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Prof. Dr. Chul-Yong Lee
School of Business, Pusan National University, 2 Busandaehak-ro 63beon-gil, Geumjeong-gu, Busan 46241, Korea

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Research Keywords & Expertise

0 Management of Technology
0 Sustainable Management
0 Discrete Choice Analysis
0 Demand forecasting using Bayesian inference
0 Analysis of consumer preference

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Journal article
Published: 13 August 2021 in Sustainability
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Ship exhaust emission is the main cause of coastal air pollution, leading to premature death from cardiovascular cancer and lung cancer. In light of public health and climate change concerns, the International Maritime Organization (IMO) and several governments are reinforcing policies to use clean ship fuels. In January 2020, the IMO reduced the acceptable sulfur content in ship fuel to 0.5% m/m (mass/mass) for sustainability. The use of liquified natural gas (LNG) as a ship fuel is currently the most likely measure to meet this regulation, and LNG bunkering infrastructure investment and network planning are underway worldwide. Therefore, the aim of this study is to predict the LNG bunkering demand for investment and planning. So far, however, there has been little quantitative analysis of LNG bunkering demand prediction. In this study, first, the global LNG bunkering demand was predicted using meta-regression analysis. Global demand for LNG bunkering is forecast to increase from 16.6 million tons in 2025 to 53.2 million tons in 2040. Second, LNG bunkering prediction by country and region was performed through analogy and artificial intelligence methods. The information and insights gained from this study may facilitate policy implementation and investments.

ACS Style

Gi-Young Chae; Seung-Hyun An; Chul-Yong Lee. Demand Forecasting for Liquified Natural Gas Bunkering by Country and Region Using Meta-Analysis and Artificial Intelligence. Sustainability 2021, 13, 9058 .

AMA Style

Gi-Young Chae, Seung-Hyun An, Chul-Yong Lee. Demand Forecasting for Liquified Natural Gas Bunkering by Country and Region Using Meta-Analysis and Artificial Intelligence. Sustainability. 2021; 13 (16):9058.

Chicago/Turabian Style

Gi-Young Chae; Seung-Hyun An; Chul-Yong Lee. 2021. "Demand Forecasting for Liquified Natural Gas Bunkering by Country and Region Using Meta-Analysis and Artificial Intelligence." Sustainability 13, no. 16: 9058.

Journal article
Published: 18 August 2020 in Transportation Research Part D: Transport and Environment
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Under the new climate-change regime, electric vehicles (EVs) have received particular attention for their ability to help mitigate greenhouse gas emissions. The government is looking to implement a vehicle-to-grid (V2G) service for EV use. The present study estimates the economic value of a V2G service, adopting the contingent valuation approach. An online contingent valuation oriented survey of 1007 interviewees was conducted for deriving their willingness-to-accept for the service. The mean willingness-to-accept estimate was achieved as KRW 9821 (USD 8.83) per month, per vehicle; thus, the estimated annual benefit amounted to KRW 117,852 (USD 106.01). The findings can offer a valuable guideline for determining the economic feasibility of a V2G service. From a management perspective, the results can help primary stakeholders decide the optimal price level for that service.

ACS Style

Chul-Yong Lee; Jung-Woo Jang; Min-Kyu Lee. Willingness to accept values for vehicle-to-grid service in South Korea. Transportation Research Part D: Transport and Environment 2020, 87, 102487 .

AMA Style

Chul-Yong Lee, Jung-Woo Jang, Min-Kyu Lee. Willingness to accept values for vehicle-to-grid service in South Korea. Transportation Research Part D: Transport and Environment. 2020; 87 ():102487.

Chicago/Turabian Style

Chul-Yong Lee; Jung-Woo Jang; Min-Kyu Lee. 2020. "Willingness to accept values for vehicle-to-grid service in South Korea." Transportation Research Part D: Transport and Environment 87, no. : 102487.

Journal article
Published: 11 June 2020 in Energies
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With the development of renewable energy, a key measure for reducing greenhouse gas emissions, interest in the levelized cost of electricity (LCOE) is increasing. Although the input variables used in the LCOE calculation, such as capacity factor, capital expenditure, annual power plant operations and maintenance cost, discount and interest rate, and economic life, vary according to region and project, most existing studies estimate the LCOE by using a deterministic methodology. In this study, the stochastic approach was used to estimate the LCOE for solar photovoltaic (PV) in South Korea. In addition, this study contributed to deriving realistic analysis results by securing the actual data generated in the solar PV project compared to the existing studies. The results indicate that the LCOE for commercial solar power ranged from KRW 115 (10 cents)/kWh to KRW 197.4 (18 cents)/kWh at a confidence level of 95%. The median was estimated at KRW 160.03 (15 cents)/kWh. The LCOE for residential solar power ranged from KRW 109.7 (10 cents)/kWh to KRW 194.1 (18 cents)/kWh at a 95% confidence level and a median value of KRW 160.03 (15 cents)/kWh. A sensitivity analysis shows that capital expenditure has the most significant impact on the LCOE for solar power, followed by the discount rate and corporate tax. This study proposes that policymakers implement energy policies to reduce solar PV hardware and soft costs.

ACS Style

Chul-Yong Lee; Jaekyun Ahn. Stochastic Modeling of the Levelized Cost of Electricity for Solar PV. Energies 2020, 13, 3017 .

AMA Style

Chul-Yong Lee, Jaekyun Ahn. Stochastic Modeling of the Levelized Cost of Electricity for Solar PV. Energies. 2020; 13 (11):3017.

Chicago/Turabian Style

Chul-Yong Lee; Jaekyun Ahn. 2020. "Stochastic Modeling of the Levelized Cost of Electricity for Solar PV." Energies 13, no. 11: 3017.

Journal article
Published: 10 May 2020 in Energies
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Under the new climate regime, renewable energy (RE) has received particular attention for mitigating the discharge of greenhouse gas. According to the third energy master plan in South Korea, by 2040, 30–35% of the energy demand must met with RE sources. To ensure relevant policy design to achieve this goal, it is crucial to analyze the public’s willingness to accept community-based RE projects. This study conducted a nationwide survey to understand the opinion of the public and also that of local inhabitants living near a RE project. A choice experiment was employed to measure public preferences toward RE projects. The analysis reveals that the type of energy source, distance to a residential area, and annual percentage incentives could affect acceptance levels. Additionally, investment levels were a factor in local inhabitants’ acceptance of energy-related projects. This study presents the relevant policy implications in accordance with the analysis results.

ACS Style

Rahel Renata Tanujaya; Chul-Yong Lee; JongRoul Woo; Sung-Yoon Huh; Min-Kyu Lee. Quantifying Public Preferences for Community-Based Renewable Energy Projects in South Korea. Energies 2020, 13, 2384 .

AMA Style

Rahel Renata Tanujaya, Chul-Yong Lee, JongRoul Woo, Sung-Yoon Huh, Min-Kyu Lee. Quantifying Public Preferences for Community-Based Renewable Energy Projects in South Korea. Energies. 2020; 13 (9):2384.

Chicago/Turabian Style

Rahel Renata Tanujaya; Chul-Yong Lee; JongRoul Woo; Sung-Yoon Huh; Min-Kyu Lee. 2020. "Quantifying Public Preferences for Community-Based Renewable Energy Projects in South Korea." Energies 13, no. 9: 2384.

Journal article
Published: 15 June 2019 in Renewable and Sustainable Energy Reviews
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Several countries have recently adopted models of community-based renewable energy projects, mainly in order to improve the local community’s acceptance of renewable energy facilities. This study analyzes the South Korea’s general public and local residents’ acceptance of community-based renewable energy projects using the contingent valuation method. Respondents’ willingness to participate in a renewable energy project are measured by the expected return on investment in the project. Analysis results indicate that the average annual rate of return expected by the general public is 3.1% for solar photovoltaic power plants, 5.4% for wind power, and 7.1% for biomass power plants. For local residents, the average annual rate of return expected by local residents is 12.3% for solar photovoltaic power plants, 9.1% for wind power, and 10.8% for biomass power plants. These results show that acceptance is markedly lower among local residents in comparison with the general public. However, simulation results prove that it is possible to provide local residents with returns beyond their expectation if the entirety of the additional incentives under the current system are given to them. Relevant policy implications and recommendations are provided based on the analysis results.

ACS Style

JongRoul Woo; Sungsam Chung; Chul-Yong Lee; Sung-Yoon Huh. Willingness to participate in community-based renewable energy projects: A contingent valuation study in South Korea. Renewable and Sustainable Energy Reviews 2019, 112, 643 -652.

AMA Style

JongRoul Woo, Sungsam Chung, Chul-Yong Lee, Sung-Yoon Huh. Willingness to participate in community-based renewable energy projects: A contingent valuation study in South Korea. Renewable and Sustainable Energy Reviews. 2019; 112 ():643-652.

Chicago/Turabian Style

JongRoul Woo; Sungsam Chung; Chul-Yong Lee; Sung-Yoon Huh. 2019. "Willingness to participate in community-based renewable energy projects: A contingent valuation study in South Korea." Renewable and Sustainable Energy Reviews 112, no. : 643-652.

Journal article
Published: 28 March 2019 in Energies
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To increase acceptance of new nuclear power plants (NPPs) by local communities, some countries offer those communities economic incentives. This study analyzes potential residents’ preferences for economic incentives provided during the construction and operation of NPPs in South Korea. This study uses stated preference data through a discrete choice experiment and the mixed logit model to reflect the heterogeneity of respondents’ preferences. The analysis results confirm heterogeneity by various incentive types, and show that respondents consider the distance between the NPP and the residential area as well as reduced electricity bills as crucial attribute of new NPPs. In addition, the result for the marginal willingness to be near to an NPP shows that reduced electricity bills, construction of new public facilities, and increased residents’ participation are relatively more effective incentives than job creation or solar panel installation. In particular, increased residents’ participation could greatly improve acceptance although it is not a direct form of financial support. The simulation analysis results indicate that acceptance of NPPs rapidly reduces as distance to the plant becomes shorter, although acceptance can change within a 0–30% range depending on the level of incentives. Several policy implications are suggested for policymakers based on the results.

ACS Style

Sung-Yoon Huh; JongRoul Woo; Chul-Yong Lee. What Do Potential Residents Really Want When Hosting a Nuclear Power Plant? An Empirical Study of Economic Incentives in South Korea. Energies 2019, 12, 1199 .

AMA Style

Sung-Yoon Huh, JongRoul Woo, Chul-Yong Lee. What Do Potential Residents Really Want When Hosting a Nuclear Power Plant? An Empirical Study of Economic Incentives in South Korea. Energies. 2019; 12 (7):1199.

Chicago/Turabian Style

Sung-Yoon Huh; JongRoul Woo; Chul-Yong Lee. 2019. "What Do Potential Residents Really Want When Hosting a Nuclear Power Plant? An Empirical Study of Economic Incentives in South Korea." Energies 12, no. 7: 1199.

Journal article
Published: 06 March 2019 in Sustainability
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As a major option for reducing greenhouse gas emission and sustainable development, renewable generation is rapidly expanding in the power sector. However, the variability and uncertainty of renewable generation undermine the reliability of the power system, requiring additional reserve capacities. This study estimates the costs induced by additional reserve capacities to reduce the uncertainty of solar generation in the Korean power system and analyzes the effectiveness of the Energy Storage System (ESS) in reducing these costs, using the stochastic form of multi-period security-constraint optimal power flow. To determine the input of stochastic solar generation, an ARMAX model and Monte Carlo method are applied for representative solar farms. The results indicate solar power generation by 2029 would increase the required reserve by 56.2% over the current level but coupling a 10 GWh of lithium-ion ESS would reduce it by 61.1% compared to increased reserve level for 2029. The operating cost reduction (benefit) by ESS would be 80.8% higher in 2029 compared to the current level and cover 89.9% of its installation cost. The benefit of ESS will be improved when (1) offer prices of reserves correctly reflect the true opportunity cost of providing reserve services and (2) more variable renewable energies are deployed.

ACS Style

Wooyoung Jeon; Chul-Yong Lee. Estimating the Cost of Solar Generation Uncertainty and the Impact of Collocated Energy Storage: The Case of Korea. Sustainability 2019, 11, 1389 .

AMA Style

Wooyoung Jeon, Chul-Yong Lee. Estimating the Cost of Solar Generation Uncertainty and the Impact of Collocated Energy Storage: The Case of Korea. Sustainability. 2019; 11 (5):1389.

Chicago/Turabian Style

Wooyoung Jeon; Chul-Yong Lee. 2019. "Estimating the Cost of Solar Generation Uncertainty and the Impact of Collocated Energy Storage: The Case of Korea." Sustainability 11, no. 5: 1389.