• Energy Research

Abstract The solar photovoltaic (PV) system is known as one of the most outstanding new renewable energy systems for achieving the nearly zero energy building (nZEB). For the continuous deployment of the solar PV system in urban environments, it is crucial to estimate the rooftop solar PV potential. Urban areas, however, where high-rise buildings abound, are not always suitable for solar PV installation. Therefore, it is important to accurately estimate the available rooftop area considering the shadows from the surrounding buildings for reliable rooftop solar PV potential estimation. Therefore, this study proposed a method for estimating the rooftop solar PV potential by analyzing the available rooftop area through Hillshade analysis. Toward this end, the rooftop solar PV potential was estimated through the following hierarchical process: (i) calculation of the physical potential; (ii) calculation of the geographic potential; and (iii) calculation of the technical potential. For accurate estimation of the rooftop solar PV potential, the geographic potential (i.e., the available rooftop area) was explored in detail by analyzing the shadow based on the location of the sun through Hillshade analysis. By applying the proposed method to the Gangnam district in Seoul, South Korea, this study estimated the physical, geographic, and technical potentials on hourly, monthly, and annual bases. Overall, the physical, geographic, and technical potentials in the Gangnam district were found to be 9,287,982 MW h, 4,964,118 m 2 , and 1,130,371 MW h, respectively. These rooftop solar PV potential results can be used in establishing solar policies by analyzing the different levels of the rooftop solar PV potential on hourly, monthly, and annual bases.

Abstract To ensure the high energy performance of a new building, its operational rating should be accurately estimated in the early design phase. Toward this end, this study developed an estimation methodology for the dynamic operational rating (DOR) of a new residential building using the advanced case-based reasoning (A-CBR) and stochastic approaches. This study was conducted in three steps: (i) establishment of a case database; (ii) retrieval of similar cases using the A-CBR approach; and (iii) estimation of the dynamic operational rating using the stochastic approach. The residential buildings located in Pusan, South Korea, were selected to validate the applicability of the developed methodology. Also, this study used the mean absolute percentage error (MAPE) to evaluate the prediction accuracy of the developed methodology (which means the difference between the predicted and measured energy performance). As a result, it was determined that the MAPE of the A-CBR model (i.e., 96.8% for electricity and 86.6% for gas energy) is superior to those of the other models (i.e., the basic CBR, multiple regression analysis, and artificial neural network models). In addition, based on the stochastic approach, it was estimated that cluster No.6, as a case study, would have the letter rating of ‘B’ grade (i.e., 25

Abstract In urban areas with dense buildings, it is expected that the building-integrated photovoltaic (BIPV) system, will become widespread. Especially, the solar photovoltaic blinds (SPB), which can block the sunlight coming into the room and produce electricity, is emerging as a new technology trend. To facilitate the installation of the SPB, this study analyzed the techno-economic performance of the smart SPB considering the PV panel type and solar tracking method used. Towards this end, this study conducted experiments using the developed smart SPB, as well as a comparative analysis in terms of the techno-economic aspects based on the experiment results. The analysis results of this study were as follows: at the same cost, (i) the monocrystalline silicon (mono-Si) PV panel generated 350.5% more electricity than the amorphous silicon (a-Si) PV panel; and (ii) the direct solar tracking system generated 12.9% more electricity than the indirect solar tracking method. Accordingly, the mono-Si PV panel and the direct solar tracking method were selected for the optimal smart SPB. The installation of the smart SPB with the proposed optimal design on the south-facing window of buildings can be helpful for raising the electricity self-sufficiency rate of buildings by up to 20.3%.

Abstract Various versions of the Leadership in Energy and Environmental Design (LEED ® ) have been introduced with the addition of more stringent sustainability parameters and credit scoring schemes over the past decade. Such changes in LEED versions strongly affect the energy performance and LEED scores of the target building in the LEED certification process. Therefore, to validate and improve the current LEED version, it is crucial to investigate and compare the impact of different LEED versions on the building energy performance and scoring scheme. However, researches comparing the sustainability metrics for mid-rise multi-family buildings are rare. Therefore, this paper investigates the potential changes in the energy performance resulted from applying different LEED versions (i.e., LEED v3 and v4) for the Energy and Atmosphere (EA) category. Towards this end, a case study was carried out with energy modeling and simulation using TRACE 700 to compare the changes in the energy performance of four analysis scenarios applied to an existing mid-rise multi-family building located in Ohio. Results showed notable changes in LEED points when different versions of LEED using different ASHRAE Standards (i.e., ASHRAE Standards 90.1-2007 and 90.1-2010) are applied for the building energy analysis. In particular, mid-rise multi-family buildings could benefit from LEED v4 in terms of LEED credits as the prerequisite for the minimum energy performance improvement in EA category became significantly lenient compared to LEED v3. On the contrary, when the percentage energy performance improvement is over 34%, mid-rise multi-family buildings would benefit from LEED v3 as it becomes difficult to gain more points for similar energy performance improvement in LEED v4 compared to LEED v3. Various stakeholders including USGBC and government can benefit from using the key findings of this study for improving the LEED certification and national energy standards.

Abstract The solar lease business is a recent market trend that has been introduced in many countries. An example is the U.S. solar lease payment (LP) business, which is a payment facility for leasing the solar PV system, where the customers pay a certain amount to a third-party company. In the solar lease business, the profit obtained by residences and third-party companies depends on the solar LP. Several impact factors should be simultaneously considered when estimating the solar LP that guarantees the profitability of the business for both sides. This study aimed to develop a model for determining the optimal solar LP in the solar lease business for residences and third-party companies. A genetic algorithm was utilized to solve the trade-off problem, among the many factors involved. The optimal solar LP was provided according to two categories: (i) the electricity generation rate by region; and (ii) the electricity consumption rates of multi-family housing complexes. In terms of the region, the optimal solar LP depended on the electricity generation rate, and the difference between the highest and lowest monthly solar LPs per unit was US$0.30. In terms of the electricity consumption rate, the optimal solar LP depended on the electricity consumption rate and the number of units, and the difference between the highest and lowest monthly solar LPs per unit was US$3.14. The developed model makes it possible for the government to suggest the optimal solar LP for promoting the solar lease business, and to develop a solar PV system.

Abstract To address the energy consumption problem in the building sector, this study sought to develop a prototype of the multi-function smart window as a combination of the photovoltaic (PV) blinds and the ventilation system by considering two perspectives: (i) design of the multi-function smart window; and (ii) operation strategy for the multi-function smart window. The main findings can be summarized as follows. First, a comprehensive performance analysis of the multi-function smart window according to the application location of the ventilation system and the PV cell types was conducted to determine the optimal configuration of the multi-function smart window. Second, the hardware prototype of the multi-function smart window was implemented considering the PV cell type, PV tracker type, ventilation type, and filter. Finally, this study developed a software prototype that can monitor and control the multi-function smart window in real time based on the NI LabVIEW software program. Through the application of a novel building envelope system developed based on this study, it is expected that zero-energy buildings can be realized and buildings’ indoor environmental quality can be improved.

This study aims to design and develop the prototype models of the smart photovoltaic system blind (SPSB). To achieve this objective, the study defined the properties in three ways: (i) the photovoltaic (PV) panel; (ii) the tracking system; and (iii) the monitoring system. First, the amorphous silicon PV panel was determined as a PV panel, and the width and length of the PV panel were determined to be 50 mm and 250 mm, respectively. Second, the four tracker types (i.e., fixed type, vertical single-axis tracker, horizontal single-axis tracker, and azimuth-altitude dual-axis tracker) was applied, as well as the direct tracking method based on the amount of electricity generated as a tracking system. Third, the electricity generation and environmental conditions were chosen as factors to be monitored in order to evaluate and manage the technical performance of SPSB as a monitoring system. The prototype model of the SPSB is designed and developed for providing the electricity generated from its PV panel, as well as for reducing the indoor cooling demands through the blind’s function, itself (i.e., blocking out sunlight).

Abstract Reducing a building’s energy consumption and providing better indoor environmental quality (IEQ) are the two major issues that building professionals are facing all over the world. It is not easy, however, to simultaneously address both issues. Therefore, this study aimed to establish the optimal occupant behavior that can simultaneously reduce total energy consumption and improve the IEQ, using an energy simulation and optimization tool. This study also developed an integrated IEQ score by combining three different IEQ indices (i.e., thermal comfort, indoor air quality (IAQ), and visual comfort) for building users to easily understand the IEQ condition. To analyze the effects of occupant behavior by region, the education facility was selected as the target facility, and five target regions were selected considering the Koppen climate classification system and the C40 Cities Climate Leadership Group. Finally, a total of 5 × 1.01 × 1022 occupant behavior combinations can be generated in the five target regions. As a result, among the four target variables (i.e., total energy consumption, thermal comfort, IAQ, and visual comfort), the total energy consumption of the optimal solution was found to have changed most dramatically compared to that of the basic condition in terms of percentage (94.7%), due to its strong correlation with the overall occupant behavior (the highest correlation coefficient: 0.879). Therefore, it is shown that occupant behavior has more influence on the total energy consumption than on the three IEQ indices. Among the three IEQ indices, the IAQ of the optimal solution decreased most significantly compared to that of the basic condition (the highest reduction ratio: 4.04% in Ulsan), which indicates that the IAQ has more influences on the integrated IEQ score than thermal and visual comfort. The facility manager and the building user can operate the building for reducing total energy consumption and improving the IEQ considering occupant behavior, which can be used as the building management guideline in various regions.

Abstract As improving energy efficiency in buildings has become a global issue today, many countries have adopted the operational rating system to evaluate the energy performance of a building based on the actual energy consumption. A rational and reasonable energy benchmark can be used in the operational rating system to evaluate the energy performance of a building accurately and effectively. This study aims to develop a new energy benchmark for improving the operational rating system of office buildings. Toward this end, this study used various data-mining techniques such as correlation analysis, decision tree (DT) analysis, and analysis of variance (ANOVA). Based on data from 1072 office buildings in South Korea, this study was conducted in three steps: (i) Step 1: establishment of the database; (ii) Step 2: development of the new energy benchmark; and (iii) Step 3: application of the new energy benchmark for improving the operational rating system. As a result, six types of energy benchmarks for office buildings were developed using DT analysis based on the gross floor area (GFA) and the building use ratio (BUR) of offices, and these new energy benchmarks were validated using ANOVA. To ensure the effectiveness of the new energy benchmark, it was applied to three operational rating systems for comparison: (i) the baseline system (the same energy benchmark is used for all office buildings); (ii) the conventional system (different energy benchmarks are used depending on the GFA, currently used in South Korea); and (iii) the proposed system (different energy benchmarks are used depending on the GFA and the BUR of offices). The results of this study showed that the baseline and conventional operational rating system can be improved by using the new energy benchmark of the office building proposed in this study.