Dheeraj of Indian Institute of Technology Roorkee (IITR)

Renewable energy, particularly solar photovoltaics (PV), is increasingly vital due to its cleanliness, affordability, and abundance. However, solar PV output depends on variable factors like temperature and irradiance, necessitating intelligent forecasting models for effective energy management. This study leverages artificial intelligence, specifically long short-term memory (LSTM) and backpropagation neural networks (BPNN), to enhance renewable energy forecasting in smart grids. By integrating real-time IoT sensor data with historical trends, our weather-based LSTM model predicts solar PV power output with high accuracy, outperforming BPNN in metrics like MAE, MAPE, RMSPE, and R2 score. The framework optimizes grid operations, enhances PV plant efficiency, and ensures grid stability under diverse conditions. Results show a 20% improvement in forecasting accuracy, enabling proactive energy management. This research highlights AI’s role in building resilient smart grids, fostering sustainable energy ecosystems

Biography:

Dr. Dheeraj Kumar Dhaked is a CHANAKYA Postdoctoral Fellow at IIT Roorkee, specializing in sustainable energy systems and AI-driven optimization. Holding a Ph.D. (2023), He has published over 25 Scopus/SCI-indexed papers, garnering 295+ citations, and secured a patent for innovative energy solutions. His current project focuses on developing digital twins for battery-based energy systems in electric vehicles, leveraging expertise in Python, TensorFlow, and machine learning models like LSTM and CNN. A recipient of the Young Researcher Award at an international conference. He has also edited book proposals for Elsevier and Springer. With a passion for renewable energy and smart grid resilience, he aims to advance energy efficiency and explore commercial ventures in sustainable technologies.

Email:

Address:Indian Institute of Technology Roorkee (IITR), Roorkee, Uttarakhand, India, 247667