• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.60 no.2
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• pp.194-206
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• 2024

This study focuses on analyzing the energy-saving effects of the recirculation aquaculture system using seawater source heat pumps and solar power generation. Based on the thermal load analysis conducted using the transient system simulation tool, the annual energy consumption of the recirculation aquaculture system was analyzed and the energy-saving effects of utilizing the photovoltaic system was evaluated. When analyzing the heat load, the sea areas where the fish farms are located, the type of breeding tank, and the circulation rate of breeding water were taken into consideration. In addition, a method for determining the appropriate capacity for each operation time was examined when applying the energy storage system instead of the existing diesel generator as an emergency power, which is required to maintain the water temperature of breeding water during power outage. The results suggest that, among the four seas considered, Jeju should be estimated to achieve the highest energy-saving performance using the solar power generation, with approximately 45% energy savings.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.6
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• pp.361-368
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• 2018

This paper proposes a grid - connected CTTS system that can be soft switched to meet the government's effective resource allocation policy for emergency generator. In order to eliminate the system instability caused by the large inrush current generation in the system switching, a new virtual rotation coordinate method for the dissimilar power source is proposed. The proposed virtual rotation coordinate method improves the voltage detection accuracy of the voltage difference of the dissimilar power supply, and it is proved that the synchronous switching characteristic is excellent. In addition, zero current and system stabilization can be achieved by realizing zero current when blocking CTTS with instantaneous reactive power control. Simulation was carried out to verify the validity of the proposed method, and the 500[kVA] system was fabricated and verified to demonstrate the superiority of the proposed method.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.280-281
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• 2011

Special Protection Scheme(SPS) that operates scenarios about faults beyond the normally protective action is wide system protection technology for the purpose of wide areas protection. Therefore, the SPS focuses on the improvement of the power supply capability by protecting the system rather than protecting the system equipments. Since the SPS requires emergency operation, the operation schedule is set up in advance by analyzing various scenarios. Since the SPS's action scheme uses generator tripping and is a classical method it is presently the most powerful one. However, as the setting of SPS is set to the most severe disturbance, the scheme tends to trip more generators than required to prevent fault propagation. It is highly likely that tripping generator units to prevent fault propagation would result in difficulty of system management and possibility of load shedding. Accordingly, it is desirable that generators are connected to the system within the range that ensures system stability and intelligent SPS is currently under development to solve the problem being stated. In this paper, as a part of developing the intelligent SPS, application of the fast-valving and braking resistor scheme to the generators is being proposed and analysed to reduce the number of tripped generators.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.327-334
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• 2017

Common-cause failure (CCF) events can significantly impact the availability of safety systems of nuclear power plants. For this reason, the International Common Cause Data Exchange (ICDE) project was initiated by several countries in 1994. Since 1997 it has been operated within the Organisation for Economic Co-operation and Development (OECD)/Nuclear Energy Agency (NEA) framework and has successfully been operated over six consecutive terms (the current term being 2015-2017). The ICDE project allows multiple countries to collaborate and exchange CCF data to enhance the quality of risk analyses, which include CCF modeling. As CCF events are typically rare, most countries do not experience enough CCF events to perform meaningful analyses. Data combined from several countries, however, have yielded sufficient data for more rigorous analyses. The ICDE project has meanwhile published 11 reports on the collection and analysis of CCF events of specific component types (centrifugal pumps, emergency diesel generators, motor operated valves, safety and relief valves, check valves, circuit breakers, level measurement, control rod drive assemblies, and heat exchangers) and two topical reports. This paper presents recent activities and lessons learnt from the data collection and the results of topical analysis on emergency diesel generator CCF impacting entire exposed population.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2534-2546
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• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.141-146
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• 2024

Station blackout (SBO) risk is one of the most significant contributors to nuclear power plant risk. In this paper, the sequence probability formulas derived by the convolution approach are compared with those derived by the conventional event tree/fault tree (ET/FT) approach for the SBO situation in which emergency diesel generators fail to start. The comparison identifies what makes the ET/FT approach more conservative and raises the issue regarding the mission time of a turbine-driven auxiliary feedwater pump (TDP), which suggests a possible modeling improvement in the ET/FT approach. Monte Carlo simulations with up-to-date component reliability data validate the convolution approach. The sequence probability of an alternative alternating current diesel generator (AAC DG) failing to start and the TDP failing to operate owing to battery depletion contributes most to the SBO risk. The probability overestimation of the scenario in which the AAC DG fails to run and the TDP fails to operate owing to battery depletion contributes most to the SBO risk overestimation determined by the ET/FT approach. The modification of the TDP mission time renders the sequence probabilities determined by the ET/FT approach more consistent with those determined by the convolution approach.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.461-462
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• 2016

본 논문은 100kW 급 비상발전용 ESS 상용화 개발을 제안한다. 비상발전기란 전력계통이 정지되었을 때 발전장치를 구동시켜 전력을 생산하는 자가발전설비를 말한다. 제안하는 시스템은 2Level 전압형 100kW 급 비상발전용 ESS 로써 정상 시 계통 전원과 동기 운전을 수행하는 계통 연계형 전력변환장치이다. 수배전 수용가에 설치되어 운영이 가능하며 일반적인 ESS PCS 기능인 주파수 조정 (Frequency Regulation), 출력 안정화, 첨두부하 저감 (Peak Shaving), 부하평준화 (Load Leveling), 수요반응 (Demand Response)에 추가하여, 자가발전 (Black Start), 무효전력제어 등의 기능을 적용 하였다. 제안된 100kW 급 비상발전기용 ESS PCS 는 시뮬레이션 및 프로토 타입을 이용하여 성능을 검증하였다.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.5
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• pp.92-98
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• 2003

A wind turbine monitoring system is essential equipment fur the performance evaluation and mechanical load analysis of a wind turbine. A monitoring system using LabVIEW is developed in this study. This system monitors signals from a meteorological mast, wind turbine generator, and tower. The discrete signals which are sampled at t Hz are automatically saved on a data file in the unit of a day. Besides these basic functions, the developed monitoring system has the other several capabilities. One of them is the information access from a remote PC through the internet. A vision image of the test site area and data files that are produced by LabVIBW software can be uploaded to the main computer located in a remote site. An emergency backup system using UPS fur the power loss on the monitoring HW is also prepared, A detail explanation for the developed wind turbine monitoring system is presented in this study.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.582-588
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• 2018

Accident diagnosis is one of the complex tasks for nuclear power plant (NPP) operators. In abnormal or emergency situations, the diagnostic activity of the NPP states is burdensome though necessary. Numerous computer-based methods and operator support systems have been suggested to address this problem. Among them, the recurrent neural network (RNN) has performed well at analyzing time series data. This study proposes an algorithm for accident diagnosis using long short-term memory (LSTM), which is a kind of RNN, which improves the limitation for time reflection. The algorithm consists of preprocessing, the LSTM network, and postprocessing. In the LSTM-based algorithm, preprocessed input variables are calculated to output the accident diagnosis results. The outputs are also postprocessed using softmax to determine the ranking of accident diagnosis results with probabilities. This algorithm was trained using a compact nuclear simulator for several accidents: a loss of coolant accident, a steam generator tube rupture, and a main steam line break. The trained algorithm was also tested to demonstrate the feasibility of diagnosing NPP accidents.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1953-1954
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• 2008

The excitation system for class 1E has been developed to apply to the nuclear power plant emergency diesel generator by utilizing the existing digital excitation system. The additional mission was to evaluate the excitation system of safety. It is the safety analysis of the excitaton system, the verification test, the aging test, the safety requirement test and so on. The verification test is classified of hardware and software part for detail.