• Corrosion Science and Technology
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• 제18권2호
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• pp.61-71
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• 2019

Flow-Accelerated Corrosion (FAC) is a phenomenon in which a protective coating on a metal surface is dissolved by a flow of fluid in a metal pipe, leading to continuous wall-thinning. Recently, many countries have developed computer codes to manage FAC in power plants, and the FAC prediction model in these computer codes plays an important role in predictive performance. Herein, the FAC prediction model was developed by applying a machine learning method and the conventional nonlinear regression method. The random forest, a widely used machine learning technique in predictive modeling led to easy calculation of FAC tendency for five input variables: flow rate, temperature, pH, Cr content, and dissolved oxygen concentration. However, the model showed significant errors in some input conditions, and it was difficult to obtain proper regression results without using additional data points. In contrast, nonlinear regression analysis predicted robust estimation even with relatively insufficient data by assuming an empirical equation and the model showed better predictive power when the interaction between DO and pH was considered. The comparative analysis of this study is believed to provide important insights for developing a more sophisticated FAC prediction model.

• 산업경영시스템학회지
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• 제41권1호
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• pp.84-93
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• 2018

In this paper, we propose an Elman recurrent neural network to predict and analyze a time series of power energy consumption. To this end, we consider the volatility of the time series and apply the sample variance and the detrended fluctuation analyses to the volatilities. We demonstrate that there exists a correlation in the time series of the volatilities, which suggests that the power consumption time series contain a non-negligible amount of the non-linear correlation. Based on this finding, we adopt the Elman recurrent neural network as the model for the prediction of the power consumption. As the simplest form of the recurrent network, the Elman network is designed to learn sequential or time-varying pattern and could predict learned series of values. The Elman network has a layer of "context units" in addition to a standard feedforward network. By adjusting two parameters in the model and performing the cross validation, we demonstrated that the proposed model predicts the power consumption with the relative errors and the average errors in the range of 2%~5% and 3kWh~8kWh, respectively. To further confirm the experimental results, we performed two types of the cross validations designed for the time series data. We also support the validity of the model by analyzing the multi-step forecasting. We found that the prediction errors tend to be saturated although they increase as the prediction time step increases. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric and the gas energies.

• 한국수소및신에너지학회논문집
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• 제22권4호
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• pp.534-545
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• 2011

This paper describes the evaluation of kinetic parameters for pyrolysis and carbon char oxidation of residual oil. The non-isothermal pyrolysis of residual oil was carried out with TGA (Thermo-Gravimetric Analyzer) at heating rate of 2, 5, 10 and $20^{\circ}C/min$ up to $800^{\circ}C$ under N2 atmosphere. The first order and nth order pyrolysis models were used to fit the experimental data, and the nth order model was turned out to follow the experimental data more precisely than the first order model. For carbon char oxidation experiment, TGA and four heating rates used in pyrolysis experiment were also adapted. The kinetic parameters for the residual carbon char particle were obtained with three char oxidation model, that is, volume reaction, grain and random pore model. Among them, the random pore model described the char oxidation behaviour quite well, compared to other two models. The non-linear regression method was used to obtain kinetic parameters for both pyrolysis and carbon char oxidation of residual oil.

• Advances in Energy Research
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• 제6권2호
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• pp.131-143
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• 2019

Global Solar Radiation (GSR) is the key element for performance estimation of any Solar Power Plant (SPP). Its forecasting may help in estimation of power production from a SPP well in advance, and may also render help in optimal use of this power. Seasonal Auto-Regressive Moving Average (SARMA) and Artificial Neural Network (ANN) models are combined in order to develop a hybrid model (SARMA-ANN) conceiving the characteristics of both linear and non-linear prediction models. This developed model has been used for prediction of GSR at Gorakhpur, situated in the northern region of India. The proposed model is beneficial for the univariate forecasting. Along with this model, we have also used Auto-Regressive Moving Average (ARMA), SARMA, ANN based models for 1 - 6 day-ahead forecasting of GSR on hourly basis. It has been found that the proposed model presents least RMSE (Root Mean Square Error) and produces best forecasting results among all the models considered in the present study. As an application, the comparison between the forecasted one and the energy produced by the grid connected PV plant installed on the parking stands of the University shows the superiority of the proposed model.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제5B권4호
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• pp.374-381
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• 2005

The ability to provide quality power has become a significant issue in power systems. The main causes of poor power quality are harmonic currents, poor power factor, supply-voltage variations, etc. A technique of achieving both active current distortion compensation, power factor correction and also mitigating the supply-voltage variation (sag or swell) at the load side is presented in this paper. The operation and rating issues of the proposed Single-phase Unified Power Quality Conditioner are also highlighted. To reduce the total cost while simultaneously increasing the performance, the system is fully digitally controlled using the fixed-point TMS320F240 digital signal processor. The performances of the UPQC, which is composed by shunt and series PWM controlled-converters, have been verified on a laboratory prototype.

• Journal of Electrical Engineering and Technology
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• 제6권2호
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• pp.239-244
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• 2011

Industrial power distribution system includes many kinds of non-linear loads, which produce the harmonics during energy conversion transition. The single-tuned passive filter is widely used to absorb the harmonics and attenuate its undesirable effect in the distribution system. However, the passive filter might be severely stressed, and sometimes even damaged, due to the absorption of harmonics. There is voltage rise on the capacitor when the single-turned harmonic filter is applied. When the capacitor voltage rose above the allowable limit, the expected life of the capacitor will considerably deteriorate. On the other hand, the reactor can experience the spike voltage even if the voltage and current of the capacitor are within the allowable limit, and this accumulated voltage stress of the reactor causes its premature fault. In this paper, we analyzed and compared the harmonic voltage and current of the reactor and capacitor in a single-tuned harmonic filter through the EMTP software and verified them with the experimental results.

• 전력전자학회논문지
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• 제12권1호
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• pp.89-97
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• 2007

본 논문에서는 새로 개발된 전력품질 보상장치의 성능을 실험실에서 효과적으로 분석하기 위해 필요한 새로운 부하모의장치를 제안하였다. 제안하는 부하모의장치는 2대의 PWM 인버터가 직류 단을 공유한 구조로 선형과 비선형부하를 단일기기로 시험 가능하도록 설계되어 있다. 그리고 전력품질보상기의 하나인 능동전력필터와 연계시험을 수행하였다. 본 논문에서는 제안하는 부하모의장치와 능동전력필터의 연계 특성을 분석할 목적으로 PSCAD/EMTDC 소프트웨어를 이용하여 시뮬레이션 실시하였고 또한 실적용시 타당성을 검증할 목적으로 20kVA 용량의 부하모의장치와 10kVA용량의 능동전력필터를 제작하여 실험을 실시하였다. 시뮬레이션과 하드웨어 실험결과 제안하는 부하모의장치는 능동전력필터의 다양한 보상 능력 검증에 충분히 활용가능함을 알 수 있었다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2002년도 추계학술대회 논문집
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• pp.7-11
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• 2002

This paper proposes an APF(Active Power Filter) with WRIM(Wounded Rotor Induction Motor) controlled by sliding mode which can compensate harmonic currents generated in a power system. As non-linear loads increase gradually in industry fields, harmonic current generated In the electric power network system also increases. Harmonic current makes a power network current distorted and generates heat, vibration and noise In the power machinery, Many approaches have been applied to compensate harmonic currents generated in the power system. Among various control strategy, in this paper, a sliding mode controlled systems is designed and evaluated. This is a flywheel compensator based on secondary excitation of WRIM(wounded rotor induction motor) with SMC(sliding mode controller). The proposed system uses a flywheel as an energy storage device. The designed control scheme is verified through simulation.

• 전기전자학회논문지
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• 제22권2호
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• pp.460-475
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• 2018

In the variable-speed wind energy system, to achieve maximum power point tracking (MPPT), the wind turbine should run close to its optimal angular speed according to the wind speed. Non-linear control methods that consider the dynamic behavior of wind speed are generally used to provide maximum power and improved efficiency. In this perspective, the mechanical power is estimated using Kalman filter. And then, from the estimated mechanical power, the wind speed is estimated with Newton-Raphson method to achieve maximum power without anemometer. However, the blade shape and air density get changed with time and the generator efficiency is also degraded. This results in incorrect estimation of wind speed and MPPT. It causes not only the power loss but also incorrect wind resource assessment of site. In this paper, the adaptive maximum power point tracking control algorithm for wind turbine system based on the estimation of wind speed is proposed. The proposed method applies correction factor to wind turbine system to have accurate wind speed estimation for exact MPPT. The proposed method is validated with numerical simulations and the results show an improved performance.

• Nuclear Engineering and Technology
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• 제31권6호
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• pp.572-585
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• 1999

The characteristics of two-phase flow instability in a vertical boiling channel connecting with an unheated riser are investigated through the linear stability analysis model. Various two-phase flow models, including thermal non-equilibrium effects, are taken into account for establishing a physical model in the time domain. A classical approach to the frequency response method is adopted for the stability analysis by employing the D-partition method. The adequacy of the linear model is verified by evaluating experimental data at high quality conditions. It reveals that the flow-pattern-dependent drift velocity model enhances the prediction accuracy while the homogeneous equilibrium model shows the most conservative predictions. The characteristics of density wave oscillations under low-power and low-quality conditions are investigated by devising a simple model which accounts for the gravitational and frictional pressure losses along the channel. The necessary conditions for the occurrences of type-I instability and flow excursion are deduced from the one-dimensional D-partition analysis. The parametric effects of some design variables on low quality oscillations are also investigated.