전력 케이블에서 발생하는 손실을 정확히 예측하기 위해서는 금속 시스에서 발생하는 와전류 손실에 대한 분석이 필요하다. 동손의 경우 도체의 저항과 전류에 의하여 쉽게 계산이 되지만 금속 시스에서 발생하는 와전류의 경우 측정 및 예측이 어렵기 때문이다. 이를 위하여 선행연구에서는 단상 케이블에서 발생하는 와전류 손실을 분석하였지만 실제 환경에서는 3상이 대부분 사용되기 때문에 적용하기에는 한계가 존재한다. 그러므로 본 논문에서는 3상 케이블의 금속 시스에서 발생하는 와전류 손실에 대하여 발생 원인에 따라 이론적으로 분석하고 전자기 수치 해석을 통하여 삼각 배열과 수평배열에서 발생하는 와전류 손실을 예측하였다.

무효전력 보상설비인 분로리액터는 전력계통의 부하 패턴에 따라서 하루에도 수 회 정도 차단기에 의해 운전되거나 정지된다. 분로리액터개폐 시 몇 가지 요인에 의해 발생하는 과전압은 차단기의 절연 성능을 저하시키며, 계통을 구성하는 전력기기에 심각한 전압 스트레스를 유발한다. 분로리액터 개폐 과정에서 발생하는 과도현상을 측정하는 것은 계통을 모의하여 차단기 성능을 검증하는 시험소 수준에서는 가능하나, 실제 계통 운전 중에 발생하는 과도현상을 측정하는 것은 여러 가지 제약으로 어려움이 있다. 따라서 본 논문에서는 실 계통에서 지상 소전류 차단과정에서 가혹한 과도회복전압(TRV: Transient Recovery Voltage)을 유발하는 재발호(reignition)나 전류재단(current chopping) 현상에 대한 해석을 위해 전자계과도해석프로그램(EMTP: Electro-magnetic Transients Program)을 활용한 모델링 과정과 이를 토대로 분로리액터 개폐 과정에서 차단기의 고장을 유발하는 주된 현상에 대해 해석하고자 한다.

There are many attempts to apply AI technology to diagnose facilities or improve the work efficiency of the power industry. The emergence of new machine learning technologies, such as deep learning, is accelerating the digital transformation of the power sector. The problem is that traditional power systems face security risks when adopting state-of-the-art AI systems. This adoption has convergence characteristics and reveals new cybersecurity threats and vulnerabilities to the power system. This paper deals with the security measures and implementations of the power system using machine learning. Through building a commercial facility operations forecasting system using machine learning technology utilizing power big data, this paper identifies and addresses security vulnerabilities that must compensated to protect customer information and power system safety. Furthermore, it provides security guidelines by generalizing security measures to be considered when applying AI.

In this paper, we designed the COS MEMS system for sensing the falling detection and explosive noise of fuse link in COS (Cut Out Switch) installing on the power distribution. This system analyzed the failure characteristics and an instantaneous breakdown of power distribution. Therefore, our system strengths the industrial competence and guaranties the stable power supply. In this paper, we applied BLE (Bluetooth Low Energy) technology which is suitable protocol for low data rate, low power consumption and low-cost sensor applications. We experimented with LSM6DSOX which is system-in-module featuring 3 axis digital accelerometer and gyroscope boosting in high-performance mode and enabling always-on low-power features for an optimal motion for the COS fuse holder. Also, we used the MP34DT05-A for gathering an ultra-compact, low power, omnidirectional, digital MEMS microphone built with a capacitive sensing element and an IC interface. The proposed COS MEMS system is developed based on nRF52 SoC (System on Chip), and contained a 3-axis digital accelerometer, a digital microphone, and a SD card. In this paper of experiment steps, we analyzed the performance of COS MEMS system with gathering the accelerometer raw data and the PDM (Pulse Data Modulation) data of MEMS microphone for broadcasting the failure of COS status.

초기 학습 데이터의 과적합으로 인한 전력망 상태예측 모델의 성능 감소를 방지하고 예측모델의 예측 정확도 유지를 통한 계속적인 현장활용을 위해서는 기계학습 모델의 예측 정확도를 지속적으로 관리할 필요가 있다. 이를 위해, 본 논문에서는 다양한 요인에 의해 끊임없이 변화하는 전력망 상태 데이터의 특성을 고려하여 예측모델의 정확성과 신뢰성을 높이고 현장 적용 가능한 수준의 품질을 유지하기 위한 기계학습 기반 전력망 상태예측 모델의 성능 유지관리 자동화 기법을 제안한다. 제안 기법은 워크플로우 관리 기술의 적용을 통해 전력망 상태예측 모델 성능 유지관리를 위한 일련의 태스크들을 워크플로우의 형태로 모델링하고 이를 자동화하여 업무를 효율화 하였다. 또한, 기존 기술에서는 시도되지 않았던 학습데이터의 통계적 특성 변화 정도와 예측의 일반화 수준을 모두 고려한 예측모델의 성능 평가를 통해 성능 결과의 신뢰성을 확보하고 이를 통해 예측 모델의 정확도를 일정 수준으로 유지관리하고 더욱 성능이 우수한 예측모델의 신규 개발이 가능하다. 결과적으로 본 논문에서 제안하는 전력망 상태예측 모델 성능 유지관리 자동화 기법을 통해 예측모델의 성능 저하문제를 해결하여 분산자원 연계 등 외부 환경의 변화에 유연한 예측모델 관리를 통해 정확성과 신뢰성이 보장된 예측 모델의 지속적인 활용이 가능하다.

DC distribution system has been evaluated as an excellent one in comparison with existing AC distribution network because it needs fewer power conversion stages and the full capacity of the equipment can be used without consideration for power factor. Recently, research and development on the implementation of DC distribution networks have been progressed globally based on the rapid advancement in power-electronics technology, and the technological developments from the viewpoint of infrastructure are also in progress. However, to configure a distribution network which is a distribution line for DC, more accurate and rapid introduction of analysis technology is needed for the monitoring, control and operation of the system, which ensure the system run flexible and efficiently. However, in case of a bipolar DC distribution network, there are two buses acting as slack buses, so the Jacobian matrix cannot be configured. Without solving this problem, DC distribution network cannot be operated when the network is unbalanced. Therefore, this paper presented a comprehensive method of analysis with consideration of operating elements which are directly connected between neutral electric potential caused by the unbalanced of load in DC distribution network with bipolar structure.

본 연구에서는 화력 발전소 보일러에 대한 연소 및 열전달 해석을 위하여 화로 내부를 다중영역으로 나누고 각 영역에서 energy와 mass balance는 1차원으로 계산하고, 복사열전달은 3차원으로 계산하는 다중영역분할 화로해석 기법을 활용하였다. 그리고 적용 기법에 대한 신뢰성 검증을 위하여 국내 500 MW 급 석탄화력 보일러 화로에 대한 계산 값과 보일러 제작사의 설계 데이터를 비교하여 양호함을 확인하였고, 동일한 설비에 대한 CFD 해석과 비교한 결과 유사한 경향을 얻었다. 본 계산 기법은 CFD 화로해석 보다는 덜 상세하지만, 빠른 시간에 연료반응성, 화로형상 및 운전변수에 따른 특성을 계산할 수 있는 장점이 있으므로 발전소 현장에서의 설비감시진단 및 일일 연료/운전 계획 수립 등 활용성 측면에서 유용할 것으로 예상된다.

Accurate forecasting of wind power is important for grid operation. Wind power has intermittent and nonlinear characteristics, which increases the uncertainty in wind power generation. In order to accurately predict wind power generation with high uncertainty, it is necessary to analyze the factors affecting wind power generation. In this paper, 6 factors out of 11 are selected for more accurate wind power generation forecast. These are wind speed, sine value of wind direction, cosine value of wind direction, local pressure, ground temperature, and history data of wind power generated.

본 논문에서는 내진설계가 고려되어 있지 않은 전력구를 포함한 기설 개착식 전력구 100개소를 대상으로, 정부의 요구수준(내진 특등급, 0.22 g)을 만족하는지 확인하기 위하여 내진성능 평가를 수행하였다. 내진성능 평가 결과, 대상 전력구들은 대부분 0.3-1 g의 내진성능을 보유하고 있는 것으로 나타나, 내진 특등급 수준을 만족하였으며 내진안전성을 확보하고 있는 것으로 나타났다. 한편 응답변위법에 의한 전력구의 내진성능 평가 방법 및 결과에 대한 타당성을 확인하고, 전력구의 내진 안전성을 검증하기 위한 지진응답 해석 및 구조실험을 수행하였다. 그 결과 0.22 g 수준의 지진 하에서 응답변위법에 의한 상대변위는 지진응답 해석 결과보다 보수적이었으며, 실규모 구조실험에 의한 하중-변위 곡선 및 응답수정계수 산정 결과를 통해 전력구의 내진 안전성을 확인할 수 있었다.

Since SF₆ gas was discovered in the early 1900s, it has been widely used as an insulation material for electrical equipment. While various indicators have been developed to diagnose oil-immersed transformers, there are still insufficient indicators for the diagnosis of gas-insulated transformers. When necessary, chemical diagnostic methods can be used for gas-insulated transformers. However, the field suitability and accuracy of those methods for transformer diagnosis have not been verified. In addition, since various types of decomposition gases are generated therein, it is also necessary to establish appropriate analysis methods to cover the variety of gases. In this study, a gas-insulated transformer was diagnosed through the analysis of decomposition gases. Reliability assessments of both simple analysis methods suitable for on-site tests and precise analysis methods for laboratory level tests were performed. Using these methods, a gas analysis was performed for the internal decomposition gases of a 154 kV transformer in operation. In addition, simulated discharge and thermal fault experiments were demonstrated. Each major decomposition gas generation characteristics was identified. The results showed that an approximate diagnosis of the inside of a gas-insulated transformer is possible by analyzing SO₂, SOF₂, and CO using simple analysis methods on-site. In addition, since there are differences in the types of decomposition gas generation patterns with various solid materials of the internal transformer, a detailed examination should be performed by using precise analysis methods in the laboratory.

In order to identify the characteristics of fine particle emissions from thermal power plants, this study conducted measurement of the primary emission concentration of TPM, PM₁₀ and PM_2.5 according to Korea standard test method (ES 01301.1) and ISO 23210 method (KS I ISO 23210). Particulate matters were sampled in total 74 units of power plants such as 59 units of coal-fired power plants, 7 units of heavy oil power plants, 2 units of biomass power plant, and 6 units of liquid natural gas power plants. The average concentration of TPM, PM₁₀, PM_2.5 by fuel are 3.33 mg/m³, 3.01 mg/m³, 2.70 mg/m³ in coal-fired plant, 3.02 mg/m³, 2.99 mg/m³, 2.93 mg/m³ in heavy oil plant, 0.114 mg/m³, 0.046 mg/m³, 0.036 mg/m³ in LNG plant, respectively. These results of TPM, PM₁₀ and PM_2.5 were satisfied with the standards of fine dust emission allowance in all units of power plants, respectively. Also, this study evaluated the characteristics of fine particle emissions by conditions of power plants including generation sources, boiler types and operation years and calculated emission factors and then evaluated fine particle emissions by sources of electricity generation.

There are many application fields of electrical energy storage such as load shifting, integration with renewables, frequency or voltage supports, and so on. Especially, the frequency regulation is needed to stabilize the electric power system, and there have to be more than 1 GW as power reserve in Korea. Ni-rich layered oxide cathode materials have been investigated as a cathode material for Li-ion batteries because of their higher discharge capacity and lower cost than lithium cobalt oxide. Nonetheless, most of them have been investigated using small coin cells, and therefore, there is a limit to understand the deterioration mode of Ni-rich layered oxides in commercial high energy Li-ion batteries. In this paper, the pouch-type 20 Ah-scale Li-ion full cells are fabricated using Ni-rich layered oxides as a cathode and graphite as an anode. Above all, two test conditions for the application of frequency regulation were established in order to examine the performances of cells. Then, the electrochemical performances of two types of Ni-rich layered oxides are compared, and the long-term performance and degradation mode of the cell using cathode material with high nickel contents among them were investigated in the frequency regulation conditions.

The superconducting synchronous generator is one of the breakthrough elements for direct-drive wind turbines because it is light and small. Normally the superconducting one has copper armature windings in the stator and superconducting field windings on the rotor. The high resistance of the armature can make large copper losses, comparing with the conventional generators with a gear box. One of the solutions for the large copper losses could be a fully superconducting generator. But the high magnetic fields from the superconducting field windings on the rotor also make high perpendicular magnetic fields on the superconducting tapes in the armature windings. We have proposed a fully superconducting synchronous generator with dual field windings. It could immensely decrease the circumferential component of the magnetic field from the field windings at the armature windings. In this paper, we conceptually designed 3 types of superconducting synchronous generators. The first one is the fully superconducting one with conventional structure, which has superconducting armature windings in the stator and superconducting field windings on the rotor. The second one is the one with dual superconducting field windings and superconducting armature windings between them. The last one is the same as the third one except the structure of the armature. If the concentrated armature windings are superconducting ones with cryostats, then they cannot be installed within the span of 2 poles. So, we adopted 3 phases windings within 4 poles system. It makes more AC losses but can be manufactured really.

In this paper, we proposed a high frequency equivalent circuit considering parasitic impedance components for differential noise analysis on the input stage during DC-DC buck converter switching operation. Based on the proposed equivalent circuit model, we presented a method to measure parasitic impedance parameters included in DC bus plate, IGBT, and PCB track using the gain phase method of a network analyzer. In order to verify the validity of this model, a DC-DC prototype consisting of a buck converter, a signal analyzer, and a LISN device, and then resonance frequency was measured in the frequency range between 150 kHz and 30 MHz. The validity of the parasitic impedance measurement method and the proposed equivalent model is verified by deriving that the measured resonance frequency and the resonance frequency of the proposed high frequency equivalent model are the same.