• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.354-361
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• 2002

This paper propose section properties factor to generate stress history for fatigue analysis and safety inspection of steel bridge. A methodology is described for the computation of numerical stress histories in the steel truss bridge, caused by the vehicles using section properties factor. The global 3-D beam model of bridge is combined with the local shell model of selected details. Joint geometry is introduced by the local shell model. The global beam model takes the effects of joint rigidity and interaction of structural elements into account. Connection nodes in the global beam model correspond to the end cross-section centroids of the local shell model. Their displacements are interpreted as imposed deformations on the local shell model. The load cases fur the global model simulate the vertical unit force along the stringers. The load cases fer the local model are imposed unit deformations. Combining these, and applying vehicle loads, numerical stress histories are obtained. The method is illustrated by test load results of an existing bridge.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.251-258
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• 2023

It is necessary to predict peak load accurately in order to supply electric power and operate the power system stably. Especially, it is more important to predict peak load accurately in winter and summer because peak load is higher than other seasons. If peak load is predicted to be higher than actual peak load, the start-up costs of power plants would increase. It causes economic loss to the company. On the other hand, if the peak load is predicted to be lower than the actual peak load, blackout may occur due to a lack of power plants capable of generating electricity. Economic losses and blackouts can be prevented by minimizing the prediction error of the peak load. In this paper, the latest deep learning model such as TCN is used to minimize the prediction error of peak load. Even if the same deep learning model is used, there is a difference in performance depending on the hyper-parameters. So, I propose methods for optimizing hyper-parameters of TCN for predicting the peak load. Data from 2006 to 2021 were input into the model and trained, and prediction error was tested using data in 2022. It was confirmed that the performance of the deep learning model optimized by the methods proposed in this study is superior to other deep learning models.

• Computers and Concrete
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• v.32 no.5
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• pp.465-474
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• 2023

The point load test (PLT) is a widely-used alternative method in the field to determine the uniaxial compressive strength due to its simple testing machine and procedure. The point load test index can estimate the uniaxial compressive strength through conversion factors based on the rock types. However, the mechanism correlating these two parameters and the influence of the mechanical properties on PLT results are still not well understood. This study proposed a theoretical model to understand the mechanism of PLT serving as an alternative to the UCS test based on laboratory observation and literature survey. This model found that the point load test is a self-confined compression test. There is a compressive ellipsoid near the loading axis, whose dilation forms a tensile ring that provides confinement on this ellipsoid. The peak load of a point load test is linearly positive correlated to the tensile strength and negatively correlated to the Poisson ratio. The model was then verified using numerical and experimental approaches. In numerical verification, the PLT discs were simulated using flat-joint BPM of PFC3D to model the force distribution, crack propagation and BPM properties' effect with calibrated micro-parameters from laboratory UCS test and point load test of Berea sandstones. It further verified the mechanism experimentally by conducting a uniaxial compressive test, Brazilian test, and point load test on four different rocks. The findings from this study can explain the mechanism and improve the understanding of point load in determining uniaxial compressive strength.

• Journal of the Korean Solar Energy Society
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• v.31 no.4
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• pp.1-8
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• 2011

In this paper, inverse building modeling was applied to building perimeter zones which have different window orientation. Two test zones of east-facing and west-facing zones in ERS(Energy Resource Station) building, which is representative of small commercial building, was used to test performance of cooling load calculation and peak cooling load reduction. The dynamic thermal load model for the east and west zone was validated using measured data for the zones and then it was used to investigate the effect of peak cooling load reduction by adjustment of indoor cooling temperature set points during on-peak time period. For the east zone, the peak load can be reduced to about 60% of the peak load for conventional control even without any precooling. For the west zone, PLR is nearly independent of the start of the on-peak period until a start time of 1pm. Furthermore, PLR has a small dependence on the precooling duration. Without any precooling, the peak cooling load can be reduced to about 35% of the peak load associated with conventional control.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.96-101
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• 2008

The field of load modeling has attracted the attention since it plays an important role for improving the accuracy of stability analysis and power flow estimation. Also, load modeling is an essential factor in the simulation and evaluation of power system performance. However, conventional load modeling techniques have some limitations with respect to accuracy for nonlinear and composite loads. Thus, precision load modeling technique and reasonable application method is needed for more accurate power system analysis. In this paper, we develop an intelligent load modeling method based. on neural network and application techniques for power system. The proposed method makes it possible to effectively estimate the load model for nonlinear models as well as linear models. Reasonable application method is also proposed for stability analysis. To demonstrate the validity of the proposed method, various experiments are performed and their results are presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1079-1085
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• 2011

To supply electrical power with high quality, the power system must be optimized in many ways such as planning, control and management. In order to optimize the power system, the analysis of the power system is necessary. The elements of the power system require an accurate model to analysis of the power system. The components of the power systems such as generators, transformers and transmission lines have been studied and researched a lot in their modeling and very sophisticated models have been proposed. However, in case of load in-depth studies on the exact model are required. In this paper, measurement-based load modeling method using real-time measured data is proposed in various methods to reflect the characteristics of the load. To prove the validity of the proposed method, PSCAD/EMTDC program is used to configure the power system and measurement data according to the various failures are used to study on load modeling.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.6
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• pp.728-737
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• 2005

Water quality of the Hwanggujicheon is poor because of the rapid housing and development in the large area of the basin. Establishment of water quality management strategy, based on the pollution sources survey and pollutant loads estimation, has to be established for the preservation of the stream water quality of the region. In this study, waste load allocation model to achieve the water quality goal of the stream and the optimization of pollutant load reduction, was developed. Nonpoint pollutant loads calculated by runoff model in the previous study are utilized for pollutant loads estimation of the drainage areas in this study. From the application result of the allocation model, water quality goals of the Hwanggujicheon that can be achieved as a matter of fact are BOD 8 mg/L. To achieve these goals, 23% of effluent BOD loads have to be reduced in the basin.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.209-211
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• 2002

This paper computes the regional, seasonal and hourly representative model of load power factor considering load characteristics of all 154/22.9 kV substations. An accurately computed representative model of load power factor is studied to present a precision improvement of power system analysis and the security of the system. The method to compute representative model of load utilizes the method of applicable moving average based on the method of flow average. The EMS data are used as the source to assess the load power factor.

• 전기의세계
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• v.29 no.4
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• pp.260-264
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• 1980

In this paper, a new algorithm is derived for short term load forecasting. The load model is represented by the state variable form to exploit the Kalman filter techniques. The suggested model has advantages that it is unnecessarty to obtain the coefficients of the harmonic components and its coefficients are not explicitly included in the model. Case studies were carried out for the hourly power demand forecasting of the Korea electrical system.