• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.1
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• pp.20-27
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• 2001

In this paper, we propose a method for estimating the peak load of pole-transformer in summer season considering the degree of cooling load possession in customer. The cooling load of customer is selected as the most reliable parameter of peak load in summer season. The proposed estimation method is restricted to the aspect of load management for pole-transformer. The main concept of proposed method is that the error of peak load estimation using load regression equation reduces with considering the degree of cooling load possession in customer. We propose an index for estimation of cooling load possession in each customer. The proposed index is defined as cooling load possession in customer (CLPC) and obtained from the increment of monthly electric energy. The membership function for deciding the uncertainty of cooling load possession in customer is used. The database of pole-transformer in Korea Electric Power Corporation (KEPCO) is used for case studies. Through the case studies, we verify that the proposed method reduces the error of peak load estimation than the conventional method in domestic.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.4
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• pp.482-488
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• 2013

Load forecasting is essential to the economical and the stable power system operations. In general, the forecasting days can be classified into weekdays, weekends, special days and special light-load periods in short-term load forecast. Special light-load periods are the consecutive holidays such as Lunar New Years holidays, Korean Thanksgiving holidays and summer special light-load period. For the weekdays and the weekends forecast, the conventional methods based on the statistics are mainly used and show excellent results for the most part. The forecast algorithms for special days yield good results also but its forecast error is relatively high than the results of the weekdays and the weekends forecast methods. For summer special light-load period, none of the previous studies have been performed ever before so if the conventional methods are applied to this period, forecasting errors of the conventional methods are considerably high. Therefore, short-term load forecast for summer special light-load period have mainly relied on the experience of power system operation experts. In this study, the trends of load profiles during summer special light-load period are classified into three patterns and new forecast algorithms for each pattern are suggested. The proposed method was tested with the last ten years' summer special light-load periods. The simulation results show the excellent average forecast error near 2%.

• Structural Engineering and Mechanics
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• v.32 no.3
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• pp.371-382
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• 2009

Response of harbor structure to environmental loads such as wave load, impact load, ship's contacting load, is a fundamental factor in designing of the structure's optimal configuration. In this paper, typical environmental loads against coastal structures are investigated for designing of the optimal harbor structure. Loads to be considered here are wave load, impact load and contacting load due to ship mooring. Statistical analysis for several harbor structure types under the corresponding loads is carried out, followed by investigation of effect of individual environmental load. Based on these, the optimal configuration for the harbor structure is obtained after considerable engineering process. Estimation of contacting load of the ship is suggested using effective energy concepts for the load, and analysis of structural behavior is done for the optimal designing of the structure in the particular load. A guideline for the design process of the harbor structure is established, and safety of the structure is examined by proposed scheme. For verification of the analytical approach, various steel-piled coastal structures and caissons are chosen and relevant structural analyses are carried out using the Finite Element Methods combined with MIDAS/GTS and ANSYS code. It is found using the Morison equation that impact load cannot be a major load in the typical harbor structure compared with the original wave load, and that configuration shape of the structure may play an important role in consideration of the response criteria.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1516-1521
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• 2008

Recently, distribution load analysis using AMR (Automatic Meter Reading) data is researched in electric utilities. Load analysis method based on AMR system generates the typical load profile using load data of AMR customers, estimates the load profile of non-AMR customers, and analyzes the peak load and load profile of the distribution circuits and sectors per every 15 minutes/hour/day/week/month. Typical load profile is generated by the algorithm calculating the average amount of power consumption of each groups having similar load patterns. Traditional customer clustering mechanism uses only contract type code as a key. This mechanism has low accuracy because many customers having same contract code have different load patterns. In this research, We propose a customer clustring mechanism using k-means algorithm with contract type code and AMR data.

• The Journal of Korean Physical Therapy
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• v.17 no.3
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• pp.429-440
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• 2005

The purpose of this study was to compare the effects of knee joint position sense following local and general load protocols in 25 healthy male subjects. Proprioception of the knee joint was evaluated by measuring absolute angular errors at matching angles before, after and between 2 different types of load protocols. Proprioception tests(on the dominant knee) were performed in which proprioception of the passivepassive reproduced and active-active reproduced knee position was measured. Local load was provided with maximum isokinetic knee extension-flexion on the isokinetic dynamometer(Cybex), and general load was 10 minutes running on a treadmill. Peak torque(knee extension and flexion) and heart rate(beats per minute) was evaluated as an indicator of local and general fatigue during load protocols. The results were as follows: 1. For pasive-pasive reproduced knee position test, significant difference in absolute angular errors after general load protocol was detected compared with that before general load protocol(P<.05), significant difference in absolute angular errors after local load protocol was detected compared with that before local load protocol(P<.05). However, no significant difference in absolute angular errors of general load protocol was detected compared with that of local load protocol (P>.05), no significant difference in absolute angular errors of local load protocol was detected compared with that of general load protocol(P>.05). 2. For active-active reproduced knee position test, significant difference in absolute angular errors after general load protocol was detected compared with that before general load protocol(P<.05), significant difference in absolute angular errors after local load protocol was detected compared with that before local load protocol (P<.05). Also, significant difference in absolute angular errors of general load protocol was detected compared with that of local load protocol(P<.05), significant difference in absolute angular errors of local load protocol was detected compared with that of general load protocol(P<.05). 3. A significant decrease of peak torque of knee extensors and flexors was seen after local load, although heart rate was significantly increased(P<.05). No significant change of peak torque of knee extensors and flexors was seen after general load(P>.05), although heart rate was also significantly increased(P<.05). The previous study revealed that knee proprioception is significantly altered when the muscle mechanoreceptors are dysfunctional due to muscle fatigue, although the joint mechanoreceptors have no significantly effect on knee proprioception when the presence of knee muscle fatigue. However, the results of this study are different from those of the previous study in that muscle weakness of the knee could not be seen after general load. This study shows that general load may diminish motor control by the central nervous system. Proprioceptional decline without muscle weakness of knee after general load suggests a change in the proprioceptional pathway without influence from muscle mechanoreceptors.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1486-1492
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• 2016

This study presents the electrical load forecasting and error correction method using a real building load pattern, and the way to manage the energy storage system with forecasting results for economical load operation. To make a unique pattern of target load, we performed the Hierarchical clustering that is one of the data mining techniques, defined load pattern(group) and forecasted the demand load according to the clustering result of electrical load through the previous study. In this paper, we propose the new reference demand for improving a predictive accuracy of load demand forecasting. In addition we study an error correction method for response of load events in demand load forecasting, and verify the effects of proposed correction method through EMS scheduling simulation with load forecasting correction.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.4
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• pp.255-261
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• 2016

Korean Power System are operating a load shedding system to prevent voltage instability phenomenon caused by severe line contingencies. In order to apply the load shedding scheme should be selected a location, amount, delay time. Current load shedding system is load shedding amount that has been calculated in the steady-state analysis to load shed the total amount in first level, load shedding amount calculated in advance, it is possible to perform an unnecessary load shedding. In this paper, set a multi-level load shedding control strategy step-by-step selection of load shedding amount for the prevention of excessive load shedding. In addition, through a voltage resilience analysis of the power system by applying motor load ratio and sensitivity parameter to selection the multi level load shedding ratio and delay time. For this reason, to take advantage of the limit data of interchange power, by utilizing interface power flow data to set a multi-level load shedding control strategy for the stabilization of the Korean Power System.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.1434-1441
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• 2005

For anchored system applications, each ground anchor is tested after installation and prior to being put into service to loads that exceed the design. This load testing methodology, combined with specific acceptance criteria, is used to verify that the ground anchor can carry the design load without excessive deformations and that the assumed load transfer mechanisms have been properly developed behind the assumed critical failure surface. After acceptance, the ground anchor is stressed to a specified load and the load is locked-off. The two types of load tests conducted during the research program included performance test and creep test which were carried out in accordance with testing procedures by AASHTO(AASHTO 1990) and FHWA(Weatherby 1998) at Samsung-Dong 00 Site. Form the measurements, ultimate load and creep rate of anchors are proposed for straight shaft pressured grouted anchors in waste landfill. The load distribution on the grout was obtained from the measured strain data at each fraction of the ultimate load during the load tests.

• Journal of the Korean housing association
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• v.11 no.2
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• pp.129-137
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• 2000

This study is about the difference of South and East facing Cooling load of Apartment s Houses using Dynamic Heat-flow Calculation. Therefore, the purpose of this study is come in to use Material for the Thermal Environments of Apartment Houses. The results of the analysis are below. (1) For the peak load of degree hour; The highest is "I" unit and the next high load is H, F, E, C, B, G, D and A unit for the south facing Apartment houses. The higher load is "H" unit and the next high load is I, E, F, B, C, G, D, A Unit for the east facing Apartment houses. (2) For the total load of degree day; The highest load is "I" unit and the next high load is H, G, F, E, C, B, D and A Unit for the south facing Apartment houses. The highest load is "H" unit and the next high load is I, G, E, F, B, C, D, A Unit for the east facing Apartment houses. (3) For the total load of degree day; The highest load is "H" Unit for the east facing Apartment houses and the Lowest load is "A" Unit for the south facing Apartment houses.is "A" Unit for the south facing Apartment houses.nt houses.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.