• 전기학회논문지P
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• 제65권4호
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• pp.235-241
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• 2016

Grid-connected, large-capacity energy storage systems (ESS) can be used for peak load supply, frequency regulation, and renewable energy output smoothing. In order to confirm the capability of battery ESS to provide such services, 4MW/ 8MWh battery ESS demonstration facility was built in the Jocheon substation on Jeju Island. The frequency regulation technology developed for the Jocheon demonstration facility then became the basis for the 28MW and 24MW frequency regulation ESS facilities installed in 2014 at the Seo-Anseong and Shin-Yongin substations, respectively. The operation control systems at these two facilities were continuously improved, and their successful commercialization led to the construction of additional ESS facilities all over Korea in 2015. In seven (7) locations nationwide (e.g., Shin-Gimje and Shin-Gyeryeong), a total of 184 MW of ESS had been commercialized in 2016. The trial run for the new ESS facilities had been completed between April and May in 2016. In this paper, results of the trial run from each of the ESS facilities are presented. The results obtained from the Seo-Anseong and Shin-Yongin substations during a transient event by a nuclear power plant trip are also presented in this paper. The results show that the frequency regulation battery ESS facilities were able to quickly respond to the transient event and trial run of ESS is necessary before it is commercialized.

• 대한전자공학회논문지
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• 제20권6호
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• pp.11-17
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• 1983

본 연구는 explicit M.K.A.C. 알고리즘으로 마이크로프로세서를 사용하여 직류전동기 속도 제어를 하였다. 실험에 사용된 적응 제어 알고리즘으로는 먼저 지수함수적 가중 최소사승법 (exponentially wighted least square method: E.W.L.S) 알고리즘의 계산상의 불안정과 수행시간을 최소로 하기 위하여 시간 지연이 있는 E.W.L.S.알고리즘에 EDUt-_인수화법을 도입한 UDUt-인수화법 알고리즘을 사용하였고, 또한 gradient-type의 알고리즘으로도 초기에 dtatl-zollr을 갖는 직류전동기를 효과적으로 제어하기 위하여 gradient-type의 알고리즘에 smoothing polynomal과 상수ℓ을 사용한 SM gradient-쇼pe의 알고리즘을 제안하였다. UDTt인수화법 알고리즘을 적용한 결과 수행시간이 단축되었으며, SM gradient-type의 알고리즘의 경우는 dead-zone을 위한 기동전압을 사용하지 않고도 효과적인 속도제어를 할 수 있음을 확인하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.735-737
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• 2017

An Off grid or remote solar electric systems are an energy supply to our home or to our companies without the utility of Grid at all. Off grid solar systems are very important for those who live in remote locations especially for developing countries where getting the electric grid is extremely expensive, inconvenient or for those who doesn't need to pay a monthly bill with the electric bill in general. The main critical components of any solar power system or renewable energy harvesting systems are the energy storage systems and its charge controller system. Energy storage systems are the essential integral part of a solar energy harvesting system and in general for all renewable energy harvesting systems. To provide an optimal solution of both high power density and high energy density at the same time we have to use hybrid energy storage systems (HESS), that combine two or more energy storage technologies with complementary characteristics. In this present work, design and simulation we use two storage systems supercapacitor for high power density and lithium based battery for high energy density. Here the system incorporates fast-response supercapacitors to provide power to manage solar smoothing and uses a battery for load shifting. On this paper discuss that the total energy throughout of the battery is much reduced and the typical thermal stresses caused by high discharge rate responses are mitigated by integrating supercapacitors with the battery storage system. In addition of the above discussion the off grid solar electric energy harvesting presented in this research paper includes battery and supercapacitor management system, MPPT (maximum power point tracking) system and back/boost convertors. On this present work the entire model of off grid electric energy harvesting system and all other functional blocks of that system is implemented in MATLAB Simulink.

• Smart Structures and Systems
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• 제21권5호
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• pp.687-694
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• 2018

The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.