Solar Tracking System for Efficient Power Generation using Image Processing

• Published in: International journal for research in applied science and engineering technology 2022-08, Vol.10 (8), p.1304-1310
• Main Authors: Kamat, Mohit, Keni, Rahil, Helekar, Mahip, Dhavjekar, Shaivik, Patil, Pranav, Bhogan, Snehal, Narveka, Ashish
• Format: Article
• Language: English
• ISSN: 2321-9653; 2321-9653
• DOI: 10.22214/ijraset.2022.46412

The emerging era is energy demanding and there is a drastic need to shift to more eco-friendly methods for power generation. The non-renewable resources generate 86% of the world's power. Around the world, coal and gas power plants are shutting down due to lack of fuel. With more and more industries and governments joining the Green Movement, the demand for cost effective renewable energy has surged. Solar power can be easily harnessed as compared to other eco-friendly methods, using solar panels and the conventional process of converting solar energy to electrical energy. Even though solar power is used in domestic as well as industrial applications, it is still a long way from making an impact on environmental change. Since solar panels can only be utilized up to their full potential in clear sky and sunny conditions, its usage is affected by geographic location. However, even in conditions of optimal usage, it's not used up to its full potential. As all solar panels are fixed due sunny side, they receive direct sunlight only for half a day. During the other half, the sun is behind the panels and hence, the power generation drops steadily. To rectify this, we introduce the principle used by sunflowers. Sunflowers intake energy by following the sun from sunrise till sunset. Using the same concept, we make the panels follow the sun resulting in significant increase in energy production. We take images of the sun throughout the day, using image processing make sure that the sun is directly incident to the panels, follow this procedure till sunset. This method makes sure that even in conditions of slight to moderate overcast weather, the sun will be directly incident on panels, such is the power of image processing. The status of the device as well as energy generated can be easily visualized using the mobile application provided. The system can further be made cost effective by modifying the existing panels. The concept is simple yet very efficient, robust and scalable. This method can be used for domestic as well as industrial applications. In optimal conditions, this method can generate up to 40% more energy than a conventional solar panel system of the same size. In conclusion, just by learning from nature, using only a gearbox and controller in addition to panels, we can generate significantly more electricity. In addition to this method, using most efficient solar panels that give maximum power output even in overcast conditions can further increase po