• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.271-274
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• 2005

Under competitive power markets, various long-term and short-term contracts based on spot price are used by producers and consumers. So an accurate forecasting for spot price allow market participants to develop bidding strategies in order to maximize their benefit. Artificial Neural Network is a powerful method in forecasting problem. In this paper we used Radial Basis Function(RBF) network to forecast spot price. To learn ANN, in addition to price history, we used some other effective inputs such as load level, fuel price, generation and transmission facilities situation. Results indicate that this forecasting method is accurate and useful.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1668-1673
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• 2011

Recent power industries are to be progressed as moving into horizontal markets and expanding of competitive systems through promoting SmartGrid. In these environments, the information on power consumers leads to establish a part of power markets through active and real-time participations instead of participating it as a passive manner presented by a vertical integration. Also, such information should be established as a way that effectively reflects changes and market behaviors occurred in power market participants. Therefore, in this study, a method that develops consumer information models, performs integrated managements, implements registration and distribution, and forms integrated management centers is presented to commonly use the consumer information according to the change in the environment of power industries.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.12
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• pp.568-574
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• 2001

The variations of real time electric power price in competitive electricity markets have influence on electric power demands of the consumers. The effects of the consumers for electric power price can be expressed the price elasticity coefficient of the power demand as a measurement. Residential, commercial, and industrial consumers with different characteristics cause the different price elasticity of the power demand due to changing the pattern of consumption. It is necessary that the effects of electric power demands as a function of elasticity coefficient for each loads should be analyzed in Korea which is processing deregulated electric market. Therefore, this paper calculate the elasticity coefficient of each loads and analysis the effects of electric power demands as a function of elasticity coefficient of inflexible and flexible consumers in competitive electricity market.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.2
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• pp.35-41
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• 2008

In this paper, the new demand-side evaluation of the technical potential of lighting dimming control and its applications in electricity markets have been presented. Currently, advanced power information technologies(IT) has been developed and the variations of power information technologies have widely provided the new research and business opportunities. In particular, the dimming control for the lighting devices with time-varying prices and advanced controls has its economically significant values in electricity markets. Therefore, in this paper, the authors have explored the usefulness of lighting dimming control in load management fields as well as energy efficiency fields under the changing competitive electricity market environments.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.804-806
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• 2005

In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity markets. Conventional forced outage rates of generators are conceptually combined with maintenance outage of generators and, consequently, effective outage rates of generators are new iy defined in order to properly address the probabilistic characteristic of generation in electricity markets. Then, original market demands are classified into several distinct demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the original demand. We have found that generators have different effective outage rates values at each classified demand cluster, depending on the market situation. From this, therefore, it can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be more efficiently analyzed in electricity markets perspectives, for this classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• Korea Trade Review
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• v.44 no.1
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• pp.269-283
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• 2019

Due to environmental issues such as global warming, the importance of renewable energy is growing. Solar Power System is one of the most growing eco-friendly energy industries in the world, but Korea's solar energy industry faces fierce competition due to the trade regulations and changes in energy related laws in the major markets such as the U.S., EU and China. Therefore, Korea needs to diversify its export markets towards emerging markets. This paper analyzed 162 countries in the world and developed a model to measure how promising the countries are. GSMI(Grid connected Solar Market Index) and OSMI(Off-grid Solar Market Index) are invented based on the models. By using the developed model and the data of 162 countries over the 15-year period from 2000 to 2014, the foreign markets are ranked for searching the export market. According to the analysis, China, Japan, U.S, India and Taiwan ranked first to fifth in GSMI and OSMI ranking, which were followed by China, India, Bangladesh, Philippines and Afghanistan. The model developed through this research is expected to provide a more reasonable and scientific approach to the advancement of the Korean solar energy industry into overseas markets.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.410-411
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• 2006

This paper is focused on the survey on the power system modeling using a clustering algorithm. In electricity markets, clustering method is a efficient tool to model the power system. It can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be widely applicable to other technical problems in power system such as generation scheduling, power flow analysis, short-term load forecasting, and so on. There are several researches on the power system modeling using a clustering algorithm. We specially surveyed their own clustering methods to model the power system.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.159-161
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• 2005

Transmission congestion is one of the key factors to local market power in competitive electricity markets. Financial transmission rights provide the financial protection to their holders by paying back the congestion cost. However, the market participants who have market power can exacerbate their market power. Due to the exacerbated market power, this paper analyzes the mitigation of local market power using Contingent transmission rights on the market price. Contingent transmission rights provide not only the financial protection but also regulative penalty. The proposed methodology was demonstrated with the Optimal Power Flow(OPF).

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.412-413
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• 2006

This paper proposed the transmission planning mechanism in competitive power markets. This mechanism used Optimal Power Flow(OPF) to calculate operation cost and Contingency Constrained OPF(CC-OPF) to consider N-1 contingency outage. In addition, this algorithm deduced a yearly transmission planning using Dynamic Programming(DP).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.462-466
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• 2009

The power expansion planning is large and capital intensive capacity planning. In the past, the expansion planning was established with the proper supply reliability in order to minimize social cost. However, the planning can't use cost minimizing objective function in the power markets with many market participants. This paper proposed the power expansion planning model using multi-criteria decision rule. This model used multi objective function considering not only cost minimizing but also GENCO's intension. This paper compared proposed model with WASP model in order to verify the result of proposed model.