method has a large time scale, generally takes months or years as a time unit, simply measures the efficiency of the power station system according to the ratio of the generated energy to the received irradiation energy in a period of time, cannot accurately measure the influence caused by the faults of various types of equipment, and particularly has less research on the aspect of efficiency loss evaluation under the condition that the photovoltaic branch is in fault. The method combines the actual situation of the photovoltaic power station to realize the accurate positioning of the photovoltaic branch with zero current or low current, and further can calculate the loss electric quantity of the abnormal photovoltaic branch. The simple introduction is as follows: the method comprises the steps of obtaining abnormal information of the photovoltaic branches, calculating an abnormal time period of each abnormal photovoltaic branch, obtaining the generated energy Q of a branch father device of the photovoltaic branch in the abnormal time period, wherein the lost electric quantity of the photovoltaic branch with zero current in the time period is Q/normal branch number, the lost electric quantity of the photovoltaic branch with low current in the time period is Q/normal branch number-the generated energy of the photovoltaic branch with low current in the time period, improving the accurate positioning of abnormal faults of the photovoltaic power station branches and the energy efficiency analysis result, wherein the energy efficiency analysis means that the loss of the whole photovoltaic power station is calculated according to the lost electric quantity of the photovoltaic branch, obtaining the occupation ratio of each loss, evaluating the operation and maintenance capability of the photovoltaic power station, and improving the operation and maintenance evaluation capability of the station.
In conclusion, the method for judging the branch fault of the photovoltaic power station realizes the method for judging the faults that the current of the photovoltaic branches such as the components, the strings and the like is zero and is low, and provides a scheme and a method for realizing the intelligent monitoring of equipment. The method is wide in application, can be applied to fault monitoring of photovoltaic branches such as an intelligent combiner box and a string inverter, and provides a feasible and practical scheme and method for intelligent fault diagnosis. The method and the device realize accurate judgment of zero branch current of the photovoltaic power station group string, avoid misjudgment, further accurately calculate the loss of the zero branch current under the fault condition, and provide a basis for evaluating the efficiency loss of the photovoltaic branch under the fault condition. By combining the actual situation of the photovoltaic station, a professional analysis method is provided from the two aspects of accurate positioning of the branch for the zero-group string and electric quantity loss caused by the fault branch, the accurate judgment of the current zero fault of the photovoltaic branch of the photovoltaic power station is improved, and the operation and maintenance evaluation capability of the station is improved.
The following are embodiments of the apparatus of the present invention that may be used to perform embodiments of the method of the present invention. For details of non-careless mistakes in the embodiment of the apparatus, please refer to the embodiment of the method of the present invention.
In another embodiment of the present invention, a photovoltaic power station branch fault determination system is provided, which can be used to implement the above photovoltaic power station branch fault determination method.
The dividing module is used for dividing all photovoltaic branches in the photovoltaic power station into a plurality of photovoltaic branch subsets; the acquisition module is used for acquiring current data of each photovoltaic branch in each photovoltaic branch subset within a preset time period; the current data comprise a plurality of sampling times and current values which correspond to the sampling times one by one; the average value calculation module is used for obtaining the average value of the current values of all the photovoltaic branches in the photovoltaic branch subsets at each sampling time according to the current data of each photovoltaic branch in the preset time period; the effective point counting module is used for counting the number of all effective time points in a preset time period to obtain the number of counted effective time points when the average value is larger than a preset average value and the current sampling time is an effective time point; the fault judgment module is used for counting the number of current values of each photovoltaic branch at the effective time point to be zero when the number of the counted effective time points is larger than the number of the preset effective time points, so as to obtain the number of zero currents of each photovoltaic branch; when the number of the zero currents of the photovoltaic branch circuits is larger than the preset zero times, the current zero fault exists in the current photovoltaic branch circuit.
In yet another embodiment of the present invention, a computer device is provided that includes a processor and a memory for storing a computer program comprising program instructions, the processor for executing the program instructions stored by the computer storage medium. The Processor may be a Central Processing Unit (CPU), or may be other general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable gate array (FPGA) or other Programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc., which is a computing core and a control core of the terminal, and is specifically adapted to load and execute one or more instructions in a computer storage medium to implement a corresponding method flow or a corresponding function; the processor provided by the embodiment of the invention can be used for operating the method for judging the branch fault of the photovoltaic power station.
In still another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory), which is a Memory device in a computer device and is used for storing programs and data. It is understood that the computer readable storage medium herein can include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also, one or more instructions, which may be one or more computer programs (including program code), are stored in the memory space and are adapted to be loaded and executed by the processor. It should be noted that the computer-readable storage medium may be a high-speed RAM memory, or may be a non-volatile memory (non-volatile memory), such as at least one disk memory. The processor may load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the method for determining a branch fault of a photovoltaic power plant in the above embodiments.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A method for judging faults of branches of a photovoltaic power station is characterized by comprising the following steps:
dividing all photovoltaic branches in a photovoltaic power station into a plurality of photovoltaic branch subsets;
acquiring current data of each photovoltaic branch in each photovoltaic branch subset in a preset time period; the current data comprise a plurality of sampling times and current values which correspond to the sampling times one by one;
obtaining an average value of current values of all photovoltaic branches in the photovoltaic branch subsets at each sampling time according to current data of each photovoltaic branch in a preset time period;
when the average value is larger than the preset average value, determining that the current sampling time corresponding to the current average value is an effective time point, and counting the number of all effective time points in a preset time period to obtain the number of the counted effective time points;
and when the number of the statistical effective time points is larger than the number of the preset effective time points, performing the step A and/or the step B:
step A: counting the number of the current values of the photovoltaic branches at the effective time points to be zero to obtain the number of the zero currents of the photovoltaic branches; when the number of zero currents of the photovoltaic branches is larger than the preset zero times, a current zero fault exists in the current photovoltaic branch;
and B, step B: counting the number of the current values of the photovoltaic branches at the effective time points, which are smaller than the preset low current value, to obtain the low current number of the photovoltaic branches; when the number of the low currents of the photovoltaic branch circuits is larger than the preset low times, the current of the photovoltaic branch circuit has a low current fault.
2. The method according to claim 1, wherein when the current data of each photovoltaic branch in each photovoltaic branch subset within the preset time period is obtained, the current data of each photovoltaic branch in each photovoltaic branch subset within the preset time period is obtained regularly according to preset obtaining time.
3. The method according to claim 2, characterized in that the preset acquisition time is a number of fixed times of day; after the plurality of fixed moments are arranged according to the time sequence, the preset time period of the first fixed moment is from the initial working moment of the photovoltaic power station to the first fixed moment on the same day, and the preset time periods of the rest of the fixed moments are from the last fixed moment to the current fixed moment.
4. The method for judging the branch fault of the photovoltaic power station as claimed in claim 1, wherein the preset time period is a time period when the real-time power of the photovoltaic power station in the current day is greater than the installed capacity of the photovoltaic power station in a preset proportion.
5. The method for judging the branch fault of the photovoltaic power station according to claim 1, wherein the specific method for obtaining the average value of the current values of all the photovoltaic branches in the photovoltaic branch subset at each sampling time according to the current data of each photovoltaic branch in the preset time period comprises the following steps: according to the current data of each photovoltaic branch in a preset time period, current values of all photovoltaic branches in the photovoltaic branch subset at each sampling time are obtained, current values which are larger than a maximum current preset value and smaller than a minimum current preset value are filtered out, and then the average value of the current values of all photovoltaic branches in the photovoltaic branch subset at each sampling time is calculated.
6. The method for judging the branch fault of the photovoltaic power station as claimed in claim 1, wherein the preset zero times and the preset lower times are both 0.5-0.8 times of the number of the statistical effective time points; the preset low current value is a preset multiple of the average value of the current values of all the photovoltaic branches in the photovoltaic branch subset at the current effective time point.
7. The method for judging the branch fault of the photovoltaic power station according to claim 1, wherein the specific method for dividing all photovoltaic branches in the photovoltaic power station into a plurality of photovoltaic branch subsets comprises the following steps: acquiring all branch father devices in the photovoltaic power station, and dividing all photovoltaic branches connected with the same branch father device into a photovoltaic branch subset, wherein the branch father devices are combiner boxes or group-series inverters.
8. The utility model provides a photovoltaic power plant branch road fault judgement system which characterized in that includes:
the dividing module is used for dividing all photovoltaic branches in the photovoltaic power station into a plurality of photovoltaic branch subsets;
the acquisition module is used for acquiring current data of each photovoltaic branch in each photovoltaic branch subset within a preset time period; the current data comprise a plurality of sampling times and current values which correspond to the sampling times one by one;
the average value calculation module is used for obtaining the average value of the current values of all the photovoltaic branches in the photovoltaic branch subsets at each sampling time according to the current data of each photovoltaic branch in the preset time period;
the effective point counting module is used for determining the current sampling time corresponding to the current average value as an effective time point when the average value is larger than the preset average value, and counting the number of all effective time points in a preset time period to obtain the number of the counted effective time points;
the fault judgment module is used for counting the number of current values of each photovoltaic branch at the effective time points to be zero when the number of the counted effective time points is larger than the number of the preset effective time points, so as to obtain the number of zero currents of each photovoltaic branch; when the number of the zero currents of the photovoltaic branch circuits is larger than the preset zero times, the current zero fault exists in the current photovoltaic branch circuit.
9. A computer arrangement comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method for photovoltaic power plant branch failure determination according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method for photovoltaic power plant branch fault diagnosis according to any one of claims 1 to 7.
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| JP5584622B2 (en) * | 2010-02-19 | 2014-09-03 | オーナンバ株式会社 | Fault detection method for photovoltaic system |
| CN104283512B (en) * | 2014-10-28 | 2017-02-01 | 上海许继电气有限公司 | Method for remotely monitoring and locating faults of set strings in photovoltaic power station system |
| JP6501535B2 (en) * | 2015-01-30 | 2019-04-17 | 東京電力ホールディングス株式会社 | Method and apparatus for diagnosing power generation status of photovoltaic system |
| WO2018028005A1 (en) * | 2016-08-11 | 2018-02-15 | 苏州瑞得恩自动化设备科技有限公司 | Fault detection algorithm for battery panel in large-scale photovoltaic power station |
| CN108696249B (en) * | 2017-04-11 | 2021-05-14 | 丰郅(上海)新能源科技有限公司 | Rapid diagnosis method for faults of photovoltaic module |
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| CN110224673B (en) * | 2019-05-14 | 2020-10-02 | 太原理工大学 | Deep learning-based solar photovoltaic cell panel fault detection method |
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| CN111614318B (en) * | 2020-05-26 | 2021-07-20 | 广东电网有限责任公司电力调度控制中心 | Method and device for detecting direct-current side current fault of photovoltaic system |
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