최동구 교수

The electricity sector in Korea is facing complex sustainability issues with recent government energy policy reprioritizing social and environmental concerns over economics. As a response, we developed a multi-criteria decision making (MCDM) model linked to an energy-system model to assess the sustainability of different policy scenarios in the Korean electricity sector. Our analysis shows that, while the new transition policy is not an attractive option in total cost and emissions, it can be de

The plan to shift towards renewable energy has recently become the central part of the energy policy on the power system in South Korea. The sudden shift towards renewable energy has raised questions regarding the reliability and flexibility of the power system. This paper proposes a research framework to evaluate the new policy in South Korea from various aspects using three simulation models in a series. The first optimal generation model finds the optimal electricity generation mix and provid

We investigate the causes behind the underwhelming adoption of voluntary Time‐of‐Use (TOU) tariffs in the residential electricity market. TOU tariffs are deployed by utilities to better match electricity generation capacity with market demand by giving consumers price incentives to reduce their consumption when electricity demand is at its peak. However, consumers in residential electricity markets are heterogeneous in their consumption preferences. Hence, utilities face a trade‐off when deployi

Adoption of electric vehicles (EVs) would affect the costs and sources of electricity and the United States efficiency requirements for conventional vehicles (CVs). We model EV adoption scenarios in each of six regions of the Eastern Interconnection, containing 70% of the United States population. We develop electricity system optimization models at the multidecade, day-ahead, and hour-ahead time scales, incorporating spatial wind energy modeling, endogenous modeling of CV efficiencies, projecti

<b>Purpose</b>: This study builds a stochastic model of a discrete-time Markov chain (DTMC) that fits well with a dataset of professional playing records. <b>Methods</b>: The point-by-point dataset of Men's single matches played in the Association of Tennis Professionals (ATP) tour from 2011 to 2015 is analyzed. A long-debated assumption on the <i>iid</i>-ness in the point winning probability of the server is statistically tested. A DTMC model is then developed to analyze the dataset further. <b