Jung-Ho Huh

A Multi-objective Optimization Method for Energy System Design Considering Initial Cost and Primary Energy Consumption

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.

Existing Building Energy Simulation Method Using Calibrated Model by Energy Audit Data

Abstract This paper represents a method of existing building energy simulation using energy audit data. Energy audit mustbe 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 characteristicsshould 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. Key words Existing buildings(기존 건축물), Energy simulation(에너지시뮬레이션), Energy audit(성능진단), Baseline model calibration(기준 모델 보정), Measurement and verification(M&V

Real-time Energy Demand Prediction Method Using Weather Forecasting Data and Solar Model

This study was designed to investigate a method for short-term, real-time energy demand prediction, to cope with changing loads for the effective operation and management of buildings. Through a case study, a novel methodology for real-time energy demand prediction with the use of weather forecasting data was suggested. To perform the input and output operations of weather data, and to calculate solar radiation and EnergyPlus, the BCVTB (Building Control Virtual Test Bed) was designed. Through the BCVTB, energy demand prediction for the next 24 hours was carried out, based on 4 real-time weather data and 2 solar radiation calculations. The weather parameters used in a model equation to calculate solar radiation were sourced from the weather data of the KMA (Korea Meteorological Administration). Depending on the local weather forecast data, the results showed their corresponding predicted values. Thus, this methodology was successfully applicable to anywhere that local weather forecast data is available.

Selecting of the Energy Performance Diagnosis Items through the Sensitivity Analysis of Existing Buildings

Abstract 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 mostbuilding energy audits are performed in the same way. The sensitivity analysis (SA) is a statistical method to quantify thecorrelation 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. Key words

Effects on Energy Saving and Thermal Comfort Improvement by Window Opening Behavior

In this study, the occupant behavior of window operation in residential buildings was implemented and dynamic building energy simulation was also conducted to examine the effect of the behavior reflection on natural ventilation rate, energy demand and thermal comfort. The process of using EMS(Energy Management System) and AFN(Air Flow Network) has been carefully proposed in order to realize the stochastic behavior model on the simulation. The energy demand and thermal comfort based on the behavior was reviewed. The results show that window operation was realized toward cooling energy reduction as well as comfort satisfaction through natural ventilation in summer. Further, when the ventilation rate was fixed, the thermal comfort was lower than other behavior models. In the future, it is necessary to develop a behavior models suitable for the domestic residential culture. In addition to window opening and closing, if behavior models for the operation of heating and cooling equipment were developed, it will be able to predict the building energy consumption with a more accuracy.

Management of cooling energy through building controls for thermal comfort and relative performance in an office building

This study aims to improve the thermal environment of buildings and their occupants’ relative performance (RP) by having buildings exploit energy for cooling from energy saved when building controls are in place. Many countries restrict indoor set-point temperatures based on energy-saving policies, although such restrictions can compromise occupants’ thermal comfort and, in turn, their RP. This study first sets the existing building energy consumption, which limits indoor temperature settings in accordance with energy-saving policies, to baseline. The study then proposes a method to find an optimal hourly set-point temperature that represents the same energy consumption as the baseline—an optimal indoor-temperature-setting method that improves the RP of occupants while keeping the same energy consumption as the baseline. In this study, the time (hour) included in the thermal comfort range has increased from 0 h to 2 h, which consequently improved RP by 0.2% to 0.4%. This result indicates that the proposed approach is a cost-effective way to improve the RP of occupants without the additional consumption of energy by their buildings. The approach is ultimately applicable to building energy management systems as a method to improve the RP of occupants in buildings in which additional energy consumption relative to existing energy consumption presents a challenge.

Prediction of Occupants based on Existing Wi-Fi Infrastructure

This study is to propose a method of predicting the number of present occupants using Wi-Fi, a sensor within the building. The accuracy and correlation of the estimated number of occupant by proposing method and schedule for generally used in a building energy simulation were compared with real occupant schedule. The validation of the proposed method has been made. MAC(Media Access Control) address and Wi-Fi was used to predict the number of present occupants, and data were collected and analyzed for 20 days. The energy consumption for air conditioning and the indoor concentration were analyzed to examine the influence of the number of present occupant using EnergyPlus. The results showed that the method considering the regression coefficient on the number of occupant accessing Wi-Fi is the most close to the real values and occupants, air-conditioning system energy use and concentration.

A Study on the Calculation Process of Carbon Dioxide Emission for Buildings with Life Cycle Assessment

International cooperation to reduce greenhouse gas emissions is expected to provide a big crisis and a great opportunity at the same time for our industry that heavily consumes energy. To cope actively with the international environmental regulation, such as the Framework Convention on Climate Change, quantitative measurement of the volume of greenhouse gases emitted by various industries and quantitative prediction of the greenhouse gas emissions of the future are becoming more important than anything else at the national level. This study aims to propose the calculation process of carbon dioxide() emission for building in life cycle. This paper describes and compares 9 different tool for environmental load estimation with LCA. This study proposed the calculation process for quantitatively predicting and assessing emissions during the life cycle of buildings based on the life cycle assessment(LCA). The life cycle steps of buildings were divided into the design/supervision, new construction, repair, renovation, use of operating energy in buildings, maintenance, and reconstruction stage in the life cycle inventory analysis and the method of assessing the environmental load in each stage was proposed.