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Binding constraints를 고려한 딥러닝 기반 최적조류계산 모델 및 대형계통 적용 사례 연구
윤상민,신한솔,곽규형,오효빈,윤형석,김욱 대한전기학회 2023 전기학회논문지 Vol.72 No.4
Recently, research using machine learning and deep learning is being conducted to quickly solve the AC optimal power flow (AC OPF) problem. The problem with the existing research is that, unlike the actual system, it did not consider the generator start-up status according to demand change by using a test system in which the minimum power generation of the generator is zero. This paper proposes a deep learning-based AC OPF model and post-processing for a simulated large-scale system in Korea. It is a difficult problem to predict in Korea's large-scale simulation system as the generator start-up status changes as the demand changes. Accordingly, the accuracy of the deep neural network model, which is a deep learning algorithm, was increased by inserting the binding constraints and generator start-up status as variables. In addition, we want to satisfy the constraints of AC OPF with post-processing including the merit order stack model and AC power flow.
실계통기반 제약조건 반영에 따른 계통한계가격과 시장참여자 편익 분석연구
장재훈,신한솔,곽규형,오효빈,윤형석,김 욱 대한전기학회 2024 전기학회논문지 Vol.73 No.1
The Korean electricity market previously determined the system marginal price (SMP) without considering actual operational constraints under the Cost Based Pool electricity market system. Recently, in order to improve system operational problems, the pricing methodology was revised to reflect constraints, with the goal of introducing the actual system-based day-ahead market. However, there are no studies comparing the methodologies before and after this change. This study used a mathematical model to simulate pricing methodologies both before and after the revision, deriving SMP, social welfare, and congestion surplus. This study evaluated the impact of the methodology change on the electricity market and underscored the need for further congestion cost studies. An analysis of this revision can serve as a reference for market and system operators to refine the domestic power market's pricing approach. It also assists market participants in managing financial risks and establishing countermeasures due to the methodology change.
임은정,조승화,강현진,오효빈,김영수,정도연 한국식품저장유통학회 2023 한국식품저장유통학회지 Vol.30 No.4
This study aimed to develop high value-added mulberry (Morus alba) vinegar by fermenting mulberry with yeast and acetic acid bacteria, for using it in various foods. To select the optimal strain for mulberry fermentation, different strains were tested and Saccharomyces cerevisiae SRCM101756 and Acetobacter pasteurianus SRCM102419, exhibiting excellent alcohol and acetic acid production ability during mulberry fermentation, were selected for fermentation. Mulberry vinegar was prepared using mulberry wine and the selected acetic acid bacteria, and the physicochemical properties and physiological effects were measured. The pH was 2.98 and total acidity was 4.70% by day 9 of fermentation, establishing the possibility of developing them into vinegars for industrial use. The α- glucosidase inhibition activity of mulberry vinegar increased from 13.22% to 19.19% in the 100-fold dilution, and from 42.35% to 46.11% in the 50-fold dilution, from before fermentation to after fermentation, respectively. The angiotensin- converting enzyme inhibition activity of mulberry vinegar was found to significantly increase from 44.82% before fermentation to 63.88% after fermentation in the 25-fold dilution. Moreover, a significant increase in pancreatic lipase inhibition activity after fermentation was observed. Thus, mulberry vinegar can be used as a functional material in vinegar and other foods.