본 연구에서는 ‘설향’ 딸기의 관부를 부분 난방하고 양액을 온수로 공급하면서 관행 재배 방식에 비해 온실 공간 온도를 낮게 관리하는 딸기 부분 난방 시험을 수행하였다. 정식 후 11월까지는 특별한 처리가 없어 대조구, 시험구 모두 온실 내 환 경이 유사하게 관리되었으며 관부 난방 및 온수 양액을 공급 하기 시작한 12월부터는 야간의 온실 온도, 관부 온도 및 베드 온도가 차이를 보였다. 12월의 온실 야간 평균 온습도는 대조구 7.1℃, 87.2%, 시험구 5.7℃, 88.7%로 시험구의 온도가 낮았으나 관부 난방을 수행함으로써 시험구 온실의 관부 및 베드의 온도를 9.3℃, 12.7℃로 유지하였고, 대조구 온실의 관부 및 베드 온도 7.9℃, 10.8℃보다 높게 관리할 수 있었다. 시험기간 내에서 시험구 온실의 딸기 관부 및 베드 온도는 대조구에 비해 모두 약 2.0℃ 가량 높게 유지되는 것으로 나타났다. 주간에는 온수 양액을 공급함으로써 지하수를 이용했을 때보 다 평균 8.7℃ 높은 온도 양액을 공급할 수 있었고 이로 인해 베드 온도도 약 5.0℃ 가량 높게 나타났다. 시험구에서는 시험 기간 동안 온실 난방, 관부 난방 및 온수 양액 공급에 총 9,475.7×10 3 kcal의 에너지를 소비하였고 대조구에서는 온실 공간 난방에 총 16,847×10 3 kcal의 에너지를 소비하여 시험구에서 대조구 대비 약 43.8%의 에너지 절감 효과를 확인할 수 있었다. 시험구에서 딸기 관부의 온도를 높게 관리함으로써 작물의 생육을 촉진시킬 수 있었고 그로 인해 정식 후 초세가 대조구에 비해 좋지 않았던 시험구의 딸기가 25주 후에는 대조구와 생육적인 면에서 큰 차이가 없는 것으로 나타났다. 딸기의 수확량은 초세가 좋았던 대조구에서 1화방의 수확량이 시험구에 비해 많았으나 2화방, 3화방에서는 관부의 온도를 높게 관리한 시험구의 수확량이 더 많았다. 3월 말까지의 주당 수확량은 시험구 412.7g/plant, 대조구 393.3g/plant로 유의미한 차이는 없었으나 시험구가 대조구에 비해 4.9% 많이 나온 것으로 보아 딸기의 온도 민감부인 관부의 온도를 높게 관리하는 것이 딸기 생육과 생산성에 영향을 미치는 것으로 판단된다.

In this study, the energy use of buildings was compared and analyzed by using weather data predicted with machine running techniques. Python was used as a predictive program to predict weather data and TRNSYS was used to simulate the energy usage of buildings. For weather forecasting, weather data from 1 August to 7 August were studied to forecast ambient air temperature and solar radiation. The lowest error came in seven days, with the outside air temperature standing at 1.8 percent and the solar radiation at 2.4 percent. The energy use of the building was simulated by using weather data predicted through the 7 days learning data with the lowest error. As a result , the error rate of cooling energy use was 1.92%, the sum of cooling energy and lighting energy use was 1.79%, and the building control by using predicted weather data didn’t show a big difference with just control.

In this study, we proposed a model for forecasting power energy demand by investigating how outside temperature at a given time affected power consumption and. To this end, we analyzed the time series of power consumption in terms of the power spectrum and found the periodicities of one day and one week. With these periodicities, we investigated two time series of temperature and power consumption, and found, for a given hour, an approximate linear relation between temperature and power consumption. We adopted an exponential smoothing model to examine the effect of the linearity in forecasting the power demand. In particular, we adjusted the exponential smoothing model by using the variation of power consumption due to temperature change. In this way, the proposed model became a mixture of a time series model and a regression model. We demonstrated that the adjusted model outperformed the exponential smoothing model alone in terms of the mean relative percentage error and the root mean square error in the range of 3%~8% and 4kWh~27kWh, respectively. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric energy together with the outside temperature.

In this paper, we propose an Elman recurrent neural network to predict and analyze a time series of gas energy consumption in an air handling unit. To this end, we consider the volatility of the time series and demonstrate that there exists a correlation in the time series of the volatilities, which suggests that the gas consumption time series contain a non-negligible amount of the non-linear correlation. Based on this finding, we adopt the Elman recurrent neural network as the model for the prediction of the gas consumption. As the simplest form of the recurrent network, the Elman network is designed to learn sequential or time-varying pattern and could predict learned series of values. The Elman network has a layer of “context units” in addition to a standard feedforward network. By adjusting two parameters in the model and performing the cross validation, we demonstrated that the proposed model predicts the gas consumption with the relative errors and the average errors in the range of 2%~5% and 3kWh~8kWh, respectively. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric and the gas energies.

In this study, the actual energy consumption of the secondary side of district heating system(DHS) with different hot water supply temperature control methods are compared. Two methods are outdoor temperature reset control and outdoor temperature predictive Control. While outdoor temperature reset control has been widely used for energy savings of the secondary side of the system, the results show that outdoor temperature predictive control method saves more energy. In general, outdoor temperature predictive control method is lowering the supply temperature of hot water, and it reduces standby losses and increases overall heat transfer value of heated spaces due to more flow into the space. During actual energy consumption monitoring, outdoor temperature predictive control method saves about 19.1% when it compared to outdoor temperature reset control method. Also, it is found that when partial load condition, such as daytime, the fluctuation of hot water supply temperature with outdoor temperature reset control is more severe than outdoor temperature prediction control. So, it proves that outdoor temperature prediction control is more stable even at partial load conditions.

This project is mainly related to evaluation of total energy consumption of low energy house, the exterior envelope of which was wholly composed of structural insulated panels(SIP). The U-value of applied SIP was in the range of 0.189 to 0.269W/㎡․K and the U-value of pair glass from 0.78 to 1.298W/㎡․K was applied for window dependent to its function respectively. For comparison of total energy performance, the energy simulation for pilot house was performed to compare with the control house having insulation criteria of Korean building regulation in 2009. Based on simulation of dynamic energy performance, the pilot house saved 48.3% of annual energy consumption while the control house in 2009 consumed as 85.7GJ/y. In case of heating, the result showed that the energy saving ratio amounted to 76.7%. For CO₂ emission, the pilot house diminished approximately 35.4% from 6,208.4kgCO₂ to 4,009.2kgCO₂. In payback period to early investment, it was analyzed the pilot house took 7.8 years, when the low energy house built by other insulation method with same thermal perfusion took 11.5 years. From this result, it is considered that the SIP is more effective, economic to Green Home application.

The purpose of this study were to investigate the state of indoor environmental factors and energy consumption during winter in residential houses and to analyze factors which influenced this environment. Energy consumptions and indoor environmental factors of this survey were conducted in 21 houses(apartment, 11 and detached houses,10) between December, 2010 and February, 2011 which measured energy consumptions and indoor environmental factors as well as kept records of interviews with residents and other related factors. The results obtained were as follows. Indoor environmental factors which were found to influence apartment houses higher than detached houses. The average gas consumption of detached houses(90.98³) was higher than that of apartment houses(76.33³). Gas consumption showed positive correlations to temperature and carbon dioxide in the residential houses. The mean concentration of PM₁₀, and CO₂ in large family were higher than those of small family. We found that the more gas consumption, the higher concentration of PM₁₀, CO₂ and temperature(p<0.01).

국내 자원의 절약과 재활용 촉진에 관한 법률에 근거한 생산자책임재활용제도(EPR System)의 대상 품목인 폐형광등은 2017년 기준 재활용 의무율은 35.6%로 책정되었으며 한국환경공단에 따르면 2015년 기준 형광등의 출고량은 약 18 천톤 정도로 나타났으나 공제조합과 재활용업 간의 재활용 위･탁 계약의 미체결로 인해 폐형광등의 실제 재활용율은 약 5.0%로 재활용 의무율을 달성하지 못하고 있는 실정이다(｢생산자책임재활용제도 시행 13년｣ 운영성평가, 한국환경공단, 2017). 폐기물로 발생되는 폐형광등에 관한 선행연구에 따르면 폐형광등에 포함된 수은은 대부분 형광분말에 포함되어 있어 이를 적절하게 처리할 필요가 있다. 또한, 형광분말에는 희유금속(이트륨, 유로퓸 등)이 포함되어 있어 형광분말에 포함된 수은을 제거하여 희유금속을 회수하여 희유금속을 필요로 하는 산업체 등에서 활용할 수 있다. 이를 위하여 폐형광등 형광분말에 포함된 수은을 제거하기 위하여 Pilot plant 규모의 폐형광등 형광분말 증류 실험을 실시하였다. 실험의 원료는 경기도 K대학에 설치된 Pilot plant 규모의 폐형광등 재활용 공정에서 회수되는 폐형광등 형광분말을 사용하였다. Pilot plant 규모의 폐형광등 형광분말의 수은증류 실험의 조건으로 증류온도는 400~600℃로 변화시켰고 각 온도에서 증류장치 내 체류시간을 1~8시간으로 변화시켰다. 본 연구에서는 각 실험조건에서 회수되는 형광분말의 수은함량을 분석하였고 증류온도와 체류시간에 따른 수은함량을 비교하여 반응속도를 고찰하였다. 또한, 각 실험조건에서 소모되는 에너지양을 비교하여 Pilot plant 규모의 폐형광등 형광분말 증류장치의 최적 에너지 사용량을 평가하고자 하였다.