• Journal of Information Technology Services
• /
• v.21 no.5
• /
• pp.81-94
• /
• 2022

This study sets the research goal of reducing energy consumption which 'H' University Industry-University Cooperation Foundation and resident companies are concerned with, as well as conducting policy research and data analysis. We tried to present a solution to the problem using the technique. The algorithm showing the greatest reliability in the power of the model for the analysis algorithm of this paper was selected, and the power consumption trend curves per minute and hour were confirmed through predictive analysis while applying the algorithm, as well as confirming the singularity of excessive energy consumption. Through an additional sub-sensor analysis, the singularity of energy consumption of the unit was identified more precisely in the facility rather than in the building unit. Through this, this paper presents a system building model for real-time monitoring of campus power usage, and expands the data center and model for implementation. Furthermore, by presenting the possibility of expanding the field through research on the integration of mobile applications and IoT hardware, this study will provide school authorities and resident companies with specific solutions necessary to continuously solve data-based field problems.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.4_2
• /
• pp.715-724
• /
• 2023

Solar energy forecasting is essential for (1) power system planning, management, and operation, requiring accurate predictions. It is crucial for (2) ensuring a continuous and sustainable power supply to customers and (3) optimizing the operation and control of renewable energy systems and the electricity market. Recently, research has been focusing on developing solar energy forecasting models that can provide daily plans for power usage and production and be verified in the electricity market. In these prediction models, various data, including solar energy generation and climate data, are chosen to be utilized in the forecasting process. The most commonly used climate data (such as temperature, relative humidity, precipitation, solar radiation, and wind speed) significantly influence the fluctuations in solar energy generation based on weather conditions. Therefore, this paper proposes a hybrid forecasting model by combining the strengths of the Prophet model and the GRU model, which exhibits excellent predictive performance. The forecasting periods for solar energy generation are tested in short-term (2 days, 7 days) and medium-term (15 days, 30 days) scenarios. The experimental results demonstrate that the proposed approach outperforms the conventional Prophet model by more than twice in terms of Root Mean Square Error (RMSE) and surpasses the modified GRU model by more than 1.5 times, showcasing superior performance.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.11a
• /
• pp.1038-1040
• /
• 2022

지속적인 지구 평균 기온 상승으로 인해 우리나라를 포함한 전 세계적으로 탄소중립을 위한 혁신이 이루어지고 있다. 본 연구는 해양수산부 '해양수산분야 2050 탄소중립 로드맵'의 기준에 따라 에너지 자립률을 극대화하고 효율을 최적화시킨 제로에너지 탄소중립 건축물을 제시한다. 태양광 발전 시스템에서, 패널의 태양 일주추적 기능을 통해 에너지 발전률을 극대화하고, 패널 하향정렬 및 딥러닝 모델을 통해 유지 보수를 용이하게 하여 성능 저하를 예방한다. 폐열을 이용한 열 회수/바이패스 환기 시스템을 통해 에너지 효율을 최적화하고, 온/습도에 가중치를 부여하여 모호했던 환기 시스템 결정 기준을 에너지 효율화에 맞게 최적화해 제시한다. 탄소중립 BEMS 기능이 내재된 앱 개발로 위의 건축물 시스템을 제어·관리한다. 본 연구를 통해 제로 에너지 건축물으로서 항만 건물의 가능성을 제고하고, 탄소중립 항만의 구현을 기대한다.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.36 no.11
• /
• pp.1433-1439
• /
• 2012

This paper introduces a sensor system based on indoor locations in order to implement the Building Energy Management System. This system consists of a thermopile sensor and an ultrasonic sensor. The sensor module is rotated by $360^{\circ}$ and yawed up-and-down by two electric motors. Therefore, it can simultaneously detect the number and location of the inhabitants in the room. It uses wireless technology to communicate with the building manager or the smart-home server, and it can save electric energy by controlling the lighting system or heating/air conditioning equipment automatically. We also demonstrate the usefulness of the proposed system by applying it to a real environment.

• Journal of Energy Engineering
• /
• v.27 no.2
• /
• pp.32-48
• /
• 2018

Monitoring of energy use should be a priority in order to efficiently manage building energy use. Energy use in buildings can be managed by dividing them into energy sources, uses, and ZONE. By energy source, electricity, gas, fuel, and district heating are supplied to run the building's facilities. The purpose can be divided into five main applications, including cooling, heating, lighting, hot water and ventilation, but not many elevators and electric heaters that are difficult to include in the five applications are classified. ZONE Star refers to the comparison or separate management of areas for which the purpose of the building is similar or different. In addition, energy efficiency management requires control of the temperature, humidity, and people who will be measuring energy in the building, and the recent problem of fine dust should directly affect the ventilation of the building.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.3
• /
• pp.1235-1242
• /
• 2013

This study deals with the BIM (Building Information Modeling)-based energy performance analysis implemented in EnergyPlus. The BIM model constructed at Revit is updated at Design Builder, adding HVAC models and converted compatibly with the EnergyPlus. We can obtain the input values about HVAC system and building environment such as HVAC system efficient, the number of air changes and energy consumption of equipment on applying GAs (Genetic algorithms). After modification about HVAC system, Optimization about HVAC system energy consumption can be analyzed. In order to maximize the building energy performance, a genetic algorithm (GA)-based optimization technique is applied to the modified HVAC models. Throughout the proposed building energy simulation, finally, the best optimized HVAC control schedule for the target building can be obtained in the form of "supply air temperature schedule". Throughout the supply air temperature schedule is applied to energy performance simulation, we obtained energy saving effect result on simulation.

• Journal of Energy Engineering
• /
• v.29 no.2
• /
• pp.79-84
• /
• 2020

In order to reduce greenhouse gas by 30% compared to BAU in 2020, research and development of zero-energy building construction technology for reducing greenhouse gas emissions in the construction industry is being conducted. With the recent implementation of the policy as mandatory through the establishment and commercialization of the zero energy building base, the government should devise measures to support and expand technology through the identification of the current status of the zero-energy building incentive system and the erasure of the erasure. In order to implement zero-energy buildings, excessive construction costs are presented as a major issue in revitalizing the supply of new and renewable energy to enhance Passive (energy efficiency grade of 1++) and achieve self sufficiency of energy (20% or higher). In this paper, the major problems and solutions for zero-energy building identification were presented in order to activate the dissemination of zero-energy buildings, and the recent policy changes resulting from the mandatory use of zero-energy buildings were analyzed.

• Journal of the Korean Solar Energy Society
• /
• v.31 no.6
• /
• pp.95-102
• /
• 2011

The purpose of study is to estimate heating, cooling load performance and economic efficiency in office building with applied the functional paint. this paint can reduced SHGC(Solar Heat Gain Coefficient) on the glazing surface by coating. In this study, estimated to compared with double glazing, low-e glazing, IP(Insulation Paint) and IPu(Insulation UV-Cut Paint) coating glazing. As a result of this study, 1)heating & cooling load Analysis, SHGC value and U-factor of double glazing is about 0.70 and 3.29($W/m^2K$). low-E glazing is about 0.65 and 2.70($W/m^2K$). Two-side it is about 0.27 and 3.25($W/m^2K$). When compared to double glazing, annual heating & cooling load of low-E glazing, Two-side IPu and IP paint coating glazing is 3,012MWh($124kWh/m^2$), 2,910MWh($120kWh/m^2$), 2,867MWh($118.4kWh/m^2$) and 2,867MWh($118.4kWh/m^2$). It i sreduced to 2.0%, 5.2%, 6.7%, and 6.7% respectively. 2)the estimation of economic efficiency, low-e glazing installed in office building can not recover the investment within a lifetime 40years. but IPu and IP paint, two-side coating in glazing, have a payback period of 13 years respectively.

• Journal of the Architectural Institute of Korea Structure & Construction
• /
• v.34 no.6
• /
• pp.63-69
• /
• 2018

The machine learning model can capture the dynamics of building systems with less inputs than the first principle based simulation model. The training data for developing a machine learning model are usually selected in a heuristic manner. In this study, the authors developed a machine learning model which can describe supply air temperature from an AHU in a real office building. For rational reduction of the training data, the progressive sampling method was used. It is found that even though the progressive sampling requires far less training data (n=60) than the offline regular sampling (n=1,799), the MBEs of both models are similar (2.6% vs. 5.4%). In addition, for the update of the machine learning model, the normalized mutual information (NMI) was applied. If the NMI between the simulation output and the measured data is less than 0.2, the model has to be updated. By the use of the NMI, the model can perform better prediction ($5.4%{\rightarrow}1.3%$).

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.36 no.6
• /
• pp.669-674
• /
• 2012

D-Cube City is a recently completed multi purpose building consisting of four types of facilities; offices, a department store, a hotel, and congregation spaces. A community energy supply system(CES) has been installed to supply this building with electricity, steam, heat, and cold water. The BEMS, building energy management system, is currently being designed to reduce building energy consumption through the efficient operation of the various pieces of building service equipment. In this study the optimal methods for operating the CES of D-Cube City were considered. This system includes three combined heat and power systems, seven steam boilers, two hot water boilers, two absorption chillers, and four turbo chillers, and various other pieces of equipment. In result, the optimal methods of operating the CES for various energy demand levels were obtained along with the seasonal effects on the economic efficiency of the operation. The effect of the amount of energy demanded by the various facility areas on the total energy consumption was also analyzed.