Estimation of the effective nominal power of a photovoltaic generator under non-ideal operating conditions. (1st January 2022)

• Record Type: Journal Article
• Authors: Angulo, José R.; Calsi, Brando X.; Conde, Luis A.; Guerra, Jorge A.; Muñoz, Emilio; de la Casa, Juan; Töfflinger, Jan A.
• Is Part Of: Solar energy. Volume 231(2022)
• Page Start: 784
• Page End: 792
• Publication Date: 2022-01-01
• Subjects: Solar photovoltaic systems -- Measurement uncertainty -- Statistical analysis -- Condition monitoring -- Nominal Power Estimation; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2021.12.015
• Languages: English
• ISSNs: 0038-092X

Abstract

Highlights: Novel procedure to estimate the nominal power of PV generators. Procedure is based on non-parametric statistics. Nominal power can be estimated under clear and partly cloudy sky conditions. The procedure is suitable for PV generators in operating conditions. An estimation uncertainty below 1% is found under both sky conditions. Abstract: 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.