Estimation of the Available Rooftop Area for Installing the Rooftop Solar Photovoltaic (PV) System by Analyzing the Building Shadow Using Hillshade Analysis

AbstractFor continuous promotion of the solar PV system in buildings, it is crucial to analyze the rooftop solar PV potential. However, the rooftop solar PV potential in urban areas highly varies depending on the available rooftop area due to the building shadow. In order to estimate the available rooftop area accurately by considering the building shadow, this study proposed an estimation method of the available rooftop area for installing the rooftop solar PV system by analyzing the building shadow using Hillshade Analysis. A case study of Gangnam district in Seoul, South Korea was shown by applying the proposed estimation method

Development of the monthly average daily solar radiation map using A-CBR, FEM, and kriging method

Photovoltaic (PV) system could be implemented to mitigate global warming and lack of energy. To maximize its effectiveness, the monthly average daily solar radiation (MADSR) should be accurately estimated, and then an accurate MADSR map could be developed for final decision-makers. However, there is a limitation in improving the accuracy of the MADSR map due to the lack of weather stations. This is because it is too expensive to measure the actual MADSR data using the remote sensors in all the sites where the PV system would be installed. Thus, this study aimed to develop the MADSR map with improved estimation accuracy using the advanced case-based reasoning (A-CBR), finite element method (FEM), and kriging method. This study was conducted in four steps: (i) data collection; (ii) estimation of the MADSR data in the 54 unmeasured locations using the A-CBR model; (iii) estimation of the MADSR data in the 89 unmeasured locations using the FEM model; and (iv) development of the MADSR map using the kriging method. Compared to the previous MADSR map, the proposed MADSR map was determined to be improved in terms of its estimation accuracy and classification level. First published online: 03 May 201

A Prototype Design and Development of the Smart Photovoltaic System Blind Considering the Photovoltaic Panel, Tracking System, and Monitoring System

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)

Intelligent planning unit for the artificial intelligent based built environment focusing on human-building interaction

The buildings’ indoor condition called “indoor environmental quality (IEQ)” has become a major goal, all IEQ elements must be maintained within a certain range for the comfort and health of the occupants. To achieve this goal, the previous studies focused on building occupants’ responses based on their activities and the changes in IEQ. Few studies, however, have comprehensively analyzed the above and reflected it in building design and operation. The study of this concept can be expressed as “human-building interaction management.” This approach is a paradigm for the healthy, sustainable, and simultaneous management of people, IEQ, and buildings. This study conducted an in-depth literature review on the above-mentioned studies. In addition, it ultimately proposed an intelligent planning unit (IPU), a new approach that can be used as a tool to apply the above human-building interaction concept to the practical design concept focusing on the planning phase. The IPU theory is designed to meet the customer expectations for the various objectives of a complex built environment. Eventually, it is expected that the proposed IPU concept will promote the spread of good health and environment-friendly buildings

Advanced Strategies for Net-Zero Energy Building: Focused on the Early Phase and Usage Phase of a Building’s Life Cycle

To cope with ‘Post-2020’, each country set its national greenhouse gas (GHG) emissions reduction target (e.g., South Korea: 37%) below its business-as-usual level by 2030. Toward this end, it is necessary to implement the net-zero energy building (nZEB) in the building sector, which accounts for more than 25% of the national GHG emissions and has a great potential to reduce GHG emissions. In this context, this study conducted a state-of-the-art review of nZEB implementation strategies in terms of passive strategies (i.e., passive sustainable design and energy-saving technique) and active strategies (i.e., renewable energy (RE) and back-up system for RE). Additionally, this study proposed the following advanced strategies for nZEB implementation according to a building’s life cycle: (i) integration and optimization of the passive and active strategies in the early phase of a building’s life cycle; (ii) real-time monitoring of the energy performance during the usage phase of a building’s life cycle. It is expected that this study can help researchers, practitioners, and policymakers understand the overall implementation strategies for realizing nZEB

A Prototype Design and Development of the Smart Photovoltaic System Blind Considering the Photovoltaic Panel, Tracking System, and Monitoring System

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)

BIM-based preliminary estimation method considering the life cycle cost for decision-making in the early design phase

Prediction of construction cost and life-cycle cost through preliminary estimate is very important for the economic decision-making in the early phase of building projects. However, the conventional preliminary estimate has a high error range and low reliability because it relies only on the basic information of projects. In addition, the consideration of the life-cycle cost of the building is insufficient, causing problems such as budget shortage, inaccurate budgeting, and life-cycle cost increase. In this study, we propose a method of preliminary estimate based on BIM below the level of detail 2 and actual construction cost data to support the decision-making in the early design phase. To verify the proposed method, a web-based prototype was implemented and applied to three test cases. The range of error rate for three test cases was 1.93–7.16% (average error rate: 5.18%). It satisfies the criteria (−30% ~ +50%) of the “American Association of Cost Engineering”. As a result, the feasibility of the proposed model was validated. It is expected to be utilized as useful information in the decision-making occurring in the early design phase, and this allows for a rapid economic review of the design alternatives, a reduced LCC, and a shortened decision-making time