This paper aims to derive the operational modes of a parallel double-window system that reduces cooling energy consumption and satisfies indoor comfort through natural ventilation. The parallel double-window system examined in this paper is a window system that could control indoor draft distribution and adjust the size of the opening depending on indoor and outdoor conditions. The system can be used in five ways (all close, out-open + in close, out-open+in open (tilt), out-open+in open (turn) and all open). This work verified the energy savings and indoor comfort of the existing mode experimentally, which were originally derived based on simple calculations at the time when the parallel double-window system was developed. A new operation mode, Alt 1, was derived, which addressed problems of the existing mode. In addition, in this work, the operation mode Alt 2 was derived, which simplified Alt 1 so that the actual occupant can use the system easily. By measuring these three operation modes and comparing the results with those of energy plus simulations, the work derived the amount of cooling energy savings and the level of indoor comfort through the use of an appropriate operation mode during inter-seasonal periods. Compared to when the natural ventilation operation mode was not used, cooling energy consumption was reduced by 60% when the operation mode was in use. The cooling temperature set point could have a significant impact on cooling energy consumption.

Although the latest energy-efficient buildings use a large number of sensors and measuring instruments to predict consumption more accurately, it is generally not possible to identify which data are the most valuable or key for analysis among the tens of thousands of data points. This study selected the electric energy as a subset of total building energy consumption because it accounts for more than 65% of the total building energy consumption, and identified the variables that contribute to electric energy use. However, this study aimed to confirm data from a building using clustering in machine learning, instead of a calculation method from engineering simulation, to examine the variables that were identified and determine whether these variables had a strong correlation with energy consumption. Three different methods confirmed that the major variables related to electric energy consumption were significant. This research has significance because it was able to identify the factors in electric energy, accounting for more than half of the total building energy consumption, that had a major effect on energy consumption and revealed that these key variables alone, not the default values of many different items in simulation analysis, can ensure the reliable prediction of energy consumption.

This study is aimed at analyzing the impact of effective shading design for office buildings. For shade design, the overheated period for the area in which a target building was located was estimated, the building was configured to be shaded during this period, and a different shading design was applied for each direction. Using this shade design, the daylighting performance and the reduction in cooling loads during the overheated period were evaluated. The daylighting performance was evaluated by employing the daylight factor and useful daylight illuminance (UDI). The results showed a 35% reduction in cooling loads due to the shading device. Regarding the daylight factor, more points were included in a proper daylight factor of 2-5%, which was shown to increase the UDI to 500-2,000 lux.

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 a growing interest in sustainable design in the building industry to reduce energy consumption and minimize adverse environmental impacts of buildings. The strategies for sustainable design are as follows: 1) reducing the size of the building's equipment system and saving energy through an optimal design; 2) maximizing natural energy use through a passive solar heating system; and 3) utilizing an active system through applications of high-performance heating, ventilation, and air conditioning (HVAC) and lighting systems, installation of new and renewable energy facilities, and so on. It is vital to evaluate and compare the energy efficiencies of design alternatives at an early design stage, and hence, to improve the energy performance of the final building, as design elements determined at an early phase in the architectural design process greatly influence the energy performance of the building itself. Further, costs increase over time with the number of design changes made. In the course of this research, the KLT (Korean lighting and thermal energy) method was revised and developed based on the lighting and thermal energy (LT) method, adjusting for South Korea's climate and architectural regulations, which can be used to assess the energy performance of buildings. This study was conducted to determine the process of selecting optimal design alternatives to maximize building energy performance at an early stage in the process.