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

被引:50
|
作者
Yu, Liang [1 ]
Xie, Di [1 ]
Huang, Chongxin [1 ]
Jiang, Tao [2 ]
Zou, Yulong [1 ]
机构
[1] Nanjing Univ Posts & Telecommun, Key Lab Broadband Wireless Commun & Sensor Networ, Minist Educ, Nanjing 210003, Jiangsu, Peoples R China
[2] Huazhong Univ Sci & Technol, Wuhan Natl Lab Optoelect, Sch Elect Informat & Commun, Wuhan 430074, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-zone commercial buildings; HVAC systems; indoor air quality (IAQ); energy cost; thermal discomfort; INTERNET DATA CENTERS; EFFICIENT BUILDINGS; COST MINIMIZATION; SMART; MICROGRIDS;
D O I
10.1109/TSG.2018.2875727
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:5103 / 5113
页数:11
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