Energy efficiency by prediction and renewable energy sources will increase resiliency (preparing for unexpected events) and reduce CO₂ emissions (sustainability) • Electricity forecasting is crucial for energy management, optimizing distribution, reducing waste, and preventing power system overloads. • The involvement of prosumers is key to building resilience in energy systems, enabling them to react swiftly to fluctuations in energy demand and supply. ContextWith rising energy demands, environmental constraints, and digital transformation, optimizing energy usage is not optional—it’s essential. Module 1 – Intelligent Buildings Predictive models leveraging temporary occupancy and alternative data sources for precise building-level energy forecasting. Module 2 – Smart Energy Management Systems Advanced machine learning and statistical methods for regional-scale energy forecasting, enabling real-time optimization and decision-making. Module 3 – Collaborative Prosumer Networks Empowering prosumers to co-manage renewable energy through smart control systems and aggregators, enhancing system resilience and sustainability. Unified Workflow Vision 1. Data Acquisition from buildings, smart meters, and prosumers 2. Forecasting & Modelling using AI and time-series methods 3. Energy Optimization through smart grids and collaborative networks ➡ a holistic approach to energy efficiency—from a single building to an entire community.