• Journal of Communications and Networks
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• v.7 no.4
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• pp.438-449
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• 2005

In this paper, we describes the information-theoretic approaches to sensor selection and sensor placement in sensor net­works for target localization and tracking. We have developed a sensor selection heuristic to activate the most informative candidate sensor for collaborative target localization and tracking. The fusion of the observation by the selected sensor with the prior target location distribution yields nearly the greatest reduction of the entropy of the expected posterior target location distribution. Our sensor selection heuristic is computationally less complex and thus more suitable to sensor networks with moderate computing power than the mutual information sensor selection criteria. We have also developed a method to compute the posterior target location distribution with the minimum entropy that could be achieved by the fusion of observations of the sensor network with a given deployment geometry. We have found that the covariance matrix of the posterior target location distribution with the minimum entropy is consistent with the Cramer-Rao lower bound (CRB) of the target location estimate. Using the minimum entropy of the posterior target location distribution, we have characterized the effect of the sensor placement geometry on the localization accuracy.

• Journal of Power Electronics
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• v.12 no.5
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• pp.813-820
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• 2012

This paper presents the development of a software supported acquisition system for metrological verification and testing of the equipment for monitoring and analysis of the basic electrical power quality parameters. The described procedure consists of two functionally connected segments. The first segment involves generation of the reference three-phase voltage signals, including the possibility of simulation of the various power quality disturbances, typical for electrical power distribution networks. The second part of this procedure includes the real-time recording of power quality disturbances in three-phase distribution networks. The procedure is functionally supported by the virtual instrumentation concept, including a software application developed in LabVIEW environment and data acquisition boards NI 6713 and NI 9215A. The software support of this system performs graphical presentation of the previously generated and recorded signal waveforms. A number of the control functions and buttons, implemented on the virtual instrument front panels, are provided to adjust the basic signal acquisition, generation and recording parameters.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.342-344
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• 2003

This paper describes the correction of overcurrent protective relaying set value in distribution networks interconnected with wind farm by dedicated line. The wind farm composed of wind turbine generators is one of the great energy sources; however, it would be also highly possible that the current in the point of common coupling is influenced by the output power of wind farm. So, the overcurrent relay applied in distribution feeders might generate trip signal for normal operation. In order to prevent the mal-operation of overcurrent relay, it is necessary to correct the relay's setting value according to the output power of end farm. This paper presents the influence of wind farm on the overcurrent relaying set value in distribution feeders for cases of fault as well as normal operation and proposes the basic strategy for correction of overcurrent relaying set value.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.2
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• pp.245-251
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• 2016

Despite the exponential throughput improvement in mobile communications systems, their ability to satisfy requirements of state-of-the-art and future applications of advanced metering infrastructure (AMI) is still under investigation. Challenges are mainly due to the inadequacy of third generation partnership project (3GPP) networks to support large amounts of devices simultaneously, while the number of AMI end-devices and the frequency of their data transmission increase with new AMI-based applications. In this introductory survey, innovative and future AMI applications and their communication requirements are first reviewed. Then, we identify challenges of 3GPP long term evolution (LTE) in enabling future AMI applications. More importantly, the latest improvements to LTE-A standard release 12 and 13 are reviewed and analyzed with regards to their potential to improve the quality of LTE-enabled AMI. It is found that 3GPP enhancements on machine type communications (MTC) standards will significantly enhance AMI communications. Beyond MTC specifications, non-MTC-specific enhancements such as carrier aggregation and multi-connectivity for user equipment will also contribute greatly to improving reliability and availability of AMI devices. The paper's focus is towards improved backhaul support for innovative and future AMI applications, beyond traditional automatic meter reading.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.608-619
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• 2018

As distributed generation (DG) is connected to grid, there is new node-type occurring in distribution network. An efficient algorithm is proposed in this paper to calculate power flow for weakly meshed distribution network with DGs in different load models. The algorithm respectively establishes mathematical models focusing on the wind power, photovoltaic cell, fuel cell, and gas turbine, wherein the different DGs are respectively equivalent to PQ, PI, PQ (V) and PV node-type. When dealing with PV node, the algorithm adopts reactive power compensation device to correct power, and the reactive power allocation principle is proposed to determine reactive power initial value to improve convergence of the algorithm. In addition, when dealing with the weakly meshed network, the proposed algorithm, which builds path matrix based on loop-analysis and establishes incident matrix of node voltage and injection current, possesses good convergence and strong ability to process the loops. The simulation results in IEEE33 and PG&G69 node distribution networks show that with increase of the number of loops, the algorithm's iteration times will decrease, and its convergence performance is stronger. Clearly, it can be effectively used to solve the problem of power flow calculation for weakly meshed distribution network containing different DGs.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.8
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• pp.898-903
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• 2004

In this paper, neural networks is studied to apply as a PD source classification in XLPE power cable specimen. For treeing discharge sources in the specimen, three defected models are made. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different models of discharge sources. And also these parameter is applied to classify PD sources by neural networks. Neural Networks has good recognition rate for three PD sources.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.279-281
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• 2001

This paper presents a chaotic neural networks to solve the distribution feeder reconfiguration problem for loss reduction. Feeder reconfiguration problem is the determination of switching option that minimizes the power losses for a particular set of loads in distribution systems. A chaotic neural networks is used to determine the switching combinations, select the status of the switches, and find the best combination of switches for minimum loss. The proposed method has been tested on 32 bus system, and the results indicate that it is able to determine the appropriate switching options for optimal configuration.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.915-917
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• 1998

Optimal routing of distribution networks can be attained by keeping the line power capacity limit to handle load requirements, acceptable voltage at customer loads, and the reliability indices such as SAIFI, SAIDI, CAIDI, and ASAI limits. This method is composed of optimal loss reduction and optimal reliability cost reduction. The former is solved relating to the conductor resistance of all alternative routes, and the latter is solved relating to the failure rate and duration of each alternative route. The routing considering optimal loss only and both optimal loss and optimal reliability cost are compared in this paper. The results showed that reliability cost should be considered as well as loss reduction to achieve the optimal routing in the distribution networks.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.3
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• pp.149-153
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• 2022

The degree distribution of the plant-pollinator network was identified by analyzing the data in the ecosystem and reproduced by a model of the growing bipartite mutualistic networks. The degree distribution of pollinator shows power law or stretched exponential distribution, while plant usually shows stretched exponential distribution. In the growth model, the plant and the pollinator are selected with probability P_p and P_A=1-P_p, respectively. The number of incoming links for the plant and the pollinator is l_p and l_A, respectively. The probability that the link of the plant selects the pollinator of the existing network given as $A_{k_i}=k^{{\lambda}_A}_i/{\sum}_i\;k^{{\lambda}_A}_i$, and the probability that the pollinator selects the plant is $P_{k_i}=k^{{\lambda}_p}_i/{\sum}_i\;k^{{\lambda}_p}_i$. When the nonlinear growth index is 𝛌_X=1 (X=A or P), the degree distribution follows a power law, and if 0≤𝛌_X<1, the degree distribution follows a stretched exponential distribution. The cumulative degree distributions of plants and pollinators of 14 empirical plant-pollinators included in Interaction Web Database were calculated. A set of parameters (P_A,P_P,l_A,l_P) that reproduces these cumulative degree distributions and a growth index 𝛌_X (X=A or P) were obtained. We found that animal takes very heterogenous connections, whereas plant takes a more flexible connection network.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.712-718
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• 2013

With the development of industry and the improvement of living standards, better quality in power electric service is required more than ever before. This paper deals with the optimal algorithms for voltage regulation in the case where Distributed Storage and Generation (DSG) systems are operated in distribution systems. It is very difficult to handle the interconnection issues for proper voltage managements, because the randomness of the load variations and the irregular operation of DSG should be considered. This paper proposes the optimal on-line real time voltage regulation methods in power distribution systems interconnected with the DSG systems. In order to deliver suitable voltage to as many customers as possible, the optimal sending voltage should be decided by the effective voltage regulation method by using artificial neural networks to consider the rapid load variation and random operation characteristics of DSG systems. The simulation results from a case study show that the proposed method can be a practical tool for the voltage regulation in distribution systems including many DSG systems.