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Applying TID-PSS to Enhance Dynamic Stability of Multi-Machine Power Systems

  • Mohammadi, Ramin Shir;Mehdizadeh, Ali;Kalantari, Navid Taghizadegan
    • Transactions on Electrical and Electronic Materials
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    • v.18 no.5
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    • pp.287-297
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    • 2017
  • Novel power system stabilizers (PSSs) have been proposed to effectively dampen low frequency oscillations (LFOs) in multi-machine power systems and have attracted increasing research interest in recent years. Due to this attention, recently, fractional order controllers (FOCs) have found new applications in power system stability issues. Here, a tilt-integral-derivative power system stabilizer (TID-PSS) is proposed to enhance the dynamic stability of a multi-machine power system by providing additional damping to the LFOs. The TID is an extended version of the classical proportional-integral-derivative (PID) applying fractional calculus. The design of the proposed three-parameter tunable TID-PSS is systematized as a nonlinear time domain optimization problem in which the tunable parameters are adjusted concurrently using a modified group search optimization (MGSO) algorithm. An integral of the time multiplied squared error (ITSE) performance index is considered as the objective function. The proposed stabilizer is simulated in the MATLAB/SIMULINK environment using the FOMCON toolbox and the dynamic performance is evaluated on a 3-machine 6-bus power system. The TID-PSS is compared with both classical PID-PSS (PID-PSS) and conventional PSS (CPSS) using eigenvalue analysis and time domain simulations. Sensitivity analyses are performed to assess the robustness of the proposed controller against large changes in system loading conditions and parameters. The results indicate that the proposed TID-PSS provides the better dynamic performance and robustness compared with the PID-PSS and CPSS.

Fault Diagnosis of Voltage-Fed Inverters Using Pattern Recognition Techniques for Induction Motor Drive (패턴인식 기법을 이용한 유도전동기 구동용 전압형 인버터의 고장진단)

  • Park, Jang-Hwan;Park, Sung-Moo;Lee, Dae-Jong;Kim, Dong-Hwa;Chun, Myung-Geun
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.19 no.3
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    • pp.75-84
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    • 2005
  • Since an unexpected fault of induction motor drive systems can cause serious troubles in many industrial applications, which the technique is required to diagnose faults of a voltage-fed PWM inverter for induction motor drives. The considered fault types are rectifier diodes, switching devices and input terminals with open-circuit faults, and the signal for diagnosis is derived from motor currents. The magnitude of dq-current trajectory is used for the feature extraction of a fault and PCA LDA are applied to diagnose. Also, we show results with respect to the execution time because of the possibility to use that a diagnosis software is embedded in the controllers of medium and small size induction motors drive for real-time diagnosis. After we performed various simulations for the fault diagnosis of the inverter, the usefulness of proposed algerian was verified.

Calculation of Magnetic Fields under 3 Phase Power Lines with Branch Lines (분기선로가 있는 3상 전력선로하의 전자파 자계 계산)

  • Kang, Dae-Ho;Lee, Yong-Sik;Kim, Bu-Gyu
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.23 no.5
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    • pp.110-119
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    • 2009
  • In this study magnetic fields near electric power lines with branch lines which have a arbitrary angle were derived and formulated by dipole antenna theory and could be calculated easily using the formula. It seems that those formula could be applicable to the consideration of magnetic fields during the design of distribution lines with branch lines. As an example those formulated equations on elements of magnetic fields were applied to a model of 3 phase distribution lines with branch lines and calculated by Matlab programs and the results were presented The analyzed results are follows. The resultant magnetic field is dominated by the componant By all over y-axis in the case of the smaller branched angle $\alpha$ and the lower observed point z. In case of ${\alpha}=\frac{\pi}{2}$[rad], the resultant field is affected by the componant Bx. The resultant field is dominated by the componant Bz at the vicinity of the power lines and it shows very large value at the branch line position of y-axis in case of ${\alpha}>\frac{\pi}{2}$.

Proposing optimum parameters of TMDs using GSA and PSO algorithms for drift reduction and uniformity

  • Mirzai, Nadia M.;Zahrai, Seyed Mehdi;Bozorgi, Fatemeh
    • Structural Engineering and Mechanics
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    • v.63 no.2
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    • pp.147-160
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    • 2017
  • In this study, the optimum parameters of Tuned Mass Dampers (TMDs) are proposed using Gravity Search Algorithm (GSA) and Particle Swarm Optimization (PSO) to reduce the responses of the structures. A MATLAB program is developed to apply the new approach to the benchmark 10 and 40-story structures. The obtained results are compared to those of other optimization methods used in the literature to verify the developed code. To show the efficiency and accuracy of the proposed methods, nine far-field and near-field worldwide earthquakes are applied to the structures. The results reveal that in the 40-story structure, GSA algorithm can reduce the Relative Displacement (RD) and Absolute Acceleration (AA) up to 43% and 21%, respectively while the PSO decreases them by 50% and 25%, respectively. In contrast, both GSA and PSO algorithms reduce the RD and AA about 29% and 21% for the 10-story structure. Furthermore, using the proposed approach the required TMD parameters reduce by 47% and 63% in the 40 and 10-story buildings in comparison with the referenced ones. Result evaluation and related comparison indicate that these methods are more effective even by using smaller TMD parameters resulting in the reduction of acting force from TMD, having smaller stiffness and damping factors while being more cost effective due to its decreased parameters. In other words, the TMD with optimum parameters can play a positive role in both tall and typical structures.

Optimization of cables size and prestressing force for a single pylon cable-stayed bridge with Jaya algorithm

  • ATMACA, Barbaros;DEDE, Tayfun;GRZYWINSKI, Maksym
    • Steel and Composite Structures
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    • v.34 no.6
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    • pp.853-862
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    • 2020
  • In recent years, due to the many advantages cable-stayed bridges have often constructed in medium and long span. These advantages can be listed as an aesthetically pleasing appearance, economic and easy construction, etc. The main structural elements of cable-stayed bridges are listed as deck, pylon, cables and foundation. Perhaps one of the most vital and expensive of these structural elements is stay-cables. Stay-cables ensure the allowable displacement and distribution of bending moments along the bridge deck with prestressing force. Therefore the optimum design of the stay-cables and prestressing force are very important in achieving the performance expected from the cable-stayed bridges. This paper aims to obtain the stay-cables size and prestressing force optimization of the cable-stayed bridge. For this purpose, single pylon and fan type cable configuration Manavgat Cable-Stayed Bridge was selected as an example. The three dimensional (3D) finite element model (FEM) of the bridge was created with SAP2000. Analysis of the 3D FEM of the bridge was conducted under the different combined effects of the self-weight of the structural element, prestressing force of stay-cable and live load. Stay-cable stress and deck displacement were taken into account as constraints for the optimization problem. To optimize this existing bridge a metaheuristic algorithm named Jaya was used in the optimization process. 3D FEM of the selected bridge was repeatedly analyzed by using Open Applicable Programming Interface (OAPI) properties of SAP2000. To carry out the optimization process the developed program which integrates the Jaya algorithm and the required codes for calling SAP2000 is coded in MATLAB. At the end of the study, the total weight of the stay-cables was reduced more than 40% according to existing stay cables under loads taken into account.

Accelerated Monte Carlo analysis of flow-based system reliability through artificial neural network-based surrogate models

  • Yoon, Sungsik;Lee, Young-Joo;Jung, Hyung-Jo
    • Smart Structures and Systems
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    • v.26 no.2
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    • pp.175-184
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    • 2020
  • Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

Adaptive Model-Free-Control-based Steering-Control Algorithm for Multi-Axle All-Terrain Cranes using the Recursive Least Squares with Forgetting (망각 순환 최소자승을 이용한 다축 전지형 크레인의 적응형 모델 독립 제어 기반 조향제어 알고리즘)

  • Oh, Kwangseok;Seo, Jaho
    • Journal of Drive and Control
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    • v.14 no.2
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    • pp.16-22
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    • 2017
  • This paper presents the algorithm of an adaptive model-free-control-based steering control for multi-axle all-terrain cranes for which the recursive least squares with forgetting are applied. To optimally control the actual system in the real world, the linear or nonlinear mathematical model of the system should be given for the determination of the optimal control inputs; however, it is difficult to derive the mathematical model due to the actual system's complexity and nonlinearity. To address this problem, the proposed adaptive model-free controller is used to control the steering angle of a multi-axle crane. The proposed model-free control algorithm uses only the input and output signals of the system to determine the optimal inputs. The recursive least-squares algorithm identifies first-order systems. The uncertainty between the identified system and the actual system was estimated based on the disturbance observer. The proposed control algorithm was used for the steering control of a multi-axle crane, where only the steering input and the desired yaw rate were employed, to track the reference path. The controller and performance evaluations were constructed and conducted in the Matlab/Simulink environment. The evaluation results show that the proposed adaptive model-free-control-based steering-control algorithm produces a sound path-tracking performance.

Sliding Mode Observer-based Fault Detection Algorithm for Steering Input of an All-Terrain Crane (슬라이딩 모드 관측기 기반 전지형 크레인의 조향입력 고장검출 알고리즘)

  • Oh, Kwangseok;Seo, Jaho
    • Journal of Drive and Control
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    • v.14 no.2
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    • pp.30-36
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    • 2017
  • This paper presents a sliding mode observer-based fault detection algorithm for steering inputs of an all-terrain crane. All-terrain cranes with multi-axles have several steering modes for various working purposes. Since steering angles at the other axles except the first wheel are controlled by using the information of steering angle at the first wheel, a reliable signal of the first axle's steering angle should be secured for the driving safety of cranes. For the fault detection of steering input signal, a simplified crane model-based sliding mode observer has been used. Using a sliding mode observer with an equivalent output injection signal that represents an actual fault signal, a fault signal in steering input was reconstructed. The road steering mode of the crane's steering system was used to conduct performance evaluations of a proposed algorithm, and an arbitrary fault signal was applied to the steering angle at the first wheel. Since the road steering mode has different steering strategies according to different speed intervals, performance evaluations were conducted based on the curved path scenario with various speed conditions. The design of algorithms and performance evaluations were conducted on Matlab/Simulink environment, and evaluation results reveal that the proposed algorithm is capable of detecting and reconstructing a fault signal reasonably well.

Modeling and Simulation of Secondary Battery-Fuel Cell Propulsion System for Underwater Vessel to Estimate the Operation Time (수중함용 2차전지-연료전지 추진체계의 성능 예측을 위한 M&S 연구)

  • Ji, Hyunjin;Cho, Sungbaek;Bae, Joongmyeon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.17 no.5
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    • pp.694-702
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    • 2014
  • One of the most important devices in an underwater vessel is a propulsion system. It should be a quiet and efficient system for stealthy operations in the large mission area. Hence lead-acid battery system has been used to supply the energy to electric motor. Recent technological developments and improvements, such as polymer electrolyte membrane(PEM) fuel cell and lithium polymer battery and have created the potential to improve overall power and propulsion performance. An underwater vessel always starts their mission with a limited energy and is not easy to refuel. Therefore design of energy elements, such as fuel cell and battery, and their load distribution are important to increase the maximum operating time of underwater vessel. In this paper, the lead-acid battery/PEM fuel cell and lithium polymer battery/PEM fuel cell were suggested as propulsion system and their performances were analyzed by modeling and simulation using Matlab/Simulink. Each model concentrated on representing the characteristics of energy element depending on demand current. As a result the effect of load distribution between battery and fuel cell was evaluated and the operation time of each propulsion system was able to be estimated exactly.

Solving the test resource allocation using variable group genetic algorithm (가변 그룹 유전자알고리즘 기반의 시험자원할당 문제 해결)

  • Mun, Chang-min
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.8
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    • pp.1415-1421
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    • 2016
  • There are considerable concern on the methods for the efficient utilization of the test-resources as increasing of the number of the tests for functionality and performance verification of weapon systems. Furthermore, with an increase in the complexity of the resource assignment the decision support is required. Test resource allocation is basically the same problems as conventional NP-hard FJSP(Flexible Job Shop Problem), therefore empirical test resource allocation method that has been used in many decades is limited in the time performance. Although research has been conducted applying the genetic algorithm to the FJSP, it is limited in the test resource allocation domain in which more than one machine is necessary for a single operation. In this paper, a variable group genetic algorithm is proposed. The algorithm is expected to improve the test plan efficiency by automating and optimizing the existing manual based allocation. The simulation result shows that the algorithm could be applicable to the test plan.