• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.4
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• pp.403-407
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• 2023

In this paper, in order to investigate the efficiency of solar power generation system operation, we have studied operation cases such as generation amount, utilization rate, and generation time, and the following conclusions were obtained. The amount of power generation in 2017 was 1,311.48 MWh, and the amount of power generation in 2018 was 1,226.03 MWh. In 2021, 1,184.28 MWh was generated, and 90.30% compared to 2017, and the amount of power generation decreased by 1.94% every year. The deterioration of photovoltaic modules could be seen as one cause of the decrease in power generation. 1,977.74 MWh was generated in the spring, and 1,621.77 MWh was generated in the summer. In addition, 1,478.87 MWh was generated in the fall, and 1,110.55 MWh was generated in the winter, showing a lot of power generation in the order of spring, summer, fall, and winter. From 2017 to 2022, the seasonal utilization rate, daily power generation time, and daily power generation were investigated, and it could be seen that the spring utilization rate varies from 19.29% to 16.99%. It could be seen that the daily generation time in winter decreased from 2.67 hours to 2.13 hours, and in spring it generated longer than spring from 4.63 hours to 4.08 hours. In addition, the daily power generation in winter also decreased from 2.67 MWh to 2.13 MWh, and in spring it decreased from 4.63 MWh to 4.08 MWh, but it could be seen that it is more than in winter.

• Bulletin of the Korea Photovoltaic Society
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• v.4 no.2
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• pp.45-53
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• 2018

Natural gas demand for power generation continued to increase until 2013 due to the expansion of large-scale LNG power plants after the black-out of 2011. However, natural gas demand for power generation has decreased sharply due to the increase of nuclear power and coal power generation. But demand for power generation has increased again as energy policies have changed, such as reducing nuclear power and coal power plants, and abnormal high temperatures and cold waves have occurred. If the gas pipeline pressure can be properly maintained by predicting these fluctuations, it can contribute to enhancement of operation efficiency by minimizing the operation time of facilities required for production and supply. In this study, we have developed a regression model with daily power demand and base power generation capacity as explanatory variables considering characteristics by day of week. The model was constructed using data from January 2013 to December 2016, and it was confirmed that the error rate was 4.12% and the error rate in the 90th percentile was below 8.85%.

• ETRI Journal
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• v.37 no.2
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• pp.283-294
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• 2015

A model that precisely forecasts how much wind power is generated is critical for making decisions on power generation and infrastructure updates. Existing studies have estimated wind power from wind speed using forecasting models such as ANFIS, SMO, k-NN, and ANN. This study applies a projected clustering technique to identify wind power patterns of wind turbines; profiles the resulting characteristics; and defines hourly and daily power patterns using wind power data collected over a year-long period. A wind power pattern prediction stage uses a time interval feature that is essential for producing representative patterns through a projected clustering technique along with the existing temperature and wind direction from the classifier input. During this stage, this feature is applied to the wind speed, which is the most significant input of a forecasting model. As the test results show, nine hourly power patterns and seven daily power patterns are produced with respect to the Korean wind turbines used in this study. As a result of forecasting the hourly and daily power patterns using the temperature, wind direction, and time interval features for the wind speed, the ANFIS and SMO models show an excellent performance.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1709-1718
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• 2017

This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.10
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• pp.28-37
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• 2011

Though Korea has introduced CBP(Cost Based pool) power trading system since 2001, long-term Generation system planning has been executed by government for Cost minimization every 2 years. Until currently the model which is used for Generation system planning and best-mix only considers cost minimization and total yearly or quarterly electricity demand every year. In a view point of one day power supply operation, technical characteristics, like the ramp up/down rate of total generation system, minimum up/down time and GFRQ(Governor Free Response Quantity), are very important. this paper analyzes Optimal Fuel-Mix for 2022 Korea generation system satisfying these constraints of each fuel type and considering pump storage plants, construction cost and $CO_2$ emission charge Using MILP(Mixed Integer Linear Programming) method. Also the sensitivity analysis which follows in future power industry environmental change accomplished.

• New & Renewable Energy
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• v.10 no.2
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• pp.19-28
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• 2014

Wind power generation of 5 MW wind turbine was predicted by using wind measurement data from HeMOSU-1 which is at south west coast of Korea. Time histories of turbulent wind was generated from 10-min mean wind speed and then they were used as input to Bladed to estimated electric power. Those estimated powers are used in both polynominal regression and neural network training. They were compared with each other for daily production and yearly production. Effect of mean wind speed and turbulence intensity were quantitatively analyzed and discussed. This technique further can be used to assess lifetime power of wind turbine.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.178-183
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• 2012

The design of the integrated quench protection (QP) system for the high current superconducting magnet (SCM) has been fabricated and tested for the toroidal field (TF) coil system of the Korea Superconducting Tokamak Advanced Research (KSTAR) device. The QP system is capable of protecting the TF SCM, which consists of 16 identical coils serially connected with a stored energy of 495 MJ at the design operation level at 35.2 kA per turn. Given that the power supply for the TF coils can only ramp up and maintain the coil current, the design of the QP system includes two features. The first is a basic fast discharge function to protect the TF SCM by a dump resistor circuit with a 7 s time constant in case of coil quench event. The second is a slow discharge function with a time constant of 360 s for a daily TF discharge or for a stop demand from the tokamak control system. The QP system has been successfully tested up to 40 kA with a short circuit and up to 34 kA with TF SCM in the second campaign of KSTAR. This paper describes the characteristics of the TF QP systems and test results of the plasma experiment of KSTAR in 2009.

• Proceedings of the KIEE Conference
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• 2003.10b
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• pp.42-44
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• 2003

As the industry is developed, uses of various electric motor are increasing from general home to various fields of industry, and the kind becomes various daily. For these reasons, it is required to study the remote control and a package management about change of a speed drive system, the supervision of administration appliance by real time, and the collection and process data together using internet prevailed on industry whole. This paper deals with the development of a Web-Based remote control system for permanent magnet synchronous motor drives. The client/server system using TCP/IP protocols and DSP controller for remote control through internet and the Web interface that users can confirm data and state of PMSM(Permanent Magnet Synchronous Motor) is developed. This system is available for driving, braking, variable speed control and monitoring for PMSM in real time through administration program of Web-Based.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.6
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• pp.265-274
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• 2001

Recently, the operation of power systems has become more difficult because the peak demand load is increasing continuously and the daily load factor is getting worse and worse. Also, the consideration of deregulation and global environment in electric power industry is required. In order to overcome those problems, a study on the planning and operation in power systems of dispersed generating sources such as fuel cell systems, photovoltaic systems and wind power systems, has been performed energetically. This paper presents a method for determining an optimal operation strategy of dispersed co-generating sources, especially fuel cell generation systems, considering thermal supply as well as electric power supply. In other words, the optimal operation of those sources can be determined easily by the principle of equal incremental fuel cost and the thermal merit of those sources can be also evaluated quantitatively through Kuhn-Tucker's optimal conditions. In additions, an priority method using the comparison of total cost at the peak load time interval is presented in order ot select the optimal locations of those sources. The validity of the proposed algorithms is demonstrated using a model system.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.5
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• pp.207-217
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• 2018

Recently, the importance of energy demand management, particularly peak load control, has been increasing due to the policy changes of the Second Energy Basic Plan. Even though the installation of distributed generation systems such as Photovoltaic and energy storage systems (ESS) are encouraged, high initial installation costs make it difficult to expand their supply. In this study, the power consumption of a university building was measured in real time and the measured power consumption data was used to calculate the optimal installation capacity of the Photovoltaic and ESS, respectively. In order to calculate the optimal capacity, it is necessary to analyze the operation methods of the Photovoltaic and ESS while considering the KEPCO electricity billing system, power consumption patterns of the building, installation costs of the Photovoltaic and ESS, estimated savings on electric charges, and life time. In this study, the power consumption of the university building with a daily power consumption of approximately 200kWh and a peak power of approximately 20kW was measured per minute. An economic analysis conducted using these measured data showed that the optimal capacity was approximately 30kW for Photovoltaic and approximately 7kWh for ESS.