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<p>This paper presents the design, simulation, and experimental validation of a standalone photovoltaic (PV) system featuring integrated smart management of electrical loads and lighting for remote healthcare facilities. Ensuring energy efficiency and service continuity in isolated areas is a critical challenge due to limited grid access and the inherent intermittency of solar radiation. The methodology integrates theoretical single-diode modeling, MATLAB simulations, and physical prototype testing using an ESP32-based embedded platform with Internet of Things (IoT) supervision via the Blynk framework. The developed system integrates a hierarchical load management strategy based on battery state of charge (SOC), enabling prioritized power delivery to critical medical loads. In addition, an adaptive lighting control strategy using PIR (Passive Infrared) motion detection and LDR (Light Dependent Resistor) ambient light sensing allows dynamic regulation of non-essential energy consumption according to occupancy and environmental conditions. A robust experimental validation on a scaled prototype confirms the effectiveness of the proposed approach under representative operating conditions. Results indicate an improvement in battery autonomy of up to 35% under tested conditions, while the adaptive lighting strategy reduces lighting energy consumption by approximately 45%. The system also demonstrates fast dynamic response, with control actions executed in less than one second. A techno-economic and environmental assessment further highlights the practical relevance of the system. The proposed solution reduces operational costs compared to diesel-based alternatives and enables significant environmental benefits, with an estimated reduction of approximately 3.9 tons of CO₂ emissions per year for the studied application. Overall, the proposed system provides a low-cost, scalable, and sustainable framework for enhancing energy efficiency, reliability, and resilience of off-grid healthcare infrastructure in resource-constrained regions.</p>

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Design, simulation, and experimental validation of a smart load and lighting management system for standalone photovoltaic applications in isolated healthcare settings

  • 期刊论文

  • 发表日期：

    2026年7月30日

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  • Djohra Saheb,
  • Leticia Arkam,
  • Ines Haddad,
  • Djedjiga Hatem,
  • Mustapha Koussa,
  • Nasreddine Belhaouas,
  • Hicham Hafdaoui,
  • Nadira Madjoudj,
  • Fateh Mehareb,
  • Amina Chahtou

摘要

This paper presents the design, simulation, and experimental validation of a standalone photovoltaic (PV) system featuring integrated smart management of electrical loads and lighting for remote healthcare facilities. Ensuring energy efficiency and service continuity in isolated areas is a critical challenge due to limited grid access and the inherent intermittency of solar radiation. The methodology integrates theoretical single-diode modeling, MATLAB simulations, and physical prototype testing using an ESP32-based embedded platform with Internet of Things (IoT) supervision via the Blynk framework. The developed system integrates a hierarchical load management strategy based on battery state of charge (SOC), enabling prioritized power delivery to critical medical loads. In addition, an adaptive lighting control strategy using PIR (Passive Infrared) motion detection and LDR (Light Dependent Resistor) ambient light sensing allows dynamic regulation of non-essential energy consumption according to occupancy and environmental conditions. A robust experimental validation on a scaled prototype confirms the effectiveness of the proposed approach under representative operating conditions. Results indicate an improvement in battery autonomy of up to 35% under tested conditions, while the adaptive lighting strategy reduces lighting energy consumption by approximately 45%. The system also demonstrates fast dynamic response, with control actions executed in less than one second. A techno-economic and environmental assessment further highlights the practical relevance of the system. The proposed solution reduces operational costs compared to diesel-based alternatives and enables significant environmental benefits, with an estimated reduction of approximately 3.9 tons of CO₂ emissions per year for the studied application. Overall, the proposed system provides a low-cost, scalable, and sustainable framework for enhancing energy efficiency, reliability, and resilience of off-grid healthcare infrastructure in resource-constrained regions.