In home solar panel applications, shade or dirt accumulation is enough to cut the power production by 50%. The problem would be easy to solve, the real issue is that it can go unnoticed for years, given that usually solar panels are in hard to reach areas.
Our project proposes a simple and efficient solution to address the inefficiencies of solar power production in home appliances. We aim to develop a user-friendly device that can be easily implemented on any system, regardless of brand or model. The proposed framework consists of three main steps: data gathering, modeling, and use case.
Firstly, we will gather information in our database through sensors to ensure optimal energy output. We will collect energy data and compare it to the expected output, which is the amount of energy that should be produced given various factors such as geographic location, solar plant setup, weather conditions, and time of the year.
Secondly, we will create a machine learning model that will use the energy data collected by the sensor to compare it to the expected output. The model will be able to predict the energy output and identify any deviations from the expected output.
Finally, we will use the internet of things (IoT) to notify the user through our app if the energy output is significantly lower than the expected output. If this is the case, the user will be notified that something is wrong, such as shading, dirt or electrical issues or others, and will be provided solutions. As these problems will be detected in an early stage typically they will be easier to solve, for instance a good cleaning of the panel can avoid years of energy loss that would go otherwise unnoticed without our service.
The proposed project has a strong scientific component, as we will be using machine learning to analyze energy data and make predictions about energy output. We will also be using IoT to collect data from the device to the cloud to notify the user of any deviations from the expected output.
The commercial potential of this project is significant, as solar energy is becoming increasingly popular and affordable. However, many households face inefficiencies in their solar power production, which leads to higher energy bills and reduced performance. Our solution will provide a cost-effective and user-friendly way for homeowners to address this issue, leading to overall savings and reduction in greenhouse gas emissions.
SunSentry is motivated to participate in this ideation competition because we believe that solar energy is the future. We want to develop an innovative solution that will improve the efficiency and accessibility of renewable energy using our expertise in data science, computer science, engineering, and mechatronics. We are excited about the opportunity to develop a solution that will have a positive impact on the environment and on people's lives.