• KEPCO Journal on Electric Power and Energy
• /
• v.2 no.1
• /
• pp.121-125
• /
• 2016

KEPCO has completed the installation and demonstration of a 52 MW battery energy storage system (BESS) for frequency regulation. Especially, 24 MW BESS is for Automatic Generation Control (AGC) in Shin-Yongin substation. Recently, KEPCO Research Institute has operated it connected to EMS of KPX. This paper discussed the operation strategy of EMS through a study on using 24 MW BESS in AGC operation and propose the improvement of AGC target. It is expected that this paper helps a safe and reliable operation and control of ESS for AGC through its continuous update.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.3
• /
• pp.848-858
• /
• 2014

In this paper the construction of a model that represents the behavior of an Electric Vehicle is described. Both the mechanical and the electric traction systems are represented using Multi-Bond Graph structural approach suited to model large scale physical systems. Then the model of the controllers, represented with a functional approach, is included giving rise to an integrated model which exploits the advantages of both approaches. Simulation and experimental results are aimed to illustrate the electromechanical interaction and to validate the proposal.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.917-919
• /
• 2003

This paper demonstrates that RADARSAT ScanSAR data can be an important data source of radar remote sensing for monitoring crop systems and estimation of rice yield for large areas in tropic and sub-tropical regions. Experiments were carried out to show the effectiveness of RADARSAT ScanSAR data for rice yield estimation in whole province of Guangdong, South China. A methodology was developed to deal with a series of issues in extracting rice information from the ScanSAR data, such as topographic influences, levels of agro-management, irregular distribution of paddy fields and different rice cropping systems. A model was provided for rice yield estimation based on the relationship between the backscatter coefficient of multi-temporal SAR data and the biomass of rice.

• Proceedings of the KIEE Conference
• /
• 2004.11b
• /
• pp.78-82
• /
• 2004

This paper suggests the power system reliability evaluation fur transmission lines planning in composite power systems. In recent the importance and necessity of some studies on reliability evaluation of grid comes from the recent black-out accidents occurred in the world. Since probabilistic criterion can reflect recognize the probabilistic nature of system components, the application of probabilistic criterion has received a lot of attention. This paper introduces features and operation modes of the Transmission Reliability Evaluation fur Large-Scale Systems(TRELSS) Version 6.2, a program made in EPRI, for assessing reliability indices of composite power system. The characteristics of the TRELSS program are illustrated by the case studies using the KEPCO system.

• Journal of Korean Society of Transportation
• /
• v.12 no.3
• /
• pp.49-64
• /
• 1994

The development of a mathematical modular framework based on Petri Network theory to model a traffic network is the subject of this paper. Traffic intersections are the primitive elements of a transportation network and are characterized as event driven and asynchronous systems. Petri network have been utilized to model these discrete event systems; further analysis of their structure can reveal information relevant to the concurrency, parallelism, synchronization, and deadlock avoidance issuse. The Petri-net based model of a generic traffic junction is presented. These modular networks are effective in synchronizing their components and can be used for modeling purposes of an asynchronous large scale transportation system. The derived model is suitable for simulations on a multiprocessor computer since its program execution safety is secured. The software pseudocode for simulating a transportation network model on a multiprocessor system is presented.

• 한국신재생에너지학회:학술대회논문집
• /
• 2006.06a
• /
• pp.584-587
• /
• 2006

An energy generating greenhouse based on fluoropolymer envelope and fresnel lens is proposed. The outstanding properties of the fluoropolymer films make them very suitable for large scale solar applications. Extremely high optical transmission over the whole solar spectrum, combined with mechanical strength, and durability allows us to design a highly optimized greenhouses for both plant growing and energy generation. Systems such as photovoltaic triple junction cells are especially attractive since they have up to 35% efficiency with much less cell material when the sun beam is focused with concentrators such as fresnel lenses. Cooling such devices will enhance the efficiency and provide useful thermal energy that could be further utilized for various applications depending on the local demands. This article introduces the basic ideas and principles of the energy generating greenhouses as a first step towards the actual deployment of such systems under Korean environment.

• Proceedings of the Earthquake Engineering Society of Korea Conference
• /
• 2006.03a
• /
• pp.563-570
• /
• 2006

Distributed control architecture is based on sharing control and data between multiple nodes on a network Communication and task sharing can be distributed between multiple control computers. Although many communication protocols exist, such as TCP/IP and UDP, they do not have the determinism that realtime control demands. Fiber-optic reflective shared memory creates the opportunity for realtime distributed control. This architecture allows control and computational tasks to be divided between multiple systems and operate in a deterministic realtime environment. One such shared memory architecture is based on Curtiss-Wright ScramNET family of fiber-optic reflective memory. MTS has built seismic and structural control software and hardware capable of utilizing ScramNET shared memory, opening up infinite possibilities in research and new capabilities in Hybrid and Model-In-The-Loop control.

• Structural Engineering and Mechanics
• /
• v.10 no.4
• /
• pp.313-336
• /
• 2000

The focus of this paper is on the development and implementation of a methodology for automated design of discrete structural systems. The research is aimed at utilizing Genetic Algorithms (GA) as an automated design tool. Several key enhancements are made to the simple GA in order to increase the efficiency, reliability and accuracy of the methodology for code-based design of structures. The AISC-ASD design code is used to illustrate the design methodology. Small as well as large-scale problems are solved. Simultaneous sizing, shape and topology optimal designs of structural framed systems subjected to static and dynamic loads are considered. Comparisons with results from prior publications and solution to new problems show that the enhancements made to the GA do indeed make the design system more efficient and robust.

• Journal of Multimedia Information System
• /
• v.8 no.1
• /
• pp.57-60
• /
• 2021

Industry 4.0 is continuous automation by applying the latest smart technologies to traditional manufacturing industries. It means that large-scale M2M (Machine-to-Machine) communication and IoT (Internet of Things) technologies are well integrated to build efficient production systems by analyzing and diagnosing various issues without human intervention. Edge computing is widely used for M2M services that handle real-time interactions between devices at industrial machinery tool sites. Here, secure data transmission is required while interacting. Thus, this paper focused on a method of creating and maintaining secret key and security tag used for message authentication between end-devices and edge-device.

• International Journal of Internet, Broadcasting and Communication
• /
• v.14 no.2
• /
• pp.192-198
• /
• 2022

Companies are building and utilizing their own data analysis systems according to business characteristics in the distributed cloud. However, as businesses and data types become more complex and diverse, the demand for more efficient analytics has increased. In response to these demands, in this paper, we propose an unsupervised learning-based data analysis agent to which reinforcement learning is applied for effective data analysis. The proposal agent consists of reinforcement learning processing manager and unsupervised learning manager modules. These two modules configure an agent with k-means clustering on multiple nodes and then perform distributed training on multiple data sets. This enables data analysis in a relatively short time compared to conventional systems that perform analysis of large-scale data in one batch.