Intelligent Building Energy Management Techniques with High Renewable penetration and Grid Integration

Abstract

Smart Grid (SG) technology utilizes two-way communication, control systems, and computing to boost power grid efficiency, stability, and security. Demand Response (DR) is crucial in SG, balancing supply and demand, leading to cost reduction in wholesale and retail markets. Customer engagement includes time-based rates like time-of-use, critical peak, and real-time pricing. A Home Energy Management System (HEMS) helps in DR, minimizing costs while maintaining comfort. However, complex smart home ecosystems complicate decision-making, and aggressive HEMS operations can challenge the grid. Future SG should address these challenges. The thesis aims to propose an efficient HEMS model tailored to individual customers, optimizing electricity payments and peak consumption without coordination among participants. It introduces a real-time Energy Management System (EMS) for public laundry facilities under a demand charge tariff (DCT), reducing energy costs and meeting customer needs. Another objective is to develop a coordinated framework for multiple HEMS in a residential neighbourhood, optimizing energy consumption while adhering to grid constraints and rewarding customers financially. The proposed HEMS is tested on benchmark systems and compared to existing approaches.