• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.823-828
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• 2007

In compare with a major developed countries, Korea consumes much energy, but also eliminates much carbon dioxide. Agricultural sector eliminate much carbon dioxide than industrial sector. In Kyoto protocol, Korea needs to reduce carbon dioxide. One way to reduce carbon dioxide is utilization of biomass in rural area. This paper focus on utilization of biomass in rural area. If use 20% potential amount of biomass, it obtain 50% of TPES on agricultural sector. The condition of utilization biomass is connected with agricultural policy, environmental policy, and energy policy. And environmental restriction keep pace with economical incentive.

• New & Renewable Energy
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• v.18 no.4
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• pp.38-53
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• 2022

T Recently, the government has been promoting the expansion and supply of renewable energy as an alternative for achieving carbon neutrality and the nationally determined contributions by 2030. In 2020, the Ministries of Industry and Environment and the Korea Forest Service collaborated to build a nationwide onshore wind energy siting atlas considering wind resources and forestry and environmental regulations focused on central regulations. In this study, the ordinances of the local governments were analyzed to examine the effects of regional location regulations on the expansion of onshore wind power energy generation facilities, in addition to those of central regulations. A development permit standard survey of 226 urban plan ordinances of the local governments nationwide showed that presently in 2022, 52 municipalities are applying regulations on wind energy generation facilities by ordinances. This is twice more than that in 2018, when renewable energy power generation facility development was difficult. Additionally, the location regulations applied by these ordinances were organized by items and regions, and regulatory characteristics, such as the number and scope, were analyzed by regions. To analyze the spatial distribution characteristics, JeollaNamdo was selected as the case area. A spatial DB was established for regulated areas based on the regional and central regulations, and the spatial distribution characteristics and the regulatory scope were compared and analyzed.

• Journal of Energy Engineering
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• v.23 no.3
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• pp.36-41
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• 2014

The world's overall need for natural gas (NG) has been growing up fast, especially in the residential sector. The better the estimation of residential NG consumption (RNGC) distribution, the better decision-making for a residential NG policy such as pricing, demand estimation, management options and so on. Approximating the distribution of RNGC is complicated by zero observations in the sample. To deal with the zero observations by allowing a point mass at zero, a mixture model of RNGC distributions is proposed and applied. The RNGC distribution is specified as a mixture of two distributions, one with a point mass at zero and the other with full support on the positive half of the real line. The model is empirically verified for household RNGC survey data collected in Korea. The mixture model can easily capture the common bimodality feature of the RNGC distribution. In addition, when covariates were added to the model, it was found that the probability that a household has non-expenditure significantly varies with some variables. Finally, the goodness-of-fit test suggests that the data are well represented by the mixture model.

• IE interfaces
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• v.20 no.3
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• pp.353-362
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• 2007

This paper proposed the calculation method of the avoided cost for natural gas and district heating DSM programs. And the proposed method is applied to real DSM programs. The avoided cost for natural gas consists of commodity avoided cost, supply equipment avoided cost, storage equipment avoided cost, and electric power avoided cost. In case of the district heating, avoided cost consists of heat generation equipment avoided cost, heat energy avoided cost, environment avoided cost, and electric power avoided cost. This method can be used to evaluate the benefit of DSM programs quantitatively in cost. Therefore, this method can contribute to make the cost-effectiveness evaluation system and to operate the DSM programs for natural gas and district heating effectively.

• Journal of the Korean Solar Energy Society
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• v.39 no.6
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• pp.113-125
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• 2019

With the opening of the small power brokerage business market in December 2018, the small power trading market has started in Korea. Operators must submit the day-ahead estimates of power output and receive incentives based on its accuracy. Therefore, the accuracy of power generation forecasts is directly affects profits of the operators. The forecasting process for power generation can be divided into two procedure. The first is to forecast solar irradiation and the second is to transform forecasted solar irradiation into power generation. There are two methods for transformation. One is to simulate with physical model, and another is to use regression model. In this study, we found the best-fit regression model by analyzing hourly data of PV output and solar irradiation data during three years for 242 PV plants in Korea. The best model was not a linear model, but a sigmoidal model and specifically a Gompertz model. The combined linear regression and Gompertz curve was proposed because a the curve has non-zero y-intercept. As the result, R² and RMSE between observed data and the curve was significantly reduced.

• Advances in Energy Research
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• v.8 no.4
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• pp.243-252
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• 2022

The hybrid wind-solar energy concept has a big influence on the spread of wind and solar power projects in India since it combines the benefits of both industries while also providing extra benefits such as resource sharing such as land, infrastructure, and power evacuation systems. Furthermore, while the hybrid policy may reduce certain barriers to the installation of wind and solar energy in India, there are still some issues that must be resolved rapidly in order to ensure a sustainable installation. According to the study's findings, the installation of wind and solar power plants is significantly influenced by energy policy. The wind-solar hybrid energy strategy will also be crucial in the near future for growing the usage of renewable energy sources. Aside from that, the establishment of Green Energy Open Access (GEOA) and the restart of the trading of Renewable Energy Certificates (REC) would promote the quick deployment of standalone and hybrid renewable power projects throughout the nation, enabling it to reach 500 GW of installed non-fossil energy capacity by 2030.

• Korea Trade Review
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• v.47 no.5
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• pp.289-304
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• 2022

Korea's LNG and crude oil are the most important energy and export raw materials, but 100% import resources by overseas. However, tanker shipping companies, which play the most crucial role in energy cargo security, are very small in number and size, which can be a factor in the supply chain crisis. Therefore, this paper studied the policy of expanding tanker transportation necessary for the transport of crude oil and LNG in Korea. In the existing literature, there was no policy study necessary for tanker ships, but referring only to the importance of overseas energy development and transportation, so we tried to derive various demands necessary for expanding the tanker fleet through expert interviews and AHP which was conducted on 89 related energy institutions to derive policies and their priorities. The results of the study are as follows. As for the policy, the financial support policy was the highest priority, followed by the business and the mutual cooperation policy of related agencies. Tax support (22.6%) and ship financing (19.4%) were the highest priorities, followed by the Energy Intermediate Promotion Act (11.9%), Tanker Guarantee Insurance (10.6%), Energy Budget Independence (9.3%), and Korea Trader Development (8.2%). Energy governance (6.3%), information center establishment (6.2%), and energy procurement committee (5.5%) ranked seventh, eighth, and ninth. The research results show that it is necessary to supply sufficient ships to the market through the expansion of ship finance for tankers and to follow business support policies such as guarantee insurance. In addition, it was also possible to derive that the financial resources need to be determined by law and independent budgets for consistency and continuity.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2062-2066
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• 2022

Nuclear energy sources are indispensable in cost effectively achieving carbon neutral economy, where public opinion is critical to adoption as the consequences of nuclear accident can be catastrophic. In this context, discussion on spent nuclear fuel is a prerequisite to expanding nuclear energy, as it leads to the issue of radioactive waste disposal. Given the dearth of study on spent nuclear fuel public acceptance, we use text mining and big data analysis on the news article and public comments data on Naver news portal to identify the Korean public opinion on spent nuclear fuel. We identify that the Korean public is more interested in the nuclear energy policy than spent nuclear fuel itself and that the alternative energy sources affect the position towards spent nuclear fuel. We recommend relating spent nuclear fuel issue with nuclear energy policy and environmental issues of alternative energy sources to further promote spent nuclear fuel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1877-1891
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• 2022

As a part of cloud computing technology, algorithms for cloud task scheduling place an important influence on the area of cloud computing in data centers. In our earlier work, we proposed DeepEnergyJS, which was designed based on the original version of the policy gradient and reinforcement learning algorithm. We verified its effectiveness through simulation experiments. In this study, we used the Proximal Policy Optimization (PPO) algorithm to update DeepEnergyJS to DeepEnergyJSV2.0. First, we verify the convergence of the PPO algorithm on the dataset of Alibaba Cluster Data V2018. Then we contrast it with reinforcement learning algorithm in terms of convergence rate, converged value, and stability. The results indicate that PPO performed better in training and test data sets compared with reinforcement learning algorithm, as well as other general heuristic algorithms, such as First Fit, Random, and Tetris. DeepEnergyJSV2.0 achieves better energy efficiency than DeepEnergyJS by about 7.814%.

• Nuclear Engineering and Technology
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• v.50 no.5
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• pp.773-779
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• 2018

This study surveyed 137 policymakers and key stakeholders (e.g., employees of government agencies, academic institutions, nonprofit organizations, industry, and advocacy groups) involved in making decisions on nuclear energy policy, investigating how they differentially perceived the importance of scientific evidence in driving nuclear policy. We also identified the policy areas that each group of decision-makers are mostly concerned about and showed how such concerns might contextualize and ultimately shape their perceptions of science-driven policy.