• Proceedings of the KIEE Conference
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• 2008.10c
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• pp.62-64
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• 2008

본 논문에서는 기존의 Particle Swarm Optimization (PSO) 알고리즘에 반발 속도 (Repulsion Velocity) 개념을 도입한 개선된 PSO 알고리즘을 제안하였다. 낮은 적합도를 가지는 지역을 멀리하는 성질을 모사한 것이 반발 속도의 개념이다. 반발 속도의 개념을 도입한 제안된 알고리즘은 기존의 알고리즘에 비해서, 더 좋은 수렴 특성을 가지고, 더 빠른 계산 특성을 가짐을 알 수 있었다. 시험 함수를 통해서 제안된 알고리즘의 검증을 수행하였고, 외전형 영구자석형 전동기의 최적화에 적용하여서 그 결과를 나타내었다.

• Journal of Power Electronics
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• v.9 no.2
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• pp.207-214
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• 2009

This paper presents a modem approach for speed control of a PMSM using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the PI-Controller. The overall system simulated under various operating conditions and an experimental setup is prepared. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. Comparison between different controllers is achieved, using a PI controller which is tuned by two methods, firstly manually and secondly using the PSO technique. The system is tested under variable operating conditions. Implementation of the experimental setup is done. The simulation results show good dynamic response with fast recovery time and good agreement with experimental controller.

• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.179-190
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• 2010

This paper describes a new stochastic heuristic algorithm in engineering problem optimization especially in power system applications. An improved particle swarm optimization (PSO) called adaptive particle swarm optimization (APSO), mixed with simulated annealing (SA), is introduced and referred to as APSO-SA. This algorithm uses a novel PSO algorithm (APSO) to increase the convergence rate and incorporate the ability of SA to avoid being trapped in a local optimum. The APSO-SA algorithm efficiency is verified using some benchmark functions. This paper presents the application of APSO-SA to find the optimal location, type and size of flexible AC transmission system devices. Two types of FACTS devices, the thyristor controlled series capacitor (TCSC) and the static VAR compensator (SVC), are considered. The main objectives of the presented method are increasing the voltage stability index and over load factor, decreasing the cost of investment and total real power losses in the power system. In this regard, two cases are considered: single-type devices (same type of FACTS devices) and multi-type devices (combination of TCSC, SVC). Using the proposed method, the locations, type and sizes of FACTS devices are obtained to reach the optimal objective function. The APSO-SA is used to solve the above non.linear programming optimization problem for better accuracy and fast convergence and its results are compared with results of conventional PSO. The presented method expands the search space, improves performance and accelerates to the speed convergence, in comparison with the conventional PSO algorithm. The optimization results are compared with the standard PSO method. This comparison confirms the efficiency and validity of the proposed method. The proposed approach is examined and tested on IEEE 14 bus systems by MATLAB software. Numerical results demonstrate that the APSO-SA is fast and has a much lower computational cost.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1470-1478
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• 2018

Recently, wireless power transfer (WPT) via coupled magnetic resonances has attracted a lot of attention owing to its long operation distance and high efficiency. However, the WPT systems is over-coupling and a frequency splitting phenomenon occurs when resonators are placed closely, which leads to a decrease in the transfer power. To solve this problem, an adaptive frequency tracking control (AFTC) was used based on a closed-loop control scheme. An improved particle swarm optimization (PSO) algorithm was proposed with the AFTC to track the maximum power point in real time. In addition, simulations were carried out. Finally, a WPT system with the AFTC was demonstrated to experimentally validate the improved PSO algorithm and its tracking performance in terms of optimal frequency.

• Journal of Korean Neurosurgical Society
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• v.59 no.6
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• pp.615-621
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• 2016

Objectives : To review surgical results of post-fusion lumbar flatback treated with pedicle subtraction osteotomy (PSO) or Smith-Petersen osteotomies (SPOs). Methods : Twenty-eight patients underwent osteotomies. Radiological outcomes by sagittal vertical axis (SVA), and pelvic tilt (PT), T1 pelvic angle (T1PA), and pelvic incidence (PI)-lumbar lordosis (LL) at preoperative, postoperative 1 month, and final were evaluated. Oswestry Disability Index (ODI), visual analog scale (VAS) score of back pain/leg pain, and Scoliosis Research Society-22 score (SRS-22r) were analyzed and compared. Patients were divided into 2 groups (SVA ${\leq}5cm$ : normal, SVA >5 cm : positive) at final and compared outcomes. Results : Nineteen patients (68%) had PSO and the other 9 patients had SPOs with anterior lumbar interbody fusions (ALIFs) (Mean age : 65 years, follow-up : 31 months). The PT, PI-LL, SVA, T1PA were significantly improved at 1 month and at final (p<0.01). VAS score, ODI, and SRS-22r were also significantly improved at the final (p<0.01). 23 patients were restored with normal SVA and the rest 5 patients demonstrated to positive SVA. SVA and T1PA at 1 month and SVA, PI-LL, and T1PA at final were significantly different (p<0.05) while the ODI, VAS, and SRS-22r did not differ significantly between the groups (p>0.05). Common reoperations were early 4 proximal junctional failures (14%) and late four rod fractures. Conclusion : Our results demonstrate that PSO and SPOs with ALIFs at the lower lumbar are significantly improves sagittal balance. For maintenance of normal SVA, PI-LL might be made negative value and T1PA might be less than $11^{\circ}$ even though positive SVA group was also significantly improved clinical outcomes.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.659-668
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• 2018

This paper proposes an optimization approach of a grid-connected photovoltaic and wind hybrid energy system including energy storage considering voltage fluctuation in the electricity grid. A techno-economic analysis is carried out in order to minimize the size of hybrid system by considering the benefit-cost. Lithium-ion battery type is used for both managing the electricity selling to the grid and reducing voltage fluctuation. A new technique is developed to limit the voltage perturbation caused by the solar irradiance and the wind speed through determining the state-of-charge of battery for every hour of a day. Improved particle swarm optimization (PSO) methods, referred to as FC-VACPSO which combines Fast Convergence Particle Swarm Optimization (FCPSO) method and Variable Acceleration Coefficient Based Particle Swarm Optimization (VACPSO) method are used to solve the optimization problem. A comparative study has been performed between standard PSO method and PSO based methods to extract the best size with the benefit cost. A sensitivity analysis has been studied for different kinds and costs of batteries, by considering variable and constant state-ofcharge of battery. The simulations, performed under Matlab environment, yield good results using the FC-VACPSO method regarding the convergence and the benefit cost of the hybrid system.

• Journal of the Korea Society for Simulation
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• v.28 no.4
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• pp.21-32
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• 2019

Inspired by the social behavior models of a bird flock or fish school, particle swarm optimization (PSO) is a popular metaheuristic optimization algorithm and has been widely used from solving a complex optimization problem to learning a artificial neural network. However, PSO is difficult to apply to many real-life optimization problems involving stochastic noise, since it is originated in a deterministic environment. To resolve this problem, this paper incorporates a resampling method called the uncertainty evaluation (UE) method into PSO. The UE method allows the particles to converge on the accurate optimal solution quickly in a noisy environment by selecting the particles' global best position correctly, one of the significant factors in the performance of PSO. The results of comparative experiments on several benchmark problems demonstrated the improved performance of the propose algorithm compared to the existing studies. In addition, the results of the case study emphasize the necessity of this work. The proposed algorithm is expected to be effectively applied to optimize complex systems through digital twins in the fourth industrial revolution.

• Journal of Korean Neurosurgical Society
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• v.47 no.2
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• pp.95-101
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• 2010

Objective : Clinical, radiographic, and outcomes assessments, focusing on complications, were performed in patients who underwent pedicle subtraction osteotomy (PSO) to assess correction effectiveness, fusion stability, procedural safety, neurological outcomes, complication rates, and overall patient outcomes. Methods : We analyzed data obtained from 13 consecutive PSO-treated patients presenting with fixed sagittal imbalances from 1999 to 2006. A single spine surgeon performed all operations. The median follow-up period was 73 months (range 41-114 months). Events during peri operative course and complications were closely monitored and carefully reviewed. Radiographs were obtained and measurements were done before surgery, immediately after surgery, and at the most recent follow-up examinations. Clinical outcomes were assessed using the Oswestry Disability Index and subjective satisfaction evaluation. Results : Following surgery, lumbar lordosis increased from $-14.1^{\circ}{\pm}20.5^{\circ}$ to $-46.3^{\circ}{\pm}12.8^{\circ}$ (p<0.0001). and the C7 plumb line improved from $115{\pm}43\;mm$ to $32{\pm}38\;mm$ (p<0.0001). There were 16 surgery-related complications in 8 patients; 3 intraoperative, 3 perioperative, and 10 late-onset postoperative. The prevalence of proximal junctional kyphosis (PJK) was 23% (3 of 13 patients). However, clinical outcomes were not adversely affected by PJK. Intraoperative blood loss averaged 2,984 mL. The C7 plumb line values and postoperative complications were closely correlated with clinical results. Conclusion : Intraoperative or postoperative complications are relatively common following PSO. Most late-onset complications in PSO patients were related to PJK and instrumentation failure. Correcting the C7 plumb line value with minimal operative complications seemed to lead to better clinical results.

• Journal of Advanced Navigation Technology
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• v.24 no.4
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• pp.291-298
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• 2020

This study proposed a model that can track MPP faster than the existing MPPT algorithm using the particle swarm optimization algorithm (PSO). The proposed model highly sets the acceleration constants of gbest and pbest in the PSO algorithm to quickly track the MPP point and eliminates the power instability problem. In addition, this algorithm was re-executed by detecting the change in power of the solar panel according to the rapid change in solar radiation. As a result of the experiment, MPP time was 0.03 seconds and power was 131.65 for 691.5 W/m2, and MPP was tracked at higher power and speed than the existing P&O and INC algorithms. The proposed model can be applied when a change in the amount of power is detected by partial shading in a Photovoltaic power plant with Photovoltaic connected in parallel. In order to improve the MPPT algorithm, this study needs a comparative study on optimization algorithms such as moth flame optimization (MFO) and whale optimization algorithm (WOA).

• The KSFM Journal of Fluid Machinery
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• v.16 no.1
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• pp.11-16
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• 2013

A numerical study was conducted to improve the performance of an impeller of centrifugal compressor. Nine design variables were chosen with constraints. Only meridional contours and blade profile were adjusted. ANN (Artificial Neural Net) was adopted as a main optimization algorithm with PSO (Particle Swarm Optimization) in order to reduce the optimization time. At first, ANN was learned and trained with the design variable sets which were obtained using DOE (Design of Experiment). This ANN was continuously improved its accuracy for each generation of which population was one hundred. New design variable set in each generation was selected using a non-gradient based method of PSO in order to obtain the global optimized result. After $7^{th}$ generation, the prediction difference of efficiency and pressure ratio between ANN and CFD was less than 0.6%. From more than 1,200 design variable sets, a pareto of efficiency versus pressure ratio was obtained and an optimized result was selected based on the multi-objective function. On this optimized impeller, the efficiency and pressure ratio were improved by 1% and 9.3%, respectively.