• Journal of Soil and Groundwater Environment
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• v.23 no.6
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• pp.82-89
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• 2018

The objective of this study is to evaluate efficiencies of chemical suppressants for control of fugitive dust in ash pond of thermal power plant. In this study, $MgCl_2$, PAM (polyacrylamide), and PVA (poly vinyl alcohol) that are generally applied to suppression of fugitive dust generated from unpaved road, coal mining, storage piles and etc, were employed as chemical dust suppressants. The coal ash (coal combustion residuals) were sampled from the ash pond of Yeongheung power division in Incheon, South Korea. The characterization of the sample including particle size distribution, pH, $pH_{PZC}$ and pore volume as well as XRF analysis were carried out. The suppressant treated-samples were investigated with the wind tunnel experiments to estimate and compare the effect of suppressants on stabilization of the surface of coal ash samples. According to the results, the stability of suppressant-treated samples were significantly improved compared to water-treated samples. Among the three kinds of suppressants, PAM and PVA showed higher efficiencies and cost saving than $MgCl_2$.

• Journal of IKEEE
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• v.23 no.1
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• pp.134-142
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• 2019

As the development of internet of energy (IoE) technologies and spread of various electronic devices have diversified patterns of energy consumption, the reliability of demand prediction has decreased, causing problems in optimization of power generation and stabilization of power supply. In this study, we propose a deep learning method, 1-Dimention-Convolution and Bidirectional Long Short-Term Memory (1D-ConvBLSTM), that combines a convolution neural network (CNN) and a Bidirectional Long Short-Term Memory(BLSTM) for highly reliable demand forecasting by effectively extracting the energy consumption pattern. In experimental results, the demand is predicted with the proposed deep learning method for various number of learning iterations and feature maps, and it is verified that the test data is predicted with a small number of iterations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.199-203
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• 2015

With the development of industry these days, the demand for electric power increases and the larger capacity for power transfer is required. The scales of facilities should become larger; and the relative systems are required to operate with a higher degree of reliability. Therefore, stabilization of electric power systems is an important issue. The high degree of reliability required in the process of production and supply of electric power is an essential part of industrial society. Accident such as blackouts causes a hugh amount of economic losses to the high-tech industrial society dependent upon electric power. This paper is about the basic study of the relations between the load current and lifetime of power cables in operation. In order to do the research, we installed a current transformer and an equipment for measuring temperature at the 6.6. kV cables in operation. The two equipments have been installed on the cable systems in operation for the last 20 years. Since the insulation resistance of most of the cables showed the value larger than the threshold, it was not easy to tell the remaining lifetime of cables. The load current of the cables was almost constant. The surrunding temperature was $15{\sim}25^{\circ}C$, little variation of temperature values.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.3
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• pp.144-151
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• 2005

This paper presents a forecasting technique of the short-term marginal price (SMP) using an Artificial Neural Network (ANN). The SW forecasting is a very important element in an electricity market for the optimal biddings of market participants as well as for market stabilization of regulatory bodies. Input data are organized in two different approaches, time-axis and day-axis approaches, and the resulting patterns are used to train the ANN. Performances of the two approaches are compared and the better estimate is selected by a composition rule to forecast the SMP. By combining the two approaches, the proposed composition technique reflects the characteristics of hourly, daily and seasonal variations, as well as the condition of sudden changes in the spot market, and thus improves the accuracy of forecasting. The proposed method is applied to the historical real-world data from the Korea Power Exchange (KPX) to verify the effectiveness of the technique.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.30 no.6
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• pp.376-380
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• 2017

In this paper, we prepared a metal alloy resistor with stable thermal electro motive force (thermal EMF) as well as a low temperature coefficient of resistance (TCR) by adjusting the manganese proportion from 3 to 12 wt% in the Cu-Mn-Ni alloy. Composition of the fabricated metal alloy was investigated using energy dispersive X-ray (EDX) analysis. The TCR of each sample was measured as 44.56, 40.54, 35.60, and 31.56 ppm for Cu-3Mn-2Ni, Cu-5Mn-2Ni, Cu-10Mn-2Ni, and Cu-12Mn-2Ni, respectively. All the resistor samples were available for the F grade (${\pm}1%$ of the allowable error of resistance) high-precision resistor. All the samples satisfied the baseline of high thermal EMF (under 3 mV at $60^{\circ}C$); however, Cu-3Mn-2Ni and Cu-5Mn-2Ni satisfied the baseline of low thermal EMF (under 0.3 mV at $25^{\circ}C$). We were thus able to design and fabricate the metal alloy resistor of Cu-3Mn-2Ni and Cu-5Mn-2Ni to have low TCR and stable thermal EMF at the same time.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.601-611
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• 2017

This paper proposes a simultaneous control of frequency deviation and electric vehicles (EVs) battery state of charge (SOC) using load frequency control (LFC) and EV controllers. In order to provide both frequency stabilization and SOC schedule near optimal performance within the whole operating regions, a multiple-input multiple-output model predictive control (MIMO-MPC) is employed for the coordination of LFC and EV controllers. The MIMO-MPC is an effective model-based prediction which calculates future control signals by an optimization of quadratic programming based on the plant model, past manipulate, measured disturbance, and control signals. By optimizing the input and output weights of the MIMO-MPC using particle swarm optimization (PSO), the optimal MIMO-MPC for simultaneous control of the LFC and EVs, is able to stabilize the frequency fluctuation and maintain the desired battery SOC at the certain time, effectively. Simulation study in a two-area interconnected power system with wind farms shows the effectiveness of the proposed MIMO-MPC over the proportional integral (PI) controller and the decentralized vehicle to grid control (DVC) controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.2
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• pp.339-346
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• 1999

A RF receiver section for INMARSAT-C external mounting unit was designed, fabricated and evaluated. Using a INA-03184, the high gain amplifier consists of matched amplifier type. Active bias circuitry can be used to provide temperature stability without requiring the large voltage drop or relatively high-dissipated power needed with a bias stabilization resistor. The bandpass filter was used to reduce a spurious level. As a result, the characteristics of the receiver section implemented here show 60 dB in gain, 44.83 dBc in a spurious level. The voltage standing wave ratios(VSWR)of input output port are less than 1.8:1, respectively.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.177-178
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• 2015

Sediments play a major role in determining pollution pattern in aquatic systems and reflecting the pollutant deposition. In the present study analysis the depth effect of organic pollutants and heavy metals using slow release biostimulant ball (BSB) in coastal sediment. BSB size fixed at 3cm, depth varied from 0cm to 10cm depth and 1 and 3 month interval period was carried out for the study. The organic pollutants of chemical oxygen demand, total solids and volatile solids were significantly changed at the surface sediment (0cm)in 1 month and 3 month interval time using BSB. In contrast, sediment depth increase upto 10cm the reduction percentage decrease like to control. Vertical distribution of heavy metals are not consistent from the surface layer toward the bottom layers. Heavy metals fractions were significantly changes, the exchangeable fraction was reduced and other organic and residual fractions were stabilized percentage are increased. This finding concluded BSB is effective for reduce organic pollutants, heavy metals stabilization from the contaminated sediment.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.601_602
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• 2009

Superconducting Magnetic Energy Storage (SMES) system is one of the key technologies to overcome the voltage sag, swell, interruption and frequency fluctuation by fast response speed of current charge and discharge. In order to evaluate the characteristics of over mega joule class grid connected High Temperature Superconducting (HTS) SMES system, the authors proposed an algorithm by which the SMES coil could be connected to the Real Time Digital Simulator (RTDS). Using the proposed algorithm, users can perform the simulation of voltage sag and frequency stabilization with a real SMES coil in real time and easily change the capacity of SMES system as much as they need. To demonstrate the algorithm, real charge and discharge circuit and active load were manufactured and experimented. The results show that the current from real system was well amplified and applied to the current source of simulation circuit in real time.

• Progress in Superconductivity and Cryogenics
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• v.7 no.4
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• pp.24-27
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• 2005

Development of a 600 kJ class Superconducting Magnetic Energy Storage (SMES) system is being in progress by Korea Electrotechnology Research Institute(KERI). High temperature superconducting (HTS) wires are going to be used for the windings for the SMES system is presented in this paper. We considered BSCCO-2223 wire for the HTS windings and the operating temperature of the winding was decided to be 20 K which will be accomplished by conduction cooling method using cyro-coolers. Auto-Tuning Niching Genetic Algorithm was adopted for an optimization method of the HTS magnets in the SMES system. The objective function of the optimal process was minimizing total amount of the HTS wire. As a result, we obtained output parameters for optimization design of 600 kJ class SMES under several constrained conditions. These HTS windings are going to be applied to the SMES system whose purpose is stabilization of the power grid.