• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.255-263
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• 2003

A multi-agent system designed to represent newly deregulated electricity markets in the USA is aimed at testing the capability of the multi-agent model to replicate the observed price behavior in the wholesale market and developing a smart business intelligence which quickly searches the optimum offer strategy responding to the change in market environments. Simulation results show that the optimum offer strategy is to withhold expensive generating units and submit relatively low offers when demand is low, regardless of firm size; the optimum offer strategy during a period of high demand is either to withhold capacity or speculate for a large firm, while it is to be a price taker a small firm: all in all, the offer pattern observed in the market is close to the optimum strategy. From the firm's perspective, the demand-side participation as well as the intense competition dramatically reduces the chance of high excess profit.

• Korean System Dynamics Review
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• v.3 no.1
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• pp.43-60
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• 2002

This paper describes the forecast of wholesale price in competitive Korean electricity market using the system dynamics approach. The system dynamics concepts have been implemented with the Ithink software. This software facilitates the development of stock and flow model with information feedback. Using this model, the future wholesale electricity price can be computed hour by hour, quarterly, and yearly. This model also gives the energy planner the opportunity to create different scenarios for the future of deregulated wholesale markets in Korea. Also It will lead to increased understanding of competitive wholesale market as a complex, dynamic system. Research results show that the plant construction appeared in waves of boom and bust in Korean electricity market like real estate construction. That is, the Korea wholesale market's new power plants and the market price will appear the Boom and Bust cycle. It is very similar behavior as real estate industry. In case of consideration of DSM program, The DSM savings lead to a somewhat different timing of the booms in construction and of price spikes. But the DSM programs do not eliminated the fundamental dynamics of the boom and bust. And the wholesale price is maintained at the lower level compared to the case of without DSM program. However, the unexpected result is found that due to the lower market price, Investor make significantly less investment in new CCs, which leads to the higher wholesale price after 2010. It suggests that the DSM Policy must be implemented with the dynamics of competitive Electricity Market.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1480-1491
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• 2015

In new deregulated electricity market, short-term price forecasting is key information for all market players. A better forecast of market-clearing price (MCP) helps market participants to strategically set up their bidding strategies for energy markets in the short-term. This paper presents a new prediction strategy to improve the need for more accurate short-term price forecasting tool at spot market using an artificial neural networks (ANNs). To build the forecasting ANN model, a three-layered feedforward neural network trained by the improved Levenberg-marquardt (LM) algorithm is used to forecast the locational marginal prices (LMPs). To accurately predict LMPs, actual power generation and load are considered as the input sets, and then the difference is used to predict price differences in the spot market. The proposed ANN model generalizes the relationship between the LMP in each area and the unconstrained MCP during the same period of time. The LMP calculation is iterated so that the capacity between the areas is maximized and the mechanism itself helps to relieve grid congestion. The addition of flow between the areas gives the LMPs a new equilibrium point, which is balanced when taking the transfer capacity into account, LMP forecasting is then possible. The proposed forecasting strategy is tested on the spot market of the Nord Pool. The validity, the efficiency, and effectiveness of the proposed approach are shown by comparing with time-series models

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.372-374
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• 2002

The Optimal Power Flow(OPF) is the optimization model that has different constraints and the specified objective function, which is very useful tool for efficient system and market operation in the competitive electricity market. The existed OPF models focus on the minimization of generation fuel cost under informed demand values at each bus Recently, the studies of OPF model with demand function considering the response behavior of customers in the deregulated electricity market have been executed. This paper implements the OPF model using demand function with specified price elasticity, and provides the analysis of related results.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.485-486
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• 2007

In the deregulated power market, suppliers, consumers and transmission companies try to maximize their profits by economical behaviors. In particular, generating companies like to sell more electricity for the revenue. Their situations will lead to various power system planning as optimal solutions for each supplier. In this paper, fundamental approaches of optimal power system planning under market positions of generating company are presented. The profit-maximizing approaches are modeled mathematically. By this analysis, each optimal planning is proved in risk of cost and monetary risk will be the economical signal for participants.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.869-871
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• 2005

As deregulated electricity markets are being implemented in different countries, the remuneration of reactive power which contribute to ancillary services is one of the key issues, so it is necessary to evaluate the generator's reactive. In this paper, we focus on the evaluation of reactive power which contributes to reactive power balance. The idea is that the main usages of the reactive power of generator can be divided into two components. First one is physically required amounts for transmitting the real power and the second one is the amounts contributed to support the system, that is, to maintain the voltage profiles. In this paper, the second component is used to evaluate the effective amounts of the reactive power contributed to ancillary service.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.667-674
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• 2013

Wind power producers face many regulation costs in deregulated environment, which remarkably lowers the value of wind power in comparison with conventional sources. One of these costs is associated with the real-time variation of power output and being paid in frequency control market according to the variation band. This paper presents a new approach to coordination of battery energy storage in wind generation system for reducing the payment in frequency control market. The approach depends on the statistic data of wind generation and the prediction of frequency control market price to determine the optimal variation band which is then kept by the real-time charging and discharging of batteries, ultimately the minimum cost of frequency regulation can be obtained. The optimization problem is formulated as trade-off between the decrease in the regulation payment and the increase in the cost of using battery, and vice versus. The approach is applied to a study case and the results of simulation show its effectiveness.

• KIEE International Transactions on Power Engineering
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• v.11A no.4
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• pp.39-44
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• 2001

As electric power systems have been moving from vertically integrated utilities to a deregulated environment, the charging of reactive power management is a new challenging them for market operators. This paper proposes a new methodology to compute the costs of providing reactive power management service in a competitive electrical power market. The proposed formulation, which is basically different from those shown in the literature, consists of two parts. One is to recover investment capital costs of reactive power supporting equipment based on a reactive power flow tracing algorithm. The other is to recover operational costs based on variable spot prices using the optimal power flow algorithm. The charging shapes resulted from the proposed approach exhibit a quite good meaning viewed from a practical sense. It turns out that reactive power charged are mostly due to recovery of capital costs and slightly due to recovery of operational costs. The methods can be useful in providing additional insight into power system operation and can be used to determined tariffs of a reactive power management service.

• Environmental and Resource Economics Review
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• v.11 no.3
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• pp.493-513
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• 2002

This empirical study analyzed the policy effect of deregulation in oil product prices. To investigate the effect of deregulation, it is tested whether gasoline prices are determined by market power. Also, the role of government in gasoline tax system is investigated. The empirical analysis has been done by using error correction model. The major findings are as follows. First of all, no significant empirical evidence is found to support that the deregulation affects the determination of gasoline prices. Secondly, the short-term CIF elasticity is estimated to be 0.14. This finding implies that if CIF increases 10%, the gasoline prices increase 1.4%. Finally, the investigation on government role in deregulated market shows that the government has still exercise the power of control through the tax system. For example, the government is seemed to increase the gasoline price more than the increase amount caused by the international oil prices and the exchange rates, because of the intention to achieve the internal revenue increases and lead to gasoline conservation.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.403-405
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• 2000

This paper presents a N-player game theory application for analyzing power transactions in a deregulated energy marketplace such as PoolCo, where, participants, especially, generating entities, maximize their net profits through optimal bidding strategies (i.e., bidding prices and bidding generations). In this paper, the electricity market for power transactions is modeled as a non-cooperative. N-player game with complete information, where the solution is determined in a continuous strategy domain having recourse to the Nash equilibrium idea.