• Journal of Korean Institute of Industrial Engineers
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• v.39 no.6
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• pp.562-576
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• 2013

Power TAC (Power Trading Agent Competition) is an agent-based simulation for competitions between electricity brokering agents on the smart grid. To win the competition, agents obtain electricity from the electricity wholesale market among the power plants. In this operation, a key to success is balancing the demand of the customer and the supply from the plants because any imbalance results in a significant penalty to the brokering agent. Given the bidding on the wholesale market requires the price and the quantity on the electricity, this paper proposes four different price estimation strategies: exponentially moving average, linear regression, fuzzy logic, and support vector regression. Our evaluations with the competition simulation show which strategy is better than which, and which strategy wins in the free-for-all situations. This result is a crucial component in designing an electricity brokering agent in both Power TAC and the real world.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.1
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• pp.30-45
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• 2013

Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.

• Environmental and Resource Economics Review
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• v.25 no.3
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• pp.449-470
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• 2016

This paper analyzes the effects of nuclear power generation on industrial growth in using the data of 22 manufacturing sectors in 14 nuclear power countries. The hypothesis that the change in the proportion of nuclear power generation in total electricity generation affects industrial value-added and industrial output through industrial electricity price reduction was tested using the dynamic panel data model. First, it was estimated that the increase in nuclear power generation by a 1% leads to a 0.8% reduction in electricity price. The results indicate that when nuclear power generation increased by a 1% point, industrial value-added and output increased by 0.16% and 0.23%,respectively, in the short-run and by 0.51% and 0.85%, respectively, in the long-run. It was also inferred that the effect of nuclear generation on industrial competitiveness working through electricity price reduction rely on institutional settings in the electricity markets. That is, the competitive effect is greater in the countries such as U.K and Japan where electricity price is high and price volatility is large. Meanwhile, in Germany which has pursued phasing out nuclear power, industrial competitiveness is promoted through stable electricity supply.

• KDI Journal of Economic Policy
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• v.13 no.1
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• pp.135-149
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• 1991

The economic policy of decreasing the electricity price is widely understood to have the effect of stabilizing the general price level and improving the income distribution. However, the impact of electricity price decrease on the income distribution is not quite sure although the electricity price decrease would increase the disposable income of all households. The electricity price change would affect the income distribution through three channels. The first impact on the income distribution is made through the electricity price sructure; Korean electricity price structure is designed to subsidized the industrial sector at the cost of household consumption sector in the sense that the price per unit electricity for industrial sector is much lower than that for household consumption sector. The second impact on the income distribution is created through the disposable household income effect of the price decrease; Relative disposable income effect among households appeared higher to lower income household group and this relative disposable income effect seem to improve the income distribution although the net effect is very small. The third impact on the income distribution is formulated through the net profit effect of entreprise sector; This unearned net profit increase to the already rich industrial entrepreneurs group could create a negative income distribution effect. A simulation of 10% electricity price decrease with all the price structure given was attempted to calculate the net effect of income distribution and it was found the net income distribution effect of flat electricity price decrease to be negative contrary to the general understanding. The income distribution effect would only be one criterion among many other criteria considered in the electricity price making process. The electricity price decrease would be helpful to the price stabilization and price competitiveness of industrial sector. However, it does not improve the general income distribution status by the electricity price decrease with the price structure given.

• Environmental and Resource Economics Review
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• v.14 no.3
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• pp.729-751
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• 2005

RPS(Renewable Portfolio Standards) is an institutional device to promote use of renewable energy through market mechanism by making renewable energy to constitute a pre-announced portion of the electricity production. We measure economic impacts of the introduction of RPS to domestic electricity market at the levels of electricity market, individual industrial sectors and the economy as a whole. First, we examine the TREC(Tradable Renewable Energy Credits) market, where the credits in excess of the obligation of the renewable energy production are sold to those who have to meet the obligation through purchased credits. We then measure end-users' additional cost originating from the introduction of RPS and TREC in electricity production, and their impacts on price and supply in the retail electricity market. Next, using input-output analysis, we measure economic impacts of the changes in retail price and supply on individual industrial sectors and the economy as a whole. Among many others, we find small price effect and large GDP effect - sectoral electricity price rises at around 5%, sectoral price level rises by 0.258%, and sectoral GDP declines by 1.940% on average by the year 2011.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.12
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• pp.1627-1636
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• 2014

In real-time electricity price environment, the energy management system can provide the significant advantage to the residential, commercial and industrial customers since it can reduce the electricity charge by controlling the load operation effectively in response to time-varying price. However, the earlier studies for load management mainly focus on the residential and commercial customers except for the industrial customers because most of load operations in industrial sector are intimately related with production schedule. So, it is possible that the inappropriate control of loads in industrial sector causes huge economic loss. In this paper, therefore, we propose load control algorithm for factory energy management system(F-EMS) to achieve not only minimizing the electricity charges but also maintaining production efficiency by considering characteristics of load operation and production schedule. Considering characteristics of load operation and production schedule, the proposed load control algorithm can reflect the various characteristics of specific industrial customer and control their loads within the range that the production efficiency is maintained. Simulation results show that the proposed load control algorithm for F-EMS leads to significant reduction in the electricity charges and peak power in industrial sector.

• 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.

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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• pp.403-411
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• 2005

At present, the Cournot model is one of the most commonly used theories to analyze the gaming situation in an oligopoly type market. However, several problems exist in the successful application of this model to the electricity market. The representative one is obtaining the inverse demand curve able to be induced from the relationship between market price and demand response. In the Cournot model, each player offers their generation quantity to obtain maximum profit, which is accomplished by reducing their quantity compared with available total capacity. As stated above, to obtain the probable Cournot equilibrium to reflect the real market situation, we have to induce the correct demand function first of all. Usually the correlation between price and demand appears over the long-term through statistical data analysis (for example, regression analysis) or by investigating consumer utility functions of several consumer groups classified as residential, industrial, and commercial. However, the elasticity has a tendency to change continuously according to the total market demand size or the level of market price. Therefore it should be updated as the trading period passes by. In this paper we propose a method for inducing and updating this price elasticity of demand function for more realistic market equilibrium.

• Environmental and Resource Economics Review
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• v.9 no.2
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• pp.333-347
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• 2000

We employed various econometic methods to estimate the production index elasticity and the price elasticity of elecricity demand in Korea and compared the forecasting power of those methods. Cointegration models (ADL model, Engle-Granger model, Full Informtion Maximum Likelihood method by Johansen and Juselius) and Dynamic OLS by Stock and Watson were considered. The forecasting power test shows that Dynamic OLS has the best forecasting power. According to Dynamic OLS, the production index elasticity and the price elasticity of electricity demand in Korea are 0.13 and -0.40, respectively.

• Journal of Energy Engineering
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• v.24 no.2
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• pp.9-16
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• 2015

As electricity is an indispensable input to human's existence and industrial production, economic benefits arise from consumption. The economic benefits of the electricity consumption are useful information in various fields of electricity-related policy. Therefore, this study attempts to value the economic benefits from electricity use. The economic benefit of electricity consumed is the area under the demand curve which made of the sum of the actual consumer expenditure and the consumer surplus. Consumer expenditure can be easily observed but the information on price elasticity of demand is necessarily required to compute consumer surplus. This study derives the estimates for price elasticities through literature review. The price elasticities of the electricity demand for residence, industry, and commercial are estimated to be -0.332, -0.351, and -0.263, respectively. Because the consumer surplus of the electricity consumption for residence, industry, and commercial are computed to be 191.54, 143.44, and 231.91 won per kWh, respectively. Given that average prices of electricity use were 127.02, 100.70, and 121.98 won per kWh for the year 2013, the economic benefit are calculated to be 318.56, 244.14, and 353.89 won per kWh, respectively. We can convert the values to 321.96, 246.75, and 357.67 won per kWh in 2014 constant price, respectively, using consumer price index. They can be used in the economic feasibility analysis of a new electricity supply project.