• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3336-3346
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• 2022

In general, a number of severe accident scenarios derived from Level 2 probabilistic safety assessment (PSA) are typically grouped into several categories to efficiently evaluate their potential impacts on the public with the assumption that scenarios within the same group have similar source term characteristics. To date, however, grouping by similar source terms has been completely reliant on qualitative methods such as logical trees or expert judgements. Recently, an exhaustive simulation approach has been developed to provide quantitative information on the source terms of a large number of severe accident scenarios. With this motivation, this paper proposes a machine learning-based categorization method based on exhaustive simulation for grouping scenarios with similar accident consequences. The proposed method employs clustering with an autoencoder for grouping unlabeled scenarios after dimensionality reductions and feature extractions from the source term data. To validate the suggested method, source term data for 658 severe accident scenarios were used. Results confirmed that the proposed method successfully characterized the severe accident scenarios with similar behavior more precisely than the conventional grouping method.

• 에너지협의회보
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• s.76
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• pp.44-57
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• 2006

이 자료는 지난 5월 24일 중국 소흥시에서 개최된 WEC 아태지역 에너지 시나리오 워크숍 및 역내 회원국 회의에서‘Energy Policy Scenarios to 2050’을 위한 아태지역 국가별 보고서 중 에너지경제연구원 김남일 박사가 발표한 우리나라의 국가 보고서 내용 입니다.

• Asian Journal of Atmospheric Environment
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• v.8 no.1
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• pp.59-68
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• 2014

The Fukushima nuclear accident in 2011 had an extensive impact on the national electricity plans. This paper outlines alternative electricity scenarios that meet the goals of nuclear phase-out and greenhouse gas (GHG) emission reduction. This paper also analyzes the results of each scenario in respect to the electricity mix, GHG emissions, costs and employment effects. The Long-range Energy Alternatives Planning system (LEAP) model was used to simulate the annual electricity demand and supply system from 2011 to 2030. The reference year was 2009. Scenarios are reference (where existing plans are continued), A1, A2, B1, B2, and C2 (where the levels of demand management and nuclear phase-out are different). The share of renewable energy in the electricity mix in 2030 for each scenario will be increased from about 1% in 2009 to 8% in the reference scenario and from 11% to 31% in five alternative scenarios. Total cumulative cost increases up to 14% more than the reference scenario by replacing nuclear power plants with renewable energy in alternative scenarios could be affordable. Deploying enough renewable energy to meet such targets requires a roadmap for electricity price realization, expansion of research, development and deployment for renewable energy technologies, establishment of an organization dedicated to renewable energy, and ambitious targets for renewable energy.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.188-188
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• 2004

In the present study, a multicriteria decision-making (MCDM) problem of ranking of important radionuclide release scenarios in a low and intermediate radioactive waste repository is to treat on the basis of non-additive fuzzy measures and fuzzy integral theory. Ranking of important scenarios can lead to the provision of more effective safety measure in a design stage of the repository. The ranking is determined by a relative degree of appropriateness of scenario alternatives.(omitted)

• Journal of the Korean Solar Energy Society
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• v.26 no.3
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• pp.119-125
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• 2006

The impacts of climate changes on building energy demand were investigated by means of the degree-days method. Future trends for the 21st century was assessed based on climate change scenarios with 7 global climate models(GCMs). We constructed hourly weather data from monthly temperatures by Trnsys 16. A procedure to estimate heating degree-days (HDD) and cooling degree-days (CDD) from monthly temperature data was developed and applied to three scenarios for Inchon. In the period 1995-2080, HDD would fall by up to 70%. A significant increase in cooling energy demand was found to occur between 1995-2004(70% based on CDD). During 1995-2080, CDD would Increase by up to 120%. Our analysis shows widely varying shifts in future energy demand depending on season. Heating costs in winter will significantly decrease whereas more expensive electrical cooling energy will be needed.

• Advances in Energy Research
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• v.5 no.1
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• pp.57-64
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• 2017

Electricity is basic need for country development. But at the present time proper planning and policy is require at high pace for power generation network extension due to the increasing population growth rate. Present study aimed to analyze the present and future demand for electricity at household level in Province of Balochistan of Pakistan via simulation modeling. Data of year 2004-2005 was used as baseline data for electricity consumption to predict future demand of electricity at both rural and urban domestic level up to subsequent 30 years, with help of LEAP software. Basically three scenarios were created to run software. One scenario was Business-As-Usual and other two were green scenarios i.e., solar and wind energy scenarios. Results predicted that by using alternative energy sources, demand for electricity will be fulfill and will also reduce burden on non-renewable energy sources due to the greater potential for solar and wind energy present in Balochistan.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.789-794
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• 2006

The potential impacts of climate change on heating and cooling energy demand were investigated by means of transient building energy simulations and hourly weather data scenarios for Inchon. Future trends for the 21 st century was assessed based oil climate change scenarios with 7 global climate models(GCMs), We constructed hourly weather data from monthly temperatures and total incident solar radiation ($W/m^2$) and then simulated heating and cooling load by Trnsys 16 for Inchon. For 2004-2080, the selected scenarios made by IPCC foresaw a $3.7-5.8^{\circ}C$rise in mean annual air temperature. In 2004-2080, the annual cooling load for a apartment with internal heat gains increased by 75-165% while the heating load fell by 52-71%. Our analysis showed widely varying shifts in future energy demand depending on the season. Heating costs will significantly decrease whereas more expensive electrical energy will be needed of air conditioning during the summer.

• Environmental and Resource Economics Review
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• v.21 no.3
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• pp.543-572
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• 2012

This paper compared historical energy use from 2000 between Japan and Korea and reviewed literature of mid-and long-term low carbon energy scenarios and plans in both countries released since 2000. In terms of energy use pattern, there are similarities between Korea and Japan; high dependence on energy imports, high proportion of manufacturing industry among OECD countries, closed electricity system disconnected with foreign countries, and high proportion of nuclear power generation with low proportion of renewable electricity despite of high potential of renewable energy. Differences are as follows; decreasing trend in Japan and increasing trend in Korea in terms of energy demand and supply, difficulty of exchanging electricity between regions in Japan unlike Korea, and prospect of nuclear power, that is, curtailing in Japan while expanding in Korea according to governmental plan. Energy Basic Plan in both countries established before nuclear accident in Fukushima required expanding about two times of nuclear energy by 2030, while civil society's energy scenarios suggested reducing energy demand, phasing-out nuclear power, and expanding renewable energy. This paper will serve as a base for future studies about long-term energy scenarios and plan in Japan and Korea.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.1
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• pp.47-58
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• 2019

The paper presents the results of a multi-criteria comparative evaluation of 12 feasible Russian nuclear energy deployment scenarios with thermal and fast reactors in a closed nuclear fuel cycle. The comparative evaluation was performed based on 6 performance indicators and 5 different MCDA methods (Simple Scoring Model, MAVT / MAUT, AHP, TOPSIS, PROMETHEE) in accordance with the recommendations elaborated by the IAEA/INPRO section. It is shown that the use of different MCDA methods to compare the nuclear energy deployment scenarios, despite some differences in the rankings, leads to well-coordinated and similar results. Taking into account the uncertainties in the weights within a multi-attribute model, it was possible to rank the scenarios in the absence of information regarding the relative importance of performance indicators and determine the preference probability for a certain nuclear energy deployment scenario. Based on the results of the uncertainty/sensitivity analysis and additional analysis of alternatives as well as the whole set of graphical and attribute data, it was possible to identify the most promising nuclear energy deployment scenario under the assumptions made.

• Journal of Radiation Protection and Research
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• v.28 no.3
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• pp.239-245
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• 2003

Every nuclear power plant measured concentrations of tritium in groundwater and surface water around the plants periodically. It was not easy to predict the tritium concentration only with these measurement data in case of various release scenarios. KAERI developed a new approach to find the relationship between the tritium release rate and tritium concentration in the environment. The approach was based upon a dynamic compartment model. In this paper the dynamic compartment model was modified to predict the tritium behavior more accurately. The mechanisms considered for the transfer of tritium between the compartments were evaporation, groundwater flow, infiltration, runoff, and hydrodynamic dispersion. Time dependent source terms of the compartment model were introduced to refine the release scenarios. Also, transfer coefficients between the compartments were obtained using realistic geographical data. In order to illustrate the model various release scenarios were developed, and the change of tritium concentration in groundwater and surface water around the nuclear power plants was estimated.