Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers

풍속과 풍력터빈 용량을 고려한 대용량 해상풍력발전단지의 경제성 평가에 관한 연구 Economic Evaluation of Large-Scale Offshore Wind Farm considering Wind Speed and Wind Turbine Capacity

문원식(Won-Sik Moon) ; 신중우(Joong-Woo Shin) ; 윤광훈(Kwang-Hoon Yoon)

This study is conducted to evaluate the economic feasibility of large-scale offshore wind farms based on mean wind speed and wind turbine capacity. The evaluation is carried out on two 400MW large-scale wind farms each consisting of 5MW wind turbine and 8MW wind turbine, by analyzing the capacity factor and levelized cost of energy due to changes in mean wind speed. Capacity factor is adopted as a measurement to analyze the changes in production amount due to variations in wind turbines’ capacities, despite different wind farms having the same capacity. Levelized cost of energy is calculated as the ratio of the annual acquisition cost to the annual energy production. To derive the annual acquisition cost, the study proposes a capital expenditure and operational cost model. A case study is conducted on a developed offshore wind farm scheduled to be operational in 2022 to eliminate variations in capital expenditure cost due to optimization of topology for internal power grid. Through the case study, the impact of wind speed and wind turbine capacity on the economic feasibility of offshore wind farms is analyzed.

태양광 발전의 출력 예측 불확실성 및 간헐성 보상 방법에 관한 연구 A Study on Photovoltaic Output Prediction Uncertainty and Intermittency Compensation Method

박우근(Woo-Geun Park) ; 김지수(Ji-Soo Kim) ; 임승민(Seung-Min Lim) ; 김철환(Chul-Hwan Kim)

Variable Renewable Energy(VRE) is impossible to maintain stable output due to uncertainty and intermittency. In this paper, Photovoltaic(PV) output is predicted through deep learning prediction technology and compared with the actual PV output. The data used as the input of the deep learning prediction model was partially selected through correlation analysis to reduce overfitting and to have high prediction performance. A Hyperparameter optimization model was used in several deep learning prediction models and the Recurrent Neural Network(RNN) prediction model was selected after comparing the performances. The difference between Predicted PV output and actual PV is compensated using Battery Energy Storage System(BESS). Moreover, the BESS capacity is calculated and the BESS State of Charge (SoC) range profile is observed.

국내 하루전 전력시장 개편의 내용 및 의의 Details and implications of reformed Korean day-ahead electricity market

옥기열(Ki-Youl Ok) ; 이성우(SungWoo Lee) ; 박민수(MinSu Park) ; 주안진(Anziin Ju) ; 조성봉(Sung-Bong Cho)

Korean government has established plans to restructure its electricity market in the era of energy transition. As a part of the plan, Korea Power Exchange has reformed day-ahead market as a first step of its two-stage market reform roadmap. Current day-ahead market using unconstrained schedule does not consider operating reserve requirements, transmission congestion and must-run generations. For these reasons, most of the real-time generations are different from those of day-ahead contracts and system marginal price determined in the day-ahead market does not reflect various system conditions. Deliverable day-ahead contracts reflecting actual system conditions are a prerequisite for the introduction of real-time balancing market. Improved price signal through system marginal price reflecting physical system conditions and newly established frequency reserve price will attract relevant resources for system flexibility. Market simulation results show improved performance of price signal without increasing consumer charges significantly.

한류기 보호 MTDC시스템에 과전류 계전기적용을 위한 전압기울기 방향 보정 연구 Study on Directional Correction using Voltage Slope for Application of Over-Current Relay in Multi Terminal DC System with Fault Current Limiter’s Protection

최상재(Sangjae Choi) ; 임성훈(Sung-Hun Lim)

In the DC system, the fault current is quite fast and rises significantly due to capacitor discharge. Due to this, DC fault conditions must be cut off more quickly and accurately than AC. However, DCCB is more complicated to operate and more expensive than AC system circuit breaker. Therefore, it is necessary to introduce a superconducting fault current limiter, and the trip delay may occur in the overcurrent relay due to the introduction of the superconducting fault current limiter. To prevent this, a correction algorithm is needed. In this paper, an algorithm that considers the voltage slope and the direction of the current is applied to effectively limit the fault current through a superconducting fault current limiter, and a method to prevent the malfunction of the circuit breaker.

역률의 변화를 이용한 유도전동기의 소프트 기동 특성 해석 Soft Start Characteristic Analysis of Induction Motor Using Change in Power Factor

김종겸(Jong-Gyeum Kim)

Induction motors are the most widely used for loads requiring rotational force because they are self-starting, very simple construction, stronger and easier to maintain than other motors. In spite of such various advantages, a large current is generated at the time of direct-on line starting, and a voltage drop is generated. Since the voltage drop may be adversely affected by other facilities connected to the same distribution system, a start-up method is required to reduce the voltage drop as much as possible. The induction motor can select several starting methods by the capacity. Recently, a soft-start starting method using thyristors has been introduced. Induction motors have a lower power factor because the proportion of reactive power for magnetization at startup is relatively higher than the active power, but as the rotation speed increases, the power factor is gradually increased if the active power is higher than the reactive power. That is, when the power factor becomes high in a low state, the phase angle is developed from a high value to a low value. When the change of this phase angle is used at the firing angle of the thyristor, the operation change of the motor can be used as it is to reduce the starting current. In order to reduce the starting current and lower the voltage drop, the power factor change of the induction motor varying from starting to normal speed during operation is used at the firing angle of the thyristor. As a result of analysis using the power factor change of the motor as the firing angle, it is confirmed that the voltage drop is extremely effectively reduced by the reduction of the starting current.

파라미터 학습을 통한 프리미엄 고효율 유도 전동기의 다중 목적 최적 설계 Multi-Objective Optimum Design of Premium High Efficiency Induction Motor Using Parameter Learning

김민석(Min-Seok Kim) ; 김창업(Chang-Eob Kim)

In this paper, the optimum design of a 3.7kW premium high-efficiency induction motor was proposed for reducing the cost using a low-grade iron core while maintaining the efficiency of the motor using a high-grade iron core. Global Response Surface Method(GRSM), one of the multi-objective optimization techniques, was used to satisfy the multi-objective optimization such as complex design problems with cost and production ranges. And GRSM performs the parallel analysis for accurate and efficient optimization search, including local and global search functions. In addition, the commercial optimization program HyperStudy and the electromagnetic FEM solver were used for the characteristic analysis of the motor. As a result of optimization, the price of optimum model was decreased 8% compared with the base model. The reliability of the proposed method was verified by the experiment.

스마트 인버터의 주파수-유효전력 제어를 위한 하드웨어 시뮬레이터 Hardware Simulator for Frequency-Watt Control in Smart Inverters

이선행(Sun-Hang Lee) ; 조성준(Sungjoon Cho) ; 이교범(Kyo-Beum Lee)

This paper presents a hardware simulator for a Frequency-Watt control in smart inverters. The power plant generator rotates at a constant speed, which is related to the frequency of the grid. The frequency of the grid is determined by the balance of power generation and power consumption. In addition, frequency fluctuations occur due to sudden changes in load or accidents. To reduce fluctuations and improve stability of grid system, the Frequency-Watt control in smart inverters was introduced. The PLL (Phase Locked Loop) control in various situations is important for grid-connected inverter to detect grid frequency. The real power limit of the smart inverter is controlled by the detected frequency to support grid stabilization. In this paper, the development of a hardware simulator for the Frequency-Watt control in smart inverters using three-level topology is introduced. The validity and performance of the proposed hardware simulator and its control strategies are demonstrated by various experimental results.

유한상태기계를 이용한 소프트스위칭 계통연계형 인버터 제어 알고리즘에 관한 연구 Study on Finite State Machine Modeling of Trajectory Control Algorithm for Soft-Switching Grid-tied Inverter

백승훈(Seunghun Baek)

This paper present a finite state machine (FSM) model of a trajectory control algorithm for single-stage soft-switching grid-tied inverters with a fast dynamic response. A Grid-tied inverter for single photovoltaic (PV) panel that interfaces distributed energy sources and grid is targeted as an application in this paper. The single-stage soft-switching operation is implemented to reduce switching losses using a resonance filter between two switching bridges. The proposed FSM model effectively selects the switching state of a converter in complex DC / AC bidirectional operations with active/reactive power control. The control scheme directly limits the amount of energy in the resonant circuit and provides a fast transient response with minimal switching actions in all quadrants on ??? ??? plane. The proposed model is digitally implemented on a TI digital signal processor and verified by Hardware-In-the-Loop (HIL) tests.

양면 태양광 모듈 발전시스템의 실용적 현장 적용에 관한 연구 A Study on the Practical Field Application of Bifacial Module Power Generation System

박흔명(Heun-Myeong Park) ; 조재철(Jae-Cheol Cho)

In this paper, bifacial modules(6.08[kW]) with the same amount of power production were installed in PV power plants with monofacial modules (6.12[kW]) to analyze the power production patterns of monofacial modules and bifacial modules. There was no significant change in rear irradiance due to changes in front irradiance, and both modules produced power proportional to solar irradiance. Average power conversion rate of bifacial modules was 8.07[%] higher than monofacial modules. Power production(power conversion rate and energy conversion rate) increased when the floor reflection surface area was made with, silver foil hemisphere, and foil vinyl. Except when shading film is installed. Power production (power conversion rate and energy conversion rate) increased when floor reflection area was made of shading film, silver foil hemispheric vinyl, and silver foil vinyl. Except when covering the shading net. The power conversion rate of silver foil hemispheric vinyl, which can be applied to large solar power plant sites, rose 0.46[%], and the power conversion rate rose 1.58[%] when silver foil vinyl was installed. However, considering the difference between the area of silver foil hemispheric vinyl(1.77[m2 ]) and silver foil vinyl(16[m2 ]), the power conversion rate of silver foil hemispheric vinyl will be higher if installed in the same area.

분할된 3K 금속도금 탄소섬유 선의 열적, 전자기적 특성 Thermal and Electromagnetic Characteristics on Segmented 3K Metal-coated Carbon Fiber Wire

이기택(Gi Taek Lee) ; 조용기(Yong KI Cho) ; 김원석(Won Seok Kim) ; 김지연(Ji Yeon Kim)

Metal such as a nickel-chrome and Ag-coated copper wire has been used to heating wire. The metal-heating wire, however, is used to be causing of risk of fire due to disconnection by low mechanical properties, low heat efficiency, and low emissivity. In this study, metal coated carbon fibers (MCFs) is replaced to solve the problems that the metal-heating wire has. MCFs show excellent heating properties and mechanical strengths. The 3K MCFs which are divided from 12K MCFs are linearized as a function of the number of twists and sizing content with a stranding machine to suppress fluff, electrical resistance and diameter. The heating properties and electromagnetic of linearized 3K MCFs are evaluated.

스펙트로그램 등고선 신경망의 타당성 검증 ? 변압기의 돌입전류에 적용 Validation of the Validity of Spectrogram Contour Neural Network ? Applied to Inrush Current Classification of Transformer

김청훈(Chunghun Kim) ; 임거수(Geosu Yim)

In this study, in order to effectively analyze the state of the devices using one-dimensional time-series data generated from industrial devices, a new learning method was designed based on Short-Time Fourier Transform (STFT), and its validity was verified. The proposed learning method is a method of extracting contour lines with a preset threshold before applying a 2D spectrogram image to a deep neural network. As such, the contour transformation of the spectrogram image of the frequency distribution is to extract the characteristics of the frequency, so it will be effective in improving the performance of learning. In order to verify the validity of the proposed contour neural network, Learning was conducted as a pre-study, using the time series values of the chaotic system with nonlinear high-dimensional characteristics as a data set, and it was confirmed that the learning rate rapidly increased at a specific contour line.

심층학습 기법을 이용한 원핫 안구 질환 진단 프레임워크 Automated One-hot Eye Diseases Diagnostic Framework using Deep-Learning Techniques

김지연(Jiyeon Kim) ; 한용섭(Yongseop Han) ; 이웅섭(Wongsup Lee) ; 강태신(Taeseen Kang) ; 이성진(Seongjin Lee) ; 김경훈(KyongHoon Kim) ; 이영섭(Yeongseop Lee) ; 김진현(Jinhyun Kim)

Multiple OCT images from the same patient for ophthalmic disease classification, such as AMD, DME, and Drusen, often conflict with each other in classification. The human doctor makes an experience-based medical decision for inconsistent OCT images, but no neural-network-based approach has been proposed to solve the same problem so far. This paper presents a new machine-learning-based framework that makes the comprehensive one-hot decision on AMD, DME, and Drusen, just like human doctors. In this study, we present a two-step deep machine learning method: In the first step, a classical Deep CNN along with transfer learning is used to make an ophthalmic diagnosis for a single OCT image. In the second step, a new framework, we propose, consisting of several supervised deep machine learning methods makes a comprehensive one-hot decision on eye disease from multiple OCT images. In this framework, we developed an AI model that can make comprehensive judgments from inconsistent results obtained from the same patient. Consequently, we could achieve 94% classification accuracy compared to the human doctor classification.

방사상 배전계통에서의 Fuse-Saving Scheme을 고려한 적응형 Recloser에 관한 연구 A Study on Adaptive Recloser Considering Fuse-Saving Scheme in Radial Distribution System

신광수(Gwang-Su Shin) ; 송진솔(Ji-Soo Kim) ; 김호영(Jin-Sol Song) ; 김철환(Ho-Young Kim)

The distribution system provides power to a large area, so the supply distance is short, but the system structure is complicated by many branch lines. In addition, changes in the system structure are frequent due to changes in load or restoration and facility inspection. Nevertheless, high quality and reliable power supply are important to customers because the distribution system is located adjacent to them. Protective coordination is very important for a reliable power supply. The distribution system, which is mostly temporary, uses protective coordination using Recloser and Fuse extensively. However, in terms of adaptive protective coordination, it is not easy for Fuse to change its capacity according to changes in the environment of the distribution system. Therefore, we propose to consider adaptive protective coordination with a relatively easy-to-setting Recloser. In this paper, we study adaptive Recloser setting considering the Fuse-saving scheme, focusing on protective coordination between Recloser and Fuse in the distribution system

PSCAD/EMTDC를 활용한 초전도 소자의 유무에 따른 기계식 DC 차단기 분석 Analysis on a mechanical DC circuit breaker depending on the presence or absence of a superconducting element using the PSCAD/EMTDC

박상용(Sang-Yong Park) ; 최효상(Hyo-Sang Choi)

With the announcement of a policy to reduce carbon emissions, the range and technologies of renewable energy sources are increasing. In new renewable energy, the amount and range of solar power generation is relatively gradually expanding[1]. Based on the high-speed DC circuit breaker used in the solar power generation, we combined the LC divergence oscillation circuit and the superconducting element that this research team is working on. This is to protect peripheral equipment against an increase in solar power generation and unspecified disturbances. The DC circuit breaker, we propose is a mechanical DC circuit breaker with a superconducting element applied. The superconducting element can lower the initial fault current within about 2 ms through the quenching operation. However, it takes a large power burden and a long time to cut-off the fault current. In the mechanical DC cut-off part, the existing high-speed mechanical circuit breaker, LC divergent oscillation circuit and Surge Arrestor are connected in parallel to safely and reliably cut off fault current. The characteristics of the cut-off operation that appear when a superconducting element and an LC divergent oscillation circuit are combined with a conventional mechanical DC circuit breaker were analyzed. As a result, through the application of the superconducting element, the speed at which the artificial zero-point of the fault current occurs was reduced, and the time to complete the shutdown was shortened.

다층신경망을 이용한 태양광 인버터 고장진단 Fault Diagnosis for Photovoltaic Inverters using a Multi-layer Neural Network

노명준(Myung-Jun Noh) ; 방준호(Junho Bang) ; 이재수(Jai-Shu Rhee) ; 조평훈(Pyoung-Hoon Cho) ; 권명회(Myeong-Hoi Kwon) ; 임종길(Jong-Gil Lim) ; 천현준(Hyun-Jun Chun) ; 송준희(Jun-Hee Song)

In this paper, an algorithm for diagnosing and predicting solar inverter failures was studied. A multi-layer neural network failure diagnosis model that can diagnose failures using inverter failure data was designed. The data were acquired from the field, and there are 307,200 items such as watt-hour meter reading value, inverter meter reading value, meter failure status, and inverter fault status. And using this data, simulations were performed to optimize parameters, and the size and input/output, activation function, loss function, optimization function, and batch size and number of times of the neural network were determined. The final simulation was performed using the determined parameters and the failure of the inverter was diagnosed. As a result, it was confirmed that the failure of the inverter was predicted with an accuracy of up to 97 [%]. Inverter failure was predicted when the operation was completely stopped, when the error between the amount of power generation and the inverter instruction value increased, and when the efficiency of the inverter changed abruptly

문자 행렬 지도 기반의 타일 격자무늬 추적 자율주행 로봇 The autonomous mobile robot that tracks tile grid pattern based on character matrix map

김정주(Jung-Ju Kim) ; 김동진(Dong-Jin Kim) ; 구경완(Kyung-Wan Koo)

We propose a method of autonomous driving by using a character matrix map to determine the current location and planning a path to the destination for the robot that tracks tile grid pattern. Compared to conventional methods, it is simpler and more economical as it enables the positioning and planned path driving of mobile robots only with information from a camera without any construction or addition of devices for mobile robotic systems.