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Wooyoung Jeon
Department of Economics, Chonnam National University, Gwangju 61186, Korea

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Journal article
Published: 24 August 2020 in Energies
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An increase in variable renewable energy sources and soaring electricity demand at peak hours undermines the efficiency and reliability of the power supply. Conventional supply-side solutions, such as additional gas turbine plants and energy storage systems, can help mitigate these problems; however, they are not cost-effective. This study highlights the potential value of electric vehicle demand response programs by analyzing three separate scenarios: electric vehicle charging based on a time-of-use tariff, smart charging controlled by an aggregator through virtual power plant networks, and smart control with vehicle-to-grid capability. The three programs are analyzed based on the stochastic form of a power system optimization model under two hypothetical power system environments in Jeju Island, Korea: one with a low share of variable renewable energy in 2019 and the other with a high share in 2030. The results show that the cost saving realized by the electric vehicle demand response program is higher in 2030 and a smart control with vehicle-to-grid capability provides the largest cost saving. When the costs of implementing an electric vehicle demand response are considered, the difference in cost saving between the scenarios is reduced; however, the benefits are still large enough to attract customers to participate.

ACS Style

Wooyoung Jeon; Sangmin Cho; Seungmoon Lee. Estimating the Impact of Electric Vehicle Demand Response Programs in a Grid with Varying Levels of Renewable Energy Sources: Time-of-Use Tariff versus Smart Charging. Energies 2020, 13, 4365 .

AMA Style

Wooyoung Jeon, Sangmin Cho, Seungmoon Lee. Estimating the Impact of Electric Vehicle Demand Response Programs in a Grid with Varying Levels of Renewable Energy Sources: Time-of-Use Tariff versus Smart Charging. Energies. 2020; 13 (17):4365.

Chicago/Turabian Style

Wooyoung Jeon; Sangmin Cho; Seungmoon Lee. 2020. "Estimating the Impact of Electric Vehicle Demand Response Programs in a Grid with Varying Levels of Renewable Energy Sources: Time-of-Use Tariff versus Smart Charging." Energies 13, no. 17: 4365.

Journal article
Published: 13 May 2019 in Energy Policy
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The current Korean administration is driving change in the power sector by gradually phasing out nuclear power plants, expanding the use of renewable energy, and imposing restrictions on the operation of coal power plants. Considering these changes, the marginal abatement cost (MAC) curve would provide crucial information to determine an appropriate greenhouse gas reduction target, especially for 2030. This study derives the MAC curves for the Korean power sector in 2030 using a bottom-up optimization model with three scenarios based on different carbon pricing schedules. In addition, the carbon price required to achieve the CO2 emission targets in the Korean power sector in 2030 are estimated. The results show that a carbon price of 135–157 US$/tCO2 would be required to achieve the 2030 emission target for the power sector. By comparing the MAC curves of three different scenarios, we can reiterate the fact that early action regarding climate change mitigation is more effective and efficient than delayed action.

ACS Style

Young-Hwan Ahn; Wooyoung Jeon. Power sector reform and CO2 abatement costs in Korea. Energy Policy 2019, 131, 202 -214.

AMA Style

Young-Hwan Ahn, Wooyoung Jeon. Power sector reform and CO2 abatement costs in Korea. Energy Policy. 2019; 131 ():202-214.

Chicago/Turabian Style

Young-Hwan Ahn; Wooyoung Jeon. 2019. "Power sector reform and CO2 abatement costs in Korea." Energy Policy 131, no. : 202-214.

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.

Journal article
Published: 13 August 2018 in Sustainability
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The recent rise in demand for electric vehicles (EV) and energy storage supporting power systems has increased the demand for lithium-ion batteries (LIB), and it is expected to be more significant in near future. However, materials for LIB, such as lithium and cobalt, may face limited supply due to oligopolistic market characteristics, and this can have a significant impact on prices of LIB materials. This paper examines the dynamics of LIB raw material prices (cobalt, lithium, nickel, and manganese prices) with EV demand using the Vector Error Correction Model (VECM) method. The result shows that the EV demand is important in short-run dynamics of cobalt and lithium prices, which indicates that the recent increase in lithium and cobalt prices has been caused by increase in EV demand. In the long-run equilibrium, lithium and nickel prices move inversely with cobalt prices. The impulse response results confirm that EV demand has an immediate positive effect on cobalt price, and the effect maintains over two years. On the other hand, the EV demand shock to nickel, lithium, and manganese prices is relatively small. This study also analyses the impact of recycling policy of LIB on material prices. Finally, the paper discusses the policy implications for stabilizing material prices of LIB.

ACS Style

Jung Youn Mo; Wooyoung Jeon. The Impact of Electric Vehicle Demand and Battery Recycling on Price Dynamics of Lithium-Ion Battery Cathode Materials: A Vector Error Correction Model (VECM) Analysis. Sustainability 2018, 10, 2870 .

AMA Style

Jung Youn Mo, Wooyoung Jeon. The Impact of Electric Vehicle Demand and Battery Recycling on Price Dynamics of Lithium-Ion Battery Cathode Materials: A Vector Error Correction Model (VECM) Analysis. Sustainability. 2018; 10 (8):2870.

Chicago/Turabian Style

Jung Youn Mo; Wooyoung Jeon. 2018. "The Impact of Electric Vehicle Demand and Battery Recycling on Price Dynamics of Lithium-Ion Battery Cathode Materials: A Vector Error Correction Model (VECM) Analysis." Sustainability 10, no. 8: 2870.

Journal article
Published: 04 October 2017 in Sustainability
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In recent years, increasing requests to reduce greenhouse gas emissions have led to renewable resources rapidly replacing conventional power sources. However, the inherent variability of renewable sources reduces the reliability of power systems. Energy storage has been proposed as a viable alternative, as it can mitigate the variability of renewable energy sources and increase the efficiency of power systems by lowering peak electricity demand. In this study, we evaluate the benefits of integrating energy storage with combined wind and solar power generation in the Korean power system through using the dynamic optimization method. Realistic wind and photovoltaic solar power generation scenarios were estimated for actual sites. The results show that the wind power-based system benefitted more from energy storage than the combined wind and solar photovoltaic power-based system. This is because the high variability of wind power was reduced when it was combined with solar power. Co-optimization for energy and reserve costs was more beneficial than optimization for energy costs alone, which suggests that the reliability offered by storage is an important cost-saving factor, in addition to the reduction of energy costs by price arbitrage. Finally, the analysis was conducted under various scenarios to determine the validity of energy storage cost effectiveness.

ACS Style

Jung Youn Mo; Wooyoung Jeon. How Does Energy Storage Increase the Efficiency of an Electricity Market with Integrated Wind and Solar Power Generation?—A Case Study of Korea. Sustainability 2017, 9, 1797 .

AMA Style

Jung Youn Mo, Wooyoung Jeon. How Does Energy Storage Increase the Efficiency of an Electricity Market with Integrated Wind and Solar Power Generation?—A Case Study of Korea. Sustainability. 2017; 9 (10):1797.

Chicago/Turabian Style

Jung Youn Mo; Wooyoung Jeon. 2017. "How Does Energy Storage Increase the Efficiency of an Electricity Market with Integrated Wind and Solar Power Generation?—A Case Study of Korea." Sustainability 9, no. 10: 1797.