• Journal of the Korean Professional Engineers Association
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• v.41 no.3
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• pp.50-54
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• 2008

Recently most companies require various type of energy sources, in order to be more energy efficient in their plant due to the increasing current oil price. So, the multi-national companies are shaping ideas how to reduce energy costs and use substitute energy. The purpose of this study Is to attempt to save energy by making more valuable high pressure steam through TVR(Thermal Vapor Recompressor) from the surplus low pressure steam of HRB(Heat Recovery Boiler) in sulfuric acid plant.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.1
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• pp.30-45
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• 2013

Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.76.1-76.1
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• 2011

With the growing penetration of distributed generation including from renewable sources, smart grid power system is needed to address the reliability problem. One important feature of smart grid is demand response. In order to design a demand response program, it is indispensable to understand how consumer reacts upon the change of electricity price. In this paper, we construct an econometrics model to estimate the hourly price elasticity of demand. This panel model utilizes the hourly load data obtained from KEPCO for the period from year 2005 to 2009. The hourly price elasticity of demand is found to be statistically significant for all the sample under investigation. The samples used for this analysis is from the past historical data under the price structure of three different time zones for each season. The result of the analysis of this time of use pricing structure would allow the policy maker design an appropriate incentive program. This study is important in the sense that it provides a basic research information for designing future demand response programs.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.107-114
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• 2016

Web system helps high-performance processing for big-data analysis and practical use to make various information using IT resources. The government have started the RPS system in 2012. The system invigorates the electricity production as using renewable energy equipment. The government operates system gathered big-data with various related information system data and the system users are distributed geographically. The companies have to fulfill the system, are available to purchase the REC to other electricity generation company sellers to procure REC for their duty volumes. The REC market operates single auction methods with users a competitive price. But the price have the large variation with various user trading strategy and sellers situations. This papler proposed RPS system modeling and simulation in web environment that is modeled in geographically distributed computing environment for web user with DEVS W/S. Web simulation system base on web service helps to analysis correlation and variables that act on trading price and volume within RPS big-data and the analysis can be forecast REC price.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.2
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• pp.295-301
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• 2023

To broaden the utilization of nuclear energy, uranium as a fuel should be mined indispensably. Mining accounts for the largest portion of the cost of producing the uranium assembly. Therefore, this study analyzes the trends of uranium prices, which have a significant impacts on the mining cost. Uranium production contributing to the price fluctuations is explained in five periods from 1945 to the present. Moreover, the series of events affecting uranium prices from the 1970s until the present are verified. Among them, the most recent incidents considered in this study are the following: COVID-19 pandemic, Kazakhstan unrest, and Russia-Ukraine war. European countries have started to reconsider the transition to nuclear power to reduce their dependence on Russian oil and gas, which has contributed to the surge in uranium prices. Based on the results of this study, various international issues have been closely associated with the nuclear power industry and uranium, affecting the production of uranium and its price.

• 한국산학경영학회:학술대회논문집
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• 2006.06a
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• pp.147-170
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• 2006

Landfill gas is a mixture of methane and carbon dioxide produced by the bacterial decomposition of organic wastes, and it is considered to produce bad smells and pollute the environment. Economic trials and the developments of landfill gas, as an alternative energy resource, become known at the recent years, Resource development of landfill gas, which is managed by Korea up to now, is for the most part generation using gas engine. Medium BTU and High BTU are considered for the power generation as well. Most income of generation using gas engine is selling charge through a power plant. Expecting to manage the power plant for up to 10 years, the analysis based on revenue and expenditure shows when the unit price is 65.2 Won and the operating rate reaches 90%, it is possible to be into the black in 2012 without considering additional financial expense, It was also analyzed that the profit at a unit price of 85 Won under the anticipated rising unit price by the operating rate of 71% is larger than at the operating rate of 90% under limited unit price of 65.2 Won. It means to manage the power plant at a unit price of 65.2 Won and the operating rate must be higher than 90% for economic logicality. If we assume that the operating rate is 90% and it increases the unit price, the unit price must be higher than 85 Won for the management of a power plant. Analysis of changing a unit price, however, might be expected to have a gradual rise of prices. If there is no price rising and additional income related to CDM(Clean Development Mechanism) and emission trading upon Kyoto protocol, the management of a power plant using gas engine will get financial difficulties because of many operating expenses. However, since landfill gas is considered as a worthy energy resource for the guarantee of sustainable development and for the equity between recent generation and future generation, the development of it must be accomplished by the government's additional supporting and efforts under the interest of all stakeholder who are involved.

• Journal of Electrical Engineering and Technology
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• v.5 no.4
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• pp.530-537
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• 2010

By development of renewable energy and more efficient facilities in an increasingly deregulated electricity market, the operation cost of distributed generation (DG) is becoming more competitive. International environmental regulations of the leaking carbon become effective to reinforce global efforts for a low-carbon paradigm. Through increased DG, operators of DG are able to supply electric power to customers who are connected directly to DG as well as loads that are connected to entire network. In this situation, a community energy system (CES) with DGs is a new participant in the energy market. DG's purchase price from the market is different from the DG's sales price to the market due to transmission service charges and other costs. Therefore, CES who owns DGs has to control the produced electric power per hourly period in order to maximize profit. Considering the international environment regulations, CE will be an important element to decide the marginal cost of generators as well as the classified fuel unit cost and unit's efficiency. This paper introduces the optimal operation of CES's DG connected to the distribution network considering CE. The purpose of optimization is to maximize the profit of CES. A Particle Swarm Optimization (PSO) will be used to solve this complicated problem. The optimal operation of DG represented in this paper would guide CES and system operators in determining the decision making criteria.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.41-50
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• 2013

Economic feasibility study using weighted average variable Jeju System Marginal Price, SMP, was conducted for Gasiri wind farm of Jeju Island. To predict the variable Jeju SMP, generator share ratio for SMP was calculated from the real time wind power production and the power demand data for years. Also, sensitivity analysis on Net Present Value, NPV, and Benefit/Cost Ratio, B/C ratio, were performed to clarify which factors are more important in assessing economic feasibility. The result shows that the Gasiri wind farm has a minimum of 110 billion won and a maximum of 132 billion won difference between fixed and variable SMP. Also, Capacity Factor, C.F., had the highest sensitivity for NPV, followed by SMP. Accordingly, when economic analysis for a potential wind farm site is carried out, the variable SMP as well as C.F. should be considered for more accurate assessment of the wind farm.

• Journal of Hydrogen and New Energy
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• v.20 no.1
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• pp.22-30
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• 2009

Energy environment has been changing rapidly such as the fluctuation of oil prices and the effect on UNFCCC. Oil price change affects Korea's economy heavily due to her poor natural resources and large dependence of consumed energy resources. Korea takes the 4th place of importing the crude oil and 9th place in $CO_2$ emissions with the 1st place of $CO_2$ emissions increasing rate. Considering the current statue of Korea including oil price change and UNFCCC, Korea will be expected to be the Annex I nation due to Korean energy environments and the quantity of $CO_2$ emission. Energy technology development is a crucial key to cope with Korea's national energy security and environments. In this study, we establish the framework, which allocates the relative weights of assessment criteria and sub-criteria, for assessing and selecting R&D programs of energy technologies strategically. We integrated fuzzy theory and analytic hierarchy process (AHP) approach since the fuzzy AHP approach reflects the vagueness of human thoughts and perception effectively as making pairwise comparisons of criteria and alternatives. The fundamental data of this research results will support R&D planning phase for policy-makers and the production of well focused R&D outcomes.

• Journal of Energy Engineering
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• v.5 no.1
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• pp.87-92
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• 1996

This paper formulates dynamic optimization model for Time-Of-Use Rates when a electric power system consists of three generators and a rating period is divided into three sub-periods. We use Pontryagin's Maximum Principle to derive optimal price and investment policy. Particularly the cross-price elasticities of demand are considered in the objective function. We get the following results. First, the price is equal to short-run marginal cost when the capacity is sufficient. However, if the capacity constraint is active, the capacity cost is included in the price. Therefore it is equal to the long-run marginal cost. Second, The length of rating period affects allocation of capacity cost for each price. Third, the capacity investment in dynamic optimization is proportional to the demand growth rate of electricity. However the scale of investment is affected by not only its own demand growth rate but also that of other rating period.