Semi Rotating Solar Panel with Inverter Circuit For Optimum Power Generation With Monitoring Over IOT Platform

Abstract

TheDualAxisSolarTrackerisan innovativeand efficient solution aimedat maximizing solar energycaptureby dynamically adjusting the orientation of solar panels. Solar energy has emerged as one of the most promising renewable energysources,butitseffectivenessisdirectlyinfluencedbythe positioning of solar panels relative to the sun’s movement. Traditional fixed solar panel systems can only generate peak energywhenthesunisdirectlyoverhead,leadingtosuboptimal energy capture during other parts of the day. To address this limitation, the Dual Axis Solar Tracker is designed to continuouslytrackthesunacrossbothhorizontal(azimuth)and vertical (elevation)axes, ensuringoptimal exposuretosunlight throughout the day and across varying seasons.At the core of this system is the NodeMCU microcontroller, which processes real-time data from Light Dependent Resistor (LDR) sensors to determine the intensity and direction of sunlight. The NodeMCU then controls servo or DC motors to adjust the solar panels’orientation accordingly, allowing them to follow the sun\'s path from sunrise to sunset. This real-time adjustmentensuresthatthepanelsremainalignedwiththesun’s changing position, significantly improving energy collection efficiency by up to 30-40% compared to fixed systems.

Introduction

1. Introduction & Background

Solar energy is a clean, renewable source but its efficiency is highly dependent on the orientation of solar panels to the sun. Fixed panels can't adjust to the sun's changing position throughout the day and year, leading to reduced energy capture.

To address this limitation, a Dual Axis Solar Tracker system is proposed, which dynamically adjusts the panel's angle along both horizontal (azimuth) and vertical (elevation) axes. This tracking ensures maximum solar exposure from sunrise to sunset, improving overall energy output by 30–40% compared to fixed systems.

2. System Overview

• Core Components:

  • NodeMCU microcontroller: Processes sensor data and controls motors.

  • LDR sensors: Detect sunlight intensity and direction.

  • Servo/DC motors: Rotate the panel to align with the sun.

  • Buck converter: Manages and regulates battery charging.

  • Temperature & humidity sensors: Monitor environmental conditions.

  • Blynk IoT platform: Enables real-time remote monitoring via a mobile app.

3. Problem Statement

Fixed solar panels lack adaptability to the sun’s movement, leading to:

• Inefficient energy capture.

• Lower return on investment.

• Greater reliance on fossil-based power backup systems.

Solution: A dual-axis tracker that auto-aligns panels based on sunlight direction, supported by real-time monitoring and control via IoT.

4. Objectives

1. Maximize solar energy capture with two-axis tracking.

2. Enhance system efficiency by aligning with sunlight continuously.

3. Enable real-time monitoring (battery, performance, environment).

4. Improve battery life using a buck converter.

5. Provide user-friendly remote access via Blynk app.

6. Monitor environmental factors for performance optimization.

7. Ensure reliability and reduce maintenance needs.

5. Literature Review Highlights

• Fixed panels lose 15–25% efficiency due to static orientation (Kalogirou, 2004).

• Single-axis trackers increase output by 10–20%.

• Dual-axis trackers improve output by up to 40% (Gupta & Mittal, 2017).

• LDR + servo-based trackers show substantial gains in real-world prototypes.

• Buck converters are essential for efficient, safe battery management (Singh & Rao, 2018).

• Though costlier upfront, dual-axis systems yield long-term benefits via higher energy output (Aly & Fayek, 2020).

6. System Architecture & Components

• Solar Panel Array: Converts sunlight to electricity.

• LDR Sensor Array: Detects sunlight direction.

• Servo Motors: Adjust panel angles.

• NodeMCU: Controls the system and connects to the IoT platform.

• Buck Converter: Prevents battery overcharging.

• Battery: Stores energy for non-sunny hours.

• Blynk IoT App: Displays real-time data (panel position, voltage, environment).

• Temperature & Humidity Sensors: Help with maintenance planning.

7. Software & Development

• Arduino IDE used to program the NodeMCU:

  • Reads LDR values.

  • Controls motor positions.

  • Monitors temperature, humidity, and battery voltage.

  • Sends data to Blynk for real-time remote access.

• Blynk App Dashboard includes:

  • Solar panel orientation.

  • Battery charge status.

  • Environmental data.

  • Alerts/notifications.

8. System Assembly & Calibration

• Panels mounted on a frame movable in both axes.

• Motors installed for actuation.

• Sensors positioned for accurate sun detection.

• NodeMCU and battery housed in a protective enclosure.

• Calibration steps include:

  • Fine-tuning motor limits.

  • Testing LDR response.

  • Verifying buck converter output.

  • Validating real-time data flow to Blynk app.

9. Benefits

• Up to 40% more energy efficiency.

• Real-time data access for users.

• Battery health optimization.

• Enhanced environmental resilience.

• Reduced maintenance through intelligent monitoring.

Conclusion

1) TheDual-AxisSolarTracker system representsa significant leap forward in the realm of solar energy technology, offering an effective and sustainable solution to the challenges of optimizing solar panel efficiency. Unlike traditional fixed solar installations,thisadvanced tracking system continuouslyadjusts theposition of solar panels in both horizontal (azimuth) and vertical (elevation) directions, ensuring that they maintain optimal alignment with the sun throughout the day and across different seasons. 2) At the heart of this system is the NodeMCU microcontroller,which seamlesslyprocessesdata from Light Dependent Resistor (LDR) sensors to detect sunlight intensity and direction. The NodeMCU drives servo or DC motors to accurately reposition the panels, enabling real- time adjustments that maximize energy collection. 3) The integration of additional features such as a buck converter for battery management, and environmental sensors for temperature and humidity monitoring, further enhances the system’s efficiency, durability, and ease of maintenance. The buck converter regulates battery charge levels, preventing overcharging or depletion, thereby extending the overall lifespan of the battery. 4) Remote control and monitoring via the BlynkIoT platform offer unparalleled user convenience, allowing for real-time access to system performance data, battery levels, and environmental conditions. This level of connectivity ensures that users can manage and troubleshoot thesystem from virtuallyanywhere, reducing downtime and enhancing operational reliability.

References

[1] S.A.Kalogirou,SolarEnergyEngineering:Processes and Systems, 2nd ed. Academic Press, 2013. A comprehensive guide to solar energy technologies, includingthedesign andoperation ofsolar panelsand tracking systems. [2] G. S. Kumar, P. Parameshachari, Implementation of Dual Axis Solar Tracker System Using Arduino, International Journal of Engineering Research & Technology(IJERT),vol.9,issue12,pp.67-71,2020. Describes the implementation of a solar tracking system usingmicrocontrollersand discusses efficiency improvements. [3] N.A.Wahab,M.N.Husain,DesignandAnalysisofa Dual-AxisSolarTrackingSystemwithHybridControl Techniques,JournalofSolarEnergyEngineering,vol.142, no. 5, pp. 51-59, 2020. Discusses hybrid control techniques for improving solar tracking system performance. [4] BlynkIoT Documentation https://docs.blynk.ioTOfficialdocumentationfor settingupandusingBlynkIoT with various microcontrollers like NodeMCU. [5] M. J. Clifford, D. Eastwood, Design of a Low-Cost Dual-Axis Solar Tracker System, Proceedings of the 2017 International Conference on SustainableEnergy Technologies (ICSET), pp. 123-128, 2017. Discusses the technical design and cost analysis of a dual-axis solar tracking system. [6] J. J. Carrasco, M. Z. Sanjaya, Development of IoT- Based Dual Axis Solar Tracking System,InternationalJournalofAdvancedComputer andApplications(IJACSA),vol.11,issue5,pp.221-227,2020.AstudyonthedevelopmentofIoT- based solar tracking systems, focusing on remote control and monitoring features. [7] J. Rizk, Y. Chaiko, Solar Tracking System: More Efficient Use of Solar Panels, World Academy of Science,EngineeringandTechnology, vol. 7,no.2,pp. 133-137, 2008.Analyze the efficiency gains of using tracking systems for solar panels compared to fixed installations. [8] M. G. Villalva, J. R. Gazoli, E. Ruppert, ComprehensiveApproach to Modelingand Simulation of PhotovoltaicArrays, IEEE Transactions on Power Electronics, vol. 24, no. 5, pp. 1198-1208, 2009. Provides insights intothe modelingand simulation of solar PV systems, relevant for understanding system efficiency and performance. [9] T. Markvart, L. Castañer, Solar Cells: Materials, Manufacture and Operation, Elsevier, 2005. A key resource on the underlying materials and operational mechanisms of solar cells, including tracking system integration.

Copyright

Copyright © 2025 Sakshi Fulari, Abhinetri Patil, Arpita Sardeshmukh, Vaishnavi Zagade, Bhanu Pratap Singh . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.