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발전소 프로젝트 파이낸싱 비재무적 계약조건이 자본구조에 미치는 효과 분석
최봉석,김도엽,임덕진,이도권,박한샘 재단법인 에너지경제연구원 2019 에너지경제연구 Vol.18 No.2
We study the optimal policy of the contractual arrangement in raising the debt-to-equity ratio for renewable power and coal power project finance deals. We investigate the impact of the optimal non-financial contractual relationship between counterparties on the soundness of projects, differing in plant type and country risk. Key findings are: first, the existence of off-taking contracts generally raises the debt-to-equity ratio, while off-taking sponsors do not. In deed, the finding is more prominent in the renewable power projects in countries with investment grade. Overall, patterns of the optimal structure of non-financial contract vary with project type and country risk. 본 연구는 1995~2017년 동안 전 세계 재생에너지 발전소와 화석에너지 발전소 프로젝트 금융 트랜치 3,766건에 관해 프로젝트의 비재무적 계약 구조가 특별목적법인(SPC)의 레버리지 비율에 미치는 효과를 분석하였다. 본 연구의 주요 발견은 다음과 같다. 최종생산물구매계약의 체결은 특별목적법인의 레버리지 비율을 유의적으로 높이나, 주로 투자등급의 사업소재국의 재생에너지 발전 사업에서 크게 나타났다. 최종생산물계약을 사업자가 체결한 경우 오히려 사업 건전성이 낮아져서 레버리지 비율을 낮추었다. 종합적으로, 비재무적 계약이 자본구조에 미치는 영향은 발전소 사업 유형과 사업소재국 신용등급에 따라 다른 양상을 띠는 것으로 분석되었다.
문유진,박범수,김상규,김은수,임덕진 전력전자학회 2023 전력전자학회 논문지 Vol.28 No.1
This paper proposes a three-phase single-stage AC-DC converter for the small wind generation system. Input power factor improvement and insulated output can be implemented with the proposed three-phase single-stage AC-DC converter under the wide power generation voltage (80–260 Vac) and frequency (10–42 Hz) in a small wind power generation (WPG) system. The proposed converter is also capable of zero-voltage switching in the primary-side switches and zero-current switching in the secondary-side diodes by phase-shift control at a fixed switching frequency. In addition, it is possible to control a wide output voltage (Vo: 39 VDC– 60 VDC) by varying the link voltage and improving the input power factor (PF) and the total harmonic distortion factor (THDi). Simulation and experimental results verified the validity of the proposed converter.
오세운(Se-woon Oh),이창현(Chang-hyun Lee),김선목(Sun-mok Kim),임덕진(Deok-jin Lim),이기백(Ki-beak Lee) 대한전기학회 2021 전기학회논문지 Vol.70 No.1
In this paper, we propose a novel multi-object distinction method with class-agnostic object detection and class retreival. Multi-object distinction is usually divided into the processes of detecting and classifying an object. Since it is common for industrial applications to add new kinds of objects to be recognized, it is inefficient to re-train the system every time the new object is added. Thus, the propose method employs two deep learning models to solve this problem. 1) Class agnostic object detection model to predict the bounding boxes regardless of the classes of objects and 2) Class retrieval model to determine the classes of the objects. The experimental results show that the proposed method successfully detects and classifies the both experienced and inexperienced objects: the final classification accuracy for 15 learned objects was 98.0%, and for the other 30 new objects that had not been learned. the accuracy was 87.7% on average.