• Journal of Energy Engineering
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• v.28 no.4
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• pp.94-102
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• 2019

The purpose of this study is to propose a method for optimizing heat generation facilities to maximize revenue by investigating their operational status during times of maximum heat demand for district heating. Based on the derived result, this study also proposes a method for determining a given power plant's optimal equipment, such as combined heat and power plant(CHP), peak load boilers (PLB), heat accumulators, and so on, depending on heat demand and facility capacities. It also offers a guide for how to operate facilities more economically by considering the operational status of district heating companies.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.10
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• pp.399-409
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• 2006

This paper presents a novel method for satisfying the thermal comfort of indoor environment and reducing the summer peak demand power by minimizing the power consumption for an Air-conditioner within a space. Korea Electric Power Corporation (KEPCO) use the fixed duty cycle control method regardless of the indoor thermal environment. However, this method has disadvantages that energy saving depends on the set-point value of the Air-Conditioner and direct load control (DLC) has no net effects on Air-conditioners if the appliance has a lower operating cycle than the fixed duty cycle. In this paper, the variable duty cycle control method is proposed in order to compensate the weakness of conventional fixed duty cycle control method and improve the satisfaction of residents and the reduction of peak demand. The proposed method estimates the predict mean vote (PMV) at the next step with predicted temperature and humidity using the back propagation neural network model. It is possible to reduce the energy consumption by maintaining the Air-conditioner's OFF state when the PMV lies in the thermal comfort range. To verify the effectiveness of the proposed variable duty cycle control method, the case study is performed using the historical data on Sep. 7th, 2001 acquired at a classroom in Seoul and the obtained results are compared with the fixed duty cycle control method.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.264-265
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• 2006

This paper presents direct load control algorithm based locational and electric load characteristics. Direct load control is defined that demand-side management program activities that can interrupt consumer load at the time of annual peak load by direct control of the utility system operator by interruption power supply to individual appliances or equipment on consumer premises. Korean power system is divided into 14-areas considering branches operating in KEPCO, and electric loads are classified into 19 load groups considering interruption costs in this paper. The purpose of proposed method is to decrease social losses by controlling electric loads mainly whose interruption costs are low. It is expected that the proposed algorithm can be used as the countermeasure for the emergency state of the electric power dispatch in a operation point of view.

• IE interfaces
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• v.16 no.1
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• pp.16-26
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• 2003

In Korea, cooling power load, which occupies about 20% of peak load in 2000 and fluctuates depending on the popular usage of air conditioning systems, has been recently the focus of the load management. The first work of KEPCO (Korea Electric Power Corporation) to regulate cooling load as low as possible was to estimate its approximate scale and to develop the indirect methods to estimate it from the available time series data for the average hourly loads. However, KEPCO would like to have their methods improved both theoretically and practically. In this paper, we analyze their current indirect methods and detect their faults to design better indirect estimation methods. Under one of the assumptions of "no cooling load in April or May", the linear relationship between basic loads and GDP's, and the normalized seasonal factors of the Winters' multiplicative seasonal model, we provide ten indirect estimation methods in total and suggest the estimated cooling load(1988-1999) based on our various indirect methods.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.767-774
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• 2013

The electricity demand and supply could be off balance if several electric vehicles(EVs) were charged at the same time or at peak load times. Therefore, smart grids are necessary to flatten the EVs' electricity demand and to enable EVs to be used as distributed storage devices as electricity demand from EV-charging increases. There are still few quantitative studies on the impact of smart grids on managing EVs' electrical loads. In this study, we analyzed the quantitative impact of smart grids on managing EVs' electrical loads and suggested policy implications. As a result, it is identified that smart grids can manage effectively EVs' impact on electrical grids. The electricity market structure and regulatory framework should support the demonstration and commercialization of smart grid technologies.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.157-163
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• 2019

K-BEMS System was introduced to reduce peak load and to save total energy of the 120 buildings that KEPCO headquarter and branch offices use. K-BEMS system is composed of PV, battery, and hybrid PCS. In this system, ESS, PV, lighting is used to save building energy based on demand prediction. Currently, neural network technique for short past data is applied to demand prediction, and fixed scheduling method by operator for ESS charging/discharging is used. To enhance this system, KEPCO research institute has carried out this K-BEMS research project for 3 years since January 2016. As the result of this project, we developed new real-time highly reliable building demand prediction technique with error free and optimized automatic ESS charging/discharging technique. Through several field test, we can certify the developed algorithm performance successfully. So we will describe the details in this paper.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.940-947
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• 2011

Load capacity varies according to a day of the week in traction power supply system, because time schedule in railway is changed as demand for passengers and freights. Therefore, Voltage drop also varies as load capacity. In Korea railway, Voltage collected from catenary in train is decreased, as load supplied traction power supply system is increased. Therefore, investigation about voltage drop should be performed, before development of countermeasure against voltage drop. The investigation can be performed by simulation or field test. Naturally, field test is more precise than simulation. In addition, field test should be carried out at peak load. This paper presents test and analysis about voltage drop in railway. The test is performed in both a day of the week and weekend. The analysis is figured out comparison load capacity between two days and voltage drop across terminal.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.295-297
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• 2000

In case of power demand forecasting the most important problem is to deal with the load of special-days, Accordingly, this paper presents a method that forecasting special-days load with regression models and neural networks. Special-days load in summer season was forecasted by the multiple regression models using weekday change ratio Neural networks models uses pattern conversion ratio, and orthogonal polynomial models was directly forecasted using past special-days load data. forecasting result obtains % forecast error of about $1{\sim}2[%]$. Therefore, it is possible to forecast long and short special-days load.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.05a
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• pp.61-65
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• 2008

Because of the high increasing rate of load demand, these days the necessity of deciding what optimum reserve level is appropriate to most stably supply electricity is being emphasized. This research studies the downward tendency of reverve ratio by analyzing the trend of change of the network scale, reserve, and reserve ratio while optimum reserve has been increased as the network system scale grow up. This means, at this moment 6,000MW is optimum level for short term prospect of power supply and demand. And also, it has been analyzed that, as the annual peak load exceeded 50,000MW, confirming the amount of optimum reserve level is more stable than keeping 10 to 12% reserve ratio.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.155-156
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• 2015

Recently, electricity consumption has rapidly increased along with economic growth. The operating strategy using emergency generator is aimed, to resolve a demand response management. For strategy of peak shedding using emergency generator, it is essential to introduce the fast transfer switching device. One of the most effective solutions is to use a static transfer switch (STS) based on thyristor. However, the characteristic of natural commutated SCR thyristor should anticipate short duration voltage sag. STS system thus requires more than a quarter cycle to successfully complete transfer process. This paper proposes the operation scheme of the STS system using the forced-commutation technique to mitigate instantaneous voltage sag during peak transfer process. Proposed STS system improved turn-off characteristic thus accomplishes the peak load shedding satisfied power quality. Performance of the proposed STS system is evaluated using electromagnetic transient program (EMTP) to confirm the effectiveness.