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<p>Photovoltaic (PV) systems are extremely prone to wear and tear and physical damage due to large variation in environmental conditions. Integration of real-time monitoring systems with PV would be highly advantageous in detecting early faults and performance degradation consequently leads to timely maintenance and repair. This can also reduce recurring cost, enhance reliability, efficacy, and performance of PV systems that eventually lead to generation of sustainable energy. This study presents a cost-effective solution that uses the Internet of Things (IoT) for real-time monitoring of PV systems and for optimizing maximum power point tracking (MPPT). A fuzzy logic-based algorithm is used in hardware to track the MPPT and process data. Furthermore, the developed solution is experimentally validated on a real system under varying outdoor conditions. The developed system is found to be 99.4% efficient in the real experimental setup under outdoor conditions. The simulated outcomes closely match the experimental results, and the developed hardware can adjust the duty cycle for MPPT tracking across varying irradiance levels.</p>

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Toward smarter solar: IoT and fuzzy logic for real-time maximum power point tracking and monitoring of photovoltaic systems

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月5日

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  • Pratibha Sharma,
  • Nishakant Kalia,
  • Mamta Awasthi,
  • Sanjay Kumar,
  • Lalit Ranakoti,
  • Meizi Wang,
  • Gusztáv Fekete

摘要

Photovoltaic (PV) systems are extremely prone to wear and tear and physical damage due to large variation in environmental conditions. Integration of real-time monitoring systems with PV would be highly advantageous in detecting early faults and performance degradation consequently leads to timely maintenance and repair. This can also reduce recurring cost, enhance reliability, efficacy, and performance of PV systems that eventually lead to generation of sustainable energy. This study presents a cost-effective solution that uses the Internet of Things (IoT) for real-time monitoring of PV systems and for optimizing maximum power point tracking (MPPT). A fuzzy logic-based algorithm is used in hardware to track the MPPT and process data. Furthermore, the developed solution is experimentally validated on a real system under varying outdoor conditions. The developed system is found to be 99.4% efficient in the real experimental setup under outdoor conditions. The simulated outcomes closely match the experimental results, and the developed hardware can adjust the duty cycle for MPPT tracking across varying irradiance levels.