Descriptive and Inferential Statistics for Supervising and Monitoring the Operation of PV Plants

Online model-based fault detection for grid connected PV systems monitoring

“…Model-based fault detection methods include, single-diodebased fault detection approaches [6][7][8], Kalman filter [9], and Fourier series [10]. In single diode model (SDM) based methods, the unknown electrical parameters of the employed PV module are firstly identified using an efficient strategy [1,6], following with maximum power point (MPP) prediction approach based on real onsite climate data measurements.…”

A statistical-based approach for fault detection and diagnosis in a photovoltaic system

“…It is composed essentially of two main approaches: Statistical [7] and Machine Learning [8][9][10] approaches.…”

“…The statistical one has been appeared in applying both descriptive and inferential statistics to detect wiring fault occurrence in PV systems [7]. In addition to the statistical approaches, machine learning ones have gained very remarkable attention in fault detection and diagnosis area.…”

Issues about monitoring the energy performance of a PV plants constellation

“…These hidden anomalies cause two problems: a) produced energy is less than the expected one, then economic revenue is reduced; b) anomalies become failures sooner or later. Paper [2] proposes a methodology to monitor the efficiency of a PV plant and to extract information about its operation. It allows to highlight anomalies also when standard benchmarks (defined in [1]) fail.…”

“…It allows to highlight anomalies also when standard benchmarks (defined in [1]) fail. Descriptive and inferential statistical tools are used in [2]. Also [3] consider statistics for assessing PV plants.…”