3. Producción
Browse
2 results
Search Results
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, Estimation of the effective nominal power of a photovoltaic generator under non-ideal operating conditions(Elsevier, 2021-12-20)The nominal power is an essential parameter for evaluating the general state of a photovoltaic plant. The American Society for Testing and Materials, the International Electrotechnical Commission and other works propose procedures that allow estimating the nominal power of a photovoltaic generator in outdoor conditions. These procedures generally require monitoring days with ideal conditions, particularly clear sky days with high irradiance values and low wind speeds. These restrictions can limit the available number of monitoring days, especially in places with frequent cloud formations. In this work, a 109.44 kW photovoltaic plant was monitored for six months in Granada, Spain. Its nominal power is first estimated applying a referential procedure reported in the literature for large PV plants under the required ideal climatic conditions. In order to overcome the restrictions for estimating the nominal power, we propose a new procedure applicable not only for ideal but also for non-ideal conditions, such as found on partially cloudy days. This new procedure applies non-parametric statistics to find the most probable value of the nominal power within a single monitoring day. A statistical analysis indicates that it reliably estimates the nominal power at non-ideal conditions while preserving the same estimation accuracy as under ideal conditions. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Assessing the accuracy of analytical methods for extracting parameters of different PV module technologies under clear and cloudy sky conditions(Elsevier Ltd, 2024-12-01)Accurately determining single-diode model parameters yields essential insights into the photovoltaic (PV) device performance and behavior. Analytical methods for extracting these parameters often rely on mathematical assumptions typically valid under controlled indoor conditions. Applying these methods to PV modules in the field introduces complexities due to varying environmental conditions and module technologies, leading to divergencies between parameters extracted under outdoor and indoor conditions. This study closes the gap in analyzing the retrieved parameters under intricate outdoor conditions by differentiating between all-, clear-, and cloudy-sky conditions and varying irradiances for different PV technologies. We examine three methods over a year of outdoor I-V curves from Al-BSF, HIT, and a-Si/µc-Si PV modules in Lima, Peru, a low-latitude site. The findings represent the first mid-term study by the country's premier laboratory uniquely equipped for diverse outdoor PV module characterization. We evaluate the accuracy of each method using the Normalized Root Mean Square Error (NRMSE) by comparing experimental against simulated I-V curves derived from the extracted parameters. Our findings reveal that the parameters for the Al-BSF and HIT modules under all-sky conditions align with reported outdoor trends for varying irradiances, while under clear skies, they correspond with indoor trends. In terms of accuracy, the methods by Phang et al. and de Blas et al. consistently achieve an average NRMSE below 1 % across all PV module types under all-sky conditions. However, when differentiating between sky conditions, the NRMSE values for the Al-BSF and HIT modules are notably lower under clear sky conditions at any irradiance level, preserving a mean value below 0.6 %, unlike the a-Si/µc-Si PV technology, which shows more consistent NRMSE values across all sky conditions and most irradiance levels and in average above 0.7 %. These results demonstrate that selecting sky conditions based on the evaluated PV technology is beneficial for enhanced accuracy in outdoor parameter extraction.