Cloud Monitoring & IoT Supervision for Photovoltaic Systems

Embedded IoT architecture for real-time photovoltaic monitoring

Overview

This work presents the design and implementation of an embedded monitoring architecture for photovoltaic energy systems.

The proposed platform integrates embedded sensing, local data processing, and cloud-based supervision to enable real-time monitoring of photovoltaic system performance.

The architecture was experimentally validated on a prototype photovoltaic energy platform integrating solar tracking, power electronics, and energy storage.

Embedded Monitoring Architecture

The system relies on a distributed embedded architecture combining low-level sensor acquisition and high-level system supervision.

The monitoring architecture follows a hierarchical structure:

This architecture enables reliable acquisition, processing, and remote visualization of photovoltaic system data.

Multi-Sensor Data Acquisition

The embedded monitoring platform integrates several sensors to characterize the photovoltaic system environment and performance.

Measured variables include:

  • solar irradiance
  • temperature
  • humidity
  • photovoltaic voltage and current
  • system power output

These measurements provide a detailed representation of the photovoltaic system operating conditions.

Embedded Control and Processing

Two embedded platforms are used:

Arduino Nano

Responsible for:

  • real-time sensor acquisition
  • analog-to-digital conversion
  • low-level hardware interface

Raspberry Pi

Responsible for:

  • supervisory control
  • data aggregation
  • communication with remote services

Communication between the embedded devices is implemented using serial and I²C communication protocols.

Cloud-Based Monitoring

The monitoring platform enables remote visualization of the photovoltaic system performance.

Main features include:

  • WiFi data transmission
  • cloud-based data storage
  • remote system supervision
  • graphical data visualization

This architecture enables continuous monitoring and remote diagnostics of the photovoltaic installation.

Experimental Validation

The embedded monitoring system was experimentally evaluated on a real photovoltaic prototype integrating:

  • a monocrystalline photovoltaic module
  • a dual-axis solar tracking mechanism
  • a boost converter charge controller
  • lead-acid battery storage

Outdoor tests confirmed the ability of the system to monitor the photovoltaic platform in real operating conditions.

Scientific Contribution

This work contributes to the development of intelligent photovoltaic energy systems through:

  • design of an embedded monitoring architecture
  • integration of multi-sensor data acquisition
  • implementation of IoT-based energy supervision
  • experimental validation on a real photovoltaic prototype

System Architecture

Conceptual representation of the monitoring system:

This architecture illustrates the integration of embedded systems and IoT technologies in photovoltaic energy platforms.