• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.264-269
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• 2009

Marginal Loss Factor(MLF) is represented as the sensitivity of transmission loss, which is computed from the change of the generation at slack bus by the change of the load at the arbitrary bus. The MLF dependent on the selection of slack bus is one of the key factors affecting nodal pricing, Genco's profits, social welfare(SW) and Nash Equilibrium in a competitive electricity market. This paper addresses the methodology of slack bus selection by using Cournot model of Cost Based Pool market. Numerical results from sample cases show that the slack bus of MLF of the highest average is beneficial from the view points of SW.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.2
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• pp.85-93
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• 2006

Since the SMP(System Marginal Price) is a vital factor to the market participants who intend to maximize the their profit and to the ISO(Independent System Operator) who wish to operate the electricity market in a stable sense, the short-term marginal price forecasting should be performed correctly. In an electricity market the short-term market price affects considerably the short-term trading between the market entities. Therefore, the exact forecasting of SMP can influence on the profit of market participants. This paper presents a new methodology for a day-ahead SMP forecasting using ARIMA(Autoregressive Integrated Moving Average) model based on the time-series method. And also the correction algorithm is proposed to minimize the forecasting error in order to improve the efficiency and accuracy of the SMP forecasting. To show the efficiency and effectiveness of the proposed method, the case studies are performed using historical data of SMP in 2004 published by KPX(Korea Power Exchange).

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.655-657
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• 2003

Power system deregulation has become a worldwide trend which introduces competition in electric power system in order to realize efficient electricity production and investment. In this regards, it is very important to develop an electricity market simulator so that it is to analyze competitive market and train market operators and market participants. In this paper, we implement the algorithm of determining market clearing price as the first module of unique market simulator. The adopted and suggested algorithm is verified by modelling a simple market with a commercial market simulator(PLEXOS).

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.550-552
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• 2001

The vertically integrated power industry was divided into six generation companies and one market operator, where electricity trading was launched at power exchange. In this environment, the profits of each generation companies are guaranteed according to utilization of their own generation equipments. Especially, the electricity demand shows seasonal and weekly regular pattern, which the some capacity should be provided into ancillary service based on the past demand forecasting error and operating results of electricity market. Namely, if generation cost function is applied to SMP and BLMP as announced the previous day, the available generation capacity of the following day could be optimally distributed, and therefore contract capacity of ancillary service applied to CBP(Cost Based Pool) and TWBP(Two-Way Bidding Pool) is determined. Consequently, it is Possible to use the retained equipments optimally. This paper represents on efficient bidding strategies for generation equipments through the calculation of the contract and the application of each generator cost function based on the past demand forecasting error and market operating data.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.94-96
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• 2004

This paper discusses the development of the educational simulator for the electricity spot market in korea. The interaction between lectures and users can be much enhanced via the web-based programs which result in the student's teaming effectiveness on an electricity spot market. However the difficulties for developing web-based application programs are that there can be the numerous unspecified users to access the application programs. To overcome the aforementioned multi-users problem and to develope the educational simulator, we have revised the system architecture, the modeling of application programs, and database which efficiently and effectively manages the complex data sets related to an electricity spot market. The developed application program is composed of the physical three tiers where the middle tier is logically divided into two kinds of application programs. The divided application programs are interconnected by using the Web-service based on XML (Extended Markup Technology) and HTTP (Hyper Text Transfer Protocol) which make it possible the distributed computing technology.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.590-592
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• 2003

The presence of congestion in transmission system can reduce the market size and split bulk system into smaller system. Consequently, this creates the problem concerining Local Market Power and can be main reason for the inclose of practical market price. In this paper, a range of indices have been derived to quantify the degree of local market power through statistical analysis in the uniform pricing market. Application of the indices has been illustrated using the electricity market in Korea. The indices proposed in this paper seem to be effectively applied in electricity market under uniform pricing scheme.

• 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.

• Environmental and Resource Economics Review
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• v.31 no.3
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• pp.367-391
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• 2022

We develop an energy-economy Bayesian DSGE model with the two sectors of electricity generations-traditional (fossil, nuclear) and renewable energy. Under imperfect substitutability between the two sectors, a technological shock on renewable energy sectors does not sufficient to facilitate energy conversion and reduce greenhouse gas emissions. Technology innovation on greenhouse gas emission reduction is also required. More importantly, sufficient investment should be derived by a well-functioning electricity market where electricity price plays a signal role in efficient allocation of resources. Indeed, market rigidities cause reduced consumption.

• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.343-346
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• 2006

Although renewable energy sources are more environmentally friendly than fossil energy sources, it is far more costly, considering current technological standards. It would not present many competitive advantages in the power market. If the renewable electricity is viable in the market, the government should take 'visible' actions to compensate production costs. Popular policies, such as Feed-In-Tariff and Renewable Portfolio Standards, can help to attract investors into generators of renewable electricity. But presently, they are mainly financed through a undifferentiated increase of electricity bills and occasionally confronted with the opposition of the electricity consumers. And most policies tend to focus on increasing the supply of renewable electricity with little consideration toward elevating the motivation of consumers. This study evaluates the potential of environmentally friendly energy consumption and examines the 'green pricing' program which realize the potential.