Electricity Consumption

Research on electricity consumption focuses on accurately predicting and managing household energy usage, driven by the increasing adoption of renewable energy sources and smart home technologies. Current efforts employ diverse machine learning models, including convolutional neural networks, recurrent neural networks (like LSTMs and GRUs), transformers, and hybrid approaches, to analyze high-frequency smart meter data and even satellite imagery for consumption prediction and load disaggregation. These advancements aim to improve grid stability, optimize energy efficiency, and empower consumers with detailed feedback on their energy use, ultimately contributing to a more sustainable energy future.