Supply Demand Coordination for Building Energy Saving: Explore the Soft Comfort

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. Note to Practitioners-Buildings are responsible for a significant part of the energy consumption in most developed and developing countries. In order to save energy while maintaining a comfortable indoor environment in buildings, the supply and the demand must coordinate with each other. This important problem is considered in this paper. We explore the fact that occupants are willing to relax their comfort requirement when the cost is high. This feature is enabled recently in modern buildings through the human building interaction. Considering the fact that renewable energy sources and storage devices may be available in buildings, an APE is used to measure the real-time generation cost of electricity in buildings. This price information will be fed back to the occupants. They may relax (or strengthen) the requirement on room temperature when the price is high (or low). In order to adjust the devices and the set ranges of room temperature in real time, a supply demand coordination optimization problem is formulated. This problem is converted to a mixed integer programming problem and can be solved using a centralized method in CPLEX (denoted as method 1). To make this approach scalable, method 2 is developed, which iteratively solves a supply side problem and a demand side problem. Numerical results show that significant energy saving is possible through exploring the softness of the comfort requirement, and method 2 provides good solution in a much faster way than method 1.