Electronic device, method for controlling electronic device, and program

Abstract

On the basis of first information indicating an acetic acid concentration in a sealing material of a solar cell module at a predetermined time point, second information indicating an acetic acid concentration in the sealing material at the expiration time of a period in which the solar cell module can output a predetermined power, and third information relating to calculation of a temporal change in the acetic acid concentration in the sealing material in a use environment of the solar cell module, this electronic device generates fourth information relating to the remaining period in which the solar cell module is assumed to be capable of outputting the predetermined power in the use environment thereof.

Description

Electronic device, electronic device control method, and program CROSS-REFERENCE TO RELATED APPLICATIONS

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

[0002] The present disclosure relates to an electronic device, a control method for an electronic device, and a program.

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

[0004] Furthermore, Non-Patent Documents 2 and 3 teach that acetic acid in the sealant of a PV module causes corrosion degradation of electrodes, and that this acetic acid is ultimately involved in 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 sealant of the PV module through glass. Patent Document 4 proposes a method for predicting the lifespan of a PV module based on the degree of degradation of the sealant of the PV module and the degree of occurrence of PID (potential induced degradation) in the PV cells.

[0005] Sarah Kurtz, et al., “Evaluation of High-Temperature Exposure of Rack-Mounted Photovoltaic Modules”, Conference Paper NREL / CP-520-45986, June2009Jiang Zhu, et al., “Changes of solar cell parameters during damp-heat exposure”, Prog. Photovolt: Res. Appl. 2016, 24,1346-1358Atsushi Masuda, et al., “Degradation by acetic acid for crystalline Si photovoltaic modules”, Jpn. J. Appl. Phys. 54, 04DR04, 2015

[0006] JP 2007-165438 A JP 2014-82309 A JP 2017-55657 A JP 2019-146338 A

[0007] An electronic device in one embodiment generates fourth information regarding the remaining period during which the solar cell module is expected to be able to output the specified power in the usage environment based on first information representing the acetic acid concentration in the sealing material of a solar cell module at a specified point in time, second information representing the acetic acid concentration in the sealing material at the end of the period during which the solar cell module is capable of outputting the specified power, and third information related to calculating the change over time in the acetic acid concentration in the sealing material in the usage environment of the solar cell module.

[0008] A method for controlling an electronic device according to one embodiment includes the steps of: acquiring first information representing the acetic acid concentration in the sealing material of a solar cell module at a predetermined time; acquiring second information representing the acetic acid concentration in the sealing material at the end of a period during which the solar cell module is capable of outputting a predetermined amount of power; acquiring third information related to calculating the change over time in the acetic acid concentration in the sealing material in the usage environment of the solar cell module; and generating fourth information relating to the remaining period during which the solar cell module is expected to be capable of outputting the predetermined amount of power in the usage environment based on the first information, the second information, and the third information.

[0009] A program according to one embodiment causes an electronic device to perform the following steps: acquire first information representing the acetic acid concentration in the sealing material of a solar cell module at a predetermined time; acquire second information representing the acetic acid concentration in the sealing material at the end of a period during which the solar cell module can output a predetermined amount of power; acquire third information related to calculating the change over time in the acetic acid concentration in the sealing material in the usage environment of the solar cell module; and generate fourth information relating to the remaining period during which the solar cell module is expected to be able to output the predetermined amount of power in the usage environment based on the first information, the second information, and the third information.

[0010] 1 is a block diagram illustrating an example of a schematic configuration of an electronic device according to an embodiment; FIG. 2 is a diagram illustrating degradation of a PV module; FIG. 3 is a diagram illustrating the structure of a typical PV module; FIG. 4 is a diagram illustrating a logic flow for lifetime prediction according to an embodiment; FIG. 5 is a diagram illustrating an example of a correspondence relationship between pH and acetic acid concentration in an encapsulant of a PV module; FIG. 6 is a diagram illustrating an example of a correspondence relationship between Raman signal intensity ratio and acetic acid concentration in an encapsulant of a PV module; FIG. 7 is a graph illustrating an example of measurement by Raman spectroscopy performed by laser Raman analysis; FIG. 8 is a diagram illustrating the time course of acetic acid concentration in EVA when a PV module is subjected to a high-temperature, high-humidity test; FIG. 9 is a diagram illustrating a hydrolysis reaction catalyzed by acid; FIG. 10 is a diagram illustrating an example of the time course of acetic acid concentration in a moist heat test at different temperatures; FIG. 11 is a diagram illustrating the results of calculations performed by an electronic device according to an embodiment, together with experimental results; FIG. 12 is a diagram illustrating predicted values ​​of acetic acid concentration obtained by an electronic device according to an embodiment, and measured values ​​of acetic acid concentration of a PV module installed in the field; FIG. 13 is a diagram illustrating an example of a correlation between acetic acid concentration and FF characteristics; FIG. 14 is a diagram illustrating the lifespan obtained by an electronic device according to an embodiment, together with the actual lifespan of a PV module installed in the field; FIG. 15 is a graph illustrating an example of the correspondence relationship between Raman signal intensity ratio and acetic acid concentration when a UV test is performed. 1 is a graph showing an example of the waveform of a Raman spectrum when deterioration of an ultraviolet absorber UVA occurs due to UV light stress.

[0011] The present disclosure relates to an electronic device, a control method for an electronic device, and a program that contribute to the evaluation of a PV module. According to one embodiment, an electronic device, a control method for an electronic device, and a program that contribute to the evaluation of a PV module can be provided.

[0012] Electronic Device An electronic device according to an embodiment will be described below with reference to the drawings.

[0013] In the present disclosure, an "electronic device" may refer to a device powered by electricity. Furthermore, in the present disclosure, a "user" may refer to a person (typically a human) who uses an electronic device and / or a system including the electronic device according to an embodiment. An assumed user of an electronic device according to an embodiment may be, for example, a person who wants to know the predicted lifespan of a PV module constituting a solar power generation system. A person who wants to know the predicted lifespan of a PV module may be, for example, a person in an ordinary household or a business who is considering installing or selling a solar power generation system. A person who wants to know the predicted lifespan of a PV module may be, for example, a person who inspects or evaluates PV modules at an inspection institute. A person who wants to know the predicted lifespan of a PV module may be, for example, a person who evaluates the asset value of a PV module at an insurance company or a financial institution. A person who wants to know the predicted lifespan of a PV module may be, for example, a person who inspects, replaces, performs safety procedures, or removes a PV module at a home builder or a homeowner. A potential user of an electronic device according to an embodiment may be anyone who wants to know the predicted lifespan of a PV module. Hereinafter, a person who operates an electronic device according to an embodiment (e.g., a consumer, a trader, an engineer, an inspection technician, etc.) will be referred to simply as a "user." If the lifespan based on the degradation of a PV module can be reasonably predicted, this will contribute to the evaluation of the PV module. Here, evaluation of a PV module may refer to, for example, the evaluation of the remaining lifespan / remaining asset value of a (used) PV module.

[0014] An electronic device according to an embodiment typically outputs information about the lifespan of a PV module in response to input by a user. For example, a user can input various pieces of information about a PV module whose lifespan is to be measured into the electronic device according to an embodiment. The electronic device according to an embodiment outputs information about a predicted lifespan of the PV module in response to various pieces of information about the PV module input by the user. The information about the predicted lifespan of the PV module output by the electronic device according to an embodiment may be, for example, information about the number of years remaining until the end of the lifespan of the PV module. The information about the period until the end of the lifespan of the PV module may be, for example, information about the period during which the PV module characteristics (Pm characteristics or FF characteristics described below) can generate electricity without a significant decrease in the characteristics of the PV module, i.e., the period during which the characteristics of the PV module decrease to a predetermined percentage based on their initial values. The information about the predicted lifespan of the PV module output in this manner can typically be displayed on a display device or the like. This allows the user to know the predicted lifespan of the PV module.

[0015] Furthermore, the electronic device according to an embodiment may generate information related to the lifetime of the PV module based on predetermined information. Here, the predetermined information may be information acquired by the electronic device according to an embodiment, or information supplied to the electronic device according to an embodiment from another electronic device, etc. For example, the electronic device according to an embodiment may acquire various types of information related to the PV module whose lifetime is to be measured. In this case, the electronic device according to an embodiment generates information related to a prediction of the lifetime of the PV module based on the acquired various types of information.

[0016] FIG. 1 is a functional block diagram illustrating a schematic configuration of an electronic device according to an embodiment.

[0017] An electronic device according to an embodiment can be configured as, for example, a dedicated terminal. Meanwhile, an electronic device according to an embodiment can also be configured as 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 an electronic device according to an embodiment can be implemented as part of the functions of another electronic device. The functions of an electronic device according to an embodiment can also be implemented by executing an application program that performs the processing of the electronic device according to an embodiment in an electronic device equipped with a computer. Furthermore, an electronic device according to an embodiment can be any information processing device, or can include any information processing device. Furthermore, an electronic device according to an embodiment can constitute at least a part of any information processing device.

[0018] 1, an electronic device 1 according to an 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 an embodiment may not include some of the functional units shown in FIG. 1, or may include functional units other than the functional units shown in FIG. 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, for example, as a CPU (hardware) and a program (software) executed by the CPU. The control unit 10 may also include a storage unit (memory) necessary for the operation of the control unit 10, as appropriate. In the electronic device 1 according to one embodiment, the control unit 10 may calculate and / or process various information related to the prediction of the lifespan of the PV module.

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

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

[0022] The input unit 20 may be any input device used by a user to perform operations, such as keys (physical keys) like a keyboard and / or a pointing device like a mouse or a trackball. In one embodiment, the input unit 20 may be any known input device, and therefore a detailed description thereof will be omitted. In one embodiment, the electronic device 1 may acquire various information necessary for predicting the lifespan of the PV module from the input unit 20.

[0023] The output unit 30 outputs processing results, etc., by the electronic device 1. In one embodiment, the output unit 30 displays, for example, information related to the prediction of the lifespan of a PV module as, for example, a display. In addition, in one embodiment, the output unit 30 may display characters or symbols, various objects, and / or various images that constitute a screen that prompts the user to input predetermined information, for example, in order to output the above-mentioned information. Data necessary for display on 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), an organic electroluminescence (EL) display (organic electroluminescence) panel, or an inorganic electroluminescence (EL) display (inorganic electroluminescence) panel. The output unit 30 may display various types of information such as characters, figures, symbols, or graphs. The output unit 30 may display various GUI objects such as pointers and buttons, as well as icon images, to prompt the user operating the electronic device 1 to perform an operation. The output unit 30 may also be configured to include a backlight, etc., 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 may have any configuration as long as it can convey information related to the predicted lifespan of the PV module to the user. For example, the output unit 30 may be replaced by a speaker that conveys information related to the predicted lifespan of the PV module by voice or the like. Furthermore, such a speaker may be provided in addition to 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, as the output unit 30, a display device such as a liquid crystal display or an organic EL display. In this case, the touchscreen display may include, as the input unit 20, a touch sensor or a touch panel that detects whether or not a user has touched the object and the position of the touch. In such a configuration, 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 an operator's touch on the object. The input unit 20 can employ various types of touch panels, such as a resistive type, a capacitive type, or an optical type.

[0027] The communication unit 40 can realize various functions including wireless communication. The communication unit 40 may realize communication using various communication methods, such as LTE (Long Term Evolution). The communication unit 40 may include, for example, a modem whose communication method is standardized by the International Telecommunication Union Telecommunication Standardization Sector (ITU-T). The communication unit 40 may wirelessly communicate with an external device, such as an external server or a cloud server, via a network, 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 a 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 functional unit that performs wireless communication. For example, the communication unit 40 may be configured as an interface for connecting to an external device via a cable or the like.

[0029] The storage unit 50 stores information acquired from the control unit 10, the communication unit 40, and the like. The storage unit 50 also stores programs executed by the control unit 10. The storage unit 50 also stores various data, such as calculation results by the control unit 10. The storage unit 50 will be described below as including a work memory used by the control unit 10. The storage unit 50 may be configured, for example, with a semiconductor memory or a magnetic disk, but is not limited thereto, and may 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. Furthermore, 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. The storage unit 50 may also be an 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 FIG. 1, the input unit 20, the output unit 30, the communication unit 40, and the storage unit 50 may each be built into the electronic device 1 or provided externally to the electronic device 1.

[0031] In the following description, various calculations and / or processes performed by the electronic device 1 according to an embodiment may be performed by the control unit 10. In the electronic device 1 according to an embodiment, information required 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 an embodiment, 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, the storage unit 50 may store a database of the calculated activation energy Ea of the acetic acid production reaction and the coefficient B0 of the acetic acid production reaction, along with the manufacturer, model number, date of manufacture, and other information about the PV module. The storage unit 50 may also store a database of the calculated effective daily stress time Heff and the annual effective temperature Teff of the PV module for each installation type, along with the region name. Here, the effective stress time Heff refers to the effective daily stress time that remains constant throughout the year, as described below. The annual effective temperature Teff refers to the temperature of the PV module that remains constant throughout the year, as described below. The actual effective daily stress time varies from day to day. The actual temperature of the PV module also varies from day to day. However, using Heff and / or Teff significantly simplifies the calculation of the annual change in acetic acid concentration, as described below.

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

[0034] <Deterioration and Lifespan of PV Module> The electronic device 1 according to an embodiment predicts the lifespan of a PV module based on predetermined information about the PV module. More specifically, the electronic device 1 according to an embodiment generates information indicating the predicted lifespan of the PV module based on the predetermined information about the PV module. The lifespan of a PV module is caused by deterioration of the PV module. Therefore, the following describes the deterioration of the PV module.

[0035] Degradation of a PV module is expected based on several perspectives. Furthermore, several factors are expected to contribute to each of these perspectives. In this disclosure, "PV module degradation" refers to a phenomenon in which the output of solar power generated by a PV module gradually decreases over time and then suddenly drops. The applicant has discovered that ultraviolet light (hereinafter also referred to as "UV") and / or moist heat stress contribute to such PV module degradation. Therefore, an 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] FIG. 2 is a diagram illustrating the degradation of a PV module. In FIG. 2, the horizontal axis represents time (years), and the vertical axis represents the output power of the PV module due to photovoltaic power generation. That is, FIG. 2 illustrates an example of how the output power of a typical PV module changes over time. FIG. 2 illustrates how the output power of a typical PV module gradually decreases over time and then suddenly decreases. As shown in FIG. 2, a typical PV module experiences initial degradation of Di% per year for M years after the start of photovoltaic power generation. Thereafter, as shown in FIG. 2, a typical PV module experiences gradual aging degradation of Da% per year. Furthermore, as shown in FIG. 2, the typical PV module experiences rapid degradation at a certain point (the end of its life), as described above. The "sudden decrease" in the output power (generated power) due to photovoltaic power generation of the PV module corresponds to the "sudden degradation" shown in FIG. 2. It is known that this rapid degradation is caused by acid generated in the encapsulant of the PV module due to UV and / or moist heat stress.

[0037] In PV modules, the mode of gradual (slow) degradation over time and the mode of sudden degradation at a certain point are not necessarily the same degradation mode. In the degradation caused by acids generated by UV and moist heat stress, which is the subject of this discussion, there is almost no degradation that constitutes the main component of (slow) aging degradation. Therefore, (slow) aging degradation is assumed to be degradation that occurs primarily due to a degradation mode other than acid degradation caused by UV and moist heat stress. The sudden degradation caused by acids generated in the encapsulant described above is a degradation mode in which output suddenly drops at a certain point. This sudden degradation is degradation that suddenly appears at a certain point, overtaking the (slow) aging degradation caused by other degradation modes up to that point.

[0038] In order to explain the causes of the above-mentioned deterioration of the PV module, the structure of the PV module and the deteriorated parts will be described below.

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

[0040] As shown in Figure 3, the PV module 100 includes a front glass 110, a back sheet 120, and a solar cell 130. The front glass 110 forms the incident surface for light such as sunlight. The front glass 110 also functions as a front surface protective material. The back sheet 120 functions as a back surface protective material. The solar cell 130 is made 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 front glass 110 and the backsheet 120 by a front-side sealant 140 and a back-side sealant 150. In many PV modules, the sealant 140 and the sealant 150 are made of an ethylene-vinyl acetate (EVA) copolymer. The front glass 110 is made of a material with high light transmittance, such as white plate glass, tempered glass, or heat-reflecting glass, with a thickness of approximately 2 mm to 5 mm. The backsheet 120 is made of one or more resins selected from polypropylene and polyolefin, and may further include an aluminum (Al) sheet between the resins. The backsheet 120 may also be made of glass.

[0042] As shown in FIG. 3 , the solar cell 130 includes 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 FIG. 3 , the electrodes 170 are formed on the semiconductor substrate via contact portions 180. In many PV modules, the contact portions 180 are formed using a thin glass layer. The electrodes 170 and the contact portions 180 are generally formed by printing a conductive paste containing glass frit, such as silver, on the semiconductor substrate and firing it. The electrodes 170 and the contact portions 180 may be formed using a film formation technique such as sputtering or a plating method, or the contact portions 180 may be formed using the same material as the electrodes 170. When the contact portions 180 are formed using Al, the contact portions 180 are configured without including a glass layer. In this case, the contact portion 180 is formed with an Al-doped Si layer and an Al—Si alloy layer in which an Al phase and a Si phase are mixed, instead of a glass layer.

[0043] Representative examples of the solar cell 130 include a BSF (Back Surface Field) type cell and a PERC (Passivated Emitter and Rear Cell) type cell. A BSF type cell may be configured to include at least one of a front Ag electrode, an AR film, an N-type diffusion layer, a P-type Si substrate, a P+ type BSF layer, a rear Al electrode, and a rear Ag electrode. A PERC type cell may be configured to include at least one of a front Ag electrode, an AR film, an N-type diffusion layer, a P-type Si substrate, a passivation film, a rear Al electrode, and a rear Ag electrode. Here, the passivation film may be an AlOx film, or a film in which an AlOx film and a SiN film are stacked.

[0044] <PV Module Deterioration Areas> As described above, UV and / or moist heat stress contributes to the deterioration of the PV module 100 shown in FIG. 3 . The UV and / or moist heat stress-related deterioration of the PV module 100 is caused by corrosion of the contact portion (glass layer) 180 formed between the electrode 170 and the semiconductor substrate by acid generated in the EVA due to UV and / or moist heat stress. A thin glass layer approximately 10 to 100 nm thick is formed in the contact portion 180 between the electrode 170 and the semiconductor substrate. This glass layer functions as both an electrical and mechanical bond between the Ag electrode 170 and the Si semiconductor substrate. Furthermore, because this glass layer is thin, the electrical connection between the electrode 170 and the semiconductor substrate is not impaired. Acid corrosion can occur on both the front and back electrodes 170 of the solar cell 130. However, since almost no UV light penetrates the back side of the solar cell 130, the electrode 170 on the back side of the solar cell 130 is mainly affected by moist heat stress. The above-mentioned acid corrosion can occur in the contact portion 180. In addition, such acid corrosion can also occur in the electrode 170.

[0045] The EVA constituting the encapsulants 140 and 150 generates acid (primarily acetic acid) under UV and / or moist heat stress. If this acid corrodes the glass layer constituting the contact portion 180, for example, the mechanical bonding function of the glass layer is lost. Even if a certain level of mechanical bonding function is maintained, the corrosion of the glass layer increases electrical resistance, degrading the electrical bonding function. When a certain amount of the mechanical and / or electrical bonding function of the contact portion 180 is lost, the corresponding amount of photogenerated carriers generated in the Si cannot be extracted from the Ag electrode. Thus, the solar cell characteristics of the PV module 100 deteriorate. The corrosion of the glass layer described above 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 confirmed by the disappearance of the glass layer of the contact portion 180 (voids between Ag and Si) corresponding to the degree of corrosion and / or compositional alteration of the glass layer. 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 confirmed by the appearance of characteristic EL dark areas corresponding to the degree of corrosion and / or the expansion of those dark areas.

[0047] The output characteristics of the solar power generated by the PV module 100 rapidly decrease when the stress of UV and / or moist heat reaches a certain level. This is a phenomenon that occurs as a result of the rapid corrosion of the contact part 180 due to the increase in the acid mentioned above. The indicator for the occurrence of this phenomenon is when the acetic acid concentration (concentration of acetic acid molecules) in the EVA reaches 10 １９ pieces / cm ３Here, the concentration of acetic acid molecules means, for example, the number of acetic acid molecules per unit volume of EVA at 25°C (298.15K) and 1 atmosphere. A state in which the output characteristics of power generated by solar power generation of the PV module 100 have suddenly decreased may be considered to be a state in which the PV module 100 has already reached the end of its life.

[0048] <Prediction of Lifespan of PV Module> Next, a principle of predicting the lifespan of a PV module based on degradation due to UV and / or moist heat using the electronic device 1 according to an embodiment will be described. Hereinafter, the prediction of the lifespan of a PV module based on degradation due to UV and / or moist heat performed by the electronic device 1 according to an embodiment will also be simply referred to as "lifespan prediction" or "lifespan prediction."

[0049] First, the basic principles for predicting a lifetime will be described. The "lifetime" predicted by the electronic device 1 according to an embodiment may be, for example, the time (period) from when the PV module starts generating power until a predetermined amount of UV and / or moist heat stress is reached and a rapid decrease in the power output characteristics begins. The "lifetime" predicted by the electronic device 1 according to an embodiment may also be, for example, the time (period) from when the PV module starts generating power until a predetermined amount of UV and / or moist heat stress is reached and a rapid decrease in the power output characteristics begins. The "lifetime" predicted by the electronic device 1 according to an embodiment may also 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 reaches a predetermined degradation rate from the initial value. In these cases, the power generation period may be considered to continue without changing the installation location and / or installation mode of the PV module. Furthermore, the “lifespan” predicted by the electronic device 1 according to an embodiment may be, for example, the time (period) from when the installation location and / or installation mode of the PV module is changed until the UV and / or moist heat stress reaches a predetermined level and the power output characteristics begin to rapidly decrease. The “lifespan” predicted by the electronic device 1 according to an embodiment may be, for example, the time (period) from when the installation location and / or installation mode of the PV module is changed until the UV and / or moist heat stress reaches a predetermined level and the power output characteristics begin to rapidly decrease. Hereinafter, the “lifespan” predicted by the electronic device 1 according to an embodiment is defined as the time until the fill factor (hereinafter also referred to as “FF characteristics”) or the power generation power (hereinafter also referred to as “Pm characteristics”) decreases by 10% compared to its initial value. Here, the initial value may refer to a value measured immediately after the PV module is completed or the nominal maximum output (rated output) value listed in a catalog, label, or the like. However, the principle of lifetime prediction by the electronic device 1 according to an embodiment may be employed even when no sudden decrease in power output characteristics is confirmed at the point when the FF characteristics or Pm characteristics decrease by 10% compared to their initial values. In this case, the principle of lifetime prediction by the electronic device 1 according to an embodiment remains valid even if the point when the FF characteristics or Pm characteristics decrease by 10%, 20%, or 30% compared to their initial values ​​is used as the guideline for lifetime.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 an embodiment is not necessarily limited to the time (period) assumed when a new PV module generates power immediately after completion. For example, it is also possible to consider a case where a used PV module has already generated power in the field (market) for a certain period of time. In such a case, the "lifespan" predicted by the electronic device 1 according to an embodiment may be the time (period) from the point after that certain period of time (year zero) until the end of the lifespan as power generation continues. The "lifespan" predicted by the electronic device 1 according to an embodiment may also be the time (period) from the point at which the acetic acid concentration of a PV module is evaluated until the power output characteristics suddenly decrease. Furthermore, the "lifespan" predicted by the electronic device 1 according to an embodiment may also be the time (period) from the point at which the acetic acid concentration of a PV module is evaluated until the power output reaches a predetermined degradation rate from its initial value.

[0051] The applicant has discovered a method for predicting, with reasonable accuracy, the lifespan of a PV module due to deterioration caused by moist heat, based on information about the acetic acid concentration in the EVA sealing material of the PV module. Hereinafter, such a method will be described. According to an electronic device 1 according to one embodiment, the lifespan of a PV module due to deterioration caused by moist heat can be predicted with reasonable accuracy, based on information about the acetic acid concentration in the EVA sealing material of the PV module.

[0052] The aforementioned Patent Document 4 describes a method for predicting the degradation of a PV module from measurement information obtained using a Raman spectrometer. This method requires Raman spectroscopy measurements 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 for predicting the remaining life of a PV module. For this reason, this method is not very practical.

[0053] Furthermore, even if Raman spectroscopy measurements are performed using the above-described method, for example, before and after a certain amount of time has passed, there may be cases where the installation location and / or installation manner of the PV module is subsequently changed. In such cases, the above-described method requires Raman spectroscopy measurements to be performed before and after a certain amount of time has passed since the change in installation location and / or installation manner of the PV module. For example, Raman spectroscopy measurements must be performed at the time the installation location and / or installation manner of the PV module is changed and at a time a certain amount of time (e.g., years) has passed since the change (i.e., at multiple different time points). For this reason, such a method still has some aspects that make it difficult to say that it is highly practical.

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

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

[0056] As shown in step S1 of FIG. 4 , the control unit 10 of the electronic device 1 acquires information A0 about the acetic acid concentration at a predetermined time in the encapsulant (EVA) of the PV module whose lifetime is to be predicted. Here, the predetermined time may be, for example, the current time, or the time at which the lifetime of the PV module is to be predicted. Specifically, the predetermined time may be immediately after the PV module is manufactured, or may be several years after the PV module is installed in the field. Thus, in one embodiment, whether the PV module is immediately after manufacture or has been installed in the field for several years, the time at which the acetic acid concentration information A0 is acquired may be considered to be time zero (i.e., A0 may be used as an initial value). In this case, the electronic device 1 according to one embodiment can predict the remaining time (e.g., the number of years) until the end of the lifetime of the PV module from the time when the acetic acid concentration is A0.

[0057] In step S1, three methods for acquiring information A0 about the acetic acid concentration in the sealing material (EVA) of the PV module are described as examples. The control unit 10 of the electronic device 1 according to an embodiment may execute at least one of the three methods (method A, method B, and method C) described below to acquire information A0 about the acetic acid concentration in the sealing material (EVA) of the PV module. Although three methods are described below as examples, the method is not limited to these three methods, and any method may be employed as long as it can directly or indirectly acquire information about the acetic acid concentration.

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

[0059] In ion chromatography analysis, the concentration of acetic acid (more precisely, acetate ion CH ３ COO －The concentration of acetic acid is given in μg / g. To convert the μg / g acetic acid concentration to / cm3, the following formula (1) can be used: In the following formula (1), the molecular weight of acetic acid is 60 g / mol, and the Avogadro constant is 6.022 x 10 ２３ [ / cm ３ ]=[μg / g]×10 －６ x 6.022 x 10 ２３ ÷60≒[μg / g]×10 １６ (1) In the above formula (1), if a more accurate value is required, acetate ion (CH ３ COO － ) has a molecular weight of 59 g / mol, so 60 in the above formula (1) may be replaced with 59.

[0060] Here, the acetate ion CH obtained by ion chromatography analysis is ３ COO － The concentration is CH ３ The molecule exists as COOH and the molecule ionizes to CH ３ COO － When measuring by ion chromatography, the total concentration is CH ３ COOH is completely ionized to CH ３ COO － That is, the acetate ion CH obtained by ion chromatography is ３ COO － The concentration can be considered to indicate the total acetic acid concentration present in the EVA (the concentration of acetic acid that was initially present and the concentration of acetic acid produced by hydrolysis).

[0061] Next, a specific example of analysis by ion chromatography will be further described. The above-mentioned analysis by ion chromatography can be carried out, for example, according to the following specific procedure. [A-1] Disassemble the PV module and collect the EVA (for example, EVA measuring about 2.5 cm x 6 cm may be collected between the tabs near the center of the cell). [A-2] Place the EVA sample in a PP (polypropylene) bag together with ultrapure water and boil (for example, boil at 90°C for 2 hours). [A-3] Quantitatively analyze the acetate ions in the boiled solution using an ion chromatography analyzer.

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

[0063] In the above-mentioned procedure [A-2], the PP bag is not particularly limited to one made of PP. As an example, the sample may be placed in a predetermined container, for example, a polypropylene bag.

[0064] In the above-mentioned procedure [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 the acetic acid concentration can be obtained by analyzing the sealant recovered from the PV module using a predetermined method and / or conditions. Similar to the analysis by ion chromatography, this method is also a destructive analysis because it requires the recovery of EVA from the PV module.

[0066] The pH information can be converted into acetic acid concentration information, for example, as follows. That is, pH measurements are performed in advance on multiple encapsulant samples with different acetic acid concentrations, and a correspondence (correlation) between the acetic acid concentration (e.g., by ion chromatography) and the pH is obtained. FIG. 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 subjecting PV modules to a high-temperature, high-humidity test and preparing multiple PV modules with different test times.

[0067] Next, a specific example of pH analysis will be further described. The above-mentioned pH analysis can be performed, for example, according to the following specific procedure. [B-1] Disassemble the PV module and collect the EVA (for example, EVA measuring approximately 2.5 cm x 2.5 cm may be collected between the tabs near the center of the cell). [B-2] Cut the EVA sample into 2 mm squares and weigh it in a vial. [B-3] Add pure water in an amount approximately 10 times the weight of the EVA sample to the vial and store it in a refrigerator (for example, it may be stored for 4 days). [B-4] Measure the solution in the vial with a pH meter.

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

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

[0070] In the above-mentioned (Method A: analysis by ion chromatography) and (Method B: pH analysis), the following points should be noted. First, since the values ​​obtained by measurement differ between EVA samples at the cell edge and EVA samples at the center, it is desirable to collect EVA samples at the same position for comparison. Also, once a PV module is disassembled, components escape from the disassembled area in a relatively short time, so it is desirable not to reuse EVA samples. Furthermore, if cracks are found in the backsheet when a PV module installed in the field is recovered, attention should be paid to the impact of component desorption.

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

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

[0073] For Raman measurements, a handheld (mobile) Raman measuring instrument that can be used outdoors can be used. By using such an instrument, it is not necessary to retrieve the PV module from its installation site, and measurements can be performed at the site where the PV module is installed. For this reason, Raman measurements can be said to be an extremely convenient and economical method.

[0074] In Raman measurements, measurements may be obtained at multiple locations within the surface of the PV module. In this case, 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 until the end of the PV module's life (e.g., years) predicted by the method described below will be the smallest value. This is a desirable method when a safety-oriented prediction of the PV module's life is desired (e.g., when an overestimation is desired even if a shorter lifespan is possible). Furthermore, the mean value and distribution width (2σ or 3σ) can also be obtained from the signal intensity distribution. In this case, the predicted value of the time until the end of the PV module's life (e.g., years) predicted by the method described below can also be treated as information with a distribution. In other words, the predicted value of the PV module's lifespan obtained by using [mean value - distribution width] can be used as a guide for the lower limit of the lifespan. Furthermore, the predicted value of the PV module's lifespan obtained by using [mean value] can be used as a guide for the average lifespan. Furthermore, the predicted value of the lifespan of the PV module obtained by using [average value + distribution width] can be used as a guideline for the upper limit of the lifespan.

[0075] Next, a specific example of Raman measurement will be further described using measurement by laser Raman analysis as an example. Figure 7 is a graph showing an example of measurement by Raman spectroscopy performed by laser Raman analysis. Figure 7 will be described in detail below.

[0076] In Figure 7, the samples subjected to laser Raman analysis were subjected to a moist heat test under conditions of 125°C and 95% humidity. Figure 7 shows the Raman spectra obtained by laser Raman analysis of samples prepared for different moist heat test times (amount of moist heat stress). The horizontal axis of the graph in Figure 7 represents Raman shift, and the vertical axis represents Raman signal intensity. Nine samples were analyzed, resulting in nine Raman spectra. The graph in Figure 7 shows the corresponding moist heat test time for each Raman spectrum. Figure 7 also shows how the Raman signal intensity increases with increasing moist heat test time. Moisture stress changes the molecular-level bonding state of the encapsulant. The change in Raman spectrum (change in signal intensity) is thought to correspond to this change in bonding state. Reactions involved in the change in the molecular-level bonding state of the encapsulant due to moist heat stress include the hydrolysis reaction described below. When the encapsulant is EVA, acetic acid is produced by the hydrolysis reaction, as described below. Due to this background, it is believed that the correlation shown in FIG. 6 occurs between the Raman signal intensity and the acetic acid concentration in the sealing material.

[0077] When the above-mentioned measurement by Raman spectroscopy is performed by laser Raman analysis, it can be performed, for example, according to the specific procedures shown below. [C-1] Laser light is transmitted through the glass surface of the PV module to measure the Raman signal intensity of the EVA on the front side (for example, the focus of the laser light may be the interface between the glass and the EVA). [C-2] A correlation graph between the signal intensity ratio (fluorescence intensity ratio) in the Raman measurement and the acetic acid concentration by ion chromatography analysis is prepared in advance (here, the signal intensity ratio in the Raman measurement is, for example, a Raman shift of 1800 to 2500 cm －１ The Raman signal intensity excluding the peak in the range of the Raman shift 2800 cm －１The Raman signal intensity may be divided by the Raman signal intensity (maximum intensity) caused by nearby CH. In other words, the target Raman signal intensity may be normalized by the 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 the acetic acid concentration can be prepared. [C-3] Estimating the acetic acid concentration using the correlation graph

[0078] In the above-mentioned step [C-1], an excitation laser having a wavelength in the range of about 500 to 560 nm can be used. Specifically, the wavelength of the excitation laser may be, for example, 532 nm or 515 nm. Furthermore, the laser Raman spectrometer may be, for example, an HR-800 (manufactured by Horiba, Ltd.).

[0079] In the above-mentioned procedure [C-2], the correlation graph prepared in advance may be, for example, as shown in FIG. －１ The CH maximum intensity around 1800 to 2500 cm may be taken as the peak intensity of the methylene group. －１ The Raman signal intensity other than the peak may be selected at any Raman shift within this range (within this range, the signal intensity will be approximately the same at any Raman shift). －１ In this range, the Raman signal intensity other than the peak may be the average value of the signal intensity excluding the peak signal intensity within this range. In this case, the Raman signal intensity ratio (fluorescence intensity ratio) is [1800 to 2500 cm －１ signal intensity] / [Raman shift 2800 cm －１ The signal strength in the vicinity may be given as

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

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

[0082] <Preparation for Predicting Time-Varying Changes (Temporal Transitions) in Acetic Acid Concentration> Next, as shown in steps S2 to S5 of FIG. 4 , the control unit 10 of the electronic device 1 prepares various physical quantities (calculates various physical quantities) to predict time-variing changes (temporal transitions) in the acetic acid concentration in the encapsulant in the usage environment of the PV module whose life span is to be predicted. Specifically, in step S2, the control unit 10 may calculate a coefficient B0 of the acetic acid production reaction. Furthermore, in step S3, the control unit 10 may calculate an activation energy Ea of the acetic acid production reaction. Furthermore, in step S4, the control unit 10 may calculate an annual effective temperature Teff of the PV module. Furthermore, in step S5, the control unit 10 may calculate an effective stress time Heff per day. Specifically, the activation energy Ea of the acetic acid production reaction and the coefficient B0 of the acetic acid production reaction can be calculated based on, for example, the results of time-variing changes in the acetic acid concentration in a moist heat test at different temperatures. The effective annual temperature Teff and effective daily stress time Heff of the PV module can be calculated based on the temperature of the PV module measured throughout the year in the environment of use.

[0083] Here, examples of the damp heat test method include the following. Specifically, the PV module is exposed to a predetermined atmosphere by placing it in a thermo-hygrostat 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. In this manner, the temperature and humidity conditions may be set as appropriate. For example, the damp heat test may be performed at a temperature of 85°C and a humidity of 85%. When measuring the acetic acid concentration (Method A: ion chromatography analysis) and (Method B: pH analysis), multiple PV modules with identical specifications are prepared and placed in a test chamber. At least one PV module is then removed at different predetermined intervals and the acetic acid concentration in the encapsulant within the PV module is measured, thereby obtaining the time course of the acetic acid concentration. When measuring the acetic acid concentration (Method C: Raman spectroscopy measurement), the PV module is removed from the test chamber at predetermined intervals and the acetic acid concentration of the PV module is measured. The PV module is then placed in the test chamber again and exposed to the specified atmosphere. By repeating this process, the time transition of the acetic acid concentration can be obtained.

[0084] When performing the operations of steps S2 to S5, the control unit 10 may acquire installation information of the PV module that is the target of the lifespan prediction and that is installed in the field or is 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 mode), and installation years of the PV module that is the target of the lifespan prediction. The control unit 10 may prompt the user to input the above information via the input unit 20, or may acquire the above 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 of the PV module for which the lifespan is to be predicted. The installation information of the PV module may be, for example, information on the installation area (location of the field where the PV module is installed), information on the installation form (how the PV module is installed in the field), and information on the installation period (the period during which the PV module has been installed in the field (e.g., number of years)).

[0086] The information on the installation area (location of the installed field) may be, for example, information such as the address or location (latitude, longitude, and / or place name) where the PV module is installed. Based on the information on the installation area, the control unit 10 may obtain temperature information published by the Japan Meteorological Agency or the like in the installation area or around the installation area via the communication unit 40.

[0087] Furthermore, information on the installation type (how it is installed in the field) may be information such as whether the PV module to be predicted for lifespan is installed in the ground, on a folded-plate roof, or on a residential roof. The temperature of a PV module tends to increase in the following order: ground-mounted, installed on a folded-plate roof, and installed 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 type of the PV module. Ground-mounted PV modules have an open space on the back side of the PV module, allowing for easy wind flow and heat dissipation. Therefore, the temperature of ground-mounted PV modules is relatively low. PV modules on residential roofs have a relatively narrow space on the back side of the module, making it difficult to dissipate heat. Therefore, the temperature of PV modules on residential roofs is relatively high.

[0088] In addition, information on the installation period (the period during which the PV module was installed in the field (e.g., the number of years)) may be information on the period during which the PV module to be predicted for lifespan was installed in the field (e.g., the number of years (Y0 [years])).

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

[0090] Below, we will explain a calculation formula for predicting the temporal change in acetic acid concentration in the encapsulant of a PV module. First, we will derive a prediction formula for the temporal change in acetic acid concentration based on the acid-catalyzed hydrolysis reaction of the encapsulant (EVA) of a PV module, and then we will explain a method for handling the temporal change in acetic acid concentration in a field environment where the temperature of the PV module fluctuates.

[0091] <Prediction formula for time transition of acetic acid concentration based on acid-catalyzed hydrolysis reaction of EVA> Acetic acid is known to be produced by the hydrolysis reaction of EVA. Figure 8 shows the acetic acid concentration [ / cm ３ ] is a graph showing the time course of acetic acid concentration [ / cm ３ ] is based on the acetic acid concentration [μg / g] obtained by ion chromatography. As shown in Figure 8, the acetic acid concentration increases exponentially with time. This exponential increase suggests that the hydrolysis reaction is an acid-catalyzed hydrolysis reaction. In other words, the H released by the acetic acid itself produced by the reaction as shown in Figure 9 ＋ (H ３ O ＋ ) acts as a catalyst to accelerate the hydrolysis reaction of EVA.

[0092] Here, the acid-catalyzed hydrolysis reaction is described by the following reaction formula (2): EV-A + H ２ O + n.H ３ O ＋ → EV-OH + AH + n・H ３ O ＋ (2)

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

[0094] In this case, 1<<α·[H ３ O ＋ ] ｎ Therefore, it can be considered that the following equation (4) holds true: d[AH] / dt=C·[EV−A]·[H ２ O] α [H ３ O ＋ ] ｎ (4)

[0095] In the above formula (4), the coefficient C is a parameter related to the rate of hydrolysis reaction in the absence of acid catalysis. Furthermore, the coefficient α is a parameter representing the degree of influence of acid catalysis. These parameters may all be values ​​determined experimentally. Alternatively, C·α, obtained by multiplying the coefficient C by the coefficient α, can be said to be a parameter determined experimentally.

[0096] The ionization reaction (instantaneous equilibrium) of acetic acid is expressed as the following equation (5): AH + H ２ O ⇔ A － + H ３ O ＋ (5)

[0097] Here, when the equilibrium constant Keq is used, the following equilibrium equation (6) holds: Keq={[A － ]・[H ３ O ＋ ]} / {[AH]・[H ２ O]} (6)

[0098] Here, in the target EVA system, when the presence of molecules that become acid or alkaline components other than acetic acid can be sufficiently ignored, [A － ]≒[H ３ O ＋ ]. Therefore, the following equation (7) holds: [H ３ O ＋ ] ２ =Keq・[AH]・[H２ O] (7)

[0099] From the above formulas (4) and (7), the following formula (8) can be derived: d[AH] / dt=C·[EV−A]·[H ２ O]・α・{Keq・[AH]・[H ２ O]} （ｎ／２） (8)

[0100] Here, B is defined as the following formula (9): B = C * [EV - A] * [H ２ O]・α・{Keq・[H ２ O]} （ｎ／２） (9)

[0101] From the above formulas (8) and (9), the following formula (10) can be derived: d[AH] / dt=B·[AH] （ｎ／２） (10)

[0102] The solutions of the above equation (10) are given by the following equations (11) and (12): When n=1: [AH]=(B / 2) ２ ・t ２ (11) When n = 2: [AH] = A0 exp(B t) (12)

[0103] Here, the experimental fact (exponential increase in acetic acid concentration) can be explained by the latter case where n = 2 (Equation (12)). 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 the high-temperature, high-humidity test (for example, by ion chromatography).

[0104] Hereinafter, equation (12) will be expressed as the following equation (13): A(t)=A0·exp(B·t) (13)

[0105] Here, equation (10) when n=2 is written as equation (14) below. d[AH] / dt=B·[AH] (14) In this case, B is expressed as equation (15) below. B=C·[EV−A]·[H ２ O] ２ ・α・Keq (15)

[0106] As can be seen from the above, B has the same water concentration [H ２ The influence of [O] is included. In other words, it is thought that the acetic acid production reaction accelerates as the moisture concentration in EVA increases. This is related to the humidity correction in remaining life prediction, which will be explained later. However, it should be noted that the absolute humidity of the air is not the only factor that determines the moisture concentration in EVA.

[0107] That is, resin sealing materials have inherent moisture adsorption properties (they have the ability to retain moisture), so even if the absolute humidity in the air were to be reduced by half (a reduction rate of 50%), the reduction in the moisture concentration in the EVA would be significantly smaller than half (a reduction rate of <50%).

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

[0109] In the above formula (16), q represents the elementary charge, k represents the Boltzmann constant, T represents the absolute temperature [K], B0 represents a coefficient, and Ea represents the activation energy of the reaction [eV]. Furthermore, qEa means q×Ea, and kT means k×T. B0 and Ea are physical quantities determined experimentally. Furthermore, by comparing the above formula (16) with the above formula (15), B0 can be calculated as the water concentration in EVA [H ２ O] is included.

[0110] From the above equations (13) and (16), the following equation (17) can be obtained: 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 be information on the hygrothermal test item, including the temperature conditions and test results (acetic acid concentration and test time) of the hygrothermal test. The experimental results used may also be information on the field-installed item, including the installation period, temperature (e.g., the annual effective temperature), and acetic acid concentration of the PV module installed in the field. Furthermore, the experimental results used may be a combination of information on the hygrothermal test item and information on the field-installed item. That is, the experimental results used may be information based on at least two levels of temperature conditions. For example, these two levels may be two levels for the experimental temperature, two levels for the annual effective temperature of the panel in the field (described later), or a combination of one level for the experimental temperature and one level for the field temperature. Specifically, the following values ​​can be obtained for B0 and Ea. Here, the unit of time t is [h]. B0 ≈ 1.6 × 10 ７ The above Ea≈0.72 eV may be regarded as corresponding to the processes performed in steps S2 and S3 shown in FIG.

[0112] In the damp 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 (immediately after manufacture). The acetic acid concentration (initial value A0) of this PV module, when the time when the damp heat test started was set to zero, was A0 ≈ 2 × 10 １７ [ / cm ３ The acetic acid concentration immediately after manufacture (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 process conditions for manufacturing the PV module). If a more accurate value is required for the acetic acid concentration immediately after manufacture (initial value A0), the value can be determined by a method using the Raman measurement described above for the PV module before the moist heat test, depending on the type and / or specifications of the PV module. If the accurate initial value is unknown, the acetic acid concentration of 2 × 10 １７ [ / cm ３] can be used as a guideline for A0.

[0113] FIG. 11 is a graph showing the results of calculations performed by equation (17) using the above values ​​of A0, B0, and Ea, together with the experimental results. In FIG. 11, the calculation results are shown by solid and dotted lines. As shown in FIG. 11, it can be confirmed that the above calculation results reproduce the experimental results with good accuracy. This indicates the validity of the values ​​of B0 and Ea obtained as described above. However, the above value of B0 (approximately 1.6×10 ７ ) are values ​​obtained under high humidity conditions (relative humidity of approximately 85 to 95%). Under humidity conditions in an actual field environment (outdoor environment) (relative humidity ≦ approximately 85%), appropriate corrections may be made as described below.

[0114] The above-mentioned B0 and Ea can basically be considered to be values ​​specific to EVA. Therefore, for PV modules using EVA as an encapsulant, the above-mentioned 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 EVA heat treatment conditions (conditions in the lamination process and / or crosslinking process). Therefore, to obtain more accurate B0 and Ea, results of two levels of damp heat test at temperatures such as those shown in FIG. 10 may be obtained 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, it is sufficient to determine B0 and Ea that give the formula (17) that best reproduces the test results shown in FIG. 11. Here, the initial acetic acid concentration A0 can be determined using a method such as the Raman measurement described above for the PV module before the damp heat test.

[0115] For example, if the target PV module has already been installed in the field for a certain period of time, the above-mentioned values ​​(B0 ≒ 1.6 × 10) are used as the guideline values ​​for B0 and Ea. ７, Ea≒0.72 eV) can be used. Furthermore, if more accurate B0 and Ea are desired, the required number of PV modules installed in the field may be collected and the results of two levels of damp heat test may be obtained for the temperatures shown in FIG. 10 . In this case, B0 and Ea that provide the formula (17) that best reproduces the test results shown in FIG. 11 may be found. The acetic acid concentration (initial value A0) after a certain period of installation in the field can be determined by a method such as the Raman measurement described above for the PV module before the damp heat test. In particular, when a handy (mobile) Raman measurement device is used, 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 after a certain period of installation in the field generally increases in accordance with the environmental stress experienced in the field compared to the acetic acid concentration immediately after the PV module was manufactured. Furthermore, the acetic acid concentration (initial value A0) of a PV module after it has been installed in the field for a certain period of time may increase by a different amount compared to the concentration immediately after manufacture depending on the number of years it has been installed in the field and / or the installation form.

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

[0117] <When PV Module Temperature Information is Available> First, a case will be described in which the temperature of the PV module is measured throughout the year and is known. In this case, the following equation (18) is formed: Σ{exp(-qEa / kT)·Δt}=exp(-qEa / kTeff)·365·Heff (18) Here, qEa means q×Ea, and kTeff means k×Teff.

[0118] The above equation (18) generally allows the time-integrated sum of reaction rates (left-hand side) to be expressed using Teff and Heff (right-hand side) in a reaction proceeding at a rate proportional to exp(-qEa / kT). Here, exp(-qEa / kT) can also be interpreted as an index of the amount of thermal stress per unit time for a reaction whose activation energy is Ea. The above equation (18) can also be interpreted as allowing the time-integrated sum of thermal stress (left-hand side) to be expressed using Teff and Heff (right-hand side). By using Teff and Heff, it is possible to calculate the annual change in acetic acid concentration much more easily, as described below.

[0119] In the above equation (18), Σ represents the cumulative sum (total) for each 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 time unit, for example, minutes [min] or hours [h]. In an example where hours are used as the time unit, Δt = 1 [h] and Heff = approximately 4.0 [h] ± 0.4 [h].

[0120] By solving the above equation (18) for Teff, the following equation (19) can be obtained. This may be considered to correspond to the process performed in step S4 shown in FIG. 4. Teff=(-qEa / k) / ln[Σ{exp(-qEa / kT)·Δt} / (Heff·365)] (19)

[0121] That is, when the PV module temperature T for each time Δt throughout the year is known, the annual effective temperature Teff can be calculated by the above formula (19). Then, 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 shown 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 when the acetic acid concentration is A0 (time of year zero).

[0123] <When PV module temperature information is unavailable> Next, a case where there is no measurement information of the PV module temperature will be described. When there is no measurement information of the PV module temperature, an estimated value of the PV module temperature is obtained using air temperature information and information on the guideline ΔT for each PV module installation type. Here, the guideline ΔT is the temperature difference between the air temperature and the temperature of the PV module when the PV module is generating electricity, and is given for each PV module installation type as follows: Ground installation: ΔT = 25°C ± 5°C Folded plate roof installation: ΔT = 30°C ± 5°C Residential roof installation: ΔT = 35°C ± 5°C

[0124] From the research conducted to date, the applicant has confirmed that the following relational expression (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) for each day of the year for 365 days. Furthermore, Tmp is the maximum temperature of the PV module for each day of the year expressed in [K], and can be obtained from the following formula (22): Tmp = Tmax + ΔT (22)

[0126] In the above formula (22), Tmax is the maximum temperature for each day throughout the year expressed in [K]. If there is temperature information related to the installation location of the PV module among the temperature information published by the Japan Meteorological Agency or the like, this information can be used for Tmax. Furthermore, if there is no temperature information for the installation location of the PV module, temperature information from a location close to the installation location of the PV module can be used.

[0127] By solving the above equation (21) for Teff, the following equation (23) can be obtained: 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 the above formula (23), the annual change in the acetic acid concentration in the EVA of the PV module can be predicted as shown in the following formula (24): A(Y)=A0·exp(B0·exp(−qEa / kTeff)·Heff·365·Y) (24)

[0129] <Using the monthly average maximum temperature instead of the daily maximum temperature> In the above formula (22), 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 prediction processing to be performed more easily without significantly reducing prediction accuracy compared to when the daily maximum temperature Tmax is used. In this case, a relational formula such as the following formula (25) can first be constructed. Σ{exp(-qEa / kTmp') Heff Day}=exp(-qEa / kTeff) 365 Heff (25)

[0130] In the above formula (25), Σ represents the cumulative sum (total) of 12 months throughout the year. 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] In the above formula (25), Tmp' is the average maximum temperature of the PV module for each month throughout the year expressed in [K], and is obtained from the following formula (26): Tmp'=Tmax'+ΔT (26)

[0132] In the above formula (26), Tmax' is the average maximum temperature for each month throughout the year expressed in [K]. If there is temperature information related to the installation location of the PV module among the temperature information published by the Japan Meteorological Agency or the like, this information can be used for Tmax'. Furthermore, if there is no temperature information for the installation location of the PV module, temperature information from a location close to the installation location of the PV module can be used.

[0133] By solving the above equation (25) for Teff, the following equation (27) can be obtained: 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 the above equation (27), the annual change in the acetic acid concentration in the EVA of the PV module can be predicted as shown in the following equation (28): A(Y)=A0·exp(B0·exp(−qEa / kTeff)·Heff·365·Y) (28)

[0135] <When the annual average value of daily maximum temperatures is used> Furthermore, the applicant has confirmed from previous research that the annual effective temperature Teff satisfies the relationship of the following equation (29): Teff ≈ Tmax annual average + ΔT (29)

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

[0137] <Regarding Effective Stress Time> Next, the calculation of the effective stress time Heff per day will be described. This may be considered to correspond to the processing performed in step S5 shown in FIG. 4. Here, the effective stress time Heff per day indicates the effective stress time per day that is constant throughout the year. On the other hand, it is possible to consider an effective stress time per day that differs every day throughout the year, and this will be represented by heff. Below, heff will be explained first, followed by an explanation of Heff.

[0138] <Regarding effective stress time heff per day> First, the effective stress time heff per day will be described. The thermal stress per day can be expressed as in the following equation (31): Σexp(-qEa / kT)=exp(-qEa / kTmp)·heff (31) Here, qEa means q×Ea, and kTmp means k×Tmp.

[0139] In the above equation (31), the summation interval on the left side is 24 hours, with each hour being taken as an hourly interval. Thus, the effective stress time heff per day may be calculated by dividing Σexp(-qEa / kT) by exp(-qEa / kTmp). Here, Σexp(-qEa / kT) is the summation, in units of a predetermined time, of an amount proportional to the stress due to heat and humidity per day in the PV module installed in the field. Furthermore, exp(-qEa / kTmp) is an amount proportional to the stress due to heat and humidity per unit time at the highest temperature of the PV module installed in the field. Furthermore, Tmp and heff are values ​​that may vary from day to day.

[0140] <Regarding the effective stress time Heff per day that is a constant value throughout the year> Next, a method will be described in which the effective stress time Heff per day that is a constant value throughout the year (a general-purpose value) is used instead of the effective stress time Heff per day that varies from day to day throughout the year. Heff and Heff are related by the following equation (32): Σ{exp(-qEa / kTmp)·heff}=exp(-qEa / kTeff)·Heff·365 (32) In the above equation (32), Σ is the cumulative sum (total) of each day for 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 Heff per day per year that can withstand general use. More preferably, when the annual average temperature of the maximum temperature Tmax in one day is referred to as "annual average Tmax," Heff [h] = 0.108 × annual average Tmax [°C] + 1.7. Even more preferably, Heff [h] = -0.00248 × (annual average Tmax [°C]). ２ + 0.245 × Tmax annual average [°C]. Also, if the module temperature in the field is available, the annual median of the effective stress time per day heff, which varies from day to day throughout the year, can be taken as Heff.

[0142] FIG. 12 shows the predicted acetic acid concentration values ​​(shown by dashed lines) obtained as described above and the measured acetic acid concentration values ​​(shown by black circles (●)) of PV modules installed in the field. That is, FIG. 12 is a diagram showing the relationship between the number of years a PV module has been installed in the field and the acetic acid concentration in the encapsulant of that PV module. As shown in FIG. 12, the two values ​​show a relatively good degree of agreement.

[0143] <Acetic Acid Concentration at the Time when the PV Module Ends its Life> Next, as shown in step S6 of FIG. 4, the control unit 10 of the electronic device 1 obtains information A of the acetic acid concentration at the time when the PV module to be predicted for its life will end. Ｔ (Hereafter, "Acetic acid concentration at end of life A Ｔ " or "Lifetime acetic acid concentration A Ｔ ") is obtained.

[0144] As corrosion of the electrodes 170 and / or contact portions 180 of the PV module by acetic acid progresses, electrical conductivity between the electrodes and the semiconductor silicon deteriorates, and the contact resistance between the electrodes and the semiconductor increases. The increased contact resistance inhibits the extraction of carriers generated in the semiconductor silicon by the photoelectric conversion effect to the electrodes, reducing the output of the PV module. It is known that the output of a PV module is determined by three pieces of information: the short-circuit current Isc, the open-circuit voltage Voc, and the fill factor FF. Increased contact resistance is particularly manifested as a deterioration in the FF characteristics.

[0145] The applicant investigated the correlation between acetic acid concentration and FF characteristics and found the correlation shown in Figure 13. Figure 13 is a graph showing the relationship between acetic acid concentration and FF change rate (deterioration rate) for a PV module that underwent a damp heat test (a damp heat test product) and a PV module that was recovered from the field (a market recovery product).

[0146] As shown in Figure 13, it can be seen that the FF characteristics deteriorate rapidly when the acetic acid concentration exceeds a certain level. There are several deterioration modes that affect the lifespan of a PV module. Among these, the rapid deterioration of the 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, an FF characteristics deterioration rate of 10% is used as a guideline for the moist heat deterioration lifespan, and the acetic acid concentration at this time is defined as the acetic acid concentration at lifespan A. Ｔ The acetic acid concentration at the end of life is A Ｔ It is considered appropriate to assume that the range of the lifetime acetic acid concentration A is approximately the range shown in the following formula (33). Ｔ ≒ 3 x 10 １８ ~ 3 x 10 １９ [ / cm ３ ] (33)

[0147] In addition, the acetic acid concentration A Ｔ The PV module is subjected to a damp heat test until the end of its life, and the acetic acid concentration information A at the end of its life is Ｔ may be given by measuring

[0148] Here, the lifetime acetic acid concentration A Ｔ can vary depending on the specifications of the PV module. That is, the lifetime acetic acid concentration A varies depending on the specifications of the electrodes of the solar cell in the PV module (composition, electrode width, electrode thickness, firing conditions, etc.) and / or the specifications of the sealing material in the PV module (main material, additives, thickness, etc.). Ｔ may be set to an appropriate value. In this case, the lifetime acetic acid concentration A Ｔ is not limited to the range of the above formula (33), and upper and lower limit values ​​may be given according to the specifications of the PV module. Specifically, a damp heat test and / or a UV damp heat combined test (for example, a UV damp heat sequential combined test in the case where a damp heat test is performed after a UV test) may be performed for each specification of the PV module. Then, a graph such as that shown in FIG. 13 is created for each specification of the PV module, and an appropriate lifetime acetic acid concentration A Ｔ (a new range to replace the range shown in equation (33)) may be determined.

[0149] <Calculation of Lifespan of 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 remaining until the lifespan of the PV module to be predicted based on deterioration due to wet heat (lifespan Y Ｔ ) is calculated.

[0150] Based on the above, the number of years until the end of the life of the PV module due to deterioration caused by damp heat (hereinafter simply referred to as the lifespan Y Ｔ (also referred to as "the concentration of acetic acid at the end of the life") is the concentration of acetic acid A Ｔ and have the relationship shown in the following equation (34). Ｔ =A0・exp(B0・exp(-qEa / kTeff)・Heff・365・Y Ｔ ) (34)

[0151] where A0 represents the acetic acid concentration in the EVA of the PV module at a given time. Ｔ is the number of years (unit: [Y (years)]) remaining until the end of the lifespan, with the time when the acetic acid concentration in the EVA of the PV module was A0 as the zero point. Also, B0 is 1.6 × 10 ７ can be used.

[0152] The above formula (34) is expressed as Y Ｔ When solving for Y, the following equation (35) is obtained. Ｔ = ln(A Ｔ / A0) / {B0・exp(-qEa / kTeff)・Heff・365} (35)

[0153] Here, the acetic acid concentration at the end of life A Ｔ is 3 x 10 １８ ~3 x 10 １９ [ / cm ３ ], the life span Y Ｔ Specifically, the acetic acid concentration A at the end of the life can be calculated as Ｔ 3 x 10 １８ The lifespan Y obtained when Ｔ The value of Y is the life span. Ｔ In addition, the acetic acid concentration A Ｔ 3 x 10 １９The lifespan Y obtained when Ｔ The value of Y is the life span. Ｔ This can be used as a guideline for the upper limit.

[0154] FIG. 14 shows the lifespan Y obtained by the above equation (35). Ｔ 14 is a graph showing the actual lifespan of a PV module installed in the field (a market-installed product) together with the lifespan Y Ｔ The upper limit of the predicted remaining life is indicated by a dashed line (predicted remaining life (upper limit)). In addition, in FIG. 14, the life span Y obtained by the above formula (35) Ｔ The lower limit of the predicted remaining life is indicated by a broken line (lower limit). In addition, in FIG. 14, products installed in the market are indicated by black circles (●).

[0155] In FIG. 14, the life span Y Ｔ is calculated with the time when the PV module is installed in the field as the zero point of time. Ｔ 3 x 10 １８ [ / cm ３ ] and life span Y Ｔ The calculation was made assuming the lower limit of the acetic acid concentration A Ｔ 3 x 10 １９ [ / cm ３ ] and life span Y Ｔ As shown in FIG. 14, the actual lifespan of the PV module is sandwiched between the lower and upper limits of the predicted lifespan, and the lifespan Y Ｔ The validity of the can be confirmed.

[0156] <Humidity Correction and UV Correction in Lifespan Prediction> In this way, the lifespan Y Ｔ This life span Y Ｔcan be considered as a guideline for the lifespan years before considering humidity correction (humidity dependence of the time until the end of life due to moist heat) and UV correction (UV light dependence of the time until the end of life due to moist heat). If the risk of deterioration until the approximate end of the lifespan of the target PV module is to be evaluated, the guideline lifespan years, as shown in Figure 14, can be considered as sufficiently useful information. On the other hand, if a more accurate determination of the lifespan years of the target PV module is desired, humidity correction and UV correction, as described below, may be considered.

[0157] When performing humidity correction and UV correction, the control unit 10 of the electronic device 1 may calculate a humidity correction coefficient as shown in step S8 of FIG. 4 and calculate a UV correction coefficient as shown in step S9. In this way, the control unit 10 calculates the lifespan Y taking into account the humidity correction and UV correction as shown in step S10. Ｔ , that is, the lifespan years based on deterioration due to UV and moist heat in the installed field can be calculated.

[0158] Here, the humidity correction is a correction made to B0 in the above formulas (34) and (35). Also, the UV correction is a correction made to A0 in the above formulas (34) and (35). Specifically, if the humidity correction coefficient is represented as βH and the UV correction coefficient is represented as βU, the above formulas (34) and (35) can be expressed as the following formulas (36) and (37). 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 the above equations (36) and (37), the humidity correction coefficient βH can be given in the range of about 0.5 to 1, and the UV correction coefficient βU can be given in the range of 1 to about 20. The humidity correction coefficient and the UV correction coefficient will be further explained below.

[0160] <Regarding the humidity correction coefficient> The humidity correction coefficient βH is a parameter for taking into account the humidity dependency of B0. This parameter is 1.6×10 ７ is multiplied by the humidity correction coefficient βH to obtain the moisture concentration [H ２ The humidity correction coefficient βH can be given in the range of about 0.5 to 1 as described above. The moisture concentration [H ２ As mentioned above, the moisture concentration [H O] is not simply proportional to the humidity of the outside air (atmosphere), but also depends on the moisture retention capacity (moisture adsorption capacity) of EVA. ２ O] may be information that should be determined experimentally. Therefore, the humidity correction coefficient βH may also be information that should be determined experimentally.

[0161] The applicant has confirmed through experiments that the humid heat degradation life of a PV module depends on the relative humidity. The applicant has also confirmed that the relative humidity at the temperature of a PV module can be determined by taking into account information on the relative humidity of the atmosphere in an actual field environment and information on the temperature of a PV module installed at that location. The applicant has also confirmed that the humid heat life of a PV module in an actual field environment can be obtained by the following procedure.

[0162] That is, first, the Arrhenius equation is applied to the humid heat life of the PV module in the high temperature and high humidity test. This determines the humid heat life under high humidity conditions at the actual field temperature (the same relative humidity conditions as the high temperature and 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 humid heat life under high humidity conditions. This allows the humid heat life of the PV module in the actual field environment to be obtained.

[0163] From the results of a moist heat test in which relative humidity conditions were used as a variable, the applicant determined that a maximum value of approximately 2 is appropriate as the humidity correction factor for lifespan prediction. The humidity correction factor for lifespan prediction is in an inverse relationship with βH, which is the correction factor for the acetic acid production reaction coefficient B0. From the above, a value in the range of approximately 0.5 to 1 was obtained as the humidity correction factor βH.

[0164] For a PV module actually installed in the field, the specific value to be adopted within the above range for 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, an analytical value of the moisture concentration in the EVA obtained by recovering the PV module installed in the field. The predetermined information may also be the remaining lifespan (lifetime) obtained by conducting an additional hygrothermal test on the PV module installed in the field. If it is considered that necessary or sufficient information is lacking for a comprehensive judgment, a value as close to 1 as possible may be adopted for the humidity correction coefficient βH. This corresponds to a relatively strict prediction of the PV module's lifespan, i.e., a short estimate. Such a prediction allows a user to prioritize safer choices over risky choices resulting from a longer prediction of the PV module's lifespan when making decisions based on the PV module's lifespan. The degree to which the humidity correction coefficient βH should be set close to 1 may be determined based on the risk policy of the entity determining the PV module's lifespan. In addition, in areas where humidity is relatively high throughout the year, such as particularly southern regions of Japan and Southeast Asia, a value close to 1 can be adopted as the humidity correction coefficient βH.

[0165] <UV Correction Coefficient> The UV correction coefficient βU is a parameter that takes into account the phenomenon in which additives in EVA are involved in the generation of acetic acid in the presence of UV light. A typical additive that is involved in the generation of acetic acid under the stress of UV light is UVA (UV absorber). The UV correction coefficient βU may be determined by taking into consideration 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. That is, first, the acetic acid concentration (e.g., 2×10) generated when a PV module after manufacture but before installation in the field is subjected to a UV irradiation test is determined as the acetic acid concentration at which the acetic acid concentration reaches a nearly saturated value. １８ / cm ３ In this case, the cumulative irradiation energy of UV light in the UV irradiation test is 300 kWh / m, assuming that the product has been installed in the field for about three years. ２ Next, the acetic acid concentration thus obtained may be adjusted to the acetic acid concentration before the UV irradiation test (for example, 1 to 2 × 10 １７ / cm ３ The maximum value of the UV correction factor βU can be obtained by dividing the UV correction factor βU by the acetic acid concentration (for example, 2×10 １８ / cm ３ The acetic acid concentration before installation in the field (for example, 1 to 2 × 10 １７ / cm ３ From the above, the UV correction coefficient βU can be given in the range of 1 to about 20, as described above.

[0166] Below, the method of determining the UV correction coefficient βU will be explained for several cases.

[0167] First, when the glass located on the light incident surface of the PV module is glass that transmits almost no UV light (UV-cutting glass), the UV correction coefficient βU may be given a value close to 1. This is because, in the case of UV-cutting glass, even if an additive such as an ultraviolet absorber UVA is blended into the EVA, almost no UV light reaches the EVA, and therefore almost no acetic acid production caused by the additive involving UV light occurs.

[0168] Next, when the glass located on the light incident surface of the PV module is glass that transmits UV light (UV-through glass) and the installation period is approximately three years or more, the UV correction coefficient βU may be assigned a value close to 1, regardless of the presence or absence of additives such as UVA. This is because, even if additives such as the ultraviolet absorber UVA are added, the reaction that produces acetic acid due to these and UV light hardly occurs after the PV module has been installed for approximately three years. Specifically, additives such as the ultraviolet absorber UVA decompose or combine with other molecules due to UV light stress over the course of approximately three years after installation, and their concentration rapidly decreases in inverse proportion to the production of acetic acid.

[0169] Next, when the glass located on the light incident surface of the PV module is UV-through glass, an additive such as an ultraviolet absorber UVA is blended into the EVA, and the PV module has been installed for less than approximately three years, the UV correction coefficient βU may be set to a value greater than or equal to 1 and up to a maximum of approximately 20. For example, the shorter the age of the PV module, the closer the UV correction coefficient βU to 20, and the closer the age of the PV module is to approximately three years, the closer the UV correction coefficient βU to 1.

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

[0171] Furthermore, when UVA is not added, if the concentration of acetic acid in EVA when it reaches near saturation in the UV irradiation test is U2, βU may be given by the following equation (39): βU=1∼U2 / A0 (39)

[0172] <Predicting Remaining Life Using Raman Measurement Information> Next, a case where the remaining life of a PV module is predicted using Raman measurement information (Raman signal intensity) will be described.

[0173] First, we will describe the case where the glass located on the light incident surface of the PV module is glass that barely transmits UV light (UV-cutting 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-cutting glass, even if an additive such as the ultraviolet absorber UVA is blended into the EVA, almost no UV light reaches the EVA, so there is almost no acetic acid production caused by the additive.

[0174] Next, we will consider the case where the glass located on the light incident surface of the PV module is glass that transmits UV light (UV-through glass). In this case, the relationship between the Raman signal intensity ratio and the acetic acid concentration may significantly differ from the correlation shown in FIG. 6 . That is, the correlation may have a different slope from the correlation shown in FIG. 6 . Specifically, the relationship between the Raman signal intensity ratio and the acetic acid concentration may be, for example, a correlation such as that shown in FIG. 15 . In such a case, a correction coefficient γ may be introduced to accurately determine the acetic acid concentration in EVA from the Raman signal intensity ratio. That is, if the correlation shown in FIG. 6 is expressed by the following equation (40), a correlation whose slope is significantly different from that of the correlation shown in FIG. 6 (for example, the correlation shown in FIG. 15 ) can be expressed 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) C1 in the above formula (40) represents the slope of the approximation equation that fits the experimental data in the graph of [log (acetic acid concentration) - Raman signal intensity ratio] shown in FIG. 6. C2 in the above formula (40) represents the intercept of the approximation equation that fits the experimental data in the graph of [log (acetic acid concentration) - Raman signal intensity ratio] also shown in FIG. 6. γ in the above formula (41) is a correction coefficient that corrects C1 (i.e., replaces the slope with γ C1) to provide the slope of the approximation equation that fits the experimental data shown in FIG. 6. By introducing the correction coefficient γ, an approximation equation that fits the experimental data, such as that shown in FIG. 15, can be obtained. The value of γ can be in the range of 0.2 to 1.0. For example, in the examples of FIGS. 6 and 15, C1 can be set to about 3.12±0.03, C2 to about 1.41±0.02, and γ to about 0.23±0.04.

[0175] When the glass located on the light incident surface of the PV module is a glass that transmits UV light (UV-through glass), the absolute value of the Raman signal intensity may be very large, and the Raman signal intensity ratio may take a form such as that shown in Figure 16. This phenomenon is particularly noticeable when an ultraviolet absorber UVA is added. Here, the Raman signal intensity ratio is calculated by dividing a predetermined Raman signal intensity by a Raman shift of 2800 cm －１ The Raman signal intensity ratio is normalized by the Raman signal intensity due to the nearby CH. Hereinafter, a method for calculating the remaining lifespan of a PV module in a case where the Raman signal intensity ratio shown in Fig. 16 is obtained will be described.

[0176] First, we will explain the case where the installation age (Y0) of the PV module is about 3 years or more (about 3 years < Y0). When the installation age of the PV module is about 3 years or more, as described above, the concentration of additives such as the ultraviolet absorber UVA has already decreased significantly. Therefore, the generation of acetic acid caused by these additives can be almost ignored thereafter. Therefore, when a Raman spectrum waveform such as that shown in FIG. 16 is observed in a PV module that has been installed for about 3 years or more, it can be considered that the acetic acid concentration caused by these additives is saturated about 3 years after installation. In other words, if the time when the PV module has been installed for about 3 years is set as the reference time (year zero), the acetic acid concentration A Ｔ and / or number of years until lifespan (remaining lifespan) Y Ｔ may be calculated using equations (36) and (37). In this case, 1 is used as the value of βU, and 1 to 2×10 is used as the reference value of A0. １８ Alternatively, 1 may be used as the value of βU, and the above-mentioned U1 or U2 may be used as the reference value of A0 at the reference time. From the above, the number of years remaining until the end of life (remaining life years) at the time of Y0 can be calculated as follows: Ｔ +(3-Y0).

[0177] Next, we will explain the case where the installation age (year Y0) of the PV module is less than about 3 years at that time (Y0<about 3 years). When the installation age of the PV module is less than about 3 years at that time, the concentration of additives such as the ultraviolet absorber UVA has not yet decreased significantly. However, unless there is a particular reason for removal, the PV module will generally continue to be installed in the same location thereafter, and the installation age will exceed about 3 years and continue for an even longer period. In this way, when it is expected that the installation age will exceed about 3 years in the future, the situation is the same as when the installation age is about 3 years or more. That is, when a PV module that has been installed for less than about 3 years (year Y0) is expected to obtain a Raman spectrum waveform such as that shown in FIG. 16 in the future, the remaining life of the PV module may be predicted as follows. That is, when the time when the PV module has been installed for about 3 years is set as the reference time (year zero), the acetic acid concentration A Ｔ and / or number of years until life expectancy Y Ｔ may be calculated using equations (36) and (37). In this case, 1 is used as the value of βU, and 1 to 2×10 is used as a guideline value for the value of A0 at the reference time. １８ Alternatively, 1 may be used as the value of βU, and the above-mentioned U1 or U2 may be used as the reference value of A0 at the reference time. From the above, the number of years remaining until the end of life (remaining life years) at the time of Y0 can be calculated as follows: Ｔ +(3-Y0).

[0178] <Relationship between Lifespan (Prediction) Based on Deterioration Due to Wet Heat and Actual Lifespan> The lifespan (prediction of remaining lifespan) of a PV module based on deterioration due to wet heat obtained by the above procedure has a magnitude relationship with the actual lifespan as shown in the following equation (42). Actual lifespan≦Lifespan (Prediction) Based on Deterioration Due to Wet Heat (42)

[0179] The relationship shown in equation (42) above is due to the fact that the actual remaining life span is affected not only by environmental stresses such as temperature, humidity, and UV light, but also by all environmental stresses, such as temperature cycle stress and / or potential difference stress. Here, potential difference stress refers to stress caused by the potential difference between the PV module and ground potential. Therefore, the life span based on humid heat degradation obtained by the electronic device 1 according to an embodiment may be interpreted as providing an upper limit for the actual life span. That is, the life span based on humid heat degradation of the PV module obtained by the electronic device 1 according to an embodiment is a value that can be obtained within a certain range depending on the acetic acid concentration at the time of life, the humidity correction factor, and / or the UV correction factor. However, taking into account the magnitude relationship with the actual life span described above, shorter life spans obtained within a range may be weighted and considered as a predicted value. Such a prediction allows a user to prioritize safer choices over risky choices resulting from a longer prediction of the PV module's life span when making decisions based on the life span of the PV module.

[0180] Furthermore, if the total lifespan of the panels is denoted as Ytotal, Ytotal can be expressed as the following equation (43): Ytotal = installation years + remaining lifespan = Y0 + Y Ｔ (43) However, the total lifespan Ytotal mentioned here is meaningful only when there is no change in the installation area / installation form before and after the measurement of the acetic acid concentration.

[0181] <Effects of Electronic Device According to an Embodiment> According to an embodiment, the electronic device 1 can predict the lifespan (remaining lifespan) due to subsequent deterioration due to moist heat based on information indicating the acetic acid concentration in the EVA in the PV module. Furthermore, according to an embodiment, when the acetic acid concentration is obtained by Raman measurement, the lifespan (remaining lifespan years) of the target PV module due to deterioration due to moist heat can be predicted based only on Raman measurement information at a single time. Furthermore, according to an embodiment, even when the installation form and / or installation location of the PV module is changed, the lifespan (remaining lifespan years) of the PV module due to deterioration due to moist heat can be predicted after the change. In this case, if acetic acid concentration information at the time of the change (Raman measurement information at the time of the change) is available, the lifespan (remaining lifespan years) of the PV module due to deterioration due to moist heat can be predicted after the change.

[0182] In recent years, a secondary market (trading market) for PV power plants has been emerging. Business schemes offering warranties for used PV modules have also emerged. In this context, a key challenge in trading used PV modules at fair prices is how to assess the current asset value of used PV modules. The technology for assessing this value is crucial. According to an electronic device 1 of an embodiment, the remaining lifespan of a used PV module can be reasonably assessed. Therefore, the assessment of the asset value of used modules using the electronic device 1 of an embodiment can be an essential technology for such business schemes. According to the electronic device 1 of an embodiment, highly reliable information regarding the remaining lifespan of a PV module can be provided in the secondary market for PV power plants.

[0183] Furthermore, in recent years, the issue of final disposal (disposal) of existing residential PV modules has begun to be recognized. Specifically, issues such as the time until disposal of the PV module (remaining lifespan), inspection methods during the period leading up to disposal, and / or final disposal methods have begun to be recognized. According to an embodiment of the electronic device 1, the remaining lifespan of an existing residential PV module can be reasonably evaluated. Therefore, evaluation of the remaining lifespan of an existing module using the electronic device 1 according to an embodiment of the present invention can be an essential technology for making appropriate decisions regarding such issues. According to an embodiment of the electronic device 1, information regarding the remaining lifespan of an existing residential PV module (remaining lifespan) can be provided as highly reliable information.

[0184] According to the electronic device 1 of the embodiment, it is possible to reasonably predict the remaining life of a PV module that uses a general EVA as an encapsulant. On the other hand, for a PV module that uses EVA with an added acid acceptor, the remaining life may be predicted by taking into account parameters other than the various parameters described above.

[0185] While the present disclosure has been described based on various drawings and examples, it should be noted that those skilled in the art can easily make various modifications and alterations based on the present disclosure. Therefore, it should be noted that these modifications and alterations are within the scope of the present disclosure. For example, the functions included in each functional unit can be rearranged so as not to cause logical inconsistencies. Multiple functional units can be combined into one or divided. The above-described embodiments of the present disclosure are not limited to faithful implementation of each of the described embodiments, but can be implemented by combining each feature or omitting some features as appropriate. In other words, those skilled in the art can make various modifications and alterations to the contents of the present disclosure based on the present disclosure. Therefore, these modifications and alterations are within the scope of the present disclosure. For example, in each embodiment, each functional unit, each means, each step, etc. can be added to other embodiments so as not to cause logical inconsistencies, or can be replaced with each functional unit, each means, each step, etc. of other embodiments. Furthermore, in each embodiment, multiple functional units, each means, each step, etc. can be combined into one or divided into two or more.

[0186] The above-described embodiments are not limited to implementation as electronic devices. For example, the above-described embodiments may be implemented as a control method for a device such as an electronic device. Furthermore, for example, the above-described embodiments 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.

[0187] REFERENCE SIGNS LIST 1 Electronic device 10 Control unit 20 Input unit 30 Output unit 40 Communication unit 50 Storage unit

Claims

1. An electronic device that generates fourth information regarding the remaining period during which the solar cell module is expected to be able to output the specified power in the usage environment, based on first information representing the acetic acid concentration in a sealing material of a solar cell module at a specified point in time, second information representing the acetic acid concentration in the sealing material at the end of a period during which the solar cell module is capable of outputting the specified power, and third information related to calculation of the change over time in the acetic acid concentration in the sealing material in the usage environment of the solar cell module.

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

3. The electronic device according to claim 1 or 2, wherein the first information is information obtained based on a Raman spectroscopy measurement performed on an encapsulant of the solar cell module.

4. The electronic device according to claim 3, wherein the first information is information obtained based on a measurement by Raman spectroscopy performed at the specified time point.

5. The electronic device according to claim 1, wherein the first information is information obtained by destroying the solar cell module.

6. The electronic device according to claim 1 or 5, wherein the first information is information obtained based on an analysis of an encapsulating material of the solar cell module by an ion chromatography method.

7. The electronic device according to claim 1 or 5, wherein the first information is information obtained based on a pH measurement performed on a sealing material of the solar cell module.

8. The electronic device according to claim 1, wherein the third information is information that represents a change in concentration of acetic acid in the sealing material over time.

9. The electronic device according to claim 1, wherein the fourth information is information relating to a period until a sudden drop in the power output by the solar cell module in the usage environment occurs.

10. The electronic device of claim 1, wherein the fourth information is generated based on the first information, the second information, and the third information, while taking into account a correction related to the humidity to which the solar cell module is exposed.

11. The electronic device of claim 1, wherein the fourth information is generated based on the first information, the second information, and the third information, and by adding correction related to ultraviolet light to which the solar cell module is exposed.

12. A method for controlling an electronic device, comprising: acquiring first information representing the concentration of acetic acid in a sealing material of a solar cell module at a predetermined point in time; acquiring second information representing the concentration of acetic acid in the sealing material at the end of a period during which the solar cell module is capable of outputting a predetermined amount of power; acquiring third information related to calculating the change over time in the concentration of acetic acid in the sealing material in the usage environment of the solar cell module; and generating fourth information relating to the remaining period during which the solar cell module is expected to be capable of outputting the predetermined amount of power in the usage environment based on the first information, the second information, and the third information.

13. A program that causes an electronic device to execute the following steps: acquiring first information representing the acetic acid concentration in the sealing material of a solar cell module at a predetermined point in time; acquiring second information representing the acetic acid concentration in the sealing material at the end of a period in which the solar cell module is capable of outputting a predetermined amount of power; acquiring third information related to calculating the change over time in the acetic acid concentration in the sealing material in the usage environment of the solar cell module; and generating fourth information regarding the remaining period in which the solar cell module is expected to be capable of outputting the predetermined amount of power in the usage environment based on the first information, the second information, and the third information.

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