How to deal with abnormal power generation of photovoltaic panels

How to detect anomalies in a PV solar power plant?

A new tool (called ISDIPV) is presented by , which is capable of detecting anomalies and diagnosing them in a PV solar power plant. It includes three fundamental operational items for data acquisition, anomaly detection, and diagnosis of the disclosed disparities regarding regular performance.

Can machine learning detect anomalies in photovoltaic systems?

The rapid industrial growth in solar energy is gaining increasing interest in renewable power from smart grids and plants. Anomaly detection in photovoltaic (PV) systems is a demanding task. In this sense, it is vital to utilize the latest updates in machine learning technology to accurately and timely disclose different system anomalies.

Are faults a problem in solar PV systems?

PV faults in solar PV array results significant power loss, lower reliability, very fast panel degradation, and further risk of fire (Gokmen et al. 2013 ). This chapter presents a comprehensive literature review along with a critical analysis of fault diagnosis and condition monitoring for solar PV systems. Major contributions are:

Can machine learning detect abnormalities in solar power plants?

Anomaly detection in modern solar power plants using data-driven approaches is vital in reducing downtimes and increasing efficiency. In this paper, three machine learning models’ performances were analyzed to illustrate the most exemplary model that can precisely determine the abnormalities in the photovoltaic (PV) system.

Can a defect cause power loss in a PV plant?

A defect is an unexpected or unusual happening which was not observed on the PV plant before. However, defects often are not the cause of power loss in the PV plants: they affect PV modules, for example, in terms of appearance (Quater et al.,2014).

Why is anomaly detection important for solar panels?

After abnormalities appear on the exterior of solar panels, if panel holders know the existence of the anomalies sooner, they can eliminate the abnormalities to prevent more power deficiency . Thus, quick and precise anomaly detection methods are significant to improving PV plants’ performance, reliability, and safety.