Uncertainty analysis of degradation parameters estimated in long-term monitoring of photovoltaic plants (original) (raw)
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ACTA IMEKO
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How accurate is a commercial monitoring system for photovoltaic plant?
Progress in Photovoltaics: Research and Applications, 2012
According to uncertainty calculations, the values recorded by means of commercial monitoring systems are expected to be less accurate than those recorded by a system optimized for the measurement of electrical parameters-the so-called dedicated system (DS). This study aims to verify if a larger expected uncertainty for commercial system (CS) actually turns into a larger spread of the measurements around the true value. In the Airport Bolzano Dolomiti plant, CS and DS are installed on the same photovoltaic arrays. The comparison performed considers the detailed uncertainty budget for the two systems using three performance indicators-energy, yield and performance ratio. Results show that the uncertainty level of the CS is much larger; for example, on performance ratio, it is about four times larger with respect to the optimized one (respectively AE16% and AE4%). Three sources mainly contribute to the uncertainty: measurements of irradiance, current and voltage. The measured values of the electrical parameter are compared in order to verify if the results of the budget calculations turn into a real difference. Results show that the CS is accurate in measuring current and voltage, respectively,~2% and~5% of difference from the DS, but not for irradiance-here, the difference is higher than 10%. In particular, the irradiance measured by the CS is systematically smaller; therefore, the performance ratio calculated through the CS is always overestimated and often larger than 100%.
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Over the last 20 years, the statistical average performance ratio of a new photovoltaic (PV) installation in moderate climates has improved from 0.65 to approximately 0.85. This continuous improvement in the field would not have been possible without operational monitoring and the continued analysis of monitoring data by the PV system community. The paper starts with a historical review of the performance of PV systems. It documents the current state of the art and good practices in PV system monitoring. Finally, it presents periodic linear regression as a simple though systematic approach for the visual and mathematical analysis of monitoring data.
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International Journal of Electrical and Computer Engineering (IJECE), 2024
The operation and maintenance activities in photovoltaic systems use meteorological and electrical measurements that must be reliable to check system performance. The International Electrotechnical Commission (IEC) standards have established general criteria to filter erroneous information; however, there is no standardized process for the evaluation of measurements. In the present work we developed 3 procedures to detect and correct measurements of a photovoltaic system based on the single diode model. The performance evaluation of each criterion was tested with 6 groups of experimental measurements from a 3 kWp installation. Based on the error of the 3 procedures performed, the most unfavorable case has been prioritized. Then, the reduction of errors between the estimated and measured value has been achieved, reducing the number of measurements to be corrected. For the clear sky categories, the coefficient of determination is 0.9975 and 0.9961 for the high irradiance profile. Although an increase of 2.5% for coefficient of determination has been achieved, the overcast sky categories should be analyzed in more detail. Finally, the different causes of measurement error should be analyzed, associated with calibration errors and sensor quality. This is an open access article under the CC BY-SA license.
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Accurate economic analysis of photovoltaic (PV) systems performance over the system lifetime requires knowledge of the performance of the PV system as the module and balance of system components age. Accelerated testing and experience with systems install 20 to 30 years ago show that PV modules will work over long periods. Nine years of PV data at Ashland, Oregon are used to determine the degradation in performance at the Ashland site. Three systems at the AEC PV Test Facility are used to study the degradation in performance over a two year period. All the systems have a degradation rate between 0.6 and 1.5% per year. It is determined that with good measurements a degradation rate of one percent can be observed over a two year period. It is unlikely that small rates of degradation can be determined accurately over one year. The accuracy of the rate determined can be improved with high precision irradiance and meteorological measurements.
Statistical Methods for Degradation Estimation and Anomaly Detection in Photovoltaic Plants
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Photovoltaic (PV) plants typically suffer from a significant degradation in performance over time due to multiple factors. Operation and maintenance systems aim at increasing the efficiency and profitability of PV plants by analyzing the monitoring data and by applying data-driven methods for assessing the causes of such performance degradation. Two main classes of degradation exist, being it either gradual or a sudden anomaly in the PV system. This has motivated our work to develop and implement statistical methods that can reliably and accurately detect the performance issues in a cost-effective manner. In this paper, we introduce different approaches for both gradual degradation assessment and anomaly detection. Depending on the data available in the PV plant monitoring system, the appropriate method for each degradation class can be selected. The performance of the introduced methods is demonstrated on data from three different PV plants located in Slovenia and Italy monitored f...
IEEE Journal of Photovoltaics, 2021
A linear performance drop is generally assumed during the photovoltaic (PV) lifetime. However, operational data demonstrate that the PV module degradation rate (Rd) is often nonlinear, which, if neglected, may increase the financial uncertainty. Although nonlinear behavior has been the subject of numerous publications, it was only recently that statistical models able to detect change-points and extract multiple Rd values from PV performance time-series were introduced. A comparative analysis of six open-source libraries, which can detect change-points and calculate nonlinear Rd, is presented in this article. Since the real Rd and change-point locations are unknown in field data, 960 synthetic datasets from six locations and two PV module technologies have been generated using different aggregation and normalization decisions and nonlinear degradation rate patterns. The results demonstrated that coarser temporal aggregation (i.e., monthly vs. weekly), temperature correction, and both PV module technologies and climates with lower seasonality can benefit the change-point detection and Rd extraction. This also raises a concern that statistical models typically deployed for Rd analysis may be highly climaticand technology-dependent. The comparative analysis of the six approaches demonstrated median mean absolute errors (MAE) ranging from 0.06 to 0.26%/year, given a maximum absolute Rd of 2.9%/year. The median MAE in change-point position detection varied from 3.5 months to 6 years.
A Novel Method for Investigating Photovoltaic Module Degradation
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This paper proposes a method for the detection and assessment of the degradation of the photovoltaic modules electrical characteristics such as short-circuit current (I sc), open-circuit voltage (V oc) and maximum output power (P max). This work presents a standardization method for measurements of these characteristics in real conditions. Standardization is bringing back the measurements in real conditions to the corresponding values in standard test conditions (STC). Thus the standardized values of short-circuit current (I sc,stc), the open-circuit voltage (V oc,stc) and the maximum output power (P max) are compared with reference values corresponding to the first putting service of module or the manufacturer's data as in our case. The data collected on a platform of measurements installed at the University of Dakar in Senegal are used to validate our approach. A Period of one operation year f of the PV module is considered. After one year of module operation, we note an average degradation of 10% for the short-circuit current, 2% for the open-circuit voltage. For the maximum output-power no degradation is yet detected at this stage.
Monitoring of Photovoltaic Systems: A case study URERMS Adrar
Algerian Journal of Renewable Energy and Sustainable Development, 2020
The electrical energy generation via the Photovoltaic system is widely utilized in the world especially in the countries where it is characterized by considerable potential of solar energy. PV systems are affected by several factors that can reduce its efficiency such as PV generator aging, failures. Photovoltaic systems monitoring is a important task for guaranteeing the reliability and stability of PV system operation. This paper addresses the monitoring of PV systems in renewable energy research unit in the Saharan region (URERMS) Adrar, through to give an insigth about the methods of measuring, acquisition, data storage of monitored parameters. In addition, the existing problems for insuring the suitable solution.