• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1093-1099
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• 2009

Alternative energy sources such as renewable energy like solar power systems, wind power systems, or fuel cell power systems has been the rising issue in the electrical power system. This paper discusses an economic study analysis of fuel cells in the korean electricity market. It includes the basic concept of a fuel cell and the korean electricity market. It also describes the need of renewable energy and how the fuel cell is connected with the local grid. This paper shows the impact of production and recovering thermal energy of a grid-connected fuel cell power system. The profit maximization approach has been structured including electrical power trade with the local grid and heat trade within the micro-grid. The strategies are evaluated using a local load that uses electric and thermal power which has different patterns between summer and winter periods. The solution algorithm is not newly developed one, but is solved by an application called GAMS. Results indicate the need and usefulness of a fuel cell power system.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.121-125
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• 2009

There have been many developed systems for harnessing the solar energy such as solar water heaters, solar thermal power systems, PV systems, daylighting and solar hydrogen systems. all of them are capable of reducing $CO_2$ emission. However, the efficiency of those systems which work without a solar tracker is lower. This paper is a step by step procedure for fabrication and a performance test of a solar tracking system. The system developed in this study consists of motion controllers, motor drives, step-motors, feedback devices and application. CdS sensors are introduced into the solar tracking system for playing a primary role in poor conditions for tracking due to a gear backlash and a strong wind. Mini-dish was used as a concentrator for collecting sun light. The solar position data, in terms of azimuth and elevation, sunrise and sunset times was compared with those of KASI(Korea Astronomy & Space Science Institute). The results presented in this article provide the high accuracy of the present system in solar tracking and indicate a potential for energy savings.

• Korean Journal of Organic Agriculture
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• v.10 no.1
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• pp.49-63
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• 2002

In order to supply 85% of total organic feed in ruminants and 80% in non-ruminants for organic animal production, nitrogen fixation ability of legume should be used in domestic roughages production. 50% of Europe organic farmer use intercropping legume in as green manure. This article is dealing with amount of biologically fixed nitrogen used by legumes and methods for estimating the transfer of biologically fixed N in rotation and separating the N benefit into fixed N and non-fixed N components are reviewed. Available data indicate that transfer amount of N to non legumes was from 50∼9.6(kg/ha) in legume-cereal rotations and proportion of legume N varied with seasons, 90% in summer, 50% in autumn. The important point in cropping system for legumes have to be included for organic forage production 6 year rotation is based on pasture system of 3 year pasture + 2 year annual(com, sudangrass), again pasture. Rye, barly and Italian ryegrass+legumes(vetch, crimson and pea) can be one of option in spring, com, soybean, sudangrass and Japanese bamyard millet would be seeded after spring harvest in the field. Farmer can make good use of rice paddy field as forge production potential area after harvesting rice. Italian, burly and rye+vetch and crimsonclover may be grown in autumn or spring time at the rice field.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.11
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• pp.1020-1028
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• 2011

As rotating machines play an important role in industrial applications such as aeronautical, naval and automotive industries, many researchers have developed various condition monitoring system and fault diagnosis system by applying artificial neural network. Since using obtained signals without preprocessing as inputs of neural network can decrease performance of fault classification, it is very important to extract significant features of captured signals and to apply suitable features into diagnosis system according to the kinds of obtained signals. Therefore, this paper proposes a neural-network-based fault diagnosis system using AR coefficients as feature vectors by LPC(linear predictive coding) and EIV(errors-in variables) analysis. We extracted feature vectors from sound, vibration and current faulty signals and evaluated the suitability of feature vectors depending on the classification results and training error rates by changing AR order and adding noise. From experimental results, we conclude that classification results using feature vectors by EIV analysis indicate more than 90 % stably for less than 10 orders and noise effect comparing to LPC.

• Journal of Energy Engineering
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• v.24 no.3
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• pp.74-81
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• 2015

Currently, the government is encouraging the introduction of energy storage system to reduce carbon emissions and peak power demand. The government is planning the cumulative capacity of ESS of 2GW in 2020. By utilizing charge and discharge of the ESS, it is possible to sell the surplus power to utility and electricity market. This paper suggests the model that economic feasibility of energy storage system for planning the construction of power generation facilities in 2035. Our results of simulation indicate the energy storage plan of utility for constructing renewable energy facilities is need to incentives from the government to encourage power utilities and expansion of ESS.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.486-495
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• 2009

This paper proposes a new methodology on reliability evaluation of a power system including solar cell generators (SCG). The SCGs using renewable energy resource such as solar radiation(SR) should be modeled as multi-state operational model because the uncertainty of the resource supply may occur an effect as same as the forced outage of generator in viewpoint of adequacy reliability of system. While a two-state model is well suited for modeling conventional generators, a multi-state model is needed to model the SCGs due to the random variation of solar radiation. This makes the method of calculating reliability evaluation indices of the SCG different from the conventional generator. After identifying the typical pattern of the SR probability distribution function(pdf) from SR actual data, this paper describes modelling, methodology and details process for reliability evaluation of the solar cell generators integrated with power system. Two test results indicate the viability of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.364-380
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• 2016

The most popular approach in object classification is based on the bag of visual-words model, which has several fundamental problems that restricting the performance of this method, such as low time efficiency, the synonym and polysemy of visual words, and the lack of spatial information between visual words. In view of this, an object classification based on weakly supervised E2LSH and saliency map weighting is proposed. Firstly, E2LSH (Exact Euclidean Locality Sensitive Hashing) is employed to generate a group of weakly randomized visual dictionary by clustering SIFT features of the training dataset, and the selecting process of hash functions is effectively supervised inspired by the random forest ideas to reduce the randomcity of E2LSH. Secondly, graph-based visual saliency (GBVS) algorithm is applied to detect the saliency map of different images and weight the visual words according to the saliency prior. Finally, saliency map weighted visual language model is carried out to accomplish object classification. Experimental results datasets of Pascal 2007 and Caltech-256 indicate that the distinguishability of objects is effectively improved and our method is superior to the state-of-the-art object classification methods.

• Journal of Satellite, Information and Communications
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• v.8 no.4
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• pp.17-20
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• 2013

In this study, we introduce an LED Driving circuit in order that the information state can indicate audio signal gain and radiate pattern of ultrasonic speaker system for a sign board. Ultrasonic speaker system decreases energy loss and transmits the sound farther. Ultrasonic speaker having such characteristics is useful in that it can be widely used in daily life. Additionally, Proposed LED circuit indicates the information state as linear LED brightness taken from interface of ultrasonic speaker system. Designed circuit is confirmed through $0.35{\mu}m$ CMOS process by Dong-bu.

• Structural Engineering and Mechanics
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• v.34 no.3
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• pp.351-366
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• 2010

A novel system identification and structural health assessment procedure of steel framed structures with semi-rigid connections is presented in this paper. It is capable of detecting damages at the local element level under normal operating conditions; i.e., serviceability limit state. The procedure is a linear time-domain system identification technique in which the structure responses are required, whereas the dynamic excitation force is not required to identify the structural parameters. The procedure tracks changes in the stiffness properties of all the elements in a structure. It can identify damage-free and damaged structural elements very accurately when excited by different types of dynamic loadings. The method is elaborated with the help of several numerical examples. The results indicate that the proposed algorithm identified the structures correctly and detected the pre-imposed damages in the frames when excited by earthquake, impact, and harmonic loadings. The algorithm can potentially be used for structural health assessment and monitoring of existing structures with minimum disruption of operations. Since the procedure requires only a few time points of response information, it is expected to be economic and efficient.

• Structural Engineering and Mechanics
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• v.61 no.2
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• pp.283-293
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• 2017

The main contribution of the present paper is to propose an intelligent fuzzy inference system approach for modeling the debonding strength of masonry elements retrofitted with Fiber Reinforced Polymer (FRP). To achieve this, the hybrid of meta-heuristic optimization methods and adaptive-network-based fuzzy inference system (ANFIS) is implemented. In this study, particle swarm optimization with passive congregation (PSOPC) and real coded genetic algorithm (RCGA) are used to determine the best parameters of ANFIS from which better bond strength models in terms of modeling accuracy can be generated. To evaluate the accuracy of the proposed PSOPC-ANFIS and RCGA-ANFIS approaches, the numerical results are compared based on a database from laboratory testing results of 109 sub-assemblages. The statistical evaluation results demonstrate that PSOPC-ANFIS in comparison with ANFIS-RCGA considerably enhances the accuracy of the ANFIS approach. Furthermore, the comparison between the proposed approaches and other soft computing methods indicate that the approaches can effectively predict the debonding strength and that their modeling results outperform those based on the other methods.