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Full-Text Articles in Engineering
Optimal Placement Of Distributed Energy Storage Systems In Distribution Networks Using Artificial Bee Colony Algorithm, Choton K. Das, Octavian Bass, Ganesh Kothapalli, Thair S. Mahmoud, Daryoush Habibi
Optimal Placement Of Distributed Energy Storage Systems In Distribution Networks Using Artificial Bee Colony Algorithm, Choton K. Das, Octavian Bass, Ganesh Kothapalli, Thair S. Mahmoud, Daryoush Habibi
Research outputs 2014 to 2021
The deployment of utility-scale energy storage systems (ESSs) can be a significant avenue for improving the performance of distribution networks. An optimally placed ESS can reduce power losses and line loading, mitigate peak network demand, improve voltage profile, and in some cases contribute to the network fault level diagnosis. This paper proposes a strategy for optimal placement of distributed ESSs in distribution networks to minimize voltage deviation, line loading, and power losses. The optimal placement of distributed ESSs is investigated in a medium voltage IEEE-33 bus distribution system, which is influenced by a high penetration of renewable (solar and wind) …
Dynamic Blind Source Separation Method Of Bearing Fault Diagnosis Based On Ga-Aw-Pso, Tianqi Zhang, Baoze Ma, Xingzi Qiang, Shengrong Quan
Dynamic Blind Source Separation Method Of Bearing Fault Diagnosis Based On Ga-Aw-Pso, Tianqi Zhang, Baoze Ma, Xingzi Qiang, Shengrong Quan
Journal of System Simulation
Abstract: The adaptive particle swarm optimization based on genetic mechanism (GA-AW-PSO) is proposed, aiming at blind source separation for dynamic hybrid bearing signals. The negentropy of separated signal is regarded as an objective function. The inertia weight is adjusted adaptively to reduce the invalid iterations according to the fitness difference. The introduction of genetic mechanism can increase diversity and is helpful for dynamic signal processing. The parameterized representation of orthogonal matrices can reduce the complexity of the algorithm. The simulation results show that the proposed method is superior to traditional blind source separation for the dynamic mechanical hybrid analog signal. …
Scheduling Based On Interruption Analysis And Pso For Strictly Periodic And Preemptive Partitions In Integrated Modular Avionics, Hui Lu, Qianlin Zhou, Zongming Fei, Rongrong Zhou
Scheduling Based On Interruption Analysis And Pso For Strictly Periodic And Preemptive Partitions In Integrated Modular Avionics, Hui Lu, Qianlin Zhou, Zongming Fei, Rongrong Zhou
Computer Science Faculty Publications
Integrated modular avionics introduces the concept of partition and has been widely used in avionics industry. Partitions share the computing resources together. Partition scheduling plays a key role in guaranteeing correct execution of partitions. In this paper, a strictly periodic and preemptive partition scheduling strategy is investigated. First, we propose a partition scheduling model that allows a partition to be interrupted by other partitions, but minimizes the number of interruptions. The model not only retains the execution reliability of the simple partition sets that can be scheduled without interruptions, but also enhances the schedulability of the complex partition sets that …
A Novel Perturbed Particle Swarm Optimization-Based Support Vector Machine Forfault Diagnosis In Power Distribution Systems, Hoang Thi Thom, Cho Ming-Yuan, Vu Quoc Tuan
A Novel Perturbed Particle Swarm Optimization-Based Support Vector Machine Forfault Diagnosis In Power Distribution Systems, Hoang Thi Thom, Cho Ming-Yuan, Vu Quoc Tuan
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a novel perturbed particle swarm optimization (PPSO) algorithm is investigated to improve the performance of a support vector machine (SVM) for short-circuit fault diagnosis in power distribution systems. In the proposed PPSO algorithm, the velocity of each particle is perturbed whenever the particles strike into a local optimum, in order to achieve a higher quality solution to optimization problems. Furthermore, the concept of proposed perturbation is applied to three variants of PSO, and improved corresponding algorithms are named perturbed C-PSO (PC-PSO), perturbed T-PSO (PT-PSO), and perturbed K-PSO (PK-PSO). For the purpose of fault diagnosis, the time- domain …
Two-Area Load Frequency Control With Redox Ow Battery Using Intelligentalgorithms In A Restructured Scenario, Lakshmi Dhandapani, Fathima Peer, Ranganath Muthu
Two-Area Load Frequency Control With Redox Ow Battery Using Intelligentalgorithms In A Restructured Scenario, Lakshmi Dhandapani, Fathima Peer, Ranganath Muthu
Turkish Journal of Electrical Engineering and Computer Sciences
Load frequency control (LFC) is an essential aspect of power system dynamics. This paper focuses on the optimization of LFC for a two-area deregulated power system under different scenarios. A recent nature-inspired ower pollination algorithm (FPA), based on the pollination process of plants, is used to tune the proportional integral (PI) controller parameters of LFC for the global minima solution. FPA is compared with a genetic algorithm, particle swarm optimization, and a conventional PI controller. During large load disturbance in the areas, controllers are incapable of reducing frequency deviations and tie-line power oscillations due to the slow response of the …
An Efficient Recurrent Fuzzy Cmac Model Based On A Dynamic-Group--Based Hybrid Evolutionary Algorithm For Identification And Prediction Applications, Chin-Ling Lee, Chengjian Lin
An Efficient Recurrent Fuzzy Cmac Model Based On A Dynamic-Group--Based Hybrid Evolutionary Algorithm For Identification And Prediction Applications, Chin-Ling Lee, Chengjian Lin
Turkish Journal of Electrical Engineering and Computer Sciences
This article presents an efficient TSK-type recurrent fuzzy cerebellar model articulation controller (T-RFCMAC) model based on a dynamic-group--based hybrid evolutionary algorithm (DGHEA) for solving identification and prediction problems. The proposed T-RFCMAC model is based on the traditional CMAC model and the Takagi--Sugeno--Kang (TSK) parametric fuzzy inference system. Otherwise, the recurrent network, which imports feedback links with a receptive field cell, is embedded in the T-RFCMAC model, and the feedback units are used as memory elements. The DGHEA, which is a hybrid of the dynamic-group quantum particle swarm optimization (QPSO) and the Nelder--Mead method, is proposed for adjusting the parameters of …
Adaptive Collaborative Speed Control Of Pmdc Motor Using Hyperbolic Secant Functions And Particle Swarm Optimization, Omer Saleem, Khalid Mahmood-Ul-Hasan
Adaptive Collaborative Speed Control Of Pmdc Motor Using Hyperbolic Secant Functions And Particle Swarm Optimization, Omer Saleem, Khalid Mahmood-Ul-Hasan
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents an adaptive collaborative speed controller for a permanent magnet direct-current (PMDC) motor. The proposed scheme beneficially combines the control efforts of a proportional-integral (PI) controller and a linear-quadratic regulator (LQR) via a weighted summing module. Initially, the weightages of the summing module are kept fixed. They are optimally tuned and tested via the particle swarm optimization algorithm. In order to synergize the controller combination, these weightages are adaptively modulated as well, using hyperbolic secant functions of the error dynamics of the motor's angular speed. The adaptive combination renders significant enhancement in the transient response, steady-state response, input-energy …