• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.513-521
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• 2017

Robust optimal operation of a microgrid is required since the increase of the penetration level of renewable generators in the microgrid raises uncertainty due to their intermittent power output. In this paper, an application of probabilistic optimization method to economical operation of a microgrid is studied. To simplify the treatment of the uncertainties of renewable generations and load, the new 'band of virtual equivalent load variation' is introduced considering their uncertainties. A simplified robust optimization methodology to generate the scenarios within the band of virtual equivalent load variation and to obtain the optimal solution for the worst scenario is presented based on Monte Carlo method. The microgrid to be studied here is composed of distributed generation system(DGs), battery systems and loads. The distributed generation systems include combined heat and power(CHP) and small generators such as diesel generators and the renewable energy generators such as photovoltaic(PV) systems and wind power systems. The modeling of the objective function for considering interruption cost by the penalty function is presented. Through the case study for a microgrid with uncertainties, the validity of proposed robust optimization methodology is evaluated.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.361-363
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• 1996

The output of solar cell should be operated in the maximum power point, since it is greatly fluctuated by insolation and temperature. Also, since the output of solar cell is a DC power, it needs the inverter to interact with utility line. In this paper, we made composed of PV system with a chopper that control the maximum power point and the inverter that drive to the high power factor and low harmonic by use of defected and compensated utility line voltage for synchronous phase with utility line.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.6
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• pp.916-921
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• 2004

This paper describes microprocessor-based control of photovoltaic power conditioning system. where the microprocessor is responsible for control of output power in accordance with the generated array DC power. The microprocessor includes the control algorithm of maximum power point tracking and converter control algorithm. In this power, we have designed a MPPT(Maximum Power Point Tracker) algorithm with environment factors and a PWM(Pulse Width Modulation) algorithm for high efficiency. The controller has been tested in the laboratory with the power conditioner and shows excellent performance.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.217-217
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• 2005

• Journal of the Korean Solar Energy Society
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• v.39 no.1
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• pp.59-66
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• 2019

BIPV or BAPV installation applied to building is increasing through public utility mandates enterprise. Solar PV energy generates only during the day, but if it is operated in convergence with ESS, which stores electrical energy, it can restrain the fossil energy used in buildings throughout the day. A solution is to converge with PV system and ESS. However, PV systems and ESS connected to the power grid in parallel can cause problems of electrical stability. A study was conducted on the case of failure to detect islanding operation under the parallel operation of PV generation and ESS that are connected in parallel to power grid. Experiments conducted various non-islanding detections under the operating conditions. In the experiment results, when one PCS - PV inverter or ESS inverter - was operating under the islanding condition, it stopped working within 0.5 seconds of the Korean grid standard. However, when both of PV inverter and ESS inverter were operating at the same time under the islanding situation, the anti-islanding algorithm did not operate normally and both inverters continuously supplied power to the connected RLC loads. islanding detection Algorithm developed by each inverter manufacturer has caused this phenomenon. Therefore, this paper presented a new test standard for islanding detection.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.534-548
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• 2021

In this paper, the feasibility of generating solar power near an abandoned quarry is examined with the objectives of resolving the essential problems that quarries encounter, such as rockfalls and space usage issues. On an abandoned quarry site in Sadang, Seoul, Republic of Korea, two different PV installation methods were analyzed. The first is attaching PV directly on the quarry slope. Since there are no corresponding safety standards and precedents for installing solar panels directly on slopes, the power generation potential was calculated by using topographic data and reasonable assumptions. The surface area of cut slope section was extracted from the Digital Elevation Model(DEM) via ArcGIS and Python programming to calculate the tilt and power capacity of installable panels. The other approach is installing PV as a rockfall barrier, and the power generation potential was analyzed with the assumption that the panel is installed in the direction of facing solar irradiation. For the derivation of power generation, the renewable energy generation analysis program SAM(System Advisor Model) was used for both methods. According to the result, quarries that have terminated resource extraction and remain devastated have the potential to be transformed into renewable energy generation sites.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.161-172
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• 2017

In the paper, a hybrid technique is proposed for detecting the location and capacity of distributed generation (DG) sources like wind and photovoltaic (PV) in power system. The novelty of the proposed method is the combined performance of both the Biography Based Optimization (BBO) and Particle Swarm Optimization (PSO) techniques. The mentioned techniques are the optimization techniques, which are used for optimizing the optimum location and capacity of the DG sources for radial distribution network. Initially, the Artificial Neural Network (ANN) is applied to obtain the available capacity of DG sources like wind and PV for 24 hours. The BBO algorithm requires radial distribution network voltage, real and power loss for determining the optimum location and capacity of the DG. Here, the BBO input parameters are classified into sub parameters and allowed as the PSO algorithm optimization process. The PSO synthesis the problem and develops the sub solution with the help of sub parameters. The BBO migration and mutation process is applied for the sub solution of PSO for identifying the optimum location and capacity of DG. For the analysis of the proposed method, the test case is considered. The IEEE standard bench mark 33 bus system is utilized for analyzing the effectiveness of the proposed method. Then the proposed technique is implemented in the MATLAB/simulink platform and the effectiveness is analyzed by comparing it with the BBO and PSO techniques. The comparison results demonstrate the superiority of the proposed approach and confirm its potential to solve the problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.437-442
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• 2001

Recently, transformerless inverters have been studied to reduce sizes and costs of utility-connected PV systems. This paper presents a transformerless PV inverter using a two-phase boost converter of reduced ripples in input current and output voltage, low voltage stress of semiconductor device and reduced size of input reactor. And new PWM method is introduced, whose on-off time is calculated from simultaneous equation induced by fourier series. To verify a validity of the proposed transformerless inverter, computer simulation has been carried out.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.291-298
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• 2020

The power generation of a PV system changes according to the weather variables, such as solar radiation and temperature. In particular, the output characteristics of photovoltaic systems, which are sensitive to changes in solar radiation, can be produced effectively and reliably in various weather conditions through MPPT (Maximum Power Point Tracking) control. This paper proposes a fuzzy-based MPPT control method to improve the efficiency and stability of the power production from a solar system. To verify the performance of the proposed method, under the same weather environment, the efficiency and stability of the newly proposed fuzzy logic were compared and evaluated empirically with P&O (Perturb and Observe), a representative algorithm of MPPT control. Furthermore, the circuits designed to improve the reliability and reliability of the hardware were manufactured from Printed Circuit Boards (PCB) to conduct experiments. Based on the results of the experiment during a certain period, the fuzzy-based MPPT proposed in this paper improved the efficiency by more than 4.4% compared to the MPPT based on the existing P&O algorithm and decreased the fluctuation width by more than 39.7% at the maximum power point.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1093-1094
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• 2008

본 논문은 수학적 모델링이 간편하고 제어기법의 적용이 쉬운 MATLAB 기반으로 태양광 셀과 모듈을 모델링하고 기존의 P&O MPPT제어 알고리즘을 분석하고 구현하였으며 전력전자 회로의 구현이 간단한 PLCES를 사용하여 부스트 컨버터 구현하였다. 이로써 일사량 변화와 온도변화의 영향이 고려되고, MATLAB 기반이므로 시뮬레이션 시간이 단축되며, 다양한 제어기법을 쉽게 적용할 수 있는 PV 발전시스템을 구축하였으며 시뮬레이션을 통해 태양광 모델의 성능과 MPPT 제어 성능을 검증하였다