The Solar Energy Estimator App is a powerful tool for predicting solar energy production based on specific parameters. It allows users to input various parameters such as plant capacity, location coordinates, tilt angle, azimuth angle, and module type. Based on these inputs, the app generates hourly, daily, and monthly solar irradiance values on an inclined plane (GII) and estimates the corresponding solar energy generation.
The primary data source for the application is the PVLIB library, which uses the NASA Power Database.
The user can enter their location coordinates (latitude and longitude), which the app uses to estimate solar irradiance and energy production for that specific location.
The app allows the user to configure their solar panel settings by entering the plant capacity, tilt angle, azimuth angle, and the desired module type. These settings are used to more accurately estimate the energy production.
The app provides solar energy generation values for different time frames: hourly, daily, and monthly. This allows users to understand the variability of solar energy production over time and plan accordingly.
The app generates dynamic charts for visual representation of the estimated solar energy values, using the powerful plotting library, Plotly.
The app leverages the PVLIB Python library to make solar energy predictions. PVLIB provides a set of procedures and functions that allow developers to model solar energy production with a high degree of accuracy.
Upon receiving user input, the app employs PVLIB's solar position algorithm to calculate the position of the sun at various times of the day. The solar irradiance on an inclined plane is then calculated based on these solar positions. Finally, the app estimates solar energy production based on the calculated solar irradiance and the solar panel configuration specified by the user.
The Solar Energy Estimator App is a user-friendly and robust tool for anyone interested in estimating solar energy production. Whether for home use, commercial projects, or academic research, this app provides accurate estimations and insightful visualizations, making the complex task of predicting solar energy generation simple and straightforward.