• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.14-19
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• 2008

The paper presents an intelligent time series model to predict uncertain electricity market price in the deregulated industry environment. Since the price of electricity in a deregulated market is very volatile, it is difficult to estimate an accurate market price using historically observed data. The parameter of an intelligent time series model is obtained based on the simultaneous perturbation stochastic approximation (SPSA). The SPSA is flexible to use in high dimensional systems. Since prediction models have their modeling error, an error compensator is developed as compensation. The SPSA based intelligent model is applied to predict the electricity market price in the Pennsylvania-New Jersey-Maryland (PJM) electricity market.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.1-7
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• 2010

Recently, smart grid has been considered a very important new energy delivery technology, and one that can help ensure a cleaner environment by making use of information and communication technology (ICT) in countries around the world. The many technological benefits smart grid offers is expected to bring about a huge change in the electric energy supply chain. In particular, smart grid with advanced ICT is likely to allow market agents to participate in the decision-making process in the restructured electricity industry, easily facilitating Homeostatic Utility Control. In this paper, we examine smart grid as a market externality, and then illustrate issues from the commercial market perspective as it relates to electricity market design. Finally, our paper identifies some of the impacts of smart grid on electricity market design, which may possibly be incorporated into the evolution of the electricity market, thus ensuring market efficiency.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.16-22
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• 2017

In order to reduce costs of electricity energy at periods of peak demand, there has been an exponential interest in Demand Response (DR). This paper discusses the effect on the participants' behavior in response to DR. Under the assumption of perfect competition, the equilibrium point of the electricity market with DR is derived by modeling a DR curve, which is suitable for microeconomic analysis. Cournot model is used to analyze the electricity market of imperfect competition that includes strategic behavior of the generation companies. Strategic behavior with DR makes it harder to compute equilibrium point due to the non-differential function of payoff distribution. This paper presents a solution method for achieving the equilibrium point using the best response function of the strategic players. The effect of DR on the electricity market is illustrated using a test system.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.292-294
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• 1998

It is very important for electric utility to expand generating facilities and transmission equipments in accordance with the increase of electricity demand. Regional electricity demand forecasting is among the most important step for long-term investment and power supply planning. The main objectives of this paper are to develop the methodologies for forecasting regional load demand. The Model consists of four models, regional economy, regional electricity energy demand, areal electricity energy demand. and areal peak load demand. This paper mainly suggests regional electricity energy demand model and areal peak load demand. A case study is also presented.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.901-922
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• 2007

To see how the electricity demand for air-conditioning responds to weather condition and what kind of weather condition works better in forecasting maximum daily electricity demand, four different regression models, which are linear, exponential, power and S-curve, are adopted. The regression outcome turns out that the electricity demand for air-conditioning is inclined to rely on the exponential model. Another major discovery of this study is that the electricity demand for air-conditioning responds more sensitively to the weather condition year after year along with the higher non-air-conditioning electricity demand. In addition, it has also been found that the discomfort index explains the electricity demand for air-conditioning better than the highest temperature.

• Journal of Korean Elementary Science Education
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• v.23 no.3
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• pp.199-207
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• 2004

Elementary science curriculum is designed to be closely-related magnetism with electricity in a physics domain and this paper explored whether elementary school students have recognized of relationships between them and whether there are any trends in the degree of recognition by grades. The elementary students of 3rd to 6th grade (total 154 persons) in a school in a local city participated in the experiment. Two forms of questionnaire were administrated to each grades. In the first questionnaire about magnetism, students were asked to rank the physics terms as the degree of proximity into magnetism and to write briefly the reason. In the second questionnaire about electricity, students were asked to do the same routine. The closer to the central term in the diagram, the lower score were given and the terms were classified as closely related to magnetism, electricity and the rest. Calculated the response frequency and averaged by the ranked terms, it was examined that the scores of proximity in how students closely rated conception to magnetism and electricity. The result said that the upper grades students showed the degree of proximity with magnetism and electricity as closely. Therefore, the sequence of comprehension of magnetism and electricity concept, which was found in the elementary school curriculum, seems to be found in the elementary students＇ recognitions by grades.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.6
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• pp.560-568
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• 2005

The cost accounting of electricity and heat produced from an energy system is important in evaluating the economical efficiency and deciding the reasonable sale price. The OECOPC method, suggested by the author, was applied to a 650 MW combined cycle cogeneration system having 4 operating modes, and each unit cost of electricity and heat products was calculated. In case that a fuel cost is ${\\}400/kg$ and there are no direct and indirect cost, they were calculated as follows; electricity cost of ${\\}23,700/GJ$ at gas-turbine mode, electricity cost of ${\\}15,890/GJ$ at combined cycle mode, electricity cost of ${\\}14,146/GJ$ and heat cost of ${\\}6,466/GJ$ at cogeneration mode, and electricity cost of ${\\}14,387/GJ$ and heat cost of ${\\}4,421/GJ$ at combined cycle cogeneration mode. Further, these unit costs are applied to account benefit on this system. Since the suggested OECOPC method can be applied to any energy system, it is expected to contribute to cost accounting of various energy systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.499-502
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• 2009

Supply of electric power and electricity safety for whole system and network are essential element. Electricity safety technology need rating for product and research about certification as product development that is done cotton flannel mixed with development of u-IT technology consists. Study on serve to develop electricity safety integration supervision system to apply product to u-City electric power appliance and cotton flannel mixed of u-IT appliance, Connection badness sensing instrument made device built-in electric power IT cotton flannel mixed in outlet that is used most in electric power appliance terminal. Using sensor on ZigBee, RFID performance estimation of communication and module for remote safety check of electricity safety integration supervision system. A performance experiment and estimation in PD, Arc detection diagnosis system and certification KS, electricity safety about product that get fitness finding.

• Transactions of the Korean hydrogen and new energy society
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• v.22 no.1
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• pp.118-127
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• 2011

An IGCC was evaluated as one of the next generation technologies that would be able to substitute for coal-fired power plants. According to "The 4th Basic Plan of Long-term Electricity Supply & Demand" which is developed by the Electricity Business Acts, the first IGCC will be operated at 2015. Like other new and renewable energy such as solar PV, Fuel cell, The IGCC is considered as non-competitive generation technology because it is not maturity technology. Before the commercial operation of an IGCC in our electricity market, its economic feasibility under the Korean electricity market, which is cost-based trading system, is studied to find out institutional support system. The results of feasibility summarized that under the current electricity trading system, if the IGCC is considered like a conventional plant such as nuclear or coal-fired power plants, it will not be expected that its investment will be recouped within life-time. The reason is that the availability of an IGCC will plummet since 2016 when several nuclear and coal-fired power plants will be constructed additionally. To ensure the reasonable return on investment (NPV>0 IRR>Discount rate), the availability of IGCC should be higher than 77%. To do so, the current electricity trading system is amended that the IGCC generator must be considered as renewable generators to set up Price Setting Schedule and it should be considered as pick load generators, not Genco's coal fired-generators, in the Settlement Payment.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.639-650
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• 2008

Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (i) a heuristic technique, (ii) a simulation model used by Ontario's Independent Electricity System Operator (IESO), (iii) a Multiple Linear Regression (MLR) model, (iv) NN model, (v) Auto Regressive Integrated Moving Average (ARIMA) model, (vi) Dynamic Regression (DR) model, and (vii) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.