• International Journal of Contents
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• v.6 no.2
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• pp.10-13
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• 2010

For applications that are grid enabled, the grid can offer a resource balancing effect by scheduling grid jobs on machines with low utilization. When jobs communicate with each other, the internet, or with storage resources, an advanced scheduler could schedule them to minimize communications traffic or minimize the distance of the communications. We propose an intelligent load distribution algorithm to minimize communications traffic and distance of the communications using genetic algorithm. The experiments show the proposed load redistribution algorithm performs efficiently in the variance of load in grid environments.

• Journal of the Semiconductor & Display Technology
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• v.4 no.2 s.11
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• pp.25-32
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• 2005

This paper proposes a method for the intelligent load distribution of two cooperating robots(TCRs) using fuzzy logic. The proposed scheme requires the knowledge of the robots' dynamics, which in turn depend upon the characteristics of large flat panel displays(LFPDs) carried by the TCRs. However, the dynamic properties of the LFPD are not known exactly, so that the dynamics of the robots, and hence the required Joint torque, must be calculated for nominal set of the LFPD characteristics. The force of the TCRs is an important factor in carrying the LFPD. It is divided into external force and internal force. In general, the effects of the internal force of the TCRs are not considered in performing the load distribution in terms of optimal time, but they are essential in optimal trajectory planning; if they are not taken into consideration, the optimal scheme is no longer fitting. To alleviate this deficiency, we present an algorithm for finding the internal-force (actors for the TCRs in terms of optimal time. The effectiveness of the proposed system is demonstrated by computer simulations using two three-joint planner robot manipulators.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1776-1786
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• 2010

Intelligent distribution automation system have total monitoring and control capability. The system covers substation, distribution network, distributed generations and customers at HV system. Various intelligent distribution facilities installed at distribution systems have voltage sensor, current sensor, aging monitoring sensor. Intelligent Feeder Remote Terminal Unit (IFRTU) tied to intelligent distribution facilities process information from facilities and it checks information of fault, power quality and aging of distribution facilities. The information is transmitted to master station through communication line. The master station have remote monitoring system covers substation, distribution network, distributed generations and customers. It also have various application programs that maintain optimal network operation by using information from on-site devices.

• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2005.09a
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• pp.110-123
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• 2005

This paper proposes an intelligent method for the optimal load distribution of two cooperating robots(TCRs) using fuzzy logic. The proposed scheme requires the knowledge of the robots' dynamics, which in turn depend upon the characteristics of large flat panel displays(LFPDs) carried by the TCRs. However, the dynamic properties of the LFPD are not known exactly, so that the dynamics of the robots, and hence the required joint torque, must be calculated for nominal set of the LFPD characteristics. The force of the TCRs is an important factor in carrying the LFPD. It is divided into external force and internal force. In general , the effects of the internal force of the TCRs are not considered in performing the load distribution in terms of optimal time, but they are essential in optimal trajectory planning: if they are not taken into consideration, the optimal scheme is no longer fitting. To alleviate this deficiency, we present an algorithm for finding the internal-force factors for the TCRs in terms of optimal time. The effectiveness of the proposed system is demonstrated by computer simulations using two three-joint planner robot manipulators.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.9
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• pp.51-58
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• 2015

Intelligent distribution automation system includes operating a switchgear of distribution system remotely when switchgear are not available to operate quickly. This system makes it possible to reduce the interrupt time. It also aims to improve the reliability of customers. Currently, Intelligent distribution automation improves the reliability by replacing manual switchgear, which is installed as sectional switchgear. However the prioritization of the replacement for the switchgear is required for its intellectualization. Many studies have been conducted related with prioritization of switchgear replacement. But it is difficult to interpret and apply to the power distribution system. That is because most of the studies just considers customer numbers for prioritizing the replacement. In this paper presents an algorithm to determine the intelligent swichgear replacement priority considering customer number, load quantity and interruption cost. Further, this algorithm is verified by using system reliability index.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1059-1062
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• 1998

This paper which can simulate FRIENDS(Flexible Reliable Intelligent Electrical eNergy Delivery System) model of distribution electrical system presents a new algorithm. In the operation of FRIENDS model, dispersed energy storage(DES) systems have an important role. We can use the active and reactive power of DES to control customer's voltage. In this, the former means load levelling operation and the later means voltage control operation of DES. We focus our research on load levelling operation of DES. We develope an algorithm to get an optimal capacity and operation schedule of DES and then apply it to the FRIENDS model. The results show the effectiveness of the proposed method.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.111-119
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• 1996

In this paper, we propose time-optimal trajectory planning algorithms for cooperative multi-robot manipulators system considering optimal load distribution. Internal forces essentially effect on time optimal trajectory planning and if they are comitted, the time optimal scheme is not no longer true. Therefore, we try to find the internal force factors of cooperative robot manipulators system in a time-optimal aspect. In this approach, a specific generalized inverse is used and is fuzzified for the purpose. In this optimal method, the fuzzy logic concept is used and selected for diminishing computation time, for finding the load distribution factors.

• International Journal of Contents
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• v.3 no.1
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• pp.34-38
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• 2007

Load redistribution is a critical resource in computer system. In sender-initiated load redistribution algorithms, the sender continues to send unnecessary request messages for load transfer until a receiver is found while the system load is heavy. These unnecessary request messages result in inefficient communications, low CPU utilization, and low system throughput in distributed systems. To solve these problems, we propose a genetic algorithm based approach for improved sender-initiated load redistribution in distributed systems. Compared with the conventional sender-initiated algorithms, the proposed algorithm decreases the response time and task processing time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.741-747
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• 2008

This paper proposes a new concept of IDSP(Intelligent Digital Switchgear Panel) which can solve the problem of the safety, the reliability and the convenience to correspond to the requirement of the general electric customer or electric power company under the ubiquitous-based home automation environments. By analyzing their requirement functions, a 32-bit micro processor is adopted as main controller to support the designed functions efficiently. The DSP-based single phase power management device is utilized to collect the electric power information and the ethernet convertor to communicate through internet among the IDSPs and the remote computer system. In the proposed IDSP, the several functions are implemented such as the earth leakage level display and waveform transmission, the electric fee display, the voltage management, the load management and the load control function. Finally, the prototype of the IDSP is made experimently based on the designed results, and then the effectiveness is verified by testing its basic functions.