Kamal-Shirupa/Photovoltaic-Power-Forecasting-using-Hybrid-Model
Our project focuses on forecasting photovoltaic (solar) power generation using a hybrid model of Gradient Boosting and LSTM. It predicts solar output with high accuracy, optimizing energy usage, improving grid stability, and enhancing renewable energy integration.
This tool helps energy managers and grid operators predict how much power solar panels will generate. You feed it historical solar generation data and weather information, and it outputs highly accurate forecasts of future solar power output. This allows for better energy planning, optimizes energy usage, and helps integrate renewable energy into the grid more smoothly.
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Use this if you need to reliably forecast solar power output to manage energy resources, optimize grid stability, or integrate renewable energy more effectively.
Not ideal if you are looking to predict energy consumption from non-solar sources or require forecasts for very short-term, intra-minute fluctuations.
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License
MIT
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Last pushed
Jul 20, 2025
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