Designing integrated intelligent control systems for photovoltaic cooling and dust panels based on IoT: Kirkuk study, Iraq

Abstract

This study presents an innovative integrated control system to enhance photovoltaic (PV) efficiency in arid regions by addressing two critical challenges: temperature-induced performance degradation and dust accumulation. Focusing on Kirkuk, Iraq, the proposed system integrates two distinct intelligent subsystems powered by IoT technology: an activated water-based cooling mechanism and an activated water-driven dust removal system. Both subsystems employ real-time data from IoT sensors (temperature, humidity, dust density, irradiance) to autonomously optimize operations through a centralized cloud platform. The cooling subsystem utilizes activated water circulated through microchannel networks embedded in PV panels, dynamically triggered by AI algorithms to maintain optimal temperatures. Simultaneously, the dust removal subsystem employs pressurized activated water sprays, activated during the night periods to minimize energy loss, with computer vision algorithms identifying dust distribution patterns for targeted cleaning. This research highlights the synergy between IoT-driven automation, activated water technologies, and dual-control optimization, offering a scalable model for renewable energy systems in arid climates. The framework aligns with sustainable development goals by balancing energy efficiency, water conservation, and cost-effectiveness. Field experiments in Kirkuk demonstrated a 27% increase in energy output and a 40% reduction in maintenance downtime compared to conventional systems. The intelligent scheduling of activated water usage reduced overall water consumption by 30% while achieving 95% dust removal efficiency. Economic analysis confirmed a 22% reduction in operational costs due to adaptive resource management and prolonged PV lifespan.