• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.89-94
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• 2006

For a development of the software which estimates the economics of a combined heat and power generation system in apartment estates, the thermal consumption and electric power consumption data were investigated in about 115 apartment estates. And the algorithm was developed, then the software was made by the macro function of the Excel spread sheets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3050-3063
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• 2023

Recommendation systems provide personalized products or services to online users by mining their past preferences. Collaborative filtering is a popular recommendation technique because it is easy to implement. However, with the rapid growth of the number of users in recommendation systems, collaborative filtering suffers from serious scalability and sparsity problems. To address these problems, a novel collaborative filtering recommendation algorithm is proposed. The proposed algorithm partitions the users using affinity propagation clustering, and searches for k nearest neighbors in the partition where active user belongs, which can reduce the range of searching and improve real-time performance. When predicting the ratings of active user's unrated items, mean deviation method is used to impute values for neighbors' missing ratings, thus the sparsity can be decreased and the recommendation quality can be ensured. Experiments based on two different datasets show that the proposed algorithm is excellent both in terms of real-time performance and recommendation quality.

• Environmental and Resource Economics Review
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• v.30 no.2
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• pp.237-268
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• 2021

As variable renewable sources rapidly increase due to the Energy Transition plan, integration cost of renewable sources to the power system is rising sharply. The increase in variable renewable energy reduces the capacity factor of existing traditional power capacity, and this undermines the efficiency of the overall power supply, and demand resources are drawing attention as a solution. In this study, we analyzed how much electric vehicle demand resouces, which has great potential among other demand resources, can reduce power supply costs if it is used as a flexible resource for renewable generation. As a methodology, a stochastic form of power system optimization model that can effectively reflect the volatile characteristics of renewable generation is used to analyze the cost induced by renewable energy and the benefits offered by electric vehicle demand resources. The result shows that virtual power plant-based direct control method has higher benefits than the time-of-use tariff, and the higher the proportion of renewable energy is in the power system, the higher the benefits of electric vehicle demand resources are. The net benefit after considering commission fee for aggregators and battery wear-and-tear costs was estimated as 67% to 85% of monthly average fuel cost under virtual power plant with V2G capability, and this shows that a sufficient incentive for market participation can be offered when a rate system is applied in which these net benefits of demand resources are effectively distributed to consumers.

• Environmental and Resource Economics Review
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• v.30 no.3
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• pp.435-469
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• 2021

The main purpose of this study is to identify the determinants of electricity import and export in 26 European Union countries using the Spatial durbin model(SDM). In particular, we would like to mainly explain it based on the amount of power generated by each energy source. Not just the usual way of constructing a weighting matrix based on contiguity, we adopt a weighting method based on the proportion of trade among countries with connected electricity systems. Moreover, the electricity systems of European countries are directly and indirectly connected, which is reflected in the weighting matrix. According to the results, nuclear power has a positive effect on exports and a negative effect on imports, and an increase in wind and solar power has a positive effect on both exports and imports by increasing power system instability. While Korea is unable to trade electricity due to geopolitical conditions, the results of this study are expected to provide implications for energy policies.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.3092-3098
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• 2011

This paper deals with analysis of measuring power dissipation when Maglev is running. With the various running scenarios for Maglev, power dissipation was measured and a comparative analysis of it and wheel-on rails were carried out. The purpose of this paper is to confirm the efficiency and economics on operation of Maglev and reflect detail design later. When the running scenarios of Maglev are the status of landing on and levitation, running at rated acceleration and deceleration and according to changes of velocity, the power dissipation was measured. The measured results are analyzed considering with apparent electric power and active power, reactive power and power factor etc. Due to the limited test track condition, it is very limited to compare and analyze Maglev and general trains. Nevertheless, It is a task of great significance to identify the efficiency and economics on operating Maglev through the results of measuring power dissipation. In the future, measuring power dissipation through more various scenarios will be carried out, and the results will be reflected the design.

• Environmental and Resource Economics Review
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• v.9 no.2
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• pp.333-347
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• 2000

We employed various econometic methods to estimate the production index elasticity and the price elasticity of elecricity demand in Korea and compared the forecasting power of those methods. Cointegration models (ADL model, Engle-Granger model, Full Informtion Maximum Likelihood method by Johansen and Juselius) and Dynamic OLS by Stock and Watson were considered. The forecasting power test shows that Dynamic OLS has the best forecasting power. According to Dynamic OLS, the production index elasticity and the price elasticity of electricity demand in Korea are 0.13 and -0.40, respectively.

• Environmental Engineering Research
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• v.21 no.4
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• pp.409-419
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• 2016

As a major energy consumption province, the issue about the carbon emissions in Hebei Province, China has been concerned by the government. The carbon emissions can be effectively reduced due to a more rational energy consumption structure. Thus, in this paper the constraint of low carbon emissions is considered as a foundation and four energies--coal, petroleum, natural gas and electricity including wind power, nuclear power and hydro-power etc are selected as the main analysis objects of the adjustment of energy structure. This paper takes energy cost minimum and carbon trading cost minimum as the objective functions based on the economic growth, energy saving and emission reduction targets and constructs an optimization model of energy consumption structure. And empirical research about energy consumption structure optimization in 2015 and 2020 is carried out based on the energy consumption data in Hebei Province, China during the period 1995-2013, which indicates that the energy consumption in Hebei dominated by coal cannot be replaced in the next seven years, from 2014 to 2020, when the coal consumption proportion is still up to 85.93%. Finally, the corresponding policy suggestions are put forward, according to the results of the energy structure optimization in Hebei Province.

• Environmental and Resource Economics Review
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• v.27 no.4
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• pp.695-723
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• 2018

Recently, extreme weather due to climate change has become more frequent, and increase of fine dust has worsen air quality in Korea. Therefore, not only negative perception on coal-fired power generation is dominant, but also the social acceptance of nuclear power generation declines. This study aims at deriving consumer preferences on the mid and long term power mix with various energy sources. Willingness to pay for each generation source was estimated and the preference heterogeneity of consumers was examined by using mixed logit and latent class models. Mixed logit estimation results show that the preference heterogeneity of consumers is especially large for the nuclear power relative to renewable or coal energy. According to the estimation results from the latent class model, group 1 prefers renewable energy while group 2 prefers coal energy. Group 3 shows lexicographic preference which means restricted rationality. As for the policy implication, it is necessary to understand the preference heterogeneity of consumer groups in planning the mid to long term power mix.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.121-122
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• 2007

Recently, there are two big paradigm shifts in the global electric power industry. First, the maintenance practice is gradually moved from time-based activities to reliability-centered activities. On the other hand, asset management is emerging as a new framework to maximize the efficiency of investments. The two paradigms are mutually exclusive in natural. Thus the power utilities usually chose the investment alternative on the basis of reliability in the past. But today's changed business environment - competition -requires the power utilities to compromise the trade-off of reliability effects and economics of investments. This paper shows what and how to interpret the reliability effects of distribution system investments into financial indicators beneficial for power utilities's managers to make decision on the perspective of corporate value.

• Journal of Power Electronics
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• v.19 no.6
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• pp.1393-1402
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• 2019

This paper proposes a new power flow control method for soft-switched, four channel, five level resonant buck dc-dc converters. These converters have two input channels, which can be supplied from sources with identical or different voltages, and four output channels with arbitrary output voltages. They are specially designed to supply multilevel inverters. The design methodology for their power flow control has been developed considering a general case when the input voltages, output voltages and loads can be asymmetrical. A special emphasize is paid to the limitations and restrictions of operation. The theoretical studies are confirmed by numerical simulations and laboratory tests carried out at various operation points. Exploiting the advantages of the newly proposed power control strategy, the converter can supply five level inverters in dc microgrids, active filters, power factor correctors and electric drives. They can also play an interfacing role in renewable energy systems.