• KEPCO Journal on Electric Power and Energy
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• 제8권2호
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• pp.73-77
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• 2022

Recently, as the number of years of operation has increased for more than 30 years, interest in evaluating the remaining life of major power facilities such as transformers and ultra-high voltage cables is increasing. In particular, the risk of failure is increasing because the underground transmission XLPE cable has been built since 1980 and has been operating in excess of 30 years of design life or close proximity. Therefore, it is necessary to develop an algorithm to evaluate the residual life of the XLPE cable considering the load to determine the risk of failure. Since load data is large amount of data, it is necessary to make the variable load information equivalent to the time unit first in order to calculate the remaining life of the system quickly. In overseas literature, transformers are reported to be standardized for variable load equivalent conversion formulas, but they have not been reported for ultra-high voltage cables. Therefore, in this paper, whether the equivalent conversion formula of a transformer can be applied to XLPE cables was reviewed through accelerated degradation tests under equivalent and variable temperature conditions, and considerations were studied when evaluating the remaining operating life of XLPE cables based on the experimental results.

• 전기학회논문지
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• 제59권6호
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• pp.1041-1045
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• 2010

Short-term electric load forecasting of power systems is essential for the power system stability and the efficient power system operation. An accurate load forecasting scheme improves the power system security and saves some economic losses in power system operations. Due to scarcity of the historical same type of holiday load data, most big electric load forecasting errors occur on load forecasting for the holidays. The fuzzy linear regression model has showed good accuracy for the load forecasting of the holidays. However, it is not good enough to forecast the load of the election day. The concept of the load variation rate for the load forecasting of the election day is introduced. The proposed algorithm shows its good accuracy in that the average percentage error for the short-term 24 hourly loads forecasting of the election days is 2.27%. The accuracy of the proposed 24 hourly loads forecasting of the election days is compared with the fuzzy linear regression method. The proposed method gives much better forecasting accuracy with overall average error of 2.27%, which improved about average error of 2% as compared to the fuzzy linear regression method.

• 전기학회논문지P
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• 제60권4호
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• pp.186-192
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• 2011

Recently, due to the expansion of electric power demands, nonlinear load such as converters and inverters connected to the electric power distribution system, and extensive application of harmonic generation sources with power electric devices, disturbance of the electric power system and its influences on industries have been continuously increasing. In this research, we develop a novel aggregation algorithm by considering the harmonics characteristics for residential loads. Using data sets acquired from various experiments, we analyzed load characteristics according to harmonics and presented the results obtained the proposed method.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1998년도 추계학술발표회요약집
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• pp.118.1-118
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• 1998

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.594-597
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• 2007

We present in this paper a novel mid and long term power load prediction method using temporal pattern mining from AMR (Automatic Meter Reading) data. Since the power load patterns have time-varying characteristic and very different patterns according to the hour, time, day and week and so on, it gives rise to the uninformative results if only traditional data mining is used. Also, research on data mining for analyzing electric load patterns focused on cluster analysis and classification methods. However despite the usefulness of rules that include temporal dimension and the fact that the AMR data has temporal attribute, the above methods were limited in static pattern extraction and did not consider temporal attributes. Therefore, we propose a new classification method for predicting power load patterns. The main tasks include clustering method and temporal classification method. Cluster analysis is used to create load pattern classes and the representative load profiles for each class. Next, the classification method uses representative load profiles to build a classifier able to assign different load patterns to the existing classes. The proposed classification method is the Calendar-based temporal mining and it discovers electric load patterns in multiple time granularities. Lastly, we show that the proposed method used AMR data and discovered more interest patterns.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.495-497
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• 1992

Hourly load forecasting has become indispensable for practical simulation of electric power system as the system become larger and more complicated. To forecast the future hourly load the cyclic behavior of electric load which follows seasonal weather, day or week and office hours is to be analyzed so that the trend of the recent behavioral change can be extrapolated for the short term. For the long term, on the other hand, the changes in the infra-structure of each electricity consumer groups should be assessed. In this paper the concept and process of hourly load forecasting for hourly load is introduced.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1427-1434
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• 2017

Since the late 2000s, there has been growing preparation in South Korea for a sudden reunification of South and North Korea. Particularly in the power industry field, thorough preparations for the construction of a power infrastructure after reunification are necessary. The first step is to estimate the peak load demand. In this paper, we suggest a new peak demand estimation methodology by integrating existing correlation analysis methods between economic indicators and power generation quantities with a power supply interruption model in consideration of power consumption patterns. Through this, the potential peak demand and actual peak demand of the Nation, which experiences power supply interruption can be estimated. For case studies on North Korea after reunification, the potential peak demand in 2015 was estimated at 5,189 MW, while the actual peak demand within the same year was recorded as 2,461 MW. The estimated potential peak demand can be utilized as an important factor when planning the construction of power system facilities in preparation for reunification.

• 복합신소재구조학회 논문집
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• 제3권2호
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• pp.19-27
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• 2012

Structural insulated panels, which are structurally performed panels consisting of a plastic insulation bonded between two structural panel facings are one of emerging products with a viewpoint of its energy and construction efficiencies. These components are applicable to fabricated wood structures. By now, there are few technical documents regulated structural performance and engineering criteria in domestic market. This study was conducted to suggest fundamental reports such as racking resistance, axial capacity, transverse load capacity, and lintel load capacity for SIPs. Test results showed that maximum load was 44.3kN, allowable load was 14.7kN for racking resistance, and that maximum load was 137.6kN, allowable load was 37.4kN/m for axial compression capacity. For transverse load capacity, test results showed $10.3kN/m^2$ of maximum load, $3.4kN/m^2$ of allowable load. For lintel load capacity for SIPs dependent to lengths, allowable loads were 20.4kN for 600mm long lintel, 23.9kN for 1,200mm long lintel, 19.3kN for 1,800mm long lintel, and 2,400mm long lintel had 14.1kN of allowable load. In the near future, when the allowable load for wall application is established, SIPs is considered to substitute the existent post-and-lintel construction to bearing wall structure.

• KEPCO Journal on Electric Power and Energy
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• 제2권3호
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• pp.425-431
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• 2016

Supply Capability of the generator, if the maximum demand occurs, refers to the maximum power that can be stably supplied and it is possible to maintain stable power supply to be greater than actual load. However, unexpected power demand and reduction in supply Capability due to stop of unexpected generator in operation can temporarily make a big chaos in power system. In fact, due to a lack of power supply Capability in the country, enforced emergency load adjustment to the September 15, 2011, the circulation power outage has occurred in several cities. As the result, interrupted operation of the elevator and stopped hospital medical equipment led to a great deal of trouble to people's lives, causing a social problem. At that time, it was found that a failed frequency control because of smaller actual supply Capability than that of predicted. The difference was about 1,170 MW with Gas turbine power plant. By accurately calculating the generator supply capability, we can not only grasp the power reserve rate, but also correspond to the time of power supply instability.

• 한국주거학회논문집
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• 제11권1호
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• pp.159-169
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• 2000

This study was examined the energy conservation and the environmental value through the computer simulation employing the micro cogeneration system and the photovoltaic power generation system in house. The results of this study were as follows:1. In case of the micro cogeneration system. With the conditions of 'the electric produced by the micro cogeneration system was not sold to the electric power company', 'control quantity of commercial power supply was 10%' , 'operating time was 6 hour', 'minimum load rate of generator was 50%', and 'having a storage tank', the micro cogeneration system was superior compare to the comparative system in 2.4% of the energy conservation and 4.18% of the environmental value. 2. In case of the photovoltaic power generation system. 1) The 66.9% of total generated electric power from the photovoltaic power system was sold to the electric power company. That is, it could help to preserve the electric power from commercial power supply.2) There is a possibility of cutting the fair rate of electric power.