• Journal of Communications and Networks
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• v.18 no.3
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• pp.484-492
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• 2016

Smart grid (SG) technology is now elevating the conventional power grid system to one that functions more cooperatively, responsively, and economically. When applied in an SG the demand side management (DSM) technique can improve its reliability by dynamically changing electricity consumption or rescheduling it. In this paper, we propose a new SG scheduling scheme that uses the DSM technique. To achieve effective SG management, we adopt a mixed pricing strategy based on the Rubinstein-Stahl bargaining game and a repeated game model. The proposed game-based pricing strategy provides energy routing for effective energy sharing and allows consumers to make informed decisions regarding their power consumption. Our approach can encourage consumers to schedule their power consumption profiles independently while minimizing their payment and the peak-to-average ratio (PAR). Through a simulation study, it is demonstrated that the proposed scheme can obtain a better performance than other existing schemes in terms of power consumption, price, average payment, etc.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.838-839
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• 2007

전력산업의 시장구조는 과점형태의 불완전 경쟁의 구조로 해석하는 것이 일반적이다. 또한 전기의 물리적 특성상 송전선로에서는 전력손실이 발생하게 되는데, 본 논문은 과점시장 모델로서 쿠르노(Cournot)모델을 사용하여 손실을 포함한 내쉬 균형점을 해석한다. 지역별 한계가격(Locational Marginal Price ; LMP)와는 달리 계통한계가격(System Marginal Price ; SMP)는 손실에 대한 가격신호를 시장에 반영하기 어렵기 때문에 손실과 함께 한계송전손실계수(Marginal Loss Factor ; MLF)를 적용하여 균형상태의 시장거래가치를 비교분석한다.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.101-103
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• 2004

Transmission congestion is one of the Key factors to local market power in competitive electricity markets. Withholding is a one of the methods exercise the market power. This paper presents an alternative methodology in market power under transmission congestion and withholding. The proposed methodology was demonstrated with the Optimal Power Flow(OPF). Case study is fulfilled by GAMS simulation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.7
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• pp.414-419
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• 2004

In TWBP new uncertainty will be increased. Risk management is risen to a important problem. Vesting contract makes market Players trade at fixed price in TWBP early stages. In the case of advanced country, market players manage risk with a future contract. When a risk management method moves from vesting contract to future contract, it may have to use together two contracts for schedule period. In this paper, risk management strategy that use vesting contract and forward contract at the same time is proposed.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.389-391
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• 2002

This paper presents the System Marginal Price(SMp) forecasting implementation using backpropagation Neural Networks in Competitive Electricity Market. SMP is very important term to seek the maximum profit to bidding participants. Demand and SMP that necessary data for training Neural Networks, supplied from Korea Power Exchange(KPX). Statistic analysis about predicted SMP presents a part of consideration in end of this paper.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.556-558
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• 2001

전압 주파수 부하 모형 추정에 사용되어 이전의 정임피던스, 정전류, 정전력 부하모형에 비해 향상된 결과를 얻었던 다항식형 부하 모형을 전력가격 부하 모형에도 적용하여 새로운 다항식 부하 모형을 제안하고, 우리나라의 전력 가격과 사용량 자료를 이용하여 부하 모형의 계수를 결정하였다. 부하의 종류별, 시간대별로 추정된 부하 모형에 부하의 구성 비율을 가중하면 결국 전체 부하 모형이 구해진다. 구해진 부하 모형은 전력 시장이 도입된 경쟁체제에서 전력의 가격 결정에 사용될 수 있을 것이다.

• Journal of Energy Engineering
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• v.8 no.2
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• pp.265-271
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• 1999

In recent years, the electric utility industry in Korea has undergone fast change. Private power generation has been introduced by competitive bidding to improve economic efficiency and to strengthen the competitive generation market. In these private generation projects, the yearly pattern of purchase price between the utility and IPPs is very important. Currently, the levelized payment schedule is applied to capacity payment, and price escalation rates are reflected to energy payment. In this paper, we Proposed different patterns of payment and analyzed the outcomes. As a result, we found possibility of applying the partial front-loading pattern in Korean market to share the risk of the long-term business. And, the importance of discount rate is also found.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.162-164
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• 2005

This paper presents an hour-ahead System Marginal Price (SMP) forecasting framework based on a neural network. Recently, the deregulation in power industries has impacted on the power system operational problems. The bidding strategy of market participants in energy market is highly dependent on the short-term price levels. Therefore, short-term SMP forecasting is a very important issue to market participants to maximize their profits. and to market operator who may wish to operate the electricity market in a stable sense. The proposed hybrid neural network is composed of tow parts. First part of this scheme is pattern classification to input data using Kohonen Self-Organizing Map (SOM) and the second part is SMP forecasting using back-propagation neural network that has three layers. This paper compares the forecasting results using classified input data and unclassified input data. The proposed technique is trained, validated and tested with historical date of Korea Power Exchange (KPX) in 2002.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.609-611
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• 2003

This paper presents a method for a congestion management in the competitive market which is modeled as the multiple bilateral transaction. Traditionary, the congestion management for the multiple bilateral transaction is accomplished through the process of adjustment bids. It is necessary in for the market entity to submit their price information when the congestion is occured. Finally, the ISOs can be blown about the approximated contract price of participants from the price of adjustment bids. However, the entities can submit only the amount of their contract to ISOs and ISOs are required the method to manage the congestion only by the contracted quantity. Therefore, this paper presents a method for congestion management by curtailing the only contracted quantity of market entities. To evaluated the above problem, we suggest Bilateral Transaction Distribution Factors(BTDFs), which is the sensitivity of line flow with curtailment of transactions. Using this factor, we studied about congestion management when the objective function is to minimize total curtailment of transaction.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.448-459
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• 2021

In this paper, we propose a method of predicting the next-day stock price fluctuations of 10 KOSDAQ-listed companies in 5G, autonomous driving, and electricity sectors by training SVM, XGBoost, and LightGBM models from macroeconomic·financial market indicators, technical indicators, social interest indicators, and daily positive indices extracted from online news. In the three experiments to find out the usefulness of social interest indicators and daily positive indices, the average accuracy improved when each indicator and index was added to the models. In addition, when feature selection was performed to analyze the superiority of the extracted features, the average importance ranking of the social interest indicator and daily positive index was 5.45 and 1.08, respectively, it showed higher importance than the macroeconomic financial market indicators and technical indicators. With the results of these experiments, we confirmed the effectiveness of the social interest indicators as alternative data and the daily positive index for predicting stock price fluctuation.