• KIEAE Journal
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• v.11 no.5
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• pp.91-96
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• 2011

This study is to analysis the characteristics of electric power consumption of apartments complex in Korea. This study shows the pattern of electric power consumption and correlation of each apartment complex's completion year monthly and timely. With this result, we are able to predict the demand pattern of electricity in a house and make the schedule by demand pattern. It is expected this data is used as reference of electric consumption of Daejeon area to operate the simulation tools to predict the building energy. The yearly data of 10 apartment complexes of 2010 are analyzed. The results of this study are followed. The averaged amount of electricity consumption in winter is higher as summer because of the high capacity of heating equipment. All of the house has electric base load from 0.26kWh to 0.5kWh. The average of the electricity consumption of month is shown as 310.2kWh. A week is seperated, as 4 part such as week, weekend, Saturday and Sunday. During week, the average of timely electricity consumption is shown as 0.426kWh. The Saturday consumption is 0.437kWh. The Sunday is 0.445kWh. The peak electricity consumption in summer and winter is measured. The peak consumption on summer season is 1.389kW on 22th August 64% higher than winter season 0.887kW on 3rd January.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.151-155
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• 2005

An electricity consumption is closely related to the economic growth structure. The change of economic growth structure affects the pattern of electricity consumption widely and severely. This paper gives that the primary changing factors of electricity growth are economic growth, change of industry structure(the change of electricity consumption ratio in case of residential sector), and the effect of electricity saying. It gives a model to analyze the influence of GDP to the change of electricity consumption patterns by sector through the period of pre and post 1998(IMF, financial crisis) to observe the contribution of each factor to the growth of electricity demand. It is anticipated that this study shows the feasible scheme of economic structure to become the developed country.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.2
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• pp.79-89
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• 2003

A research about finding a new electricity load model that is sensitive to the price of electricity is conducted. This new model i5 polynomial type price sensitive electricity consumption model, while former electricity consumption models have exponential terms or statistic terms. The pattern of electricity consumption of each electricity using devices were identified first, then the proportion of the devices at buses or nodes are investigated, finally weighted sum of electricity consumption and the proportion makes the load model or consumption model of electricity at one bus or node. This new model is easy to use in the simulations or calculations of the electricity consumption, because the arithmetic of functions with polynomial terms are easy compared to the functions with transcendental terms.

• 한국태양에너지학회:학술대회논문집
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• 2011.04a
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• pp.127-132
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• 2011

Worldwide, the building energy simulation becomes inevitable step for predicting the energy consumption in building. In simulation process, the expertise is required for the accurate analysis results. In Korea, however, most of user use the inconsistent data with Korea circumstance. In this step, we need to construct the standard input data matched building in Korea. In this study, electricity consumption of apartments in Daejeon is analyzed. The yearly data of a apartment complexes of 2009 are analyzed as monthly, daily(week and weekend), timely, and completion year. With this result, we are able to predict the demand pattern of electricity in a house and make the schedule by demand pattern. The results of this study are followed. The averaged amount of electricity consumption in winter is higher than summer because of the high capacity of heating equipment. All of the house has electric base load from 0.26kWh to 0.5kWh. The average of the electricity consumption of month is shown as 326.7kWh. A week is seperated as 4 part such as week, weekend, Saturday and Sunday. During week, the average of timely electricity consumption is shown as 0.442kWh. The Saturday consumption is 0.453kWh. The Sunday is 0.461kWh.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1536-1541
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• 2018

For effective electricity consumption in urban railway station such as peak load shaving, it is important to know each electrical load pattern by various usage. The total electricity consumption in the urban railway substation is already measured in Korea, but the electricity consumption for each usage is not measured. The author proposed the deep learning method to estimate the electrical load pattern for each usage in the urban railway substation with public data such as weather data. GRU (gated recurrent unit), a variation on the LSTM (long short-term memory), was used, which aims to solve the vanishing gradient problem of standard a RNN (recursive neural networks). The optimal model was found and the estimation results with that were assessed.

• Journal of the Korean housing association
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• v.23 no.6
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• pp.31-38
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• 2012

In this paper, we draws tendency of the electricity consumption in residential buildings according to inhabitants Composition types and the level of incomes. it is necessary to reduce energy cost and keep energy security through the electricity demand forecasting and management technology. Progressive social change such as increases of single household, the aging of society, increases in the income level will replace the existing residential electricity demand pattern. However, Only with conventional methods that using only the energy consumption per-unit area are based on Energy final consumption data can not respond to those social and environmental change. To develop electricity demand estimation model that can cope flexibly to changes in the social and environmental, In this paper researches propensity of electricity consumption according to the type of residents configuration, the level of income. First, we typed form of inhabitants in residential that existed in Korea. after that we calculated hourly electricity consumption for each type through National Time-Use Survey performed at the National Statistical Office with considering overlapping behavior. Household appliances and retention standards according to income level is also considered.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.591-593
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• 2007

This paper is to cluster the AMR (Automatic Meter Reading) data. The load survey system has been applied to record the power consumption of sampling the contract assortment in KEPRI AMR. The effect of the contract assortment change to the customer power consumption is determined by executing the clustering on the load survey results. We can supply the power to customer according to usage to the analysis cluster. The Korea a class of the electricity supply type is less than other country. Because of the Korea electricity markets exists one electricity provider. Need to further divide of electricity supply type for more efficient supply. We are found pattern that is different from supplied type to customer. Out experiment use the Clementine which data mining tools.

• Journal of Energy Engineering
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• v.24 no.1
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• pp.137-148
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• 2015

So far, the phenomenon of "electrification" has been deepened in Korean industry and especially direct heating energy which accounted for 44.0%(2010) of total energy consumed in Korean manufacturing has been significantly electrified. This paper decomposed electricity consumption for direct heating in Korean manufacturing from 1992 to 2012 using LMDI(Log Mean Divisia Index). This paper includes 4 different factors such as electricity proportion effect, direct heating proportion effect, energy intensity effect and added value effect. And this paper compared the consumption pattern by business type. As results, electricity proportion effect had contributed the most to the increase of electricity consumption for direct heating in Korean manufacturing. And Petrol-Chemical and Iron & Steel had the most electrification of direct heating.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.97-115
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• 2022

Smart power grid is a user friendly system that transforms the traditional electric grid to the one that operates in a co-operative and reliable manner. Demand Response (DR) is one of the important components of the smart grid. The DR programs enable the end user participation by which they can communicate with the electricity service provider and shape their daily energy consumption patterns and reduce their consumption costs. The increasing demands of electricity owing to growing population stresses the need for optimal usage of electricity and also to look out alternative and cheap renewable sources of electricity. The solar and wind energy are the promising sources of alternative energy at present because of renewable nature and low cost implementation. The proposed work models a smart home with renewable energy units. The random nature of the renewable sources like wind and solar energy brings an uncertainty to the model developed. A stochastic dual descent optimization method is used to bring optimality to the developed model. The proposed work is validated using the simulation results. From the results it is concluded that proposed work brings a balanced usage of the grid power and the renewable energy units. The work also optimizes the daily consumption pattern thereby reducing the consumption cost for the end users of electricity.

• KDI Journal of Economic Policy
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• v.41 no.1
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• pp.43-58
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• 2019

Since 2009, electricity consumption has developed a unique seasonal pattern in South Korea. Winter loads have sharply increased, and they eventually exceeded summer peaks. This trend reversal distinguishes these load patterns from those in the USA and the EU, where annual peaks are observed during the summer months. Using Levene's test, we show statistical evidence of a rise in temperature but a decrease in variance over time regardless of the season. Despite the overall increase in the temperature, regardless of the season there should be another cause of the increased demand for electricity in winter. With the present study using data from 1991 to 2012, we provide empirical evidence that relatively low electricity prices regulated by the government have contributed significantly to the rapid upward change in electricity consumption, specifically during the winter months in the commercial sector in Korea.