An AI-Powered System for Residential Demand Response

Recent studies show that energy consumption of buildings has dramatically increased over the last decade, accounting for more than 35% global use. However, with proper operation, significant savings can be achieved. Demand response is envisioned as a key enabler this operation enhancement, it may contribute to reduction demand peaks and maximization renewable exploitation while mitigating potential problems grid stability. In article, system based on artificial intelligence solves complex multi-objective problem bring programs residential sector proposed. Through application novel machine learning-based algorithms, unique control loop developed help dwellers determine how when use their appliances. The feasibility validity proposed been demonstrated in real-world neighbourhood where notable shift electricity Concretely, accordance extreme changes prices, users have ability periods lower prices well reducing power during higher thus fully translating peak time.