CN116865669A - Distributed photovoltaic fault detection system - Google Patents

Distributed photovoltaic fault detection system Download PDF

Info

Publication number
CN116865669A
CN116865669A CN202310807464.2A CN202310807464A CN116865669A CN 116865669 A CN116865669 A CN 116865669A CN 202310807464 A CN202310807464 A CN 202310807464A CN 116865669 A CN116865669 A CN 116865669A
Authority
CN
China
Prior art keywords
photovoltaic
photovoltaic panel
region
gray value
panel
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
CN202310807464.2A
Other languages
Chinese (zh)
Inventor
贺松波
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hunan Huachenyue Technology Co ltd
Original Assignee
Hunan Huachenyue Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hunan Huachenyue Technology Co ltd filed Critical Hunan Huachenyue Technology Co ltd
Priority to CN202310807464.2A priority Critical patent/CN116865669A/en
Publication of CN116865669A publication Critical patent/CN116865669A/en
Withdrawn legal-status Critical Current

Links

Classifications

    • 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
    • H02S50/00—Monitoring or testing of PV systems, e.g. load balancing or fault identification
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
    • 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
    • H02S40/00—Components or accessories in combination with PV modules, not provided for in groups H02S10/00 - H02S30/00
    • H02S40/30—Electrical components
    • 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
    • H02S50/00—Monitoring or testing of PV systems, e.g. load balancing or fault identification
    • H02S50/10—Testing of PV devices, e.g. of PV modules or single PV cells
    • 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
    • H02S50/00—Monitoring or testing of PV systems, e.g. load balancing or fault identification
    • H02S50/10—Testing of PV devices, e.g. of PV modules or single PV cells
    • H02S50/15—Testing of PV devices, e.g. of PV modules or single PV cells using optical means, e.g. using electroluminescence
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Human Computer Interaction (AREA)
  • Photovoltaic Devices (AREA)

Abstract

The invention relates to the technical field of distributed photovoltaic fault detection, in particular to a distributed photovoltaic fault detection system, which is characterized in that an area photovoltaic distribution zoning module, an area photovoltaic panel basic parameter acquisition module, an area photovoltaic panel operation parameter acquisition module, an area operation parameter detection analysis module, a cloud database and an area intelligent display terminal are arranged, so that the traditional photoelectric output detection is more efficient and rapid by utilizing a cloud, each area distributed photovoltaic panel is subjected to high-definition thermal imaging image acquisition by utilizing an unmanned plane, modern novel image processing and cloud contrast analysis are utilized, and meanwhile, the photoelectric, temperature, hot spots, environment, shadow, dust and extreme weather comprehensive influences of each area distributed photovoltaic panel are considered, so that compared with the traditional detection, the comprehensive and accurate rate of a photovoltaic system are improved, each state of the system is intuitively known in real time by the area intelligent display terminal, and the observability and detection efficiency of the system are enhanced.

Description

Distributed photovoltaic fault detection system
Technical Field
The invention relates to the technical field of distributed photovoltaic fault detection, in particular to a distributed photovoltaic fault detection system.
Background
The rapid consumption of earth energy makes people pay more attention to the use of renewable energy, a photovoltaic power generation plate is power generation equipment for converting light energy into electric energy by utilizing the photovoltaic effect, when light irradiates on a semiconductor material, photons interact with atoms in the material to excite electrons and electron hole pairs so as to generate current, so that the output and transmission of electric power are realized, a photovoltaic power generation system can be distributed and deployed, a plurality of small-scale photovoltaic systems are distributed in places such as buildings, roofs and solar agricultural greenhouses, the cost of electric energy transmission loss and line construction is effectively reduced, the self-sufficiency of the photovoltaic power generation system can be promoted, the dependence on external energy supply is reduced, the energy safety is enhanced, but the photoelectric effect, the temperature, the hot spots, the environment, the shadows, the dust and the extreme comprehensive influence of the distributed photovoltaic plate are not considered at the same time, the comprehensive and accurate analysis cannot be realized, and therefore, the accurate positioning and the operation risk and the stability of the photovoltaic system based on the distributed photovoltaic fault detection system are required.
The prior art has a great degree of limitation on fault detection of distributed photovoltaic, and specific layers comprise:
1. in the distributed photovoltaic system, the distributed photovoltaic is different from the large-area array photovoltaic, the large system can be integrated for unified management, the distributed photovoltaic is scattered and relatively independent, and if the fault is reported by the detection system, the component corresponding to the parameter of the fault is required to be accurately positioned in time. Because the photovoltaic system is affected by a number of factors, the fault may be caused by different factors, and conventional detection methods cannot accurately locate the fault point and require a lot of time and effort.
2. In the distributed photovoltaic system, the existing detection system is mainly used for carrying inspection equipment by inspection personnel to carry out regular and fixed-point inspection, and the traditional inspection mode only can be used for inspecting the output voltage and current of the photovoltaic panel, and potential abnormal operation factors of the distributed photovoltaic panel cannot be scientifically and comprehensively screened, so that timeliness of response processing of the distributed photovoltaic panel is greatly reduced, and frequency of photovoltaic power generation sudden faults in a corresponding area is increased. Meanwhile, the distributed photovoltaic panels are scattered and independent, the period for detecting and judging the abnormality is long, the fixed maintenance cost is high, and the reasonable and efficient maintenance operation of the distributed photovoltaic panels is not facilitated.
3. In the distributed photovoltaic system, the existing detection system lacks judgment on the influences of specific distributed photovoltaic surface hot spots, surface dust, surface shadows and air dust and eliminates the destructive disturbance of extreme weather on the distributed photovoltaic detection, does not have cloud data ends for analyzing and judging all factors, does not have specific visual data chart reports on all factors, lacks visual and effective observation of each specific operation condition of the distributed photovoltaic panel, cannot detect and judge specific operation parameters of the distributed photovoltaic panel in real time, and has extremely low efficiency and accuracy.
Disclosure of Invention
In order to overcome the defects in the background technology, the embodiment of the invention provides a distributed photovoltaic fault detection system, which can effectively solve the problems related to the background technology.
The aim of the invention can be achieved by the following technical scheme: a distributed photovoltaic fault-based detection system, comprising: the system comprises a regional photovoltaic distribution zoning module, a regional photovoltaic panel basic parameter acquisition module, a regional photovoltaic panel operation parameter acquisition module, a regional operation parameter detection analysis module, a cloud database and a regional intelligent display terminal. And the regional photovoltaic distribution zoning module divides the distributed photovoltaic into a plurality of regions, wherein each region corresponds to a plurality of photovoltaic panels respectively and is marked as each regional photovoltaic panel. The regional photovoltaic panel basic parameter acquisition module is used for acquiring basic parameters of the photovoltaic panels in all regions and evaluating photoelectric coincidence coefficients. The regional photovoltaic panel operation parameter acquisition module is used for acquiring operation parameters of the regional photovoltaic panels, acquiring high-definition thermal imaging images of the regional photovoltaic panels, performing image processing on the acquired high-definition thermal imaging images of the regional photovoltaic panels, and evaluating an operation temperature coincidence coefficient and a light absorption weakening index according to an image processing result. The regional operation parameter detection and analysis module is used for acquiring and analyzing the operation parameters of the photovoltaic panels in each region according to the photoelectric coincidence coefficient, the operation temperature coincidence coefficient and the light absorption weakening index of the photovoltaic panels in each region and evaluating the operation risk index corresponding to the photovoltaic panels in each region. The cloud database is used for storing basic parameters and operation parameters of the photovoltaic panels in all areas, evaluation results obtained according to the parameters and data of the processing process, and storing predefined gray values under image processing. And the regional intelligent display terminal is used for comprehensively displaying according to the running risk indexes of the photovoltaic panels in each region and the basic parameters and the running parameters of the photovoltaic panels in each region of the cloud database.
As a preferred design scheme, the cloud database is used for storing each basic parameter and each operation parameter of each regional photovoltaic panel, and the evaluation result and the data of the processing procedure obtained according to each parameter, and specifically includes: the cloud database stores various operation parameters of the photovoltaic panels in each region, including predefined ageing loss factors of the photovoltaic panels in each region, factors affecting the photovoltaic panels in each region by the shadow coverage of the photovoltaic panels in each region, predefined extreme weather correction factors of the photovoltaic panels in each region, factors affecting the photovoltaic panels in each region by the air dust density under a predefined standard gray value, and factors affecting the photovoltaic panels in each region by the dust density on the photovoltaic panels in each region under a predefined standard gray value. And determining a starting temperature and an ambient temperature gray value image by the predefined hot spots of the photovoltaic panel in each area. And the predefined values correspond to gray values under the image processing of the photovoltaic panels of the areas, and the predefined values comprise the predefined gray values corresponding to the standard temperatures of the photovoltaic panels of the areas, the predefined standard illumination dust-free matching standard gray values of the photovoltaic panels of the areas and the predefined shade threshold matching standard gray values of the photovoltaic panels of the areas.
As a preferred design, the specific process of obtaining the basic parameters of each regional photovoltaic panel in the regional photovoltaic panel basic parameter obtaining module includes: determining the corresponding placement positions and numbers of the photovoltaic panels in each region, wherein n represents the numbers of the placement positions of the photovoltaic panels in each region, the placement positions and the numbers are in one-to-one correspondence, and dividing the use time length of the photovoltaic panels in each region by a plurality of equal ratios to obtain each detection time point, which is marked as t 0 ，t 0 =1, 2,..t. At each detection timeDetecting basic parameters of the photovoltaic panel in each region, wherein the basic parameters comprise output current, output voltage and illumination intensity of the photovoltaic panel in each regionEffective light area->The air dust density D is used for obtaining the output current and the output voltage of the photovoltaic panel corresponding to each region at each detection time point, and then the actual output power +.>And calculating to obtain the actual average output power of the photovoltaic panel in each region in each detection time>The serial numbers, the detection time points, the output currents, the output voltages, the illumination intensity, the effective light area, the output power and the air dust density D of the photovoltaic panel placed positions in each area are uploaded to the cloud database in real time. Matching the corresponding output power of each area light Fu Banguang of the effective light area of each area photovoltaic panel of the cloud database under the intensity interval to obtain the corresponding output power of each area photovoltaic panel of the effective light area of each area photovoltaic panel in each detection time pointAccording to each detection time point, matching with predefined aging loss factors of the photovoltaic panels in each region of the cloud database to obtain aging loss values +. >
As a preferred design scheme, the photoelectric coincidence coefficient α corresponding to the regional photovoltaic panel basic parameter acquisition module comprises the following specific acquisition steps: detecting a time point t according to the number n of the placement positions of the photovoltaic panels in each area 0 Corresponding actual output powerActual average output power +.>Effective light area->Intensity of illumination->Ageing loss value->And the corresponding output power of the photovoltaic panel of each region of the effective light area of the photovoltaic panel of each region +.>The specific calculation formula for calculating the photoelectric coincidence coefficient alpha is as follows: />Wherein->For the preset output power allowable deviation value of the photovoltaic panel corresponding to the battery panel in each region, +.>And uploading the photoelectric coincidence coefficient alpha to the cloud database in real time for outputting a stable influence factor of the output power of each preset region photovoltaic panel.
As a preferred design scheme, the module for acquiring the operation parameters of the regional photovoltaic panel is also used for judging the hot spot duty ratio of each regional photovoltaic panel, and the specific process comprises the following steps: the high-definition thermal imaging camera carried by the unmanned aerial vehicle shoots all the photovoltaic full panels in the areas in a short distance, and an operation temperature image and an environment temperature image of the photovoltaic panels in each area are obtainedWith predefined standard temperature K of cloud database 1 The corresponding gray value is used as a reference, all gray value points are counted after the gray value processing of the obtained temperature image, and the gray value points are recorded as m 0 ，m 0 Number n of each region photovoltaic panel placement position stored in the cloud database, and obtaining the actual operating temperature of each region photovoltaic panelDetermining initial temperature according to predefined hot spots of photovoltaic panels in each region of the cloud database>Setting a hot spot determination function->Counting all predefined hot spot judging initial temperatures of photovoltaic panels in all areas +.>The corresponding gray value points are counted, the ratio of the hot spots of the photovoltaic panel to the gray value of the whole panel in each region is marked as sigma, and the calculation formula is as follows: />And uploading the ratio sigma of the hot spots of the photovoltaic panels and the gray value of the full panel in each region to a cloud database in real time.
As a preferred design scheme, the operation temperature corresponding to the operation parameter acquisition module of the regional photovoltaic panel accords with a coefficient beta, and the specific acquisition steps are as follows: according to the ambient temperature gray value image of the cloud database, matching to obtain the ambient temperatureActual operating temperature of the photovoltaic panels in the respective region +.>Marking the ratio of the hot spot of the photovoltaic panel and the gray value of the whole panel in each region as sigma, calculating the operating temperature to be in line with the coefficient beta, and operatingThe specific calculation formula of the line temperature coincidence coefficient beta is as follows: / >Wherein->And (3) matching error factors for the temperature of the high-heat-clearing imaging gray value image of the unmanned aerial vehicle, wherein phi is an operation temperature correction factor of the photovoltaic panel in each region, and the operation temperature accords with the coefficient beta and is uploaded to the cloud database in real time.
As a preferred design scheme, the operation parameter obtaining module of the regional photovoltaic panel is further configured to determine the surface dust and surface shadow ratio of each regional photovoltaic panel and perform new gray level conversion on the gray level value of each actual point image of each regional photovoltaic panel, and the specific process includes: shooting all the photovoltaic full panels in the areas in a short distance through a high-definition thermal imaging camera carried by an unmanned aerial vehicle by the actual running image of the photovoltaic panel in each area to obtain a surface dust image and a surface shadow image of the photovoltaic panel in each area, counting all gray value points, and marking as j 0 ，j 0 =1, 2,..j, dividing the average use time length of each region photovoltaic panel by a plurality of equal ratios to obtain each gray value detection time point, and recording as g 0 ，g 0 The actual gray value of each point of each region photovoltaic panel at each gray value detection time point is obtained by the serial numbers n of the placing positions of each region photovoltaic panel, which are stored in the cloud database, of the number 1,2The gray value of the standard illumination dust-free matching standard gray value image of the photovoltaic panel in each area is predefined to be G according to the cloud database Without any means for Let surface dust determination function->Statistics of all G Without any means for The gray value points are counted, and the ratio of dust on the surface of the photovoltaic panel in each area to the gray value of the whole panel is marked as sigma 1 The calculation formula is as follows: />Ratio sigma of dust on surface of photovoltaic panel and gray value of full panel in each region 1 And uploading the cloud database in real time. The gray value of the photovoltaic panel shadow threshold matching standard gray value image of each region is predefined to be G according to the cloud database Yin type vagina Setting a surface shading determination functionStatistics of all G Without any means for The gray value points are counted, and the ratio of the shadow of the photovoltaic panel surface in each area to the gray value of the whole panel is recorded as sigma 2 The calculation formula is as follows: />Surface shading of photovoltaic panel in each region and full panel gray value occupation ratio sigma 2 And uploading the cloud database in real time. Reading the number n of the storage position of each region photovoltaic panel of the cloud database, simultaneously carrying out new gray level conversion on the gray level value of each region photovoltaic panel actual point image, and marking the new gray level value of each region photovoltaic panel actual point image as S n The specific calculation formula is ∈ ->Representation pair P r (r w ) Integration is carried out in the range 0 to r, wherein +.>j w The number of occurrences of the grey values of Fu Bandi w images of each region light is represented, j represents the total number of grey values of the actual points of the photovoltaic panel of each region, L-1 is the total value domain of the grey values of the actual points of the photovoltaic panel of each region, and r is the range of statistics required by the new grey values, namely ∈ - > For the maximum gray value of the actual points of the photovoltaic panel in each region,/->For the minimum gray value of the actual each point image of the photovoltaic panel in each region, r w The probability of occurrence of the w-th image gray value of the image of each actual point in the range of statistics required for representing the new gray value.
As a preferred design scheme, the light absorption weakening index corresponding to the regional photovoltaic panel operation parameter acquisition module is marked as omega, and the specific acquisition steps are as follows: marking the new gray value of the actual each point image of the photovoltaic panel according to each region as S n The ratio of the dust on the surface to the gray value of the whole plate is sigma 1 The ratio of the surface shading to the full plate gray value is recorded as sigma 2 And the air dust density D collected by the regional photovoltaic panel basic parameter module is used for calculating the light absorption weakening index omega, wherein the specific calculation formula of the light absorption weakening index omega is as follows:and H is the influence factor of the air dust density on the photovoltaic panel in each region under the predefined standard gray value of the cloud database, E is the influence factor of the dust density on the photovoltaic panel in each region under the predefined standard gray value of the cloud database, F is the influence factor of the shadow coverage on the photovoltaic panel in each region under the predefined standard gray value of the cloud database, and the light absorption weakening index omega is uploaded to the cloud database in real time.
As a preferred design, the operation risk index corresponding to the regional operation parameter detection and analysis module is Γ, and the specific obtaining steps are: according to the photoelectric coincidence coefficient alpha, the operation temperature coincidence coefficient beta and the light absorption weakening index omega of the photovoltaic panel in each region, an operation risk index gamma is calculated, and a specific calculation formula of the operation risk index gamma is as follows:wherein P is a predefined extreme weather correction factor of each region photovoltaic panel of the cloud database, Y is an integrated correction factor for gray value transformation of actual each point image of each region photovoltaic panel, and ψ is the light absorption weakening index of each region photovoltaic panelAnd uploading the operation risk index gamma to the cloud database in real time by using the correction factors of the electric coincidence coefficient and the operation temperature coincidence coefficient.
As a preferred design, the area intelligent display terminal performs comprehensive display, and specifically includes: and the data display module intuitively displays all basic parameters and all operation parameters of the photovoltaic panel in all areas stored in the cloud database in a chart form in real time, and checks historical data of the photovoltaic panel in all areas when needed. The fault diagnosis module judges the fault points and problems existing in the system according to the basic parameters, the operation parameters and the evaluation results of the photovoltaic panels in each area and provides corresponding alarms and prompts.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
1. the invention provides a distributed photovoltaic fault detection system, which can acquire basic parameters of a regional photovoltaic panel, respectively detect each distributed photovoltaic panel in the regional photovoltaic panel in a regional manner, and comprises a placement position, a serial number of the placement position, an output current, an output voltage, an effective light area, an output power and basic parameters including illumination intensity, comprehensively consider the illumination intensity and aging power to obtain photoelectric coincidence coefficients of the distributed photovoltaic panel, and upload the basic parameters and the photoelectric coincidence coefficients of the distributed photovoltaic panel to a cloud database in real time. Each parameter of each photovoltaic panel in each region can be detected in real time, distributed photovoltaic can be managed uniformly, and all detection parameters are in one-to-one correspondence with each region photovoltaic, so that all fault detection errors can be timely determined in specific positions and fault points, the detection efficiency is improved, and the time and energy of fault detection are saved.
2. The invention provides a distributed photovoltaic fault detection system, which can acquire regional photovoltaic panel operation parameters, shoot all regional photovoltaic panels through a high-definition thermal imaging camera carried by an unmanned aerial vehicle in a short-distance mode, perform adverse effect evaluation after image processing, eliminate the need of manual detection, reduce maintenance detection cost, bring various potential factors into comprehensive evaluation, greatly expand the fault detection range, and effectively prevent the faults from happening before the faults happen through the detection of the operation parameters.
3. The invention provides a distributed photovoltaic fault detection system, which can detect and analyze the operation parameters of photovoltaic panels in all areas, obtains the hot spot area, surface dust, air dust and environmental shadows of the photovoltaic panels in all areas after image processing, evaluates the operation temperature coincidence coefficient and light absorption weakening index of the photovoltaic panels in all areas, evaluates the photoelectric coincidence index corresponding to the photovoltaic panels in all areas and various weather parameter factors of a cloud database, takes extreme weather factors into consideration, analyzes the operation risk index under the influence of comprehensive multiple factors according to the extreme weather factors, and exceeds the accuracy and the anti-interference capability of the traditional distributed photovoltaic fault detection system which cannot perform reasonable fault detection in extreme weather, thereby being beneficial to long-term stable operation of the distributed photovoltaic panels. And all the operation parameters are uploaded to the cloud database in real time and displayed in a graph form, and the operation parameters of all the photovoltaic panels in all the areas are in one-to-one correspondence according to the serial numbers of the placing positions of the photovoltaic panels in all the areas, so that the operation risk prediction and the timeliness and response speed of fault detection are greatly improved.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
Fig. 1 is a schematic structural view of the present invention.
Fig. 2 is a parameter diagram of basic parameters and operating parameters of the present invention.
Fig. 3 is a schematic diagram of a system running risk index flow chart according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a distributed photovoltaic fault-based detection system includes: the system comprises a regional photovoltaic distribution zoning module, a regional photovoltaic panel basic parameter acquisition module, a regional photovoltaic panel operation parameter acquisition module, a regional operation parameter detection analysis module, a cloud database and a regional intelligent display terminal. The regional photovoltaic distribution zoning module is connected with the regional photovoltaic panel basic parameter acquisition module and the regional photovoltaic panel operation parameter acquisition module, the regional photovoltaic panel basic parameter acquisition module is connected with the regional operation parameter detection and analysis module and the cloud database, the regional photovoltaic panel operation parameter acquisition module is connected with the regional operation parameter detection and analysis module and the cloud database, the regional operation parameter detection and analysis module is connected with the regional photovoltaic distribution zoning module, the regional photovoltaic panel basic parameter acquisition module and the cloud database, and the regional intelligent display terminal is connected with the cloud database.
And the regional photovoltaic distribution zoning module divides the distributed photovoltaic into a plurality of regions, wherein each region corresponds to a plurality of photovoltaic panels respectively and is marked as each regional photovoltaic panel.
It should be explained that the above-mentioned distributed photovoltaic division areas are suitable for local conditions, but preferably, the number of each photovoltaic panel in one area does not exceed the range of centralized display of one chart of the area intelligent display terminal.
The cloud database is used for storing basic parameters and operation parameters of the photovoltaic panel in each area, evaluation results obtained according to the parameters and data of the processing process, and storing predefined gray values under image processing;
in a specific embodiment, the cloud database is configured to store data of each basic parameter and each operation parameter of each regional photovoltaic panel, and an evaluation result and a processing procedure obtained according to each parameter, and includes: the cloud database stores various operation parameters of the photovoltaic panels in each region, including predefined ageing loss factors of the photovoltaic panels in each region, factors affecting the photovoltaic panels in each region by the shadow coverage of the photovoltaic panels in each region, predefined extreme weather correction factors of the photovoltaic panels in each region, factors affecting the photovoltaic panels in each region by the air dust density under a predefined standard gray value, and factors affecting the photovoltaic panels in each region by the dust density on the photovoltaic panels in each region under a predefined standard gray value. And determining a starting temperature and an ambient temperature gray value image by the predefined hot spots of the photovoltaic panel in each area. And the predefined values correspond to gray values under the image processing of the photovoltaic panels of the areas, and the predefined values comprise the predefined gray values corresponding to the standard temperatures of the photovoltaic panels of the areas, the predefined standard illumination dust-free matching standard gray values of the photovoltaic panels of the areas and the predefined shade threshold matching standard gray values of the photovoltaic panels of the areas.
The method comprises the steps of acquiring basic parameters of the regional photovoltaic panel, acquiring operating parameters of the regional photovoltaic panel and detecting and analyzing the operating parameters of the regional photovoltaic panel, wherein all predefined values are required to come from a cloud database. The cloud database receives various parameter outputs of the regional photovoltaic panel basic parameter acquisition module, the regional photovoltaic panel operation parameter acquisition module and the regional operation parameter detection analysis module in real time, and finally displays the various parameter outputs in a chart and an image form on the regional intelligent display terminal.
The regional photovoltaic panel basic parameter acquisition module is used for acquiring basic parameters of the photovoltaic panels in all regions and evaluating photoelectric coincidence coefficients.
In a specific embodiment, the obtaining, in the regional photovoltaic panel basic parameter obtaining module, basic parameters of each regional photovoltaic panel includes: determining the corresponding placement positions and numbers of the photovoltaic panels in each region, wherein n represents the numbers of the placement positions of the photovoltaic panels in each region, the placement positions and the numbers are in one-to-one correspondence, and dividing the use time length of the photovoltaic panels in each region by a plurality of equal ratios to obtain each detection time point, which is marked as t 0 ，t 0 =1, 2,..t. Detecting basic parameters of the photovoltaic panel in each region at each detection time point, wherein the basic parameters comprise output current, output voltage and illumination intensity of the photovoltaic panel in each region Effective light area->The air dust density D is used for obtaining the output current and the output voltage of the photovoltaic panel corresponding to each region at each detection time point, and then the actual output power +.>And calculating to obtain the actual average output power of the photovoltaic panel in each region in each detection time>The serial numbers, the detection time points, the output currents, the output voltages, the illumination intensity, the effective light area, the output power and the air dust density D of the photovoltaic panel placed positions in each area are uploaded to the cloud database in real time. Matching the corresponding output power of each region light Fu Banguang of the effective light area of each region photovoltaic panel of the cloud database under the intensity interval to obtain the corresponding output power of each region photovoltaic panel of the effective light area of each region photovoltaic panel in each detection time point +>According to each detection time point, matching with predefined aging loss factors of the photovoltaic panels in each region of the cloud database to obtain aging loss values +.>
The method is characterized in that output voltage and current in the regional photovoltaic panel basic parameter acquisition module are directly measured by using output test sensors installed in the photovoltaic panels in all regions, illumination intensity is measured by a light intensity meter, air dust density is measured by an air dust particle counter, effective light area is directly measured by a photovoltaic power generation panel, and a communication module is carried to directly send basic parameters to a cloud database.
Referring to fig. 2, in a specific embodiment, the obtaining steps of the photoelectric coincidence coefficient α corresponding to the regional photovoltaic panel basic parameter obtaining module are: according to the number n of the placement positions of the photovoltaic panels in each region,detection time t 0 Corresponding actual output powerActual average output power +.>Effective light area->Intensity of illumination->Ageing loss value->And the corresponding output power of the photovoltaic panel of each region of the effective light area of the photovoltaic panel of each region +.>The specific calculation formula for calculating the photoelectric coincidence coefficient alpha is as follows: />Wherein->For the preset output power allowable deviation value of the photovoltaic panel corresponding to the battery panel in each region, +.>And uploading the photoelectric coincidence coefficient alpha to the cloud database in real time for outputting a stable influence factor of the output power of each preset region photovoltaic panel.
It should be explained that the photoelectric coincidence coefficients corresponding to the regional photovoltaic panel basic parameter acquisition module must consider whether the types of the regional distributed photovoltaic panels are consistent, and the characteristics of the distributed photovoltaic panels are scattered and independent, so that in actual situations, the types of one regional photovoltaic panel are likely to be different, and different photovoltaic panels must have different output power correction and correction on each influence factor of the output power, so that the judgment of the photoelectric operation coefficients of the specific photovoltaic panels is scientific and accurate.
The regional photovoltaic panel operation parameter acquisition module is used for acquiring operation parameters of the regional photovoltaic panels, acquiring high-definition thermal imaging images of the regional photovoltaic panels, performing image processing on the acquired high-definition thermal imaging images of the regional photovoltaic panels, and evaluating an operation temperature coincidence coefficient and a light absorption weakening index according to an image processing result.
In a specific embodiment, the regional photovoltaic panel operation parameter acquisition module is further used for determining the hot spot duty ratio of each regional photovoltaic panel, and includes: shooting all the photovoltaic full panels in the areas in a short distance through a high-definition thermal imaging camera carried by an unmanned aerial vehicle to obtain an operation temperature image and an environment temperature image of the photovoltaic panels in each area, and predefining a standard temperature K of a cloud database 1 The corresponding gray value is used as a reference, all gray value points are counted after the gray value processing of the obtained temperature image, and the gray value points are recorded as m 0 ，m 0 Number n of each region photovoltaic panel placement position stored in the cloud database, and obtaining the actual operating temperature of each region photovoltaic panelDetermining initial temperature according to predefined hot spots of photovoltaic panels in each region of the cloud database>Setting a hot spot determination function->Counting all predefined hot spot judging initial temperatures of photovoltaic panels in all areas +. >The corresponding gray value points are counted, the ratio of the hot spots of the photovoltaic panel to the gray value of the whole panel in each region is marked as sigma, and the calculation formula is as follows:and uploading the ratio sigma of the hot spots of the photovoltaic panels and the gray value of the full panel in each region to a cloud database in real time.
It should be explained that the hot spot determination functionIn the middle, if->And if the temperature corresponding to the gray value point is more than or equal to 0, judging that the temperature exceeds the hot spot, wherein the temperature belongs to the hot spot area, and otherwise, the temperature does not belong to the hot spot area, so that the proportion of the hot spot area in the whole photovoltaic panel is judged, and the photovoltaic hot spot is a shielded or defective area in a series branch of the photovoltaic assembly in an operating state and is used as a load, so that energy generated by other areas is consumed, and local overheating is caused. The cloud database directly captures all hot spot data of the same type of the photovoltaic in each region by receiving the photovoltaic images in each region, and obtains the predefined hot spot judgment starting temperature through comparison and matching, so that the hot spot judgment is more accurate.
In a specific embodiment, the operating temperature corresponding to the regional photovoltaic panel operating parameter obtaining module accords with a coefficient beta, and the obtaining steps are as follows: according to the ambient temperature gray value image of the cloud database, matching to obtain the ambient temperatureActual operating temperature of the photovoltaic panels in the respective region +. >The ratio of the hot spot of the photovoltaic panel to the gray value of the whole panel in each region is recorded as sigma, and the operating temperature accords with the coefficient beta, and a specific calculation formula of the operating temperature accords with the coefficient beta is as follows: />Wherein->High heat clearing effect for unmanned aerial vehicleAnd (3) matching error factors with the temperature of the image with the gray value, wherein phi is an operation temperature correction factor of the photovoltaic panel in each region, and the operation temperature accords with the coefficient beta and is uploaded to the cloud database in real time.
It should be explained that, in the actual judgment, the temperature of the photovoltaic panel in each region is judged by thermal imaging, and the temperature in each region is not completely uniform, so that errors exist, and the judgment and analysis of interference factors in details are required, and the influence on the operating temperature index is corrected. Besides the actual temperature and the environment temperature, the operating temperature of the photovoltaic panel in each area also needs to consider the influence of the hot spot area of the photovoltaic panel, only the influence of the operating temperature and the environment temperature is judged, and the fact that the hot spot area of the photovoltaic panel has overlarge proportion is very likely, but the operating temperature is still normal, and the operating temperature of the photovoltaic panel is not objectively and comprehensively judged, so that the judgment of the operating temperature is more comprehensive and scientific due to the correction and complement of special conditions, the judgment range of the operating temperature of the distributed photovoltaic panel and the comprehensiveness of factors are improved, the traditional temperature detection model is optimized, meanwhile, the parameters and the coefficients of the operating temperature are uploaded to a cloud database in real time and displayed on an area terminal, and the timeliness of a detection system is improved.
In a specific embodiment, the regional photovoltaic panel operation parameter obtaining module is further configured to determine a surface dust and a surface shadow ratio of each regional photovoltaic panel and perform new gray level conversion on gray level values of actual points of each regional photovoltaic panel, and includes: shooting all the photovoltaic full panels in the areas in a short distance through a high-definition thermal imaging camera carried by an unmanned aerial vehicle by the actual running image of the photovoltaic panel in each area to obtain a surface dust image and a surface shadow image of the photovoltaic panel in each area, counting all gray value points, and marking as j 0 ，j 0 =1, 2,..j, dividing the average use time length of each region photovoltaic panel by a plurality of equal ratios to obtain each gray value detection time point, and recording as g 0 ，g 0 The actual gray value of each point of each region photovoltaic panel at each gray value detection time point is obtained by the serial numbers n of the placing positions of each region photovoltaic panel, which are stored in the cloud database, of the number 1,2The gray value of the standard illumination dust-free matching standard gray value image of the photovoltaic panel in each area is predefined to be G according to the cloud database Without any means for Let surface dust determination function->Statistics of all G Without any means for The gray value points are counted, and the ratio of dust on the surface of the photovoltaic panel in each area to the gray value of the whole panel is marked as sigma 1 The calculation formula is as follows: />Ratio sigma of dust on surface of photovoltaic panel and gray value of full panel in each region 1 And uploading the cloud database in real time. The gray value of the photovoltaic panel shadow threshold matching standard gray value image of each region is predefined to be G according to the cloud database Yin type vagina Let surface shading decision function->Statistics of all G Without any means for The gray value points are counted, and the ratio of the shadow of the photovoltaic panel surface in each area to the gray value of the whole panel is recorded as sigma 2 The calculation formula is as follows: />Surface shading of photovoltaic panel in each region and full panel gray value occupation ratio sigma 2 And uploading the cloud database in real time. Reading the number n of the storage position of each region photovoltaic panel of the cloud database, simultaneously carrying out new gray level conversion on the gray level value of each region photovoltaic panel actual point image, and marking the new gray level value of each region photovoltaic panel actual point image as S n The specific calculation formula is ∈ ->Representation pair P r (r w ) Integration is carried out in the range 0 to r, wherein +.>j w Fu Bandi w image gray scale values representing each region lightJ represents the total number of gray values of the actual points of the photovoltaic panel in each region, L-1 is the total value domain of the gray values of the actual points of the photovoltaic panel in each region, and r is the range of statistics required by the new gray value, namely-> For the maximum gray value of the actual points of the photovoltaic panel in each region,/- >For the minimum gray value of the actual each point image of the photovoltaic panel in each region, r w The probability of occurrence of the w-th image gray value of the image of each actual point in the range of statistics required for representing the new gray value.
It should be noted that the surface dust determination functionIn the middle, if->If the gray value is more than or equal to 0, the gray value of the actual each point image of the photovoltaic panel corresponding to the gray value point exceeds the dust judgment, and belongs to the dust area, otherwise, the gray value is not the dust area, and the surface dust area occupation ratio and the surface dust judgment function of the whole photovoltaic panel are judged>In the middle, if->If the gray value is more than or equal to 0, the gray value of the actual each point image of the photovoltaic panel corresponding to the gray value point exceeds the shadow judgment, belongs to the shadow area, and does not belong to the shadow area, so that the surface shadow area ratio of the whole photovoltaic panel is judged, meanwhile, the difference of influence degree of dust and shadow is considered, further correction is needed, and L-1 in new gray conversion is photovoltaic of each areaThe total value field of the gray value of the actual point image of the plate is generally the default gray change original total value field 255. In the actual judgment of the photovoltaic panel in each area, because the gray value image directly obtained after the thermal imaging image processing possibly has relative gray value intervals, in consideration of extreme conditions, when the ambient temperature is very high, the running temperature is very high, when the ambient temperature is very low, the running temperature is still far lower than the standard temperature although the running temperature is lower than the ambient temperature, at the moment, the gray value after the image processing is relatively close, the temperature is difficult to accurately read, relative errors can be amplified, the influence of different degrees on surface dust and surface shadow can also cause errors, so secondary transformation is needed to be carried out on the gray value after the image processing, the gray value is amplified to a reasonable interval, and the corresponding temperature, dust and shadow are judged in a refined mode. At the moment, compared with the image processing of the similar distributed photovoltaic fault detection system, the method is more accurate and reasonable, can better cover the influence brought by extreme weather, and enhances the anti-interference performance, the scientificity and the application range of the system.
Referring to fig. 2, in a specific embodiment, the light absorption reduction index corresponding to the regional photovoltaic panel operation parameter acquisition module is denoted as ω, and the acquisition steps are as follows: marking the new gray value of the actual each point image of the photovoltaic panel according to each region as S n The ratio of the dust on the surface to the gray value of the whole plate is sigma 1 The ratio of the surface shading to the full plate gray value is recorded as sigma 2 And the air dust density D collected by the regional photovoltaic panel basic parameter module is used for calculating the light absorption weakening index omega, wherein the specific calculation formula of the light absorption weakening index omega is as follows:and H is the influence factor of the air dust density on the photovoltaic panel in each region under the predefined standard gray value of the cloud database, E is the influence factor of the dust density on the photovoltaic panel in each region under the predefined standard gray value of the cloud database, F is the influence factor of the shadow coverage on the photovoltaic panel in each region under the predefined standard gray value of the cloud database, and the light absorption weakening index omega is uploaded to the cloud database in real time.
It should be explained that, the general detection system ignores or conservatively counts the influence of dust and shadow on the operation of the photovoltaic panel, but the actual influence is not negligible, and when extreme weather such as sand storm and the like occurs, the existing detection system has no countermeasure, so that the normal operation of the distributed photovoltaic fault detection system is seriously disturbed, therefore, when the image processing is performed, the light absorption attenuation index calculation must be carried out on the photovoltaic panel, the surface dust, the surface shadow and the air dust in each region, and the parameters are all in dynamic change, so that the cloud database must grasp the influence factors of the surface dust, the surface shadow and the air dust on the photovoltaic panel in each region in real time and incorporate the influence factors into the light absorption attenuation index calculation. The method has the advantages that the influence of extreme weather on the operation of the photovoltaic panels in each distributed area is quantized, the cloud database is used for dynamically optimizing and adjusting the influence, the influence of each environmental factor in each area can be calculated comprehensively in real time, the extremely strong anti-interference capability can be achieved in the extreme weather, early warning can be sent out before the extreme weather is incubated, the abnormal light absorption is indicated, the regional display terminal is reminded, and the unified management of the distributed photovoltaic is facilitated.
Referring to fig. 3, in a specific embodiment, the operation risk index corresponding to the regional operation parameter detection and analysis module is Γ, and the obtaining step is: according to the photoelectric coincidence coefficient alpha, the operation temperature coincidence coefficient beta and the light absorption weakening index omega of the photovoltaic panel in each region, an operation risk index gamma is calculated, and a specific calculation formula of the operation risk index gamma is as follows:and the cloud database is uploaded by the running risk index gamma in real time.
It should be explained that, although the calculation of incorporating the photoelectric coincidence coefficient, the operation temperature coincidence coefficient and the light absorption attenuation index into the operation risk index is relatively comprehensive, the accuracy damage of the existing detection system caused by extreme weather as an exception must be predefined through a cloud database, various errors in the actual detection means are considered, meanwhile, the influence factors can influence each other, and finally, the adverse influence of the superposition amplification error on the calculation result is caused, the corresponding correction factors must be comprehensively considered, and the accuracy of the detection system is ensured by incorporating the corresponding correction factors into the calculation. And judging and calculating the comprehensive factors of the photovoltaic panels in each region to obtain an operation risk index. The photovoltaic panel detection system can comprehensively consider the influence of a plurality of factors on the system performance, so that the accuracy of a detection result is improved. By combining parameters such as weather conditions, environmental factors, voltage and current, and the like, the false alarm rate can be effectively reduced by comprehensively considering a plurality of factors, unnecessary maintenance and unnecessary cost are avoided, whether the photovoltaic panel has faults or performance degradation can be accurately judged, problems can be found early, appropriate maintenance measures are adopted, the service life of the system is prolonged, and the power generation efficiency and economic benefit are improved.
And the regional intelligent display terminal is used for comprehensively displaying according to the running risk indexes of the photovoltaic panels in each region and the basic parameters and the running parameters of the photovoltaic panels in each region of the cloud database.
In a specific embodiment, the regional intelligent display terminal performs comprehensive display and comprises a data display module and a fault diagnosis module. And the data display module intuitively displays all basic parameters and all operation parameters of the photovoltaic panel in all areas stored in the cloud database in a chart form in real time, and checks historical data of the photovoltaic panel in all areas when needed. The fault diagnosis module judges the fault points and problems existing in the system according to the basic parameters, the operation parameters and the evaluation results of the photovoltaic panels in each area and provides corresponding alarms and prompts.
It should be explained that the data of the data display module includes the placement position of the photovoltaic panel in each area, the number of the placement position, the output current, the output voltage, the effective light area, the output power, the ratio of the hot spot of illumination intensity to the gray value of the whole panel, the ratio of the dust on the surface to the gray value of the whole panel, the ratio of the shadow on the surface to the gray value of the whole panel, the photoelectric coincidence coefficient, the operation temperature coincidence coefficient, the light absorption weakening index and the like, so that the operation state of the system can be mastered in time, any abnormality or fault can be found, and the normal operation of the photovoltaic system is ensured. And the fault diagnosis module is used for continuously comparing the evaluation data of the real-time data display module with the corresponding standard value, giving a yellow warning if the difference is too large, prompting that the running point corresponding to the data is possibly faulty, and directly giving a red warning if the difference exceeds a predefined limit value, prompting that the running point corresponding to the data is faulty. The regional intelligent display terminal provides comprehensive management and control for the photovoltaic system through the data display module and the fault diagnosis module, helps a user to know the state of the system in real time, optimizes energy output, improves the stability and efficiency of the system, and therefore achieves more reliable and efficient distributed photovoltaic power generation.
Based on distributed photovoltaic fault detecting system with various detectors direct reading and with high in clouds interconnection on basic parameter, utilize unmanned aerial vehicle to carry out high definition thermal imaging image acquisition to each regional distributed photovoltaic board on operating parameter, utilize modern novel image processing and high in clouds contrast analysis, consider the photoelectricity of each regional distributed photovoltaic board simultaneously, temperature, hot spot, environment, shadow, dust and extreme weather comprehensive influence, comprehensive evaluation running risk index, detecting system's comprehensiveness and accuracy have been improved, all parameters are linked to the display terminal through the high in clouds and are displayed comprehensively, understand each item state that detecting system detected directly perceivedly, timeliness and response speed have been improved, observability and detection efficiency have been strengthened.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art of describing particular embodiments without departing from the structures of the invention or exceeding the scope of the invention as defined by the claims.

Claims (10)

1. A distributed photovoltaic fault-based detection system, comprising:
The regional photovoltaic distribution dividing module divides the distributed photovoltaic into a plurality of regions, wherein each region corresponds to a plurality of photovoltaic panels and is marked as each regional photovoltaic panel;
the regional photovoltaic panel basic parameter acquisition module is used for acquiring basic parameters of the photovoltaic panels in all regions and evaluating photoelectric coincidence coefficients;
the regional photovoltaic panel operation parameter acquisition module is used for acquiring operation parameters of the regional photovoltaic panels, acquiring high-definition thermal imaging images of the regional photovoltaic panels, performing image processing on the acquired high-definition thermal imaging images of the regional photovoltaic panels, and evaluating an operation temperature coincidence coefficient and a light absorption weakening index according to an image processing result;
the regional operation parameter detection and analysis module is used for acquiring and analyzing the operation parameters of the photovoltaic panels in each region according to the photoelectric coincidence coefficient, the operation temperature coincidence coefficient and the light absorption weakening index of the photovoltaic panels in each region and evaluating the operation risk index corresponding to the photovoltaic panels in each region;
the cloud database is used for storing basic parameters and operation parameters of the photovoltaic panel in each area, evaluation results obtained according to the parameters and data of the processing process, and storing predefined gray values under image processing;
And the regional intelligent display terminal is used for comprehensively displaying according to the running risk indexes of the photovoltaic panels in each region and the basic parameters and the running parameters of the photovoltaic panels in each region of the cloud database.
2. The distributed photovoltaic panel fault detection system according to claim 1, wherein the cloud database is configured to store data of each basic parameter and each operation parameter of each regional photovoltaic panel, and an evaluation result and a processing procedure obtained according to each parameter, and specifically includes:
the cloud database stores various operation parameters including various factors of photovoltaic panels in various areas, including predefined ageing loss factors of the photovoltaic panels in various areas, factors affecting the photovoltaic panels in various areas by the shadow coverage of the photovoltaic panels in the surfaces, predefined extreme weather correction factors of the photovoltaic panels in various areas, factors affecting the photovoltaic panels in various areas by the air dust density under a predefined standard gray value, and factors affecting the photovoltaic panels in various areas by the dust density on the surfaces of the photovoltaic panels in various areas under a predefined standard gray value;
a pre-defined hot spot judgment starting temperature and an ambient temperature gray value image of the photovoltaic panel in each area;
and the predefined values correspond to gray values under the image processing of the photovoltaic panels of the areas, and the predefined values comprise the predefined gray values corresponding to the standard temperatures of the photovoltaic panels of the areas, the predefined standard illumination dust-free matching standard gray values of the photovoltaic panels of the areas and the predefined shade threshold matching standard gray values of the photovoltaic panels of the areas.
3. The distributed photovoltaic fault detection system according to claim 1, wherein the specific process of obtaining the basic parameters of each regional photovoltaic panel in the regional photovoltaic panel basic parameter obtaining module comprises:
determining the corresponding placement positions and numbers of the photovoltaic panels in each region, wherein n represents the numbers of the placement positions of the photovoltaic panels in each region, the placement positions and the numbers are in one-to-one correspondence, and dividing the use time length of the photovoltaic panels in each region by a plurality of equal ratios to obtain each detection time point, which is marked as t 0 ，t 0 ＝1,2,...,t；
Detecting basic parameters of the photovoltaic panel in each region at each detection time point, wherein the basic parameters comprise output current, output voltage and illumination intensity of the photovoltaic panel in each regionEffective light area->The air dust density D is used for obtaining the output current and the output voltage of the photovoltaic panel corresponding to each region at each detection time point, and then the actual output power +.>And calculating to obtain the actual average output power of the photovoltaic panel in each region in each detection time>The serial numbers of the photovoltaic panel placing positions in all areas, the detection time points, the output current, the output voltage, the illumination intensity, the effective light area, the output power and the air dust density D are uploaded to a cloud database in real time;
Matching the corresponding output power of each area light Fu Banguang of the effective light area of each area photovoltaic panel of the cloud database under the intensity interval to obtain the corresponding output power of each area photovoltaic panel of the effective light area of each area photovoltaic panel in each detection time point
According to each detection time point, matching with predefined aging loss factors of the photovoltaic panels in each region of the cloud database to obtain aging loss values of the photovoltaic panels in each region
4. The distributed photovoltaic fault detection system according to claim 3, wherein the photoelectric coincidence coefficient α corresponding to the regional photovoltaic panel basic parameter acquisition module comprises the following specific acquisition steps:
detecting a time point t according to the number n of the placement positions of the photovoltaic panels in each area 0 Corresponding actual output powerActual average output power +.>Effective light area->Intensity of illumination->Ageing loss value->And the corresponding output power of the photovoltaic panel of each region of the effective light area of the photovoltaic panel of each region +.>The specific calculation formula for calculating the photoelectric coincidence coefficient alpha is as follows:
wherein->For the preset output power allowable deviation value of the photovoltaic panel corresponding to the battery panel in each region, +.>And uploading the photoelectric coincidence coefficient alpha to the cloud database in real time for outputting a stable influence factor of the output power of each preset region photovoltaic panel.
5. The distributed photovoltaic fault detection system according to claim 1, wherein the regional photovoltaic panel operation parameter acquisition module is further configured to determine a hot spot duty cycle of each regional photovoltaic panel, and the specific process includes:
shooting all the photovoltaic full panels in the areas in a short distance through a high-definition thermal imaging camera carried by an unmanned aerial vehicle to obtain an operation temperature image and an environment temperature image of the photovoltaic panels in each area, and predefining a standard temperature K of a cloud database 1 The corresponding gray value is used as a reference, all gray value points are counted after the gray value processing of the obtained temperature image, and the gray value points are recorded as m 0 ，m 0 Number n of each region photovoltaic panel placement position of storage of the cloud database, m, and 1,2, to obtain each regionActual operating temperature of field photovoltaic panel
Determining initial temperature according to predefined hot spots of photovoltaic panels in each region of cloud databaseDetermination function for setting hot spotCounting all predefined hot spot judging initial temperatures of photovoltaic panels in all areas +.>The corresponding gray value points are counted, the ratio of the hot spots of the photovoltaic panel to the gray value of the whole panel in each region is marked as sigma, and the calculation formula is as follows:and uploading the ratio sigma of the hot spots of the photovoltaic panels and the gray value of the full panel in each region to a cloud database in real time.
6. The distributed photovoltaic fault detection system according to claim 5, wherein the operating temperature corresponding to the regional photovoltaic panel operating parameter acquisition module conforms to a coefficient β, and the specific acquisition steps are as follows:
according to the ambient temperature gray value image of the cloud database, matching to obtain the ambient temperatureActual operating temperature of the photovoltaic panels in the respective region +.>The ratio of the hot spot of the photovoltaic panel to the gray value of the whole panel in each region is recorded as sigma, and a specific calculation formula of the operating temperature conforming to the coefficient beta is calculatedThe method comprises the following steps:
wherein->The method comprises the steps that error factors are matched for the temperature of the high-heat-clearing imaging gray value image of the unmanned aerial vehicle, phi is an operation temperature correction factor of the photovoltaic panel in each area, e is a natural constant, and the operation temperature accords with a coefficient beta and is uploaded to a cloud database in real time.
7. The distributed photovoltaic fault detection system according to claim 1, wherein the regional photovoltaic panel operation parameter acquisition module is further configured to determine a surface dust and a surface shadow ratio of each regional photovoltaic panel and perform a new gray level transformation on an actual image gray level value of each point of each regional photovoltaic panel, and the specific process includes:
shooting all the photovoltaic full panels in the areas in a short distance through a high-definition thermal imaging camera carried by an unmanned aerial vehicle by the actual running image of the photovoltaic panel in each area to obtain a surface dust image and a surface shadow image of the photovoltaic panel in each area, counting all gray value points, and marking as j 0 ，j 0 =1, 2,..j, dividing the average use time length of each region photovoltaic panel by a plurality of equal ratios to obtain each gray value detection time point, and recording as g 0 ，g 0 The actual gray value of each point of each region photovoltaic panel at each gray value detection time point is obtained by the serial numbers n of the placing positions of each region photovoltaic panel, which are stored in the cloud database, of the number 1,2
The gray value of the standard illumination dust-free matching standard gray value image of the photovoltaic panel in each area is predefined to be G according to the cloud database Without any means for Setting a surface dust determination functionStatistics of all G Without any means for The gray value points are counted, and the ratio of dust on the surface of the photovoltaic panel in each area to the gray value of the whole panel is marked as sigma 1 The calculation formula is as follows: />Ratio sigma of dust on surface of photovoltaic panel and gray value of full panel in each region 1 Uploading a cloud database in real time;
the gray value of the photovoltaic panel shadow threshold matching standard gray value image of each region is predefined to be G according to the cloud database Yin type vagina Setting a surface shading determination functionStatistics of all G Without any means for The gray value points are counted, and the ratio of the shadow of the photovoltaic panel surface in each area to the gray value of the whole panel is recorded as sigma 2 The calculation formula is as follows: />Surface shading of photovoltaic panel in each region and full panel gray value occupation ratio sigma 2 Uploading a cloud database in real time;
Reading the number n of the storage position of each region photovoltaic panel of the cloud database, simultaneously carrying out new gray level conversion on the gray level value of each region photovoltaic panel actual point image, and marking the new gray level value of each region photovoltaic panel actual point image as S n The specific calculation formula isRepresentation pair P r (r w ) Integration is carried out in the range 0 to r, wherein +.>j w The number of occurrences of the gray values of Fu Bandi w images of each region light is represented, j represents the total number of the gray values of the actual points of each region photovoltaic panel, L-1 is the total value domain of the gray values of the actual points of each region photovoltaic panel, and r is the required total value of the new gray valuesThe range of the meter, i.e.)> For the maximum gray value of the actual points of the photovoltaic panel in each region,/->For the minimum gray value of the actual each point image of the photovoltaic panel in each region, r w The probability of occurrence of the w-th image gray value of the image of each actual point in the range of statistics required for representing the new gray value.
8. The distributed photovoltaic fault detection system according to claim 7, wherein the light absorption reduction index corresponding to the regional photovoltaic panel operation parameter acquisition module is marked as ω, and the specific acquisition steps are as follows:
marking the new gray value of the actual each point image of the photovoltaic panel according to each region as S n The ratio of the dust on the surface to the gray value of the whole plate is sigma 1 The ratio of the surface shading to the full plate gray value is recorded as sigma 2 And the air dust density D collected by the regional photovoltaic panel basic parameter module is used for calculating the light absorption weakening index omega, wherein the specific calculation formula of the light absorption weakening index omega is as follows:
and H is the influence factor of the air dust density on the photovoltaic panel in each region under the predefined standard gray value of the cloud database, E is the influence factor of the dust density on the photovoltaic panel in each region under the predefined standard gray value of the cloud database, F is the influence factor of the shadow coverage on the photovoltaic panel in each region under the predefined standard gray value of the cloud database, and the light absorption weakening index omega is uploaded to the cloud database in real time.
9. The distributed photovoltaic fault detection system according to claim 8, wherein the region operation parameter detection and analysis module corresponds to an operation risk index Γ, and the specific obtaining steps are:
according to the photoelectric coincidence coefficient alpha, the operation temperature coincidence coefficient beta and the light absorption weakening index omega of the photovoltaic panel in each region, an operation risk index gamma is calculated, and a specific calculation formula of the operation risk index gamma is as follows:
And the cloud database is uploaded by the running risk index gamma in real time.
10. The distributed photovoltaic fault detection system according to claim 1, wherein the regional intelligent display terminal performs comprehensive display, and specifically comprises a data display module and a fault diagnosis module:
the data display module intuitively displays all basic parameters and all operation parameters of the photovoltaic panel in all areas stored in the cloud database in a chart form in real time, and checks historical data of the photovoltaic panel in all areas when needed;
the fault diagnosis module judges the fault points and problems existing in the system according to the basic parameters, the operation parameters and the evaluation results of the photovoltaic panels in each area and provides corresponding alarms and prompts.
CN202310807464.2A 2023-07-04 2023-07-04 Distributed photovoltaic fault detection system Withdrawn CN116865669A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310807464.2A CN116865669A (en) 2023-07-04 2023-07-04 Distributed photovoltaic fault detection system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310807464.2A CN116865669A (en) 2023-07-04 2023-07-04 Distributed photovoltaic fault detection system

Publications (1)

Publication Number Publication Date
CN116865669A true CN116865669A (en) 2023-10-10

Family

ID=88226227

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310807464.2A Withdrawn CN116865669A (en) 2023-07-04 2023-07-04 Distributed photovoltaic fault detection system

Country Status (1)

Country Link
CN (1) CN116865669A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117309060A (en) * 2023-10-20 2023-12-29 广东省装饰有限公司 Building curtain wall structure performance monitoring system based on cloud computing
CN117478064A (en) * 2023-10-20 2024-01-30 重庆千信新能源有限公司 Photovoltaic panel new energy power grid abnormality screening system based on electric power parameters

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117309060A (en) * 2023-10-20 2023-12-29 广东省装饰有限公司 Building curtain wall structure performance monitoring system based on cloud computing
CN117478064A (en) * 2023-10-20 2024-01-30 重庆千信新能源有限公司 Photovoltaic panel new energy power grid abnormality screening system based on electric power parameters
CN117309060B (en) * 2023-10-20 2024-05-17 广东省装饰有限公司 Building curtain wall structure performance monitoring system based on cloud computing
CN117478064B (en) * 2023-10-20 2024-06-04 重庆千信新能源有限公司 Photovoltaic panel new energy power grid abnormality screening system based on electric power parameters

Similar Documents

Publication Publication Date Title
CN116865669A (en) Distributed photovoltaic fault detection system
Triki-Lahiani et al. Fault detection and monitoring systems for photovoltaic installations: A review
JP2874156B2 (en) Power generation system
TWI586066B (en) Solar power generation monitoring method and the solar power generation monitoring system used in the method
CN102362360B (en) For the fault detection method of solar power system
CN108092622B (en) Photovoltaic string fault diagnosis method based on resistance calculation
US20110066401A1 (en) System for and method of monitoring and diagnosing the performance of photovoltaic or other renewable power plants
JP6093465B1 (en) Power generation diagnosis method and power generation diagnosis apparatus for solar power generation system
Ma et al. Photovoltaic module current mismatch fault diagnosis based on IV data
Ventura et al. Development of models for on-line diagnostic and energy assessment analysis of PV power plants: The study case of 1 MW Sicilian PV plant
KR101532163B1 (en) Evaluation and condition diagnosis system for photovoltaic power generator
Liao et al. Using Matlab real-time image analysis for solar panel fault detection with UAV
JP2012138448A (en) Output drop detector and detection method of photovoltaic power generation
CN104821789A (en) Method for detecting reliability of photovoltaic power generation system
Meng et al. Performance variability and implications for yield prediction of rooftop PV systems–Analysis of 246 identical systems
CN117634742A (en) Distributed photovoltaic running state evaluation method
CN117332920A (en) New energy station operation fault evolution analysis method
CN112764130A (en) Power grid meteorological monitoring and early warning device and monitoring method
Babasaki et al. Using PV string data to diagnose failure of solar panels in a solar power plant
Higuchi et al. Classification of causes of broken solar panels in solar power plant
KR20160106395A (en) Self-diagnosising monitoring system for solar module
KR101642684B1 (en) A Module of Abnormal Condition Diagnosis System in BIPV and Method thereof
Bakır A comparative evaluation and real-time measurement of failures in solar power plants by thermal imaging in Turkey
CN116388685B (en) Solar cell panel operation control system
KR102645222B1 (en) PV system diagnostic device through voltage and current estimation of solar modules

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
WW01 Invention patent application withdrawn after publication

Application publication date: 20231010

WW01 Invention patent application withdrawn after publication