• IE interfaces
• /
• v.24 no.4
• /
• pp.351-361
• /
• 2011

Forecasting of electricity demand have difficulty in adapting to abrupt weather changes along with a radical shift in major regional and global climates. This has lead to increasing attention to research on the immediate and accurate forecasting model. Technically, this implies that a model requires only a few input variables all of which are easily obtainable, and its predictive performance is comparable with other competing models. To meet the ends, this paper presents an energy demand forecasting model that uses the variable selection or extraction methods of data mining to select only relevant input variables, and employs support vector regression method for accurate prediction. Also, it proposes a novel performance measure for time-series prediction, shift index, followed by description on preprocessing procedure. A comparative evaluation of the proposed method with other representative data mining models such as an auto-regression model, an artificial neural network model, an ordinary support vector regression model was carried out for obtaining the forecast of monthly electricity demand from 2000 to 2008 based on data provided by Korea Energy Economics Institute. Among the models tested, the proposed method was shown promising results than others.

• Advances in Energy Research
• /
• v.3 no.2
• /
• pp.71-80
• /
• 2015

This paper describes nuclear energy technologies for the solution of long term energy problem with better reliability. A short overview about nuclear energy applications are explained with a basic analysis of energy. Furthermore, industrial application, space application of nuclear systems and ship propulsion in nuclear energy application are demonstrated in more detail. This report also includes some examples of the experienced nuclear power plant to identify energy production. The general purpose of the article is to understand how efficiently nuclear systems generates energy, and solve the world's increasing energy demand in our century.

• Environmental and Resource Economics Review
• /
• v.32 no.4
• /
• pp.267-292
• /
• 2023

In this paper, we estimate a time series model of energy demand in the industrial sector with an asymmetric response to energy prices. Including the asymmetric response to energy prices in the model strengthens robustness of the cointegration relationship and reduces the variation of the estimated coefficients across the estimating methods. We find that rising energy prices have a larger impact on energy demand than falling energy prices, with the largest impact occurring when energy prices rise to new highs. The estimation results are partially improved when using gross output rather than value added as a measure of production. Using single equation methods to estimate the asymmetric response model, the elasticity of gross output ranged from 1.05 to 1.09 and the elasticity of price-rise ranged from -0.48 to -0.56, which is similar to the results of international studies.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.3
• /
• pp.29-39
• /
• 2019

In this study, we introduce a model that satisfies energy efficiency and economical efficiency by introducing and demonstrating cogeneration generators in industrial complexes using various actual data collected at the site. The proposed model is composed of three scenarios, ie, full - time operation, scenario operated according to demand, and a fusion type. In this study, the power generation profit and surplus thermal energy are measured according to the operation of the generator, and the thermal energy is traded according to the demand of the customer to calculate the profit and loss including the heat and evaluate the economic efficiency. As a result of the study, it is relatively profitable to reduce the generation of the generator under the condition that the electricity rate is low and the gas rate is high, while the basic charge is not increased. On the contrary, if the electricity rate is high and the gas rate is low, The more you start up, the more profit you can see. These results show that even a cogeneration power plant with a low economic efficiency due to a low "spark spread" has sufficient economic value if it can sell more than a certain amount of heat energy from a nearby customer and adjust the applied power through peak management.

• Journal of the Korean Institute of Gas
• /
• v.24 no.6
• /
• pp.34-46
• /
• 2020

In order to supply stable natural gas in the future, it is necessary to forecast the demand in advance and secure the quantity of supply. In this paper, we propose a method of estimating the demand function of industrial natural gas, which is the core of the increase of domestic natural gas demand in the future. The cross-sectional data of 304 domestic industries were used to estimate the demand function of the industrial natural gas, and the effect of industry specific characteristics such as capital investment, manufacturing cost. Finally, the least absolute deviation estimation method which is robust to outliers and does not assume the homogeneity of the error term and the normality, And the results were derived. In addition, the economic value of industrial city gas was estimated using the price elasticity of industrial city gas. Therefore, it can be seen that the continuous expansion and supply of city gas to the industrial sector is beneficial at the national level, and the government needs to promote expansion through the industrial city gas support policy.

• Proceedings of the KIEE Conference
• /
• 2003.11a
• /
• pp.457-459
• /
• 2003

As a competitive power market has introduced, many energy management systems have been developed. This paper presents the web-based energy management system which is developed by our company. The users tan monitor and analysis their load information using our energy management system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.26 no.2
• /
• pp.18-26
• /
• 2012

Though electricity consumption amount in industry has been increased gradually, corresponding power supply show symptoms of marginal point. Importance of demand-side management from large-industries has also been raised. This paper deals with induction motor, which is one of representative examples of heavy electricity consumption utilities, to analyze potential technical capability, economic feasibility from consumers' viewpoint and demand-side management feasibility from nation-wide perspective. Nation-wide economic feasibility analysis was done through California test, which has been used as demand-side management evaluation model. This paper also describes limitation of existing high efficiency induction motor in terms of contribution to demand-side management and utilizes premium motor to calculate demand-side management contribution level and economic feasibility evaluation. Likewise, this paper emphasizes the efficiency improvement of induction motor and analyzes how much premium motor related technologies can contribute to demand-side management.

• Journal of Energy Engineering
• /
• v.23 no.2
• /
• pp.119-124
• /
• 2014

After the oil crisis in 1970s, many countries have tried to reduce oil dependency. Especially, in Korea, rapid declining oil consumption has speedily brought to electrification and a surge in electricity demand. This paper attempts to estimate the relationship between declining oil use and electrification in Korea using OECD panel data covering from 1985 to 2011. To this end, random effect model and fixed effect model are employed. The increase in the ratio of energy oil to total energy consumption by 10%p leads to reduce the electricity demand by about 15%. This result can be useful information to cope with the recent crisis of electric power. In addition, industrial sector is ranked in forth the ratio of industrial electricity use to total electricity use according to the result of comparative analysis of electricity consumption by use in OECD countries. Therefore, industrial sector should be treated as the main target of demand-side management policies for electricity.

• Journal of the Korean Solar Energy Society
• /
• v.34 no.4
• /
• pp.83-90
• /
• 2014

South Korea's solar energy industry has been made vertical integration and specialization as part of the restructuring in the downturn of the world economy and the oversupply situation of raw materials. This study is to understand the characteristics of the solar energy industry, using data to systematic approach. In this study, it was defined the major business of firms as 22 business types and classified into 5 enterprise groups as technology and business strategy. After that, It was deduced features of Enterprise group by the statistical analysis and looked to draw a map of the industrial structure by social network analysis using the information on companies' demand and supply.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.8
• /
• pp.1347-1354
• /
• 2016

This paper presents optimal operational scheduling model and economic assessment of Li-ion battery energy storage systems installed in non-residential customers. The operation schedule of a BESS is determined to minimize electric bill, which is composed of demand and energy charges. Dynamic programming is introduced to solve the nonlinear optimization problem. Based on the optimal operation schedule result, the economics of a BESS are evaluated in the investor and the social perspective respectively. Calculated benefits in the investor or customer perspective are the savings of demand charge, energy charge, and related taxes. The social benefits include fuel cost savings of generating units, construction deferral effects of the generation capacity and T&D infra, and incremental CO2 emission cost impacts, etc. Case studies are applied to an large industrial customer that shows similarly repeated load patterns according to days of the week.