The AI Powered Solar Energy Management System (AI-SEMS) is an intelligent and efficient solution designed to optimize solar power generation, storage, and utilization using Artificial Intelligence (AI), Battery Management System (BMS), MPPT control, and IoT technologies. The system integrates solar panels, a MOSFET-based MPPT charging circuit, a 12V battery pack, inverter, sensors, and cloud monitoring to ensure maximum energy efficiency and battery life. In this system, solar energy is captured from the solar panel and processed through a MOSFET-based MPPT (Maximum Power Point Tracking) circuit to extract maximum available power. The charging circuit regulates and stores this energy in a rechargeable battery pack. The inverter converts the stored DC power into AC power to drive AC loads. A relay controlled by the Raspberry Pi manages battery charging and load switching operations. The Raspberry Pi acts as the main controller and performs intelligent energy management by analyzing real-time data from voltage and current sensors. It calculates key battery parameters such as State of Charge (SOC) and State of Health (SOH). Based on these parameters, the system automatically controls charging/discharging cycles to improve battery performance and lifespan. Multiple sensors including solar voltage and current sensors, battery voltage and current sensors, DHT11 (temperature and humidity sensor), and light intensity sensors continuously monitor environmental and electrical parameters. The system also measures PWM signals, efficiency, and overall system performance. All real-time data such as solar voltage, solar current, battery voltage, battery current, SOC, SOH, temperature, humidity, light intensity, PWM duty cycle, and efficiency are uploaded to the ThingSpeak cloud platform for remote monitoring and data visualization. The LCD display shows live system status locally, while a buzzer provides alerts during abnormal conditions such as overvoltage, overheating, or low battery levels. By integrating AI-based predictive analytics with IoT cloud monitoring, the proposed system enhances energy utilization efficiency, ensures optimal battery health, enables smart load management, and provides real-time remote monitoring. This makes the AI-SEMS highly suitable for smart homes, renewable energy systems, and sustainable power management applications.          

Main Objectives:  

• To maximize solar energy utilization by implementing a MOSFET-based MPPT controller for efficient power extraction from solar panels.
• To monitor and manage battery health by calculating State of Charge (SOC) and State of Health (SOH) using an intelligent Battery Management System (BMS).
• To implement AI-based energy management for optimizing charging, discharging, and load control operations to improve overall system efficiency.
• To provide real-time monitoring and remote access of solar, battery, and environmental parameters through IoT cloud platforms such as ThingSpeak.
• To enhance the reliability and sustainability of renewable energy systems through smart load management, fault detection, and efficient energy storage utilization.

        The major building blocks of this project are:

• Power supply.
• Raspberry pi.
• SOLAR Panel.
• Charging circuit.
• Temperature sensor.
• Voltage sensor.
• Current sensor.
• Light Intensity Sensor/
• DHT11(temperature & humidity) sensor.
• Buzzer.
• 12v Battery pack.
• Relay.
• LCD display.
• LED Indicators
• MPPT module.
• ESP8266 wi-fi module.

    Software’s used in the project:

1. Raspbian OS.
2. Python language.
3. Express SCH for Circuit design.
4. Machine learning (ML).

     

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