• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.117-124
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• 2017

A Smart Grid is a system that can efficiently use energy by exchanging real-time information in both directions between a consumer and a power supplier using ICT technology on an existing power network. DR(Demand response) is an arrangement in which electricity users can sell the electricity they save to the electricity market when the price of electricity is high or the power system is crisis. In this study, we developed a power meter data transmission device and power IT system that measure the demand information in real-time using a smart meter and transmit it to a cloud server. The power meter data transmission device developed in this study uses alight sensor connected to a Raspberry Pi 3 to measure the number of blinking lamps on the KEPCO meter per unit of power, in order to provide reliable data without any measurement errors with respect to the KEPCO power data. The power measurement data transmission device uses the standard communication protocol, OpenADR 2.0b. The measured data is transmitted to the power IT system, which consists of the VEN, VTN, and calculation program, via the LTE WiFi communication network and stored in its MySQL DB. The developed power measurement data transmission device issues a power supply instruction and performs a peak reduction DR when a power system crisis occurs. The developed power meter data transmission device has the advantage of allowing the user to adjust it every 1 minute, where as the existing smart metering time is fixed at once every 15 minutes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2215-2220
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• 2011

The accurate short-term load forecasting is essential for the efficient power system operation and the system marginal price decision of the electricity market. So far, errors of load forecasting for Chuseok Holiday are very big compared with forecasting errors for the other special days. In order to improve the accuracy of load forecasting for Chuseok Holiday, selection of input data, the daily normalized load patterns and load forecasting model are investigated. The efficient data selection and daily normalized load pattern based on fuzzy linear regression model is proposed. The proposed load forecasting method for Chuseok Holiday is tested in recent 5 years from 2006 to 2010, and improved the accuracy of the load forecasting compared with the former research.

• ETRI Journal
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• v.37 no.1
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• pp.197-202
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• 2015

A smart grid is a modernized electrical grid that uses information about the behaviors of suppliers and consumers in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity. In the operation of a smart grid, demand side management (DSM) plays an important role in allowing customers to make informed decisions regarding their energy consumption. In addition, it helps energy providers reduce peak load demand and reshapes the load profile. In this paper, we propose a new DSM scheduling scheme that makes use of the day-ahead pricing strategy. Based on the Rubinstein-Stahl bargaining model, our pricing strategy allows consumers to make informed decisions regarding their power consumption, while reducing the peak-to-average ratio. With a simulation study, it is demonstrated that the proposed scheme can increase the sustainability of a smart grid and reduce overall operational costs.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.981-987
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• 2017

In this paper, we estimate the economic benefits of Energy Storage Systems (ESSs) for peak load shaving in an urban railway substation using the annual cost. The annual investment cost of ESSs is estimated using Net Present Value (NPV) and compared with the cost reduction of electricity by the ESS. The optimal capacities of the battery and Power Converting System (PCS) are determined for peak load shaving. The optimal capacity of the ESS and the peak load shaving is determined to maximize the profit by the ESS. The proposed method was applied to real load data in an urban railway substation, and the results show that electric power costs can be reduced. Other aspects of the ESS, such as the lifetime and unit price of the battery, are also investigated economically.

• Journal of Electrical Engineering and Technology
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• v.4 no.3
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• pp.337-345
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• 2009

Deregulation in power industry has made the reactive power ancillary service management a critical task to power system operators from both technical and economic perspectives. Reactive power management in power systems is a complex combinatorial optimization problem involving nonlinear functions with multiple local minima and nonlinear constraints. This paper proposes a practical market-based reactive power ancillary service management scheme to tackle the challenge. In this paper a new model for voltage security and reactive power management is presented. The proposed model minimizes reactive support cost as an economic aspect and insures the voltage security as a technical constraint. For modeling validation study, two optimization algorithm, a genetic algorithm (GA) and particle swarm optimization (PSO) method are used to solve the problem of optimum allocation of reactive power in power systems under open market environment and the results are compared. As a case study, the IEEE-30 bus power system is used. Results show that the algorithm is well competent for optimal allocation of reactive power under practical constraints and price based conditions.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.7
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• pp.352-357
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• 2005

In competitive electricity markets, the System Operator (SO) coordinates the overall maintenance schedules when the collective maintenance schedule reported to 50 by Gencos not satisfy the specified operating criteria, such as system reliability or supply adequacy. This paper presented a method that divides generator maintenance scheduling of the 50 into a master-problem and a sub-problem. Master-problem is schedule coordination and sub-problem is DC-optimal power flow. If sub-problem is infeasible, we use the algorithm of modifying operating criteria of master-problem. And, the 50 should use the open information only, because the information such as cost function of a generator and bidding Price is highly crucial for the strategies of profit maximization.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.18-23
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• 2008

A FCM with locational price and regional information between locations are proposed in this paper. Any point in a networked system has its own values indicating the physical characteristics of that networked system and regional information at the same time. The similarity measure used for FCM in this paper is defined through the system-wide characteristic values at each point. To avoid the grouping of geometrically distant locations with similar measures, the locational information are properly considered and incorporated in the proposed similarity measure. We have verified that the proposed measure has produced proper classification of a networked system, followed by an example of a networked electricity system.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1996.10b
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• pp.45-53
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• 1996

한전은 1995년 5월에 가격기능에 의한 수요관리 효과를 증진시키기 위하여 계절·시간대별 차등요금(이하 계시별 요금)을 대폭적으로 변경하였다. 본 연구는 이와 같은 요금구조 변경에 대한 수용가의 반응도 분석을 위한 것이다. 이를 위하여 요금구조 변경전인 95년 4월을 기준으로 1년후인 1996년 4월의 일반용(을) 및 산업용(병) 갑 및 을 종별에 대한 가격탄력성과 수용가의 부하패턴 변화를 측정하였다. 가격탄력성은 산술적 모형을 이용하면 산업평균 최대부하 시간대가 -0.0121, 중부하 및 경부하 시간대가 각각 -0.0788 및 -0.0012으로 산출되었다. 또한 회귀모형을 이용할 경우 최대부하 시간대가 -0.0126, 중부하 시간대가 -0.0018 및 최대부하 시간대가 0.0006로 나타났다. 한편 계시별 요금에 대한 수용가의 반응성은 다음과 같이 요약할 수 있다. 첫째, 계시별 요금이 피크시간대에 매우 낮으나 분명한 수요감소에 영향을 주고 있다. 둘째, 산업별로의 수용가의 반응성이 매우 다르다. 셋째, 상업용 수용가의 반응도가 매우 낮다. 넷째, 같은 가격탄력성은 수용가의 규모가 클수록 가격 변화에 대한 수용가의 반응성은 낮은 것으로 나타났다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.642-643
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• 2011

스마트그리드 구현에 실시간요금제 적용이 핵심으로 등장하고 있다. 실시간요금제 적용 시 전력수요의 변동을 시뮬레이션하기 위하여 2005년부터 2009년의 전자식전력량계 계량데이터를 이용하여 전력 수요의 가격탄력성을 구하였다. 가격탄력성을 산출하기 위하여 시계열 분석과 횡단면 분석을 동시에 수행할 수 있는 패널모형 분석을 적용하였으며, 국내 전기요금에 대하여 계약종별, 산업분류별 가격탄력성을 실시간 요금제에 대비하여 1시간 단위로 구하였다. 국내 전력수요의 가격탄력성은 계약종별 및 산업분류별로 대부분의 경우 -0.1 이내로 산출되어 가격탄력성이 매우 낮게 나타났다. 산업분류별로 가격탄력성을 산출함으로써 통계적 유의수준이 높게 나타났다.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.559_560
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• 2009

정부의 녹색성장기본법(안)에 따라 총량제한 배출권 거래제가 도입될 예정이므로, 배출규제에 대응한 전력시장의 제도적 대응이 요구된다. 본 논문은 배출비용을 감안한 발전원가를 평가하고, 전력시장이 현 비용입찰시장(CBP)의 형태를 유지한다는 전제하에 배출규제에 따른 전력시장가격의 영향을 분석하였다. 배출비용을 감안하더라도 전원별 급전우선순위는 변화하지 않으므로 비용최소화를 위한 전략은 기존 발전패턴을 유지하고 배출권을 구입하는 전략이 된다. 그러나 전기요금 안정화를 위한 발전회사의 수익 규제는 연료전환을 유도하여 배출감축에는 기여하지만, 발전비용 및 전력시장가격을 다소 상승시키게 된다. 한편 발전회사에 대한 수익규제는 배출권시장의 수급여건을 변화시키게 되므로, 전력시장과 배출권시장의 운영, 분석 및 규제에 대한 일원화된 체제의 필요성을 강하게 시사한다.