WO2022063282A1

WO2022063282A1 - Method and device for determining life cycle of photovoltaic module

Info

Publication number: WO2022063282A1
Application number: PCT/CN2021/120786
Authority: WO
Inventors: 孙少华; 杨林慧; 李海龙; 张广德; 李宏波; 方晨; 杨兴; 周尚虎; 刘永胜; 李智年; 唐玉萍
Original assignee: 国家电网有限公司; 国网青海省电力公司; 国网青海省电力公司信息通信公司
Priority date: 2020-09-27
Filing date: 2021-09-26
Publication date: 2022-03-31
Also published as: CN112163018A

Abstract

A method and device for determining the life cycle of a photovoltaic module. The method comprises: obtaining historical operation data of a photovoltaic module (S102); monitoring the current environment data and the current operation data of the photovoltaic module (S104); and determining the usable life cycle of the photovoltaic module according to the current environment data, the historical operation data, and the current operation data (S106). The method and device solve the technical problem in the prior art that the usable life cycle of the photovoltaic module cannot be dynamically evaluated only by setting the service life of the photovoltaic module according to experience.

Description

Method and device for determining the life cycle of a photovoltaic module

technical field

The present invention relates to the field of photovoltaic technology, and in particular, to a method and device for determining the life cycle of a photovoltaic module.

Background technique

The need for optimization of China's energy structure is imminent, and vigorous development of clean energy such as solar energy, wind energy, and geothermal energy has become an inevitable trend. As the core equipment of solar power generation, photovoltaic modules, their quality problems and attenuation characteristics directly affect the total power generation of photovoltaic power plants.

In traditional design, the service life of PV modules is only set at 25 years based on experience, and it is impossible to dynamically evaluate the quality level and attenuation stage of PV modules. On the other hand, some photovoltaic modules that have been in service for 25 years but with good performance will be replaced in advance and increase the economic cost.

For the above problems, no effective solution has been proposed yet.

SUMMARY OF THE INVENTION

The embodiments of the present invention provide a method and apparatus for determining the life cycle of a photovoltaic module, so as to at least solve the technical problem in the prior art that the service life of a photovoltaic module is only set based on experience, and the usable life cycle of the photovoltaic module cannot be dynamically evaluated .

According to an aspect of the embodiments of the present invention, a method for determining the life cycle of a photovoltaic module is provided, including: acquiring historical operation data of the photovoltaic module; monitoring the current environment data and current operation data of the photovoltaic module; according to the current environment data , the above-mentioned historical operation data and the above-mentioned current operation data to determine the usable life cycle of the above-mentioned photovoltaic modules.

Optionally, before determining the usable life cycle of the photovoltaic module according to the current environment data, the historical operation data and the current operation data, the method further includes: determining a life cycle decay index of the photovoltaic module; obtaining a sample environment data, sample historical operation data, and sample current operation data; based on the above-mentioned life cycle attenuation index, and based on the above-mentioned sample environmental data, the above-mentioned sample historical operation data, and the above-mentioned sample current operation data, a photovoltaic module attenuation model is established.

Optionally, determining the usable life cycle of the photovoltaic module according to the current environment data, the historical operation data, and the current operation data includes: determining the life cycle of the photovoltaic module according to the current environment data, the historical operation data, and the current operation data. The above-mentioned sample environmental data, the above-mentioned sample historical operation data, and the above-mentioned sample current operation data corresponding to the photovoltaic module attenuation model; the above-mentioned current environmental data is analyzed based on the above-mentioned sample environmental data to obtain a first analysis result, and the above-mentioned sample historical operation data is analyzed according to the above-mentioned historical operation data. The historical operation data is analyzed to obtain a second analysis result, and the current operation data is analyzed according to the sample current operation data to obtain a third analysis result; the first analysis result, the second analysis result and the third analysis result are obtained. The above-mentioned available life cycle in at least one analysis result of .

Optionally, the above-mentioned life cycle attenuation index includes at least one of the following: photovoltaic module glass scratch index, light transmittance index, backplane mechanical characteristic index, cell cracking index, hot spot effect and process control PID effect index, random Attenuation index, backsheet and sealing ethylene-vinyl acetate copolymer EVA film chemical deterioration index, photovoltaic module cleaning index.

Optionally, obtaining the historical operating data of the photovoltaic modules includes: obtaining the historical output current and historical output power of the photovoltaic modules; monitoring the current environmental data of the photovoltaic modules, including: controlling the UAV-based photovoltaic module scanning and detection system, The above-mentioned current environmental data is collected and obtained, wherein the above-mentioned current environmental data includes at least one of the following: light irradiance, ambient temperature, humidity, front panel temperature, and wind power; monitoring the current operation data of the above-mentioned photovoltaic modules, including: controlling the unmanned The photovoltaic module scanning and detection system of the machine is used to monitor the current output current and current output power of the above photovoltaic modules.

Optionally, the above photovoltaic modules are photovoltaic modules arranged in high-altitude desert areas.

According to another aspect of the embodiments of the present invention, there is also provided a system for determining the life cycle of a photovoltaic module, including: a monitor for monitoring current environmental data and current operation data of the photovoltaic module; The device is connected to obtain the historical operation data of the photovoltaic module, and according to the above-mentioned current environment data, the above-mentioned historical operation data and the above-mentioned current operation data, the usable life cycle of the above-mentioned photovoltaic module is determined.

Optionally, the processor is further configured to determine the life cycle decay index of the photovoltaic module; obtain sample environmental data, sample historical operation data, and sample current operation data; based on the life cycle decay index, according to the sample environment data, the sample The PV module attenuation model is established based on the historical operating data and the current operating data of the above samples.

Optionally, the above-mentioned processor is further configured to determine the above-mentioned sample environmental data, the above-mentioned sample historical operation data and the above-mentioned sample current operation data corresponding to the above-mentioned photovoltaic module attenuation model according to the above-mentioned current environmental data, the above-mentioned historical operation data and the above-mentioned current operation data. The first analysis result is obtained by analyzing the above-mentioned current environmental data based on the above-mentioned sample environment data, the second analysis result is obtained by analyzing the above-mentioned historical operation data according to the above-mentioned sample historical operation data, and the above-mentioned current operation data is analyzed according to the above-mentioned sample current operation data. The data is analyzed to obtain a third analysis result; the above-mentioned usable life cycle in at least one of the above-mentioned first analysis result, the above-mentioned second analysis result and the above-mentioned third analysis result is obtained.

Optionally, the above-mentioned system further includes: a photovoltaic module scanning and detection system for collecting and obtaining the above-mentioned current environmental data and the above-mentioned current operation data, wherein the above-mentioned current environmental data includes at least one of the following: light irradiance, ambient temperature, Humidity, front panel temperature, wind power, the above current operating data includes: current output current and current output power.

According to another aspect of the embodiments of the present invention, an apparatus for determining the life cycle of a photovoltaic module is also provided, including: an acquisition module for acquiring historical operating data of the photovoltaic module; a monitoring module for monitoring the current status of the photovoltaic module Environmental data and current operation data; a determination module, configured to determine the usable life cycle of the photovoltaic module according to the current environment data, the historical operation data and the current operation data.

According to another aspect of the embodiments of the present invention, a non-volatile storage medium is also provided, wherein the non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and performing the determination of any item A method for the life cycle of photovoltaic modules.

According to another aspect of the embodiments of the present invention, there is also provided a processor for running a program, wherein the program is configured to execute any one of the above-mentioned methods for determining the life cycle of a photovoltaic module when running.

According to another aspect of the embodiments of the present invention, there is also provided an electronic device, comprising a memory and a processor, the memory stores a computer program, and the processor is configured to run the computer program to execute any one of the above A method for determining the life cycle of photovoltaic modules.

In the embodiment of the present invention, the historical operation data of the photovoltaic module is obtained; the current environment data and the current operation data of the photovoltaic module are monitored; according to the current environment data, the historical operation data and the current operation data, the The usable life cycle achieves the purpose of dynamically evaluating the usable life cycle of photovoltaic modules, thereby achieving the technical effect of avoiding setting the service life of photovoltaic modules only by experience, thereby solving the problem of setting photovoltaic modules only by experience in the prior art. The service life of the modules cannot be dynamically evaluated for the technical problems of the usable life cycle of photovoltaic modules.

Description of drawings

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

FIG. 1 is a flowchart of a method for determining the life cycle of a photovoltaic module according to an embodiment of the present invention;

FIG. 2 is a schematic structural diagram of a system for determining the life cycle of a photovoltaic module according to an embodiment of the present invention;

FIG. 3 is a schematic structural diagram of an apparatus for determining the life cycle of a photovoltaic module according to an embodiment of the present invention.

detailed description

In order to make those skilled in the art better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only Embodiments are part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

It should be noted that the terms "first", "second" and the like in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used may be interchanged under appropriate circumstances such that the embodiments of the invention described herein can be practiced in sequences other than those illustrated or described herein. Furthermore, the terms "comprising" and "having" and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those expressly listed Rather, those steps or units may include other steps or units not expressly listed or inherent to these processes, methods, products or devices.

Example 1

According to an embodiment of the present invention, an embodiment of a method for determining the life cycle of a photovoltaic module is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings may be implemented in a computer system such as a set of computer-executable instructions. and, although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that herein.

FIG. 1 is a flowchart of a method for determining the life cycle of a photovoltaic module according to an embodiment of the present invention. As shown in FIG. 1 , the method includes the following steps:

Step S102, obtaining historical operation data of the photovoltaic module;

Step S104, monitoring the current environmental data and current operating data of the photovoltaic modules;

In step S106, the usable life cycle of the photovoltaic module is determined according to the current environment data, the historical operation data and the current operation data.

In the embodiment of the present application, the above-mentioned method for determining the life cycle of a photovoltaic module can be run through a new energy big data platform, and the above new energy big data platform is used to provide open IaaS infrastructure services, PaaS platform services, DaaS data services, and server 223 units, the platform has built-in more than 100 general algorithms and models, the access capacity exceeds 10 million measuring points/second, has PB-level data storage capacity and high-throughput data concurrency capability, and meets the operation management and control requirements of 200GW and more than 600 new energy power stations .

Optionally, the above-mentioned new energy big data platform is used to realize online health monitoring and intelligent diagnosis of photovoltaic modules, real-time collection of multi-source heterogeneous data on the source, network, and load side, and realize the smallest particle size at the fan component level and photovoltaic panel level. Data collection, the collection frequency is 5-7 seconds/time, the cumulative access data has exceeded 5.5 billion, and the daily new data volume exceeds 60GB, which efficiently supports the construction and use of various industry applications.

In the embodiments of the present application, based on the intelligent photovoltaic power station fault detection and life prediction technology, the health online monitoring and intelligent diagnosis of photovoltaic modules are realized, and the usable life cycle of the photovoltaic modules is determined. The photovoltaic system fault diagnosis method is to realize the health of photovoltaic modules. The basis of online monitoring and intelligent diagnosis, on this basis, through the proposed establishment of a new energy big data platform for photovoltaic arrays with multi-sensor fusion of machines, electricity, images, etc., to complete the environmental (input) and power (output) of solar panels. ) comprehensive monitoring to establish a good data foundation for later information mining.

As an optional embodiment, in this embodiment of the present application, in addition to using data such as output voltage and power for real-time monitoring of battery panel faults, fault detection may also be performed using data such as surface defects of the battery panel and whether it is dirty. It is planned to control the unmanned aerial vehicle to take the image of the battery panel, and then use the relevant methods of machine vision to establish a surface crack and hot spot diagnosis model based on image recognition, and obtain the data of the surface defect and contamination degree of the battery panel, so as to realize the real-time online fault diagnosis capability.

In addition, the new energy big data platform in the embodiment of the present application uses data processing technologies such as logistic regression, naive Bayes, and decision tree. Since the data that can be monitored in the photovoltaic power station system has various types and poor structure, it is proposed to use logistic regression. It uses methods such as Naive Bayes and Naive Bayes for fault classification, and uses regression methods and decision trees to continuously predict the usable life cycle (ie, life) of photovoltaic modules.

As another optional embodiment, acquiring historical operating data of photovoltaic modules includes: acquiring historical output current and historical output power of the photovoltaic modules; monitoring current environmental data of photovoltaic modules, including: controlling the photovoltaic module based on drones The component scanning and detection system collects and obtains the above-mentioned current environment data, wherein the above-mentioned current environment data includes at least one of the following: light irradiance, ambient temperature, humidity, front panel temperature, and wind power; monitoring the current operation data of the above-mentioned photovoltaic modules, Including: controlling the photovoltaic module scanning and detection system based on the drone, and monitoring the current output current and current output power of the above photovoltaic modules.

In the embodiment of this application, by purchasing different manufacturers and different types of photovoltaic modules with a span of ten years, and supporting experimental equipment including irradiance meter, light transmittance meter, microscope, PID special test power supply, solar simulator, EL detectors, infrared imagers, multimeters, drones, temperature cycle test chambers, environmental monitoring equipment, photovoltaic module cleaning equipment, etc., to build a photovoltaic module attenuation test experimental platform.

And by quantifying the attenuation indicators of photovoltaic modules from the perspective of component structure, including the changes in the physical and chemical properties of photovoltaic glass, backsheets, cells, and sealing EVA film, as well as the fouling effect, hot spot effect and the attenuation of photovoltaic modules. PID effect index, carry out photovoltaic module power generation comparison experiments over the years, photovoltaic glass mechanical and optical characteristics experiments, backplane mechanical characteristics detection and GPC test experiments, cell crack distribution statistics and EL test experiments, PID test experiments, hot spot effect Testing experiments, attenuation comparison experiments of photovoltaic modules of different materials and types, attenuation comparison experiments of photovoltaic modules with different cleaning degrees, accelerated attenuation and destructive experiments, etc.

Finally, by using big data and drone technology to monitor the operation of photovoltaic modules in real time, drones are equipped with visual and infrared imaging equipment to monitor optical components, and at the same time, through artificial regular cleaning, trade-in and timely repair of faults and other measures, reduce the number of photovoltaic modules in Africa. Influence on photovoltaic power generation under normal attenuation conditions.

In an optional embodiment, for the research on the state monitoring and analysis system of the wind turbine, the embodiment of the present application realizes the state monitoring of the main shaft vibration and the tower through the ultra-low frequency vibration acceleration sensor; Vibration status monitoring of transmission chain equipment such as wheels, gearboxes and generators, triggering relevant acquisition strategies with the help of speed sensors; other current, voltage, power, wind speed and other signals connected to the unit are transmitted to the same software platform through process signals. Through a variety of alarm processing methods and auxiliary diagnosis functions, intelligent alarms for equipment failures are realized, and then the wind turbine computer monitoring system network is used for data transmission to realize remote diagnosis and equipment status evaluation by experts.

In an optional embodiment, for the research on the wind turbine tower and foundation settlement monitoring and analysis system, the embodiment of the present application can monitor the working state of the wind turbine tower through the wind turbine tower and foundation settlement monitoring and analysis system And the foundation settlement state, real-time collection of tower vibration signal, sway and inclination data, analysis of the wind turbine operating state, through the real-time monitoring map of the unit overturning, the monitoring map of the dangerous speed area, the inclination angle distribution map, the spectrum map, the trend map, the analysis and comparison It can perform data management through various tools such as alarm display, autonomous alarm, data report, log query, user management, etc., and propose the best condition monitoring solution for the healthy operation of wind turbines.

In another optional embodiment, for the research on the wind turbine blade health monitoring and analysis system, in the embodiment of the present application, during the operation of the wind turbine, the blades are subjected to aerodynamic load, gravitational load, inertial load and operating load. These loads work together to form a complex load spectrum of wind turbines. The damage or aging of composite materials during blade service is a gradual process with time, especially in the harsh and complex environment of wind farms. In addition to the role of mechanical mechanics, physical and chemical interactions between external chemical elements and blade materials may occur, which may lead to material damage. deterioration and structural failure. The wind turbine blade health online monitoring system, by adding special sensors, obtains the structural dynamics and temperature signals on the fan blades, and carries out the timing acquisition and analysis of structural dynamics and related signals, thereby obtaining the operating status of the fan impeller equipment Therefore, the early failure of wind turbine blades can be detected in time to avoid serious damage to the machine and accidents.

In another optional embodiment, for the research on the health online monitoring and intelligent diagnosis system of the key equipment of the hydropower station, the embodiment of the present application can continuously monitor the operation process of the hydroelectric generating set online through the research on the online state monitoring and analysis system of the hydroelectric generating set. Vibration, swing, pressure pulsation, air gap, magnetic field strength and other stability-related parameters and working conditions parameters such as active power, reactive power, excitation voltage, relay stroke, etc., and long-term records useful data for equipment management and diagnosis, provide Professional diagnostic map, automatically generate unit status analysis report, and finally transmit and publish the data on the network; it can identify the unit status in time, find early signs of failure, and make judgments on the cause, severity, and development trend of the failure. It can eliminate hidden troubles in time and avoid the occurrence of destructive accidents.

In yet another optional embodiment, for the research on fault detection and life prediction technology of intelligent photovoltaic power station, this embodiment of the present application researches and extracts environmental indicators ( Such as light irradiance, ambient temperature, humidity, photovoltaic panel front panel temperature, wind) and panel indicators (such as size, material, photovoltaic array output current, output power), as well as monitoring data indicating whether there is a fault, etc. Research the fault diagnosis technology based on variable indicators/features, and use the above environmental indicators as input to establish offline/online real-time fault diagnosis models. And build a photovoltaic module scanning and detection system based on UAV, using the UAV scanning path and attitude control method, by controlling the UAV to obtain high-quality fault images of surface cracks and hot spots, build a storage platform for fault images, Realize the effective acquisition and storage of fault images, so as to build a photovoltaic module scanning and detection system based on UAV.

In the above-mentioned optional embodiments, the embodiments of the present application are based on the real-time diagnosis technology of micro-cracks and hot spots on the surface of components, the image preprocessing and fault feature extraction technology of fault images (including infrared images, etc.), and establish the image recognition-based surface The crack and hot spot diagnosis model realizes the real-time online fault diagnosis capability. For example, by performing image tilt correction (perspective transformation) on the infrared image of the photovoltaic panel, intercepting the single photovoltaic panel, image preprocessing, and Otsu threshold selection algorithm, etc. Connected areas are marked, and deep mining technology is used to monitor historical data of photovoltaic power plants, carry out photovoltaic array attenuation analysis and life prediction, obtain photovoltaic module attenuation data, study data mining technology, and establish machine learning models for failure and life prediction, and study environmental indicators The mapping relationship with the life prediction model realizes the ability to predict the attenuation of photovoltaic arrays based on environmental indicators.

In an optional embodiment, before determining the usable life cycle of the photovoltaic module according to the current environment data, the historical operation data, and the current operation data, the method further includes:

Step S202, determining the life cycle attenuation index of the above-mentioned photovoltaic module;

Step S204, obtaining sample environment data, sample historical operation data and sample current operation data;

Step S206 , based on the above-mentioned life cycle attenuation index, and according to the above-mentioned sample environment data, the above-mentioned sample historical operation data, and the above-mentioned sample current operation data, a photovoltaic module attenuation model is established.

In the above-mentioned optional embodiment, the above-mentioned life cycle attenuation index includes at least one of the following: photovoltaic module glass scratch index, light transmittance index, backplane mechanical characteristic index, cell crack index, hot spot effect and process control PID effect index, random attenuation index, chemical deterioration index of backsheet and sealing ethylene-vinyl acetate copolymer EVA film, photovoltaic module cleaning index.

There is also an optional embodiment. For the quality assessment of photovoltaic power station components and the research on the attenuation mechanism, the embodiment of the present application builds a photovoltaic component attenuation test experimental platform, regularly measures photovoltaic power generation data, and explores the impact of different environmental factors on photovoltaic component attenuation. .

For example, for the photovoltaic modules operating year by year from 2008 to 2018, 20 photovoltaic modules in each year (200 in total in 10 years) are selected, and the photovoltaic modules in each year are 14 monocrystalline silicon produced by multiple manufacturers. 4 pieces of polysilicon and 2 pieces of amorphous silicon, all photovoltaic modules are gathered together, and a photovoltaic module attenuation test experimental platform is built according to the actual operating status of photovoltaic modules; continuous monitoring of photovoltaic power generation data for a period of one year, including open-circuit voltage and short-circuit of modules Photovoltaic power generation data such as current and power attenuation rate; group photovoltaic modules, compare the attenuation of photovoltaic modules under different irradiation, temperature, and dust conditions, analyze the weight of each factor, and carry out follow-up experiments after the completion of photovoltaic power generation data monitoring.

In the above-mentioned optional embodiment, the attenuation test experimental research on photovoltaic modules can be further quantified from the physical and chemical perspectives in addition to the power generation, including the photovoltaic module glass scratch index, light transmittance index, backplane Mechanical characteristics index, cell crack index, hot spot effect and PID effect index, random attenuation index, chemical deterioration index of backsheet and sealing EVA film, photovoltaic module cleaning index, etc. Carry out photovoltaic module power generation comparison experiments over the years, photovoltaic glass mechanical characteristics and optical characteristics experiments, backplane mechanical characteristics detection and GPC test experiments, cell crack distribution statistics and EL test experiments, PID test experiments, hot spot effect detection experiments, different Materials and types of photovoltaic module attenuation comparison experiments, photovoltaic module attenuation comparison experiments with different cleaning levels, accelerated attenuation and destructive experiments, etc.

And by establishing a photovoltaic module attenuation model, predict the future operation of photovoltaic modules and research on photovoltaic module attenuation monitoring, prevention and control measures, for example, establish a photovoltaic module attenuation model in high-altitude desert areas to accurately predict the future operation of photovoltaic modules; Long-term power generation data monitoring of modules and visual and infrared monitoring of drones to prevent abnormal attenuation of optical modules, take effective measures for photovoltaic module attenuation, reduce the attenuation rate and the adverse factors such as strong radiation, large temperature difference, and dust in the environment. influence.

As an optional embodiment, in the aspect of equipment health online monitoring and intelligent diagnosis, big data analysis is used to determine the current health status of the large components of the wind turbine, the current health status of the hydro turbine, the points with operational risks and possible faults, and the maintenance Provide the basis for spare parts preparation, maintenance plan formulation, etc. In the research of fault detection and life prediction technology of intelligent photovoltaic power station, aiming at the problem of fault diagnosis of photovoltaic system in high-altitude areas, combined with exploration of historical data, environmental data and real-time monitoring data, the optimization technology of photovoltaic power station operation and maintenance is researched based on big data method. The accurate diagnosis of photovoltaic power generation system provides a theoretical basis. Photovoltaic power station module quality assessment and research on attenuation mechanism are carried out around the attenuation of photovoltaic modules. By quantifying the attenuation indicators of photovoltaic modules and combining with environmental climate data over the years, the attenuation factors of photovoltaic modules are identified, the main factors causing module attenuation are clarified, and the attenuation mechanism of photovoltaic modules is clarified. , to establish a photovoltaic module attenuation model to accurately predict the future operation of photovoltaic power plants.

In an optional embodiment, determining the usable life cycle of the photovoltaic module according to the above-mentioned current environment data, the above-mentioned historical operation data and the above-mentioned current operation data, including:

Step S302, according to the above-mentioned current environment data, the above-mentioned historical operation data and the above-mentioned current operation data, determine the above-mentioned sample environmental data, the above-mentioned sample historical operation data and the above-mentioned sample current operation data corresponding to the above-mentioned photovoltaic module attenuation model;

Step S304, analyze the current environment data based on the sample environment data to obtain a first analysis result, analyze the historical operation data according to the sample historical operation data to obtain a second analysis result, and analyze the current environment data according to the sample current operation data. The operation data is analyzed to obtain a third analysis result;

Step S306: Obtain the usable life cycle in at least one of the first analysis result, the second analysis result, and the third analysis result.

In the above-mentioned optional embodiment, the above-mentioned sample environmental data, the above-mentioned sample historical operation data and the above-mentioned sample current operation data corresponding to the above-mentioned photovoltaic module attenuation model are determined according to the current environmental data, the above-mentioned historical operation data and the above-mentioned current operation data; and analyze the current environment data based on the sample environment data to obtain a first analysis result, analyze the historical operation data according to the sample historical operation data to obtain a second analysis result, and analyze the current operation data according to the sample current operation data Perform analysis to obtain a third analysis result; and then obtain the usable life cycle in at least one of the first analysis result, the second analysis result, and the third analysis result.

The solution for online monitoring and intelligent diagnosis of equipment health provided by the embodiments of the present application breaks through the regular maintenance mode of traditional equipment, and solves the problem of "over-maintenance" or "insufficient maintenance" of equipment. Transform the traditional post-event maintenance and planned maintenance of equipment to condition maintenance and predictive maintenance. As the basic means of predictive maintenance, equipment health status monitoring and intelligent diagnosis technology play an important role in promoting the continuous development of equipment management. In the research of fault detection and life prediction technology of intelligent photovoltaic power station, one is to build a photovoltaic module detection system based on drones, which is the basis for fault analysis; the other is to predict the life of photovoltaic modules based on environmental and historical data. In terms of PV power station module quality assessment and attenuation mechanism research, first, the attenuation of PV modules in high-altitude desert areas is measured by a single index of power attenuation rate and expanded to multiple indicators (including: photovoltaic module glass scratch index, light transmittance index, etc.). rate index, backplane mechanical characteristics index, cell cracking index, hot spot effect and PID effect index, random attenuation index, backplane and sealing EVA film chemical deterioration index, photovoltaic module cleaning index) to measure, is the subject of this topic. Main features and innovations. The second is to establish a PV module attenuation model in high-altitude desert areas for the first time, to accurately predict the future operation of PV modules, and to provide a basis and reference for the formulation of module attenuation standards in the PV industry.

The embodiments of the present application help to proactively troubleshoot equipment failures, reduce operating risks, extend equipment service life, and improve equipment utilization, safety, and reliability through research on equipment health online monitoring and intelligent diagnosis. Carry out maintenance according to the equipment condition Comprehensively monitor the work and process, reduce the number of machine overhauls, thus reduce maintenance costs and reduce indirect losses caused by overhauls. Eliminate the risk of failure due to unnecessary maintenance or "over-maintenance" to smooth-running machines. Combining equipment health monitoring technology with proactive and reliable maintenance methods can greatly reduce losses caused by unplanned downtime.

The embodiment of the present application conducts research on fault detection and life prediction technology for smart photovoltaic power plants, and researches on fault diagnosis technology for photovoltaic power generation systems in high-altitude areas. The research results can effectively reduce the failure rate of photovoltaic modules, improve the quality of photovoltaic power generation of large-scale photovoltaic power plants, prolong the life cycle of battery modules, reduce the operation and maintenance costs of photovoltaic power plants, help the healthy development of photovoltaic operation and maintenance industry, and effectively improve the intelligence of photovoltaic power plants. It can effectively guarantee the reliability of photovoltaic power plants.

In the embodiment of the present application, aiming at the quality evaluation of photovoltaic power station components and the research on the attenuation mechanism, the current situation of attenuation of photovoltaic components in the western desert areas with large photovoltaic power generation scale is investigated, and in-depth research is carried out. Photovoltaic modules of different types and manufacturers in operation are used as the research objects to build a photovoltaic module attenuation test platform, explore the attenuation mechanism of photovoltaic modules, and establish a photovoltaic module attenuation model, which provides a theoretical basis for the accurate prediction of photovoltaic power generation in desert areas in our province. The formulation of PV module attenuation standards provides a reference, enhances the competitiveness of PV module manufacturers, and facilitates the healthy development of the PV operation and maintenance industry.

Example 2

According to an embodiment of the present invention, a system embodiment for implementing the above method for determining the life cycle of a photovoltaic module is also provided. FIG. 2 is a schematic structural diagram of a system for determining the life cycle of a photovoltaic module according to an embodiment of the present invention. 2, the above-mentioned system for determining the life cycle of photovoltaic modules includes: a monitor 30 and a processor 32, wherein:

The monitor 30 is used to monitor the current environmental data and the current operation data of the above-mentioned photovoltaic modules; the processor 32 is connected to the above-mentioned monitor 30 and used to obtain the historical operation data of the photovoltaic modules, and based on the above-mentioned current environmental data, the above-mentioned historical operation data The data and the above-mentioned current operation data are used to determine the usable life cycle of the above-mentioned photovoltaic modules.

Optionally, the processor 32 is further configured to determine the life cycle attenuation index of the photovoltaic module; obtain sample environment data, sample historical operation data, and sample current operation data; The PV module attenuation model is established based on the sample historical operation data and the above-mentioned sample current operation data.

Optionally, the above-mentioned processor 32 is further configured to determine the above-mentioned sample environmental data, the above-mentioned sample historical operation data and the above-mentioned sample current corresponding to the above-mentioned photovoltaic module attenuation model according to the above-mentioned current environmental data, the above-mentioned historical operation data and the above-mentioned current operation data. Operation data; analyze the current environment data based on the sample environment data to obtain a first analysis result, analyze the historical operation data according to the sample historical operation data to obtain a second analysis result, and analyze the current environment data according to the sample current operation data to obtain a second analysis result. The operation data is analyzed to obtain a third analysis result; and the above-mentioned usable life cycle in at least one analysis result of the above-mentioned first analysis result, the above-mentioned second analysis result and the above-mentioned third analysis result is obtained.

In the embodiments of the present application, the photovoltaic module scanning and detection system may include various sensors, monitors, and one or more processors or chips having a communication interface capable of implementing a communication protocol, and may also include a memory if necessary and related interfaces, system transmission buses, etc.; the processor or chip executes program-related codes to implement corresponding functions.

It should be noted that the specific structure of the system for determining the life cycle of photovoltaic modules shown in FIG. 2 in this application is only for illustration. In specific applications, the system for determining the life cycle of photovoltaic modules in this application can be compared with FIG. 2 The system shown for determining the life cycle of photovoltaic modules has a more or less structure.

It should be noted that any optional or preferred method for determining the life cycle of a photovoltaic module in the above Embodiment 1 can be executed or implemented in the system for determining the life cycle of a photovoltaic module provided in this embodiment. .

In addition, it should be noted that for optional or preferred implementations of this embodiment, reference may be made to the relevant descriptions in Embodiment 1, and details are not repeated here.

Example 3

According to an embodiment of the present invention, an embodiment of an apparatus for implementing the above-mentioned method for determining the life cycle of a photovoltaic module is also provided. FIG. 3 is a schematic structural diagram of an apparatus for determining the life cycle of a photovoltaic module according to an embodiment of the present invention. 3, the above-mentioned device for determining the life cycle of a photovoltaic module includes: an acquisition module 40, a monitoring module 42 and a determination module 44, wherein:

The acquisition module 40 is used to acquire the historical operation data of the photovoltaic modules; the monitoring module 42 is used to monitor the current environment data and the current operation data of the photovoltaic modules; the determination module 44 is used to monitor the current environment data, the historical operation data and the The above current operating data determines the usable life cycle of the above photovoltaic modules.

It should be noted that the above modules can be implemented by software or hardware. For example, the latter can be implemented in the following ways: the above modules can be located in the same processor; or, the above modules can be arbitrarily combined. in different processors.

In the embodiment of the present application, the acquisition module 40 and the determination module 44 may be one or more processors or chips with a communication interface capable of implementing a communication protocol, and may also include a memory and related interfaces, a system transmission bus if necessary etc.; the processor or chip executes program-related codes to implement corresponding functions. The monitoring module 42 may include a variety of sensors, monitors, and one or more processors or chips with communication interfaces capable of implementing communication protocols, and may also include memory and related interfaces, system transmission buses, etc. if necessary; The processor or chip executes the program-related code to implement the corresponding function. Alternatively, an alternative solution is that the acquisition module 40, the determination module 44, and the monitoring module 42 share an integrated chip or share devices such as a processor and a memory. The shared processor or chip executes program-related codes to implement corresponding functions.

It should be noted here that the above acquisition module 40, monitoring module 42 and determination module 44 correspond to steps S102 to S106 in Embodiment 1, and the above modules and corresponding steps have the same examples and application scenarios, but are not limited to The content disclosed in Example 1 above.

It should be noted that, for optional or preferred implementations of this embodiment, reference may be made to the relevant descriptions in Embodiment 1, and details are not repeated here.

Optionally, the above-mentioned device for determining the life cycle of a photovoltaic module may also include a processor and a memory, and the above-mentioned acquisition module 40, monitoring module 42 and determination module 44 are all stored in the memory as program units, and are executed by the processor and stored in the memory. The above program units in the memory implement the corresponding functions.

The processor includes a kernel, and the kernel calls the corresponding program unit from the memory, and one or more of the above-mentioned kernels can be set. Memory may include non-persistent memory in computer readable media, random access memory (RAM) and/or non-volatile memory, such as read only memory (ROM) or flash memory (flash RAM), the memory including at least one memory chip.

According to an embodiment of the present application, an embodiment of a non-volatile storage medium is also provided. Optionally, in this embodiment, the above-mentioned non-volatile storage medium includes a stored program, wherein when the above-mentioned program runs, the device where the above-mentioned non-volatile storage medium is located is controlled to execute any of the above to determine the life cycle of the photovoltaic module. Methods.

Optionally, in this embodiment, the above-mentioned non-volatile storage medium may be located in any computer terminal in the computer terminal group in the computer network, or in any mobile terminal in the mobile terminal group, the above-mentioned non-volatile storage medium Sexual storage media include stored programs.

Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: obtaining historical operating data of photovoltaic modules; monitoring current environmental data and current operating data of the photovoltaic modules; The operating data and the above-mentioned current operating data are used to determine the usable life cycle of the above-mentioned photovoltaic modules.

Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: determine the life cycle decay index of the photovoltaic module; obtain sample environment data, sample historical operation data and sample current operation data; based on the above life cycle For the attenuation index, the photovoltaic module attenuation model is established according to the sample environment data, the sample historical operation data, and the sample current operation data.

Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following function: according to the above-mentioned current environmental data, the above-mentioned historical operation data and the above-mentioned current operation data, determine the above-mentioned sample environmental data corresponding to the above-mentioned photovoltaic module attenuation model , the above-mentioned sample historical operation data and the above-mentioned sample current operation data; the first analysis result is obtained by analyzing the above-mentioned current environment data based on the above-mentioned sample environment data, and the second analysis result is obtained by analyzing the above-mentioned historical operation data according to the above-mentioned sample historical operation data, and analyzing the above-mentioned current operation data according to the above-mentioned sample current operation data to obtain a third analysis result; obtaining the above-mentioned usable life data in at least one analysis result of the above-mentioned first analysis result, the above-mentioned second analysis result and the above-mentioned third analysis result cycle.

Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: obtaining the historical output current and historical output power of the above photovoltaic modules; Current environmental data, wherein the above-mentioned current environmental data includes at least one of the following: irradiance, ambient temperature, humidity, front panel temperature, and wind power; control the UAV-based photovoltaic module scanning and detection system to monitor the above-mentioned photovoltaic modules. Current output current and current output power.

According to an embodiment of the present application, an embodiment of a processor is also provided. Optionally, in this embodiment, the above-mentioned processor is configured to run a program, wherein, when the above-mentioned program runs, any one of the above-mentioned methods for determining the life cycle of a photovoltaic module is executed.

An embodiment of the present application provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute any one of the above-mentioned methods of determining the life of a photovoltaic module. cycle method.

The application also provides a computer program product, when executed on a data processing device, adapted to execute a program initialized with the steps of the method of determining the life cycle of a photovoltaic module.

The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages or disadvantages of the embodiments.

In the above-mentioned embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units may be a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or may be Integration into another system, or some features can be ignored, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of units or modules, and may be in electrical or other forms.

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

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.

The integrated unit, if implemented in the form of a software functional unit and sold or used as an independent product, may be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product in essence, or the part that contributes to the prior art, or all or part of the technical solution can be stored in a non-volatile In a non-volatile storage medium, several instructions are included to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned non-volatile storage media include: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other various storage media medium of program code.

The above are only the preferred embodiments of the present invention. It should be pointed out that for those skilled in the art, without departing from the principles of the present invention, several improvements and modifications can be made. It should be regarded as the protection scope of the present invention.

Claims

A method for determining the life cycle of a photovoltaic module, comprising:

Obtain historical operating data of PV modules;

monitoring current environmental data and current operating data of the photovoltaic modules;

According to the current environment data, the historical operation data and the current operation data, the usable life cycle of the photovoltaic module is determined.
The method according to claim 1, wherein before determining the usable life cycle of the photovoltaic module according to the current environmental data, the historical operation data and the current operation data, the method further comprises: :

determining the life cycle decay index of the photovoltaic module;

Obtain sample environment data, sample historical operation data and sample current operation data;

Based on the life cycle attenuation index, a photovoltaic module attenuation model is established according to the sample environment data, the sample historical operation data and the sample current operation data.
The method according to claim 2, wherein determining the usable life cycle of the photovoltaic module according to the current environmental data, the historical operation data and the current operation data, comprising:

determining the sample environment data, the sample historical operation data and the sample current operation data corresponding to the photovoltaic module attenuation model according to the current environment data, the historical operation data and the current operation data;

A first analysis result is obtained by analyzing the current environment data based on the sample environment data, a second analysis result is obtained by analyzing the historical operation data according to the sample historical operation data, and a pair of The current operating data is analyzed to obtain a third analysis result;

The usable life cycle in at least one of the first analysis result, the second analysis result, and the third analysis result is acquired.
The method according to claim 2, wherein the life cycle attenuation index includes at least one of the following: a photovoltaic module glass scratch index, a light transmittance index, a backplane mechanical characteristic index, a cell cracking index, a thermal Speckle effect and process control PID effect index, random attenuation index, back sheet and sealing ethylene-vinyl acetate copolymer EVA film chemical deterioration index, photovoltaic module cleaning index.
The method of claim 1, wherein:

Obtaining historical operating data of photovoltaic modules, including: obtaining historical output current and historical output power of the photovoltaic modules;

Monitoring the current environmental data of photovoltaic modules includes: controlling a photovoltaic module scanning and detection system based on drones, and collecting and obtaining the current environmental data, wherein the current environmental data includes at least one of the following: light irradiance, environmental temperature, humidity, front panel temperature, wind;

Monitoring the current operating data of the photovoltaic modules includes: controlling a photovoltaic module scanning and detection system based on a drone, and monitoring the current output current and current output power of the photovoltaic modules.
The method according to any one of claims 1 to 5, wherein the photovoltaic assembly is a photovoltaic assembly disposed in a high-altitude desert region.
A system for determining the life cycle of photovoltaic modules, comprising:

a monitor for monitoring current environmental data and current operating data of the photovoltaic module;

a processor, connected to the monitor, for acquiring historical operating data of the photovoltaic module, and determining the usable life cycle of the photovoltaic module according to the current environmental data, the historical operating data and the current operating data .
The system according to claim 7, wherein the processor is further configured to determine the life cycle decay index of the photovoltaic module; obtain sample environmental data, sample historical operation data and sample current operation data; A periodic decay index, a photovoltaic module decay model is established according to the sample environment data, the sample historical operation data and the sample current operation data.
The system according to claim 8, wherein the processor is further configured to determine, according to the current environment data, the historical operation data and the current operation data, all corresponding values in the photovoltaic module attenuation model. the sample environment data, the sample historical operation data and the sample current operation data; the first analysis result is obtained by analyzing the current environment data based on the sample environment data, and the historical The operation data is analyzed to obtain a second analysis result, and the current operation data is analyzed according to the sample current operation data to obtain a third analysis result; the first analysis result, the second analysis result and the third analysis result are obtained; The usable life cycle in at least one of the three analysis results.
The system of claim 8, further comprising:

Photovoltaic module scanning and detection system, used for collecting the current environment data and the current operation data, wherein the current environment data includes at least one of the following: light irradiance, ambient temperature, humidity, front plate temperature, Wind power, the current operation data includes: current output current and current output power.
The system according to any one of claims 7 to 10, wherein the photovoltaic module is a photovoltaic module arranged in a high-altitude desert area.
A device for determining the life cycle of a photovoltaic module, characterized in that it includes:

The acquisition module is used to acquire the historical operation data of PV modules;

a monitoring module for monitoring current environmental data and current operating data of the photovoltaic module;

and a determining module, configured to determine the usable life cycle of the photovoltaic module according to the current environment data, the historical operation data and the current operation data.
A non-volatile storage medium, characterized in that the non-volatile storage medium stores a plurality of instructions, the instructions are adapted to be loaded by a processor and execute the determination according to any one of claims 1 to 6 A method for the life cycle of photovoltaic modules.
A processor, characterized in that the processor is configured to run a program, wherein the program is configured to execute the method for determining the life cycle of a photovoltaic module according to any one of claims 1 to 6 when running. .
An electronic device comprising a memory and a processor, characterized in that, a computer program is stored in the memory, and the processor is configured to run the computer program to execute any one of the claims 1 to 6. The described method for determining the life cycle of photovoltaic modules.