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![(a): Using Bathtub curve to explain PV Durability and Reliability Issues [4].](profile/Chibuisi-Okorieimoh-3/publication/353332679/figure/fig1/AS:1047219968946178@1626688105917/a-Using-Bathtub-curve-to-explain-PV-Durability-and-Reliability-Issues-4.png)
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![Figure 1 (b): Multiple failure modes overlap of solar PV modules [4].](profile/Chibuisi-Okorieimoh-3/publication/353332679/figure/fig2/AS:1047219968942083@1626688105974/b-Multiple-failure-modes-overlap-of-solar-PV-modules-4_Q320.jpg)
![Figure 2: Degradation of Solar PV system [1].](profile/Chibuisi-Okorieimoh-3/publication/353332679/figure/fig3/AS:1047219973152768@1626688106006/Degradation-of-Solar-PV-system-1_Q320.jpg)
Solar photovoltaic (PV) panels experience long-term performance degradation as compared to their initial performance, resulting in lower like-per-like efficiencies and performance ratios. Manufacturers of solar photovoltaic modules normally guarantee a lifespan of more than 20 years. To meet such commitments, it is important to monitor and mitigate...
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Context 1
... cause of failure mode A may be due to fundamental design faults, processing issues, errors in manufacturing, or inappropriate installation [4]. Therefore, Passing IEC 61215 or 61646 qualification tests are not proof that a PV module has been tested and shown to be durable and reliable rather the IEC environmental stress test protocols are designed primarily to test the period of early life failures (infant mortality) (see Figure 1 (b)) [6]. Failure mode C: Failure mode C is the constant (random) failures (also, known as normal life). ...
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... daily incident solar radiation for any given location is determined by the sun's path across the sky and the amount of cloud cover in the area ( Trueblood et al., 2013 46 ). Figure 11 (a-d) depicts daytime power profiles at quarter-hourly (15-minute), half-hourly (30-minute), and hourly (60-minute) intervals for three days in each season: a clear day, an overcast day, and a middle day. The clear day, as defined here, is the day of the season with the greatest amount of solar irradiation, resulting in a parabolic curve (see Figure 11 (a-d)); the overcast day is a day with the least amount of solar irradiation, resulting in distortions from perfect parabolic shapes (see Figure 11 (a-d)); and a middle day is a day with the median amount of solar irradiation, resulting in partial parabolic curves. ...
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... daily incident solar radiation for any given location is determined by the sun's path across the sky and the amount of cloud cover in the area ( Trueblood et al., 2013 46 ). Figure 11 (a-d) depicts daytime power profiles at quarter-hourly (15-minute), half-hourly (30-minute), and hourly (60-minute) intervals for three days in each season: a clear day, an overcast day, and a middle day. The clear day, as defined here, is the day of the season with the greatest amount of solar irradiation, resulting in a parabolic curve (see Figure 11 (a-d)); the overcast day is a day with the least amount of solar irradiation, resulting in distortions from perfect parabolic shapes (see Figure 11 (a-d)); and a middle day is a day with the median amount of solar irradiation, resulting in partial parabolic curves. The chosen days of power profiles span the months of each of the four seasons (winter, spring, summer, and autumn) (see Figure 12). ...
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... daily incident solar radiation for any given location is determined by the sun's path across the sky and the amount of cloud cover in the area ( Trueblood et al., 2013 46 ). Figure 11 (a-d) depicts daytime power profiles at quarter-hourly (15-minute), half-hourly (30-minute), and hourly (60-minute) intervals for three days in each season: a clear day, an overcast day, and a middle day. The clear day, as defined here, is the day of the season with the greatest amount of solar irradiation, resulting in a parabolic curve (see Figure 11 (a-d)); the overcast day is a day with the least amount of solar irradiation, resulting in distortions from perfect parabolic shapes (see Figure 11 (a-d)); and a middle day is a day with the median amount of solar irradiation, resulting in partial parabolic curves. The chosen days of power profiles span the months of each of the four seasons (winter, spring, summer, and autumn) (see Figure 12). ...
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... clear day, as defined here, is the day of the season with the greatest amount of solar irradiation, resulting in a parabolic curve (see Figure 11 (a-d)); the overcast day is a day with the least amount of solar irradiation, resulting in distortions from perfect parabolic shapes (see Figure 11 (a-d)); and a middle day is a day with the median amount of solar irradiation, resulting in partial parabolic curves. The chosen days of power profiles span the months of each of the four seasons (winter, spring, summer, and autumn) (see Figure 12). Figure 12 shows that the clear days (as seen in Figure 11 (a-d)) in winter, spring, summer, and autumn were caused by an increase in daily sunshine hours in February, May, June, and September. ...
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... chosen days of power profiles span the months of each of the four seasons (winter, spring, summer, and autumn) (see Figure 12). Figure 12 shows that the clear days (as seen in Figure 11 (a-d)) in winter, spring, summer, and autumn were caused by an increase in daily sunshine hours in February, May, June, and September. Because of the highest amount of solar irradiation at the site location, these days were generally characterized by an increase in PV output generation. ...
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... chosen days of power profiles span the months of each of the four seasons (winter, spring, summer, and autumn) (see Figure 12). Figure 12 shows that the clear days (as seen in Figure 11 (a-d)) in winter, spring, summer, and autumn were caused by an increase in daily sunshine hours in February, May, June, and September. Because of the highest amount of solar irradiation at the site location, these days were generally characterized by an increase in PV output generation. ...
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... a result, PV output generation was moderately high. The overcast day was generally characterized by low solar irradiation due to a decrease in daily sunshine hours, as seen in December, March, August, and November (see Figure 12). As a result, the overcast day generates less PV output. ...
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... Is used to compute the degradation rates (RD) [25]. Figures 13-17 show annual PR regression graphs for five years (2016)(2017)(2018)(2019)(2020) for both temperature-corrected PR and uncorrected PR. Table 4 and Figure 18 show the annual uncorrected system PR, temperature-corrected system PR, degradation rates, and percentage of temperature losses from 2016 to 2020. Figure 17 depicts a decrease in PV power output over time due to the performance loss rate or degradation rate. ...
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... 13-17 show annual PR regression graphs for five years (2016)(2017)(2018)(2019)(2020) for both temperature-corrected PR and uncorrected PR. Table 4 and Figure 18 show the annual uncorrected system PR, temperature-corrected system PR, degradation rates, and percentage of temperature losses from 2016 to 2020. Figure 17 depicts a decrease in PV power output over time due to the performance loss rate or degradation rate. It can be seen using error bars and the Severity ranking of failure mode proposed by Pramod et al [17]. ...
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... 4 and Figure 18 show the annual uncorrected system PR, temperature-corrected system PR, degradation rates, and percentage of temperature losses from 2016 to 2020. Figure 17 depicts a decrease in PV power output over time due to the performance loss rate or degradation rate. It can be seen using error bars and the Severity ranking of failure mode proposed by Pramod et al [17]. ...
Citations
... Identifying and quantifying these trends is essential for accurate performance evaluation and predictive maintenance. Photovoltaic (PV) modules that convert solar energy into electrical energy [1] gradually degrade over time [7] giving reduced output power manifest in a lower performance ratio [8]. The module degradation rate depends on the specification and manufacture of PV modules as well as operational ambient temperatures and their variation, relative humidity, intensity and spectrum of incident solar radiation, wind speed, and extent of exposure to rain, snow, and dust [1]. ...
Photovoltaic (PV) systems are widely adopted for renewable energy generation, but their performance is influenced by complex interactions between longer-term trends and seasonal variations. This study aims to remove these factors and provide valuable insights for optimising PV system operation. We employ comprehensive datasets of measured PV system performance over five years, focusing on identifying the distinct contributions of longer-term trends and seasonal effects. To achieve this, we develop a novel analytical framework that combines time series and statistical analytical techniques. By applying this framework to the extensive performance data, we successfully break down the overall PV system output into its constituent components, allowing us to find out the impact of the system degradation, maintenance, and weather variations from the inherent seasonal patterns. Our results reveal significant trends in PV system performance, indicating the need for proactive maintenance strategies to mitigate degradation effects. Moreover, we quantify the impact of changing weather patterns and provide recommendations for optimising the system's efficiency based on seasonally varying conditions. Hence, this study not only advances our understanding of the intricate variations within PV system performance but also provides practical guidance for enhancing the sustainability and effectiveness of solar energy utilisation in both residential and commercial settings.
