• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.8
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• pp.466-471
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• 2004

Electricity industries throughout the world are undergoing unprecedented changes. As a result, these changes lead to the separation of traditional integrated utilities and the introduction of competition in order that increase efficiency in electricity industry. Direct load control (DLC) system in competitive electricity market has a hierarchical interactive operation system, therefore, its control logic is also applied by bilateral interactive method that interchanges information related to interruptible load between operation hierarchies. Consequently, load curtailment allocation algorithm appropriate for new DLC system is required, and based on interchanged information, this algorithm should be implemented by most efficient way for each operation hierarchy. In this paper, we develop the load curtailment allocation algorithm in an emergency for new DLC system. Especially, the optimal algorithm for load aggregator (LA) that participates in competitive electricity market as a main operator for load management is developed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1342-1348
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• 2008

One important objective of the electricity market is to decrease the price by ensuring stability in the market operation. Interconnected to this is another objective; namely, to realize sustainable consumption of electricity by equitably distributing the effects and benefits of participating in the market among all participants of the industry. One method that can help achieve these objectives is the ^{(R)}$demand-response program, - which allows for active adjustment of the loadage from the demand side in response to the price. The demand-response program requires a customer baseline load (CBL), a criterion of calculating the success of decreases in demand. This study was conducted in order to calculate undistorted CBL by analyzing the correlations between such external or seasonal factors as temperature, humidity, and discomfort indices and the amounts of electricity consumed. The method and findings of this study are accordingly explicated.

• JOURNAL OF ELECTRICAL WORLD
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• no.2 s.158
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• pp.2-4
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• 1990

• Proceedings of the Korean Nuclear Society Conference
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• 2002.05a
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• pp.371.1-371
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• 2002

• Environmental and Resource Economics Review
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• v.23 no.1
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• pp.91-132
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• 2014

We investigate the effect of ICT capital on the demands for labor and energy in manufacturing and electricity gas water industries of Korea, US, and UK. Assuming ICT capital, non-ICT capital, labor, electricity, fuel, and material as input factors for manufacturing and ICT capital, non-ICT capital, labor and energy material as input factors for electricity gas water industry, we estimate the Morishima elasticities of substitution. Considering the relative price changes of input factors, ICT capital has substituted labor in manufacturing and electricity water gas industries of the three countries. ICT capital has substituted both electricity and fuel in US and UK manufacturing. Although ICT capital has substituted electricity and fuel each other in Korean manufacturing, ICT capital is unlikely to decrease the demands for electricity and fuel when considering their relative price changes. ICT capital has substituted energy material in electricity gas water industries of the three countries.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.219-243
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• 2004

Generally, electricity market has monopoly market structure because of need of enormous investment for infrastructure. However, the introduction of competition in network industry as electricity is a tendency of the world with decreasing the effects of economy of scale due to the advancement of technology. Now, electricity industry restructuring is in progress but the competition in electricity retail market is not in force yet in Korea. Whether a effective competition exist or not is very important to policy decision maker who drive restructuring, but there are small numbers of quantitative researches on that. In this study, we estimated the effectiveness of competition in the electricity retail market through switching costs. If switching costs are high, consumers actually can be locked in incumbent firm in spite of introduction of competition. Therefore switching is a critical factor to determine effectiveness of competition and to estimate the size of switching costs quantitatively can proffer the information about whether the competition in the electricity retail market is effective or not in the future. We estimated switching costs using consumer' stated-preference data by conjoint analysis. In according to estimation results, the cost of switching process is not so high, but the relative brand loyalty of an incumbent company is significantly high. And the price is considered as the most important factor choosing an electric service commodity. Based on the empirical results, it is possible to analyze the relationship between suppliers' competitiveness resulted from management efficiency and customers' switching possibilities. The paper therefore provides guidance for suppliers in deciding to enter into retail competition and for policy makers in introducing retail competition. And it has a significance of estimating the switching costs directly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.52-59
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• 2020

Currently, the domestic electricity rates for houses are charged by applying a progressive level according to monthly electricity usage. Electricity rates rise sharply wWhen the amount of electricity used is large, electricity rates rise sharply. The standardized electricity rate progressive system has limitations in that it lacks consideration of the consumers' power usage patterns and limits consumers' their options. Accordingly, the Ministry of Trade, Industry and Energy and the Korea Electric Power Corporation have been demonstrating the basis of a rate system for housing, which is a method of charging electricity according to the amount of electricity used by season and time. In this paper, 10 electricity usage patterns were derived through from AMI data analysis for 5 five years of 362 apartment complexes located in metropolitan cities. The patterns were, and then applied to the existing domestic electricity rate and time-by-time rates applied to demonstrations, and by time-by-time rates in the US and Australia. The effect of the optional rate by pattern was compared and analyzed. As a result, it was confirmed that benefits occurred in five5 patterns compared to existing rate plans, and the electricity rates increased in 5 five patterns, and t. This phenomenon shows the same phenomenon withis the same as the overseas rates, including domestic rates being demonstrated.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.772-774
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• 2005

Interstate electric power system, as an alternative for energy cooperation under regional economic bloc, has been hotly debated before progressing the restructure in electric power industry and rapidly expanded in many regions after 1990s. Especially, since northeast asia has strong supplementation in resource, load shape, fuel mix etc., electric power system interconnection in this region may bring considerable economic benefits. Moreover, since Korean electric power system has a great difficulty in a geographical condition to interrupt electricity transaction with other countries, it has been expanded as an independent system to supply all demand domestically. As a result, Korean electric power system makes considerable payment for maintaining system security and reliability and expands costly facilities to supply a temporary summer peak demand. Under this inefficiency, if there are electricity transactions with Russia via the North Korea route then economic electric power system operation may be achieved using seasonal and hourly differences in electricity price and/or load pattern among these countries. In this paper, we estimate price cap of transacted electricity via interstate electric power system in northeast asia. For this study, we perform quantitative economic analysis on various system interconnection scenarios.

• 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.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.189-204
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• 2018

This study is on forecasting the electricity consumption of an industrial manufacturing building called GGM from January 2014 to April 2017. We fitted models using SARIMA, SARIMA + GARCH, Holt-Winters method and ARIMA with Fourier transformation. We also forecasted electricity consumption for one month ahead and compared the predicted root mean square error as well as the predicted error rate of each model. The electricity consumption of GGM fluctuates weekly and annually; therefore, SARIMA + GARCH model considering both volatility and seasonality, shows the best fit and prediction.