Online HVAC Temperature and Air Quality Control for Cost-efficient Commercial Buildings Based on Lyapunov Optimization Technique - (:unkn) unknown (My University, 2018)
Commercial buildings consume up to 35.5% of total electricity consumed in the United States. As a subsystem in the smart building management system, Heating, Ventilation, and Air Conditioning (HVAC) systems are responsible for 45% of electricity consumption in commercial buildings. Therefore, energy management of HVAC systems is of interest. The HVAC system brings thermal and air quality comfort to the occupants of the building, designing a controller that maximizes this comfort is the first objective. Inevitably, ideal comfort tracking means more energy consumption and energy cost. Hence, the more advanced objective is balancing the comfort-cost tradeoff. Since HVAC systems have nonlinear, complex and MIMO characteristics, modeling the system and formulating an optimization problem for them is challenging. Moreover, there are physical and comfort constraints to be satisfied, and randomness of parameters such as thermal disturbances, number of occupants in the building that affects the air quality, thermal and air quality setpoints we want to track, electricity price and outside temperature to be considered. Adding real time analysis to this problem furthers the challenge. In this thesis, utilizing Lyapunov optimization technique, we first transform the constraints to stability equations, and formulate a stochastic optimization problem, then we minimize the time average of the expected cost of the system while the cost is a weighted sum of the discomfort and energy cost. Results show that using the proposed algorithm and real data, the algorithm is feasible, and an optimal solution for the problem is achieved.
Keywords: Building Automation Systems(BAS); HVAC systems control; Lyapunov Optimization Technique(LOT); non linear control; Stochastic optimization