• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1110-1122
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• 2018

This paper proposes an alternative method to evaluate the effect of wind power to the power system stability with small disturbance. Alternatively, available techniques for stability analysis of a power system based on deterministic methods are less accurate for high penetration of wind power. Numerical simulations of random behaviors are computationally expensive. A stochastic stability index (SSI) is proposed for the power system stability evaluation based on the theory of stochastic stability and energy function, specifically the stochastic derivative of the relative well-defined energy function and the critical energy. The SSI is implemented on the modified nine-bus system including wind turbines under different conditions. A doubly-fed induction generator (DFIG) wind turbine is characterized and modeled using measured wind data from several sites in Thailand. Each of the obtained wind power data is analyzed. The wind power effect is modeled considering the aggregated effect of wind turbines. With the proposed method, the system behavior is properly predicted and the stability is quantitatively evaluated with less computational effort compared with conventional numerical simulation methods.

• Journal of IKEEE
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• v.22 no.3
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• pp.829-835
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• 2018

Recently, studies have been actively conducted to reduce spare power that is unnecessarily generated or wasted in existing power systems and to improve energy use efficiency. In this study, smart meter, which is one of the element technologies of smart grid, is implemented to improve the efficiency of energy use by controlling power of electric devices, and predicting trends of energy usage based on deep learning. We propose and develop an algorithm that controls the power of the electric devices by comparing the predicted power consumption with the real-time power consumption. To verify the performance of the proposed smart meter based on the deep running, we constructed the actual power consumption environment and obtained the power usage data in real time, and predicted the power consumption based on the deep learning model. We confirmed that the unnecessary power consumption can be reduced and the energy use efficiency increases through the proposed deep learning-based smart meter.

• Journal of the Korean Society for Railway
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• v.20 no.5
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• pp.595-601
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• 2017

Due to the electrification of railways, fault at the traction line is increasing year by year. So importance of the fault locator is growing higher. Nevertheless at the field traction line, it is difficult to locate accurate fault point due to various conditions. In this paper railway feeding system current loop equation was simplified and generalized though measured data. And substation, train power data were measured under synchronized condition. Finally catenary impedance was predicted through generalized equation. Also simulation model was designed to figure out the effect of load current for train at same location. Train current was changed from min to max range and catenary impedance was compared at same location. Finally, power measurement was performed in the field at train and substation simultaneously and catenary system impedance was predicted and calculated. Through this method catenary impedance can be measured more easily and continuously compared to the past method.

• Journal of KIBIM
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• v.9 no.3
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• pp.19-29
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• 2019

Currently, BIPV (Building Integrated Photovoltaic) design technology lacks analysis function at the planning stage, and there is a lack of understanding and reliability of BIPV design method and system for building designers. To design and consider various building integrated solar design alternatives, the color of building integrated solar is often monotonous or does not match the design direction of the building. In this study, architectural designers can select various color modules in the planning and design process of the building and analyze the characteristics of color module solar cells and compare and analyze the actual solar radiation and predicted solar radiation in Republic ofKorea Seoul to reduce the confusion of design methods. By building a BIM design integrated system that can prove the quality of the building and analyze the shading analysis and power generation performance architecturally, it can improve the reliability of color module solar cell applicability that can express aesthetics in buildings and the predicted solar power generation capacity of each region. In the initial design stage, based on the empirical data of the BIPV system, it is possible to analyze the power generation performance for each installation angle and installation direction by analyzing the surrounding environment and the installation area, and accurately determine the appropriateness of the design accordingly.

• 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.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1566-1577
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• 2018

This paper presents a stability analysis of AC-DC power system feeding a speed controlled DC motor in which this load behaves as a constant power load (CPL). A CPL can significantly degrade power system stability margin. Hence, the stability analysis is very important. The DQ and generalized state-space averaging methods are used to derive the mathematical model suitable for stability issues. The paper analyzes the stability of power systems for both speed control natural frequency and DC-link parameter variations and takes into account controlled speed motor dynamics. However, accurate DC-link filter and DC motor parameters are very important for the stability study of practical systems. According to the measurement errors and a large variation in a DC-link capacitor value, the system identification is needed to provide the accurate parameters. Therefore, the paper also presents the identification of system parameters using the adaptive Tabu search technique. The stability margins can be then predicted via the eigenvalue theorem with the resulting dynamic model. The intensive time-domain simulations and experimental results are used to support the theoretical results.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.15 no.3
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• pp.281-299
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• 2017

The inventory management of radionuclides is essential for the safe management of disposal facilities. In this study, we compared the activity of dry active waste predicted using the generated waste data and that measured for the accepted waste in the disposal facility. For very low level waste, the measured activity was higher than the predicted activity for $^{137}CS$, $^{90}Sr$, $^{99}Tc$ and $^{129}I$. In low level waste, the predicted activity was higher than the measured activity for all radionuclides. We also evaluated the variation in the predicted quantity and total activity of each level of dry active waste through a sensitivity analysis on a scaling factor. This result will contribute to the construction of a Safety Case and safe operation of disposal facilities.

• 한국연소학회:학술대회논문집
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• 2006.10a
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• pp.187-195
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• 2006

In this work, we introduce a newly constructed arc-jet device of 150 kW input power. The design of this device is a Huels type with a narrow downstream electrode. General features of this device are first described. From the measured values of electrical power input, heat discharged into cooling water, gas flow rate, and settling chamber pressure, average enthalpy was determined using the heat balance and sonic throat methods. Using the settling chamber pressure and average enthalpy values, the flow properties in the nozzle and the heat transfer rate to the stagnation point of a blunt body are calculated accounting for thermochemical nonequilibrium. The envelope of enthalpy, pressure, degree of dissociation, and heat transfer rate are presented. Stagnation temperature is predicted to be between 4630 to 6050 $^{\circ}K$, and the stagnation point heat transfer rate is predicted to be between 175 and 318 W/$cm^{2}$ for a blunt body of 3 mm nose radius. Degree of dissociation in the stagnation region of the blunt body exceeds 30%.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.375-383
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• 2008

This paper deals with reduction and analysis of cogging torque for permanent magnet synchronous generators with multi-pole rotor for wind power applications. Open-circuit field solutions are derived using a magnetic vector potential and a two-dimensional (2-d) polar coordinate systems. On the basis of derived open-circuit field solutions and 2-d permeance functions, we also derive open-circuit field solutions considering stator slotting effects. By using open-circuit field solutions considering stator slotting effects and energy variation methods, this paper analytically predicts the cogging torque considering skew effects. All analytical results are shown in good agreement with those obtained from finite element (FE) analyses. In order to reduce the cogging torque, by predicting the variation of the cogging torque according to pole arc/pitch ratio using analytical and FE methods, pole arc/pitch ratio which makes the cogging torque minimum are determined. However, we confirm that measured value for cogging torque of the PMG with determined pole arc/pitch ratio is twice higher than predicted value. Therefore, the reason for an error between measured and predicted cogging torque is discussed in terms of a shape of PMs and is proved experimentally.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.6
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• pp.427-437
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• 1997

Complex terrain which is rather typical topographic character in Korea would greatly influence the dispersion of air pollutant. In this study, we investigated how the complex terrain in the vicinity of the coal-fired plant affects the air dispersion modeling results by using several US EPA models: SCREEN, CTSCREEN, ISCLT3, ISCST3, and RTDM. Screening analysis was followed by long-term analysis, and the plume movement over the terrain was precisely tracked for selected cases. Screening analysis revealed that the highest concentration of sulfur dioxide occurs at the downwind distance of 1.3 km under the unstable conditions with weak winds. However, this highest level of $SO_2$ could be raised by 4 times even in the presence of a hill of 170 m at a distance of 2 to 3 km. Seasonal and annual average concentrations predicted with the ISCLT3, ISCST3, and RTDM models showed a rapid incrase of $SO_2$ levels in front of the high mountains which are located more than 15 km away fromt the source. The highest concentrations predicted with ISCST3 were significantly higher than those with ISCLT3 and RTDM mainly because ISCST3 chooses simple-terrain model calculations for receptors between stack height and plume height. Although the highest levels under the stable conditions were usually found in the areas beyond 15 km or more, their absolute values were not so high due to enough dispersion effects between the source and the receptors.