• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.2
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• pp.74-78
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• 2015

With the improvement of living standards and economic development, electricity consumption continues to grow. The electricity is a special energy which is hard to store, so its supply must be consistent with the demand. The objective of electricity demand forecasting is to make best use of electricity energy and provide balance between supply and demand. Hence, it is very important work to forecast electricity demand with higher precision. So, various forecasting methods have been developed. They can be divided into five broad categories such as time series models, regression based model, artificial intelligence techniques and fuzzy logic method without considering special-day effects. Electricity demand patterns on holidays can be often idiosyncratic and cause significant forecasting errors. Such effects are known as special-day effects and are recognized as an important issue in determining electricity demand data. In this research, we developed the power demand forecasting method using ELM(Extreme Learning Machine) for special day, particularly, lunar new year and Chuseok holiday.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.19-23
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• 2017

Energy is a vital resource for the economic growth and the social development for any country. As the industry becomes more sophisticated and the economy more grows, the electricity demand is increasing. So forecasting electricity demand is an important for electricity suppliers. Forecasting electricity demand makes it possible to distribute electricity demand. As the market for Negawatt market began to grow in Korea from 2014, the prediction of electricity consumption demand becomes more important. Moreover, power consumption forecasting provides a way for demand management to be directly or indirectly participated by consumers in the electricity market. We use Genetic Algorithms to predict the energy demand of the fishing industry in Jeju Island by using GDP, per capita gross national income, value add, and domestic electricity consumption from 1999 to 2011. Genetic Algorithm is useful for finding optimal solutions in various fields. In this paper, genetic algorithm finds optimal parameters. The objective is to find the optimal value of the coefficients used to predict the electricity demand and to minimize the error rate between the predicted value and the actual power consumption values.

• Journal of Energy Engineering
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• v.22 no.1
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• pp.1-7
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• 2013

This paper attempts to estimate the residential electricity demand function, using survey data of 521 households in Korea. As the residential electricity demand function provides us information on the pattern of consumer's electricity consumption, it can be usefully utilized in predicting the impact of policy variables such as electricity price and forecasting electricity demands. We apply least absolute deviation(LAD) estimation as a robust approach to estimating parameters. The results showed that price and income elasticities are -0.68 and 0.14 respectively, and statistically significant at the 10% levels. The price and income elasticities portray that residential electricity is price- and income-inelastic. This implies that the residential electricity is indispensable goods to human-being's life, thus the residential electricity demand would not be promptly adjusted to responding to price and/or income change.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.700-706
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• 2010

Carbon costs, either in the form of a carbon tax or through permit prices in an emissions trading scheme, would ultimately be reflected in higher electricity prices. This price "pass-through" is very critical to the effective design of new policies to curb the amount of carbon emissions. This paper sets out in a structured way the factors that determine price pass-through and how carbon costs would impact on the electricity market and the existing coal-fired power plants. It is shown that pass-through can vary drastically if the underlying dispatch potential of generators varies significantly across alternative emissions reduction scenarios. It can also vary depending on the availability of competing cleaner forms of generation. Pass-through as a measure of business performance is therefore hard to generalize across different circumstances and should be interpreted carefully.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.843-845
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• 2005

The uncertainty of long term electricity plan consists of the uncertainty of demand forecast and additional generating capacity. Demand forecast is clearly improved the accuracy than the past through improving forecasting methods. However, the uncertainty of additional generating capacity is increased due to the change of market environment. In an operation by a sole utility, additional generating capacity would be possible by the regulation of government. Currently the generation companies have spined off from KEPCO and some IPPs participate the electricity market. It increases the uncertainty due to weakened regulation. Also the environment movement by NGOs and occurrence of civil affairs cause the increase of uncertainty. This research would analyze the current situation on the uncertainty of additional generating capacity and construction delays. Furthermore this research would present the plan to reflecting it in long term electricity plan.

• Proceedings of the KIEE Conference
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• summer
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• pp.677-679
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• 2004

Although Jeju is an island, its electricity demand is 430MW. It indicates electricity demand and its growth rate in Jeju are higher than mainland average. The supply of electricity in Jeju consists of power plants within the island and connection of main system using cable line. The cost of supply is higher than mainland system. However the electricity rate and DSM incentives were treated equally with mainland. Therefore, Effective DSM promotion has not been carried out. This paper analyzes the policy alternatives of supply in Jeju and presents effective DSM countermeasures. Also it presents long-term policy on stabilization of supply and demand in Jeju.

• The Korean Journal of Food & Health Convergence
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• v.5 no.4
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• pp.19-23
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• 2019

In recent years, the Internet was a lot of information on the use of Tesla coils bifilar [1] in conjunction with induction cooker, for "free" electricity during power resistive load, including different incandescent lamps. With the development of scientific and technological progress, the demand for electricity in each year is increasing, and at the same time, the need to increase the capacity of electricity production, which entails large investments and, consequently, increase of prices for consumers. As before today, the search for free electric energy is an up-to-date and still open topic. The purpose of research - simplification of information on the possibility of using bifilar coils as an electric current source in conjunction with induction cooker. Consequently, it can be concluded from the above that the use of Tesla coils in combination with induction cooker has very low k.k.d. and it is not possible to obtain excessive electric energy using the Tesla coil under the connection schemes considered.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2150-2156
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• 2010

In this paper, we investigate how an electricity capacity market design may encourage generators to exaggerate their available capacity. In order for an analytical approach, a two player game model is introduced. We focus on two pure strategy Nash equilibria: an equilibrium at which generators offer their true capacities, and an equilibrium at which generators offer exaggerated capacities. The latter case is caused by asymmetries of information between players and so called 'moral hazard' in terms of the economics literature. This paper shows that, considering practical electricity markets, the moral hazard case is highly probable. Moreover, it is shown that, with the considered capacity market design in the real world, the better the electricity energy market performs, the higher the risk of moral hazard becomes.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.2
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• pp.94-100
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• 2016

A virtual power plant (VPP) technology is a cluster of distributed generation installations. VPP system is that integrates several types of distributed generation sources, so as to give a reliable overall power supply. Virtual power plant systems play a key role in the smart grids concept and the move towards alternative sources of energy. They ensure improved integration of the renewable energy generation into the grids and the electricity market. VPPs not only deal with the supply side, but also help manage demand and ensure reliability of grid functions through demand response (DR) and other load shifting approaches in real time. In this paper, utilizing a variety of distributed generation resources(such as emergency generator, commercial generator, energy storage device), activation scheme of the virtual power plant technology. In addition, through the analysis of the domestic electricity market, it describes a scheme that can be a virtual power plant to participate in electricity market. It attempts to derive the policy support recommendation in order to obtain the basics to the prepared in position of power generation companies for the commercialization of virtual power plant.

• 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.