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It has been identified that improving building energy efficiency is an effective method to reduce greenhouse gas (GHG) emissions. Although standards have been established to satisfy a building’s minimum energy demand while ensuring the comfort of its residents, they are difficult to implement in mixed-humid regions. This study proposes a hybrid ventilation strategy that can comprehensively reduce cooling, heating, and ventilation energy in mixed-humid climate regions to significantly decrease the primary energy demand and reduce the impact of buildings on the environment. This study evaluated the changes in energy saving potential and thermal comfort according to the extension of the natural ventilation period and passive strategies, such as decentralized ventilation. Changes in indoor air temperature, operative temperature, and PMV for each strategy were analyzed. As a result, extending the natural ventilation and the decentralized ventilation strategies can save 32% and 34% of the building’s energy, respectively. Considering that electricity is the main energy source for cooling in Korea, the extension of the natural ventilation period was judged to be the best approach from the perspective of primary energy demand. The results can be used to predict changes in building energy demand and thermal comfort and select an appropriate ventilation strategy based on occupant information obtained using Internet of Things.

A B S T R A C T K E Y W O R DPurpose: Because of the growing concern over fossil fuel use and increasing demand for greenhouse gas emission reduction since the 1990s, the building energy analysis field has produced various types of methods, which are being applied more often and broadly than ever. A lot of research products have been actively proposed in the area of the building energy simulation for over 50 years around the world. However, in the last 20 years, there have been only a few research cases where the trend of building energy analysis is examined, estimated or compared. This research aims to investigate a trend of the building energy analysis by focusing on methodology and characteristics of each method. Method: The research papers addressing the building energy analysis are classified into two types of method: engineering analysis and algorithm estimation. Especially, EPG(Energy Performance Gap), which is the limit both for the existing engineering method and the single algorithm-based estimation method, results from comparing data of two different levels-in other words, real time data and simulation data. Result: When one or more ensemble algorithms are used, more accurate estimations of energy consumption and performance are produced, and thereby improving the problem of energy performance gap.

There is growing concern that airtight and well-insulated buildings designed to limit heat loss in temperate and cold climates could unintentionally elevate the risk of overheating in summers. Existing literature primarily uses dynamic simulation to investigate this problem due to the difficulty of obtaining large-scale in-performance data. To address this gap, we undertake a meta-analysis of large-scale indoor air temperature data for 195 UK dwellings, as a study of performance in a temperate climate. Of these, 113 are baseline (i.e., typical existing dwellings) and the rest designed to the high-performance Passivhaus standard. Using both Passivhaus and the well-known CIBSE TM59 overheating standards, this study found that there were few overheated cases for any building type. However, the average summer nighttime temperature of Passivhaus bedrooms was 1.6 °C higher than baseline, with 20 out of 31 measured bedrooms exceeding the overheating criterion, and the average overheating hours constituting approximately 19% of the total summertime observation period. These findings suggest that bedrooms in highly insulated dwellings may pose an overheating risk although whole-dwelling overheating risk is low.