4.7 Article

Energy Optimization of HVAC Systems in Commercial Buildings Considering Indoor Air Quality Management

Journal

IEEE TRANSACTIONS ON SMART GRID
Volume 10, Issue 5, Pages 5103-5113

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2018.2875727

Keywords

Multi-zone commercial buildings; HVAC systems; indoor air quality (IAQ); energy cost; thermal discomfort

Funding

  1. National Natural Science Foundation of China [61502252, 61729101, 61771258, 61522109, 61671253, 91738201, 51507085]
  2. Major Program of National Natural Science Foundation of Hubei in China [2016CFA009]
  3. Natural Science Foundation of Jiangsu Province [BK20150869, BK20150040, BK20171446]
  4. Fundamental Research Funds for the Central Universities [2015ZDTD012]
  5. Key Project of Natural Science Research of Higher Education Institutions of Jiangsu Province [15KJA510003]
  6. Open Project of State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System [BK218002]

Ask authors/readers for more resources

To intelligently schedule heating, ventilation, and air conditioning (HVAC) systems for reducing energy cost of commercial buildings, indoor temperature and indoor air quality (IAQ) should be jointly considered. Otherwise, the health and productivity of occupants may be affected. In this paper, we investigate the problem of minimizing the sum of energy cost associated with HVAC systems and thermal discomfort cost related to occupants in multi-zone commercial buildings considering IAQ management. Firstly, by taking uncertainties of electricity price, outdoor temperature, number of occupants, temperature preference of each occupant, and external thermal disturbance into consideration, we formulate a time-averaged expected total cost minimization problem without violating the constraints of indoor temperature and IAQ. Due to the existence of uncertain system parameters, temporally and spatially coupled constraints, the nonconvex objective function, and nonconvex constraints, it is particularly challenging to solve the formulated problem. To this end, we propose a real-time algorithm based on the framework of Lyapunov optimization techniques. The key idea of the proposed algorithm is to construct virtual queues related to indoor temperatures and stabilize such queues so that indoor temperatures fluctuate around the ideal time-average indoor temperature. By dynamically controlling the average fluctuation level of indoor temperatures, the total cost could be optimized. Extensive simulation results show the effectiveness of the proposed algorithm.

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