Demand Response Program

Demand response programs (DRPs) aim to optimize electricity consumption by incentivizing consumers and producers to shift energy usage away from peak demand periods, thereby improving grid stability and resource efficiency. Current research focuses on developing advanced control algorithms, such as multi-agent reinforcement learning (MARL) and distributed optimization methods like ADMM, often integrated with machine learning techniques for load forecasting and consumer segmentation. These efforts leverage smart meter data and aim to enhance DRP effectiveness by considering factors like thermal comfort, privacy concerns, and the integration of renewable energy sources, ultimately contributing to a more sustainable and resilient power grid.