Enhancing solar PV efficiency in mining operations through optimized cleaning intervals and automated dust mitigation

Area of Science:

• Energy Science
• Environmental Engineering
• Materials Science

Background:

• Mining operations generate dust, hindering solar photovoltaic (PV) energy utilization.
• Harsh environmental conditions in mining impact the performance and longevity of PV panels.
• Optimizing PV panel cleaning is essential for efficient renewable energy generation in industrial settings.

Purpose of the Study:

• To quantify the seasonal impact of dust deposition on PV panel performance in mining areas.
• To determine optimal cleaning frequencies for PV panels under operational mining conditions.
• To design, develop, and validate an automated dry dust cleaning system for mining environments.

Main Methods:

• A 26-week study monitored dust deposition density and PV panel energy output across three seasonal phases.
• Performance analysis of PV panels under varying dust loads and environmental conditions.
• Validation of an innovative automated dry dust cleaning system in an active mining field.

Main Results:

• Pre-summer phase showed highest dust deposition (5.98 g/m²), reducing maximum power output (Pmax) by 63.50%.
• Recommended cleaning schedules: 3-4 days for pre-summer, 6-7 days for dry winter and early monsoon.
• Automated cleaning system achieved an average Pmax recovery of 40% across different environmental phases.

Conclusions:

• Dynamic cleaning schedules are vital for effective solar energy utilization in the mining industry.
• The developed automated dry dust cleaning system demonstrates significant effectiveness in real-world mining conditions.
• Integration of smart sensors and AI can further enhance sustainable solar energy use in mining.