Photovoltaic inverter maintenance learning

Can machine learning predict the maintenance needs of solar PV plants?

Scientists from Malaysia and Thailand have developed a novel machine-learning model for predicting the maintenance needs of large-scale solar PV plants.

Why is inverter reliability important in a large-scale PV plant?

Abstract: In large-scale PV plants, inverters have consistently been the leading cause of corrective maintenance and downtime. Improving inverter reliability is critical to increasing solar photovoltaic (PV) affordability and overall plant reliability.

Can k-means predict the maintenance of large-scale solar photovoltaic plants?

The algorithm was described in the study “ Anomaly detection using K-Means and long-short term memory for predictive maintenance of large-scale solar (LSS) photovoltaic plant ,” which was recently published in Energy Reports.

Why are inverters a problem at photovoltaic sites?

Inverters are a leading source of hardware failures and contribute to significant energy losses at photovoltaic (PV) sites.

Why is inverter reliability important?

Conferences > 2023 IEEE 50th Photovoltaic S... In large-scale PV plants, inverters have consistently been the leading cause of corrective maintenance and downtime. Improving inverter reliability is critical to increasing solar photovoltaic (PV) affordability and overall plant reliability.

How can machine learning help reduce PV site failures?

Advanced implementations of machine learning techniques coupled with standardization of asset labels and descriptions can extend these insights into actionable information that can support development of algorithms for condition-based maintenance, which could further reduce failures and associated energy losses at PV sites.