Electronic device, method for controlling electronic device, and program

Abstract

To provide an electronic apparatus which contributes to evaluation of a solar cell module, a control device of the electronic apparatus, and a program.SOLUTION: An electronic apparatus generates fourth information regarding the remaining period supposed that a solar cell moule can output predetermined power in its use environment on the basis of first information representing acetic acid concentration at a predetermined point of time in an encapsulant of the solar cell mole, second information representing the acetic acid concentration in the encapsulant at an expiration point of time of a period in which the solar cell moule can output predetermined power, and third information related to calculation of time variation of the acetic acid concentration in the encapsulant in the use environment of the solar cell module.SELECTED DRAWING: Figure 4

Description

Cross-reference of related applications

[0001] This application claims priority to Japanese Patent Application No. 2023-124710, filed in Japan on 31 July 2023, and the entire disclosure of the earlier application is incorporated herein by reference. [Technical Field]

[0002] This disclosure relates to electronic equipment, methods for controlling electronic equipment, and programs. [Background technology]

[0003] In recent years, research on the degradation of solar cell modules (hereinafter sometimes referred to as "PV modules" or simply "modules," and also generally called "solar panels" or "PV panels") has been progressing. For example, Non-Patent Document 1 discloses the degradation of polymer materials in PV modules operating in high-temperature environments. Also, for example, Patent Document 1 discloses a method for evaluating PV modules that measures water ingress before deterioration occurs in the PV module. Also, for example, Patent Document 2 discloses a management device that predicts the output degradation of PV modules.

[0004] Furthermore, Non-Patent Documents 2 and 3 teach that acetic acid in the encapsulant of a PV module causes corrosion degradation of the electrodes, and that this acetic acid, in turn, contributes to the degradation of the PV module. Patent Document 3 proposes a method for evaluating the lifespan of a PV module by detecting the degree of degradation of the encapsulant through glass. Patent Document 4 proposes a method for predicting the lifespan of a PV module based on the degree of degradation of the encapsulant and the degree of PID (potential induced degradation) in the PV cell. [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] Sarah Kurtz, et al., “Evaluation of High-Temperature Exposure of Rack-Mounted Photovoltaic Modules”, Conference Paper NREL / CP-520-45986, June2009 [Non-Patent Document 2] Jiang Zhu, et al., “Changes of solar cell parameters during damp-heat exposure”, Prog. Photovolt: Res. Appl. 2016, 24,1346-1358 [Non-Patent Document 3] Atsushi Masuda, et al., “Degradation by acetic acid for crystalline Si photovoltaic modules”, Jpn. J. Appl. Phys. 54, 04DR04, 2015 [Patent Documents]

[0006] [Patent Document 1] Japanese Patent Publication No. 2007-165438 [Patent Document 2] Japanese Patent Publication No. 2014-82309 [Patent Document 3] Japanese Patent Publication No. 2017-55657 [Patent Document 4] Japanese Patent Publication No. 2019-146338 [Overview of the project]

[0007] An electronic device according to one embodiment is First information representing the acetic acid concentration in the encapsulant of a solar cell module at a predetermined time point, Second information representing the acetic acid concentration in the encapsulant at the end of the life cycle of the solar cell module, and Based on the third piece of information regarding the acetic acid production reaction in the aforementioned sealing material, A fourth piece of information regarding the risk of deterioration up to the aforementioned lifespan is generated. The third piece of information is information representing the activation energy of the acetic acid production reaction in the sealing material, or information representing the coefficient of the acetic acid production reaction in the sealing material.

[0008] A control method for electronic equipment according to one embodiment is: A step of obtaining first information representing the acetic acid concentration in the encapsulant of a solar cell module at a predetermined time point, A step of obtaining second information representing the acetic acid concentration in the encapsulant at the end of the life cycle of the solar cell module, A step of obtaining third information regarding the acetic acid production reaction in the sealing material, A step of generating a fourth piece of information regarding the risk of deterioration up to the lifespan based on the first piece of information, the second piece of information, and the third piece of information, Includes. The third piece of information is information representing the activation energy of the acetic acid production reaction in the sealing material, or information representing the coefficient of the acetic acid production reaction in the sealing material.

[0009] A program according to one embodiment, for an electronic device, A step of obtaining first information representing the acetic acid concentration in the encapsulant of a solar cell module at a predetermined time point, A step of obtaining second information representing the acetic acid concentration in the encapsulant at the end of the life cycle of the solar cell module, A step of obtaining third information regarding the acetic acid production reaction in the sealing material, A step of generating a fourth piece of information regarding the risk of deterioration up to the lifespan based on the first piece of information, the second piece of information, and the third piece of information, Make it run. The third piece of information is information representing the activation energy of the acetic acid production reaction in the sealing material, or information representing the coefficient of the acetic acid production reaction in the sealing material. [Brief explanation of the drawing]

[0010] [Figure 1] This is a block diagram showing a schematic configuration example of an electronic device according to one embodiment. [Figure 2] This diagram illustrates the degradation of PV modules. [Figure 3] This is a diagram illustrating the structure of a typical PV module. [Figure 4]This figure shows the logic flow of life prediction according to one embodiment. [Figure 5] This figure shows an example of the relationship between pH and acetic acid concentration in the encapsulating material of a PV module. [Figure 6] This figure shows an example of the relationship between the Raman signal intensity ratio and acetic acid concentration in the encapsulating material of a PV module. [Figure 7] This graph shows an example of a measurement performed using laser Raman analysis in addition to Raman spectroscopy. [Figure 8] This figure shows the time course of acetic acid concentration in EVA when a PV module is subjected to high temperature and high humidity testing. [Figure 9] This is a diagram illustrating an acid-catalyzed hydrolysis reaction. [Figure 10] This figure shows an example of the time course of acetic acid concentration in moist heat tests at different temperatures. [Figure 11] This figure shows the results of calculations performed using an electronic device according to one embodiment, along with experimental results. [Figure 12] This figure shows the predicted acetic acid concentration obtained by an electronic device according to one embodiment, and the measured acetic acid concentration of a PV module installed in the field. [Figure 13] This figure shows an example of the correlation between acetic acid concentration and FF characteristics. [Figure 14] This figure shows the lifespan obtained by an electronic device according to one embodiment, along with the actual lifespan of a PV module installed in the field. [Figure 15] This graph shows an example of the correspondence between the Raman signal intensity ratio and acetic acid concentration when UV testing is performed. [Figure 16] This graph shows an example of a Raman spectrum waveform when UVA light degradation occurs due to UV light stress. [Modes for carrying out the invention]

[0011] Predicting the lifespan of PV modules based on their degradation contributes to the evaluation of PV modules. This disclosure relates to electronic equipment, a control method for electronic equipment, and a program that contribute to the evaluation of PV modules. According to one embodiment, electronic equipment, a control method for electronic equipment, and a program that contribute to the evaluation of PV modules can be provided.

[0012] <Electronic equipment> Hereinafter, an electronic device according to one embodiment will be described with reference to the drawings.

[0013] In this disclosure, “electronic device” may mean an electric-powered device. In this disclosure, “user” may mean a person (typically a human) who uses an electronic device and / or a system including such electronic device according to one embodiment. An assumed user of an electronic device according to one embodiment may be, for example, a person who wants to know the expected lifespan of a PV module that constitutes a solar power generation system. A person who wants to know the expected lifespan of a PV module may be, for example, a person in a general household or business who is considering introducing or selling a solar power generation system. A person who wants to know the expected lifespan of a PV module may also be, for example, a person who inspects or evaluates a PV module at an inspection agency. A person who wants to know the expected lifespan of a PV module may also be, for example, a person in an insurance company or financial institution who evaluates the asset value of a PV module. A person who wants to know the expected lifespan of a PV module may also be, for example, a person in a housing manufacturer or homeowner who inspects / replaces / takes safety measures / removes a PV module. An assumed user of an electronic device according to one embodiment may be any person who wants to know the expected lifespan of a PV module. Hereinafter, a person operating an electronic device according to one embodiment (e.g., a consumer, vendor, technician, or inspection technician) will be simply referred to as "user." Being able to reasonably predict the lifespan of a PV module based on its degradation would be beneficial for evaluating the PV module. Here, the evaluation of a PV module may mean, for example, an evaluation of the remaining lifespan / remaining asset value of a (used) PV module.

[0014] An electronic device according to one embodiment typically outputs information regarding the lifespan of a PV module in response to user input. For example, a user can input various information about a PV module whose lifespan they wish to measure into the electronic device according to one embodiment. The electronic device according to one embodiment outputs information regarding the predicted lifespan of the PV module in response to the various information about the PV module input by the user. The information regarding the predicted lifespan of the PV module output by the electronic device according to one embodiment may be, for example, information about a period, such as the number of years until the PV module reaches the end of its lifespan. The information about the period until the end of the PV module's lifespan may be, for example, the period during which the PV module can generate power without a significant decrease in its characteristics (Pm characteristics or FF characteristics described later), that is, the period during which the characteristics of the PV module decrease to a predetermined percentage based on its initial value. The information regarding the predicted lifespan of the PV module output in this way can typically be displayed on a display device or the like. Therefore, the user can know the predicted lifespan of the PV module.

[0015] Furthermore, the electronic device according to one embodiment may generate information regarding the lifespan of a PV module based on predetermined information. Here, the predetermined information may be acquired by the electronic device according to one embodiment, or it may be supplied to the electronic device according to one embodiment from other electronic devices. For example, the electronic device according to one embodiment may acquire various information regarding a PV module whose lifespan is to be measured. In this case, the electronic device according to one embodiment generates information regarding the prediction of the lifespan of the PV module based on the acquired information.

[0016] Figure 1 is a functional block diagram schematically showing the configuration of an electronic device according to one embodiment.

[0017] An electronic device according to one embodiment can be configured, for example, as a dedicated terminal. On the other hand, an electronic device according to one embodiment may be composed of various devices such as a notebook PC (Personal Computer), a desktop PC, a tablet terminal, a smartphone, or a mobile phone. Furthermore, the functions of the electronic device according to one embodiment may be realized as part of the functions of other electronic devices. The functions of the electronic device according to one embodiment can also be realized by executing an application program that performs the processing of the electronic device according to one embodiment in any electronic device equipped with a computer. Furthermore, an electronic device according to one embodiment may be any information processing device, or may include any information processing device. Furthermore, an electronic device according to one embodiment may constitute at least a part of any information processing device.

[0018] As shown in Figure 1, the electronic device 1 according to one embodiment includes a control unit 10, an input unit 20, an output unit 30, a communication unit 40, and a storage unit 50. The electronic device 1 according to one embodiment may not include some of the functional units shown in Figure 1, or it may include functional units other than those shown in Figure 1.

[0019] The control unit 10 controls and manages the entire electronic device 1, including each functional unit that constitutes the electronic device 1. The control unit 10 can be configured to include, for example, a CPU (Central Processing Unit) or a DSP (Digital Signal Processor). In one embodiment, the control unit 10 may be configured as, for example, a CPU (hardware) and a program (software) executed by the CPU. The control unit 10 may appropriately include a storage unit (memory) necessary for the operation of the control unit 10. In one embodiment of the electronic device 1, the control unit 10 may calculate and / or process various information related to predicting the lifespan of the PV module.

[0020] The electronic device 1 may include at least one processor as a control unit 10 to provide control and processing capabilities for performing various functions. According to various embodiments, the at least one processor may be implemented as a single integrated circuit (IC), or as a plurality of communicably connected integrated circuits and / or discrete circuits. The at least one processor can be implemented according to various known techniques.

[0021] In one embodiment, the processor includes one or more circuits or units configured to perform one or more data computation procedures or processes. For example, the processor may perform the functions described below by including one or more processors, controllers, microprocessors, microcontrollers, application-specific integrated circuits (ASICs), digital signal processing devices, programmable logic devices, field-programmable gate arrays, or any combination of these devices or configurations, or other known combinations of devices or configurations.

[0022] The input unit 20 can be any input device used by the user for operation, such as keys (physical keys) like a keyboard, and / or a pointing device like a mouse or trackball. In one embodiment, the input unit 20 can be any known input device, so a more detailed explanation is omitted. In one embodiment, the electronic device 1 may obtain various information necessary for predicting the lifespan of the PV module from the input unit 20.

[0023] The output unit 30 outputs the processing results from the electronic device 1, etc. In one embodiment, the output unit 30 displays, for example, information regarding the predicted lifespan of a PV module as a display. In another embodiment, the output unit 30 may also display characters or symbols, various objects, and / or various images that constitute a screen prompting the user to input predetermined information in order to output the above-mentioned information. The data necessary for display in the output unit 30 is supplied from the control unit 10.

[0024] The output unit 30 may be any display device such as a liquid crystal display (LCD), organic electro-luminescence panel (OLED), or inorganic electro-luminescence panel (IEL). The output unit 30 may display various types of information such as characters, figures, symbols, or graphs. The output unit 30 may also display various GUI objects such as pointers and buttons, as well as icon images, to prompt the user operating the electronic device 1 to take action. The output unit 30 may also be configured to include a backlight, as appropriate.

[0025] Furthermore, the output unit 30 is not necessarily limited to a device that provides a visual effect to the user. The output unit 30 can employ any configuration as long as it can convey information regarding the predicted lifespan of the PV module to the user. For example, the output unit 30 may be replaced with a speaker that conveys information regarding the predicted lifespan of the PV module by voice or other means. Moreover, such a speaker may be installed alongside the output unit 30, such as a display.

[0026] In one embodiment, the output unit 30 may be configured together with the input unit 20 as, for example, a touchscreen display. In this case, the touchscreen display may include a display device such as a liquid crystal display or an organic EL display as the output unit 30. In this case, the touchscreen display may include, for example, a touch sensor or touch panel as the input unit 20 that detects whether or not a user makes contact and the location of such contact. In such a configuration, for example, keys such as a numeric keypad or icons can be displayed as objects on the output unit 30, and the input unit 20 can detect when an operator touches such objects. The input unit 20 can employ various types of touch panels, such as resistive, capacitive, or optical touch panels.

[0027] The communication unit 40 can implement various functions, including wireless communication. The communication unit 40 may implement communication using various communication methods, such as LTE (Long Term Evolution). The communication unit 40 may include a modem whose communication method is standardized by, for example, the ITU-T (International Telecommunication Union Telecommunication Standardization Sector). The communication unit 40 may communicate wirelessly via a network to external devices, such as an external server or cloud server, for example, via an antenna. In one embodiment, the communication unit 40 may receive various information from an external database, such as an external server or cloud server. The various information received by the communication unit 40 in this manner may be stored in the storage unit 50. In one embodiment, the electronic device 1 may receive or acquire various information necessary for predicting the lifespan of the PV module via the communication unit 40.

[0028] The communication unit 40 is not limited to a function unit that performs wireless communication. For example, the communication unit 40 may be configured as an interface for wired connection with external devices using cables or the like.

[0029] The storage unit 50 stores information acquired from the control unit 10 and the communication unit 40, etc. The storage unit 50 also stores programs executed by the control unit 10. In addition, the storage unit 50 stores various data, such as calculation results by the control unit 10. Furthermore, the storage unit 50 may also include work memory for when the control unit 10 is operating, as will be described below. The storage unit 50 can be made of, for example, a semiconductor memory or a magnetic disk, but is not limited to these, and can be any storage device. For example, the storage unit 50 may be an optical storage device such as an optical disk, or a magneto-optical disk, etc. Also, for example, the storage unit 50 may be a storage medium such as a memory card inserted into the electronic device 1 according to this embodiment. Also, the storage unit 50 may be the internal memory of the CPU used as the control unit 10. In one embodiment, the electronic device 1 may store various information necessary for predicting the lifespan of the PV module in the storage unit 50.

[0030] In Figure 1, the input unit 20, output unit 30, communication unit 40, and storage unit 50 may be built into the electronic device 1 or provided outside the electronic device 1.

[0031] In the following description, various calculations and / or processes performed by the electronic device 1 according to one embodiment may be performed by the control unit 10. In the electronic device 1 according to one embodiment, the information necessary for the various calculations and / or processes performed by the control unit 10 may be stored in the storage unit 50, obtained from the input unit 20, or received from the communication unit 40. Furthermore, in the electronic device 1 according to one embodiment, the results of the various calculations and / or processes performed by the control unit 10 may be stored in the storage unit 50, output from the output unit 30, or transmitted to the outside from the communication unit 40.

[0032] For example, in the storage unit 50, the activation energy Ea of the acetic acid generation reaction and the coefficient B0 of the acetic acid generation reaction obtained by calculation may be stored in a database together with the manufacturer, model number, manufacturing date, and other information related to the PV module. Also, in the storage unit 50, the effective stress time Heff per day and the annual effective temperature Teff of the PV module for each installation form obtained by calculation may be stored in a database together with the name of the region. Here, the effective stress time Heff is the effective stress time per day that is a constant value throughout the year, as will be described later. Also, the annual effective temperature Teff is the temperature of the PV module that is a constant value throughout the year, as will be described later. The actual effective stress time per day varies from day to day. Also, the actual temperature of the PV module varies from day to day. However, by using Heff and / or Teff, the calculation of the annual change in acetic acid concentration described later can be facilitated at each stage.

[0033] Next, the operations and / or processes performed by the electronic device 1 according to an embodiment will be described.

[0034] <Deterioration and Lifetime of PV Module> The electronic device 1 according to an embodiment predicts the lifetime of the PV module based on predetermined information related to the PV module. More specifically, the electronic device 1 according to an embodiment generates information indicating the predicted lifetime of the PV module based on predetermined information related to the PV module. The lifetime of the PV module is caused by the deterioration of the PV module. Therefore, the deterioration of the PV module will be described below.

[0035] Several types of degradation are expected in PV modules. Furthermore, several factors are expected to be involved in each type of degradation. In this disclosure, "PV module degradation" refers to the phenomenon in which the power output of a PV module generated by solar power gradually decreases over time and eventually drops sharply. The applicant has found that ultraviolet light (hereinafter also referred to as "UV") and / or moist heat stress are involved as factors in such PV module degradation. Therefore, electronic device 1 according to one embodiment predicts the lifespan of a PV module based on degradation due to UV and / or moist heat.

[0036] Figure 2 illustrates the degradation of a PV module. In Figure 2, the horizontal axis represents time [years], and the vertical axis represents the output of the PV module due to solar power generation. In other words, Figure 2 shows an example of how the output of a typical PV module changes over time. Figure 2 shows how the output of a typical PV module gradually decreases over time, and then eventually decreases rapidly. As shown in Figure 2, in a typical PV module, initial degradation of Di% per year occurs from the start of solar power generation until year M. After that, as shown in Figure 2, a gradual aging degradation of Da% per year occurs in a typical PV module. Furthermore, as shown in Figure 2, a typical PV module undergoes rapid degradation at a certain point (when it reaches the end of its lifespan) as described above. The "rapid decrease" in the output (power generated) of the PV module due to solar power generation corresponds to the "rapid degradation" shown in Figure 2. This rapid degradation is known to be caused by acids generated in the encapsulant of the PV module due to UV and / or humid heat stress.

[0037] In a PV module, the modes of degradation that gradually (slowly) deteriorate over time and the mode that deteriorates rapidly at a certain point are not necessarily the same mode of degradation. In the degradation due to acids generated by UV and humid heat stress dealt with here, there is hardly any degradation that becomes the main component of (slow) aging degradation. Therefore, (slow) aging degradation is assumed to be degradation that occurs mainly due to other degradation modes different from the degradation due to acids caused by UV and humid heat stress. The rapid degradation due to acids generated in the above-mentioned encapsulant is a degradation mode in which the output rapidly decreases at a certain point. This rapid degradation is a degradation that suddenly appears at a certain point, overtaking the (slow) aging degradation due to other degradation modes until then.

[0038] Hereinafter, in order to explain the factors of degradation of the PV module as described above, the structure and degradation sites of the PV module will be described.

[0039] <Structure of PV Module> FIG. 3 is a diagram for explaining the structure of a PV module. FIG. 3 is a diagram showing a cross-section of a PV module. FIG. 3 schematically shows a cross-section of a typical PV module as an example. The PV module shown in FIG. 3 has a thickness in the direction of the Z axis shown in FIG. 3. In the PV module shown in FIG. 3, the positive direction side of the Z axis is also referred to as the "front side", and the negative direction side of the Z axis is also referred to as the "back side". In FIG. 3, the illustration of parts that are not related or weakly related to the degradation of the PV module as described above is appropriately omitted.

[0040] As shown in FIG. 3, the PV module 100 includes a front glass 110, a backsheet 120, and a solar cell 130. The front glass 110 constitutes a light incident surface such as sunlight. The front glass 110 also has a function as a surface protective material. The backsheet 120 has a function as a back protective material. The solar cell 130 is composed of a semiconductor such as silicon (Si). The solar cell 130 absorbs light energy and converts it into electricity.

[0041] The solar cell 130 is sealed between the surface glass 110 and the backsheet 120 by a surface-side sealant 140 and a back-side sealant 150. In many PV modules, the sealants 140 and 150 are made of ethylene vinyl acetate (EVA) copolymer. For the surface glass 110, a material with high light transmittance such as white glass, tempered glass, or heat-reflective glass with a thickness of about 2 mm to 5 mm is used. For the backsheet 120, one or more resins from polypropylene and polyolefin are used, and it may also have an aluminum (Al) sheet between the resins. The backsheet 120 may also be made of glass.

[0042] As shown in Figure 3, the solar cell 130 is provided with electrodes 170 on the front and back sides of a semiconductor substrate made of silicon or the like. The electrodes 170 are formed using a metal such as silver (Ag) or aluminum (Al). Any number of electrodes 170 may be formed on at least one of the front and back sides of the semiconductor substrate. As shown in Figure 3, the electrodes 170 are formed on the semiconductor substrate via contact portions 180. In many PV modules, the contact portions 180 are formed by a thin glass layer. The electrodes 170 and contact portions 180 are generally formed by printing a conductive paste such as silver containing glass frit onto the semiconductor substrate and firing it. The electrodes 170 and contact portions 180 may also be formed using film deposition techniques such as sputtering or plating methods, and the contact portions 180 may be formed from the same material as the electrodes 170. When the contact portions 180 are formed from Al, the contact portions 180 are constructed without a glass layer. In this case, the contact portion 180 is formed with an Al-doped Si layer and an Al-Si alloy layer containing a mixture of Al and Si phases, instead of a glass layer.

[0043] Examples of typical solar cells 130 include BSF (Back Surface Field) cells or PERC (Passivated Emitter and Rear Cell) cells. The BSF cell may be configured to include at least any one of, for example, a front Ag electrode, an AR film, an N-type diffusion layer, a P-type Si substrate, a P+ type BSF layer, a back Al electrode, and a back Ag electrode. Further, the PERC cell may be configured to include at least any one of, for example, a front Ag electrode, an AR film, an N-type diffusion layer, a P-type Si substrate, a passivation film, a back Al electrode, and a back Ag electrode. Here, the passivation film may be an AlOx film or a film formed by laminating an AlOx film and a SiN film.

[0044] <Deterioration sites of PV module> As described above, UV and / or damp heat stress is involved in the deterioration of the PV module 100 shown in FIG. 3. The deterioration in the PV module 100 in which UV and / or damp heat stress is involved is caused by the contact portion (glass layer) 180 formed between the electrode 170 and the semiconductor substrate being corroded by the acid generated in the EVA due to UV and / or damp heat stress. A thin glass layer with a thickness of about 10 to 100 nm is formed in the contact portion 180 between the electrode 170 and the semiconductor substrate. This glass layer has both the functions of electrical and mechanical bonding between the Ag electrode 170 and the Si semiconductor substrate. Also, since the thickness of this glass layer is thin, the electrical connection between the electrode 170 and the semiconductor substrate is not inhibited. Corrosion by acid can occur in either the front or back electrode 170 of the solar cell 130. However, since almost no UV light enters the back side of the solar cell 130, mainly damp heat stress is involved in the back electrode 170 of the solar cell 130. Corrosion by acid as described above can occur in the contact portion 180. Also, such corrosion by acid may occur in the electrode 170.

[0045] The EVA constituting the encapsulating materials 140 and 150 generates acid (mainly acetic acid) under UV and / or humid heat stress. If the glass layer constituting the contact portion 180 is corroded by this acid, for example, the mechanical bonding function of the glass layer is lost. Even if a certain level of mechanical bonding function is maintained, the electrical resistance increases due to the corrosion of the glass layer, and the electrical bonding function deteriorates. When the mechanical and / or electrical bonding function of the contact portion 180 is lost by a predetermined amount, it becomes impossible to extract the photogenerated carriers generated in the Si from the Ag electrode, corresponding to that predetermined amount. In this way, the solar cell characteristics of the PV module 100 deteriorate. The above-described corrosion of the glass layer can occur in the contact portion 180. Furthermore, such corrosion of the glass layer can occur in the contact portion 180 and / or the electrode 170.

[0046] Corrosion of the contact portion 180 can be directly confirmed, for example, by performing cross-sectional SEM observation or EPMA analysis of the contact portion 180. That is, corrosion of the contact portion 180 can be identified by the disappearance of the glass layer of the contact portion 180 (voids between Ag and Si) and / or compositional alteration of the glass layer, corresponding to the degree of corrosion. More simply, the presence and / or degree of corrosion of the glass layer can also be determined by observing the EL image of the PV module. That is, corrosion of the contact portion 180 can be identified by the occurrence of a characteristic EL dark area corresponding to the degree of corrosion and / or expansion of that dark area.

[0047] The power output characteristics of the PV module 100 from solar power generation decrease sharply when UV and / or moist heat stress reaches a certain level. This phenomenon occurs as a result of the rapid corrosion of the contact portion 180 due to the increase in the aforementioned acid. An indicator of when this phenomenon occurs is when the acetic acid concentration (concentration of acetic acid molecules) in the EVA reaches 10 19 pieces / cm 3It can be set as the time point before and after. Here, the concentration of acetic acid molecules means, for example, the number of acetic acid molecules in the unit volume of EVA at 25 °C (298.15 K) and 1 atmosphere. The state where the output characteristics of the electric power generated by the PV module 100 by sunlight generation rapidly decrease may be regarded as the state where the PV module 100 has already reached the end of its life.

[0048] <Prediction of the life of the PV module> Next, the principle of predicting the life based on the deterioration of the PV module due to UV and / or damp heat by the electronic device 1 according to one embodiment will be described. Hereinafter, the prediction of the life based on the deterioration of the PV module due to UV and / or damp heat performed by the electronic device 1 according to one embodiment is also simply referred to as "life prediction" or "life expectancy prediction".

[0049] First, the basic principles for predicting lifespan will be explained. The "lifespan" predicted by the electronic device 1 according to one embodiment may be, for example, the time (period) from when the PV module starts generating power until the UV and / or humid heat stress reaches a predetermined amount and a rapid decrease in the power output characteristics begins. Alternatively, the "lifespan" predicted by the electronic device 1 according to one embodiment may be, for example, the time (period) from when the PV module starts generating power until the UV and / or humid heat stress reaches a predetermined amount and a rapid decrease in the power output characteristics occurs. The "lifespan" predicted by the electronic device 1 according to one embodiment may be, for example, the time (period) from when the PV module starts generating power until the power output characteristics begin to rapidly decrease as described above, and the power output drops from the initial value to a predetermined degradation rate. In these cases, the installation location and / or installation method of the PV module may remain unchanged, and the power generation period may continue. Furthermore, the "lifespan" predicted by the electronic device 1 according to one embodiment may be, for example, the time (period) from when the installation location and / or installation method of the PV module is changed until the UV and / or humid heat stress reaches a predetermined amount and the power output characteristics begin to rapidly decrease. Furthermore, the "lifespan" predicted by the electronic device 1 according to one embodiment may be, for example, the time (period) from when the installation location and / or installation method of the PV module is changed until the UV and / or humid heat stress reaches a predetermined amount and the power output characteristics begin to rapidly decrease.Hereinafter, the "lifespan" predicted by the electronic device 1 according to one embodiment is roughly defined as the point at which the curve factor (hereinafter also referred to as "FF characteristics") or generated power (hereinafter also referred to as "Pm characteristics") decreases by 10% compared to the initial value.Hereinafter, the initial value may refer to the measured value immediately after the completion of the PV module, or the nominal maximum output (rated output) value stated in the catalog or label, etc. However, the principle of predicting the lifespan of the electronic device 1 according to one embodiment may also be adopted even when a sharp decrease in power output characteristics is not observed at the point when the FF characteristics or Pm characteristics decrease by 10% compared to the initial value. In this case, the principle of predicting the lifespan of the electronic device 1 according to one embodiment remains the same even if the lifespan is measured up to the point when the FF characteristics or Pm characteristics decrease by 10%, 20%, or 30% compared to the initial value.Here, the output characteristics of the PV module are measured in accordance with the IEC 60891 standard (or JIS C8914).

[0050] As described above, the "lifespan" predicted by the electronic device 1 according to one embodiment is not necessarily limited to the time (period) assumed when a new PV module starts generating power immediately after completion. For example, it is also possible to consider cases where a used PV module has already been used to generate power for a certain period in the field (market). In such cases, the "lifespan" predicted by the electronic device 1 according to one embodiment may be the time (period) from the point after that certain period as the origin (year zero), until power generation continues and the module reaches the end of its lifespan. The "lifespan" predicted by the electronic device 1 according to one embodiment may be the time (period) from the point in time when the acetic acid concentration of a certain PV module is evaluated until the power output characteristics rapidly decrease. Alternatively, the "lifespan" predicted by the electronic device 1 according to one embodiment may be the time (period) from the point in time when the acetic acid concentration of a certain PV module is evaluated until the power output drops from its initial value to a predetermined degradation rate.

[0051] The applicant has found a method for predicting the lifespan of a PV module based on degradation due to moist heat, using information on the acetic acid concentration in the EVA encapsulant of the PV module, with reasonable accuracy and good precision. The method will now be described. According to one embodiment of the electronic device 1, the lifespan of a PV module based on degradation due to moist heat can be predicted with reasonable accuracy and good precision, using information on the acetic acid concentration in the EVA encapsulant of the PV module.

[0052] The aforementioned Patent Document 4 describes a method for predicting the degradation of PV modules from measurement information using a Raman spectrometer. This method requires Raman spectroscopy measurements to be performed before and after a predetermined time has elapsed, i.e., at multiple different times (multiple times). Therefore, this method requires a considerable amount of time (e.g., years) to obtain information that predicts the remaining lifespan of a PV module. For this reason, such a method is not very practical.

[0053] Furthermore, even if measurements are taken using the above method, for example, by Raman spectroscopy before and after a certain period of time has elapsed, there may be cases where the installation location and / or installation method of the PV module is changed afterward. In such cases, according to the above method, it is necessary to take measurements by Raman spectroscopy before and after a predetermined period of time has elapsed since the installation location and / or installation method of the PV module was changed. For example, it is necessary to take measurements by Raman spectroscopy at the time the installation location and / or installation method of the PV module was changed, and at a time after a certain period of time (e.g., years) has elapsed since the change (i.e., at multiple different time points). For this reason, such a method cannot be said to be highly practical.

[0054] In contrast, the electronic device 1 according to one embodiment can predict the lifespan (e.g., remaining lifespan in years) of the PV module based on degradation due to moist heat by performing measurements using Raman spectroscopy at a single time point in time.

[0055] <Logic flow for lifespan prediction> Figure 4 is a diagram showing the logic flow of life prediction according to one embodiment. Figure 4 schematically shows the logic flow when electronic device 1 according to one embodiment performs life prediction. As shown in Figure 4, electronic device 1 according to one embodiment may perform life prediction based on the following logic flow.

[0056] As shown in step S1 of Figure 4, the control unit 10 of the electronic device 1 acquires information A0 of the acetic acid concentration in the encapsulant (EVA) of the PV module whose lifespan is to be predicted at a predetermined point in time. Here, the predetermined point in time may be, for example, the current time, or the point in time when the lifespan of the PV module is to be predicted. Specifically, the predetermined point in time may be immediately after the PV module is manufactured, or it may be several years after the PV module has been installed in the field. Thus, in one embodiment, whether the PV module is newly manufactured or has been installed in the field for several years, the point in time when the acetic acid concentration information A0 is acquired may be set as time zero (i.e., A0 may be set as the initial value). In this case, the electronic device 1 according to one embodiment can predict the remaining time (a period such as years) from the point in time when the acetic acid concentration is A0 until the PV module reaches the end of its lifespan.

[0057] Three methods for obtaining information A0 about the acetic acid concentration in the encapsulant (EVA) of the PV module in step S1 are described below as examples. The control unit 10 of the electronic device 1 according to one embodiment may perform at least one of the three methods (method A, method B, and method C) described below to obtain information A0 about the acetic acid concentration in the encapsulant (EVA) of the PV module. Three methods are described below as examples, but the method is not limited to these three, and any method can be adopted as long as information about the acetic acid concentration can be obtained directly or indirectly.

[0058] (Method A: Analysis by ion chromatography) In ion chromatography analysis, information on the acetic acid concentration in EVA can be obtained by analyzing EVA recovered from the PV module using a predetermined method and / or conditions. This method requires the recovery of EVA from the PV module and is therefore a destructive analysis.

[0059] In ion chromatography analysis, the concentration of acetic acid (more precisely, acetate ions CH3COO) is usually measured. -The concentration (in [μg / g]) is obtained in units of [μg / g]. To convert the acetic acid concentration in units of [μg / g] to the acetic acid concentration in units of [ / cm3], the following formula (1) can be used. In the following formula (1), the molecular weight of acetic acid is assumed to be 60 g / mol, and Avogadro's constant is 6.022×10 23 is assumed. [ / cm 3 = [μg / g] × 10 -6 × 6.022×10 23 ÷ 60 ≈ [μg / g] × 10 16 (1) In the above formula (1), when a more accurate value is required, considering that the molecular weight of acetate ion (CH3COO - ) is 59 g / mol, 60 in the above formula (1) may be replaced by 59.

[0060] Here, the acetate ion CH3COO - concentration obtained by analysis using ion chromatography is the total concentration of the molecules present as CH3COOH in EVA and the molecules present as ionized CH3COO - . When measuring by ion chromatography, CH3COOH is completely ionized and measured in the form of CH3COO - . That is, it can be considered that the acetate ion CH3COO - concentration obtained by analysis using ion chromatography indicates the total acetic acid concentration (the concentration of acetic acid initially present and the concentration of acetic acid generated by hydrolysis) present in EVA.

[0061] Next, a specific example of the analysis by ion chromatography will be further described. The analysis by ion chromatography described above can be performed, for example, according to the following specific procedure. [A-1] Disassemble the PV module and collect EVA (for example, the EVA may be about 2.5 cm × 6 cm in size, and the one between the tabs near the center of the cell may be collected). [A-2] Put the EVA sample into a bag made of PP (polypropylene) together with ultrapure water and boil it (for example, it may be boiled at 90°C for 2 hours). [A-3] The acetate ions in the boiled solution are quantitatively analyzed using an ion chromatograph.

[0062] In the procedure described above [A-1], the tab (also called an interconnector) is a connecting member that connects adjacent cells in series. In the type of solar cell having electrodes on both sides, the tab connected to the electrode on the front of one solar cell is connected to the electrode on the back of the adjacent solar cell. Two to twelve tabs are connected to one side of the electrode (busbar electrode). The EVA can be collected near the center of the solar cell. However, the EVA between adjacent tabs, rather than the EVA on the tab itself, may be collected from the surface side.

[0063] In the procedure described above [A-2], the PP bag is not limited to being made of PP. For example, the sample may be placed in a designated container, such as a polypropylene bag.

[0064] In the procedure described above [A-3], the ion chromatograph analyzer may be, for example, an ICS-2100 manufactured by DIONEX.

[0065] (Method B: pH analysis) In pH analysis, information on acetic acid concentration can be obtained by analyzing the encapsulant recovered from the PV module using a predetermined method and / or conditions. This method, like ion chromatography analysis, requires the recovery of EVA from the PV module and is therefore a destructive analysis.

[0066] pH information can be converted to acetic acid concentration information, for example, as follows: That is, pH measurements can be performed in advance on multiple encapsulant samples with different acetic acid concentrations, and the correspondence (correlation) between acetic acid concentration (e.g., by ion chromatography) and pH can be obtained. Figure 5 is a graph showing an example of the correspondence between pH and acetic acid concentration. Multiple encapsulant samples with different acetic acid concentrations can be obtained, for example, by immersing a PV module in a high-temperature, high-humidity test and preparing multiple PV modules with different test times.

[0067] Next, we will further explain specific examples of pH analysis. The pH analysis described above can be performed, for example, by following the specific procedure shown below. [B-1] Disassemble the PV module and collect the EVA (for example, the EVA should be about 2.5cm x 2.5cm in size, and can be collected from between the tabs near the center of the cell). [B-2] Cut the EVA sample into 2mm squares and weigh it into a vial. [B-3] Add approximately 10 times the weight of the EVA sample in distilled water to the vial and store in the refrigerator (for example, for 4 days). [B-4] Measure the pH of the solution in the vial using a pH meter.

[0068] In the procedure described above [B-1], the tabs are connecting members that connect adjacent cells in series. In the type of solar cell having electrodes on both sides, the tabs connected to the electrodes on the surface of one solar cell are connected to the electrodes on the back of the adjacent solar cell. Two to twelve tabs are connected to one side of the electrodes (busbar electrodes). The EVA can be collected near the center of the solar cell. However, the EVA between adjacent tabs, rather than the EVA on the tab itself, may be collected from the surface side.

[0069] In the procedure described above [B-4], the stored vial can be removed from the refrigerator and the pH measurement can be performed after the solution has reached room temperature. The pH meter can be, for example, a LAQUA twin AS-pH-22 (manufactured by Horiba, Ltd.). Furthermore, in the procedure described above [B-4], the acetic acid concentration can be obtained from a graph showing the correlation between pH and acetic acid concentration, such as that shown in Figure 5.

[0070] In the above-mentioned methods (Method A: Analysis by Ion Chromatography) and (Method B: pH Analysis), the following points should be noted. First, since the values ​​obtained from EVA samples at the cell ends and EVA samples in the center will differ, it is desirable to collect EVA samples from the same location for comparison. Also, once a PV module is disassembled, components will leach out from the disassembled area in a relatively short time, so it is desirable not to reuse the EVA samples. Furthermore, if there are cracks in the backsheet when a PV module that has been installed in the field is recovered, attention should be paid to the effects of component leaching.

[0071] (Method C: Measurement by Raman spectroscopy) In Raman spectroscopy (Raman measurement), information on acetic acid concentration can be obtained from the signal intensity (Raman signal intensity) of the fluorescence generated by irradiating the encapsulant of the PV module with probe light in a predetermined manner and / or under predetermined conditions. This method does not require the recovery of the encapsulant from the PV module, making it a non-destructive analysis.

[0072] Information from Raman signal intensity can be converted into information from acetic acid concentration, for example, as follows: Raman measurements can be performed in advance on multiple encapsulant samples with different acetic acid concentrations to obtain the correspondence between acetic acid concentration (e.g., by ion chromatography) and Raman signal intensity. Figure 6 is a graph showing an example of the correspondence (correlation) between Raman signal intensity ratio and acetic acid concentration. Multiple encapsulant samples with different acetic acid concentrations can be obtained, for example, by immersing a PV module in a high-temperature, high-humidity test and preparing multiple PV modules with different test times.

[0073] For Raman measurements, handheld (mobile) Raman analyzers that can be used outdoors are available. By using such analyzers, it is not necessary to retrieve the PV modules from their installation sites, and measurements can be taken at the site where the PV modules are installed. For this reason, Raman measurement is an extremely convenient and economical method.

[0074] In Raman measurements, measurements may be obtained at multiple locations within the plane of the PV module. If there is no significant difference in the distribution of Raman signal intensity values, the average value can be used. On the other hand, if there is a significant difference in the distribution of Raman signal intensity, the value with the highest signal intensity can be used. In this case, the time to the lifespan of the PV module (e.g., in years) predicted by the method described below will be the smallest value. This is a desirable method when you want to make a prediction that prioritizes safety regarding the lifespan of the PV module (for example, when you want to avoid overestimating the lifespan even if it can be predicted to be shorter). In addition, the average value and distribution width (2σ or 3σ) can be obtained from the distribution of signal intensity. In this case, the predicted value of the time to the lifespan of the PV module (e.g., in years) predicted by the method described below can also be treated as information with a distribution. That is, the predicted lifespan of the PV module obtained using [average value - distribution width] can be used as a guideline for the lower limit of the lifespan. Also, the predicted lifespan of the PV module obtained using [average value] can be used as a guideline for the average lifespan. Furthermore, the predicted lifespan of a PV module obtained using [mean value + distribution width] can be used as a guideline for the upper limit of its lifespan.

[0075] Next, we will further explain a specific example of Raman measurement, using laser Raman analysis as an example. Figure 7 is a graph showing an example of a measurement performed by laser Raman analysis using Raman spectroscopy. The following is a detailed explanation of Figure 7.

[0076] In Figure 7, the samples subjected to laser Raman analysis were those tested under moist heat conditions of 125°C and 95% humidity. Figure 7 shows the Raman spectra of samples prepared with different moist heat test durations (amount of moist heat stress), each subjected to laser Raman analysis. In the graphs shown in Figure 7, the horizontal axis represents the Raman shift, and the vertical axis represents the Raman signal intensity. Nine samples were analyzed, resulting in nine Raman spectra. The graphs in Figure 7 indicate the corresponding moist heat test duration for each Raman spectrum. Figure 7 shows that the Raman signal intensity increases in response to increasing moist heat test duration. Moist heat stress alters the molecular-level bonding state of the encapsulant. The changes in the Raman spectra (changes in signal intensity) are thought to correspond to these changes in bonding state. Reactions involved in the change of molecular-level bonding state of the encapsulant due to moist heat stress include hydrolysis reactions, which will be discussed later. In the case of EVA as the encapsulant, acetic acid is produced by the hydrolysis reaction, as will be discussed later. Due to these factors, it is believed that a correlation exists between the Raman signal intensity and the acetic acid concentration in the encapsulating material, as shown in Figure 6.

[0077] When performing the above-described Raman spectroscopy measurements using laser Raman analysis, for example, it can be done according to the specific procedure shown below. [C-1] Laser light is transmitted through the glass surface of the PV module, and the Raman signal intensity of the EVA on the front side is measured (for example, the focal point of the laser light may be the interface between the glass and the EVA). [C-2] Prepare a correlation graph in advance between the signal intensity ratio (fluorescence intensity ratio) in Raman measurement and the acetic acid concentration obtained by ion chromatography (here, the signal intensity ratio in Raman measurement is, for example, a Raman shift of 1800-2500 cm⁻¹). -1 The Raman signal intensity excluding peaks within the range is calculated using a Raman shift of 2800 cm. -1The value obtained by dividing the target Raman signal intensity by the maximum intensity due to nearby CH is acceptable. In other words, the target Raman signal intensity can be normalized by a reference Raman signal intensity. Using the signal intensity ratio obtained in this way, a correlation graph between the Raman signal intensity ratio (fluorescence intensity ratio) and acetic acid concentration can be prepared. [C-3] Estimate acetic acid concentration using a correlation graph.

[0078] In the procedure described above [C-1], the excitation laser can be one with a wavelength in the range of approximately 500 to 560 nm. Specifically, the wavelength of the excitation laser may be, for example, 532 nm or 515 nm. The laser Raman spectrometer may be, for example, an HR-800 (manufactured by Horiba, Ltd.).

[0079] In the procedure described above [C-2], the correlation graph to be prepared in advance may be, for example, as shown in Figure 6. Also, Raman shift 2800 cm -1 The maximum CH intensity in the vicinity can be considered as the peak intensity of the methylene group. In the procedure described above [C-2], 1800~2500 cm -1 Within this range, Raman signal intensity other than the peak can be selected at any Raman shift within this range (within this range, the signal intensity will be approximately the same value at any Raman shift). Also, in the procedure [C-2] described above, 1800~2500 cm -1 Within this range, the average signal intensity excluding the peak signal intensity may be used for Raman signal intensities other than the peak. In this case, the Raman signal intensity ratio (fluorescence intensity ratio) is [1800~2500 cm] -1 [Signal strength] / [Raman shift 2800cm] -1 The signal strength in the vicinity may be used.

[0080] The correlation graph used in the above procedure [C-3] may be, for example, one like the one shown in Figure 6. The Raman signal intensity ratio increases as the acetic acid concentration increases. Also, the acetic acid concentration increases as the amount of moist heat stress increases. In Figure 6, the longer the high temperature and high humidity test time, the higher the acetic acid concentration and the larger the Raman signal intensity ratio.

[0081] In the above-mentioned method (Method C: Measurement by Raman spectroscopy), the following points should be noted. First, by fixing the laser focus at the same position (for example, at the interface between glass and EVA), stable measurement results can be obtained. Therefore, it is recommended to adjust the measurement conditions according to the thickness of the surface glass. Also, the Raman signal intensity (fluorescence intensity) is actually increased not only by moist heat but also by the effect of UV (described later). Furthermore, the normalization method is not particularly limited to the method described above, as long as a correspondence with the acetic acid concentration can be established.

[0082] <Preparation for predicting the time course (temporal changes) of acetic acid concentration> Next, as shown in steps S2 to S5 of Figure 4, the control unit 10 of the electronic device 1 prepares various physical quantities (calculates various physical quantities) in order to predict the time change (time progression) of the acetic acid concentration in the encapsulant in the operating environment of the PV module to be subject to life prediction. Specifically, in step S2, the control unit 10 may calculate the coefficient B0 of the acetic acid formation reaction. Also, in step S3, the control unit 10 may calculate the activation energy Ea of the acetic acid formation reaction. Also, in step S4, the control unit 10 may calculate the annual effective temperature Teff of the PV module. Also, in step S5, the control unit 10 may calculate the effective stress time Heff per day. Specifically, the activation energy Ea of the acetic acid formation reaction and the coefficient B0 of the acetic acid formation reaction can be calculated, for example, based on the results of the time progression of acetic acid concentration obtained from moist heat tests at different temperatures. The annual effective temperature Teff and the effective stress time Heff per day of the PV module can be calculated based on the temperature of the PV module measured throughout the year in the operating environment.

[0083] Here, the following is an example of a method for a moist heat test. Specifically, the PV module is exposed to a predetermined atmosphere by placing it in a constant temperature and humidity test chamber set to predetermined temperature and humidity conditions. The temperature range used is 80 to 135°C. The humidity range used is 85 to 95% relative humidity. Thus, the temperature and humidity conditions may be set as appropriate. For example, a moist heat test may be performed under conditions of 85°C and 85% humidity. When measuring acetic acid concentration using (Method A: Analysis by ion chromatography) or (Method B: pH analysis), multiple PV modules of the same specifications are prepared and multiple PV modules are placed in the test chamber. Then, at least one PV module is removed at different predetermined time intervals, and the acetic acid concentration in the encapsulant inside the PV module is measured to obtain the time course of acetic acid concentration. Also, when measuring acetic acid concentration using (Method C: Measurement by Raman spectroscopy), the acetic acid concentration of the PV module is measured after removing the PV module from the test chamber at predetermined time intervals. Then, the PV module is placed back into the test apparatus and exposed to the specified atmosphere. By repeating this process, the time course of acetic acid concentration can be obtained.

[0084] When performing steps S2 to S5, the control unit 10 may acquire installation information of PV modules that are subject to life prediction and are installed in the field or are scheduled to be installed in the field. Specifically, the control unit 10 may acquire information such as the installation area (installation location), installation type (installation configuration), and number of years of installation of the PV modules subject to life prediction. The control unit 10 may prompt the user to input the aforementioned information via the input unit 20, or may acquire the aforementioned information from an external source via the communication unit 40.

[0085] In steps S2 to S5, the control unit 10 may prompt the user to input installation information for the PV module to be used for life prediction. Installation information for the PV module may include, for example, information on the installation area (location of the field where it is installed), information on the installation method (how it is installed in the field), and information on the installation period (the period during which it is installed in the field (e.g., in years)).

[0086] Information about the installation area (location of the field where it is installed) may include, for example, the address or location (latitude, longitude, and / or place name) where the PV module is installed. Based on the information about the installation area, the control unit 10 may obtain temperature information published by the Japan Meteorological Agency or other organizations in the installation area or surrounding areas via the communication unit 40.

[0087] Furthermore, information on the installation method (how it is installed in the field) may include information such as whether the PV module subject to life prediction is installed in the ground, on a corrugated metal roof, or on a residential roof. The temperature of PV modules tends to increase in the order of ground installation, installation on a corrugated metal roof, and installation on a residential roof. This is because the ease of heat dissipation from the back side of the PV module differs depending on the installation method. Ground-mounted PV modules have an open space on the back side, allowing for easy airflow and heat dissipation. Therefore, the temperature of ground-mounted PV modules tends to be relatively low. PV modules on residential roofs have a relatively narrow space on the back side of the module, making heat dissipation difficult. Therefore, the temperature of PV modules on residential roofs tends to be relatively high.

[0088] Furthermore, the information regarding the installation period (the period during which the PV module was installed in the field (e.g., in years)) may refer to the period during which the PV module subject to life prediction was installed in the field (e.g., in years (Y0 [years])).

[0089] In steps S2 to S5, instead of prompting the user to input installation information for the PV module, the control unit 10 may obtain installation information for the PV module from an external device via the communication unit 40 or the like.

[0090] Hereinafter, a calculation formula for predicting the secular change in acetic acid concentration in the encapsulant of a PV module will be described. First, a prediction formula for the time change in acetic acid concentration based on the hydrolysis reaction of the encapsulant (EVA) of the PV module with an acid as a catalyst will be derived, and then a method for handling the time change in acetic acid concentration in the environment of a field where the temperature of the PV module fluctuates will be described.

[0091] <Prediction formula for the time change in acetic acid concentration based on the hydrolysis reaction of EVA with an acid as a catalyst> Acetic acid is known to be produced by the hydrolysis reaction of EVA. FIG. 8 is a graph showing the time change in acetic acid concentration [ / cm 3 in EVA when the PV module is put into a high-temperature and high-humidity test. Here, the acetic acid concentration [ / cm 3 is based on the acetic acid concentration [μg / g] obtained by ion chromatography. As shown in FIG. 8, the acetic acid concentration increases exponentially with the passage of time. This exponential increase suggests that the hydrolysis reaction is a hydrolysis reaction with an acid as a catalyst. That is, the H + (H3O + ) released by the acetic acid itself generated by the reaction shown in FIG. 9 acts as a catalyst, indicating that the hydrolysis reaction of EVA is accelerated.

[0092] Here, the hydrolysis reaction with an acid as a catalyst is described by the reaction formula shown in the following formula (2). EV-A + H2O + n·H3O + → EV-OH + AH + n·H3O + (2)

[0093] In equation (2) above, A represents an acetate group, AH represents acetic acid, and EV-A represents EVA (Ethylene Vinyl Acetate). Also, OH represents an OH group. EV-OH represents a state in which an OH group is bonded in place of the acetate group A in EVA-A. In this case, the differential equation describing the time course of acetic acid concentration [AH] can be expressed as shown in equation (3) below (hereafter, the unit of concentration is [ / cm²). 3 ( ) d[AH] / dt=C·[EV-A]·[H2O]·{1+α·[H3O + ] n (3)

[0094] In this case, 1≪α·[H3O + ] n Therefore, we can consider that the following equation (4) holds true. d[AH] / dt=C·[EV-A]·[H2O]·α·[H3O + ] n (4)

[0095] In equation (4) above, the coefficient C is a parameter related to the rate of the hydrolysis reaction in the absence of acid catalysis. The coefficient α is a parameter that represents the degree of influence when acid catalysis is present. Both of these parameters can be considered experimentally determined values. Alternatively, C·α, obtained by multiplying coefficient C and coefficient α, can be said to be an experimentally determined parameter.

[0096] By the way, the ionization reaction (instantaneous equilibrium) of acetic acid is described by the following equation (5). AH + H2O ⇔ A - + H3O + (5)

[0097] Here, using the equilibrium constant Keq, the equilibrium equation shown in equation (6) below holds. Keq={[A - ]·[H3O + ]} / {[AH]·[H2O]} (6)

[0098] Here, if the presence of molecules that are acidic or alkaline components other than acetic acid within the EVA system in question can be sufficiently ignored, [A - ]≒[H3O + ] can be expressed as follows. Therefore, the following equation (7) holds true. [H3O + ] 2 =Keq·[AH]·[H2O] (7)

[0099] From equations (4) and (7) above, we can derive equation (8). d[AH] / dt=C·[EV-A]·[H2O]·α·{Keq·[AH]·[H2O]} (n / 2) (8)

[0100] Here, we define B as shown in equation (9) below. B=C·[EV-A]·[H2O]·α·{Keq·[H2O]} (n / 2) (9)

[0101] From equations (8) and (9) above, we can derive the following equation (10). d[AH] / dt=B·[AH] (n / 2) (10)

[0102] The solution to equation (10) above is given by equations (11) and (12) below. When n=1: [AH]=(B / 2) 2 ·t 2 (11) When n=2: [AH]=A0·exp(B·t) (12)

[0103] Here, the latter case, n=2 (equation (12)), can explain the experimental fact (the exponential increase in acetic acid concentration). Also, A0 is the acetic acid concentration at t=0, i.e., the initial value. A0 can be obtained by analyzing the EVA of the PV module before it is subjected to high temperature and high humidity testing (for example, by ion chromatography).

[0104] Hereafter, equation (12) will be expressed as equation (13). A(t) = A₀·exp(B·t) (13)

[0105] Here, equation (10) for the case of n=2 is written as equation (14) below. d[AH] / dt=B·[AH] (14) In this case, B is expressed as shown in equation (15) below. B = C·[EV-A]·[H2O] 2 ·α·Keq (15)

[0106] As can be seen from the above, B includes the effect of the water content [H2O] in the EVA. In other words, the acetic acid formation reaction is thought to accelerate as the water content in the EVA increases. This is related to the humidity correction in the remaining life prediction, which will be explained later. However, it should be noted that absolute humidity in the air is not the only factor that determines the water content in the EVA.

[0107] In other words, resin encapsulants have inherent moisture adsorption properties (they have the ability to retain moisture). Therefore, even if the absolute humidity in the air were to decrease by half (decrease rate = 50%), the decrease in moisture concentration in EVA would be considerably smaller than half (decrease rate < 50%).

[0108] Figure 10 is a graph showing an example of the time course of acetic acid concentration in a moist heat test at different temperatures. In Figure 10, the analytical values ​​of acetic acid concentration at each time point are indicated by black circles (●) and white circles (〇). As shown in Figure 10, it can be seen that the rate of acetic acid production is faster at higher temperatures. This temperature dependence is thought to be described by the Arrhenius equation. That is, B in equation (15) above can be rewritten as equation (16). B = B₀·exp(-qEa / kT) (16)

[0109] In equation (16) above, q represents the elementary charge, k represents the Boltzmann constant, T represents the absolute temperature [K], B0 represents the coefficient, and Ea represents the activation energy of the reaction [eV]. Also, qEa means q × Ea, and kT means k × T. B0 and Ea are physical quantities determined experimentally. Furthermore, by comparing equation (16) above with equation (15) above, it can be seen that B0 contains information about the water concentration [H2O] in the EVA.

[0110] From equations (13) and (16) above, we can obtain the following equation (17). A(t)=A0·exp(B0·exp(-qEa / kT)·t) (17)

[0111] Here, B0 and Ea can be uniquely determined so that equation (17) explains the experimental results (i.e., so that equation (17) fits the experimental results). The experimental results used may include information on the humid heat test specimen, including the temperature conditions and test results (acetic acid concentration and test time) of the humid heat test. Alternatively, the experimental results used may include information on the field-installed PV module, including its installation period, temperature (e.g., annual effective temperature), and acetic acid concentration. Furthermore, the experimental results used may be a combination of information on the humid heat test specimen and information on the field-installed specimen. In other words, the experimental results used only need to be based on at least two levels of temperature conditions. For example, these two levels may be two levels for experimental temperature, two levels for the annual effective temperature of the panel in the field (described later), or a combination of one level for experimental temperature and one level for field temperature. Specifically, B0 and Ea can be obtained with the following values. Here, the unit of time t is [h]. B0 ≈ 1.6 × 10 7 Ea ≈ 0.72 eV The above may be considered equivalent to the processes performed in steps S2 and S3 shown in Figure 4.

[0112] In the moist heat test shown in Figure 10, the PV module used as the test sample was one that had not yet been installed in the field after manufacturing (immediately after manufacturing). For this PV module, the acetic acid concentration (initial value A0) when the time at which the moist heat test began is set to zero is A0 ≈ 2 × 10⁻¹⁰. 17 [ / cm 3 The acetic acid concentration immediately after manufacturing (initial value A0) can vary to some extent depending on the type and / or specifications of the PV module (differences in the specifications of the EVA used and / or the process conditions for manufacturing the PV module). If a more accurate value of the acetic acid concentration immediately after manufacturing (initial value A0) is required, the value can be determined by using the method described above, such as Raman measurement, for the PV module before the humid heat test, depending on the type and / or specifications of the PV module. If the exact initial value is unknown, the acetic acid concentration of 2 × 10⁻¹⁰ 17 [ / cm 3 The values ​​before and after can be used as a guideline for A0.

[0113] Figure 11 is a graph showing the results of calculations performed using equation (17) with the above-mentioned values ​​of A0, B0, and Ea, along with the experimental results. In Figure 11, the calculation results are shown by solid and dotted lines. As shown in Figure 11, it can be confirmed that the above-mentioned calculation results accurately reproduce the experimental results. This indicates the validity of the values ​​of B0 and Ea obtained as described above. However, the above-mentioned value of B0 (approximately 1.6 × 10) 7 The values ​​obtained are those obtained under high humidity conditions (relative humidity of approximately 85-95%). In actual field environments (outdoor environments) with humidity conditions (relative humidity ≤ approximately 85%), appropriate corrections may be made as described later.

[0114] The B0 and Ea values ​​mentioned above can be considered as values ​​inherent to EVA. Therefore, for PV modules using EVA as a encapsulant, the above values ​​can be used as guideline values ​​for B0 and Ea. However, these B0 and Ea values ​​may vary slightly depending on the additives added to the EVA and / or the heat treatment conditions of the EVA (conditions in the lamination and / or crosslinking processes). Therefore, if you want to determine B0 and Ea more accurately, you may obtain results from two levels of moist heat tests at the temperatures shown in Figure 10, depending on the type and / or specifications of the PV module (differences in the specifications of the EVA used and / or the process conditions for manufacturing the PV module). In this case, you should determine B0 and Ea that give the calculation formula (17) that best reproduces the test results shown in Figure 11. Here, the initial value A0 of the acetic acid concentration can be determined for the PV module before the moist heat test using the method described above, such as Raman measurement.

[0115] For example, if the target PV module has already been installed in the field for a certain period of time, the above values ​​(B0 ≈ 1.6 × 10) can be used as guideline values ​​for B0 and Ea. 7, (Ea ≒ 0.72 eV) can be used. Also, when more accurate values of B0 and Ea are desired, the necessary number of PV modules installed in the field can be collected, and the results of a two-level damp heat test for the temperatures as shown in FIG. 10 can be obtained. In this case, B0 and Ea that give the calculation formula (17) that can best reproduce the test results as shown in FIG. 11 can be determined. The acetic acid concentration at the time when the PV module has been installed in the field for a certain period (this is taken as the initial value A0) can be determined by the method using Raman measurement etc. described above for the PV module before the damp heat test. Especially when using a handy type (mobile type) Raman measurement device, the acetic acid concentration (initial value A0) of the PV module can be determined while it is installed in the field. The acetic acid concentration (initial value A0) of the PV module at the time when it has been installed in the field for a certain period generally increases in accordance with the environmental stress received in the field with respect to the acetic acid concentration at the time immediately after the PV module is manufactured. Also, the acetic acid concentration (initial value A0) of the PV module at the time when it has been installed in the field for a certain period may vary in the amount of increase with respect to the concentration at the time immediately after manufacture depending on the number of years of field installation and / or installation form etc.

[0116] <Method for dealing with the time change of acetic acid concentration in the environment of a field where the temperature of the PV module fluctuates> Next, a method for predicting the time change of acetic acid concentration under the installation conditions of a field where the temperature of the PV module fluctuates will be described. This may be regarded as corresponding to the processing performed in steps S4 and S5 shown in FIG. 4. Here, a method using the concepts of the annual effective temperature of the PV module (hereinafter, also simply referred to as "annual effective temperature") and the effective stress time per day (hereinafter, also simply referred to as "effective stress time") will be described.

[0117] <When there is temperature information of the PV module> First, the case where the temperature of the PV module is measured throughout the year and is known will be described. In this case, the following formula (18) is constructed. Σ{exp(-qEa / kT)·Δt}=exp(-qEa / kTeff)·365·Heff (18) Here, qEa means q × Ea, and kTeff means k × Teff.

[0118] Equation (18) above allows the time-integrated sum of reaction rates (left-hand side) in a reaction that generally proceeds at a rate proportional to exp(-qEa / kT) to be expressed using Teff and Heff (on the right-hand side). Here, exp(-qEa / kT) can also be interpreted as an indicator of the amount of thermal stress per unit time for a reaction whose activation energy is Ea. Equation (18) above can also be interpreted as allowing the time-integrated sum of thermal stress (left-hand side) to be expressed using Teff and Heff (on the right-hand side). By using Teff and Heff, the calculation of the year-on-year change in acetic acid concentration can be made significantly easier, as will be described later.

[0119] In equation (18) above, Σ represents the cumulative sum over time Δt throughout the year, Δt represents the time of the cumulative step, Teff represents the annual effective temperature of the PV module, and Heff represents the effective stress time per day that can be used throughout the year. The units of T and Teff are absolute temperature [K]. exp(-qEa / kT) and exp(-qEa / kTeff) represent quantities proportional to the amount of thermal stress per unit time. Δt and Heff can be expressed in the same unit of time, for example, minutes [min] or hours [h]. In the example where [h] is used as the unit of time, Δt can be approximately 1 [h] and Heff can be approximately 4.0 [h] ± 0.4 [h].

[0120] Solving equation (18) for Teff yields equation (19). This can be considered to correspond to the process performed in step S4 shown in Figure 4. Teff=(-qEa / k) / ln[Σ{exp(-qEa / kT)·Δt} / (Heff·365)] (19)

[0121] That is, when the PV module temperature T at every time interval Δt throughout the year is known, the annual effective temperature Teff can be calculated by the above formula (19). And by using the annual effective temperature Teff shown in the above formula (19), the annual change in the acetic acid concentration in the EVA of the PV module can be predicted as in the following formula (20). A(Y)=A0·exp(B0·exp(-qEa / kTeff)·Heff·365·Y) (20)

[0122] In the above formula (20), A0 represents the initial acetic acid concentration, Y represents the number of years (unit: [Y]), and A(Y) represents the acetic acid concentration Y years after the time point (zero-year time point) when the acetic acid concentration is A0.

[0123] <When there is no temperature information of the PV module> Next, the case where there is no measurement information on the temperature of the PV module will be described. When there is no measurement information on the temperature of the PV module, an estimated value of the temperature of the PV module is obtained using the air temperature information and the reference value ΔT information for each installation form of the PV module. Here, the reference value ΔT is the temperature difference between the temperature of the PV module during power generation and the air temperature, and is given as follows for each installation form of the PV module. Stand-alone installation: ΔT = 25°C ± 5°C Installation on a corrugated roof: ΔT = 30°C ± 5°C Installation on a residential roof: ΔT = 35°C ± 5°C

[0124] The applicant has confirmed from previous research that the relational expression of the following formula (21) can be constructed. Σ{exp(-qEa / kTmp)·Heff}=exp(-qEa / kTeff)·365·Heff (21)

[0125] In the above formula (21), Σ is the cumulative sum (total sum) for 365 days for each day throughout the year. Also, Tmp represents the maximum temperature of the PV module for each day throughout the year in units of [K], and can be obtained from the following formula (22). Tmp=Tmax+ΔT (22)

[0126] In equation (22) above, Tmax represents the daily maximum temperature throughout the year in units of [K]. If temperature information for the PV module installation location is available from the temperature information published by the Japan Meteorological Agency or other sources, Tmax can be used. If temperature information for the PV module installation location is not available, temperature information for a location close to the PV module installation location can be used.

[0127] Solving equation (21) above for Teff yields equation (23). Teff=(-qEa / k) / ln[Σ{exp(-qEa / kTmp)·Heff} / (Heff·365)] =(-qEa / k) / ln[Σ{exp(-qEa / kTmp)} / 365] (23)

[0128] Using the annual effective temperature Teff shown in equation (23) above, the annual change in acetic acid concentration in the EVA of a PV module can be predicted as shown in equation (24). A(Y)=A0·exp(B0·exp(-qEa / kTeff)·Heff·365·Y) (24)

[0129] <When using monthly average maximum temperatures instead of daily maximum temperatures> In equation (22) above, a similar prediction formula can be obtained by using the monthly average maximum temperature Tmax' instead of the daily maximum temperature Tmax. This method allows for simpler prediction processing without significantly reducing prediction accuracy compared to using the daily maximum temperature Tmax. In this case, a relational equation like the following equation (25) can be constructed. Σ{exp(-qEa / kTmp')·Heff·Day}=exp(-qEa / kTeff)·365·Heff (25)

[0130] In equation (25) above, Σ represents the cumulative sum (total) of each month over the course of the year. Also, Day is set to 31 days for January, March, May, July, August, October, and December, 30 days for April, June, September, and November, and 28 days for February.

[0131] Furthermore, in equation (25) above, Tmp' represents the average maximum temperature of the PV module for each month throughout the year, expressed in units of [K], and is obtained from the following equation (26). Tmp' = Tmax' + ΔT (26)

[0132] In equation (26) above, Tmax' represents the average monthly maximum temperature throughout the year, expressed in units of [K]. If temperature information for the PV module installation location is available from the temperature information published by the Japan Meteorological Agency or other sources, Tmax' can be used. If temperature information for the PV module installation location is not available, temperature information for a location close to the PV module installation location can be used.

[0133] Solving equation (25) above for Teff yields equation (27). Teff=(-qEa / k) / ln[Σ{exp(-qEa / kTmp')·Heff·Day} / (Heff·365)] =(-qEa / k) / ln[Σ{exp(-qEa / kTmp')·Day} / 365] (27)

[0134] Using the annual effective temperature Teff shown in equation (27) above, the annual change in acetic acid concentration in the EVA of a PV module can be predicted as shown in equation (28). A(Y)=A0·exp(B0·exp(-qEa / kTeff)·Heff·365·Y) (28)

[0135] <When using the annual average of the daily maximum temperature> Furthermore, the applicant has confirmed from previous research that the annual effective temperature Teff is related to the following equation (29). Teff≒Tmax annual average +ΔT (29)

[0136] In equation (29) above, the annual average Tmax is the annual average of the daily maximum temperature Tmax. The annual average Tmax may be the average of the daily maximum temperatures obtained for one year in the field, or it may be the average of the monthly averages of the daily maximum temperatures obtained for one year in the field. Using the annual effective temperature Teff shown in equation (29) above, the annual change in acetic acid concentration in the EVA of the PV module can be predicted as shown in equation (30) below. A(Y)=A0·exp(B0·exp(-qEa / kTeff)·Heff·365·Y) (30)

[0137] <Regarding effective stress time> Next, we will explain how to calculate the effective stress time (Heff) per day. This can be considered equivalent to the process performed in step S5 shown in Figure 4. Here, the effective stress time (Heff) per day represents the effective stress time per day that remains constant throughout the year. On the other hand, we can consider the effective stress time per day that varies each day throughout the year, and we will denote this as heff. Below, we will explain heff, and then explain Heff again.

[0138] <Regarding effective stress time (heff) per day> First, let's explain the effective stress time (heff) per day. The heat stress per day can be expressed as shown in equation (31) below. Σexp(-qEa / kT)=exp(-qEa / kTmp)·heff (31) Here, qEa means q × Ea, and kTmp means k × Tmp.

[0139] In equation (31) above, the summation interval on the left side is 24 hours for every 1 hour. Thus, the effective stress time heff per day can be taken as the value obtained by dividing Σexp(-qEa / kT) by exp(-qEa / kTmp). Here, Σexp(-qEa / kT) is the sum of predetermined time units proportional to the daily humid heat stress in the PV module installed in the field. Also, exp(-qEa / kTmp) is a quantity proportional to the humid heat stress per unit time at the maximum temperature of the PV module installed in the field. Furthermore, Tmp and heff are values ​​that can differ from day to day.

[0140] <Regarding Heff, the average effective stress time per day that remains constant throughout the year> Next, we will explain a method that uses a daily effective stress time (Heff) that is constant (general value) throughout the year, instead of a daily effective stress time (heff) that varies from day to day throughout the year. heff and Heff are related as shown in equation (32) below. Σ{exp(-qEa / kTmp)·heff}=exp(-qEa / kTeff)·Heff·365 (32) In equation (32) above, Σ is the cumulative sum (total sum) of each day over 365 days throughout the year.

[0141] From previous research, the applicant has confirmed that Heff = 4.0[h] ± 0.4[h] can be used as a guideline for the effective stress time per day per year Heff that is suitable for general use. More preferably, when the annual average temperature of the maximum temperature Tmax in a day is written as "Tmax annual average", Heff[h] = 0.108 × Tmax annual average [°C] + 1.7 can be used. Even more preferably, Heff[h] = -0.00248 × (Tmax annual average [°C]) 2 It can be calculated as +0.245 × Tmax annual average [°C]. Furthermore, if the module temperature in the field is available, Heff can be defined as the annual median of the effective stress time per day, which varies daily throughout the year.

[0142] Figure 12 shows the predicted acetic acid concentration (indicated by a dashed line) obtained as described above and the measured acetic acid concentration of the PV module installed in the field (indicated by black circles (●)). That is, Figure 12 is a diagram showing the relationship between the number of years since the PV module was installed in the field and the acetic acid concentration in the encapsulant of the PV module. As shown in Figure 12, it can be seen that the two show a relatively good degree of agreement.

[0143] <Acetic acid concentration at the time when the PV module reaches the end of its life> Next, as shown in step S6 of Figure 4, the control unit 10 of the electronic device 1 obtains information A on the acetic acid concentration at the time when the PV module targeted for life prediction reaches the end of its life T (hereinafter also referred to as "acetic acid concentration A at the end of life" T " or "end-of-life acetic acid concentration A" T ").

[0144] When the corrosion of the electrode 170 and / or the contact portion 180 of the PV module by acetic acid progresses, the electrical conduction between the electrode and the semiconductor silicon deteriorates, and the contact resistance between the electrode and the semiconductor increases. When the contact resistance increases, the operation of extracting carriers generated in the semiconductor silicon by the photovoltaic conversion effect to the electrode is inhibited, and the output of the PV module is reduced. It is known that the output of the PV module is determined by three pieces of information: the short-circuit current Isc, the open-circuit voltage Voc, and the fill factor FF. The increase in the contact resistance appears particularly as a decrease in the FF characteristics.

[0145] The applicant investigated the correlation between the acetic acid concentration and the FF characteristics and obtained a correlation as shown in Figure 13. Figure 13 is a graph showing the relationship between the acetic acid concentration and the FF change rate (deterioration rate) for PV modules subjected to a damp heat test (damp heat test samples) and PV modules recovered from the field (market recovery samples).

[0146] As shown in Figure 13, it can be confirmed that the FF characteristics deteriorate rapidly when the acetic acid concentration exceeds a certain level. There are multiple deterioration modes that affect the lifespan of a PV module. Among them, the rapid deterioration of FF characteristics due to electrode corrosion caused by acetic acid (lifespan deterioration due to moist heat stress) is an extremely important deterioration mode that determines the upper limit of the lifespan of a PV module. Here, a 10% deterioration rate of FF characteristics is used as a guideline for the moist heat deterioration lifespan, and the acetic acid concentration at this point is defined as the acetic acid concentration A at the end of its lifespan. T It is noted that the acetic acid concentration A at the end of its lifespan is as follows. T It is reasonable to assume a range of approximately the extent shown in the following equation (33). Lifetime Acetate Concentration A T ≈ 3 × 10 18 ~ 3 × 10 19 [ / cm 3 (33)

[0147] Also, the acetic acid concentration A at the end of its lifespan T This involves conducting a moist heat test on the target PV module until it reaches the end of its lifespan, and collecting information on the acetic acid concentration at the time of reaching the end of its lifespan. T It may be given by measurement.

[0148] Here, the lifespan of the acetic acid concentration A T This can vary depending on the specifications of the PV module. Specifically, the lifetime acetic acid concentration A may vary depending on the specifications of the solar cell electrodes in the PV module (composition, electrode width, electrode thickness, firing conditions, etc.) and / or the specifications of the encapsulant in the PV module (main material, additives, thickness, etc.). T This can be set to an appropriate value. In this case, the lifetime acetic acid concentration A T The upper and lower limits may be set according to the specifications of the PV module, without being limited to the range of formula (33) above. Specifically, for each specification of the PV module, a moist heat test and / or a UV moist heat combined test (for example, a UV moist heat sequential combined test when a moist heat test is performed after a UV test) may be performed. Then, a graph as shown in Figure 13 is created for each specification of the PV module, and the appropriate lifetime acetic acid concentration A is determined. T A new range (to replace the range shown in equation (33)) may be determined.

[0149] <Calculation of the service life years of the PV module> Next, as shown in step S7 of FIG. 4, the control unit 10 of the electronic device 1 calculates the number of years (service life years Y T ) until the service life based on the deterioration of the PV module to be predicted due to damp heat.

[0150] Based on the above, the number of years until the service life based on the deterioration of the PV module due to damp heat (hereinafter, simply referred to as service life years Y T is also denoted) has the following relationship with the acetic acid concentration A at the above-mentioned service life T and the following formula (34). A T = A0·exp(B0·exp(-qEa / kTeff)·Heff·365·Y T ) (34)

[0151] Here, A0 represents the acetic acid concentration in the EVA of the PV module at a predetermined time point. Also, Y T is the number of years until the service life (unit: [Y (year)]) with the time point when the acetic acid concentration in the EVA of the PV module was A0 as the zero time point. Also, B0 can be 1.6×10 7 as in the case of the above formula (17).

[0152] Solving the above formula (34) for Y T yields the following formula (35). Y T = ln(A T / A0) / {B0·exp(-qEa / kTeff)·Heff·365} (35)

[0153] Here, considering that the acetic acid concentration A at the service life can have a distribution width of about 3×10 T ~ 3×10 18 ~ 3×10 19 [ / cm 3 , a distribution width can also be given to the service life years Y T . Specifically, the value of the service life years Y T obtained when the acetic acid concentration A at the service life is 3×10 18 is taken as the value of the service life years Y T ​T can be used as a reference for the lower limit value. Also, the acetic acid concentration A at the end of life T is set to 3×10 19 The value of the service life years Y obtained when T can be used as a reference for the upper limit value of the service life years Y T .

[0154] FIG. 14 is a graph showing the service life years Y obtained by the above formula (35) T plotted together with the actual service life years of PV modules (market-installed products) installed in the field. In FIG. 14, the upper limit of the service life years Y obtained by the above formula (35) is indicated by a dashed-dotted line (predicted remaining life (upper limit)). Also, in FIG. 14, the lower limit of the service life years Y obtained by the above formula (35) is indicated by a broken line (predicted remaining life (lower limit)). Also, in FIG. 14, the market-installed products are indicated by black circles (●). T In FIG. 14, the lower limit of the service life years Y obtained by the above formula (35) is indicated by a broken line (predicted remaining life (lower limit)). Also, in FIG. 14, the market-installed products are indicated by black circles (●). T In FIG. 14, the service life years Y is calculated with the time when the PV module is installed in the field as the zero point of time. Also, in FIG. 14, the acetic acid concentration A at the end of life is set to 3×10

[0155] In FIG. 14, the service life years Y T is calculated with the time when the PV module is installed in the field as the zero point of time. Also, in FIG. 14, the acetic acid concentration A at the end of life T is set to 3×10 18 [ / cm 3 and the lower limit value of the service life years Y T is calculated assuming the acetic acid concentration A at the end of life T is set to 3×10 19 [ / cm 3 and the upper limit value of the service life years Y T are shown. As shown in FIG. 14, the actual service life years of the PV module are sandwiched between the lower limit value and the upper limit value of the predicted service life years, and the validity of the service life years Y calculated by formula (35) can be confirmed. T .

[0156] <Humidity correction and UV correction in life prediction> As described above, the service life years Y T can be obtained. This service life years Y TThis can be considered an estimated lifespan before considering humidity correction (humidity dependence of the lifespan due to moist heat) and UV correction (UV light dependence of the lifespan due to moist heat). If you are evaluating the degradation risk of the target PV module until its approximate future lifespan, the estimated lifespan, as shown in Figure 14, is sufficiently useful information. On the other hand, if you want to determine the lifespan of the target PV module more accurately, you may consider the humidity correction and UV correction described below.

[0157] When humidity correction and UV correction are performed, the control unit 10 of the electronic device 1 may calculate the humidity correction coefficient as shown in step S8 of Figure 4 and the UV correction coefficient as shown in step S9. In this way, the control unit 10 calculates the lifespan Y considering humidity correction and UV correction as shown in step S10. T In other words, it is possible to calculate the lifespan based on degradation due to UV and humid heat in the installed field.

[0158] Here, humidity correction is applied to B0 in equations (34) and (35) above. UV correction is applied to A0 in equations (34) and (35) above. Specifically, if the humidity correction coefficient is denoted as βH and the UV correction coefficient as βU, then equations (34) and (35) above can be expressed as equations (36) and (37) below. A T =(A0·βU)·exp((B0·βH)·exp(-qEa / kTeff)·Heff·365·Y T ) (36) Y T =ln(A T / (A0·βU)) / {(B0·βH)·exp(-qEa / kTeff)·Heff·365} (37)

[0159] In equations (36) and (37) above, the humidity correction coefficient βH can be given in the range of approximately 0.5 to 1, and the UV correction coefficient βU can be given in the range of 1 to approximately 20. The humidity correction coefficient and the UV correction coefficient will be explained further below.

[0160] <Regarding humidity correction factors> The humidity correction coefficient βH is a parameter used to account for the humidity dependence of B0. This parameter is equal to the value of B0 obtained in the high-temperature, high-humidity test described above, which is 1.6 × 10⁻⁶. 7 By multiplying by the humidity correction factor βH, the moisture concentration [H2O] in the EVA under actual field conditions (field humidity conditions) is taken into consideration. As mentioned above, the humidity correction factor βH can be given in the range of approximately 0.5 to 1. As mentioned above, the moisture concentration [H2O] in the EVA is not simply proportional to the humidity of the outside air (atmosphere), but also depends on the moisture retention performance (moisture adsorption performance) of the EVA. For this reason, the moisture concentration [H2O] in the EVA should be determined experimentally. Consequently, the humidity correction factor βH should also be determined experimentally.

[0161] The applicant has confirmed through experiments conducted to date that the lifespan of PV modules based on degradation due to humid heat depends on relative humidity. The applicant has also confirmed that the relative humidity at the temperature of a PV module can be determined by considering information on the relative humidity of the atmosphere in the actual field environment and the temperature information of the PV module installed at that location. Furthermore, the applicant has confirmed that the humid heat lifespan of a PV module in the actual field can be obtained through the following procedure.

[0162] Specifically, first, the Arrhenius equation is applied to the moist heat life of the PV module in the high-temperature, high-humidity test. This allows us to determine the moist heat life under high-humidity conditions at actual field temperatures (the same relative humidity conditions as the high-temperature, high-humidity test). Next, a predetermined humidity correction factor (determined based on relative humidity information at the temperature of the PV module in the actual field environment) is applied to this moist heat life under high-humidity conditions. This allows us to obtain the moist heat life of the PV module in the actual field environment.

[0163] At this time, the applicant derived that a value of around 2 at maximum is appropriate as the humidity correction coefficient in life prediction from the results of the damp heat test with the relative humidity condition as a variable. The humidity correction coefficient in life prediction is in an inverse relationship with βH, which is the correction coefficient of the coefficient B0 of the acetic acid generation reaction. From the above, a value in the range of approximately 0.5 to 1 as described above was obtained as the humidity correction coefficient βH.

[0164] In the PV module installed in the actual field, the value to be specifically adopted within the above range as the humidity correction coefficient βH may be determined by comprehensively judging from the accumulation of predetermined information. Here, the predetermined information may be, for example, the analysis value of the moisture concentration in EVA by recovering the PV module installed in the field. Also, the predetermined information may be the remaining period (life time) until the life obtained by performing an additional damp heat test on the PV module installed in the field. If it is considered that there is insufficient information necessary or sufficient for comprehensive judgment, a value as close to 1 as possible may be adopted as the humidity correction coefficient βH. This corresponds to predicting the life years of the PV module relatively strictly, that is, estimating it to be short. By such prediction, when the user makes a judgment based on the life years of the PV module, a safer choice can be prioritized over a choice including risks caused by predicting the life years of the PV module to be longer. How close the humidity correction coefficient βH is to 1 may be determined based on the risk policy of the entity judging the life years of the PV module. Also, for example, in the southern region of Japan in particular, and in regions with relatively high humidity throughout the year such as Southeast Asia, a value close to 1 can be adopted as the humidity correction coefficient βH.

[0165] <Regarding the UV correction coefficient> The UV correction coefficient βU is a parameter that takes into account the phenomenon of acetic acid generation in the presence of additives in EVA when UV light is present. A typical example of an additive involved in acetic acid generation under UV light stress is the ultraviolet absorber UVA (UV absorber). The UV correction coefficient βU may be determined by considering the UV light transmission characteristics of the glass located on the light incident surface of the PV module, the presence or absence and concentration of additives in the EVA, and the number of years the PV module has been installed. Here, the maximum value of the UV correction coefficient βU can be obtained as follows: First, the acetic acid concentration (e.g., 2 × 10⁻¹⁰) at which the acetic acid concentration generated when a PV module, after manufacturing but before being installed in the field, is subjected to a UV irradiation test has reached approximately saturation. 18 / cm 3 The degree to which this is obtained is 300 kWh / m², based on the conditions under which the UV light has been installed in the field for about 3 years. 2 This is a reasonable value. Next, the acetic acid concentration obtained in this way should be compared to the acetic acid concentration before being subjected to the UV irradiation test (for example, 1-2 × 10⁻⁶). 17 / cm 3 By dividing by (approximately), the maximum value of the UV correction coefficient βU can be obtained. Furthermore, the maximum value of the UV correction coefficient βU is obtained by the acetic acid concentration (e.g., 2 × 10) of a PV module that has been installed in the field for more than 3 years. 18 / cm 3 (approximately) the acetic acid concentration before installation in the field (for example, 1-2 × 10 17 / cm 3 It can also be obtained by dividing by (degree). Therefore, the UV correction coefficient βU can be given in the range of 1 to approximately 20, as described above.

[0166] The following explains how to determine the UV correction coefficient βU in several different cases.

[0167] First, if the glass located on the light incident surface of the PV module is glass that hardly transmits UV light (UV-cut glass), the UV correction coefficient βU can be given a value close to 1. This is because, in the case of UV-cut glass, even if additives such as the UV absorber UVA are blended into the EVA, almost no UV light reaches the EVA, so acetic acid formation caused by the additives involving UV light hardly occurs.

[0168] Next, in the case where the glass located on the light incident surface of the PV module is UV-transmitting glass (UV-through glass) and the installation period is approximately 3 years or longer, the UV correction coefficient βU can be given a value close to 1, regardless of the presence or absence of additives such as UVA. This is because, even if additives such as UVA absorbers are added, the reaction between these additives and UV light that produces acetic acid will almost cease to occur by the time the PV module has been installed for approximately 3 years. Specifically, additives such as UVA absorbers decompose or combine with other molecules due to UV light stress during the approximately 3 years after installation, and their concentration decreases rapidly in inverse proportion to the production of acetic acid.

[0169] Next, if the glass located on the light incident surface of the PV module is UV-through glass, and additives such as the ultraviolet absorber UVA are incorporated into the EVA, and the installation period of the PV module is less than approximately 3 years, the UV correction coefficient βU may be in the range of 1 to approximately 20. For example, the shorter the installation period of the PV module, the closer the UV correction coefficient βU may be to 20, and the closer the installation period is to approximately 3 years, the closer the UV correction coefficient βU may be to 1.

[0170] More specifically, the UV correction coefficient βU may be given according to the amount of additive added. For example, if UVA is added, and the amount of UVA added is U1, and the acetic acid concentration in EVA is A0, then βU may be given by the following equation (38). βU=1~U1 / A0 (38)

[0171] Furthermore, if UVA is not added, and U2 is the acetic acid concentration in EVA when it is nearly saturated in the UV irradiation test, then βU may be given by the following equation (39). βU=1~U2 / A0 (39)

[0172] <When predicting remaining life using Raman measurement information> Next, we will explain how to predict the remaining lifespan of a PV module using Raman measurement information (Raman signal intensity).

[0173] First, let's consider the case where the glass located on the light incident surface of the PV module is glass that hardly transmits UV light (UV-cut glass). In this case, the relationship between the Raman signal intensity ratio and the acetic acid concentration is as shown in Figure 6, and the acetic acid concentration in the EVA can be determined from the Raman signal intensity ratio. This is because, in the case of UV-cut glass, even if additives such as the ultraviolet absorber UVA are mixed into the EVA, almost no UV light reaches the EVA, so acetic acid production due to the additive hardly occurs.

[0174] Next, we will describe the case where the glass located on the light incident surface of the PV module is UV-transmitting glass (UV-through glass). In this case, the relationship between the Raman signal intensity ratio and the acetic acid concentration may differ significantly from the correlation shown in Figure 6. That is, there may be cases where the correlation has a different slope from the correlation shown in Figure 6. Specifically, for example, the correlation shown in Figure 15 may be obtained as the relationship between the Raman signal intensity ratio and the acetic acid concentration. In such cases, a correction factor γ may be introduced so that the acetic acid concentration in the EVA can be correctly determined from the Raman signal intensity ratio. That is, if the correlation shown in Figure 6 is expressed by the following equation (40), the correlation when the slope is significantly different from the correlation in Figure 6 (for example, the correlation shown in Figure 15) can be given by the following equation (41) using γ. log(acetic acid concentration [μg / g]) = C1 × Raman signal intensity ratio + C2 (40) log(acetic acid concentration [μg / g]) = γ·C1 × Raman signal intensity ratio + C2 (41) In equation (40) above, C1 represents the slope of the approximation formula that fits the experimental data in the graph of [log(acetic acid concentration)-Raman signal intensity ratio] shown in Figure 6. Also, C2 in equation (40) above represents the intercept of the approximation formula that fits the experimental data in the graph of [log(acetic acid concentration)-Raman signal intensity ratio] shown in Figure 6. Furthermore, γ in equation (41) above is a correction coefficient that corrects C1, which gives the slope of the approximation formula that fits the experimental data shown in Figure 6 (i.e., the slope is replaced by γ·C1). By introducing the correction coefficient γ, an approximation formula that fits the experimental data can be obtained, for example, as shown in Figure 15. The value of γ can be in the range of 0.2 to 1.0. For example, in the examples of Figure 6 and Figure 15, C1 can be approximately 3.12±0.03, C2 approximately 1.41±0.02, and γ approximately 0.23±0.04.

[0175] When the glass located on the light incident surface of a PV module is UV-transmitting glass (UV-through glass), the absolute value of the Raman signal intensity can be very large, and the Raman signal intensity ratio may take the form shown in Figure 16, for example. This phenomenon is particularly pronounced when the ultraviolet absorber UVA is added. Here, the Raman signal intensity ratio is calculated by setting a predetermined Raman signal intensity to a Raman shift of 2800 cm⁻¹. -1 This is normalized by the Raman signal intensity caused by nearby CHs. Below, we will explain how to determine the remaining lifespan of a PV module when the Raman signal intensity ratio shown in Figure 16 is obtained.

[0176] First, the case where the installation years (Y0 years) of the PV module are about 3 years or more (when about 3 years < Y0 years) will be described. When the installation years of the PV module are about 3 years or more, as described above, the concentration of additives such as the ultraviolet absorber UVA has already significantly decreased. Therefore, the generation of acetic acid caused by these additives can be almost ignored thereafter. Thus, in the PV module with an installation year of about 3 years or more, when the waveform of the Raman spectrum as shown in FIG. 16 is observed, it may be considered that the acetic acid concentration caused by these additives is saturated at about 3 years after installation. That is, when the time point of about 3 years after the installation of the PV module is taken as the reference time (zero year), the acetic acid concentration A T and / or the years until the end of life (remaining life years) Y T can be obtained using Equations (36) and (37). In this case, 1 is used as the value of βU, and 1 to 2×10 18 is used as the reference value of A0 at the reference time. Alternatively, 1 can be used as the value of βU, and the above-mentioned U1 or U2 can be used as the reference value of A0 at the reference time. From the above, the years until the end of life (remaining life years) at the time of Y0 years is Y T +(3 - Y0).

[0177] Next, we will explain the case where the installation period of the PV module (Y0 year) is less than approximately 3 years at that point (Y0 year < approximately 3 years). When the installation period of the PV module is less than approximately 3 years at that point, the concentration of additives such as the ultraviolet absorber UVA has not yet decreased significantly. However, unless there is a particular reason to remove it, the PV module is generally left installed in the same location, and the installation period exceeds approximately 3 years, and is installed for a long period of time. Thus, when it is assumed that the installation period will exceed approximately 3 years in the future, the situation is the same as when the installation period is approximately 3 years or more as described above. That is, for a PV module with an installation period of less than approximately 3 years (Y0 year), if it is expected that a Raman spectrum waveform like the one shown in Figure 16 will be obtained in the future, the remaining lifespan of the PV module may be predicted as follows. That is, taking the point in time when the installation period of the PV module is approximately 3 years as the reference time (year 0), the acetic acid concentration A after that reference time... T and / or the number of years until the end of life Y T This can be calculated using equations (36) and (37). In this case, use 1 as the value of βU, and use 1 to 2 × 10 as the approximate value of A0 at the reference time. 18 You may use this. Alternatively, you may use 1 as the value of βU and use the aforementioned U1 or U2 as the reference value for A0 at the reference time. Therefore, the number of years until the end of life (remaining lifespan) at year Y0 is Y T It is given by +(3-Y0).

[0178] <Relationship between predicted lifespan based on deterioration due to moist heat and actual lifespan> The lifespan (predicted remaining lifespan) of the PV module based on degradation due to moist heat obtained by the procedure described above has the following relationship with the actual lifespan as shown in equation (42). Actual lifespan ≤ Predicted lifespan based on deterioration due to moist heat (42)

[0179] The relationship shown in equation (42) above is because the actual remaining lifespan is influenced not only by environmental stresses such as temperature, humidity, and UV light, but also by all environmental stresses, including temperature cycle stress and / or potential difference stress. Here, potential difference stress is the stress caused by the potential difference between the PV module and the ground potential. Therefore, the lifespan based on degradation due to moist heat obtained by the electronic device 1 according to one embodiment may be understood as giving an upper limit to the actual lifespan. That is, the lifespan based on degradation due to moist heat obtained by the electronic device 1 according to one embodiment is a value that can be obtained with a certain range depending on how the acetic acid concentration at the time of life, humidity correction coefficient, and / or UV correction coefficient are given. However, considering the relationship with the actual lifespan as described above, shorter lifespans may be weighted and considered as predicted values ​​among the lifespans obtained with a range. With such prediction, when a user makes a decision based on the lifespan of the PV module, they can prioritize a safer choice than a choice that includes risks resulting from predicting a longer lifespan for the PV module.

[0180] Furthermore, if we denote the total lifespan of the panels as Ytotal, Ytotal can be expressed as shown in the following equation (43). Ytotal = Installation Years + Remaining Lifespan = Y0 + Y T (43) However, the total lifespan (Ytotal) mentioned here is only meaningful if there is no change in the installation area / installation method before and after the measurement of acetic acid concentration.

[0181] <Effects of the electronic device according to one embodiment> According to one embodiment of the electronic device 1, the remaining lifespan based on subsequent degradation due to moist heat can be predicted based on information representing the acetic acid concentration in the EVA within the PV module. Furthermore, according to one embodiment of the electronic device 1, when the acetic acid concentration is obtained by Raman measurement, the remaining lifespan based on degradation due to moist heat of the target PV module can be predicted based solely on Raman measurement information at a single time point. Moreover, according to one embodiment of the electronic device 1, even when the installation configuration and / or installation location of the PV module is changed, the remaining lifespan based on degradation due to moist heat of the modified PV module can be predicted. In this case, if information on the acetic acid concentration at the time of the change is available (if Raman measurement information at the time of the change is available), the remaining lifespan based on degradation due to moist heat of the modified PV module can be predicted.

[0182] In recent years, a secondary market (buying and selling market) for PV power plants has been emerging. In this market, business schemes offering guaranteed used PV modules have also appeared. In this context, a crucial challenge in trading used PV modules at a fair price is how to assess their current asset value; the technology for this assessment is extremely important. According to one embodiment of the electronic device 1, the remaining lifespan of a used PV module can be rationally assessed. Therefore, the assessment of the asset value of used modules using the electronic device 1 according to one embodiment can become an indispensable technology in such business schemes. According to the electronic device 1 according to one embodiment, information regarding the remaining lifespan of PV modules can be provided as highly reliable information in the secondary market for PV power plants.

[0183] Furthermore, in recent years, the issue of the final disposal (disposal) of existing PV modules for residential use has begun to be recognized. Specifically, the time until disposal of PV modules (remaining lifespan), inspection methods during the period until disposal, and / or the final disposal method are beginning to be recognized as issues. According to the electronic device 1 of one embodiment, the remaining lifespan of existing residential PV modules can be rationally evaluated. Therefore, the evaluation of the remaining lifespan of existing modules by the electronic device 1 of one embodiment can become an indispensable technology for making appropriate judgments regarding such issues. According to the electronic device 1 of one embodiment, information regarding the remaining lifespan of existing residential PV modules (remaining lifespan) can be provided as highly reliable information.

[0184] According to one embodiment of the electronic device 1, the lifespan of a PV module using EVA, a common encapsulant, can be reasonably predicted. On the other hand, for PV modules using EVA with added acid acceptors, for example, the lifespan may be predicted by considering other parameters besides the various parameters mentioned above.

[0185] While this disclosure has been described based on the drawings and embodiments, it should be noted that those skilled in the art will find it easy to make various modifications or alterations based on this disclosure. Therefore, it should be noted that these modifications or alterations are within the scope of this disclosure. For example, the functions included in each functional part can be rearranged in a logically consistent manner. Multiple functional parts may be combined into one or divided. The embodiments relating to this disclosure described above are not limited to being implemented strictly according to the respective embodiments, but can be implemented by combining features or omitting parts as appropriate. In other words, the contents of this disclosure can be modified and altered in various ways based on this disclosure by those skilled in the art. Therefore, these modifications and alterations are within the scope of this disclosure. For example, in each embodiment, each functional part, each means, each step, etc. can be added to other embodiments in a logically consistent manner, or replaced with each functional part, each means, each step, etc. from other embodiments. Also, in each embodiment, multiple functional parts, each means, each step, etc. can be combined into one or divided.

[0186] The embodiments described above are not limited to implementation as electronic devices. For example, the embodiments described above may be implemented as a control method for devices such as electronic devices. Furthermore, for example, the embodiments described above may be implemented as a program executed by a device such as an electronic device or a computer, or as a storage medium or recording medium on which such a program is recorded. [Explanation of Symbols]

[0187] 1 Electronic equipment 10 Control Unit 20 Input section 30 Output section 40 Communications Department 50 Storage section

Claims

1. First information representing the acetic acid concentration in the encapsulant of a solar cell module at a predetermined time point, Second information representing the acetic acid concentration in the encapsulant at the end of the life cycle of the solar cell module, and Based on the third piece of information regarding the acetic acid production reaction in the aforementioned sealing material, An electronic device that generates fourth information regarding the risk of deterioration up to the lifespan, The third information is information representing the activation energy of the acetic acid production reaction in the encapsulating material, or information representing the coefficient of the acetic acid production reaction in the encapsulating material, in an electronic device.

2. The electronic device according to claim 1, wherein the fourth information is information relating to the period until the lifespan, or information relating to the degradation rate until the lifespan.

3. The electronic device according to claim 1, wherein the first information is information obtained without destroying the solar cell module.

4. The electronic device according to claim 1, wherein the first information is information obtained based on measurements performed on the sealing material by Raman spectroscopy.

5. The electronic device according to claim 2, wherein the information relating to the period until the end of life is information relating to the period before the power output by the solar cell module drops sharply.

6. The electronic device according to claim 1, wherein the fourth information is generated based on the first information, the second information, and the third information, and with a correction relating to the humidity to which the solar cell module is exposed.

7. The electronic device according to claim 1, wherein the fourth information is generated based on the first information, the second information, and the third information, and with a correction relating to the ultraviolet light to which the solar cell module is exposed.

8. The electronic device according to claim 1, wherein the third information is generated based on information representing the time change in the acetic acid concentration in the sealing material.

9. A step of obtaining first information representing the acetic acid concentration in the encapsulant of a solar cell module at a predetermined time point, A step of obtaining second information representing the acetic acid concentration in the encapsulant at the end of the lifespan of the solar cell module, A step of obtaining third information regarding the acetic acid production reaction in the sealing material, A step of generating a fourth piece of information regarding the risk of deterioration up to the lifespan based on the first piece of information, the second piece of information, and the third piece of information, A method for controlling electronic equipment, including, A control method wherein the third information is information representing the activation energy of the acetic acid production reaction in the sealing material, or information representing the coefficient of the acetic acid production reaction in the sealing material.

10. In electronic devices, A step of obtaining first information representing the acetic acid concentration in the encapsulant of a solar cell module at a predetermined time point, A step of obtaining second information representing the acetic acid concentration in the encapsulant at the end of the lifespan of the solar cell module, A step of obtaining third information regarding the acetic acid production reaction in the sealing material, A step of generating a fourth piece of information regarding the risk of deterioration up to the lifespan based on the first piece of information, the second piece of information, and the third piece of information, Make it run, The program wherein the third information is information representing the activation energy of the acetic acid production reaction in the sealing material, or information representing the coefficient of the acetic acid production reaction in the sealing material.

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