• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 A
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• pp.165-167
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• 2004

End-user electric power consumption trends shows various load curves dependant on industry, contract, season, day and time. Analysis of end-user electric power consumption trends has a key role to efficiently meet electricity demand. There are several factors of change in electricity demand such as the change of weather, international conflict, and industrial trends during summer. This paper has analyzed the analysis the end-user electric power consumption trends using the load curve during international conflict. We observed that international conflict decreased electric demand by $5.4\%$. This increase is not significant, and therefore we conclude that the international conflict has not greatly affected Korea's electricity demands. This paper provides useful information so as to mon: efficiently perform demand side management.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 학술대회 논문집 전문대학교육위원
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• pp.97-100
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• 2007

There are regulations on each building for its classification and It is corresponding determined contract demand. For transformer's capability calculation algorithm, cumulated power information of each customer is used to analysis the correlation between power usage and Demand Rate. By modeling this using Least Square Method, it can be targeted to recognize the pattern of transformer use in the past and make a prediction on it in the future.

• 자원ㆍ환경경제연구
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• 제30권2호
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• pp.237-268
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• 2021

에너지전환 정책의 가속화로 변동성 재생에너지가 가파르게 증가하면서 계통수용비용이 빠르게 상승하고 있다. 변동성 재생에너지 증가는 기존 전통적 발전자원의 이용률을 하락시켜서 전력공급에 비효율성을 가중시키는데 이에 대한 해결책으로 수요자원이 주목받고 있다. 본 연구에서는 수요자원 중 큰 잠재력을 가지고 있는 전기차 수요가 재생발전에 대한 유연성 자원으로 활용될 경우 전력공급비용을 얼마나 경감시킬 수 있는지 9차 전력수급계획을 반영하여 분석하였다. 분석모형으로 재생발전의 확률적 특성을 사실적으로 반영할 수 있는 확률적 전력시스템 최적화 모형을 적용해서 재생에너지가 유발하는 비용과 전기차 수요자원의 편익을 분석하였다. 분석결과 계시별 요금제보다 가상발전소 기반의 직접제어방식이 편익이 더 높고, 발전구성에서 재생에너지의 비중이 높아질수록 편익이 더 높아지는 것으로 나타났다. 전기차 수요자원의 구현비용인 중개사업자 수수료와 배터리마모비용을 고려한 순편익 추정결과, 충방전이 가능한 가상발전소 방식의 경우 월평균 운행비용의 67~85% 수준으로 나타났다. 이러한 수요자원 순편익이 소비자에게 효과적으로 분배되는 요금체계가 적용될 경우 시장참여유인이 높을 것으로 추정된다.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.568-579
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• 2018

Virtual power plants can be regarded as systems that have entered the network after restructure of power systems. In fact, these plants are a set of consumers capable of consuming and generating power. In response to widespread implementation of plug-in hybrid electric vehicles, further investigation of energy management in this type of power plants seems to be of great value. In effect, these vehicles are able to receive and inject power from/into the network. Hence, study of the effects of these vehicles on management of virtual power plants seems to be illuminative. In this paper, management of power consumption/generation in virtual power plants has been investigated in the presence of hybrid electric vehicles. The objective function of virtual power plants problem management is to minimize the overall costs including not only the costs of energy production in power generation units, fuels, and degradation of batteries of vehicles, but also the costs of purchasing electricity from the network. Furthermore, the constraints on the operational of plants, loads and hybrid vehicles, level of penalty for greenhouse gas emissions ($CO_2$ and $NO_x$) produced by power plants and vehicles, and demand response to the immediate price of market have all been attended to in the present study. GAMS/Cplex software system and sample power system have been employed to pursue computer implementation and simulation.

• KIEE International Transactions on Power Engineering
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• 제5A권3호
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• pp.214-220
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• 2005

In order to improve energy efficiency and solve power disturbances, power components measurement for both the supply and demand side of a power system must be implemented before appropriate action on the power problems can be taken. This paper presents a DSP (Digital Signal Processor)-based multi-channel (voltage 8-channel and current 10-channel) power measurement system that can simultaneously measure and analyze power components for both supply and demand. Voltage 8-channel and current 10-channel measurement is made through voltage and current sensors connected to the developed system, and power components such as reactive power, power factor and harmonics are calculated and measured by the DSP. The measured data are stored in a personal computer (PC) and a commercial program is then used for measurement data analysis and display. After voltage and current measurement accuracy revision using YOKOGAWA 2558, the developed system was tested using a programmable ac power source. The test results showed the accuracy of the developed system to be about 0.3 percent. Also, a simultaneous measurement field test of the developed system was implemented by application to the supply and demand side of the three-phase power system.

• Journal of Electrical Engineering and Technology
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• 제9권5호
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• pp.1454-1470
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• 2014

This paper propose a new power conditioner topology with intelligent power management controller that integrates multiple renewable energy sources such as solar energy, wind energy and fuel cell energy with battery backup to make best use of their operating characteristics and obtain better reliability than that could be obtained by single renewable energy based power supply. The proposed embedded controller is programmed for maintaining a constant voltage at PCC, maximum power point tracking for solar PV panel and WTG and power flow control by regulating the reference currents of the controller on instantaneous basis based on the power delivered by the sources and load demand. Instantaneous variation in reference currents of the controller enhances the controller response as it accommodates the effect of continuously varying solar insolation and wind speed in the power management. The power conditioner uses a battery bank with embedded controller based online SOC estimation and battery charging system to suitably sink or source the input power based on the load demand. The simulation results of the proposed power management system for a standalone solar/WTG/fuel cell fed hybrid power supply with real time solar radiation and wind velocity data collected from solar centre, KEC for a sporadically varying load demand is presented in this paper and the results are encouraging in reliability and stability perspective.

• 전기학회논문지P
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• 제56권4호
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• pp.179-185
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• 2007

In this paper, the method of computing demand rate with respect to a transformer capacity is proposed and addressed to predict a future demand rate. The simulation data are taken from switchgears of a real medium voltage transformer. Data taken from the electrical instrument at 22.9 kVY power receiving panels are employed to evaluate the correlation between demand rate and power usage of transformer. It is verified a usefulness with respect to an proposed index of demand rate for transformer by using a least square error of regressive modeling, As a result of investigation and simulation on the spot to a few buildings, it is considered that there is necessity to make a partial amendment of demand rate being applicable currently for electrical energy saving in domestic.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제11권7호
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• pp.307-314
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• 2022

최근 전력수요를 예측하기 위해 통계기반 시계열 분석 기법을 대체하기 위해 딥러닝 기법을 활용한 연구가 활발히 진행되고 있다. 딥러닝 기반 전력수요 예측 연구 결과를 분석한 결과, LSTM 기반 예측 모델의 성능이 우수한 것으로 규명되었으나 장기간의 지역 범위 전력수요 예측에 대해 LSTM 기반 모델의 성능이 충분하지 않음을 확인할 수 있다. 본 연구에서는 기온 데이터를 반영하여 24시간 이전에 전력수요를 예측하는 WaveNet 기반 딥러닝 모델을 개발하여, 실제 사용하고 있는 통계적 시계열 예측 기법의 정확도(MAPE 값 2%)보다 우수한 예측 성능을 달성하는 모델을 개발하고자 한다. 먼저 WaveNet의 핵심 구조인 팽창인과 1차원 합성곱 신경망 구조를 소개하고, 전력수요와 기온 데이터를 입력값으로 모델에 주입하기 위한 데이터 전처리 과정을 제시한다. 다음으로, 개선된 WaveNet 모델을 학습하고 검증하는 방법을 제시한다. 성능 비교 결과, WaveNet 기반 모델에 기온 데이터를 반영한 방법은 전체 검증데이터에 대해 MAPE 값 1.33%를 달성하였고, 동일한 구조의 모델에서 기온 데이터를 반영하지 않는 것(MAPE 값 2.31%)보다 우수한 전력수요 예측 결과를 나타내고 있음을 확인할 수 있다.

• 전기학회논문지
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• 제63권4호
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• pp.451-454
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• 2014

Short-term load forecasting(STLF) for electric power demand is essential for stable power system operation and efficient power market operation. We improved STLF method by using hourly temperature as an input data. In order to using hourly temperature to STLF algorithm, we calculated temperature-electric power demand sensitivity through past actual data and combined this sensitivity to exponential smoothing method which is one of the STLF method. The proposed method is verified by case study for a week. The result of case study shows that the average percentage errors of the proposed load forecasting method are improved comparing with errors of the previous methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.119-121
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• 2007

The increment of electric power demand causes interest on new higher power system such as 42V Power Net, and furthermore necessity for development of energy storage device is highlighted recently. Owing to high efficiency and easy speed control of brushless DC(BLDC) motor, the demand of BLDC motor that has high power and low noises are increasing. Especially demand of interior permanent magnet(IPM) type BLDC with high efficiency and high power in electric motion vehicle is increasing. This paper presents the design of the BLBC motor for EHPS(Electro-Hydraulic Power Steering) in 42V system and verified the characteristics by simulation and test results.