Soiling

Raptor Maps analyzed 24.5 GW of large-scale solar assets and determined that power losses due to equipment anomalies nearly doubled from 1.61% in 2019 to 3.13% in 2022. At the module level, cell and diode anomalies were the most common issues, it said.

Virtuous-Re’s new PVradar Cleaning App can reportedly model soiling losses and cleaning benefits, while reducing cleaning costs and maximizing the overall economic performance of projects.

The two dominant methods used in the industry to estimate soiling levels on solar projects go some way in mitigating losses, but there is plenty of scope for more accurate observation.

A new report by the International Energy Agency’s Photovoltaic Power Systems Programme (IEA-PVPS) estimates that lost revenue from PV module soiling amounts to more than €3 billion ($3.2 billion) per year – an amount that is only set to increase as PV systems grow larger and more efficient.

Israel’s scarce land resources and lack of interconnections to neighboring countries have driven the rise of rooftop solar. Now a number of recent policy changes, mainly due to electricity reforms, are set to reinforce the decentralization trend, reports Ilias Tsagas.

A first-of-its-kind survey has revealed the extent to which automation and robot module cleaning is being adopted by large-scale PV project owners and operators. And the trend is clear; as solar expands geographically and projects grow, the use of robotics in solar operations and maintenance (O&M) is increasing, and the level of understanding as to their benefits is on the rise. Ecoppia, a pioneer in the robotic cleaning segment, partnered with pv magazine on the survey and the results speak volumes.

India-based Solavio has developed the Eco Bot portable and shareable robotic cleaning solution, which is compatible with ground-mounted solar arrays and rooftop PV installations.

Cost efficiency while maximizing power output is the name of the game in solar project development and asset management. And the automation of the provision of utility scale solar operations and maintenance (O&M) is fast becoming one of the most compelling opportunities. Help shape the future of automation in solar O&M by completing this first-of-its kind survey.

Scientists in the United States used machine learning to analyze maintenance reports, performance data and weather records from more than 800 solar farms located across the country. The analysis allowed them to determine which weather conditions have the biggest impact on PV generation, and to suggest the most effective ways to boost the resilience of PV installations to extreme weather events.

A group of scientists in Bangladesh has developed a model to determine the optimal cleaning schedule for a PV installation at any location in the globe, requiring only the average insolation and soiling rate for a given site to make the calculation. The study also draws new conclusions regarding the influence of sandstorms and rain on soiling, and aims to be among the first studies to paint a global picture of soiling trends by region.