• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2166-2176
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• 2017

Electricity price prediction plays a crucial part in making the schedule and managing the risk to the competitive electricity market participants. However, it is a difficult and challenging task owing to the characteristics of the nonlinearity, non-stationarity and uncertainty of the price series. This study proposes a hybrid improved strategy which incorporates data preprocessor components and a forecasting engine component to enhance the forecasting accuracy of the electricity price. In the developed forecasting procedure, the Seasonal Adjustment (SA) method and the Ensemble Empirical Mode Decomposition (EEMD) technique are synthesized as the data preprocessing component; the Coupled Simulated Annealing (CSA) optimization method and the Least Square Support Vector Regression (LSSVR) algorithm construct the prediction engine. The proposed hybrid approach is verified with electricity price data sampled from the power market of New South Wales in Australia. The simulation outcome manifests that the proposed hybrid approach obtains the observable improvement in the forecasting accuracy compared with other approaches, which suggests that the proposed combinational approach occupies preferable predication ability and enough precision.

• 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.

• Journal of Energy Engineering
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• v.25 no.2
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• pp.37-44
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• 2016

The demand for electricity has a considerable impact on various energy sectors since electricity is generated from various energy sources. This paper attempts to estimate the electricity demand function and obtain some quantitative information on price and income elasticities of the demand. To this end, we apply a lagged dependent variable model to derive long-run as well as short-run elasticities using the time-series data over the period 1991-2014. Our dependent variable is annual electricity demand. The independent variables include constant term, real price of electricity, and real gross domestic product. The results show that the short-run price and income elasticities of the electricity demand are estimated to be -0.142 and 0.866, respectively. They are statistically significant at the 5% level. That is, the electricity demand is in-elastic with respect to price and income changes in the short-run. The long-run price and income elasticities of the electricity demand are calculated to be -0.210 and 1.287, respectively, which are also statistically meaningful at the 5% level. The electricity demand is still in-elastic with regard to price change in the long-run. However, the electricity demand is elastic regarding income change in the long-run. Therefore, this indicates that the effect of demand-side management policy through price-control is restrictive in both the short- and long-run. The growth in electricity demand following income growth is expected to be more remarkable in the long-run than in the short-run.

• Korean System Dynamics Review
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• v.3 no.1
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• pp.43-60
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• 2002

This paper describes the forecast of wholesale price in competitive Korean electricity market using the system dynamics approach. The system dynamics concepts have been implemented with the Ithink software. This software facilitates the development of stock and flow model with information feedback. Using this model, the future wholesale electricity price can be computed hour by hour, quarterly, and yearly. This model also gives the energy planner the opportunity to create different scenarios for the future of deregulated wholesale markets in Korea. Also It will lead to increased understanding of competitive wholesale market as a complex, dynamic system. Research results show that the plant construction appeared in waves of boom and bust in Korean electricity market like real estate construction. That is, the Korea wholesale market's new power plants and the market price will appear the Boom and Bust cycle. It is very similar behavior as real estate industry. In case of consideration of DSM program, The DSM savings lead to a somewhat different timing of the booms in construction and of price spikes. But the DSM programs do not eliminated the fundamental dynamics of the boom and bust. And the wholesale price is maintained at the lower level compared to the case of without DSM program. However, the unexpected result is found that due to the lower market price, Investor make significantly less investment in new CCs, which leads to the higher wholesale price after 2010. It suggests that the DSM Policy must be implemented with the dynamics of competitive Electricity Market.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.2
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• pp.88-96
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• 2005

At present, the Korean electricity industry is undergoing restructuring and the Cost Based-generation Pool(CBP) market is being operated preparing for Two Way Bidding Pool(TWBP) market open. As the circumstance of the traditional system is changed according to power system deregulation, the simulation tool which should reflect market code providing market operating mechanism is needed to analyze an electricity market. This paper presents the development of an unique market simulator, Market Modeling and Price Simulator(MMPS) that is designed to imitate the Korean electricity market considering uniform price. The MMPS is developed in VB.NET and is composed of two modules that consist of market modeling and price simulation interfacing access database program. To evidence the features and the performance of MMPS, a small two way bidding market with 12-bus system and one way bidding market for generator competition will be presented for the electricity market simulations using MMPS.

• Journal of Energy Engineering
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• v.21 no.1
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• pp.81-85
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• 2012

Electricity is the basic building block of economic development, and constitutes one of the vital infra-structural inputs in socio-economic development. The demand for electricity has been increasing due to extensive urbanization, industrialization, and a rise in the standard of living, as is the case with residential electricity consumption. This paper attempts to estimate the consumer surplus and the economic value of the residential consumption of electricity in Seoul to assist in decision-making in electricity management. The estimated consumer surplus represents the value of the area under the demand curve, above the actual price that is paid for residential electricity consumption. The estimated annual consumer surplus and economic value for the year 2005 amount to 2,144.7 and 3,727.4 billion won, respectively. The estimates per kWh were 184.9 and 316.0 won, respectively, which imply that the consumer surplus and the economic value of residential electricity consumption significantly outweigh the average price of electricity in 2005 of 91.1 won per kWh.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.435-437
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• 2001

The change of the electricity charge from cost base to price base due to the introduction of the electricity market competition causes consumer to choose a variety of charge schemes and a portion of loads to be affected by this change. Besides, it is required the index that consolidate the price volatility experienced on the power exchange with gaming and strategic bidding by suppliers to increase profits. Therefore, in order to find a mathematical model of the sensitively-responding-to-price loads, the price-sensitive load model is needed. And the development of state-of-the-art technologies affects the electricity price, so the diffusion of high-efficient end-uses and these price affect load patterns. This paper shows the analysis on learning curves algorithms which is used to investigate the correlation of the end-uses' price and load patterns.

• Environmental and Resource Economics Review
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• v.24 no.2
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• pp.365-410
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• 2015

Block-rate structures are widely used in utility-pricing, including the Korean residential electricity sector. In the case of the current pricing structure, Korean citizens are highly concerned about incurring excessive electricity costs. For these reasons, there have been many discussions concerning mitigation of the strict pricing structure. Existing studies on the residential electricity demand function under block-rate structure have the following three issues - the consumer's budget constraint is non-linear, perceived price under block-rate structure is uncertain, block-rate structure has endogeneity in the price variable. In this context, this paper estimates the residential electricity demand function using micro-level household expenditure data and simulates the impact of alternative block-pricing schedules.

• 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.