• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.670-672
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• 2003

The market participants make plans of bidding and transaction strategies to maximize their own profits in competitive electricity market. Also, It is concerned with transmission congestion in power market. Two methods are generally used for congestion management;nodal pricing and uplift. The participants will have different strategies for their profits in the two methods. This paper analyzes their equilibrium strategies by using the supply function model and congestion methods.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.37-52
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• 2013

Prior to full-scale implementation of smart grid, the Korean government is conducting a smart grid testbed in Jeju island. However, the participants of the ongoing program are skeptical about the success of the expansion of smart grid. The concern rises from various reasons; the limits of the Korean electricity market mainly led by both the government and KEPCO, high stability and reliability of the existing electricity grid, insufficient utilization of renewable energy, and public fear of raised electricity bills. Five key issues in regards to facilitating the Korean smart grid market are extracted and evaluated. The issues are conflict of interest among participants, the effect of introducing real-time pricing, lack of customer participation of demand response, and absence of business models.

• The Journal of Society for e-Business Studies
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• v.17 no.2
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• pp.105-114
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• 2012

Recently, global warming, energy shortage, and environmental disruption have been serious problems in every nation. It became more and more important to reduce the emission of CO2 and to use of energy efficiently. Smart grid was also introduced using the rapidly developing information technology. It deployed the mutual communication concept between customers and the suppliers in the electricity supply. There were increasing demands to adopt the smart meter and to present incentive for efficient energy usage in many developed countries. The objective of this research was to develop the optimal real time pricing model which maximized the profit of the power retailer and reduced the usage of energy. The simulation study was given to show the usefulness of the model. Simulation considered the customer demand response rate and price elasticity rate. The price elasticity rate was compared in the condition of fixed value according to time and variable value according to the customers. The optimal price model could maximize the profit of the power retailer and reduce the energy usage of the consumers.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.7
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• pp.311-316
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• 2002

It has been a basic model for the present electric power industry that more than two generators compete, and thereby the market clearing price and the generation schedules are determined through the bid process. In order for this paradigm to be applicable to real electric power systems and markets, it is necessary to reflect many physical and economic constraints related to frequency and transmission in the dispatching schedule. The paper presents an approach to deriving a Nash bargaining solution in a competitive electricity market where multiple generators are playing with the system operator who mitigates the transmission congestion to minimize the total transaction cost. In this study, we take the effect of the line flows and the role of system operator into the Game. Finally, a case study has been demonstrated to verify the proposed cooperative game.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.812-813
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• 2007

The procurement of generation and transmission/Distribution capacity in vertically-integrated electric industry is sufficient by facility construction in suitable time. However, the introduction of competitive electricity market increase the efficiency of availability for facilities and fuels. As a result, long-term capacity procurement is required for stable demand-supply balance since it is expected to maintain their generation capacity at a minimum for profit maximization. In this paper, a new long-term capacity procurement mechanism is constructed, which is able to assure supplemental contribution in competitive electricity market.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.75-106
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• 2007

In this study, it is analyzed whether oil price plays a major role in the pricing return on Koran stock market and examined why the covariance risk between oil and return on stock is different in each industry. Firstly, this study explores whether the expected rate of return on stock is pricing due to global oil price factors as a function of risk premium by using a two-factor APT. Also, it is examined whether spill-over effects of oil price volatility affect the beta risk to oil price. Considering the asymmetry of oil price volatility, we use the GJR model. As a result, it shows that oil price is an independent pricing factor and oil price volatility transmits to stock return in only electricity and electrical equipment. Secondly, the two step-analyzing process is introduced to find why the covariance between oil price factor and stock return is different in each industry. The first step is to study whether beta risk exists in each industry by using two proxy variables like size and liquidity as control variables. The second step is to grasp the systematic relationship between the difference of liquidity and size and beta to oil price factor by using the panel-data model which can be analyzed efficiently using the cross-sectional data formed with time series. Through the analysis, we can argue that oil price factor is an independent pricing factor in only electricity and electrical equipment having the greatest market capitalization, and know that beta risk to oil price factor is a proxy of size in the other industries. According to the result of panel-data model, it is argued that the beta to oil price factor augments when market capitalization increases and this fact supports the first assertion. In conclusion, the expected rate of return of electricity and electrical equipment works as a function of risk premium to market portfolio and oil price, and the reason to make beta risk power differentiated in each industry attributes to the size.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.111-112
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• 2007

This paper presents the capacity payment in electricity power markets. The capacity payment (CP) needs to recover fixed costs. But most CP is allocated by energy policy. So, this paper analysis CP using capacity proportion and Reliability Pricing Model (RPM). The capacity proportion method uses base capacity price and supply available capacity. The RPM method uses value of each region and operation attribute of each generator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1481-1501
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• 2019

In opportunistic network, the behavior of a node is autonomous and has social attributes such as selfishness.If a node wants to forward information to another node, it is bound to be limited by the node's own resources such as cache, power, and energy.Therefore, in the process of communication, some nodes do not help to forward information of other nodes because of their selfish behavior. This will lead to the inability to complete cooperation, greatly reduce the success rate of message transmission, increase network delay, and affect the overall network performance. This article proposes a hybrid incentive mechanism (Mim) based on the Reputation mechanism and the Credit mechanism.The selfishness model, energy model (The energy in the article exists in the form of electricity) and transaction model constitute our Mim mechanism. The Mim classifies the selfishness of nodes and constantly pay attention to changes in node energy, and manage the wealth of both sides of the node by introducing the Central Money Management Center. By calculating the selfishness of the node, the currency trading model is used to differentiate pricing of the node's services. Simulation results show that by using the Mim, the information delivery rate in the network and the fairness of node transactions are improved. At the same time, it also greatly increases the average life of the network.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1144-1150
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• 2016

Short-term load forecasting is essential to the electricity pricing and stable power system operations. The conventional weekday 24-hour load forecasting algorithms consider the temperature model to forecast maximum load and minimum load. But 24-hour load pattern forecasting models do not consider temperature effects, because hourly temperature forecasts were not present until the latest date. Recently, 3 hour temperature forecast is announced, therefore hourly temperature forecasts can be produced by mathematical techniques such as various interpolation methods. In this paper, a new 24-hour load pattern forecasting method is proposed by using similar day search considering the hourly temperature. The proposed method searches similar day input data based on the anomalous weather features such as continuous temperature drop or rise, which can enhance 24-hour load pattern forecasting performance, because it uses the past days having similar hourly temperature features as input data. In order to verify the effectiveness of the proposed method, it was applied to the case study. The case study results show high accuracy of 24-hour load pattern forecasting.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.158-163
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• 2005

Competitive electricity markets necessitate equitable methods for allocating transmission usage in order to set transmission usage charges and congestion charges in an unbiased and an open-accessed basis. So in competitive markets it is usually necessary to trace the contribution of each participant to line usage, congestion charges and transmission losses, and then to calculate charges based on these contributions. A UPFC offers flexible power system control, and has the powerful advantage of providing, simultaneously and independently, real-time control of voltage, impedance and phase angle, which are the basic power system parameters on which sys-tem performance depends. Therefore, UPFC can be used efficiently and flexibly to optimize line utilization and increase system capability and to enhance transmission stability and dampen system oscillations. In this paper, a mathematical approach to allocate the contributions of system users and UPFCs to transmission system usage is presented. The paper uses a dc-based load flow modeling of UPFC-inserted transmission lines in which the injection model of the UPFC is used. The relationships presented in the paper showed modified distribution factors that modeled impact of utilizing UPFCs on line flows and system usage. The derived relationships show how bus voltage angles are attributed to each of changes in generation, injections of UPFC, and changes in admittance matrix caused by inserting UPFCs in lines. The relationships derived are applied to two test systems. The results illustrate how transmission usage would be affected when UPFC is utilized. The relationships derived can be adopted for the purpose of allocating usage and payments to users of transmission network and owners of UPFCs used in the network. The relationships can be modified or extended for other control devices.