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신주영(Shin Ju-Young),고석환(Ko Suk-Whan),신우균(Shin Woo-Gyun),황혜미(Hwang Hye-Mi),주영철(Ju Young-chul),강기환(Kang Gi-Hwan),장효식(Chang Hyo-Sik) 한국태양에너지학회 2021 한국태양에너지학회 논문집 Vol.41 No.5
The Korean government is actively promoting mandatory zero energy building (ZEB) implementations to achieve its goal of reducing greenhouse gas emissions. Photovoltaic (PV) technologies are hence being applied in the construction of ZEBs, and building-integrated photovoltaic (BIPV) systems are in the spotlight. BIPV systems are presently being integrated in the building envelopes as parts of the buildings, such as facades, roofs, and windows, to produce on-site clean electricity without requiring additional space. However, the monotonous black-colored BIPV modules are not popular because they affect the aesthetics of the buildings. To mitigate this problem, studies have been conducted on colored BIPV modules to improve the aesthetics of buildings by implementing various colored components. Power estimation is an important part of judging the faults in PV systems. Therefore, this paper proposes a performance estimation model using the characteristics of color BIPV systems based on I-V curve measurements. A color BIPV and meteorological monitoring systems were installed to acquire field survey data. The goal of this study was to verify the superiority of the proposed model by comparison with the power estimated using a simulation tool. The proposed model with high-accuracy power estimations is expected to help diagnose the performance of the BIPV system.
1.5MW 풍력발전시스템 출력 성능시험 및 불확도 분석
김건훈,주영철,김대호,Kim, Keon-Hoon,Ju, Young-Chul,Kim, Dae-Ho 한국태양에너지학회 2006 한국태양에너지학회 논문집 Vol.26 No.4
The installed capacity of wind turbines in KOREA are growing and enlarging by the central government's support program. Thus, the importance of power performance verification and its uncertainty analysis are recognizing rapidly. This paper described the Power testing results of a 1.5MW wind turbine and analysed an uncertainty level of measurements. The measured power curves are very closely coincide with the calculated one and the annual power production under the given Rayleigh wind speed distribution are estimated with the $4.7{\sim}22.0%$ of uncertainty but, in the dominant wind speed region as $7{\sim}8m/s$, the uncertainty are stably decreased to $7{\sim}8%$.