IEEE

Mid-Term Load Forecasting with Minimal Data: An In-Context-Learning-Aware Approach Using Large Language Models

Abstract: Accurate mid-term load forecasting at the building level is vital for the strategic planning, operation, and sustainability of modern power systems. Machine learning approaches often require ...
IEEE

Optimizing Deep Residual Networks for Short-Term Load Forecasting With Multidimensional Weather Data and Principal Component Analysis

Abstract: Short-term load forecasting (STLF) is essential for power system operations, supporting efficient grid management and resource planning. Deep Residual Networks (DRNs) have emerged as a ...