• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.179-185
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• 2005

This paper presents a novel circuit topology of a high efficiency single-phase power conditioner. This power conditioner is composed of time-sharing sinewave absolute pulse width modulated boost chopper with a bypass diode in the first power processing stage and time-sharing sinewave pulse width modulated full-bridge inverter in the second power processing stage operated by time-sharing dual mode pulse pattern control scheme. The unique operating principle of the two power processing stage with time-sharing dual mode sinewave modulation scheme is described with a design example. This paper proposes also a sinewave tracking voltage controlled soft switching PWM boost chopper with a passive auxiliary edge-resonant snubber. The new conceptual operating principle of this novel power conditioner related to new energy utilization system is presented and discussed through the experimental results.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.498-500
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• 2012

According to the climatic characteristics of the wind power output is difficult to predict and a severe strain due to a change in output has been very influential in the grid. Jeju Hangwon wind farm, many of the wind generator is installed in a wide area because it is not have this device that artificially Smoothing is needed. In addition, By the requirements of the power company active power supply / control and improve power system reliability and energy storage during the peak demand for electricity using the energy stored in the power supply is needed. In this paper, Unit 12 in Jeju Hangwon demonstrated 0.5MW PCS and energy storage system associated with the wind through the stabilization of output and the leveling of output and test results will be introduced.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.4
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• pp.505-510
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• 2009

In this paper, building energy analysis and energy cost of power stand up and demand control over the power proposed to reduce power demand. Through analysis of the load power demand special day were able to apply the pattern. In addition, the existing rate of change of load forecasting to reduce the large errors were not previously available data. And daily schedules and special day for considering the exponential smoothing methods were used. Previous year's special day and the previous day due to the uncertainty of the load and the model components were considered. The maximum demand power control simulation using the fuzzy control of power does not exceed the contract. Through simulation, the benefits of the proposed energy-saving techniques were demonstrated.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.319-322
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• 2006

This paper deals with the HVDC system fault analysis and the sound noise analysis. In this paper, the reasons of the audible noise and vibration were analyzed, the fault waveform were analyzed using DTR (Digital Transient Recorder). Finally, using the fault current waveform and the vibration equation, the reason of crack of smoothing reactor support is estimated.

• Proceedings of the KIPE Conference
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• 2016.11a
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• pp.206-207
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• 2016

The intermittent characteristics of wind power (WP) may have negative effect on grid stability, especially in weak grid. WP fluctuation rate can be reduced by using energy storage system (ESS) through charging and discharging. The operation of ESS will decide its losses and lifetime of batteries. From this point, this paper proposes WP smoothing control by using short-term average of WP. In this case, the ESS will only operate at high WP fluctuation rate. Then, the output power of ESS will be estimated by short-term average value. The effectiveness of proposed method will be verified by comparing with conventional method. The simulation results will be carried out by using Matlab program.

• Journal of electromagnetic engineering and science
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• v.4 no.1
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• pp.23-29
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• 2004

In this paper we analyze convergence constraints and time constant of IT-LMS algorithm and derive a method of making it's time constant independent of signal power by using input variance estimation. The method for estimating the input variance is to use a single-pole low-pass filter(LPF) with common smoothing parameter value, θ. The estimator is with narrow bandwidth for large θ but with wide bandwidth for small θ. This small θ gives long term average estimation(low frequency) of the fluctuating input variance well as short term variations (high frequency) of the input power. In our simulations of multipath communication channel equalization environments, the method with large θ has shown not as much improved convergence speed as the speed of the original IT-LMS algorithm. The proposed method with small θ=0.01 reach its minimum MSE in 100 samples whereas the IT-LMS converges in 200 samples. This shows the proposed, tap-power normalized IT-LMS algorithm can be applied more effectively to digital wireless communication systems.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.134-135
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• 2012

This paper analyzes the characteristics of the power system of Jeju island in 2014, which has wind farms with the support of BESSs (Battery Energy Storage Systems). In the simulation, the electrical loads are predicted based on Korea Power Exchange's data and the wind turbines are considered with new installed plans within 2014. The situation that some wind farms are forced to disconnect from the grid instantaneously is considered. The BESSs are controlled by using SOC (State of Charge) and power smoothing control algorithm. The simulation results show the effectiveness of the proposed method.

• Journal of the Korean Solar Energy Society
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• v.38 no.1
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• pp.13-24
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• 2018

As part of the "Carbon free Island 2030" policy, the local government of Jeju Island is currently working to reduce carbon through renewable energy supply. However, renewable energy is difficult to predict due to intermittent characteristics. If the share of renewable energy increase, it is difficult to plan of supply of electricity to grid due to that characteristic of renewable. In this paper analyze the fluctuation rate and the capacity credit of wind power and PV to find out how much wind power and PV contribute to supply of electricity of power system in Jeju. As a result mean value of variation rate of wind power and PV is about 3%, 5% and capacity credit is about 10% and 2% respectively.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.481-482
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• 2013

This paper presents the method to determine the battery capacity for controlling the wind power with BESS for stabilizing the output of HanGeong wind farm in accordance with grid codes for distributed generators in Jeju Island. To find appropriate capacity of BESS, three kinds of simulations are carried out : There are focused on smoothing control, the frequency fluctuation and the renewable energy resources standards, respectively. As the simulation result, maximum C-rates of BESS for the wind farm are calculated as 2C, 5C and 2C that are for each method and battery capacities have 25%, 20% and 10% of total capacity of HanGeong wind farm. Finally, simulations for this paper are carried out by using PSCAD/EMTDC.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.63-75
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• 2002

To improve the efficiency of the electric power generation, monthly maximum electric power consumptions for a next one year should be forecasted in advance and used as the fundamental input to the yearly electric power-generating master plan, which has a greatly influence upon relevant sub-plans successively. In this paper, we analyze the past 22-year hourly maximum electric load data available from KEPCO(Korea Electric Power Corporation) and select necessary data from the raw data for our model in order to reflect more recent trends and seasonal components, which hopefully result in a better forecasting model in terms of forecasted errors. After analyzing the selected data, we recommend to KEPCO the Winters' multiplicative model with decomposition and exponential smoothing technique among many candidate forecasting models and provide forecasts for the electric power consumptions and their 95% confidence intervals up to December of 1999. It turns out that the relative errors of our forecasts over the twelve actual load data are ranged between 0.1% and 6.6% and that the average relative error is only 3.3%. These results indicate that our model, which was accepted as the first statistical forecasting model for monthly maximum power consumption, is very suitable to KEPCO.