• Proceedings of the Korea Water Resources Association Conference
• /
• 2018.05a
• /
• pp.373-373
• /
• 2018

화력발전소, 석유화학공단 등 대규모 배출원에서 발생되는 이산화탄소를 활용하여 온실가스의 배출을 줄이고, 경제적 가치를 창출할 수 있는 탄소자원화는 기후변화 대응을 위한 국가전략프로젝트 중 하나이다. 전 세계적으로 탄소자원화 기술은 아직 상용화 단계이지만 최근 강화된 온실가스 감축 의무로 인하여 탄소자원화 시장은 더욱 확대될 전망이다. 화력발전소의 이산화탄소 발생 과정에서 배출되는 수증기는 응축기술을 통하여 새로운 수원으로 활용이 가능하다. 응축된 물의 최적 활용과 사용처 지향적 효율적 물순환을 위한 시설 내 스마트 워터 그리드(SWG) 개념의 물분배 시스템은 발전 산업 내에 탄소자원화의 핵심기술로 사용될 수 있다. SWG는 시설 내 용수공급 관리에서의 관망 운영, 물 수요 관리 등 ICT를 활용한 종합적인 물 분배 시스템으로, 본 연구에서는 SWG 물순환 시스템의 국내외 기술조사를 통해 발전 산업 시설 내에 적용성을 검토하였다. 물의 재이용 시스템을 포함한 SWG 기술, 지능형 관망 운영 기법 기술, 실시간 수질 감시 체계 기술 연구를 기반으로, ICT 기반 용수공급 정보 관리 기술과 수운영 모니터링 기술을 통하여 SWG가 발전 산업 연계 기술로써 적용될 수 있도록 하였다. 본 연구에서 제시된 SWG 시스템을 적용한 산업 인프라를 통하여 산업적 파급 효과를 높이고, 이를 활용한 인력과 비용 절감이 기대되며, 저에너지, 고효율화를 위한 기술력과 글로벌 물 시장진출 경쟁력을 향상시키기 위한 기초연구자료로써 활용이 가능할 것으로 기대된다.

• Journal of Information Processing Systems
• /
• v.15 no.2
• /
• pp.386-398
• /
• 2019

The transmission capacity of transmission lines is affected by environmental parameters such as ambient temperature, wind speed, wind direction and so on. The environmental parameters can be measured by the installed measuring devices. However, it is impossible to install the environmental measuring devices throughout the line, especially considering economic cost of power grid. Taking into account the limited number of measuring devices and the distribution characteristics of environment parameters and transmission lines, this paper first studies the environmental parameter estimating method of inverse distance weighted interpolation and ordinary Kriging interpolation. Dynamic thermal rating of transmission lines based on IEEE standard and CIGRE standard thermal equivalent equation is researched and the key parameters that affect the load capacity of overhead lines is identified. Finally, the distributed thermal rating of transmission line is realized by using the data obtained from China meteorological data network. The cost of the environmental measurement device is reduced, and the accuracy of dynamic rating is improved.

• Journal of Information Processing Systems
• /
• v.15 no.2
• /
• pp.331-343
• /
• 2019

Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambient temperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty is an important parameter to evaluate the reliability of measurement results. This paper presents the uncertainty analysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probability density function of the input parameter value, the probability density function of the output value is determined by probability distribution random sampling. Through the calculation and analysis of the transient thermal balance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, the transient current carrying capacity, the standard uncertainty and the probability distribution of the minimum and maximum values of the conductor under 95% confidence interval are obtained. The simulation results indicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, and increase the validity and reliability of the uncertainty evaluation.

• Journal of Hydrogen and New Energy
• /
• v.29 no.6
• /
• pp.606-619
• /
• 2018

This study focuses on the performance of hydrogen energy based hybrid system in terms of system reliability of electricity generation. With this aim to evaluate the off-grid system of photovoltaic (PV), wind turbine, electrolyzer, fuelcell, $H_2$ tank and storage batteries, 14 different sites in South Korea are simulated using HOMER. Performance analysis includes simulation on the different sites, verification of operational behaviors on regional and seasonal basis, and comparison among a control group. The result shows that the generation performance of hydrogen powered fuelcell is greatly affected by geographical change rather than seasonal effect. In addition, as the latitude of the hybrid systems location decrease, renewable power output and penetration ratio (%) increase under constant electrical load. Therefore, the hydrogen based hybrid system creates the stability of electricity generation, which best suits in the southern part of South Korea.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.96-98
• /
• 2014

Wireless Sensor Network(WSN) is a wireless real-time information(Acquired from the sensor nodes that have the computing power and wireless communication capabilities.) collected, and to take advantage of processing techniques. Currently it is very diverse, such as environmental monitoring, health care, security, smart home, smart grid applications is that. Thus it is required in the wireless sensor network, the algorithm for the efficient use of the limited energy capacity. Suggested by the algorithm for selecting a cluster head node for a hybrid type and clustered, by comparing the amount of energy remaining and a connection between the nodes In this paper, we aim to increase efficiency and accuracy of the wireless sensor network.

• Journal of IKEEE
• /
• v.25 no.1
• /
• pp.109-115
• /
• 2021

In this paper, the fine dust detecting terminal which can transmit data in real time was developed. The terminal used a wide spreading LTE network and was powered by solarcell and battery for easy installation and independent operation, because it did not need the wired power grid or wired communication network. The data showed the possibility of forecasting fine dust changes by analyzing with the data from public meteorologic data. The developed terminal will be helpful for predicting and analyse fine dust's more precise flow and effect on environment with an easy installation on any places.

• Electronics and Telecommunications Trends
• /
• v.36 no.3
• /
• pp.76-86
• /
• 2021

Technologies for lithium secondary batteries are now increasingly expanding to simultaneously improve the safety and higher energy and power densities of large-scale battery systems, such as electric vehicles and smart-grid energy storage systems. Next-generation lithium batteries, such as lithium-sulfur (Li-S) and lithium-air (Li-O₂) batteries by adopting solid electrolytes and lithium metal anode, can be a solution for the requirements. In this analysis of battery technology trends, solid electrolytes, including polymer (organic), inorganic (oxides and sulfides), and their hybrid (composite) are focused to describe the electrochemical performance achievable by adopting optimal components and discussing the interfacial behaviors that occurred by the contact of different ingredients for safe and high-energy lithium secondary battery systems. As next-generation rechargeable lithium batteries, Li-S and Li-O₂ battery systems are briefly discussed coupling with the possible use of solid electrolytes. In addition, Electronics and Telecommunications Research Institutes achievements in the field of solid electrolytes for lithium rechargeable batteries are finally introduced.

• Genomics & Informatics
• /
• v.20 no.2
• /
• pp.16.1-16.12
• /
• 2022

Various methodologies for the genetic analysis of longitudinal data have been proposed and applied to data from large-scale genome-wide association studies (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with traits of interest and to detect SNP-time interactions. We recently proposed a grid-based Bayesian mixed model for longitudinal genetic data and showed that our Bayesian method increased the statistical power compared to the corresponding univariate method and well detected SNP-time interactions. In this paper, we further analyze longitudinal obesity-related traits such as body mass index, hip circumference, waist circumference, and waist-hip ratio from Korea Association Resource data to evaluate the proposed Bayesian method. We first conducted GWAS analyses of cross-sectional traits and combined the results of GWAS analyses through a meta-analysis based on a trajectory model and a random-effects model. We then applied our Bayesian method to a subset of SNPs selected by meta-analysis to further discover SNPs associated with traits of interest and SNP-time interactions. The proposed Bayesian method identified several novel SNPs associated with longitudinal obesity-related traits, and almost 25% of the identified SNPs had significant p-values for SNP-time interactions.

• Nuclear Engineering and Technology
• /
• v.53 no.8
• /
• pp.2708-2715
• /
• 2021

The Multi-Purpose Overload Robot (CMOR) is a key subsystem of China Fusion Engineering Test Reactor (CFETR) remote handling system. Due to the long cantilever and large loads of the CMOR, it has a large rigid-flexible coupling deformation that results in a poor position accuracy of the end-effector. In this study, based on the Levenberg-Marquardt algorithm, the spatial grid, and the linearized variable load principle, a variable parameter compensation model was designed to identify the parameters of the CMOR's kinematics models under different loads and at different poses so as to improve the trajectory tracking accuracy. Finally, through Adams-MATLAB/Simulink, the trajectory tracking accuracy of the CMOR's rigid-flexible coupling model was analyzed, and the end position error exceeded 0.1 m. After the variable parameter compensation model, the average position error of the end-effector became less than 0.02 m, which provides a reference for CMOR error compensation.

• Journal of Drive and Control
• /
• v.19 no.3
• /
• pp.9-15
• /
• 2022

This paper proposes a method for constructing and verifying datasets used in deep learning technology, to prevent safety accidents in automated construction machinery or autonomous vehicles. Although open datasets for developing image recognition technologies are challenging to meet requirements desired by users, this study proposes the interface of virtual simulators to facilitate the creation of training datasets desired by users. The pixel-level training image dataset was verified by creating scenarios, including various road types and objects in a virtual environment. Detecting an object from an image may interfere with the accurate path determination due to occlusion areas covered by another object. Thus, we construct a database, for developing an occlusion area detection algorithm in a virtual environment. Additionally, we present the possibility of its use as a deep learning dataset to calculate a grid map, that enables path search considering occlusion areas. Custom datasets are built using the RDBMS system.