WO2022063282A1 - 确定光伏组件的生命周期的方法及装置 - Google Patents

确定光伏组件的生命周期的方法及装置 Download PDF

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Publication number
WO2022063282A1
WO2022063282A1 PCT/CN2021/120786 CN2021120786W WO2022063282A1 WO 2022063282 A1 WO2022063282 A1 WO 2022063282A1 CN 2021120786 W CN2021120786 W CN 2021120786W WO 2022063282 A1 WO2022063282 A1 WO 2022063282A1
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data
current
operation data
photovoltaic module
photovoltaic
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French (fr)
Inventor
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
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State Grid Qinghai Electric Power Co Ltd
Information and Telecommunication Branch of State Grid Qinghai Electric Power Co Ltd
State Grid Corp of China SGCC
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State Grid Qinghai Electric Power Co Ltd
Information and Telecommunication Branch of State Grid Qinghai Electric Power Co Ltd
State Grid Corp of China SGCC
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2465—Query processing support for facilitating data mining operations in structured databases
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/04—Ageing analysis or optimisation against ageing
    • 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
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Definitions

  • 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.
  • 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 .
  • a method for determining the life cycle of a photovoltaic module 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.
  • the method 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.
  • 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 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 .
  • 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.
  • 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.
  • the above photovoltaic modules are photovoltaic modules arranged in high-altitude desert areas.
  • 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.
  • 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.
  • 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
  • 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.
  • 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.
  • a photovoltaic module scanning and detection system for collecting and obtaining the above-mentioned current environmental data and the above-mentioned current operation data
  • 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.
  • the above photovoltaic modules are photovoltaic modules arranged in high-altitude desert areas.
  • an apparatus for determining the life cycle of a photovoltaic module 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.
  • a 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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
  • 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.
  • 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.
  • the above photovoltaic modules are photovoltaic modules arranged in high-altitude desert areas.
  • 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 .
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the wind turbine computer monitoring system network is used for data transmission to realize remote diagnosis and equipment status evaluation by experts.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • environmental indicators such as light irradiance, ambient temperature, humidity, photovoltaic panel front panel temperature, wind
  • panel indicators such as size, material, photovoltaic array output current, output power
  • 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.
  • the method 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.
  • 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.
  • 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. .
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • a photovoltaic module scanning and detection system for collecting and obtaining the above-mentioned current environmental data and the above-mentioned current operation data
  • 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.
  • the above photovoltaic modules are photovoltaic modules arranged in high-altitude desert areas.
  • 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.
  • 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. .
  • 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.
  • 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.
  • the above modules can be implemented by software or hardware.
  • 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.
  • 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.
  • 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.
  • 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.
  • an embodiment of a non-volatile storage medium is also provided.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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
  • 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.
  • an embodiment of a processor is also provided.
  • 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 disclosed technical content can be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units may be a logical function division.
  • multiple units or components may be combined or may be Integration into another system, or some features can be ignored, or not implemented.
  • 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.
  • 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.
  • 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
  • a computer device which may be a personal computer, a server, or a network device, etc.
  • 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.

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Abstract

一种确定光伏组件的生命周期的方法及装置。其中，该方法包括：获取光伏组件的历史运行数据（S102）；监测上述光伏组件的当前环境数据和当前运行数据(S104)；依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期(S106)。该方法及装置解决了现有技术中仅凭经验设定光伏组件的使用寿命，无法动态评估光伏组件的可使用生命周期的技术问题。

Description

确定光伏组件的生命周期的方法及装置 技术领域
本发明涉及光伏技术领域，具体而言，涉及一种确定光伏组件的生命周期的方法及装置。
背景技术
中国能源结构优化的需求迫在眉睫，大力发展太阳能、风能、地热能等清洁能源成为必然趋势，光伏组件作为太阳能发电的核心设备，其质量问题和衰减特性直接影响光伏电站的总发电量的高低。
传统设计中，仅凭经验将光伏组件的使用寿命定为25年，无法动态评估光伏组件质量水平及衰减阶段，这一方面会导致部分工作于高海拔环境下的光伏组件在未满25年寿命时就出现故障无法使用的问题；另一方面会导致部分已服役25年但性能良好的光伏组件被提前替换增大经济成本。
针对上述的问题，目前尚未提出有效的解决方案。
发明内容
本发明实施例提供了一种确定光伏组件的生命周期的方法及装置，以至少解决现有技术中仅凭经验设定光伏组件的使用寿命，无法动态评估光伏组件的可使用生命周期的技术问题。
根据本发明实施例的一个方面，提供了一种确定光伏组件的生命周期的方法，包括：获取光伏组件的历史运行数据；监测上述光伏组件的当前环境数据和当前运行数据；依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期。
可选的，在依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期之前，上述方法还包括：确定上述光伏组件的生命周期衰减指标；获取样本环境数据、样本历史运行数据和样本当前运行数据；基于上述生命周期衰减指标，依据上述样本环境数据、上述样本历史运行数据和上述样本当前运行数据建立光伏组件衰减模型。
可选的，依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定 上述光伏组件的可使用生命周期，包括：依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件衰减模型中对应的上述样本环境数据、上述样本历史运行数据和上述样本当前运行数据；基于上述样本环境数据对上述当前环境数据进行分析得到第一分析结果，依据上述样本历史运行数据对上述历史运行数据进行分析得到第二分析结果，以及依据上述样本当前运行数据对上述当前运行数据进行分析得到第三分析结果；获取上述第一分析结果、上述第二分析结果和上述第三分析结果中的至少一个分析结果中的上述可使用生命周期。
可选的，上述生命周期衰减指标包括以下至少之一：光伏组件玻璃划痕指标、透光率指标、背板机械特性指标、电池片隐裂指标、热斑效应和进程控制PID效应指标、随机衰减指标、背板和密封乙烯-醋酸乙烯共聚物EVA胶膜化学变质指标、光伏组件清洁指标。
可选的，获取光伏组件的历史运行数据，包括：获取上述光伏组件的历史输出电流和历史输出功率；监测光伏组件的当前环境数据，包括：控制基于无人机的光伏组件扫描与检测系统，采集得到上述当前环境数据，其中，上述当前环境数据包括如下至少之一：光辐照度、环境温度、湿度、正板温度、风力；监测上述光伏组件的当前运行数据，包括：控制基于无人机的光伏组件扫描与检测系统，监测上述光伏组件的当前输出电流和当前输出功率。
可选的，上述光伏组件为设置在高海拔荒漠地区的光伏组件。
根据本发明实施例的另一方面，还提供了一种确定光伏组件的生命周期的系统，包括：监测器，用于监测上述光伏组件的当前环境数据和当前运行数据；处理器，与上述监测器连接，用于获取光伏组件的历史运行数据，并依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期。
可选的，上述处理器还用于确定上述光伏组件的生命周期衰减指标；获取样本环境数据、样本历史运行数据和样本当前运行数据；基于上述生命周期衰减指标，依据上述样本环境数据、上述样本历史运行数据和上述样本当前运行数据建立光伏组件衰减模型。
可选的，上述处理器还用于依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件衰减模型中对应的上述样本环境数据、上述样本历史运行数据和上述样本当前运行数据；基于上述样本环境数据对上述当前环境数据进行分析得到第一分析结果，依据上述样本历史运行数据对上述历史运行数据进行分析得到第二分析结果，以及依据上述样本当前运行数据对上述当前运行数据进行分析得到第三分析结果；获取上述第一分析结果、上述第二分析结果和上述第三分析结果中的至少一个分析结果中的上述可使用生命周期。
可选的，上述系统还包括：光伏组件扫描与检测系统，用于采集得到上述当前环 境数据和上述当前运行数据，其中，上述当前环境数据包括如下至少之一：光辐照度、环境温度、湿度、正板温度、风力，上述当前运行数据包括：当前输出电流和当前输出功率。
可选的，上述光伏组件为设置在高海拔荒漠地区的光伏组件。
根据本发明实施例的另一方面，还提供了一种确定光伏组件的生命周期的装置，包括：获取模块，用于获取光伏组件的历史运行数据；监测模块，用于监测上述光伏组件的当前环境数据和当前运行数据；确定模块，用于依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期。
根据本发明实施例的另一方面，还提供了一种非易失性存储介质，上述非易失性存储介质存储有多条指令，上述指令适于由处理器加载并执行任意一项的确定光伏组件的生命周期的方法。
根据本发明实施例的另一方面，还提供了一种处理器，上述处理器用于运行程序，其中，上述程序被设置为运行时执行任一项中上述的确定光伏组件的生命周期的方法。
根据本发明实施例的另一方面，还提供了一种电子装置，包括存储器和处理器，上述存储器中存储有计算机程序，上述处理器被设置为运行上述计算机程序以执行任一项中上述的确定光伏组件的生命周期的方法。
在本发明实施例中，通过获取光伏组件的历史运行数据；监测上述光伏组件的当前环境数据和当前运行数据；依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期，达到了动态评估光伏组件的可使用生命周期的目的，从而实现了避免仅凭经验设定光伏组件的使用寿命的技术效果，进而解决了现有技术中仅凭经验设定光伏组件的使用寿命，无法动态评估光伏组件的可使用生命周期的技术问题。
附图说明
此处所说明的附图用来提供对本发明的进一步理解，构成本申请的一部分，本发明的示意性实施例及其说明用于解释本发明，并不构成对本发明的不当限定。在附图中：
图1是根据本发明实施例的一种确定光伏组件的生命周期的方法的流程图；
图2是根据本发明实施例的一种确定光伏组件的生命周期的系统的结构示意图；
图3是根据本发明实施例的一种确定光伏组件的生命周期的装置的结构示意图。
具体实施方式
为了使本技术领域的人员更好地理解本发明方案，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分的实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都应当属于本发明保护的范围。
需要说明的是，本发明的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本发明的实施例能够以除了在这里图示或描述的那些以外的顺序实施。此外，术语“包括”和“具有”以及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
实施例1
根据本发明实施例，提供了一种确定光伏组件的生命周期的方法的实施例，需要说明的是，在附图的流程图示出的步骤可以在诸如一组计算机可执行指令的计算机系统中执行，并且，虽然在流程图中示出了逻辑顺序，但是在某些情况下，可以以不同于此处的顺序执行所示出或描述的步骤。
图1是根据本发明实施例的一种确定光伏组件的生命周期的方法的流程图，如图1所示，该方法包括如下步骤：
步骤S102，获取光伏组件的历史运行数据；
步骤S104，监测上述光伏组件的当前环境数据和当前运行数据；
步骤S106，依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期。
在本发明实施例中，通过获取光伏组件的历史运行数据；监测上述光伏组件的当前环境数据和当前运行数据；依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期，达到了动态评估光伏组件的可使用生命周期的目的，从而实现了避免仅凭经验设定光伏组件的使用寿命的技术效果，进而解决了现有技术中仅凭经验设定光伏组件的使用寿命，无法动态评估光伏组件的可使用生命周期的技术问题。
可选的，上述光伏组件为设置在高海拔荒漠地区的光伏组件。
在本申请实施例中，可以通过新能源大数据平台运行上述确定光伏组件的生命周 期的方法，上述新能源大数据平台用于提供开放的IaaS基础设施服务、PaaS平台服务、DaaS数据服务,服务器223台，平台内置超过100种通用算法和模型，接入能力超过1000万测点/秒，具备PB级数据存储容量和高吞吐数据并发能力，满足200GW、600座以上新能源电站的运营管控要求。
可选的，上述新能源大数据平台用于实现光伏组件的健康在线监测与智能诊断，源、网、荷侧多源异构数据的实时采集，实现风机部件级、光伏板件级最小颗粒度数据采集，采集频率5-7秒/次，累积接入数据已经超过55亿条，每日新增数据量超过60GB，高效支撑各类行业应用构建和使用。
在本申请实施例中，基于智能光伏电站故障检测与寿命预测技术实现光伏组件的健康在线监测与智能诊断，确定光伏组件的可使用生命周期，其中，光伏系统故障诊断方法是实现光伏组件的健康在线监测与智能诊断的基础，在此基础上，通过拟建立机、电、图像等多传感器融合的光伏阵列的新能源大数据平台，以完成对太阳能电池板进行环境(输入)和电力(输出)的全方位监控，为后期的信息挖掘建立良好的数据基础。
作为一种可选的实施例，本申请实施例除了利用输出电压和功率等数据进行电池板故障的实时监测，还可以利用电池板的表面缺陷和是否脏污等数据进行故障检测。拟通过控制无人机拍摄电池板图像，然后进行利用机器视觉的相关方法建立基于图像识别的表面裂纹和热斑诊断模型，得到电池板表面缺陷和脏污程度数据，实现实时在线故障诊断能力。
此外，本申请实施例中新能源大数据平台运用逻辑回归、朴素贝叶斯和决策树等数据处理技术，针对光伏电站系统中可监测的数据具有类型繁多且结构性差等特点，拟采用逻辑回归和朴素贝叶斯等方法进行故障分类、采用回归方法和决策树等进行连续预测光伏组件的可使用生命周期(即寿命)。
作为另一种可选的实施例，获取光伏组件的历史运行数据，包括：获取上述光伏组件的历史输出电流和历史输出功率；监测光伏组件的当前环境数据，包括：控制基于无人机的光伏组件扫描与检测系统，采集得到上述当前环境数据，其中，上述当前环境数据包括如下至少之一：光辐照度、环境温度、湿度、正板温度、风力；监测上述光伏组件的当前运行数据，包括：控制基于无人机的光伏组件扫描与检测系统，监测上述光伏组件的当前输出电流和当前输出功率。
在本申请实施例中，通过选购跨度为十年的不同厂家、不同类型光伏组件，及配套的实验仪器设备包括辐照仪、透光率仪、显微镜、PID专用测试电源，太阳模拟器、EL检测仪、红外成像仪、万用表、无人机、温度循环试验箱、环境监测设备、光伏组件清洁设备等，搭建光伏组件的衰减测试实验平台。
并通过从组件结构组成的角度量化光伏组件衰减指标，包括光伏玻璃、背板、电 池片、密封EVA胶膜的物理、化学性质的变化，以及致使光伏组件衰减的积灰效应、热斑效应和PID效应指标，开展历年光伏组件发电功率对比实验、光伏玻璃机械特性和光学特性实验、背板机械特性检测和GPC测试实验、电池片隐裂分布统计和EL测试实验、PID测试实验、热斑效应检测实验、不同材质和类型的光伏组件衰减对比实验、不同清洁程度光伏组件衰减对比实验、加速衰减和破坏性实验等。
最后通过利用大数据与无人机技术实时监控光伏组件运行情况，无人机搭载视觉与红外成像设备监控光组件，同时通过人为的定期清洁、以旧换新和及时修复故障等措施，减少光伏组件在非正常衰减情况下对光伏发电的影响。
在一种可选的实施例中，针对风力发电机组状态监测与分析系统研究，本申请实施例通过超低频振动加速度传感器实现主轴振动和塔筒的状态监测；通过普通加速度振动加速度传感器实现对行星轮、齿轮箱以及发电机等传动链设备的振动状态监测，借助转速传感器触发相关采集策略；接入机组其他的电流、电压、功率、风速等信号等通过过程量信号传输到同一个软件平台，通过多种报警处理方式，以及辅助诊断功能实现对设备故障的智能报警，然后利用风力发电机组计算机监控系统网络进行数据传输，实现专家的远程诊断与设备状态评估。
在一种可选的实施例中，针对风力发电机塔筒及地基沉降监测与分析系统研究，本申请实施例通过风力发电机塔筒及地基沉降监测与分析系统可监测风电机组塔筒工作状态及基础沉降状态，实时采集塔筒振动信号、晃度及倾角数据，分析风电机组运行状态，可通过机组倾覆实时监测图、危险转速区监测图、倾角分布图、频谱图、趋势图、分析对比图进行机组运行状况诊断分析，并能通过报警显示、自主报警、数据报表、日志查询、用户管理等多种工具进行数据管理，为风电机组健康运行提出最佳的状态监测解决方案。
在另一种可选的实施例中，针对风力发电机组叶片健康监测与分析系统研究，本申请实施例通过在风力发电机组运行过程中，叶片承受包括气动载荷、重力载荷、惯性载荷以及操作载荷等在内的多重载荷，这些载荷共同作用，形成了风力发电机组复杂的载荷谱。叶片服役期间复合材料的损坏或老化是一个随时间而渐变的过程，特别是风电场环境恶劣、复杂，除了机械力学的作用，外部化学元素与叶片材料还会发生物理化学作用，从而可能导致材料的劣化与结构失效。风电机组叶片健康在线监测系统，通过加装专用传感器，获得风机叶片上的结构动力学和温度信号，并进行结构动力学及相关信号的定时采集和分析处理，由此获得风机叶轮设备的运行状态信息，从而及时检测出风力发电机叶片的早期故障，避免机器的严重损坏和事故发生。
在另一种可选的实施例中，针对水电站关键设备健康在线监测与智能诊断系统研究，本申请实施例通过水轮发电机组在线状态监测和分析系统研究能够在线连续监测水轮发电机组运行过程中的振动、摆度、压力脉动、空气间隙、磁场强度等稳定性相 关参数及有功、无功、励磁电压、接力器行程等工况参数，并长期记录对设备管理、诊断有用的数据，提供专业的诊断图谱，自动生成机组状态分析报告，最终能把数据在网络上传输与发布；可以及时识别机组的状态、发现故障早期征兆，对故障原因、严重程度、及发展趋势做出判断，从而可以及时消除故障隐患，避免破坏性事故的发生。
在又一种可选的实施例中，针对智能光伏电站故障检测与寿命预测技术研究，本申请实施例基于环境传感器的光伏阵列在线故障诊断技术，研究并提取与光伏故障密切相关的环境指标(例如光辐照度、环境温度、湿度、光伏板正板温度、风力)和电池板指标(例如尺寸、材质、光伏阵列输出电流、输出功率)，以及表示是否故障的监督数据等。研究基于变量指标/特征的故障诊断技术，将以上环境指标作为输入，建立离线/在线实时故障诊断模型。并搭建基于无人机的光伏组件扫描和检测系统，采用无人机扫描路径与姿态控制方法，通过控制无人机获取高质量的表面裂纹和热斑的故障图像，搭建故障图像的存储平台，实现故障图像的有效获取和存储，从而搭建基于无人机的光伏组件扫描与检测系统。
在上述可选的实施例中，本申请实施例基于图像的组件表面微裂纹和热斑实时诊断技术，故障图像(包括红外线图像等)图像预处理与故障特征提取技术，建立基于图像识别的表面裂纹和热斑诊断模型，实现实时在线故障诊断能力，例如，通过对光伏板红外图片进行图像倾斜校正(透视变换)，单片光伏板截取，图像预处理，Otsu阈值选取算法等处理，实现对连通区域标记，并通过光伏电站监控历史数据深度挖掘技术，进行光伏阵列衰减度分析和寿命预测，获取光伏组件衰减数据，研究数据挖掘技术，并建立故障和寿命预测的机器学习模型，研究环境指标与寿命预测模型的映射关系，实现基于环境指标的光伏阵列衰减度预测能力。
在一种可选的实施例中，在依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期之前，上述方法还包括：
步骤S202，确定上述光伏组件的生命周期衰减指标；
步骤S204，获取样本环境数据、样本历史运行数据和样本当前运行数据；
步骤S206，基于上述生命周期衰减指标，依据上述样本环境数据、上述样本历史运行数据和上述样本当前运行数据建立光伏组件衰减模型。
在上述可选的实施例中，上述生命周期衰减指标包括以下至少之一：光伏组件玻璃划痕指标、透光率指标、背板机械特性指标、电池片隐裂指标、热斑效应和进程控制PID效应指标、随机衰减指标、背板和密封乙烯-醋酸乙烯共聚物EVA胶膜化学变质指标、光伏组件清洁指标。
还存在一种可选的实施例，针对光伏电站组件质量评估及衰减机制研究，本申请 实施例通过搭建光伏组件衰减测试实验平台，定期测定光伏发电数据，探究不同环境因素对光伏组件衰减的影响。
例如，针对2008-2018这十年间逐年运行的光伏组件，选取每一年的光伏组件20块(10年共计200块)，各年光伏组件分别为由多个厂家出产的单晶硅14块，多晶硅4块，非晶硅2块，所有光伏组件集中起来，按照实际光伏组件运行状态，搭建光伏组件衰减测试实验平台；开展为期1年的光伏发电数据的持续监测，包括组件的开路电压、短路电流、功率衰减率等光伏发电数据；对光伏组件进行分组，对比不同辐照、温度、灰尘条件下光伏组件衰减情况，分析各因素权重，并在光伏发电数据监测完成后开展后续实验。
在上述可选的实施例中，针对光伏组件进行衰减测试实验研究，可以从除发电功率外的物理和化学角度进一步量化组件衰减指标，包括光伏组件玻璃划痕指标、透光率指标，背板机械特性指标，电池片隐裂指标，热斑效应和PID效应指标，随机衰减指标，背板和密封EVA胶膜化学变质指标，光伏组件清洁指标等。开展历年光伏组件发电功率对比实验、光伏玻璃机械特性和光学特性实验、背板机械特性检测和GPC测试实验、电池片隐裂分布统计和EL测试实验、PID测试实验、热斑效应检测实验、不同材质和类型的光伏组件衰减对比实验、不同清洁程度光伏组件衰减对比实验、加速衰减和破坏性实验等。
并通过建立光伏组件衰减模型，预测光伏组件未来运行情况并对光伏组件衰减监测、预防和控制措施的研究，例如，建立高海拔荒漠地区光伏组件衰减模型，准确预测光伏组件未来运行情况；对光伏组件的进行长期发电数据监测和无人机搭载视觉与红外监测，预防光组件非正常衰减，针对光伏组件衰减采取有效措施，降低衰减速率和环境中辐射强、温差大、灰尘多等不利因素的影响。
作为一种可选的实施例，设备健康在线监测与智能诊断方面，通过大数据分析，判定风电机组大部件、水轮机组当前的健康状况、存在运行风险的点位和可能存在的故障，为检修备件准备、检修方案制定等提供依据。智能光伏电站故障检测与寿命预测技术研究方面，针对高海拔地区光伏系统故障诊断难题，结合历史数据、环境数据和实时监测数据等探索，基于大数据方法对光伏电站运维优化技术进行研究，为光伏发电系统精确诊断提供理论依据。光伏电站组件质量评估及衰减机制研究围绕光伏组件衰减开展，通过量化光伏组件衰减的指标并结合历年环境气候数据，探明光伏组件的衰减因素，明确致使组件衰减的主要因素，明晰光伏组件衰减机理，建立光伏组件衰减模型，以便精准预测光伏电站未来运行情况。
在一种可选的实施例中，依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期，包括：
步骤S302，依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确 定上述光伏组件衰减模型中对应的上述样本环境数据、上述样本历史运行数据和上述样本当前运行数据；
步骤S304，基于上述样本环境数据对上述当前环境数据进行分析得到第一分析结果，依据上述样本历史运行数据对上述历史运行数据进行分析得到第二分析结果，以及依据上述样本当前运行数据对上述当前运行数据进行分析得到第三分析结果；
步骤S306，获取上述第一分析结果、上述第二分析结果和上述第三分析结果中的至少一个分析结果中的上述可使用生命周期。
在上述可选的实施例中，通过当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件衰减模型中对应的上述样本环境数据、上述样本历史运行数据和上述样本当前运行数据；并基于上述样本环境数据对上述当前环境数据进行分析得到第一分析结果，依据上述样本历史运行数据对上述历史运行数据进行分析得到第二分析结果，以及依据上述样本当前运行数据对上述当前运行数据进行分析得到第三分析结果；进而获取上述第一分析结果、上述第二分析结果和上述第三分析结果中的至少一个分析结果中的上述可使用生命周期。
本申请实施例提供的设备健康在线监测与智能诊断方案，突破传统设备的定期维检修模式，解决设备“维修过剩”或“维修不足”问题。将设备传统的事后维修、计划检修向状态维修、预知维修迈进。设备健康状态监测及智能诊断技术作为预知检修的基础手段，在推进设备管理的不断发展中起到了重要作用。智能光伏电站故障检测与寿命预测技术研究方面，一是搭建基于无人机的光伏组件检测系统，是对故障分析的基础；二是基于环境和历史数据对光伏组件寿命进行预测。在光伏电站组件质量评估及衰减机制研究方面，一是针对高海拔荒漠地区的光伏组件的衰减由功率衰减率这一单一指标来衡量扩展为多指标(包括：光伏组件玻璃划痕指标、透光率指标，背板机械特性指标，电池片隐裂指标，热斑效应和PID效应指标，随机衰减指标，背板和密封EVA胶膜化学变质指标，光伏组件清洁指标)来衡量，是本课题的主要特色和创新之处。二是首次建立高海拔荒漠地区光伏组件衰减模型，对光伏组件未来运行情况进行准确预测，为光伏行业组件衰减标准的制定提供依据和参考。
本申请实施例通过设备健康在线监测与智能诊断研究，有助于主动排查设备故障，降低运行风险，延长设备使用寿命，提高设备利用率、安全性和可靠性。根据设备状况进行维护对工作和过程进行全面的监测，减少机器检修的次数，从而降低维护成本，降低因检修产生的间接损失。消除因不必要维修或“过度维修”给平稳运行的机器带来的故障风险。通过设备健康状态监测技术结合主动性、可靠维修方式可大大降低非计划停机造成的损失。
本申请实施例通过智能光伏电站故障检测与寿命预测技术研究，针对高海拔地区光伏发电系统故障诊断技术进行研究，重点基于历史数据、环境数据和实时监测数据， 实现光伏系统立体式诊断机制，其研究成果能有效降低光伏组件的故障率，提高大规模光伏电站光伏发电质量，延长电池组件的生命周期，降低光伏电站运维成本，助力光伏运维行业的健康发展，可有效提高光伏电站的智能化水平，有效的保障光伏电站的可靠性。
在本申请实施例中，针对光伏电站组件质量评估及衰减机制研究，对光伏发电规模较大西部荒漠地区的光伏组件的衰减现状展开调查，进行深入研究，通过现场取样选取跨度为十年间逐年投入运营的不同类型、不同厂家的光伏组件作为研究对象，搭建光伏组件衰减测试平台，探究光伏组件衰减机理，建立光伏组件衰减模型，为我省荒漠地区的光伏发电功率精准预测提供了理论基础，为光伏组件衰减标准的制定提供参考，提升光伏组件制造企业的竞争力，助力光伏运维行业的健康发展。
实施例2
根据本发明实施例，还提供了一种用于实施上述确定光伏组件的生命周期的方法的系统实施例，图2是根据本发明实施例的一种确定光伏组件的生命周期的系统的结构示意图，如图2所示，上述确定光伏组件的生命周期的系统，包括：监测器30和处理器32，其中：
监测器30，用于监测上述光伏组件的当前环境数据和当前运行数据；处理器32，与上述监测器30连接，用于获取光伏组件的历史运行数据，并依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期。
可选的，上述处理器32还用于确定上述光伏组件的生命周期衰减指标；获取样本环境数据、样本历史运行数据和样本当前运行数据；基于上述生命周期衰减指标，依据上述样本环境数据、上述样本历史运行数据和上述样本当前运行数据建立光伏组件衰减模型。
可选的，上述处理器32还用于依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件衰减模型中对应的上述样本环境数据、上述样本历史运行数据和上述样本当前运行数据；基于上述样本环境数据对上述当前环境数据进行分析得到第一分析结果，依据上述样本历史运行数据对上述历史运行数据进行分析得到第二分析结果，以及依据上述样本当前运行数据对上述当前运行数据进行分析得到第三分析结果；获取上述第一分析结果、上述第二分析结果和上述第三分析结果中的至少一个分析结果中的上述可使用生命周期。
可选的，上述系统还包括：光伏组件扫描与检测系统，用于采集得到上述当前环境数据和上述当前运行数据，其中，上述当前环境数据包括如下至少之一：光辐照度、环境温度、湿度、正板温度、风力，上述当前运行数据包括：当前输出电流和当前输出功率。
可选的，上述光伏组件为设置在高海拔荒漠地区的光伏组件。
在本申请的实施例中，所述光伏组件扫描与检测系统可以包括多种传感器、监测器，以及具有通信接口能够实现通信协议的一个或多个处理器或者芯片，如有需要还可以包括存储器及相关的接口、系统传输总线等；所述处理器或者芯片执行程序相关的代码实现相应的功能。
需要说明的是，本申请中的图2中所示确定光伏组件的生命周期的系统的具体结构仅是示意，在具体应用时，本申请中的确定光伏组件的生命周期的系统可以比图2所示的确定光伏组件的生命周期的系统具有多或少的结构。
需要说明的是，上述实施例1中的任意一种可选的或优选的确定光伏组件的生命周期的方法，均可以在本实施例所提供的确定光伏组件的生命周期的系统中执行或实现。
此外，仍需要说明的是，本实施例的可选或优选实施方式可以参见实施例1中的相关描述，此处不再赘述。
实施例3
根据本发明实施例，还提供了一种用于实施上述确定光伏组件的生命周期的方法的装置实施例，图3是根据本发明实施例的一种确定光伏组件的生命周期的装置的结构示意图，如图3所示，上述确定光伏组件的生命周期的装置，包括：获取模块40、监测模块42和确定模块44，其中：
获取模块40，用于获取光伏组件的历史运行数据；监测模块42，用于监测上述光伏组件的当前环境数据和当前运行数据；确定模块44，用于依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期。
需要说明的是，上述各个模块是可以通过软件或硬件来实现的，例如，对于后者，可以通过以下方式实现：上述各个模块可以位于同一处理器中；或者，上述各个模块以任意组合的方式位于不同的处理器中。
本申请的实施例中，所述获取模块40、确定模块44可以是具有通信接口能够实现通信协议的一个或多个处理器或者芯片，如有需要还可以包括存储器及相关的接口、系统传输总线等；所述处理器或者芯片执行程序相关的代码实现相应的功能。所述监测模块42可以包括多种传感器、监测器，以及具有通信接口能够实现通信协议的一个或多个处理器或者芯片，如有需要还可以包括存储器及相关的接口、系统传输总线等；所述处理器或者芯片执行程序相关的代码实现相应的功能。或者，可替换的方案为，所述获取模块40、确定模块44，监测模块42共享一个集成芯片或者共享处理器、存 储器等设备。所述共享的处理器或者芯片执行程序相关的代码实现相应的功能。
此处需要说明的是，上述获取模块40、监测模块42和确定模块44对应于实施例1中的步骤S102至步骤S106，上述模块与对应的步骤所实现的实例和应用场景相同，但不限于上述实施例1所公开的内容。
需要说明的是，本实施例的可选或优选实施方式可以参见实施例1中的相关描述，此处不再赘述。
可选地，上述的确定光伏组件的生命周期的装置还可以包括处理器和存储器，上述获取模块40、监测模块42和确定模块44等均作为程序单元存储在存储器中，由处理器执行存储在存储器中的上述程序单元来实现相应的功能。
处理器中包含内核，由内核去存储器中调取相应的程序单元，上述内核可以设置一个或以上。存储器可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)，存储器包括至少一个存储芯片。
根据本申请实施例，还提供了一种非易失性存储介质实施例。可选地，在本实施例中，上述非易失性存储介质包括存储的程序，其中，在上述程序运行时控制上述非易失性存储介质所在设备执行上述任意一种确定光伏组件的生命周期的方法。
可选地，在本实施例中，上述非易失性存储介质可以位于计算机网络中计算机终端群中的任意一个计算机终端中，或者位于移动终端群中的任意一个移动终端中，上述非易失性存储介质包括存储的程序。
可选地，在程序运行时控制非易失性存储介质所在设备执行以下功能：获取光伏组件的历史运行数据；监测上述光伏组件的当前环境数据和当前运行数据；依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件的可使用生命周期。
可选地，在程序运行时控制非易失性存储介质所在设备执行以下功能：确定上述光伏组件的生命周期衰减指标；获取样本环境数据、样本历史运行数据和样本当前运行数据；基于上述生命周期衰减指标，依据上述样本环境数据、上述样本历史运行数据和上述样本当前运行数据建立上述光伏组件衰减模型。
可选地，在程序运行时控制非易失性存储介质所在设备执行以下功能：依据上述当前环境数据、上述历史运行数据和上述当前运行数据，确定上述光伏组件衰减模型中对应的上述样本环境数据、上述样本历史运行数据和上述样本当前运行数据；基于 上述样本环境数据对上述当前环境数据进行分析得到第一分析结果，依据上述样本历史运行数据对上述历史运行数据进行分析得到第二分析结果，以及依据上述样本当前运行数据对上述当前运行数据进行分析得到第三分析结果；获取上述第一分析结果、上述第二分析结果和上述第三分析结果中的至少一个分析结果中的上述可使用生命周期。
可选地，在程序运行时控制非易失性存储介质所在设备执行以下功能：获取上述光伏组件的历史输出电流和历史输出功率；控制基于无人机的光伏组件扫描与检测系统，采集得到上述当前环境数据，其中，上述当前环境数据包括如下至少之一：光辐照度、环境温度、湿度、正板温度、风力；控制基于无人机的光伏组件扫描与检测系统，监测上述光伏组件的当前输出电流和当前输出功率。
根据本申请实施例，还提供了一种处理器实施例。可选地，在本实施例中，上述处理器用于运行程序，其中，上述程序运行时执行上述任意一种确定光伏组件的生命周期的方法。
本申请实施例提供了一种电子装置，包括存储器和处理器，所述存储器中存储有计算机程序，所述处理器被设置为运行所述计算机程序以执行上述任意一种的确定光伏组件的生命周期的方法。
本申请还提供了一种计算机程序产品，当在数据处理设备上执行时，适于执行初始化有确定光伏组件的生命周期的确定光伏组件的生命周期的方法步骤的程序。
上述本发明实施例序号仅仅为了描述，不代表实施例的优劣。
在本发明的上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见其他实施例的相关描述。
在本申请所提供的几个实施例中，应该理解到，所揭露的技术内容，可通过其它的方式实现。其中，以上所描述的装置实施例仅仅是示意性的，例如所述单元的划分，可以为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，单元或模块的间接耦合或通信连接，可以是电性或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取非易失性存储介质中。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个非易失性存储介质中，包括若干指令用以使得一台计算机设备(可为个人计算机、服务器或者网络设备等)执行本发明各个实施例所述方法的全部或部分步骤。而前述的非易失性存储介质包括：U盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、移动硬盘、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述仅是本发明的优选实施方式，应当指出，对于本技术领域的普通技术人员来说，在不脱离本发明原理的前提下，还可以做出若干改进和润饰，这些改进和润饰也应视为本发明的保护范围。

Claims (15)

  1. 一种确定光伏组件的生命周期的方法，其特征在于，包括：
    获取光伏组件的历史运行数据；
    监测所述光伏组件的当前环境数据和当前运行数据；
    依据所述当前环境数据、所述历史运行数据和所述当前运行数据，确定所述光伏组件的可使用生命周期。
  2. 根据权利要求1所述的方法，其特征在于，在依据所述当前环境数据、所述历史运行数据和所述当前运行数据，确定所述光伏组件的可使用生命周期之前，所述方法还包括：
    确定所述光伏组件的生命周期衰减指标；
    获取样本环境数据、样本历史运行数据和样本当前运行数据；
    基于所述生命周期衰减指标，依据所述样本环境数据、所述样本历史运行数据和所述样本当前运行数据建立光伏组件衰减模型。
  3. 根据权利要求2所述的方法，其特征在于，依据所述当前环境数据、所述历史运行数据和所述当前运行数据，确定所述光伏组件的可使用生命周期，包括：
    依据所述当前环境数据、所述历史运行数据和所述当前运行数据，确定所述光伏组件衰减模型中对应的所述样本环境数据、所述样本历史运行数据和所述样本当前运行数据；
    基于所述样本环境数据对所述当前环境数据进行分析得到第一分析结果，依据所述样本历史运行数据对所述历史运行数据进行分析得到第二分析结果，以及依据所述样本当前运行数据对所述当前运行数据进行分析得到第三分析结果；
    获取所述第一分析结果、所述第二分析结果和所述第三分析结果中的至少一个分析结果中的所述可使用生命周期。
  4. 根据权利要求2所述的方法，其特征在于，所述生命周期衰减指标包括以下至少之一：光伏组件玻璃划痕指标、透光率指标、背板机械特性指标、电池片隐裂指标、热斑效应和进程控制PID效应指标、随机衰减指标、背板和密封乙烯-醋酸乙烯共聚物EVA胶膜化学变质指标、光伏组件清洁指标。
  5. 根据权利要求1所述的方法，其特征在于，
    获取光伏组件的历史运行数据，包括：获取所述光伏组件的历史输出电流和历史输出功率；
    监测光伏组件的当前环境数据，包括：控制基于无人机的光伏组件扫描与检测系统，采集得到所述当前环境数据，其中，所述当前环境数据包括如下至少之一：光辐照度、环境温度、湿度、正板温度、风力；
    监测所述光伏组件的当前运行数据，包括：控制基于无人机的光伏组件扫描与检测系统，监测所述光伏组件的当前输出电流和当前输出功率。
  6. 根据权利要求1至5中任意一项所述的方法，其特征在于，所述光伏组件为设置在高海拔荒漠地区的光伏组件。
  7. 一种确定光伏组件的生命周期的系统，其特征在于，包括：
    监测器，用于监测所述光伏组件的当前环境数据和当前运行数据；
    处理器，与所述监测器连接，用于获取光伏组件的历史运行数据，并依据所述当前环境数据、所述历史运行数据和所述当前运行数据，确定所述光伏组件的可使用生命周期。
  8. 根据权利要求7所述的系统，其特征在于，所述处理器还用于确定所述光伏组件的生命周期衰减指标；获取样本环境数据、样本历史运行数据和样本当前运行数据；基于所述生命周期衰减指标，依据所述样本环境数据、所述样本历史运行数据和所述样本当前运行数据建立光伏组件衰减模型。
  9. 根据权利要求8所述的系统，其特征在于，所述处理器还用于依据所述当前环境数据、所述历史运行数据和所述当前运行数据，确定所述光伏组件衰减模型中对应的所述样本环境数据、所述样本历史运行数据和所述样本当前运行数据；基于所述样本环境数据对所述当前环境数据进行分析得到第一分析结果，依据所述样本历史运行数据对所述历史运行数据进行分析得到第二分析结果，以及依据所述样本当前运行数据对所述当前运行数据进行分析得到第三分析结果；获取所述第一分析结果、所述第二分析结果和所述第三分析结果中的至少一个分析结果中的所述可使用生命周期。
  10. 根据权利要求8所述的系统，所述系统还包括：
    光伏组件扫描与检测系统，用于采集得到所述当前环境数据和所述当前运行 数据，其中，所述当前环境数据包括如下至少之一：光辐照度、环境温度、湿度、正板温度、风力，所述当前运行数据包括：当前输出电流和当前输出功率。
  11. 根据权利要求7至10中任意一项所述的系统，其特征在于，所述光伏组件为设置在高海拔荒漠地区的光伏组件。
  12. 一种确定光伏组件的生命周期的装置，其特征在于，包括：
    获取模块，用于获取光伏组件的历史运行数据；
    监测模块，用于监测所述光伏组件的当前环境数据和当前运行数据；
    确定模块，用于依据所述当前环境数据、所述历史运行数据和所述当前运行数据，确定所述光伏组件的可使用生命周期。
  13. 一种非易失性存储介质，其特征在于，所述非易失性存储介质存储有多条指令，所述指令适于由处理器加载并执行如权利要求1至6中任意一项的确定光伏组件的生命周期的方法。
  14. 一种处理器，其特征在于，所述处理器用于运行程序，其中，所述程序被设置为运行时执行所述权利要求1至6任一项中所述的确定光伏组件的生命周期的方法。
  15. 一种电子装置，包括存储器和处理器，其特征在于，所述存储器中存储有计算机程序，所述处理器被设置为运行所述计算机程序以执行所述权利要求1至6任一项中所述的确定光伏组件的生命周期的方法。
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