Hierarchical Optimization for Building Energy Systems

Optimal tradeoff between energy efficiency and thermal comfort is a critical aspect for building heating, ventilation, and air-conditioning (HVAC) systems. Traditional optimization and control schemes such as, PID and rule-based control (RBC), may not sufficiently address this issue in smart buildings. Moreover, most optimization-based previous works have only considered either water-side HVAC or air-side HVAC separately while both of these systems significantly affect the performance of each other. This paper presents a hierarchical optimization approach to take water-side and air-side HVAC systems into account simultaneously for energy efficiency and thermal comfort requirements. We establish an outer-inner loop algorithmic framework and develop the hierarchical gradient descent algorithm and its variants to search for optimal set points. A notion of communication period is also introduced to control the computational complexity of the algorithm. A numerical case study is used for demonstrating the efficacy of the proposed approach.