• Transactions of the Korean Society of Mechanical Engineers B
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• v.33 no.4
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• pp.278-287
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• 2009

Plug-in hybrid electric vehicle (PHEV) with capability of being recharged from the power-grid will reduce oil consumption. Also, the PHEV will affect the utility operations by adding additional electricity demand for charging. In this research, the power-grid impact by demand of PHEV charging is presented and the optimal charging control strategy for utility operators is proposed with simulated data. The penetration of PHEV is assumed to be 50% in the circumstances of Korean passenger car market and Korean power-grid market limitedly. To obtain smooth load shape and utilize the surplus electricity in power-grid at midnight and dawn, the peak of charging demand should be controlled to be located before 4:00 a.m., and the time slot which can supply the electricity power to PHEV should be allowed between 1:00 a.m.$\sim$7:00 a.m.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.1
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• pp.70-77
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• 2011

Sewage treatment plants, consuming 1,756[GWh] which is 0.53[%] of national wide electricity consumption, is one of the electricity consuming facilites. At the research of electricity consumption and power quality analysis on sewage treatment plants, average utilization of transformer was less than 40[%] because peak load was very lower than its capacity due to excess capacity. So reduction of power loss can be achieved by transformer design optimization. The achievement in this research, is to meet reduction of power loss through optimizing the capacity and to improve as high efficiency-low loss transformer while the transformer is operating.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.264-269
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• 2009

Marginal Loss Factor(MLF) is represented as the sensitivity of transmission loss, which is computed from the change of the generation at slack bus by the change of the load at the arbitrary bus. The MLF dependent on the selection of slack bus is one of the key factors affecting nodal pricing, Genco's profits, social welfare(SW) and Nash Equilibrium in a competitive electricity market. This paper addresses the methodology of slack bus selection by using Cournot model of Cost Based Pool market. Numerical results from sample cases show that the slack bus of MLF of the highest average is beneficial from the view points of SW.

• Environmental and Resource Economics Review
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• v.23 no.4
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• pp.617-641
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• 2014

Korean electricity market is a Cost-Based Pool (CBP) designed to minimize electricity production cost through cost by providing cost reduction incentives to generators. Generation companies have shown diverse efforts to reduce costs in CBP market such as procuring low-price fuels, installing high efficiency gas turbine and constructing power plants near the heavy-load site. Recently, as a way to improve CBP market, a proposal to exclude no-load cost from System Marginal Price (SMP) and to compensate generators ex post was suggested to Korea Power Exchange. This study analyzes the impact of excluding no-load cost from SMP on the cost reduction incentive of generators. We found that excluding no-load cost from SMP enhances the likelihood of decreasing the cost reduction incentives of LNG combined-cycle generators lying on the price-setting range.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.246-250
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• 1989

Owing to the rapid development of economy and the higher living standard of people, electricity demands have growth and the peak load has been increased rapidly. To cope with this impacts and to reduce the cost of service,utilities are conserned about power load management program. This paper shows a scheme of power load control and the basic structure of direct load control system. And also radio control method using the public pager which is one of the best economical and serviceable method in techniques will be introduced briefly.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.300-301
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• 2015

Accurate and robust load forecasting model plays very important role in power system operation. In case of short-term electric load forecasting, its results offer standard to decide a price of electricity and also can be used shaving peak. For this reason, various models have been developed to improve accuracy of load forecasting. This paper proposes a newly forecasting model for weather sensitive season including temperature and Cooling Degree Hour(C.D.H) data as an input. This Forecasting model consists of previous electric load and preprocessed temperature, constant, parameter. It optimizes load forecasting model to fit actual load by PSO and results are compared to Holt-Winters and Artificial Neural Network. Proposing method shows better performance than comparison groups.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.4
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• pp.265-272
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• 2011

The electrical load profiles of end-users must be analysed properly to introduce distributed generation system efficiently. In this study, numerical simulation for predicting a residential electrical load profile was developed to satisfy categorized electricity consumption range. We applied bottom-up approach to compose electrical load profile by using data from official reports and statistics. The electrical load profile produced from the simulation predicted peak times of public report accurately and agreed well with the standard residential electrical load profile of official reports within average error of 16.2%.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.2
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• pp.315-323
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• 2015

Nowadays, it is expected that mobility loads such as electric railways and electric vehicles will be penetrated gradually and affect on the power system stability by their load characteristics. Various researches have been carried out about electric vehicles for the recent decade though the load of electric railway could be forecasted because of the specified path and timetable, is a field with a long historic background. Some precise 5th polynomial equations are required to analyze the power system stability considering mobility load to be increased in the immediate future while the electric railway dispatching simulator uses load models with constant power and constant impedance for the system analysis. In this paper, seasonal urban railway load models are established as the form of 5th polynomial equations and substation load modeling methods are proposed merging railway station load models and general load models. Additionally, load management effects by the load modeling are confirmed through the case studies, in which seasonal load models are developed for Seoul Subway Line No. 2, Gyeongui Line and Airport Railroad and the substation load change is analyzed according to the railway load change.

• Environmental and Resource Economics Review
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• v.15 no.2
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• pp.319-353
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• 2006

This paper shows how weather derivatives can be used to hedge against the price risk and volume risk of purchasing relatively large amounts of electricity. Our specific approach to designing new contracts for electricity is to focus on the return over a summer season rather than on the daily levels of demand and price. It is shown that correct market signals can be preserved in a contract and the associated financial risk can be offset by weather options. The advantage of combining a forward contract with a weather derivative is that the high prices on hot days or when the temperature is high reflect the underlying high cost of producing power when the load is high and that the combined contract with a weather derivative substantially reduces the volatility of the return.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.199-206
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• 2008

The introduction of competition in electricity markets emphasizes the importance of sufficient transmission capacities to guarantee effective power transactions. Therefore, for the economic and stable electric power system operation, transmission security constrains should be incorporated into the dispatch scheduling problem. With the intent to solve this problem, we decompose a dispatch scheduling problem into a master problem(MP) and several subproblems(SPs) using Benders decomposition. The MP solves a general optimal power flow(OPF) problem while the SPs inspect the feasibility of OPF solution under respective transmission line contingencies. If a dispatch scheduling solution given by the MP violates transmission security constraints, then additional constraints corresponding to the violations are imposed to the MP. Through this iterative process between the MP and SPs, we derive an optimal dispatch schedule incorporating the post-contingency corrective rescheduling. In addition, we consider interruptible loads as active control variables since the interruptible loads can participate as generators in competitive electricity markets. Numerical examples demonstrate the efficiency of the proposed algorithm.