• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.15 no.3
• /
• pp.67-73
• /
• 2001

This paper resents a developed measuring device of resistive leakage current and a fundamental discussion of deterioration diagnosis for Zinc Oxide(ZnO) arrester blocks. We have developed the leakage current detection device for ageing test and durability evaluation for ZnO arrester blocks. The resistive leakage current can be used as an indicator to discriminate whether the ZnO arrester blocks is in good state or in bad. The resistive leakage current measuring system with the compensation circuit was designed and fabricated. The sauce tests for ZnO arrester blocks were investigated by observing the resistive leakage current together with fast Fourier transform analysis. The proposed monitoring systems for the resistive leakage current can effectively be used to investigate the electrophysical properties of ZnO arrester blocks in laboratory and to develop the techniques of forecasting the deterioration of ZnO arresters in electric power systems.

• Journal of IKEEE
• /
• v.23 no.1
• /
• pp.134-142
• /
• 2019

As the development of internet of energy (IoE) technologies and spread of various electronic devices have diversified patterns of energy consumption, the reliability of demand prediction has decreased, causing problems in optimization of power generation and stabilization of power supply. In this study, we propose a deep learning method, 1-Dimention-Convolution and Bidirectional Long Short-Term Memory (1D-ConvBLSTM), that combines a convolution neural network (CNN) and a Bidirectional Long Short-Term Memory(BLSTM) for highly reliable demand forecasting by effectively extracting the energy consumption pattern. In experimental results, the demand is predicted with the proposed deep learning method for various number of learning iterations and feature maps, and it is verified that the test data is predicted with a small number of iterations.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.3
• /
• pp.100-115
• /
• 2020

The manufacturing-oriented mobility system is being reorganized around the future mobility system represented by electrification, sharing, and autonomy, driven by the social demand for sustainable development. Changes in future mobility systems are expected to accelerate thanks to advances in IT technology. To this end, this study conducted an expert survey (N=23) to predict the direction of changes in the future mobility system. Through the survey, 'mobility sharing' was selected as a key factor in the future mobility system among four future mobility. In addition, 'safety' was selected as the most important service factors in future mobility system among eight future mobility service factors. We hope that the results of this study will be used as basic information to design policies and service directions of preparation for the future mobility system.

• Journal of the Korean Wood Science and Technology
• /
• v.48 no.6
• /
• pp.917-935
• /
• 2020

In this study, an automated sensor to measure forest fire surface fuel moistures was developed to predict changes in the moisture content and risk of forest fire surface fuel, which was indicators of forest fire occurrence and spread risk. This measurement sensor was a method of automatically calculating the moisture content of forest fire surface fuel by electric resistance. The proxy of forest fire surface fuel used in this sensor is pine (50 cm long, 1.5 cm in diameter), and the relationship between moisture content and electrical resistance, R(R:Electrical resistance)=2E(E:Exponent of 10)+13X(X:Moisture content)-9.705(R²=0.947) was developed. In addition, using this, the software and case of the automated measurement sensor for forest fire surface fuel moisture were designed to produce a prototype, and the suitability (R²=0.824) was confirmed by performing field monitoring verification in the forest. The results of this study would contribute to develop technologies that can predict the occurrence, spread and intensity of forest fires, and are expected to be used as basic data for advanced forest fire risk forecasting technologies.

• Journal of Korea Technology Innovation Society
• /
• v.13 no.3
• /
• pp.558-586
• /
• 2010

This paper analyze the economic effect of R&D investment for the IT Green growth initiatives in Korea, relating to Green growth which is main force for activating in order to durable growth currently. The IT green growth initiatives can be grouped by IT manufacture, IT service, and S/W and computer-related services in the R&D investment and to be analyzed by the RAS forecasting methods. The results indicate that the production-inducing effect is about 31,853 billion won for the IT manufacture, and IT service is about 14,360 billion won, and the next is S/W and computer-related service whose effect is about 4,482 billion won. The import, value added, and employment effect of IT manufacture is also bigger than those of any other sectors in IT. This is because R&D investment in case of IT manufacture is more huge than IT service. Besides, employment-inducing effects show that IT manufacture is highest in 16,596 persons; IT service is secondly highest in 9,000 persons and S/W; lastly, computer-related service is much lower than those of any other sector. So we can conjecture that the long-term initiatives of IT green growth implementation lead to increasing size of benefits in the IT sectors.

• Korean Journal of Construction Engineering and Management
• /
• v.16 no.1
• /
• pp.74-81
• /
• 2015

As one of urban infrastructure system, the electricity substation is critical for urban life and industrial activity as the electricity demands get higher than ever. However the substation is generally regarded as unpleasant or dangerous facility, which finally results in the continuous opposition movement by resident due to the belief of unidentified negative effect in apartment prices. Accordingly, as the scientifically objective and quantitative analysis is required to solve the social conflict, this study intends to examine the variation affected by urban infrastructure system, expecially for substation. After the independent variable defining the price of apartment and the dependent variable, which is apartment price, are identified and their spatial data has been filed, the forecasting model has been developed through the hedonic price function as well as artificial neural networks system. The research finding indicated that the spatial range affected by substation is not notable and the range of some case was applicable for less than 600m. It is expected that these research findings can be applied for establishing the one of solid cases for the analysis of economical effect to local housing market by the urban infrastructure system.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.2
• /
• pp.187-192
• /
• 2019

Hybrid power storage system with emergency power function for demand management and power outage minimizes the investment cost in the building of buildings and factories requiring emergency power generation facilities, We propose a new business model by developing technology that can secure economical efficiency by reducing power cost at all times. Normally, system power is supplied to load through STS (Static Transfer Switch), and PCS is connected to system in parallel to perform demand management. In order to efficiently operate the electric power through demand forecasting, the EMS issues a charge / discharge command to the ESS as a PMS (Power Management System), and the PMS transmits the command to the PCS controller to operate the system. During the power outage, the STS is rapidly disengaged from the system, and the PCS becomes an independent power supply and can supply constant voltage / constant frequency power to the load side. Therefore, it is possible to secure reliability through verification of actual system linkage and independent operation performance of hybrid ESS, By enabling low-carbon green growth technology to operate in conjunction with an efficient grid, it is possible to improve irregular power quality and contribute to peak load by generating renewable energy through ESS linkage. In addition, the ESS is replacing the frequency follow-up reserve, which is currently under the charge of coal-fired power generation, and thus it is anticipated that the operation cost of the LNG generator with high fuel cost can be reduced.