Solar power generation analysis and forecasting using ANNs
Machine learning models for cost-effective solar power forecasting from real-world data.
Tools: Python, TensorFlow.
This project developed models targeting reliability challenges in solar power generation and investigated cost-effective methods for solar power forecasting. The work applied machine learning models, including LSTM and autoregressive CNN methods, to real-world generation data.
Publication: Solar Power Generation Analysis and Forecasting Real-World Data Using LSTM and Autoregressive CNN