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광역도시 에너지계획단계에서의 DB기반 에너지수요예측 시스템 개발
공동석(Dong-Seok Kong),이상문(Sang-Mun Lee),이병정(Byung-Jeong Lee),허정호(Jung-Ho Huh) 대한설비공학회 2009 대한설비공학회 학술발표대회논문집 Vol.2009 No.-
Energy planning for hybrid energy system is important to increase the flexibility in the urban community and national energy systems. Expected maximum loads, load profiles and yearly energy demands are important input parameters to plan for the technical and environmental optimal energy system for a planning area. The method for energy demand prediction has been based on artificial neural networks(ANN). The advantage of ANN with respect to the other method is their ability of modeling a multivariable problem given by the complex relationships between the variables. This method can produce 10% of errors hourly load profile from individual building to urban community. As the results of this paper, energy demand prediction system has been developed based on simulink.
건물에너지 시스템 설계를 위한 최적설계 방법론에 관한 연구
공동석(Kong, Dong-Seok),장용성(Jang, Yong-Sung),허정호(Huh, Jung-Ho) 한국건축친환경설비학회 2012 한국건축친환경설비학회 학술발표대회 논문집 Vol.2012 No.10
This study presented a new method to use a genetic algorithm for the optimum design of a building energy system. It is essential to apply high-performance equipment and renewable energy source for energy efficiency and reduction of energy consumption. What and how much the equipment used changes the actual energy efficiency in buildings because fuel consumption of equipment has non-linear properties reflected on the partial load. Using the equipment load factor and size as variables, this study conducted optimization to minimize primary energy use. According to the result of the optimization using the genetic algorithm, this design method have led to a potential energy reduction of 10%-18%.
대규모 전시장의 전력 및 냉수 사용량을 기반으로 한 하절기 에너지소비 특성
공동석(Kong Dong-Seok),고인석(Ko In-seok),전형준(Jeon Hyung-Jun),권한솔(Kwon Han-sol),곽노열(Kwak Ro-Yeul),허정호(Huh Jung-Ho) 한국건축친환경설비학회 2008 한국건축친환경설비학회 학술발표대회 논문집 Vol.- No.-
Exhibition facilities are known as an internal load dominated-type building, as compared to other buildings. For the energy efficiency improvement of the subject large commercial building complex, it is valuable to monitor and manage energy performance data through FMS or BAS. Large amount of hourly raw data sets of the entire cooling season were processed and analyzed for the research purpose. The study objective is to investigate correlations between energy consumptions and various field conditions including weather data. Non-energy related data such as leased floor area was identified as a good indicator for the load prediction. The results showed the acceptable load characteristics and expectable correlations between factors and implies the necessity of extra valuable data monitoring such as accurate occupancy and use information.
초기투자비와 1차 에너지소비량을 고려한 에너지시스템의 다중최적 설계 방법론
공동석(Dong-Seok Kong),장용성(Yong-Sung Jang),허정호(Jung-Ho Huh) 대한설비공학회 2014 설비공학 논문집 Vol.26 No.8
This paper proposed a multi-objective optimization method for building energy system design using primary energy consumption and initial cost. The designing of building energy systems is a complex task, because life cycle cost and efficiency of building are determined by decisions of engineer during the early stage of design. Therefore, methods such as pareto analysis that can generate various alternatives for decision making are necessary. In this study, the optimization is performed using the NSGAⅡ, and case study was carried out for feasibility of the proposed method. As a result, alternative solutions can be obtained for the optimal building energy system design.
성능진단 데이터로 보정된 모델을 이용한 기존건축물의 에너지시뮬레이션 기법
공동석(Dong-Seok Kong),김두환(Du-Hwan Kim),장용성(Yong-Sung Chang),허정호(Jung-Ho Huh) 대한설비공학회 2014 설비공학 논문집 Vol.26 No.5
This paper represents a method of existing building energy simulation using energy audit data. Energy audit must be carried out for reasonable analysis, because characteristics of existing buildings such as efficiency of fan, pump, flow rate, pressure, COP and operating schedule could be changed during the building operation. These building characteristics should be measured to estimate actual energy consumption of the existing building. In this study, we conducted energy audit and calculated energy savings for a 7-stories building as a case-study. The energy audit data were used to calibrate the building model of EnergyPlus simulation. Baseline model validated according to M&V guideline index. As a result, building characteristics are significant parameters making a big impact on energy savings in existing buildings.
민감도 분석을 통한 기존건축물의 에너지성능 진단항목 선별
공동석(Dong-Seok Kong),장용성(Yong-Sung Chang),허정호(Jung-Ho Huh) 대한설비공학회 2015 설비공학 논문집 Vol.27 No.7
The building energy audit is an important process when collecting basic information for improving the energy performance of existing buildings. Audit parameters should be associated with the energy performance of the building. Such audit parameters will vary according to an individual building’s characteristics and energy consumption patterns, but most building energy audits are performed in the same way. The sensitivity analysis (SA) is a statistical method to quantify the correlation between inputs and outputs that can determine which input is influential to which output. Therefore, an SA can identify influential parameters when applied to building energy analysis. In this paper, we adopted the Morris method to identify building energy audit parameters and performed a Monte Carlo simulation for uncertainty analysis. As a result, this method was able to identify an influential parameter for building energy audits and reduce uncertainty in energy consumption in buildings.
공동석(Dong-Seok Kong),장용성(Yong-Sung Jang),안명호(Myung-Ho Ahn),허정호(Jung-Ho Huh) 대한설비공학회 2012 대한설비공학회 학술발표대회논문집 Vol.2012 No.6
For improving energy efficiency and reducing energy consumption, many researches carried out in decade. However, it is difficult to decide which energy system is the best, what way to operate equipment is the best, because building load demand turned into dynamic aspects. This study, proposes a optimal design method using Genetic Algorithm(GA) which could deal with nonlinear optimization problems. GA is carried out to minimize primary energy use by fitness function. The result shows that this method has a potential chance to reduce energy consumption and improve equipment efficiency.
도심지역 에너지계획을 위한 인공신경망 기반의 에너지수요예측에 관한 연구
공동석(Kong Dong-Seok),곽영훈(Kwak Young-Hoon),허정호(Huh Jung-Ho) 대한건축학회 2010 대한건축학회논문집 Vol.26 No.2
Under situations of our country to plan new cities and to proceed with urban renaissance constantly, it must be very essential to establish adequate energy demand-supply plans under estimation of energy demand for buildings in planning of Urban district. Especially, it needs to establish energy use plan based on load profile per time unit for step-by-step use and reuse of energy and should be based on existing energy consumption for reasonable estimation of energy demand. Artificial neural network which is a technology to express human brain as mathematical model would be possible to estimate future value in use of energy consumption and weather DB and its performance has been proved through previous related studies. In this study, we applied building energy DB to artificial neural network for development of energy demand prediction simulator per time unit at the planning stage on the basis of simulink and as the preceeding activity for this development of the system, we classified building categorys and energy to be estimated by each purpose to use.