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권일한(Kwon, Il-han),김진한(Kim, jin-han),백인수(Paek,In-su),유능수(Yoo, Neung-so) 한국태양에너지학회 2013 한국태양에너지학회 논문집 Vol.33 No.1
Effects of Weibull shape parameter, k, on capacity factors of wind turbines were investigated. Wind distributions with mean wind speeds of 5 m/s, 6 m/s, 7m/s and 8m/s were simulated and used to estimate the annual energy productions and capacity factors of a 2MW wind turbine for various Weibull shape parameters. It was found from the study that the capacity factors of wind turbines are much affected by Weibull shape parameters. When the annual mean wind speed at the hub height of a wind turbine was about 7 m/s, and the air density was assumed to be1.225 kg/㎥, the maximum capacity factor of a 2MW wind turbine having a rated wind speed of 13 m/s was found to occur with the shape parameter of 2. It was also found that as the mean wind speed increased, the Weibull k parameter which yielded the maximum capacity factor increased. The simulated results were also validated by predictions of capacity factors of wind turbines using wind data measured in complex terrain.
MERRA 재해석 자료를 이용한 복잡지형 내 풍력발전단지 연간에너지발전량 예측
김진한(Kim Jin-Han),권일한(Kwon Il-Han),박웅식(Park Ung-Sik),유능수(Yoo Neungsoo),백인수(Paek Ins) 한국태양에너지학회 2014 한국태양에너지학회 논문집 Vol.34 No.2
The MERRA reanalysis data provided online by NASA was applied to predict the annual energy productions of two largest wind farms in Korea. The two wind farms, Gangwon wind farm and Yeongyang wind farm, are located on complex terrain. For the prediction, a commercial CFD program, WindSim, was used. The annual energy productions of the two wind farms were obtained for three separate years of MERRA data from June 2007 to May 2012, and the results were compared with the measured values listed in the CDM reports of the two wind farms. As the result, the prediction errors of six comparisons were within 9 percent when the availabilities of the wind farms were assumed to be 100 percent. Although further investigations are necessary, the MERRA reanalysis data seem useful tentatively to predict adjacent wind resources when measurement data are not available.
생물막 반응키에서의 폐수 처리 및 Fluorescence In Situ Hybridization에 의한 복합 미생물계 구조 해석
김동진,한동우,이수철,박병곤,권일,성창근,박완철,Kim, Dong-Jin,Han, Dong-Woo,Lee, Soo-Choul,Park, Byeong-Gon,Kwon, Il,Sung, Chang-Keun,Park, Wan-Cheol 한국생물공학회 2002 KSBB Journal Vol.17 No.1
유기물 제거뿐만 아니라 안정적으로 질소와 인의 동시 제거를 위한 순환식 생물막 반응기를 제작, 운전하여 최적의 운전 인자를 도출하고, 질소 제거의 텃 번째 단계인 질산화 및 뒤이은 탈질에 관여하는 미생물들의 군집 구조 분석을 수행하였다. 유기물 제거와 질소와 인의 동시 제거를 위한 순환식 생물막 반응기는 143일 동안 운전되었다. 이 결과 $COD_{cr},\;BOD_5$, SS의 경우 각각 88, 88, 97%의 평균 제거효율을 보였다 이 기간 중 질산화율은 약 96% 정도로 유입 ${{NH_4}^{+}}_{-}N$의 대부분이 제거됨을 보였다. 하지만 탈질율은 평균 45% 정도로 나타났다. 반응기로 유입되는 총 인의 경우 약 44%가 제거되었다. 질소제거의 첫 번째 단계인 질산화가 일어나는 호기성 반응조 내 질산화 미생물의 경우 FISH 관찰 결과, 주요 암모니아 산화균 및 아질산 산화균으로는 Nitrosomonas spp.와 Nitrospira sap.가 관찰되었다. 또한 탈질 반응이 일어나는 준혐기성 반응조에서는 Rhodobacter, Rhodovulum, Roseebacter 그리고 Paracoccus 속에 속하는 탈질 미생물들이 전체 미생물의 약 10~20% 정도를 차지하며 분포하였다. Laboratory scale aerobicfanaerobic biofilm reactor was used for simultaneous and stable removal of organics, N and P components to investigate optimum design and operation parameters and to analyze the microbial distribution and consortium structure of nitrification and denitrification bacteria in aerobic and anaerobic biofilm systems. The biofilm reactor was successfully operated for 143 days to show $COD_{cr},\;BOD_5$, SS removal efficiencies of 88, 88, and 97%, respectively. During the experiment period, almost complete nitrification efficiency of 96% was achieved. Denitrification efficiency was about 45% without addition of any external carbon sources. In case of total phosphorus removal, 74% of the inlet phosphorus was removed. Fluorescence in situ hybridization (FISH) results showed that most of the ammonia oxidizing bacteria in the aerobic nitrification zone was found to be Nitrosomonas species while Nitrospira was the representative nitrite oxidizing bacteria. For the denitrification, Rhodobacter, Rhodovulum, Roseebacter and Paracouus were the dominant denitrification bacteria which was 10 to 20% of the total bacteria in numbers.