• Journal of Electrical Engineering and Technology
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• 제11권3호
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• pp.551-559
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• 2016

The present trend of increasing the penetration levels of Distributed Generator (DG) in the distribution network has made the issue of Islanding crucial for the reliable operation of the network. The islanding, if not detected early may lead to the collapse of the system as it can drive the distribution system to the cascaded failure. In this paper, an extensive study of the effect of DG placement and sizing is performed by dividing the system into different zones to obtain a reduced effect of islanding. The siting and sizing of DG is carried out to improve the overall voltage profile or/and reduction in active power loss using two stage Genetic Algorithm (GA). In the first stage a basic knockout selection is considered and the best population is taken for next stage, where roulette selection for crossover and mutation is performed for optimal placement and sizing of DGs. The effect of the islanding, due to load variations is reduced by optimal siting and sizing of DG. The effectiveness of the proposed scheme is tested on the IEEE 33 and 69 radial bus systems and the results obtained are promising.

• 제어로봇시스템학회논문지
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• 제4권3호
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• pp.342-348
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• 1998

A majority of industrial robots are controlled by a simple joint servo control of joint actuators. In this type of control, the performance of control is greatly influenced by the joint interaction torques including Coriolis and centrifugal forces, which act as disturbance torques to the control system. As the speed of the robot increases, the effect of this disturbance torque increases, and hence makes the high speed - high precision control more difficult to achieve. In this paper, the joint disturbance torque of robots is analyzed. The joint disturbance torque is defined using the coefficients of dynamic equation of motion, and for the case of a 2 DOF planar robot, the conditions for the minimum and maximum joint disturbance torques are identified, and the effect of link parameters and joint variables on the joint disturbance torque are examined. Then, a solution to the optimal path placement problem is propose that minimizes the joint disturbance torque during a straight line motion. The proposed method is illustrated using computer simulation. The proposed solution method can be applied to a class of robots that are controlled by independent joint servo control, which includes the vast majority of industrial robots.

• Smart Structures and Systems
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• 제12권3_4호
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• pp.235-250
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• 2013

Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale structures. According to the mathematical background and implicit assumptions made in the triaxial effective independence (EfI) method, this paper presents a novel multi-dimensional OSP method for the Canton Tower focusing on application demands. In contrast to existing methods, the presented method renders the corresponding target mode shape partitions as linearly independent as possible and, at the same time, maintains the stability of the modal matrix in the iteration process. The modal assurance criterion (MAC), determinant of the Fisher Information Matrix (FIM) and condition number of the FIM have been taken as the optimal criteria, respectively, to demonstrate the feasibility and effectiveness of the proposed method. Numerical investigations suggest that the proposed method outperforms the original EfI method in all instances as expected, which is looked forward to be even more pronounced should it be used for other multi-dimensional optimization problems.

• Journal of Electrical Engineering and Technology
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• 제9권4호
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• pp.1240-1247
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• 2014

The applications of Distributed Generation (DG) in a smart distribution grid environment are widely employed especially for power balancing and supporting demand responses. Using these applications can have both positive and negative impacts on the distribution system. The sizing and location of their installations are the issues that should be taken into consideration to gain the maximum benefit from them when considering the economic aspects. This paper presents an application of the Bat Algorithm (BA) for the optimal sizing and siting of DG in a smart distribution power system in order to maximize the Benefit to Cost Ratio (BCR), subjected to system constraints including real and reactive power generation, line and transformer loading, voltage profile, energy losses, fault level as well as DG operating limits. To demonstrate the effectiveness of the proposed methodology and the impact of considering economic issues on DG placement, a simplify 9-bus radial distribution system of the Provincial Electricity Authority of Thailand (PEA) is selected for the computer simulation to explore the benefit of the optimal DG placement and the performance of the proposed approach.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.1769-1777
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• 2018

This paper proposes a method for optimal placement of Phasor Measurement Units (PMUs) considering system configuration and its attributes during the planning phase of PMU deployment. Each bus of the system is assessed on four diverse attributes; namely, redundancy of measurements, rotor angle and frequency monitoring of generator buses, reactive power deficiency, and maximum loading limit under transmission line outage contingency, and a consolidated 'degree of criticality' is determined using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The major contribution of the proposed work is the development of modified objective function which incorporates values of the degree of criticality of buses. The problem is formulated as maximization of the aggregate degree of criticality of the system. The resultant PMU configuration extends complete observability of the system and majority of the PMUs are located on critical buses. As budgetary restrictions on utilities may not allow installation PMUs even at optimal locations in a single phase, multi-horizon deployment of PMUs is also addressed. The proposed approach is tested on IEEE 14-bus, IEEE 30-bus, New England (NE) 39-bus, IEEE 57-bus and IEEE 118-bus systems and compared with some existing methods.

• 대한전자공학회논문지
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• 제24권6호
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• pp.1049-1055
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• 1987

This paper describes a near-optimal standard cell layout strategy which consists of three consecutives steps` partition, placement, and routing. In the partition step, a given network is torn apart into many subnetworks such that each subnetworks contains as many cells as possible with minimum interocnnections between subnetwork. In the placement step, the conventional string placement algorithm was modified. Also, bonding pads were placed such that their connections to the related cells are shortest. As a result for the tested example, the placement time was saved by 60% and the total routing lengths were saved by more than 20% and substantial improvements in the number of feed-through cell and the track density were obtained. The layout program is coded in PASCAL and implemented on a VAX 11-750/UNIX computer.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1997년도 춘계학술대회논문집; 경주코오롱호텔; 22-23 May 1997
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• pp.308-315
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• 1997

In this study, the effect of modal filter error on the vibration control characteristics of flexible structures is analyzed for IMSC(Independent Modal Space Control), and optimal sensor placement in the structural vibration control with consideration of performance of modal filter has been studied. An Lyapunov asymptotic stability condition has been derived, which depends on the magnitude of the modal filter errors. The extent of the response deviation of the closed-loop system is also derived and evaluated using operator techniques. A sensor placement technique has also been suggested to maximize the performance of the modal filter. It has been found by a series of simulation that the suggested sensor placement technique is very effective on the determination of the number and placement of sensors of modal filter in the structural vibration control.

• 한국컴퓨터정보학회논문지
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• 제7권3호
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• pp.42-48
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• 2002

배치(Placement)는 VLSI 회로의 physical design에서 중요한 단계로서 회로의 성능을 최대로 하기 위하여 회로 모듈의 집합을 배치시키는 문제이며, 배치 문제에서 최적의 해를 얻기 위해 클러스터 성장(cluster growth), 시뮬레이티드 어닐링(simulated annealing; SA), ILP(integer linear programming)등의 방식이 이용된다. 본 논문에서는 배치 문제에 대하여 유전자 알고리즘(genetic algorithm; GA)을 이용한 해 공간 탐색(solution space search) 방식을 제안하였으며, 제안한 방식을 시뮬레이티드 어닐링 방식과 비교, 분석하였다.

• 디지털산업정보학회논문지
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• 제17권2호
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• pp.13-20
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• 2021

Placement is a very important step in the VLSI physical design process. It is the problem of placing circuit modules to optimize the circuit performance and reliability of the circuit. It is used at the layout level to find strongly connected components that can be placed together in order to minimize the layout area and propagation delay. The most popular algorithms for circuit placement include the cluster growth, simulated annealing, integer linear programming and genetic algorithm. In this paper we propose a adapted genetic algorithm searching solution space for the placement problem, and then compare it with simulated annealing and genetic algorithm by analyzing the results of each implementation. As a result, it was found that the adaptive genetic algorithm approaches the optimal solution more effectively than the simulated annealing and genetic algorithm.

• Smart Structures and Systems
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• 제16권2호
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• pp.243-262
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• 2015

Optimal sensor placement (OSP) is a critical issue in construction and implementation of a sophisticated structural health monitoring (SHM) system. The uncertainties in the identified structural parameters based on the measured data may dramatically reduce the reliability of the condition evaluation results. In this paper, the information entropy, which provides an uncertainty metric for the identified structural parameters, is adopted as the performance measure for a sensor configuration, and the OSP problem is formulated as the multi-objective optimization problem of extracting the Pareto optimal sensor configurations that simultaneously minimize the appropriately defined information entropy indices. The nondirective movement glowworm swarm optimization (NMGSO) algorithm (based on the basic glowworm swarm optimization (GSO) algorithm) is proposed for identifying the effective Pareto optimal sensor configurations. The one-dimensional binary coding system is introduced to code the glowworms instead of the real vector coding method. The Hamming distance is employed to describe the divergence of different glowworms. The luciferin level of the glowworm is defined as a function of the rank value (RV) and the crowding distance (CD), which are deduced by non-dominated sorting. In addition, nondirective movement is developed to relocate the glowworms. A numerical simulation of a long-span suspension bridge is performed to demonstrate the effectiveness of the NMGSO algorithm. The results indicate that the NMGSO algorithm is capable of capturing the Pareto optimal sensor configurations with high accuracy and efficiency.