ABSTRACT

In order to meet the world's energy needs and combat climate change, solar energy has become a viable and eco-friendly substitute for traditional fossil fuels. This project uses PV Lib-Python, a sophisticated open-source framework for modeling and analyzing solar energy systems, to simulate solar photovoltaic (PV) systems. To evaluate a photovoltaic system's performance and power output, the simulation incorporates important environmental and geographic factors such sun irradiation, temperature, latitude, longitude, and time.

PV Lib makes it possible to accurately calculate sun position, irradiance components, and system performance by utilizing mathematical models and real-world meteorological data. The tool is useful for system design, optimization, and feasibility analysis since it makes it easier to assess solar panel performance in various climatic circumstances. To see patterns in energy production and evaluate possible solar generation, users can enter specified parameters in this simulation, such as location (e.g., Chennai), system capacity, and date periods. The results help in understanding how solar panels would perform if installed at a given location, even without physically connecting hardware. Overall, the project shows how software-based simulation may enhance energy planning, encourage the adoption of clean energy technology, and support decision-making in the implementation of renewable energy. One of the most promising renewable energy options for sustainable power generation is solar photovoltaic (PV) technology. Using PV Lib-Python, a potent package for simulating solar resource data and PV system performance, this project offers

a thorough simulation of solar energy systems. To estimate the electrical energy production of solar panels, the simulation takes into account important factors including solar irradiation, atmospheric conditions, geographic location (latitude and longitude), and system setup. The system accurately forecasts solar energy generation over predetermined time periods by using mathematical models and real-time or historical meteorological records. Users of the application can examine how various environmental factors affect system output and efficiency.

Keywords:

Solar Energy, Photovoltaic System, PV Lib-Python, Solar Irradiance, Renewable Energy, Energy Simulation, Solar Panel Performance, Climate Data Analysis, Power Output Estimation, Geographic Parameters, Sustainable Energy, Solar Modeling, Python Simulation, Green Technology, Energy Optimization