Investigation of the Temperature Sensitivity of 20-Years Old Field-Aged Photovoltaic Panels Affected by Potential Induced Degradation

Abstract

One effect of moisture ingress on solar panels is potential induced degradation (PID). Solar panels affected by PID experience large leakage currents between the solar cells and the module’s frame, which leads to substantial power degradation. In the present work, the temperature coefficients of 3 old PV panels affected by PID were investigated. In the electroluminescence images, solar cells nearer to the edge of the modules appear darker due to ohmic shunting. IR thermal images acquired under clear sky outdoor conditions show that the majority of the warmer cells (hotspots) were located closer to the edge of the modules. The difference in cell temperature (∆T) due to PID effect ranges from 7 °C to 15 °C for the 3 field-aged modules. The average temperature coefficient of efficiency (β_ηm) was found to be −0.5%/°C. Also, it was observed that the temperature coefficients of open circuit voltage (β_Voc = −0.4%/°C), maximum power point voltage (β_Vmpp = −0.5%/°C), and fill factor (β_FF = −0.2%/°C), were the underlying factors for the degradation in the P_max of the old solar panels affected by PID. This accounted for an average 1.2%/year overall degradation in the efficiency of these modules. Most notably, it was discovered that the PV modules affected by PID show negative temperature coefficients of maximum power point current (β_Jmpp) due to large leakage currents. This observed negative β_Jmpp we believe is characteristic of PV panels affected by PID.

1. Introduction

One of the underlying effects of moisture ingress on photovoltaic (PV) modules is potential induced degradation (PID) [1,2,3,4,5,6,7]. PID occurs when there is an increased material conductivity and leakage current between the PV module’s frame and the cells [8,9,10,11,12,13,14,15]. This has severe consequences for PV module power reliability and can constitute up to 100% of power loss in PV plants [16].

According to Naumann et al. [10], high surface defect density on interdigitated back contact (IBC) solar cells results in decreased field effect passivation. Decreased field effect passivation leads to high surface recombination, and hence, causes PID of polarization/passivation (PID-p) type. However, PID-p is temporary and reversible [10,17,18,19]. Investigations revealed that the transport of mobile ions, especially sodium (Na+) ions, within the PV module bulk is responsible for the PID of shunting (PID-s) type [2,15,20,21]. High conductivity of sodium decorated stacking faults across the solar cell emitter leads to shunting, hence, PID-s [2,20]. PID-s manifests itself in the degradation in the open circuit voltage, short circuit current, and fill factor [2,3]. Hence, PID-s type appears to be the key problem in the field [17].

There have been efforts to prevent PID at the cell and module manufacturing levels, installation, and during operation [2,5,22]. Current-voltage (I-V) characterization, electroluminescence (EL), and infrared (IR) thermography could be used to detect and monitor the onset of PID in PV plants under sunlight or in the dark with external bias conditions [2,21]. PID-s cells are identified as warmer cells in IR thermal images and darker cells in EL images [3,6,15]. According to Carolus et al. [14], Current-voltage (I-V) and external quantum efficiency (EQE) measurements could be used to differentiate PID-s from PID-p. Proposed methods for reversing the PID effect appears to be saddled with other limitations [8,22]. Indeed, the TS IEC 62804-1 standard exists to ensure PID reliability of commercial PV modules. However, the PID effect continues to be a challenge for the PV community [2,6,20,23,24].

In addition to power degradation, PID also induces mismatch losses due to non-uniform degradation [9,20,25,26]. Degraded cells that are affected by PID cause current reverse biasing, which leads to local overheating or joule heating [14,27]. This triggers hotspots, which influence the PV module operating temperature (T_m), hence, the temperature sensitivity [20,25,28]. According to Islam et al. [23], PID in polycrystalline solar panels can accelerate cell crack propagation and can lead to the degradation in the temperature coefficient of efficiency. In addition, Wang et al. [24] observed an increased temperature coefficient of maximum power (P_max) in PV modules affected by PID. Extensive research on the influence of the temperature sensitivity on PV modules main electrical parameters is available in literature [25,26,28,29,30,31]. However, studies on the influence of PID on the temperature coefficients of PV modules are rare [20,25,26,28]. Moreover, only a few were done on field-aged PV modules [23,24]. Yet, we have not found any report on the influence of PID on the temperature coefficients of the maximum power point voltage (β_Vmpp) and current (β_Jmpp) of PV modules.

A procedure for detecting PID based on temperature coefficient profiling of PID affected field-aged multicrystalline silicon (mc-Si) PV modules is presented in this contribution. I-V characterization, EL, and IR thermal imaging were used for the investigation. It turned out that PV modules affected by PID could be detected by monitoring the temperature coefficient of maximum power point current (β_Jmpp). Section 2 presents the material and methods used for the investigation and the results and the insights from the investigation are presented in Section 3.

2. Materials and Methods

In the present work, field-aged NESTE NP100G12 multicrystalline silicon (mc-Si) PV modules affected by PID were investigated. The 3 solar panels (namely A, B, and C) were chosen from a batch of solar panels which were installed on a Renewable Energy Park in Dømmesmoen, Grimstad (58.3447° N, 8.5949° E), Norway in the year 2000. However, the PV modules on the Energy Park were decommissioned in 2011 and were kept securely for research purposes [32]. In an earlier report on the types of defects and faults modes of these old solar panels by the present authors, EL and IR thermal data of PV panel C was used to show that some of the old PV panels were affected by PID. The manufacture’s data sheet and the measured electrical data on the 3 old PV panels (namely A, B, and C) is summarized in

Table 1. Technical data sheet (2000) and the measured electrical parameters (2021) of old solar panels normalized to Standard Test Conditions (STC).

PV Module		Pmax (W)	Voc (V)	Isc (A)	Vmpp (V)	Impp (A)	FF (%)	η (%)
2000 (Data sheet)		100	21.6	6.7	16.7	6.0	70	13.0
	A	75.0	19.5	5.9	14.3	5.2	65	9.7
2021	B	75.9	19.3	6.1	14.2	5.3	65	9.9
	C	78.3	19.6	6.1	14.7	5.3	66	10.2

.

The PV modules were made using anodized aluminum (Al-) frame, low iron tempered front glass, ethylene vinyl acetate (EVA) encapsulation, white multi-layered Tedlar^®/Polyester/Tedlar^® (TPT) backsheet, and 2 weatherproof plastic casing junction boxes (accommodating a bypass diode each). Each PV module consists of (12 × 2) series connected solar cells and 3 substrings, refer to Figure 1. The solar cells feature a full area screen-printed Al-grid rear surface with dimensions of 100 × 100 mm² and a titania antireflective coating (ARC).

2.1. I-V Measurements

The sampled old solar panels were each taken through electrical performance measurements using an HT^® Instruments I-V 500 w I-V Curve Tracer. This was done by following the IEC 60904-1 standard. By these measurements, information on the maximum power (P_max), open circuit voltage (V_oc), maximum power point voltage (V_mpp), short circuit current (I_sc), maximum power point current (I_mpp), fill factor (FF), in-plane irradiance (G_I), and module temperature characteristics of each panel at Standard Test Conditions (STC) was acquired. STC indicates solar cell temperature at 25 °C, G_I at 1000 W/m² and air mass 1.5 (AM1. 5) spectrum for commercial solar PV panels. The entire experimental procedure was carried out under clear sky in-plane irradiance conditions (960–1060 W/m²). The I-V tracer converted all measurements to STC automatically to minimize errors associated with data acquisition.

2.2. Temperature Coefficient Profiling

On a clear sky sunny day in the summer, the PV modules were taken out to the outdoor measuring rack in turns from a storeroom where the modules were kept. The PV module and the reference device were shaded using a cardboard. Measurement was initiated immediately after the shade was removed. The measurements on the 3 field-aged PV modules were done on the same day between 12.30 and 14.30 h and at wind speed less than 2 ms⁻¹. According to IEC 60891-4 standard, the temperature range of the data values should be at least 30 °C. However, this seems challenging in practical field measurements, especially for the investigation site.

A graph of electrical parameters (P_max, V_oc, I_sc, FF, η_m, V_mpp, I_mpp) versus PV module’s temperature (T_m) was plotted and a least-squares-fit graph through each data set was acquired to get the relative temperature coefficients. The regression equation for such relation can be represented as y = mx + c, where m and c are the slope (temperature coefficient) and the intercept (the value of the electrical parameter at 0 °C), respectively [33]. The relative temperature coefficient of parameter X (β_x) in%/°C was calculated by dividing the slope of parameter X by the intercept of parameter X. That is, β_x = m/c.

2.3. Electroluminescence (EL) Tomography

EL tomography is interesting especially for characterizing old PV panels affected by PID. The 3 sampled PV panels were taken through the EL characterization in a dark room using the BrightSpot EL Test Kit, see Figure 2. The kit comprises of a 24 megapixels modified DSLR (digital single-lens reflex) Nikon D5600 camera, DC power supply set, and computer with data acquisition and image processing software. The image acquisition and processing were done according to the IEC 60904-13 standard and the IEA procedure [3,15]. The EL characterization of the PV modules was done under 0.1I_sc and at I_sc current density conditions.

2.4. Infrared (IR) Thermal Imaging

The sampled solar panels were also taken through IR thermography using the Fluke Ti400 Infrared Camera (λ ≈ 650 nm) as per the IEA recommended procedure [15] and the IEC 62446-3 standard. Figure 3 shows the outdoor experimental setup. Measurements were done under clear sky field conditions. The IR thermal images were acquired after soaking the PV modules in the sun for at least 15 min, as prescribed by the IEC 62446-3 standard.

3. Results and Discussion

3.1. I-V Characteristics of the PV Panels

Figure 4 illustrates the I-V characteristics of the field-aged PV Modules A, B, and C. The I-V curve for the manufacturer’s data sheet in 2000 illustrates the I-V characteristics of the panels when they were new, i.e., when they were not affected by PID. However, in 2021, when the solar panels were affected by PID, the 3 panels show similar degradation trend in electrical characteristics. There was ca. 10% degradation in both I_sc and V_oc and ca. 24% degradation in P_max over the 20 years. That is, annual degradation of ca. 0.5% in I_sc and V_oc and ca. 1.2% in P_max, which agrees with observation elsewhere [34]. This resulted in the decrease in fill factor (F) of ca. 0.3%/year and a drop in efficiency of ca. 1.2%/year, see Table 1. A drop in the P_max, I_sc, V_oc, and FF was also observed by other researchers [3,14,15,29].

It was reported that the effect of PID is more severe under lower irradiation conditions as compared to STC [3,16]. This means that PV modules deployed in the cold regions are more susceptible to the PID effect than those deployed in climates with high regular irradiance conditions. Low irradiance and shading conditions predispose PV modules to mismatch losses, hence, hotspots [33]. These hotspots can induce the onset of PID [16,20,35]. For the 3 field-aged PV modules, the average degradation in the V_mpp and I_mpp were 0.7% and 0.6% per year, respectively (refer to Table 1). Figure 5 illustrates the relative change (∆) in the electrical parameters of the old solar panels affected by PID over the 20 years. The relative change (∆) in the electrical parameters of the PID affected old solar panels was computed as the difference between the datasheet values (2000) and the values measured in the year 2021, a recommended procedure by Köntges et al. [17].

The position of the box indicates the percentage degradation, and the dots show the outliers. The degree of deviation of the electrical parameter from the mean value is indicated by the length of the box. The degradation in the electrical parameters of the 3 old solar panels follow a similar trend. P_max shows more than 20% degradation over the 20 years, refer to Table 1. It appears from Figure 5 that the underlying cause of the P_max degradation is the degradation in all electrical parameters, especially degradation in V_oc and V_mpp. Yet, it is blurry as to the degree of contribution from each electrical parameter to the overall degradation in P_max.

It is known that P_max is directly related to the maximum power point voltage (V_mpp) and the maximum power point current (I_mpp) by the following relation:

$$P_{max}{=V}_{\mathit{mpp}}·I_{\mathit{mpp}}$$

(1)

However, fill factor (FF) of a PV module could also be written as

$$\mathit{FF}=\frac{V_{\mathit{mpp}}·I_{\mathit{mpp}}}{V_{\mathit{oc}}·I_{\mathit{sc}}}$$

(2)

So, the maximum power output of a PV panel is related to the fill factor as

$$P_{max}{=V}_{\mathit{oc}}·I_{\mathit{sc}}·\mathit{FF}$$

(3)

The PV module efficiency (η_m) is related to the P_max, module’s area (A_m), and the input power (P_in) as

$${\eta }_m=\frac{P_{max}}{A_m·P_{in}}$$

(4)

That means, any drop or degradation in V_oc, I_sc, FF, V_mpp, and I_mpp affects the P_max or η_m of the PV module directly, refer to Figure 4. Since the P_in for η_m calculations is assumed as 1 kWm⁻², P_max ≈ η_m/A_m. A_m is the product of the solar cell’s area and the number of solar cells in the module. From

Table 2. Correlation of the degradation in PV modules electrical parameters to the degradation in P_max due to PID. R² indicates the degree of correlation.

PV Module	R2
	∆Voc	∆Vmpp	∆FF	∆Impp	∆Isc
A	0.98	0.99	0.86	0.23	0.47
B	0.98	0.98	0.57	0.55	0.17
C	0.99	0.99	0.88	0.06	0.04

, the regression plots (which indicates the degree of correlation) for P_max versus V_oc and V_mpp gave R² > 97. On the other hand, the R² < 0.6 for I_sc and I_mpp. Resistance losses due to PID is the reason for the higher R² values for the fill factor (FF) of the modules, especially for solar panels A and C. The I-V curves of the modules in Figure 4 support this observation. Solar panel C appears to be the least affected by PID, hence, shows the weakest R² in both ∆I_sc and ∆I_mpp, refer to Table 2. This is because PID alters the current flow characteristics of the PV module [5,8,13]. When PID is caused by negative bias, it can induce optical degradation [5]. This is why most of these old solar panels were found to be affected by optical degradation as well.

Degradation in P_max, V_oc, V_mpp, and FF due to PID was also reported by other authors [3,14,16,29]. They believed that the loss in P_max due to PID could be up to 100% in severe cases [16]. The I-V characteristics of the old solar panels suggest that they are suffering from PID, as reported in other investigations [2,3,5,8,13,14,16,20,21,24,35].

3.2. Electroluminescence Characteristics

Figure 6 shows the EL analyses of the solar panels. The EL images were acquired under I_sc (Figure 6a–c) and 0.1I_sc (Figure 6d–f) forward bias conditions, respectively. The red marked out areas on the images in Figure 6 show some of the areas affected by PID in each PV module. In Figure 6a–c, apart from some darker spots, these images give little or no information on the areas affected by PID. This is because EL under I_sc conditions highlights metal contact or shunt issues [3,15]. In fact, contact issues such as cracks and corrosion are highlighted as darker spots in Figure 6a–c. Hence, EL under I_sc conditions are less suitable for detecting PID in PV modules, as observed in other studies [3,13,15].

On the other hand, under 0.1I_sc conditions, the effect of PID in the field-aged PV modules are well highlighted, see Figure 6d–f. The effect of PID manifests itself in the degradation of the solar cells located closer to the perimeter of the solar panel [8,22]. This accelerated degradation of the cells nearer to the frame of the PV module is due to high leakage currents associated with the PID effect [2,7,24]. Degraded solar cells appear as darker cells in the EL analyses due to strong ohmic shunting of the cell with the panel’s Al-frame [24,27].

The PID affected areas in the solar panels are marked out in red. The trend in Figure 6 is that majority of the darker cells are located close to the edge of the old solar panels. The degradation pattern in Figure 6 suggests that these PV modules are affected by PID, as reported by other authors [3,9,14,15,35].

3.3. IR Thermal Image Characteristics

In IR thermal images, solar cells affected by PID appear as warmer cells or hotspots [16,36]. Figure 7 shows the IR thermograms of the 3 old solar panels (A, B, and C). In Figure 7, the areas marked out in white corresponds to the areas marked out in Figure 6. They show some of the areas in the PV modules that have been affected by PID. Figure 7 shows that majority of the warmer cells are located nearer to the perimeter of the old solar panels, as observed elsewhere [3,15,20,35].

It could be seen that the locations of the warmer cells in the IR thermal images (Figure 7) correspond with the locations of the darker cells in the EL images, refer to Figure 6. Another observation from Figure 7 is that the cells which are closer to the negative terminal (left) of the field-aged PV modules are warmer than the cells which are located nearer to the positive terminal (right), especially those cells that are closer to the Al- frame. This was also reported by other researchers [9,15,35]. This is due to the direction of current flow in a PV module under illumination. Under in-plane radiation, current move by diffusion from the negative to the positive terminal. In PID affected areas, there is high resistance to current flow culminating into high module temperature localized to these areas [20,26,28], as observed in Figure 7.

This is opposite to the direction of current flow when the IR thermal imaging is done under forward bias (drift) conditions, as it is done in EL imaging. This also explains why the defective solar cells are clearly seen at the areas closer to the negative terminal in the field-aged PV modules. Also, high negative leakage current accelerates PID degradation [5,9,20,24,35].

Table 3. Difference in temperature (∆T) of the solar cells with the highest temperature (T_cH) and lowest temperature (T_cL) for PV Modules A, B, and C which were affected by PID.

PV Module	Temperature (°C)		∆T (°C)
	TcH	TcL
A	36.9	29.5	7.4
B	51.3	36.7	14.6
C	49.5	40.5	9.0

shows the extracted solar cells’ temperatures of the old solar panels from the IR thermograms. The difference in the solar cells’ temperature (∆T) extracted from the IR thermograms of each solar panel was calculated according to Equation (4):

$$\Delta T=T_{\mathit{cH}}-T_{\mathit{cL}},$$

(5)

where T_cH is the solar cell with the highest temperature and T_cL is the solar cell with the lowest temperature. ∆T due to PID for the 3 modules which have been affected by PID ranges from 7 °C to 15 °C. Our results for these old panels agrees with the ∆T values reported in literature [15]. The reported ∆T values for solar panels affected by PID is in the range of ca. 7.5–30 °C depending on the severity of the PID effect [3,15,16].

The severity of the PID effect depends on the module materials- antireflection coating and encapsulation [6,21], module configuration [3,11], climatic conditions such as temperature and humidity [4,24,26], and voltage stress [5,9].

3.4. Temperature Coefficient Characteristics

Figure 8 illustrates the characteristics of the relative temperature coefficients of P_max (β_Pmax), V_oc (β_Voc), I_sc (β_Jsc), FF (β_FF), V_mpp (β_Vmpp), and I_mpp (β_Jmpp) of solar panels A, B, and C. Figure 8 compares the variation of each electrical parameter from the average value measured in the year 2021. Degradation in electrical parameters stems from the degradation in the relative temperature coefficients of PV modules [25,26,29]. That is, PID increases recombination in the emitter region of the solar cell [10,11,17,18,19], and this leads to a drop in the V_oc [25]. A drop in the V_oc influence the temperature characteristics of the solar panel [30,37]. A change in the V_oc accounts for more than 80% of the temperature sensitivity of the PV modules [25]. From Figure 8, the main root causes for the observed degradation in P_max became clearer, unlike in Figure 5. That is, the β_Voc and β_Vmpp of the PV modules are the main underlying causes of the P_max degradation.

Figure 8 also suggests that degradation in β_FF is significantly responsible for the degradation in P_max. This supports the earlier observation in Figure 5 that the solar panels affected by PID experience large resistance losses. Degradation in β_Voc and β_FF due to PID effects were reported earlier [20,26,28]. Figure 8 also shows clear outliers for β_Pmax, β_Voc, β_Vmpp, and β_FF. It could be seen that the majority of these outliers are correlated to higher temperature coefficient values which results from higher T_m [38]. This suggests that when T_m increases, the reliability of PV modules affected by PID decreases, as observed elsewhere [24,39].

Conceptually, the effect of T_m on P_max could be derived from Equation (3) because PV module parameters (V_oc, I_sc, FF) depend strongly on T_m [30,32,40]. Hence, could be represented as

$${\beta }_{\mathit{Pmax}}={\beta }_{\mathit{Voc}}+{\beta }_{\mathit{Jsc}}+{\beta }_{\mathit{FF}}$$

(6)

Interestingly, each of these parameters in Equation (5) depends on different loss mechanisms in the PV module [25,35]. These loss mechanisms mainly depend on the effects of different defects and fault mechanisms on the charge carrier generation-recombination balances at maximum power point (MPP) [35,41]. Therefore, Equations (1) and (5) could be represented in terms of V_mpp and I_mpp as

$${\beta }_{\mathit{Pmax}}={\beta }_{\mathit{Vmpp}}+{\beta }_{\mathit{Jmpp}}$$

(7)

The V_oc is the charge carrier generation-recombination characteristic of a solar panel. So, the temperature sensitivity of a solar panel improves when the V_oc increases [40,42]. Moreover, the β_Voc of a PV module accounts for 80–90% of the β_Pmax of the PV module [25]. For that matter, and inferring from Equation (6), β_Vmpp could be assumed to have the greatest impact on the degradation in β_Pmax, and hence, on P_max degradation. The correlation of values of β_Voc and β_Vmpp to β_Pmax degradation is shown in Figure 9. In Figure 9, the regression plots show high correlation of R² > 90 and R² > 88 for β_Voc and β_Vmpp, respectively. Indeed, Figure 8 and Figure 9 suggest that the root causes of degradation in the PV modules affected by PID are more accurately profiled using their temperature coefficients. They suggest that the β_Voc and β_Vmpp are the underlying factors for the degradation in the efficiency of the solar panels.

In Figure 9a,d, the slopes of the regression plots for PV Module A are 0.14 and 0.19 for β_Voc and β_Vmpp, respectively. However, the average of the slope values of β_Voc and β_Vmpp is ca. 0.17. Interestingly, from Figure 9, the slopes of PV Modules B and C for both β_Voc and β_Vmpp regression plots are ca. 0.17. Also, the slopes of the regression plots for β_Vmpp are closer to the average 0.17 value. Hence, we can predict the behaviour of β_Pmax better with the slopes of β_Vmpp for the PV modules affected by PID. This suggests that a unit change in β_Pmax is accounted for by 0.17 change in either β_Voc or β_Vmpp for each PV module affected by PID. The values of the slopes from the regression plots of β_Pmax versus β_Voc and β_Vmpp can be used to monitor PID severity in solar panels. On that basis, Figure 9 suggest that the effect of PID on PV Module A is the severest. Another observation from Figure 9d–f is that, when β_Pmax is zero, then by extrapolation, β_Vmpp will be ca. 0.4%/°C, 0.6%/°C, and 0.6%/°C for PV Module A, B, and C, respectively. These values are very close to the β_Vmpp values for the 3 field-aged PV modules in

Table 4. Average temperature coefficients of the 3 solar panels.

PV Module	Temperature Coefficient (%/°C)
	βVoc	βJsc	βFF	βηm	βVmpp	βJmpp
A	−0.4	0.02	−0.2	−0.5	−0.5	−0.06
B	−0.4	0.03	−0.1	−0.5	−0.4	−0.09
C	−0.4	0.01	−0.2	−0.5	−0.5	−0.02

.

Figure 10 shows the profiles of the temperature coefficients of efficiency, η_m (β_ηm) of the 3 solar panels. The average of β_ηm has been found to be ca. −0.5%/°C for the 3 field-aged PV modules. In literature, the β_ηm for mc-Si PV modules is 0.4%/°C [25,26,28,29,30]. PV modules in good conditions are expected to be more efficient when PV module operating temperature (T_m) drops below 25 °C [30,32]. However, by extrapolation when T_m is equal to zero, η_m < 13%, refer to Figure 10. This is characteristic of degraded PV modules which are suffering from resistive losses [20,26,40].

The average temperature coefficients of the 3 solar panels are shown in Table 4. The observed values for β_Voc and β_Vmpp agree with the values reported by King et al. [30] for conventional mc-Si PV modules. However, the β_Voc values are far less than the −1.2%/°C reported by Cheng et al. [38] and the −0.7%/°C reported by Wang et al. [24] for PV modules affected by PID. On the other hand, the β_Jsc values are relatively lower for these PV modules that have been affected by PID than observed elsewhere [24,38]. This suggests that in solar panels affected by PID, the contribution from thermally generated electrons towards the overall current density is less.

In addition, the β_FF values for the 3 field-aged PV modules are lower than the −0.4%/°C reported for β_FF by Cheng et al. [38] for solar panels affected by PID. The fact that the modules studied by Cheng et al. [38] were aged artificially whiles our modules were field aged should not be ignored. Comparison of lab and field results are to be done with caution due to factors of uncertainty [43,44]. Our values are also in a good agreement with the −0.2%/°C reported for β_FF by Wang et al. [24] for solar panels affected by PID.

Interestingly, the β_Jmpp of all the 3 solar panels show negative values. It is believed that the negative β_Jmpp values observed for the 3 old solar panels is due to the large leakage current experienced by PV modules affected by PID. Indeed, earlier investigation on the temperature profiles of solar panels affected by optical degradation indicated that negative β_Jmpp values are likely when the electrical circuit of the module is affected. However, in such cases, the β_Jmpp values are relatively higher and the β_Jsc values are by far higher as well. In that investigation, one of the modules affected by optical degradation showed a β_Jmpp of −0.01%/°C and an average β_Jsc for the 3 modules was 0.05%/°C. Moreover, a majority of the darker cells in the EL and warmer cells in IR thermal images were closer to the edge of the PV module affected by optical degradation. This suggests that the module in question is affected by at least optical degradation and PID. It is known that PID can lead to optical degradation and vice versa [5].

Furthermore, an earlier investigation on some of the solar panels under partial shading conditions, negative β_Jmpp values were observed for the modules investigated. However, under partial shading conditions, beside the peculiar I-V characteristics, the degradation in the P_max strongly depends mainly on the degradation in the β_Jmpp and β_FF. Moreover, under partial shading conditions, the effect on β_ηm becomes far higher, with β_ηm ≥ −0.6%/°C [33]. It therefore suggests that an effective, quick, and reliable method of detecting PID in solar panels is to monitor the temperature coefficients, and specifically, the β_Jmpp of PV panels.

4. Conclusions

The temperature coefficients of 20 years old field-aged mc-Si PV modules which were affected by PID were investigated. Characterization utilized I-V characterization, EL imaging, IR thermal imaging, and temperature coefficient profiling. The results showed that the field-aged PV modules were indeed affected by PID. EL images acquired under 0.1I_sc indoor conditions show degraded darker cells located closer to the perimeter of the PV modules. The weak signal of the cells closer to the edge of the modules is due to strong ohmic shunting of the solar cells with the PV module’s Al- frame. In the IR thermal images acquired under clear sky conditions, majority of the warmer cells (hotspots) were seen closer to the perimeter of the modules. In addition, areas closer to the negative terminals were also observed to be warmer than areas closer to the positive terminals. Our results show that the module ∆T due to PID ranges from 7 °C to 15 °C for the 3 old solar panels.

The modules show an average degradation of 0.5%/year in both I_sc and V_oc, 1.2%/year in P_max, and 0.3%/year in fill factor. For the 3 field-aged PV panels, the average degradation in the V_mpp and I_mpp were 0.7% and 0.6% per year, respectively. It turns out that the key underlying causes for PID in the field-aged PV modules and the subsequent degradation is degradation in V_oc, V_mpp, and FF. The average temperature coefficients of β_ηm, β_Voc, β_Jsc, β_FF, β_Jmpp, and β_Vmpp were found to be −0.5%/°C, −0.4%/°C, 0.02%/°C, −0.2%/°C, −0.06%/°C, and −0.5%/°C, respectively. This shows that all the temperature coefficients of the field-aged modules have undergone some form of degradation. However, it was observed that the β_Voc, β_Vmpp, and β_FF were the primary factors for the degradation in the P_max for the old solar PV panels affected by PID. This translated into an average 1.2%/year overall degradation in the efficiency of these modules.

Most interestingly, it was observed that solar panels affected by PID show negative β_Jmpp due to large leakage currents. Hence, PID could be detected decisively by monitoring the β_Jmpp of solar PV panels. These findings have the potential of enhancing the existing knowledge on defects and faults diagnostics in PV arrays.