Control Methods for Energy Efficiency Technologies in Buildings

Dear Colleagues,

Since the oil crisis in the 1970s and the climate change agreement in the 1990s, energy reduction and energy efficiency technologies have been important topics in buildings. Recently, in the field of building energy systems, research on building energy efficiency using artificial intelligence and IoT technology has been actively conducted. By using deep learning, cloud-based computing, and optimal algorithms to predict the building environment and implement algorithms that control the building energy system in real time, researchers are striving to realize smart buildings that ensure energy savings and comfort. This Special Issue invites original research in the area of recent research and development efforts in passive and active building energy efficiency technology, the design, modeling and optimization aspects of energy and environmental systems for building energy audits, assessment and commissioning, such as heating, ventilating and air conditioning (HVAC) systems, renewable energy and passive systems, smart and intelligent buildings, building automation control and operation, building energy management systems (BEMS), fault detection diagnosis (FDD) and calibration, and sustainable and net-zero energy buildings. Topics covered by this Special Issue include but are not limited to the following specific issues:

• Building energy efficiency technology;
• Building automation control and operation;
• Building energy audits, assessment and commissioning;
• Building energy management systems (BEMS);
• Building HVAC system;
• Fault detection diagnosis (FDD) and calibration;
• Heating, ventilating and air conditioning (HVAC) systems;
• Machine and deep learning control;
• Renewable energy and passive systems;
• Sustainable and net-zero energy buildings;
• Smart and intelligent buildings;
• Smart sensors for indoor air monitoring;
• Human comfort and indoor environmental quality;
• Ventilation and air circulation;
• Artificial intelligence and neural networks;
• Building energy and environmental control;
• Building energy systems design, modeling and optimization.

Prof. Dr. Young-Hum Cho
Dr. Sung Lok Do
Guest Editors

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