• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.513-520
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• 2018

Since Paris Climate Change Conference in 2015, many policies to reduce the emission of greenhouse gas have been accelerating, which are mainly related to renewable energy resources and micro-grid. Presently, the technology development and demonstration projects are mostly focused on diversifying the power resources by adding wind turbine, photo-voltaic and battery storage system in the island-type small micro-grid. It is expected that the large-scaled micro-grid projects based on the regional district and town/complex city, e.g. the block type micro-grid project in Daegu national industrial complex will proceed in the near future. In this case, the economic cost or the carbon emission can be optimized by the efficient operation of energy mix and the appropriate construction of electric and heat supplying facilities such as cogeneration, renewable energy resources, BESS, thermal storage and the existing heat and electricity supplying networks. However, when planning a large residential town or city, the concrete plan of the energy infrastructure has not been established until the construction plan stage and provided by the individual energy suppliers of water, heat, electricity and gas. So, it is difficult to build the efficient energy portfolio considering the characteristics of town or city. This paper introduces an energy mix optimization(EMO) method to determine the optimal capacity of thermal and electric resources which can be applied in the design stage of the real large-scaled residential town or city, and examines the feasibility of the proposed method by applying the real heat and electricity demand data of large-scale residential towns with thousands of households and by comparing the result of HOMER simulation developed by National Renewable Energy Laboratory(NREL).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.708-717
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• 2009

Recently, Korea government decided to introduce RPS (Renewable Portfolio Standard) mechanism which requires electricity providers to gradually increase the amount of renewable energy sources such as wind, solar, bioenergy, and geothermal. As a consequence, it is expected that the long-term fuel mix would be changed to result in more expensive production and the increased production costs would be distributed to the rate payers via electricity tariffs. This paper presents the change in long-term fuel mix in year 2020 with the four RPS scenarios of 3%, 5%, 10% and 20%, and the methodologies for collecting the increased production costs through new tariff schedule. The studies on long-term fuel mix have been carried out with the GATE-PRO (Generation And Transmission Expansion Program) optimization package, a mixed-integer program developed by the Korea Energy Economics Institute and Hongik university. Three methodologies for distributing the production costs to the rate payers have also been demonstrated.

• Journal of the Korean Institute of Gas
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• v.10 no.4 s.33
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• pp.11-16
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• 2006

The purposes of this study is to develop a domestic MARKAL(MARKet ALlocation) model with construction of database system to find the technology mix for the electricity generation market in Korea. The MARKAL model is officially used for national energy system optimization in the International Energy Agency(IEA), and the role is becoming more important in relation to analyze the greenhouse gas mitigation potential and to evaluate the technologies. Four scenarios specially emphasized on the greenhouse gas reduction and technology mix of electric generation were applied, each of them covering the analysis periods between 2004 and 2040.

• Environmental and Resource Economics Review
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• v.11 no.2
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• pp.211-231
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• 2002

This paper summarizes the results of a study that assess how a demand side management (DSM) system addresses key economic and environmental challenges facing in the Korean natural gas sector considering; ${\bullet}$ high discrepancies of seasonal consumption volume and of load factor in unmatured domestic LNG market, ${\bullet}$ unfavorable and volatile international LNG market, imposing with the contestable "take-or-pay" contract terms, ${\bullet}$ low profile of LNG and existence of market barriers against an optimal fuel mix status in the industrial energy sector. A particular focus of this study is to establish an 'extended' DSM system in the unmatured gas market, especially in industry sector, that could play a key role to assure an optimum fuel mix scheme. Under the concept of 'extended' DSM, a system dynamics modeling approach has been introduced to explore the option to maximize economic benefits in terms of the national energy system optimization, entailing different ways of commitments accounting for different DSM measures and time delay scenarios. The study concludes that policy options exist that can reduce inefficiencies in gas industry and end-use system at no net costs to national economy. The most scenarios find that, by the year 2015, it is possible to develop a substantial potential of increased industrial gas end-uses under more reliable and stable load patterns. Assessment of sensitivity analysis suggests that time delay factor, in formulating DSM scenarios, plays a key role to overcome various market barriers in domestic LNG market and provides a strong justification for the policy portfolios 'just in time' (time accurateness), which eventually contribute to establish an optimum fuel mix strategy. The study indicates also the needs of advanced studies based on SD approach to articulate uncertainty in unmatured energy market analysis, including gas.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.2
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• pp.76-84
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• 2006

Interstate electric power system, as an alternative for energy cooperation under regional economic block, has been hotly debated before progressing the restructure in electric power industry and rapidly expanded in many regions after 1990s. Especially, since northeast asia has strong supplementation in resource, load shape, fuel mix etc., interconnection of electric power systems in this region may bring considerable economic benefits. This paper implements a mathematical optimization model, ORIRES, proposed by Russia, in analysing the economic feasibility of system interconnection. Additional analyses on the environmental impact of the system interconnection, and sensitivity of key factor inputs have been performed.

• Environmental and Resource Economics Review
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• v.28 no.2
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• pp.177-200
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• 2019

Energy demand forecast which serves as an essential input in energy policy is exposed to multiple factors of uncertainty such as GDP and weather forecast uncertainty. The Master Plan of Electricity Market in Korea which is biennially prepared is critically based on fluctuating energy demand forecast whereas its resulting proposal on electricity generation mix is substantially irreversible. The paper provides a real options model to evaluate energy transition policy by considering Knightian uncertainty as a measure to study multiple uncertainties with multiple set of probability distributions. Our finding is that the current energy transition policy under the master plan is not robust in terms of securing stable management of electricity demand and supply system.

• Journal of Energy Engineering
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• v.25 no.3
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• pp.114-129
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• 2016

Since the release of mid-term domestic GHG goals until 2020, in 2009, some various GHG reduction policies have been proposed to reduce the emission rate about 30% compared to BAU scenario. There are two types of modeling approaches for identifying options required to meet greenhouse gas (GHG) abatement targets and assessing their economic impacts: top-down and bottom-up models. Examples of the bottom-up optimization models include MARKAL, MESSAGE, LEAP, and AIM, all of which are developed based on linear programming (LP) with a few differences in user interface and database utilization. The bottom-up model for electric sector requires demand management, regeneration energy mix, fuel conversation, etc., thus it has a very complex aspect to estimate some various policies. In this paper, we suggest a bottom-up BAU model for electric sector and how we can build it through step-by-step procedures such that includes load region, hydro-dam and pumping storage.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.165-204
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• 2022

This study organized data from 2000 to 2014 for 20 grid-connected countries in Europe and analyzed the determinants of carbon emissions through the panel GLS method considering the problem of heteroscedasticity and autocorrelation. At the same time, the effect of introducing ETS was considered by dividing the sample period as of 2005 when the European emission trading system was introduced. Carbon emissions from individual countries were used as dependent variables, and proportion of generation by each source, power self-sufficiency ratio of neighboring countries, power production from resource-holding countries, concentration of power sources, total energy consumption per capita in the industrial sector, tax of electricity, net electricity export per capita, and size of national territory per capita. According to the estimation results, the proportion of nuclear power and renewable energy generation, concentration of power sources, and size of the national territory area per capita had a negative (-) effect on carbon emissions both before and after 2005. On the other hand, the proportion of coal power generation, the power supply and demand rate of neighboring countries, the power production of resource-holding countries, and the total energy consumption per capita in the industrial sector were found to have a positive (+) effect on carbon emissions. In addition, the proportion of gas generation had a negative (-) effect on carbon emissions, and tax of electricity were found to have a positive (+) effect. However, all of these were only significant before 2005. It was found that net electricity export per capita had a negative (-) effect on carbon emissions only after 2005. The results of this study suggest macroscopic strategies to reduce carbon emissions to green growth, suggesting mid- to long-term power mix optimization measures considering the electricity trade market and their role.