Short-Term Load Forecasting for Residential-Level Smart Microgrids: A Comparative Evaluation of Machine Learning and Deep Learning Architectures
Accurate short-term load forecasting (STLF) is essential for modern grid operations, enabling efficient scheduling, demand response, and renewable energy integration. This paper presents a systematic comparison of five forecasting architectures applied to a large dataset of 98 residential homes, with 1-minute and 15-mi...