Title :
Supply Demand Coordination for Building Energy Saving: Explore the Soft Comfort
Author :
Zhanbo Xu ; Qing-Shan Jia ; Xiaohong Guan
Author_Institution :
MOE KLINNS Lab., Xi´an Jiaotong Univ., Xi´an, China
Abstract :
Due to the large amount of energy consumed in buildings, building energy savings has attracted more and more attention recently. The total energy consumed during building operations is determined by the building energy efficiency and the total demand. On the one hand, though most existing studies focus on improving building energy efficiency, there are limits. On the other hand, the demand grows fast and without limit. Therefore it is important to coordinate the supply and demand in buildings. We consider this important problem in this paper and make the following major contributions. First, the concept of average price of electricity (APE) is defined to measure the average generation cost of electricity using multiple devices. Second, a comfort model of occupant is developed to capture the tradeoff between thermal comfort and cost. Human building interaction allows the user to adjust their temperature set ranges according to the APE in real time. Third, an iterative solution method is developed to solve the supply demand coordination optimization problem. Numerical examples show that significant energy saving is possible through exploring the soft comfort requirement of the occupants, and the iterative method achieves a solution which is close to that of the centralized method, but in a much faster way. We hope this work brings insight to building energy saving in general.
Keywords :
buildings (structures); energy conservation; iterative methods; optimisation; supply and demand; average price of electricity; building energy efficiency; building energy saving; generation cost; human building interaction; iterative solution method; supply demand coordination optimization problem; Batteries; Buildings; Cooling; Electricity; Lighting; Predictive models; Temperature distribution; Building energy saving; comfort model; iterative method; mixed integer programming; supply demand coordination;
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
DOI :
10.1109/TASE.2014.2306964