• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.11
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• pp.596-603
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• 2004

This paper proposes an expert system based on the pattern recognition method which can enhance the accuracy and effectiveness of real-time bus reconfiguration strategy for the transfer of faulted load when a main transformer fault occurs in the automated substation. The minimum distance classification method is adopted as the pattern recognition method of expert system. The training pattern set is designed MTr by MTr to minimize the searching time for target load pattern which is similar to the real-time load pattern. But the control pattern set, which is required to determine the corresponding bus reconfiguration strategy to these trained load pattern set is designed as one table by considering the efficiency of knowledge base design because its size is small. The training load pattern generator based on load level and the training load pattern generator based on load profile are designed, which are can reduce the size of each training pattern set from max L/sup (m+f)/ to the size of effective level. Here, L is the number of load level, m and f are the number of main transformers and the number of feeders. The one reduces the number of trained load pattern by setting the sawmiller patterns to a same pattern, the other reduces by considering only load pattern while the given period. And control pattern generator based on exhaustive search method with breadth-limit is designed, which generates the corresponding bus reconfiguration strategy to these trained load pattern set. The inference engine of the expert system and the substation database and knowledge base is implemented in MFC function of Visual C++ Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and pattern recognition solution based on diversity event simulations for typical distribution substation.

• Earthquakes and Structures
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• v.6 no.4
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• pp.437-455
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• 2014

Some conventional lateral load patterns for pushover analysis, and proposing a new accurate pattern was investigated in present research. The new proposed load pattern has load distribution according weight and stiffness variation in height and mode shape of structure. The assessment of pushover application with mentioned pattern in X type braced steel frames and steel moment resisting frames, with stiffness and mass variation in height, was studied completely and the obtained results were compared with nonlinear dynamic analysis method (including time history analysis). The methods were compared from standpoints of some basic parameters such as displacement, drift and shape of lateral load pattern. It is concluded that proposed load pattern results are closer to nonlinear dynamic analysis (NDA) compared to other pushover load patterns especially in tall and medium-rise buildings having different stiffness and mass during the height.

• Structural Engineering and Mechanics
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• v.16 no.4
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• pp.441-468
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• 2003

This paper investigates the structural behavior of modular falsework system under sequential pattern loads. Based on the studies of 25 construction sites, the pattern load sequence modeling is defined as models R (rectangle), L and U. The study focuses on the system critical loads, regions of largest reaction forces, discrepancy between the pattern load and the uniform load, and the warning-system plan. The analysis results show that the critical loads of modular falsework systems with sequential pattern loads are very close to those with the uniform load used in design. The regions of largest reaction forces are smaller than those calculated by the uniform load. However, the regions of largest reaction forces of three models under sequential pattern loads can be considered as the crucial positions of warning-system based on the measured index of loading. The positions of the sensors for the warning-system for these three different models are not identical.

• Steel and Composite Structures
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• v.27 no.5
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• pp.623-632
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• 2018

Performance-Based Plastic Design (PBPD) method has been recently developed to evaluate the behavior of structures in different performance levels. The PBPD method utilizes a base shear force and a lateral load pattern that are estimated based on energy and yielding mechanism concepts. Using of current lateral force pattern results in weak structural members in upper stories of a structure so that the values of the story drift in these stories are larger than the target drift, particularly in high-rise buildings. Therefore, such distribution requires modifications to overcome this drawback. This paper proposes a modified lateral load pattern for steel Eccentrically Braced Frames (EBFs) based on parametric study. In order to achieve the modified load pattern, a group of 26 EBFs has been analyzed under a set of 20 earthquake ground motions. Additionally, results of nonlinear dynamic analyses of EBFs have been post-processed by nonlinear regression analysis in order to derive the new load pattern. To prove the efficiency of present study, three EBFs as examples were designed by modified pattern and current PBPD distribution. Inelastic dynamic analyses results showed that the story drifts using modified lateral load pattern were well within the target values in comparison with current pattern in PBPD, particularly where the effect of the height is significant. The modified load pattern reduces the possibility of underdesigning in upper levels and overdesigning in lower levels of the frames.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.16-22
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• 2016

This paper addresses the load usage scheduling in the HEMS for residential power consumers. The HEMS would lead the residential users to change their power usage, so as to minimize the cost in response to external information such as a time-varying electricity price, the outside temperature. However, there may be a consumer's inconvenience in the change of the power usage. In order to improve this, it is required to understand the pattern of load usage according to the external information. Therefore, this paper suggests a methodology to model the load usage pattern, which classifies home appliances according to external information affecting the load usage and models the usage pattern for each appliance based on a copula function representing the correlation between variables. The modeled pattern would be reflected as a constraint condition for an optimal load usage scheduling problem in HEMS. To explain an application of the methodology, a case study is performed on an electrical water heater (EWH) and an optimal load usage scheduling for EHW is performed based on the branch-and-bound method. From the case study, it is shown that the load usage pattern can contribute to an efficient power consumption.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.416-418
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• 2001

This Paper presents the 2-step load cycle of daily load curve for representative load pattern of power distribution transformer. We decide the representative load pattern of distribution transformer in domestic using the pattern classification algorithm. The K-mean method is used for the pattern classification algorithm. The acquisition equipment of field load data is utilized for 96-sample distribution transformers and the field data is used in the construction of the database for the creation of daily load pattern.

• 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 A
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• v.53 no.9
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• pp.513-520
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• 2004

In the paper, we summarize the result of the experimental research for the overload criteria of domestic distribution transformers considering the electric consumption patterns of customers. For the basic characteristic data of distribution transformer overload, the actual experiments are accomplished. The field data of loads are surveyed from sample transformers for analyzing the consumption pattern of customer load. The load data acquisition devices are equipped, and the algorithm of load pattern classification is applied. In addition to this efforts, various load pattern data. in past are gathered. Then the representative load pattern of each customer type in domestic is extracted. The final results of overload criterions are presented as tabular form through the results of experiments and survey are combined. The field test of the experiment results is peformed using the special manufactured transformers, which can measure both the load and top-oil temperature of transformer. Through this, we verify that the results of field test are similar to the laboratory one and the Proposed overload criteria can be effectively applied to the real system.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.10a
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• pp.459-462
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• 1999

This paper presents a numerical study on the effect of live load pattern on RC flat plate under in-plane compression. Through the numerical study on various live load pattern, the load condition that governs the strength of the flat plate is determined. Effects of L.L/D.L. and arrangement of reinforcement on the behavior of the flat plate are also studied. And the efficient arrangement of reinforcement regarding to live load pattern is proposed.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.1
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• pp.61-69
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• 2016

Understanding load patterns and customer classification is a basic step in analyzing the behavior of electricity consumers. To achieve that, there have been many researches about clustering customers' daily load data. Nowadays, the deployment of advanced metering infrastructure (AMI) and big-data technologies make it easier to study customers' load data. In this paper, we study load clustering from the view point of yearly and daily load pattern. We compare four clustering methods; K-means clustering, hierarchical clustering (average & Ward's method) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise). We also discuss the relationship between clustering results and Korean Standard Industrial Classification that is one of possible labels for customers' load data. We find that hierarchical clustering with Ward's method is suitable for clustering load data and KSIC can be well characterized by daily load pattern, but not quite well by yearly load pattern.