• Journal of Electrical Engineering and Technology
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• 제5권2호
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• pp.307-318
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• 2010

In this work, an accurate analysis of low frequency current ripple in residential fuel cell power generation systems is performed based on the proposed residential load model and its unique operation algorithm. Rather than using a constant dc voltage source, a proton exchange membrane fuel cell (PEMFC) model is implemented in this research so that a system-level analysis considering the fuel cell stack, power conditioning system (PCS), and the actual load is possible. Using the attained results, a comparative study regarding the discrepancies of low frequency current ripple between a simple resistor load and a realistic residential load is performed. The data indicate that the low frequency current ripple of the proposed residential load model is increased by more than a factor of two when compared to the low frequency current ripple of a simple resistor load under identical conditions. Theoretical analysis, simulation data, and experimental results are provided, along with a model of the load usage pattern of low frequency current ripples.

• 전기학회논문지P
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• 제61권1호
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• pp.29-34
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• 2012

Due to the increasing of nonlinear loads such as converters and inverters connected to the electric power distribution system, and extensive application of harmonic generation sources with power electronic devices, disturbance of the electric power system and its influences on industries have been continuously increasing. Thus, it is difficult to construct accurate load model for active and reactive power in environments with harmonics. In this research, we develop a load modeling method based on Extreme Learning Machine(ELM) with fast learning procedure for residential loads. Using data sets acquired from various residential loads, the proposed method has been intensively tested. As the experimental results, we confirm that the proposed method makes it possible to effective estimate active and reactive powers than conventional methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.212-213
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• 2006

Load models are important for improving the accuracy of stability analysis and power flow studies. Load characteristics change for different voltages and frequencies. In this research, ANN is used to construct the load model. Characteristics of some residential loads are tested under various voltage and frequency conditions. Acquired data are used to construct load models by ANN. Experiments and modeling results are presented in conclusions.

• 전기학회논문지P
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• 제60권1호
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• pp.6-12
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• 2011

In this study, we proposed a residential load modeling method based on neuro-fuzzy inference system by considering of various harmonics. The developed method was implemented by using harmonic information, fundamental frequency and voltage which are essential input factors in conventional method. Thus, the proposed method makes it possible to effectively estimate load characteristics in power lines with harmonics. To show the effectiveness, the proposed method has been intensively tested with various dataset acquired under the different frequency and voltage and compared it with a conventional method based on neural networks.

• 전기학회논문지P
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• 제57권4호
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• pp.362-369
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• 2008

In this study, we developed RBFN(Radial Basis Function Networks) based load modeling method with harmonic components. The developed method considers harmonic information as well as fundamental frequency and voltage considered as essential factors in conventional method. Thus, the proposed method makes it possible to effectively estimate load characteristics in power lines with harmonics. RBFN has some advantage such as simple structure and rapid computation ability compared with multi-layer perceptorn which is extensively applied for load modeling. To verify the effectiveness, the proposed method has been intensively tested with various dataset acquired under the different frequency and voltage and compared it with conventional methods such as polynomial method, MLPN and RBFN with no harmonic components.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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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.

• KIEE International Transactions on Power Engineering
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• 제2A권4호
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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.

• 전기학회논문지
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• 제58권12호
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• pp.2385-2390
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• 2009

Based on the detailed analysis of output characteristics of PV array and residential load usage pattern, a design method to calculate optimal battery capacity for stand-alone PV generation systems is proposed. And also, according to power flow Actual irradiation and temperature data are analyzed to compose a PV array simulator and also six representative home appliances are electrically modeled for load simulator, along with 24hours usage pattern. The surplus and insufficient power can be calculated from the proposed simulation platform, so that selection of an optimal battery capacity can be possible. The theoretical analysis and design process will be explained, along with informative simulation results.

• 전기학회논문지
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• 제65권1호
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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.

• 한국화재소방학회논문지
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• 제25권6호
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• pp.58-63
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• 2011

본 연구는 주거공간에 배치된 가연물의 열역학적 연소모델을 구현하는데 목적이 있다. 화재하중과 화재 강도는 성능설계의 사용이 증가함에 따라 건축물 화재안전 설계에 중요한 요소로 대두되고 있으며, 컴퓨터를 이용한 수치해석을 통해 예측이 가능해 지고 있다. 주거 가연물의 열역학적 연소특성을 예측하기 위해 각 가연물의 수치해석용 모델을 설계하였다. 해석된 결과를 검증하기 위해 수치해석의 결과를 실물 연소실험의 열방출량 결과와 비교하였다. 수치해석을 위해 FDS를 사용하였으며, 난류해석을 위해 LES모델이 사용되었다. 검증결과 열방출율 및 총발열량은 실험결과와 잘 일치함을 확인하였다.