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This is the companion paper of part Ⅰ of DeST overview. DeST was developed as a building simulation tool with the aim of benefiting both design of and research on building energy efficiency. During its development, DeST has been applied to many projects, development of building regulations, and research. This paper gives examples of several areas in which DeST has been applied, including building design consultation, building commissioning, building energy conservation assessment, a building energy labeling system, and scientific research. Examples from a demonstration building are presented to demonstrate the entire process of aiding design with DeST. Additional projects and regulations are also mentioned to introduce other applications of DeST.

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Background: Governments and societies all over the world pay more and more attention to the research and development of smart buildings. There are numerous research projects on smart buildings that have been or being conducted worldwide. Case presentation: In this project report, we give an introduction about a newly launched research project sponsored by the Chinese central government. This project aims to combine information technology and control & optimization methodology to address challenging problems in building energy. To study and implement a decentralized control and optimization paradigm in smart buildings is one of the key tasks of this project. Conclusions: The combination of informatics and energy is a very important viewpoint to study the management and operation of modern buildings. Research activities in this area shall contribute a lot to the invention and development of new building industrial opportunities.

This study proposes a novel decentralized sensor fault detection and self-repair method for heating, ventilation and air-conditioning systems. From the perspective of network structure, sensor fault diagnosis in heating, ventilation and air-conditioning systems is distributed to the updated smart sensors without the monitoring host, which is necessary in the traditional centralized method. A fully distributed flat sensor network is established based on fundamental physical equations. Similar to the structure, mechanism and characteristics of biological communities, a smart sensor needs only to communicate with adjacent nodes and operate collaboratively to complete sensor fault detection and self-repair tasks. These tasks are formulated as a constrained optimization and are solved by a decentralized algorithm with a penalty function executed in all the sensor nodes in parallel. The diagnosis model introduces an exponential function method to determine the precise location and undertake self-repair of a fault node. Simulation results on a chilled water system illustrate the effectiveness of the proposed method. Practical application: The traditional sensor fault detection and diagnosis methods for heating, ventilation and air-conditioning systems are based on a centralized structure with several deficiencies, such as high maintenance and labor costs, link congestion and operational lag. This study presents a decentralized sensor network structure and exponential-function-based method that possess the advantages of plug-and-play, rapid deployment, high flexibility and convenience for engineering implementation without having to build a central monitor. The efficiency and effectiveness of the proposed method are demonstrated via a case study.