• 한국지리정보학회지
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• 제17권4호
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• pp.86-100
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• 2014

본 연구의 목적은 산지 내 풍력발전단지 입지 적합성 분석을 통해 입지선정 가이드라인과 산지 훼손 최소화를 위한 제도적 개선방안을 도출하는 것이다. 먼저 풍력발전단지 입지 적합성 분석을 위해 국내외 사례 및 현장조사, 연구문헌 고찰을 통해 산지 내 풍력발전단지 입지선정을 위한 요인을 도출하고, 요인별 세부항목 및 가중치를 결정하여 이를 바탕으로 각 항목별 세부평가기준을 수립함으로써 입지 적합성 모델을 개발하였다. 강원도를 사례지역으로 선정하여 풍력자원 밀도 데이터, 법적 산지보전지역, 입지 기준 요인 항목별 자료를 토대로 공간 DB를 구축하여 산지 내 풍력발전 입지가능지역을 도출하였다. 일정 개수 이상의 풍력발전기가 입지할 수 있는 풍력발전단지 잠재 입지가능면적의 추정을 위해서 본 연구에서는 근린분석방법인 Block Statistics와 Focal Statistics 방법을 이용하였다. 그 결과 Block Statistics 방법에 의한 풍력발전기 잠재적 입지가능 면적은 1,261ha이며, Focal Statistics 방법에 의한 풍력발전기 잠재적 입지가능 면적은 1,411ha으로 나타났다. 본 연구의 결과를 바탕으로 대규모 절성토에 의한 산림재해 발생 우려 및 산지경관 훼손을 방지하기 위한 저감대책이 마련되어야 할 것이다.

• 한국해양공학회지
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• 제35권4호
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• pp.287-295
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• 2021

This paper describes a recurrent neural network (RNN) for the fault classification of a blade pitch system of a spar-type floating wind turbine. An artificial neural network (ANN) can effectively recognize multiple faults of a system and build a training model with training data for decision-making. The ANN comprises an encoder and a decoder. The encoder uses a gated recurrent unit, which is a recurrent neural network, for dimensionality reduction of the input data. The decoder uses a multilayer perceptron (MLP) for diagnosis decision-making. To create data, we use a wind turbine simulator that enables fully coupled nonlinear time-domain numerical simulations of offshore wind turbines considering six fault types including biases and fixed outputs in pitch sensors and excessive friction, slit lock, incorrect voltage, and short circuits in actuators. The input data are time-series data collected by two sensors and two control inputs under the condition that of one fault of the six types occurs. A gated recurrent unit (GRU) that is one of the RNNs classifies the suggested faults of the blade pitch system. The performance of fault classification based on the gate recurrent unit is evaluated by a test procedure, and the results indicate that the proposed scheme works effectively. The proposed ANN shows a 1.4% improvement in its performance compared to an MLP-based approach.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1064-1072
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• 2017

The power of controlled generators in microgrids randomly fluctuate because of the stochastic volatility of the outputs of photovoltaic systems and wind turbines as well as the load demands. To address and dispatch these stochastic factors for daily operations, a dynamic economic dispatch model with the goal of minimizing the generation cost is established via chance-constrained programming. A Monte Carlo simulation combined with particle swarm optimization algorithm is employed to optimize the model. The simulation results show that both the objective function and constraint condition have been tightened and that the operation costs have increased. A higher stability of the system corresponds to the higher operation costs of controlled generators. These operation costs also increase along with the confidence levels for the objective function and constraints.

• 대한조선학회논문집
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• 제60권5호
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• pp.375-387
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• 2023

The subsea power cables are increasingly important for harvesting renewable energies as we develop offshore wind farms located at a long distance from shore. Particularly, the continuous flexural motion of inter-array dynamic power cable of floating offshore wind turbine causes tremendous fatigue damages on the cable. As the subsea power cable consists of the helical structures with various components unlike a mooring line and a steel pipe riser, the fatigue analysis of the cables should be performed using special procedures that consider stick/slip phenomenon. This phenomenon occurs between inner helically wound components when they are tensioned or compressed by environmental loads and the floater motions. In particular, Vortex-induced vibration (VIV) can be generated by currents and have significant impacts on the fatigue life of the cable. In this study, the procedure for VIV fatigue analysis of the dynamic power cable has been established. Additionally, the respective roles of programs employed and required inputs and outputs are explained in detail. Demonstrations of case studies are provided under severely sheared currents to investigate the influences on amplitude variations of dynamic power cables caused by the excitation of high mode numbers. Finally, sensitivity studies have been performed to compare dynamic cable design parameters, specifically, structural damping ratio, higher order harmonics, and lift coefficients tables. In the future, one of the fundamental assumptions to assess the VIV response will be examined in detail, namely a narrow-banded Gaussian process derived from the VIV amplitudes. Although this approach is consistent with current industry standards, the level of consistency and the potential errors between the Gaussian process and the fatigue damage generated from deterministic time-domain results are to be confirmed to verify VIV fatigue analysis procedure for slender marine structures.

• 신재생에너지
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• 제6권2호
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• pp.33-39
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• 2010

The objective of this study is to present a basis for the evaluation on the renewable energy dissemination program in Korea applying the outcome evaluation, one of the five types of evaluation methods of EERE, DOE, and the effectiveness indicator, which is suggested by IEA, OECD. The outcome evaluation quantifies achievements of program outputs and outcomes against planned time frame. We analyze the correlation coefficients between cumulative expenditure on the renewable energy dissemination program and each renewable energy deployment and the unit installation cost of several dissemination programs for the outcome evaluation. Meanwhile, the effectiveness indicator is calculated by dividing the additional renewable energy deployment achieved in a given year by the remaining mid-term realizable potential to 2020 in each source of renewable energy. The results show that correlation coefficients between cumulative expenditure and each renewable energy deployment are significantly positive during the implementation period of each deployment program. And photovoltaic energy, bio energy, and wind power energy show high effectiveness indicator.

• Advances in Energy Research
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• 제7권1호
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• pp.67-84
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• 2020

Given the recent surge of interest towards utilization of renewable distributed energy resources (DER), in particular in remote areas, this paper aims at designing an optimal hybrid system in order to supply loads of a village located in Esfarayen, North Khorasan, Iran. This paper illustrates the optimal design procedure of a standalone hybrid system which consists of Wind Turbine Generator (WTG), Photo Voltaic (PV), Diesel-generator, and Battery denoting as the Energy Storage System (ESS). The WTGs and PVs are considered as the main producers since the site's ambient conditions are suitable for such producers. Moreover, batteries are employed to smooth out the variable outputs of these renewable resources. To this end, whenever the available power generation is higher than the demanded amount, the excess energy will be stored in ESS to be injected into the system in the time of insufficient power generation. Since the standalone system is assumed to have no connection to the upstream network, it must be able to supply the loads without any load curtailment. In this regard, a Diesel-Generator can also be integrated to achieve zero loss of load. The optimal hybrid system design problem is a discrete optimization problem that is solved, here, by means of a recently-introduced meta-heuristic optimization algorithm known as Lightning Attachment Procedure Optimization (LAPO). The results are compared to those of some other methods and discussed in detail. The results also show that the total cost of the designed stand-alone system in 25 years is around 92M€ which is much less than the grid-connected system with the total cost of 205M€. In summary, the obtained simulation results demonstrate the effectiveness of the utilized optimization algorithm in finding the best results, and the designed hybrid system in serving the remote loads.

• 한국건설관리학회논문집
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• 제20권6호
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• pp.126-131
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• 2019

최근 태양광의 발전 효율성과 경제성이 높은 발전소 부지를 확보하기 위해 특정 지역을 대상으로 태양광 발전량을 정확히 예측하기 위한 연구들이 수행되었다. 하지만 국내의 경우 기존 발전량 데이터가 부족함에 따라 정확한 발전량 추정에 문제가 발생할 수 있으며, 우리나라 기준으로 어떠한 기상조건을 나타내는 변수가 태양광발전에 어느 정도의 영향을 미치는지에 대한 연구가 부족한 실정이다. 따라서 본 연구는 지형 효과를 충분히 고려하여 제작된 태양복사에너지 지도와 미세먼지와 같은 기상조건을 추가하여 태양광 발전량 추정 회귀모델을 제시하고, 추정된 발전량과 실제 발전량을 비교 분석하였다. 그 결과, 습도를 제외한 태양복사에너지, 온도, 풍속, 운량, 강수량, 일조시간, 미세먼지가 발전 효율에 통계적으로 유의미한 영향을 미치는 것으로 나타났으며, 회귀 분석모델을 통해 추정된 발전량과 실제 발전량을 비교 분석하여 RMSE는 48.261(h), nRMSE는 1.592(%), MAPE는 11.696(%), 그리고 는 0.979이 도출되었다. 이러한 결과는 국내 태양광 발전 부지를 평가함에 있어서 고려해야 하는 중요한 기상 조건 등 태양광 발전량 추정 모델을 설계하는데 활용할 수 있으며, 이를 바탕으로 태양광 발전소 건설 부지를 선정함에 있어 중요한 지표인 발전량을 정확히 추정하는데 기여할 것으로 사료된다.