The building sector accounts for approximately 30% of global final energy consumption. Within buildings, HVAC systems are responsible for nearly 50% of total energy use, highlighting the critical importance of improving operational efficiency and control strategies. Although rule-based approaches are widely adopted in current practice due to their simplicity and robustness, advanced control methodologies, including data-driven and learning-based techniques, offer significant potential to optimize energy consumption while maintaining occupant comfort and indoor air quality. This work investigates advanced HVAC control strategies using a real-world office environment as a case study, enabling performance assessment under realistic operating conditions. The analyzed environment consists of an open-space office equipped with twelve Personalized Environmental Control (PEC) systems and a Ceiling-Based System (CBS), both operating under Variable Air Volume (VAV) regulation and supplied by a centralized Air Handling Unit (AHU).