• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1008-1011
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• 1996

Most control systems of power plants are using classical PID controllers for their process control. In order to get the desired control performances, the correct tuning of PID controllers is very important. Sometimes, it is necessary to retune PID controllers after the change of system operating condition and system design change, etc. Commercial auto-tuning controllers such as relay feedback controller can be used for this purpose. However, using these controllers to the safety-critical systems of nuclear power plants may be cause of unsafe operation, because they are using test signals for tuning. A new system identification auto-tuning method without using test signal has been developed in this paper. This method uses process input/output signals for system identification of unknown control process. From the model information of control process which was obtained from system identification approach, the optimal PID parameters can be calculated. The method can be used in the safety-critical systems because it is not using test signals during system modeling process.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.460-465
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• 2003

The modeling of PEM (Proton Exchange Membrane) fuel cell system consisting of fuel cell stack and BOP (Balance of Plant) is presented in this paper. The effects of temperature, pressure (air, hydrogen), and humidity on the fuel cell system performance were mainly investigated using thermo-dynamical and electro-chemical equations. To understand the power distribution characteristics of fuel cell system, the effects of operating temperature and air pressure on maximum power and system power were also demonstrated. Through this study, we can get the basic insight into the fuel cell stack and BOP component sizing and it can be used effectively for the optimization of the practical fuel cell systems in purpose.

• 한국정밀공학회지
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• 제15권6호
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• pp.5-14
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• 1998

In this paper we propose a new approach to the development of the automatic vision system to examine and repair the steam generator tubes at remote distance. In nuclear power plants, workers are reluctant of works in steam generator because of the high radiation environment and limited working space. It is strongly recommended that the examination and maintenance works be done by an automatic system for the protection of the operator from the radiation exposure. Digital signal processors are used in implementing real time recognition and examination of steam generator tubes in the proposed vision system. Performance of proposed digital vision system is illustrated by simulation and experiment for similar steam generator model.

• 한국산학기술학회논문지
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• 제21권11호
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• pp.672-682
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• 2020

최근 다양한 산업/제조 현장에서 운영 효율화를 위한 디지털 트윈(digital twin) 기술 연구가 활발하게 수행 중이고, 화석 연료의 점진적 고갈과 환경오염 문제는 파력발전소와 같은 신재생/친환경 발전방식을 요구한다. 하지만, 파도의 에너지에 의해서 전기를 생산하는 파력발전에서 변동성이 높은 파도에너지에 의해서 발전량과 고장 등의 운영효율화 요소가 밀접하게 관련되어 있어 이들 사이의 관계를 이해하고 예측하는 것이 매우 중요하다. 따라서 첫 번째로 파고 데이터, 진동수주(OWC: Oscillating Water Column, 이하 OWC) 챔버의 센서 데이터 등과 같은 변동성이 높은 데이터 간에 의미 있는 상관관계 도출이 필요하다. 두 번째로 도출된 상관관계를 기반으로 추출된 데이터로 예측 상황을 학습함으로써 원하는 정보를 예측할 수 있는 방법론 연구가 이루어져야 한다. 본 연구에서는 파력발전 시스템의 디지털 트윈으로 스마트 운용 및 유지보수가 가능하도록 실제 파력발전소의 IoT 센서 데이터를 이용하여 OWC의 압력 예측을 위해 머신러닝 프레임워크를 활용한 워크플로우 기반의 학습모델을 설계하고, 검증 및 평가 데이터셋을 통한 압력 예측분석의 유효성을 확인한다.

• 한국응용과학기술학회지
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• 제33권3호
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• pp.529-539
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• 2016

Modeling은 기상의 흐름, 화학반응 및 대기오염물질의 형성과정 등 대기현상을 과학적으로 이해하고 개발계획 및 대기 개선에 따른 정책수립의 기초자료로 활용된다. 최근 컴퓨팅 계산능력이 발전하면서 수치모델의 모델링 영역과 모델결과의 이용분야가 점차 다양해지고 있으며, 오염물질 발생원으로부터 시간의 흐름에 따라 오염물질농도를 예측이 가능해졌다. 본 연구는 일산열병합발전소 및 고양시 소각장 주변지역을 대상으로 CALPUFF 확산모델을 적용하여 대기 중 배출 된 NO와 TSP의 확산을 모사하고, 실제 측정결과와 비교함으로써 배출원에 의한 주변지역의 기여농도를 검토하였다. 1, 2차 $NO_2$ 기여율 비교 결과 A-3 지점이 타 지점에 비해 비교적 높게 나타났으며, 이는 열병합발전소 및 소각시설에서 배출되는 질소산화물의 영향이 타 지역에 비해 비교적 높다는 것을 알 수 있다. 1, 2차 TSP 기여율 비교 결과 A-5 지점이 비교적 타 지점에 비해 다소 높게 나타났으나, 기여율 값이 매우 낮음에 따라 열병합발전소 및 소각시설에서 배출되는 먼지에 의한 영향은 비교적 낮다고 판단된다.

• Nuclear Engineering and Technology
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• 제55권9호
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• pp.3409-3416
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• 2023

Licensing the next-generation of nuclear reactor designs requires extensive use of Modeling and Simulation (M&S) to investigate system response to many operational conditions, identify possible accidental scenarios and predict their evolution to undesirable consequences that are to be prevented or mitigated via the deployment of adequate safety barriers. Deep Learning (DL) and Artificial Intelligence (AI) can support M&S computationally by providing surrogates of the complex multi-physics high-fidelity models used for design. However, DL and AI are, generally, low-fidelity 'black-box' models that do not assure any structure based on physical laws and constraints, and may, thus, lack interpretability and accuracy of the results. This poses limitations on their credibility and doubts about their adoption for the safety assessment and licensing of novel reactor designs. In this regard, Physics Informed Neural Networks (PINNs) are receiving growing attention for their ability to integrate fundamental physics laws and domain knowledge in the neural networks, thus assuring credible generalization capabilities and credible predictions. This paper presents the use of PINNs as surrogate models for accidental scenarios simulation in Nuclear Power Plants (NPPs). A case study of a Loss of Heat Sink (LOHS) accidental scenario in a Nuclear Battery (NB), a unique class of transportable, plug-and-play microreactors, is considered. A PINN is developed and compared with a Deep Neural Network (DNN). The results show the advantages of PINNs in providing accurate solutions, avoiding overfitting, underfitting and intrinsically ensuring physics-consistent results.

• Advances in Energy Research
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• 제1권2호
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• pp.127-146
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• 2013

Torrefaction technologies convert assorted biomass feedstocks into energy-concentrated, carbon neutral fuel that is economically transported and easily ground for blending with fossil coals at numerous power plants around the world without needs to retrofit. Utilization of torrefied biomass in conventional electric generating units may be an increasingly attractive alternative for electricity generation as aging power plants in the world need to be upgraded or improved. This paper examines the economic feasibility of torrefaction in different scenarios by modeling torrefaction plants producing 136,078 t/year (150,000 ton/year) biocoal from wood and corn stover. The utilization of biocoal blends in existing coal-fired power plants is modeled to determine the demand for this fuel in the context of emerging policies regulating emissions from coal in the U.S. setting. Opportunities to co-locate torrefaction facilities adjacent to corn ethanol plants and coal-fired power plants are explored as means to improve economics for collaborating businesses. Life cycle analysis was conducted in parallel to this economic study and was used to determine environmental impacts of converting biomass to biocoal for blending in coal-fired power plants as well as the use of substantial flows of off-gasses produced in the torrefaction process. Sensitivity analysis of the financial rates of return of the different businesses has been performed to measure impacts of different factors, whether input prices, output prices, or policy measures that render costs or rewards for the businesses.

• 시스템엔지니어링학술지
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• 제16권2호
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• pp.1-15
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• 2020

Nuclear power plants in South Korea are operated to cover the baseload demand. Hence they are operated at 100% rated power and do not deploy power tracking control except for startup, shutdown, or during transients. However, as the contribution of renewable energy in the energy mix increases, load follow operation may be needed to cover the imbalance between consumption and production due to the intermittent nature of electricity produced from the conversion of wind or solar energy. Load follow operation may be quite challenging since the operators need to control the axial power distribution and core reactivity while simultaneously conducting the power maneuvering. In this paper, a systems engineering approach for multi-physics load follow simulation of APR1400 is performed. RELAP5/SCDAPSIM/MOD3.4/3DKIN multi-physics package is selected to simulate the Korean Advanced Power Reactor, APR1400, under load follow operation to reflect the impact of feedback signals on the system safety parameters. Furthermore, the systems engineering approach is adopted to identify the requirements, functions, and physical architecture to provide a set of verification and validation activities that guide this project development by linking each requirement to a validation or verification test with predefined success criteria.

• Nuclear Engineering and Technology
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• 제53권8호
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• pp.2696-2707
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• 2021

The purpose of this study is to investigate the efficiency of various structural modeling schemes for evaluating seismic performances and fragility of the reactor containment building (RCB) structure in the advanced power reactor 1400 (APR1400) nuclear power plant (NPP). Four structural modeling schemes, i.e. lumped-mass stick model (LMSM), solid-based finite element model (Solid FEM), multi-layer shell model (MLSM), and beam-truss model (BTM), are developed to simulate the seismic behaviors of the containment structure. A full three-dimensional finite element model (full 3D FEM) is additionally constructed to verify the previous numerical models. A set of input ground motions with response spectra matching to the US NRC 1.60 design spectrum is generated to perform linear and nonlinear time-history analyses. Floor response spectra (FRS) and floor displacements are obtained at the different elevations of the structure since they are critical outputs for evaluating the seismic vulnerability of RCB and secondary components. The results show that the difference in seismic responses between linear and nonlinear analyses gets larger as an earthquake intensity increases. It is observed that the linear analysis underestimates floor displacements while it overestimates floor accelerations. Moreover, a systematic assessment of the capability and efficiency of each structural model is presented thoroughly. MLSM can be an alternative approach to a full 3D FEM, which is complicated in modeling and extremely time-consuming in dynamic analyses. Specifically, BTM is recommended as the optimal model for evaluating the nonlinear seismic performance of NPP structures. Thereafter, linear and nonlinear BTM are employed in a series of time-history analyses to develop fragility curves of RCB for different damage states. It is shown that the linear analysis underestimates the probability of damage of RCB at a given earthquake intensity when compared to the nonlinear analysis. The nonlinear analysis approach is highly suggested for assessing the vulnerability of NPP structures.

• 대한전기학회논문지
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• 제34권8호
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• pp.308-316
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• 1985

This paper proposes an analytic tool for long-term generation expansion planning based on the maximum principle. Many research works have been performed in the field of generation expansion planning. But few works can be found with the maxinmum principle. A recently published one worked by professor Young Moon Park et al. shows remarkable improvements in modeling and computation. But this modeling allows only thermal units. This paper has extended Professor Park's model so that the optimal pumped-storage operation is taken into account. So the ability for practical application is enhanced. In addition, the analytic supply-shortage cost function is included. The maximum principle is solved by gradient search due to its simplicity. Every iteration is treated as if mathematical programming such that all controls from the initial to the terminal time are manipulated within the same plane. Proposed methodology is tested in a real scale power system and the simulation results are compared with other available package. Capability of proposed method is fully demonstrated. It is expected that the proposed method can be served as a powerful analytic tool for long-term generation expansion planning.