• Journal of Power Electronics
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• 제15권2호
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• pp.378-388
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• 2015

This paper proposes a pulse width modulation (PWM)-based sliding mode controller (SMC) for a full-bridge DC-DC converter that can eliminate static output voltage error. Hysteretic SMC in DC-DC converter does not have a fixed switching frequency, and applying hysteretic SMC to full-bridge converters is difficult. Fixed-frequency SMC, which is also called PWM-based SMC, based on equivalent control overcomes these shortcomings. However, the controller order reduction in equivalent control in PWM-based SMC causes static output voltage error. To resolve this issue, an integral item is added to the PWM-based SMC. Sliding mode coefficients are designed by applying a standard second-order system to the sliding mode surface. The effect of adding an integral item on the controller is analyzed, and an integral coefficient design method is proposed. Experiment results on a three-level full-bridge DC-DC converter verify the control scheme and design method proposed in this paper.

• Journal of Power Electronics
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• 제16권5호
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• pp.1950-1963
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• 2016

A novel open-circuit fault diagnosis method for 3-phase 4-wire 3-level active power filters based on voltage error correlation is proposed in this paper. This method is based on observing the output pole voltage error of the active power filter through two kinds of algorithms. One algorithm is a voltage error analytical algorithm, which derives four output voltage error analytic expressions through the pulse state, current value and dc bus voltage, respectively, assuming that all of the IGBTs of a certain phase come to an OC fault. The other algorithm is a current circuit equation algorithm, which calculates the real-time output voltage error through basic circuit theory. A correlation is introduced to measure the similarity of the output voltage errors between the two algorithms, and OC faults are located by the maximum of the correlations. A FPGA has been chosen to implement the proposed method due to its fast prototyping. Simulation and experimental results are presented to show the performance of the proposed OC fault diagnosis method.

• 한국지능시스템학회논문지
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• 제18권5호
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• pp.611-616
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• 2008

Error correcting codes는 일반적으로 soft error를 막기 위해서 사용된다. single error의 수정과 double error의 검출(SEC-DED) 코드들은 이런 목적으로 사용된다. 본 논문에서는 이러한 회로의 크기, 지연시간, 전력 소비를 선택적으로 최소로 하는 SEC-DED의 설계방법을 제안한다. 이러한 SEC-DED의 설계는 비선형 최적화 문제로 포함되는데 우리는 다목적 유전자 알고리즘을 이용하여 이 문제를 해결한다. 제안하는 방법은 여러 가지 SEC-DED code들을 제공하여 사용자의 환경에 따라 알맞은 회로를 선택할 수 있도록 한다. 제안하는 방법을 효율적인 ECC코드로 알려져 있는 odd-column weight Hsiao code에 적용하여 그 효율성을 입증하였다.

• 전기학회논문지
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• 제63권5호
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• pp.713-718
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• 2014

DC urban railway power system consists of DC power network and AC power network. The DC power network supplies electric power to railway vehicles and the AC power network supplies electric power to station electric equipment. Recently, because of power consumption reduction and peak load shaving, intelligent measurement of regenerative energy and renewable energy adapted on DC urban railway is required. For this reason, DC smart metering system for DC power network shall be developed. Therefore, in this paper, DC voltage sensor, current sensor, and DC smart meter were developed and evaluated by performance test. DC voltage sensor was developed for measuring standard voltage range of DC urban railway, and DC current sensor was developed as hall effect split core type in order to install in existing system. DC smart meter possesses function of general intelligent electric power meter, such as measuring electricity and wireless communication etc. And, DC voltage sensor showed average 0.17% of measuring error for 2,000V/50mA, and current sensor showed average 0.21% of measuring error for ${\pm}2,000V/{\pm}4V$ in performance test. Also DC smart meter showed maximum 0.92% of measuring error for output of voltage sensor and current sensor. In similar environment for real DC power network, measuring error rate was under 0.5%. In conclusion, accuracy of DC smart metering system was confirmed by performance test, and more detailed performance will be verified by further real operation DC urban railway line test.

• Nuclear Engineering and Technology
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• 제51권3호
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• pp.709-718
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• 2019

The international nuclear industry has undergone a lot of changes since the Fukushima, Chernobyl and TMI nuclear power plant accidents. However, there are still large and small component deficiencies at nuclear power plants in the world. There are many causes of electrical equipment defects. There are also factors that cause component failures due to human errors. This paper analyzed the root causes of failure and types of human error in 300 cases of electrical component failures. We analyzed the operating experience of electrical components by methods of root causes in K-HPES (Korean-version of Human Performance Enhancement System) and by methods of human error types in HuRAM+ (Human error-Related event root cause Analysis Method Plus). As a result of analysis, the most electrical component failures appeared as circuit breakers and emergency generators. The major causes of failure showed deterioration and contact failure of electrical components by human error of operations management. The causes of direct failure were due to aged components. Types of human error affecting the causes of electrical equipment failure are as follows. The human error type group I showed that errors of commission (EOC) were 97%, the human error type group II showed that slip/lapse errors were 74%, and the human error type group III showed that latent errors were 95%. This paper is meaningful in that we have approached the causes of electrical equipment failures from a comprehensive human error perspective and found a countermeasure against the root cause. This study will help human performance enhancement in nuclear power plants. However, this paper has done a lot of research on improving human performance in the maintenance field rather than in the design and construction stages. In the future, continuous research on types of human error and prevention measures in the design and construction sector will be required.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.12-15
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• 2002

Korea Power System Protection Setting Rule was used from the rectify 1990's. Thereafter transmission voltage is raised the voltage into 765kV, and introduction to new technology of Power System, and was many of variation but, it is using. The present is using Digital type distance relay for 765kV transmission line protection. If impedance value of transmission line were to value lower than setting, this would be operating and relay setting rule is for 85% into Zone 1 self section, and Zone 2 is a 125%, Zone 3 is a 225%. Which's $15{\sim}25%$ include current transformer error 5%, potential transformer 5%, relay calculation error 5% and margin factor from the field experience. This paper is discussed transmission protective relay and relay setting rule of high voltage power system and we verify the correctness relay setting rule with distance relay using Matlab simulation.

• 한국통신학회논문지
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• 제13권4호
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• pp.285-301
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• 1988

다치 직교 PRS(Partial Response Signaling) 시스템이 잡음, 간섭, 캐리어옵\ulcornerV, 위상지터, 페이딩 등에 의해 개별적으로 또는 복합적으로 영향을 받았을 경우에 대한 PRS 신호의 오율식을 유도하였다. 유도된 식에 의해 반송파 대잡음 전력비, 반송파 대 간섭파 전력비, 위상에러, 임펄스 지수, 가우스성 잡음전력 대 임펄스성 잡음 전력비, PLL(Phase Locked Loop)의 신호 대 잡음전력비, 페이딩 지수 등을 함수로 하여 수치계산을 통해 각 경우의 오율특성을 구했다. 얻은 결과로부터, 일반적으로 임펄스성 잡음보다 오율 특성을 보다 더 열화시키지만 일단 신호가 페이딩을 받게되면 그 반대로 가우스성 잡음이 임펄스성 잡음보다 더욱 에러를 발생시킨다는 것을 알 수 있었다.

• Journal of Power Electronics
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• 제9권5호
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• pp.748-756
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• 2009

This paper presents a compensation algorithm for position error due to an amplitude imbalance between resolver output signals. Resolvers are typically used to obtain absolute position information for motor drive systems in severe environments. Position error is caused by an amplitude imbalance of the resolver output signals. As a result, the d- and q-axis currents of synchronous reference frame have periodic ripples in the stator fundamental frequency in permanent magnet synchronous motor (PMSM) drive systems. Therefore, this paper proposes a compensation algorithm to reduce the position error generated by the amplitude imbalance. The proposed method does not require any additional hardware, and reduces computation time with a simple integral operation according to rotor position. In addition, the position error can be directly compensated for by the estimated position error. The effectiveness of the proposed compensation algorithm is verified through several simulations and experiments.

• 동력기계공학회지
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• 제17권5호
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• pp.86-93
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• 2013

This paper proposes the used of genetic algorithm for optimizing PI controller and describes the dynamic modeling simulation for the permanent magnet synchronous motor driven by simplified vector control with the aid of MATLAB-Simulink environment. Furthermore, three kinds of error criterion minimization, integral absolute error, integral square error, and integral time absolute error, are used as objective function in the genetic algorithm. The modeling procedures and simulation results are described and presented in this paper. Computer simulation results indicate that the genetic algorithm was able to optimize the PI controller and gives good control performance of the system. Moreover, simplified vector control on permanent magnet synchronous motor does not need to regulate the direct axis component current. This makes simplified vector control of the permanent magnet synchronous motor very useful for some special applications that need simple control structure and low cost performance.

• 전기전자학회논문지
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• 제23권1호
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• pp.120-126
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• 2019

최근 에너지 인터넷에서 지능형 원격검침 인프라를 이용하여 확보된 대량의 전력사용데이터를 기반으로 효과적인 전력수요 예측을 위해 다양한 기계학습기법에 관한 연구가 활발히 진행되고 있다. 본 연구에서는 전력량 데이터와 같은 시계열 데이터에 대해 효율적으로 패턴인식을 수행하는 인공지능 네트워크인 Gated Recurrent Unit(GRU)을 기반으로 딥 러닝 모델을 제안하고, 실제 가정의 전력사용량 데이터를 토대로 예측 성능을 분석한다. 제안한 학습 모델의 예측 성능과 기존의 Long Short Term Memory (LSTM) 인공지능 네트워크 기반의 전력량 예측 성능을 비교하며, 성능평가 지표로써 Mean Squared Error (MSE), Mean Absolute Error (MAE), Forecast Skill Score, Normalized Root Mean Squared Error (RMSE), Normalized Mean Bias Error (NMBE)를 이용한다. 실험 결과에서 GRU기반의 제안한 시계열 데이터 예측 모델의 전력량 수요 예측 성능이 개선되는 것을 확인한다.