CN113242018A - Photovoltaic equipment fault diagnosis method and application device thereof - Google Patents
Photovoltaic equipment fault diagnosis method and application device thereof Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- 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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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
Abstract
The method comprises the steps of firstly judging whether the equipment to be diagnosed has a start-stop fault or not according to target diagnosis data after the target diagnosis data related to the running process of the equipment to be diagnosed is obtained, and further determining an alarm level according to the target diagnosis data if the equipment to be diagnosed has the start-stop fault. Compared with the prior art, the fault diagnosis method provided by the invention realizes fault diagnosis based on the target diagnosis data related to the running process of the equipment to be diagnosed, and further determines the alarm level, and the running state of the photovoltaic system does not need to be changed in the diagnosis process, so that the stable running of the photovoltaic system is ensured, and the stable generating capacity is provided.
Description
Technical Field
The invention relates to the technical field of photovoltaic power generation, in particular to a photovoltaic equipment fault diagnosis method and an application device thereof.
Background
The photovoltaic system comprises photovoltaic group strings, a combiner box, an inverter, a transformer, a connecting cable and other equipment, and among the equipment of the photovoltaic system, direct-current side equipment, namely the photovoltaic group strings, the combiner box and the inverter, is equipment with frequent faults. Among the types of faults of the dc-side equipment, the most serious is a start delay fault and an abnormal shutdown fault, which cause the corresponding equipment to directly lose power generation capacity, even enlarge the fault range, damage other power generation equipment in the system, and cause property loss.
Therefore, the fault diagnosis of the direct-current side equipment has very important significance for improving operation and maintenance efficiency, guaranteeing safe operation of the power station, reducing property loss risks of the power station and increasing investment income. Chinese patent CN107395119A provides a method for fault location of a photovoltaic array, which has the core idea that fault diagnosis is performed on a photovoltaic array primarily according to abnormal changes of output power of each channel, fault location is performed on a photovoltaic string with a local shadow shielding or hot spot phenomenon, a faulty branch is determined by adjusting output voltage of the photovoltaic array M times in the fault location process, combining with conduction state changes of bypass diodes in the photovoltaic array, and the degree of the shadow shielding or hot spot phenomenon in the photovoltaic array and the specific position of a photovoltaic module with the shadow shielding or hot spot phenomenon are determined according to the conduction sequence of the diodes.
However, in the fault diagnosis method in the prior art, the output voltage of the photovoltaic array needs to be adjusted in the diagnosis process, which affects the normal operation of the photovoltaic system and the power generation amount of the photovoltaic system.
Disclosure of Invention
The invention provides a photovoltaic equipment fault diagnosis method and an application device thereof, which realize fault diagnosis and alarm grade determination of equipment to be diagnosed based on target diagnosis data related to the operation process of the equipment to be diagnosed, and the diagnosis process does not influence the normal operation of a photovoltaic system, thereby being beneficial to the stable control of the power generation capacity of the photovoltaic system.
In order to achieve the purpose, the technical scheme provided by the invention is as follows:
in a first aspect, the present invention provides a method for diagnosing a fault of a photovoltaic device, including:
acquiring target diagnosis data related to the operation process of equipment to be diagnosed;
judging whether the equipment to be diagnosed has start-stop faults or not according to the target diagnosis data;
and if the equipment to be diagnosed has the start-stop fault, determining an alarm level according to the target diagnosis data.
Optionally, the target diagnostic data includes: the method comprises the following steps of (1) sampling values corresponding to a theoretical starting moment, a plurality of historical moments of target electrical parameters at the current moment and before the current moment, and a preset starting judgment threshold;
the judging whether the equipment to be diagnosed has the start-stop fault according to the target diagnosis data comprises the following steps:
judging whether the equipment to be diagnosed has a start delay fault or not according to the theoretical start time, the current time and each sampling value;
and if the equipment to be diagnosed has no start delay fault, judging whether the equipment to be diagnosed has an abnormal shutdown fault or not according to the sampling values and the preset start judgment threshold value.
Optionally, the determining, according to the theoretical starting time, the current time, and each sampling value, whether a starting delay fault occurs in the device to be diagnosed includes:
calculating the difference between the current time and the theoretical starting time to obtain diagnosis duration;
if the diagnosis time length is greater than a preset time length threshold value and each sampling value is zero, judging that the equipment to be diagnosed has a start delay fault;
and if the diagnosis time length is less than or equal to the preset time length threshold value or any sampling value is not zero, judging that the equipment to be diagnosed has no start delay fault.
Optionally, the determining, according to each of the sampling values and the preset starting judgment threshold, whether the to-be-diagnosed device has an abnormal shutdown fault includes:
sequencing the sampling values according to a time sequence to obtain a sequencing result;
judging whether the sequencing result comprises a target sampling value which is larger than the preset judgment starting threshold value or not;
if the sequencing result comprises the target sampling value and each sampling value behind the target sampling value is finally reduced to zero, judging that the equipment to be diagnosed has abnormal shutdown fault;
and if the sequencing result does not include the target sampling value, or all sampling values after the target sampling value are larger than zero, judging that the equipment to be diagnosed has no abnormal shutdown fault.
Optionally, the process of obtaining the theoretical starting time includes:
obtaining a plurality of sets of historical values for the target electrical parameter;
any historical value set corresponds to a historical natural day before the natural day to which the current time belongs;
sorting each historical value in each historical value set according to time sequence;
according to the sequencing result of each historical value set, respectively determining the historical value of the first non-zero value in each historical value set to obtain a corresponding target historical value;
taking the occurrence time corresponding to each target historical value as the historical starting time of the corresponding historical natural day;
and determining the theoretical starting time according to the historical starting times.
Optionally, the determining the theoretical starting time according to each historical starting time includes:
respectively converting each historical starting time into corresponding true solar time to obtain corresponding starting true solar time;
screening each starting true solar time according to a preset screening algorithm;
and taking the average value of the starting true solar time included in the screening result as the theoretical starting moment.
Optionally, if the device to be diagnosed includes an inverter, the target electrical parameter includes active power;
if the equipment to be diagnosed comprises a combiner box, the target electrical parameter comprises total direct current power;
if the equipment to be diagnosed comprises a photovoltaic string, the target electrical parameter comprises a maximum allowable access current.
Optionally, if the device to be diagnosed includes an inverter, the process of obtaining the preset starting judgment threshold includes:
obtaining a rated value and a first preset coefficient of active power of the inverter;
taking the product of the rated value of the active power and the first preset coefficient as a preset starting judgment threshold value of the inverter;
if the equipment to be diagnosed comprises a combiner box, acquiring the process of the preset starting judgment threshold value, comprising the following steps:
calculating the sum of peak power of each photovoltaic group string connected with the combiner box to obtain a rated value of the total direct current power of the combiner box;
taking the product of the rated value of the rated total direct current power and a second preset coefficient as a preset judgment starting threshold value of the combiner box;
if the device to be diagnosed comprises a photovoltaic string, acquiring the preset starting judgment threshold value, wherein the process comprises the following steps:
obtaining a rated value and a third preset coefficient of the maximum allowable access current of the photovoltaic group string;
and taking the product of the rated value of the maximum allowable access current of the photovoltaic group string and the third preset coefficient as a preset starting judgment threshold value of the photovoltaic group string.
Optionally, if there are multiple devices to be diagnosed with the start-stop fault, determining an alarm level according to the target diagnosis data includes:
taking each device to be diagnosed with the start-stop fault as a target device;
determining the highest-grade target equipment in all the target equipment according to a preset equipment grade;
and determining the alarm grade according to the target diagnosis data of the target equipment with the highest grade.
Optionally, the determining an alarm level according to the target diagnostic data of the target device with the highest level includes:
determining a current alarm score according to the target diagnosis data of the target equipment with the highest grade;
inquiring a preset mapping relation, and determining an alarm grade corresponding to the current alarm score;
wherein, the preset mapping relation records the corresponding relation between different alarm scores and alarm grades.
Optionally, the target diagnostic data includes a plurality of alarm score indicators;
the determining a current alarm score according to the target diagnostic data of the target device with the highest grade includes:
determining the index value of each alarm score index according to the score mapping relation corresponding to each alarm score index;
and determining the current alarm score of the target equipment with the highest grade according to each index value.
Optionally, the determining, according to each index value, a current alarm score of the target device with the highest level according to the index value includes:
acquiring a weight coefficient corresponding to each alarm scoring index;
respectively calculating the index weighted value of each alarm scoring index according to the index value and the weight coefficient corresponding to each alarm scoring index;
and taking the sum of the weighted values of the indexes as the current alarm score of the target equipment with the highest grade.
Optionally, the alarm scoring index includes: the current weather type of the diagnosis day, the historical weather type of the natural day of the preset number of days before the diagnosis day, the equipment type and the alarm time;
wherein the diagnosis day is a natural day to which the current time belongs.
Optionally, if there are multiple devices to be diagnosed with the start-stop fault, determining an alarm level according to the target diagnosis data includes:
and determining the alarm level of each device to be diagnosed with the start-stop fault according to the target diagnosis data corresponding to each device to be diagnosed with the start-stop fault.
Optionally, the photovoltaic device diagnosis method provided by the first aspect of the present invention further includes:
and respectively taking each direct current side device in the photovoltaic system as a device to be diagnosed.
In a second aspect, the present invention provides a photovoltaic system comprising: at least one path comprises a photovoltaic subsystem, a transformer and a main controller of direct current side equipment, wherein,
the alternating current output end of each photovoltaic subsystem is connected with the primary winding of the transformer;
the secondary winding of the transformer is connected with an alternating current power grid;
the main controller is connected to the dc-side devices in each of the photovoltaic subsystems, and executes the method for diagnosing a fault of a photovoltaic device according to any one of the first aspect of the present invention.
Optionally, the dc-side device includes a photovoltaic string and a string inverter;
alternatively, the first and second electrodes may be,
the direct current side equipment comprises a photovoltaic string, a combiner box and a centralized inverter.
In a third aspect, the present invention provides a server, comprising: a memory and a processor; the memory stores a program adapted to be executed by the processor to implement the method for diagnosing the failure of the photovoltaic device according to any one of the first aspect of the present invention.
According to the photovoltaic equipment fault diagnosis method provided by the invention, after target diagnosis data related to the running process of the equipment to be diagnosed is obtained, whether the equipment to be diagnosed has the start-stop fault or not is judged according to the target diagnosis data, and if the equipment to be diagnosed has the start-stop fault, the alarm level is further determined according to the target diagnosis data. Compared with the prior art, the fault diagnosis method provided by the invention realizes fault diagnosis based on the target diagnosis data related to the running process of the equipment to be diagnosed, and further determines the alarm level, and the running state of the photovoltaic system does not need to be changed in the diagnosis process, so that the stable running of the photovoltaic system is ensured, and the stable generating capacity is provided.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for diagnosing a fault of a photovoltaic device according to an embodiment of the present invention;
fig. 2 is a flowchart of an alarm level determination method according to an embodiment of the present invention;
fig. 3 is a flowchart of a method for obtaining a theoretical starting time according to an embodiment of the present invention;
fig. 4 is a block diagram of a server according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, 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 application.
The photovoltaic equipment diagnosis method provided by the invention can be applied to any photovoltaic equipment which can obtain corresponding target diagnosis data and execute the control program realized based on the method provided by the invention in a photovoltaic system, and can also be applied to other electronic equipment independent of the photovoltaic system, wherein the electronic equipment can be a notebook computer or a PC, and certainly, under certain conditions, the method can also be realized by a server on a network side.
Referring to fig. 1, fig. 1 is a flowchart of a method for diagnosing a fault of a photovoltaic device according to an embodiment of the present invention, where the method may include:
s100, target diagnosis data related to the operation process of the equipment to be diagnosed are obtained.
The photovoltaic equipment diagnosis method provided by the embodiment of the invention and the subsequent embodiments is mainly used for diagnosing whether the direct current side equipment in the photovoltaic system has faults or not, in practical application, the direct current side equipment in the photovoltaic system is different due to different specific architectures of the photovoltaic system, and can be roughly divided into two types based on the difference of inverter type selection, if the inverter selects a centralized inverter, the direct current side equipment related in the invention mainly comprises the centralized inverter, a combiner box and a photovoltaic string; if the inverter is a string-type inverter, correspondingly, the direct-current side equipment related to the invention mainly comprises the string-type inverter and a photovoltaic string.
Based on the above, the device to be diagnosed mentioned in the present embodiment may be any one or more of the devices on the dc side of the photovoltaic system. In practical application, the selection of the actual number of the devices to be diagnosed should be determined by combining hardware resources and data processing capability of the electronic device to which the diagnosis method provided by the present invention is applied, and a plurality of devices to be diagnosed are diagnosed at the same time, which naturally corresponds to a higher hardware performance requirement, and under the condition of limited hardware performance, the diagnosis can be performed on one device to be diagnosed at a time, and then the diagnosis of the whole photovoltaic system is completed in a traversal manner.
Optionally, the target diagnosis data described in this embodiment may include a theoretical starting time of the device to be diagnosed, sampling values corresponding to a plurality of historical times of a target electrical parameter corresponding to the device to be diagnosed at and before the current time, and a corresponding preset starting and judging threshold value. It should be noted that, because the photovoltaic system converts solar energy into electrical energy, the working process must be performed under the condition of illumination, and may be regarded as a natural day as a working cycle, the natural day to which the current time for diagnosis belongs is defined as a diagnosis day according to the present scheme, and based on this, the current time and a plurality of historical times before the current time belong to the same natural day, that is, the diagnosis day. Correspondingly, the theoretical starting time refers to the theoretical starting time of the equipment to be diagnosed within the diagnosis day. The specific application of each target diagnostic data will be developed in the following, and will not be detailed here.
Alternatively, the target diagnostic data may be derived from a cloud platform of the photovoltaic system, or other data storage system having similar functions and capable of storing historical operating data, current operating data, and corresponding weather type data of each photovoltaic device in the photovoltaic system. It should be noted that, no matter what implementation is adopted, the method does not interfere or control the operation process of the photovoltaic system in the process of acquiring the target diagnosis data.
And S110, judging whether the equipment to be diagnosed has start-stop faults or not according to the target diagnosis data, and if so, executing S120.
As described above, the start-stop failure of the photovoltaic device mainly includes two types, one is a start-up delay failure, and the other is an abnormal shutdown failure. When the judgment is carried out, whether the equipment to be diagnosed has the start delay fault or not is judged according to the theoretical start time and the current time of the equipment to be diagnosed and the sampling value corresponding to the target electrical parameter, and if the equipment to be diagnosed does not have the start delay fault, whether the equipment to be diagnosed has the abnormal shutdown fault or not is judged according to each sampling value corresponding to the target electrical parameter and a preset start judgment threshold value. On the contrary, if the starting delay fault of the diagnostic equipment is judged, the subsequent abnormal shutdown fault judgment is not needed, because the equipment to be diagnosed is likely not to be started successfully, and the abnormal shutdown fault judgment is not practical.
Optionally, an embodiment of the present invention provides a method for diagnosing a start-up delay fault. Firstly, calculating the time difference between the current time corresponding to the current diagnosis process and the theoretical starting time of the equipment to be diagnosed to obtain the diagnosis duration; if the obtained diagnosis time length is greater than the preset time length threshold value and the sampling values corresponding to all the moments acquired in the previous steps are all zero, the starting delay fault of the equipment to be diagnosed can be judged, and correspondingly, if the obtained diagnosis time length is less than or equal to the preset time length threshold value or any sampling value is not zero, the starting delay fault of the equipment to be diagnosed can be judged not to occur.
The selection of the preset duration threshold needs to be determined by combining historical operating data and historical meteorological data of the device to be diagnosed, if the operating process or the operating environment of the device to be diagnosed is not stable enough, and a situation that the start-up is late or the change of the start-up time is large often occurs, the preset duration threshold can be set to be a large value, if the operating situation of the device to be diagnosed is opposite to the above-mentioned situation or the requirement on the control precision is high, the preset duration threshold can be set to be a small value appropriately, of course, the preset duration threshold can also be set to be a duration range, and the judgment condition can be determined to be met as long as the obtained diagnosis duration is within the duration range.
Optionally, for the diagnosis of the abnormal shutdown fault, firstly, the sampling values are sorted according to a time sequence, that is, according to the existing sequence of the sampling time, to obtain a sorting result, then, whether a target sampling value larger than a preset starting judgment threshold is included in the sorting result is judged, if the target sampling value is included in the sorting result and each sampling value behind the target sampling value is finally reduced to zero, it is judged that the abnormal shutdown fault occurs to the device to be diagnosed, and conversely, if the target sampling value larger than the preset starting judgment threshold is not included in the sorting result, or each sampling value behind the target sampling value is larger than zero, it is judged that the abnormal shutdown fault does not occur to the device to be diagnosed.
In practical applications, the target electrical parameters corresponding to different devices to be diagnosed are also different. In the embodiment of the present invention, if the device to be diagnosed is an inverter (including the aforementioned string inverter and centralized inverter), the target electrical parameter mainly includes the active power of the inverter; if the equipment to be diagnosed is a junction box, the target electrical parameter mainly refers to the total direct current power of the junction box, and optionally, the target electrical parameter can be obtained by calculating the total direct current corresponding to the junction box and the direct current bus voltage. If the equipment to be diagnosed is the photovoltaic string, the target electrical parameter is correspondingly the maximum allowable access current of the combiner box or the string type inverter connected with the photovoltaic string.
Correspondingly, the preset starting judgment threshold values corresponding to different target electrical parameters and the determination process of the preset starting judgment threshold values are different. The embodiment of the invention provides a method for determining a corresponding preset starting judgment threshold value for different equipment to be diagnosed, which comprises the following specific steps:
if the equipment to be diagnosed is an inverter, firstly, a rated value and a first preset coefficient of active power of the inverter are obtained, and the product of the rated value and the first preset coefficient of the active power is used as a preset starting judgment threshold value of the inverter.
If the equipment to be diagnosed is a junction box, firstly, the sum of the peak powers of all photovoltaic group strings connected with the junction box is calculated to obtain a rated value of the total direct current power of the junction box, and then the product of the rated value of the total direct current power and a second preset coefficient is used as a preset judgment starting threshold value of the junction box.
If the equipment to be diagnosed is the photovoltaic string, firstly, a rated value and a third preset coefficient of the maximum allowable access current of the photovoltaic string are obtained, and the product of the rated value and the third preset coefficient of the maximum allowable access current of the photovoltaic string is used as a preset starting judgment threshold value of the photovoltaic string.
It should be noted that, for the first preset coefficient, the second preset coefficient, and the third preset coefficient mentioned above, it needs to be flexibly set in combination with the actual application scenario. In practical application, because the output conditions of the photovoltaic system in different areas and different weathers are greatly different and an over-matching phenomenon mostly exists, the capacity ratio in different resource areas is different, and the electronic device executing the diagnosis method provided by the embodiment of the invention is extremely sensitive to data, a corresponding preset judgment starting threshold value needs to be set according to a practical application scene so as to eliminate the influence of weather factors on the running state of the device to be diagnosed and reduce the probability of misjudgment. For example, the system defaults to an abnormal shutdown of all power stations under 0.5 times rated power without attention, because a lot of statistics show that the shutdown under the power is mostly caused by extreme weather, and no alarm is needed. However, the power station conditions of different types in different areas are different, and a user can adjust the value to be larger or smaller according to the actual condition of the power station.
And S120, determining the alarm level according to the target diagnosis data.
As described above, the start-stop fault of the device to be diagnosed mainly includes a delayed start fault and an abnormal shutdown fault, and the alarm level is determined according to the target diagnosis data when the delayed start fault and/or the abnormal shutdown fault occur in the device to be diagnosed.
If only one device to be diagnosed with the start-stop fault exists, the alarm level can be determined directly based on the target diagnosis data of the device to be diagnosed, and if a plurality of devices to be diagnosed with the start-stop fault exist, different processing modes can be adopted.
Optionally, referring to fig. 2, fig. 2 is a flowchart of an alarm level determining method provided in the embodiment of the present invention, where the flowchart includes:
and S200, taking each device to be diagnosed with the start-stop fault as a target device.
For each device to be diagnosed without start-stop failure, the device does not participate in the processing procedure of the embodiment shown in fig. 2.
S210, determining the highest-level target equipment in the target equipment according to the preset equipment level.
Optionally, as described above, the dc-side device in the photovoltaic system includes the inverter, the combiner box, and the photovoltaic string, and as an optional preset device level sorting manner, the inverter is set to be at the highest level, and then the combiner box is set, and the lowest level is the photovoltaic string. Of course, in the case where no combiner box is included, the inverter is then the photovoltaic string.
According to the preset equipment grade, the target equipment with the highest grade can be determined in all the target equipment.
And S220, determining the alarm level according to the target diagnosis data of the target equipment with the highest level.
Optionally, this embodiment provides a preset mapping relationship, where the preset mapping relationship records a corresponding relationship between different alarm scores and alarm levels, and based on this, after determining the current alarm score according to the target diagnostic data of the target device with the highest level, the preset mapping relationship is queried, so that the alarm level corresponding to the current alarm score can be determined.
The specific embodiment form of the preset mapping relationship may be implemented based on the prior art, for example, the specific embodiment form of the preset mapping relationship may be an array form or a chart form.
Alternatively, the current alert score for the highest ranked target device may be determined as follows.
Firstly, determining the index value of each alarm scoring index of the target equipment with the highest grade according to the scoring mapping relation corresponding to each alarm scoring index. The target diagnosis data provided by this embodiment further includes a plurality of alarm score indicators, which at least include a current weather type on a diagnosis day, a historical weather type on a natural day that is a preset number of days before the diagnosis day, an equipment type, and an alarm time. The equipment type specifically comprises an inverter, a combiner box and a photovoltaic group string, and the alarm time can be directly selected from the current time.
For example, the weather type is sunny day, and the index value is 1; the weather type is non-sunny day, and the index value is 0; the equipment type is the inverter, and the index value is 1, and the equipment type is collection flow box or photovoltaic group cluster, and the index value is 0. And analogizing in turn, and recording index values of the alarm score indexes under different conditions in the score mapping relation corresponding to each alarm score index.
Then, after the index value of each alarm scoring index is determined, the weight coefficient corresponding to each alarm scoring index is obtained, the index weighted value of each alarm scoring index is respectively calculated according to the index value and the weight coefficient corresponding to each alarm scoring index, and the sum of the index weighted values is used as the current alarm score of the target equipment with the highest grade.
The weight coefficient of each alarm scoring index can be flexibly selected according to the importance of each alarm scoring index and the influence degree on the normal operation of the photovoltaic system, and the method is not limited to this.
It is conceivable that the lower the alarm score is, the higher the alarm level is, based on the above-described manner of calculating the alarm score. Based on the method, the alarm levels can be divided into a level I, a level II and a level III, wherein the level I is the most serious and needs to be processed immediately, the level II is more serious and needs to be processed in time, and the level III is relatively serious and needs to be arranged for processing. Of course, other level divisions can be set according to actual conditions, and are not listed here.
In the embodiment shown in fig. 2, the alarm level is determined according to the target diagnostic data of the target device with the highest level, and as another alternative implementation manner, the alarm level of each device to be diagnosed with the start-stop fault may be determined according to the target diagnostic data corresponding to each device to be diagnosed with the start-stop fault, that is, the alarm level of each device to be diagnosed with the start-stop fault is obtained. As for the specific method for determining the alarm level, the foregoing can be referred to, and the description is not repeated here.
In summary, the photovoltaic device diagnosis method provided by the invention realizes fault diagnosis based on the target diagnosis data related to the operation process of the device to be diagnosed, and further determines the alarm level, and the operation state of the photovoltaic system does not need to be changed in the diagnosis process, thereby being beneficial to ensuring the stable operation of the photovoltaic system and further providing stable power generation.
Furthermore, as the basic data are derived from the cloud platform of the photovoltaic system, any other additional hardware equipment does not need to be added in the photovoltaic system, and the increase of the construction cost and the operation and maintenance cost of the photovoltaic system cannot be caused.
And judging whether the equipment to be diagnosed has the process of starting and stopping faults or not, setting a corresponding preset starting and judging threshold value, eliminating the influence of bad weather conditions, contributing to improving the precision of fault diagnosis and avoiding false alarm. Meanwhile, on the basis of setting the levels for each direct current side device, the alarm level is determined from two dimensions of weather and time, and a more accurate real-time diagnosis result with more detailed hierarchical division is provided for operation and maintenance.
In addition, the whole diagnosis process is completed based on data information in the cloud platform, and compared with a diagnosis method which can be realized only by arranging separate sampling equipment or controlling the operation process of the photovoltaic system in the prior art, the diagnosis method provided by the embodiment has higher execution efficiency and can effectively reduce operation and maintenance cost.
Optionally, in the foregoing embodiment, the process of determining whether the start-up delay fault occurs in the device to be diagnosed is completed based on a theoretical start-up time of the device to be diagnosed within a diagnosis day, and an optional method for determining the theoretical start-up time is further provided in the embodiment of the present invention, referring to fig. 3, a flow of the theoretical start-up time determining method includes:
s300, acquiring a plurality of historical value sets of the target electrical parameters.
It should be emphasized that, in the foregoing, the target electrical parameter corresponds to a sampling value at a current time and sampling values at a plurality of historical times, the current time and the historical times belong to the same natural day, that is, within a diagnosis day, and any one of the historical value sets in this step corresponds to a historical natural day before the natural day to which the current time belongs, that is, each historical value set is acquired on a natural day between the diagnosis days, for example, historical values at 30 natural days before the diagnosis day may be acquired, and a plurality of historical values of the target electrical parameter are included in any one of the historical value sets.
As for the acquisition process of each historical value set, the acquisition process can be implemented by combining the prior art, and the present invention is not limited to this.
And S310, sorting the historical values in the historical value sets according to time sequence.
And sorting all the historical values in the historical value set according to the occurrence time corresponding to the historical value to obtain a corresponding sorting result. It should be emphasized here that the sorting of the history values is not performed in the time sequence of acquisition, but in accordance with the occurrence time corresponding to the history values. Furthermore, the purpose of obtaining the historical values is to determine the theoretical starting time, so the historical values in each historical value set should be selected as far as possible, in practical application, the startup time range of the photovoltaic system can be determined according to the historical data of the specific photovoltaic system, and the historical values are collected in the startup time range.
S320, respectively determining the historical value of the first non-zero value in each historical value set according to the sequencing result of each historical value set to obtain the corresponding target historical value.
The first non-zero value of the history value, which corresponds to the first valid output of the device to be diagnosed after the device is turned on, is defined as a target history value in this embodiment.
And S330, taking the occurrence time corresponding to each target historical value as the historical starting time of the corresponding historical natural day.
The occurrence time corresponding to the target history value corresponding to any historical natural day can be determined as the historical starting time of the historical natural day.
It is conceivable that, since discrete historical values are obtained, in order to improve the accuracy of the historical starting time as much as possible, the sampling density of the historical values must be increased, and accordingly, the requirements on the data transmission and data storage capacity of the hardware device are increased, so that in practical applications, an appropriate sampling density should be selected in combination with the performance of the hardware device to seek a balance between accuracy and execution efficiency.
And S340, determining theoretical starting time according to the historical starting time.
Optionally, each historical starting time is converted into a corresponding true solar time to obtain a corresponding starting true solar time.
The conversion formula of the true solar time is as follows:
wherein LST represents the time of starting the true sun;
LT represents the historical starting time;
TC represents a time correction factor, TC ═ 4 × (Longitude-120) + E;
wherein Longitude represents the Longitude of the position of the photovoltaic system, and E is a time equation. The solving formula of the time equation is as follows: e ═ 9.87 × sind (2 × B) -7.53 × cosd (B) -1.5 × sind (B).
The solution formula for B in the time equation is:
where N indicates that the corresponding historical natural day belongs to the day of the year.
And secondly, screening each starting true solar time according to a preset screening algorithm to obtain a corresponding screening result. For example, a box-type graph algorithm can be selected to provide the abnormal time in each real solar starting time, and certainly, other modes can be adopted to realize the data definition.
And finally, taking the average value of all the starting true solar time included in the screening result as the theoretical starting time.
Optionally, as described above, the number of the dc-side devices in the photovoltaic system is large, and if diagnosis of each dc-side device needs to occupy a large amount of hardware resources of the electronic device, as an optional implementation manner, each dc-side device in the photovoltaic system may be used as a device to be diagnosed, and the dc-side devices may be diagnosed in batches and repeatedly according to the diagnosis method provided in any of the above embodiments until all the dc-side devices in the photovoltaic system are traversed, so as to complete diagnosis of the photovoltaic system.
Optionally, an embodiment of the present invention further provides a photovoltaic system, including: at least one path comprises a photovoltaic subsystem, a transformer and a main controller of direct current side equipment, wherein,
the alternating current output end of each photovoltaic subsystem is connected with the primary winding of the transformer;
the secondary winding of the transformer is connected with an alternating current power grid;
the main controller is connected with the direct-current side equipment in each photovoltaic subsystem respectively, and executes the photovoltaic equipment fault diagnosis method provided by any one of the embodiments.
Optionally, the dc-side device includes a photovoltaic string and a string inverter;
alternatively, the first and second electrodes may be,
the direct current side equipment comprises a photovoltaic string, a combiner box and a centralized inverter.
Optionally, referring to fig. 4, fig. 4 is a block diagram of a server according to an embodiment of the present invention, and as shown in fig. 4, the server may include: at least one processor 100, at least one communication interface 200, at least one memory 300, and at least one communication bus 400;
in the embodiment of the present invention, the number of the processor 100, the communication interface 200, the memory 300, and the communication bus 400 is at least one, and the processor 100, the communication interface 200, and the memory 300 complete the communication with each other through the communication bus 400; it is clear that the communication connections shown by the processor 100, the communication interface 200, the memory 300 and the communication bus 400 shown in fig. 4 are merely optional;
optionally, the communication interface 200 may be an interface of a communication module, such as an interface adapted to a vehicle-mounted OBD interface or other CAN network interfaces;
the processor 100 may be a central processing unit CPU or an application Specific Integrated circuit asic or one or more Integrated circuits configured to implement embodiments of the present invention.
The memory 300, which stores application programs, may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.
The processor 100 is specifically configured to execute an application program in the memory to implement any embodiment of the photovoltaic device diagnosis method described above.
The embodiments of the invention are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments can be referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The foregoing is merely a preferred embodiment of the invention and is not intended to limit the invention in any manner. Although the present invention has been described with reference to the preferred embodiments, it is not intended to be limited thereto. Those skilled in the art can make numerous possible variations and modifications to the present teachings, or modify equivalent embodiments to equivalent variations, without departing from the scope of the present teachings, using the methods and techniques disclosed above. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.
Claims (18)
1. A method for diagnosing faults of photovoltaic equipment is characterized by comprising the following steps:
acquiring target diagnosis data related to the operation process of equipment to be diagnosed;
judging whether the equipment to be diagnosed has start-stop faults or not according to the target diagnosis data;
and if the equipment to be diagnosed has the start-stop fault, determining an alarm level according to the target diagnosis data.
2. The photovoltaic apparatus fault diagnosis method according to claim 1, wherein the target diagnosis data includes: the method comprises the following steps of (1) sampling values corresponding to a theoretical starting moment, a plurality of historical moments of target electrical parameters at the current moment and before the current moment, and a preset starting judgment threshold;
the judging whether the equipment to be diagnosed has the start-stop fault according to the target diagnosis data comprises the following steps:
judging whether the equipment to be diagnosed has a start delay fault or not according to the theoretical start time, the current time and each sampling value;
and if the equipment to be diagnosed has no start delay fault, judging whether the equipment to be diagnosed has an abnormal shutdown fault or not according to the sampling values and the preset start judgment threshold value.
3. The method for diagnosing the faults of the photovoltaic equipment according to claim 2, wherein the step of judging whether the equipment to be diagnosed has the startup delay fault or not according to the theoretical startup time, the current time and each sampling value comprises the following steps:
calculating the difference between the current time and the theoretical starting time to obtain diagnosis duration;
if the diagnosis time length is greater than a preset time length threshold value and each sampling value is zero, judging that the equipment to be diagnosed has a start delay fault;
and if the diagnosis time length is less than or equal to the preset time length threshold value or any sampling value is not zero, judging that the equipment to be diagnosed has no start delay fault.
4. The method for diagnosing the faults of the photovoltaic equipment according to claim 2, wherein the step of judging whether the equipment to be diagnosed has the abnormal shutdown fault or not according to each sampling value and the preset starting judgment threshold value comprises the following steps:
sequencing the sampling values according to a time sequence to obtain a sequencing result;
judging whether the sequencing result comprises a target sampling value which is larger than the preset judgment starting threshold value or not;
if the sequencing result comprises the target sampling value and each sampling value behind the target sampling value is finally reduced to zero, judging that the equipment to be diagnosed has abnormal shutdown fault;
and if the sequencing result does not include the target sampling value, or all sampling values after the target sampling value are larger than zero, judging that the equipment to be diagnosed has no abnormal shutdown fault.
5. The method for diagnosing the fault of the photovoltaic equipment according to claim 2, wherein the process of obtaining the theoretical starting moment comprises:
obtaining a plurality of sets of historical values for the target electrical parameter;
any historical value set corresponds to a historical natural day before the natural day to which the current time belongs;
sorting each historical value in each historical value set according to time sequence;
according to the sequencing result of each historical value set, respectively determining the historical value of the first non-zero value in each historical value set to obtain a corresponding target historical value;
taking the occurrence time corresponding to each target historical value as the historical starting time of the corresponding historical natural day;
and determining the theoretical starting time according to the historical starting times.
6. The method according to claim 5, wherein the determining the theoretical starting time from each historical starting time comprises:
respectively converting each historical starting time into corresponding true solar time to obtain corresponding starting true solar time;
screening each starting true solar time according to a preset screening algorithm;
and taking the average value of the starting true solar time included in the screening result as the theoretical starting moment.
7. The method according to claim 2, wherein if the device to be diagnosed includes an inverter, the target electrical parameter includes active power;
if the equipment to be diagnosed comprises a combiner box, the target electrical parameter comprises total direct current power;
if the equipment to be diagnosed comprises a photovoltaic string, the target electrical parameter comprises a maximum allowable access current.
8. The method for diagnosing the fault of the photovoltaic equipment according to claim 7, wherein if the equipment to be diagnosed includes an inverter, the process of obtaining the preset starting judgment threshold value includes:
obtaining a rated value and a first preset coefficient of active power of the inverter;
taking the product of the rated value of the active power and the first preset coefficient as a preset starting judgment threshold value of the inverter;
if the equipment to be diagnosed comprises a combiner box, acquiring the process of the preset starting judgment threshold value, comprising the following steps:
calculating the sum of peak power of each photovoltaic group string connected with the combiner box to obtain a rated value of the total direct current power of the combiner box;
taking the product of the rated value of the rated total direct current power and a second preset coefficient as a preset judgment starting threshold value of the combiner box;
if the device to be diagnosed comprises a photovoltaic string, acquiring the preset starting judgment threshold value, wherein the process comprises the following steps:
obtaining a rated value and a third preset coefficient of the maximum allowable access current of the photovoltaic group string;
and taking the product of the rated value of the maximum allowable access current of the photovoltaic group string and the third preset coefficient as a preset starting judgment threshold value of the photovoltaic group string.
9. The method according to claim 1, wherein if there are a plurality of devices to be diagnosed with the start-stop fault, the determining an alarm level according to the target diagnosis data includes:
taking each device to be diagnosed with the start-stop fault as a target device;
determining the highest-grade target equipment in all the target equipment according to a preset equipment grade;
and determining the alarm grade according to the target diagnosis data of the target equipment with the highest grade.
10. The method for diagnosing the fault of the photovoltaic equipment, according to claim 9, wherein the step of determining the alarm level according to the target diagnosis data of the target equipment with the highest level comprises the following steps:
determining a current alarm score according to the target diagnosis data of the target equipment with the highest grade;
inquiring a preset mapping relation, and determining an alarm grade corresponding to the current alarm score;
wherein, the preset mapping relation records the corresponding relation between different alarm scores and alarm grades.
11. The photovoltaic equipment fault diagnosis method according to claim 10, wherein the target diagnosis data includes a plurality of alarm score indicators;
the determining a current alarm score according to the target diagnostic data of the target device with the highest grade includes:
determining the index value of each alarm score index according to the score mapping relation corresponding to each alarm score index;
and determining the current alarm score of the target equipment with the highest grade according to each index value.
12. The method for diagnosing the faults of the photovoltaic equipment, according to claim 11, wherein the step of determining the current alarm score of the target equipment with the highest grade according to each index value comprises the following steps:
acquiring a weight coefficient corresponding to each alarm scoring index;
respectively calculating the index weighted value of each alarm scoring index according to the index value and the weight coefficient corresponding to each alarm scoring index;
and taking the sum of the weighted values of the indexes as the current alarm score of the target equipment with the highest grade.
13. The photovoltaic device fault diagnosis method according to claim 11, wherein the alarm score indicator includes: the current weather type of the diagnosis day, the historical weather type of the natural day of the preset number of days before the diagnosis day, the equipment type and the alarm time;
wherein the diagnosis day is a natural day to which the current time belongs.
14. The method according to claim 1, wherein if there are a plurality of devices to be diagnosed with the start-stop fault, the determining an alarm level according to the target diagnosis data includes:
and determining the alarm level of each device to be diagnosed with the start-stop fault according to the target diagnosis data corresponding to each device to be diagnosed with the start-stop fault.
15. The photovoltaic apparatus fault diagnosis method according to any one of claims 1 to 14, characterized by further comprising:
and respectively taking each direct current side device in the photovoltaic system as a device to be diagnosed.
16. A photovoltaic system, comprising: at least one path comprises a photovoltaic subsystem, a transformer and a main controller of direct current side equipment, wherein,
the alternating current output end of each photovoltaic subsystem is connected with the primary winding of the transformer;
the secondary winding of the transformer is connected with an alternating current power grid;
the main controller is respectively connected with the direct-current side equipment in each photovoltaic subsystem, and executes the photovoltaic equipment fault diagnosis method according to any one of claims 1 to 15.
17. The pv system of claim 16 wherein the dc-side equipment comprises pv strings and string inverters;
alternatively, the first and second electrodes may be,
the direct current side equipment comprises a photovoltaic string, a combiner box and a centralized inverter.
18. A server, comprising: a memory and a processor; the memory stores a program adapted to be executed by the processor to implement the photovoltaic device fault diagnosis method according to any one of claims 1 to 15.
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