• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.4
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• pp.172-179
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• 2001

A component based method out of load modeling is to aggregate component load model according to the composition rate of each component load at load bus based on the circuit theory. But the most of component loads respond complex nonlinear characteristics respect to voltage and frequency variation due to the control techniques and semiconductor elements applied to component load. It needs to verify this approach through actual experiment of the aggregation of component load even if it can be down. To identify this aggregation method well known, this paper is proposed the classifying method of component load characteristics for component loads to group by quantitative analysis. The component load characteristics were divided into several types by KSOM (kohonen self organizing map), which can classify multi-dimension vector, component load pattern, into two-dimension vector. Some ambiguous cases happened from KSOM were classified by the proposed closing degree.

• KIEE International Transactions on Power Engineering
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• v.2A no.4
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• pp.136-144
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• 2002

Load models are very important for improving the accuracy of stability analysis and load flow studies. Various loads are connected to a power bus and their characteristics of power consumption change with voltage and frequency. Thus, the effect of voltage/frequency changes must be considered in load modeling. In this work, artificial neural networks-ANNs- were used to construct the component load models for more accurate modeling. A typical residential load was selected and subjected to a test under variable voltage/frequency conditions. Acquired data were used to construct component models by ANNs. The aggregation process of separately determined load models is also presented in the paper. Furthermore, this paper proposes a method to transform a single load model constructed by the aggregation method into a mathematical load model that can be used in traditional power system analysis software.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.4
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• pp.96-101
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• 1999

Load model is very important to improve accuracy of stability analysis and load flow study in power systems. A power system bus is composed by various loads, and loads have different power consumption due to voltage/frequency changing. Thus the effect of voltage/frequency changing must he considered to load mxleling. In this research, ANN was used to construct component load moddel for more accurate load mxleling. Typical residential load was selected, and characteristics exrerimented on voltage/frequency changing. Acquired data used to construct the component ANN model, and aggregation method of component load model was presented based on component load model and composition rate. Furthennore, it's transfomlation method to the mathematical load model to he used at the traditional power system analysis soft wares was also presented.sented.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.3
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• pp.179-182
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• 2003

Component-based method for load model not only should include the performances of the load components, but also should take into consideration the core losses of transformers, the line losses and the capacitor banks. Especially, capacitor bank affects the accuracy of reactive load model in load modeling. But it is difficult to identify actual reactive powers of capacitor banks in power system for load modeling. This research improves the component-based modeling method including uncertain capacitor bank. The proposed method is hybrid technique, which adds the measurement-based method to the existing component-based method for reliable information of capacitor band. The results of case studies were presented to verify the validity of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.2
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• pp.45-52
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• 2002

Load modeling is classified into two methods according to approaching method, so called the measurement and component-based method. The measurement method is to model the load characteristics measured directly at substations and feeders. But it is difficult to measure continuously load characteristics from naturally occurring. system variation. The component-based method consists of the fellowing process; component load modeling, composition rate estimation and aggregation of component loads, etc. In this paper, the characteristic experiment of component loads was performed to obtain data for the component load modeling as the component-based method. At first, representative component loads were selected by the proposed method considering the accuracy of load modeling and the performance possibility of component load experiment in the laboratory. Also an algorithm was Proposed to identify the reliability of data obtained from the component load characteristic experiments. In addition, the results were presented as the case studies.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.6
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• pp.279-286
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• 2001

A load modeling, micro method, is performed by component load modeling, load composition rate estimation and aggregation of component load model, etc. The load model obtained from this process must be applied to actual load bus to verify it and to get reliable load model. But it is difficult to apply every load bus due to al lot of load buses and complex experiment. This paper proposed the field test method in load bus to verify the load modeling. For appropriate field test, representative load buses are selected by the proposed algorithm considering the composition rate of user category in all load buses. The field tests were performed at selected load buses to obtain load characteristics of bus by time and seasonal without blackout. The results of measurement and analysis are presented in detail.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1230-1232
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• 1999

In this research, ANN load model was built on results of field test using residential load, and then proposed ANN load model was applied to transient analysis. The results of this research are as follows. The first, component load modeling using ANN was implemented. The second, group load model was proposed by aggregation of component load. The third, proposed load model was applied to power system analysis. Therefore, Importance of load modeling and precise load modeling method was suggested in this paper.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.2
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• pp.65-71
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• 2013

Nonlinear loads with harmonics exist in an actual power system where harmonic currents make voltage distortion. The sum of reactive power measured at individual load is different from the measured reactive power at a bus in a power system with linear and non-linear loads. In this study, ANN(artificial neural network) load modeling technique with consideration of harmonics is introduced for more accurate component load modeling and an impact coefficient is proposed for aggregation of component loads. Results of this research show more accurate load modeling method. Since precise data for power system analysis can be acquired, the proposed method will be used for power system planning and maintenance.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.325-327
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• 1999

In this research, selection of component load and measurement device is considered for accurate component load modeling. The procedure of component load characteristic experiments is also presented.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1478-1480
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• 1999

The accurate analysis of power system requires detailed load model. There are two basic approaches in modeling the load characteristics. One is to directly measure the voltage and frequency sensitivity of the load P and Q at substations and feeders. The other is to build up a composite load model from each load component. Each of these methods has advantages and disadvantages. This paper presents load composition for KEPCO's power system to develop load models by the component-based load modeling.