| Ilhami Suleymanov, Nazli Muradova An Intelligent Dust Detection and Protection System (DDPS) for Autonomous Management of Photovoltaic Performance |
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| Abstract. Dust accumulation introduces significant performance degradation in photovoltaic (PV) systems operating under uncertain and dynamic environmental conditions, particularly in arid, remote, and infrastructurelimited regions. Traditional maintenance approaches based on periodic manual inspection or fixed cleaning schedules are inefficient, resource-intensive, and poorly suited for environments where access, water, and human intervention are constrained. This paper presents an information-driven Dust Detection and Protection System (DDPS) for the autonomous management of photovoltaic performance. The proposed system integrates sensor-based environmental monitoring with a predictive reflex control architecture implemented on an embedded microcontroller platform. Instead of relying on predefined schedules, the DDPS continuously evaluates real-time sensor data and triggers cleaning actions only when performance degradation is detected, forming a closed-loop cyber-physical control system. A waterless air-fan cleaning mechanism is employed, and all system components are powered directly by the host photovoltaic panel, enabling complete energy autonomy. Experimental evaluation of a functional prototype demonstrates effective restoration of photovoltaic performance following dust-induced degradation, achieving an average power output improvement of 56.055%. The results confirm that eventdriven, reflex-based control can significantly enhance system efficiency while minimizing unnecessary actuation, energy consumption, and mechanical wear. Beyond its application to solar panel maintenance, the proposed DDPS illustrates a scalable and low-complexity framework for autonomous performance management in complex physical systems. The architecture is applicable to a wide range of cyber-physical and embedded control problems requiring adaptive, real-time decision-making under environmental uncertainty. |
| Keywords: Photovoltaic systems, Autonomous system management, Sensorbased control, Waterless solar panel cleaning, Dust accumulation, Efficiency optimization |
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| DOI: https://doi.org/10.54381/itta2026.4.07 |