• Advances in environmental research
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• v.4 no.3
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• pp.143-153
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• 2015

The ventilation system is a key device to ensure both healthful indoor air quality (IAQ) and thermal comfort in buildings. The ventilation system should make the IAQ meet the standards such as ASHRAE 62. This study deals with a new approach to modeling the ventilation and IAQ requirement in residential buildings. In that approach, Elite software is used to calculate the air supply volume, and CONTAM model as a multi-zone and contaminant dispersal model is employed to estimate the contaminants' concentrations. Amongst various contaminants existing in the residential buildings, two main contaminates of carbon dioxide ($CO_2$) and carbon monoxide (CO) were considered. CO and $CO_2$ are generated mainly from combustion sources such as gas cooking and heating oven. In addition to the mentioned sources, $CO_2$ is generated from occupants' respirations. To show how that approach works, a sample house with the area of $80m^2$ located in Tehran was considered as an illustrative case study. The results showed that $CO_2$ concentration in the winter was higher than the acceptable level. Therefore, the air change rate (ACH) of 4.2 was required to lower the $CO_2$ concentration below the air quality threshold in the living room, and in the bedrooms, the rate of ventilation volume should be 11.2 ACH.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.17 no.1
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• pp.1-13
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• 2021

Before newly-built building and building remodeling, it is important to predict and analyze building energy performance through energy simulation programs. Nevertheless, simulation results widely vary depending on individual user experience and input values. Therefore, this study uses prototypical building model, a versatile tool in building energy modeling, simulation and research for researchers and policy-makers, and ASHRAE standards. Then, it analyzed the changes in design type (roof type, number of floors) for the base case. As the result, it was found that the gap of annual energy demand per between them is maximally 9.1%.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.36 no.3
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• pp.169-176
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• 2020

The authors developed a nodal network model that simulates the flow of moist air and the thermal behavior of a target area. The nodal network model was enhanced using a parameter estimation technique based on the measured temperature, humidity, and schedule data. However, the nodal model is not good enough for predicting humidity of the target space, having 55.6% of CVRMSE. It is because re-evaporation effect could not be modeled due to uncertain factors in the field measurement. Hence, a data-driven model was introduced using an artificial neural network (ANN). It was found that the data-driven model is suitable for predicting the condensation compared to the nodal model satisfying ASHRAE Guideline with 3.36% of CVRMSE for temprature, relative humidity, and surface temperature on average. The model will be embedded in automated devices for real-time predictive control, to minimize the risk of surface condensation at dressroom in an apartment housing.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.60 no.1
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• pp.87-99
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• 2024

This study deals with the application of an artificial neural network (ANN) model to predict power consumption for utilizing seawater source heat pumps of recirculating aquaculture system. An integrated dynamic simulation model was constructed using the TRNSYS program to obtain input and output data for the ANN model to predict the power consumption of the recirculating aquaculture system with a heat pump system. Data obtained from the TRNSYS program were analyzed using linear regression, and converted into optimal data necessary for the ANN model through normalization. To optimize the ANN-based power consumption prediction model, the hyper parameters of ANN were determined using the Bayesian optimization. ANN simulation results showed that ANN models with optimized hyper parameters exhibited acceptably high predictive accuracy conforming to ASHRAE standards.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.4
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• pp.159-166
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• 2017

The growing global interest in energy saving is particularly evident in the building sector. The transmitted solar irradiance is an important input in the prediction of the building-energy load, but it is a value that is difficult to measure. In this paper, a calculation method, for which the total horizontal irradiance that can be easily measured is employed, for the measurement of the transmitted solar irradiance through windows is proposed. The method includes a direct and diffuse split model and a variable-transmittance model. The results of the proposed calculation model are compared with the TRNSYS-simulation results at each stage for the purpose of validation. The final results show that the CVRMSE over the year between the proposed model and the reference is less than 30 %, whereby the ASHRAE guideline was achieved.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.8
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• pp.394-400
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• 2014

Several models and methods have been developed to verify the improvement of energy performance in retrofit buildings. The verification is important to confirm the effectiveness of new technologies or retrofits. Inverse model toolkit proposed by ASHRAE evaluates the changes of the energy performance of retrofit buildings by using actual energy consumption data. In this study, the inverse model toolkit was used to analyze heating and cooling energy performance of an office building. Analyzed coefficients of correlation of actual energy consumption with estimated energy consumption was above 0.92 and well fitted. It was confirmed that energy consumption of natural gas decreased by 43.4% and also that electricity decreased by 13.8%, after the retrofit of the case building. For the energy usage, cooling energy was increased by 7.4%, heating energy was decreased by 42.3%, hot water and cooking were increased by 3.4%, lighting and electronics were decreased by 19.3%, and the total energy was decreased by 18.9%.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.10
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• pp.1262-1272
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• 1997

An experimental study on the frequency control of an inverter heat pump to get the desired indoor room temperature has been conducted for the performance characteristics during the steady, 4, 8, and 16 step frequency operations. The heat pump model used in this study was operated to meet the experimental conditions of ASHRAE standard. The performance of the system was tested by measuring the temperature and pressure of the refrigerant, and cooling capacity, power consumption, etc. of the system. As the controlling frequency steps increased, the running time of the compressor increased as well as the electric consumption of the system and the cooling energy due to the wall heating load. However, the average cooling COP was improved.

• Journal of Environmental Science International
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• v.23 no.3
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• pp.503-510
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• 2014

To estimate the benefit of high-resolution meteorological data for building energy estimation, a building energy analysis has been conducted over Busan metropolitan areas. The heating and cooling load has been calculated at seven observational sites by using temperature, wind and relative humidity data provided by WRF model combined with the inner building data produced by American Society of Heating Refrigeration and Air-conditioning Engineers (ASHRAE). The building energy shows differences 2-3% in winter and 10-30% in summer depending on locations. This result implicates that high spatiotemporal resolution of meteorological model data is significantly important for building energy analysis.

• Journal of the Korean Solar Energy Society
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• v.38 no.1
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• pp.1-11
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• 2018

In this work, we propose weather prediction models to estimate hourly outdoor temperatures and solar irradiance in the next day using forecasting information. Hourly weather data predicted by the proposed models are useful for setting system operating strategies for the next day. The outside temperature prediction model considers 3-hourly temperatures forecasted by Korea Meteorological Administration. Hourly data are obtained by a simple interpolation scheme. The solar irradiance prediction is achieved by constructing a dataset with the observed cloudiness and correspondent solar irradiance during the last two weeks and then by matching the forecasted cloud factor for the next day with the solar irradiance values in the dataset. To verify the usefulness of the weather prediction models in predicting a short-term building load, the predicted data are inputted to a TRNSYS building model, and results are compared with a reference case. Results show that the test case can meet the acceptance error level defined by the ASHRAE guideline showing 8.8% in CVRMSE in spite of some inaccurate predictions for hourly weather data.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.11
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• pp.73-79
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• 2018

In this study, for the prediction of energy consumption in the ventilator, one of the components of the air conditioning system, the predicted results were analyzed and accurate by the change in the number of neurons and inputs. The input variables of the prediction model for the energy volume of the fan were the supply air flow rate, the exhaust air flow rate, and the output value was the energy consumption of the fan. A predictive model has been developed to study with the Levenbarg-Marquardt algorithm through 8760 sets of one-minute resolution. Comparison of actual energy use and forecast results showed a margin of error of less than 1% in all cases and utilization time of less than 3% with very high predictability. MBE was distributed with a learning period of 1.7% to 2.95% and a service period of 2.26% to 4.48% respectively, and the distribution rate of ${\pm}10%$ indicated by ASHRAE Guidelines 14 was high.8.