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Articles 31 - 60 of 87
Full-Text Articles in Physical Sciences and Mathematics
Robust Optimal Operation Of Smart Distribution Grids With Renewable Basedgenerators, Omid Zare, Sadjad Galvani, Murtaza Farsadi
Robust Optimal Operation Of Smart Distribution Grids With Renewable Basedgenerators, Omid Zare, Sadjad Galvani, Murtaza Farsadi
Turkish Journal of Electrical Engineering and Computer Sciences
Modern distribution systems are equipped with various distributed energy resources (DERs) because of the importance of local generation. These distribution systems encounter more and more uncertainties because of the ever-increasing use of renewable energies. Other sources of uncertainty, such as load variation and system components? failure, will intensify the unpredictable nature of modern distribution systems. Integrating energy storage systems into distribution grids can play a role as a flexible bidirectional source to accommodate issues from constantly varying loads and renewable resources. The overall functionality of these modern distribution systems is enhanced using communication and computational abilities in smart grid frameworks. …
Joint Modeling Of Rayleigh Wave Dispersion And H/V Spectral Ratio Using Pareto-Basedmultiobjective Particle Swarm Optimization, Ersi̇n Büyük, Ekrem Zor, Abdullah Karaman
Joint Modeling Of Rayleigh Wave Dispersion And H/V Spectral Ratio Using Pareto-Basedmultiobjective Particle Swarm Optimization, Ersi̇n Büyük, Ekrem Zor, Abdullah Karaman
Turkish Journal of Earth Sciences
Estimating the shear wave velocity and thickness of geologic units in a sedimentary structure is important for quantifying the local site effect caused by an earthquake. Inversion of the Rayleigh wave dispersion alone is sensitive to the absolute average shear wave velocity, while the H/V spectral ratio is sensitive to velocity contrasts. The solution of these models in a joint system using conventional inversion techniques suffers from difficulties while evaluating partial derivatives, dependencies to the initial model that is sometimes difficult to estimate, and trapping at a local minimum. Herein, a joint model using the Pareto optimality technique with multiobjective …
Research On Social Network Inference Method Based On Observation Data, Hailiang Chen, Bin Chen, Yuan Peng, Dong Jian, Chuan Ai
Research On Social Network Inference Method Based On Observation Data, Hailiang Chen, Bin Chen, Yuan Peng, Dong Jian, Chuan Ai
Journal of System Simulation
Abstract: Internet technology and online social networks have developed rapidly, which enables people to randomly express their opinions, ideas, emotional exchanges and economic exchanges. Inferring social networks is made possible through the observation data exchanged by people on the Internet. Through the analysis of ConNIe (Convex Network Inference) algorithm, this paper researches the effects of sparse parameter, propagation time distribution model and its parameters on the inference results of the algorithm. According to the analysis, a social network inference framework based on ConNIe algorithm is proposed. Combining the perceptron and particle swarm optimization algorithm, the ConNIe algorithm inference becomes a …
Jammer Placement Algorithm Based On Particle Swarm Optimization, Fang Fang, Chunming Ye, Haibo Liu
Jammer Placement Algorithm Based On Particle Swarm Optimization, Fang Fang, Chunming Ye, Haibo Liu
Journal of System Simulation
Abstract: A novel jammer placement algorithm based on particle swarm optimization is proposed to solve the problems of nodes’ mobility and restrictions on placement areas in ad-hoc network. There are three steps in this algorithm: network simulation, jamming simulation, and optimization. The algorithm simulates the network communication process and movement of nodes with discrete simulation method. Simple particle swarm optimization is applied to compute the exact coordinates of jammers. Experiment results show that this algorithm is good at jamming network nodes moving in different ways. The algorithm has stable performance with varying conditions such as different placement areas, jamming …
Multi-Seats Collaborative Task Planning Based On Improved Particle Swarm Optimization, Cai Rui, Wang Wei, Jue Qu, Hu Bo
Multi-Seats Collaborative Task Planning Based On Improved Particle Swarm Optimization, Cai Rui, Wang Wei, Jue Qu, Hu Bo
Journal of System Simulation
Abstract: Aiming at the allocation conflict between task and operator of multi-seats collaborative task planning in command and control cabin, a multi-seats collaborative task planning method based on improved particle swarm optimization is proposed. This method describes and analyzes the multi-seats collaborative task and establishes a solution space model based on task sequence. In solving the model, the particle swarm optimization (PSO) was improved by using multi-dimensional asynchronous processing and modifying inertia weight parameters so that the efficiency and local searching ability of the PSO were improved. The example analysis shows that the model and the algorithm can effectively reduce …
Multi-Strategy Cooperative Evolutionary Pso Based On Cauchy Mutation Strategy, Yongji Wang, Tingting Su, Liu Lei
Multi-Strategy Cooperative Evolutionary Pso Based On Cauchy Mutation Strategy, Yongji Wang, Tingting Su, Liu Lei
Journal of System Simulation
Abstract: For improving the performance of particle swarm optimization (PSO) in optimization simulation, a multi-strategy cooperative evolutionary PSO based on Cauchy mutation strategy is proposed. The new algorithm divides the whole swarm into three sub-swarms. A part of particles is selected to Cauchy mutation with a certain probability, and the rest of particles adjust their exploitation and exploration by different evolutionary strategies (large-scale search strategy, local search strategy, and adaptive velocity updating strategy). The sub-swarms share their information to achieve cooperation. Three strategies are used to optimize three test functions, and the result shows the advantages …
Prediction Of Aircraft Cabin Energy Consumption Based On Pso And Cro Algorithms, Xiuyan Wang, Yanmin Liu, Gewen Zhang, Zongshuai Li, Jiaquan Lin
Prediction Of Aircraft Cabin Energy Consumption Based On Pso And Cro Algorithms, Xiuyan Wang, Yanmin Liu, Gewen Zhang, Zongshuai Li, Jiaquan Lin
Journal of System Simulation
Abstract: To meet the requirements of the rapidity and the accuracy of the aircraft cabin energy consumption prediction for bridge-load air conditioner when an aircraft berthing, a forecasting method based on the combination of neural network, particle swarm and coral reef is proposed. The energy consumption prediction model is established based on wavelet neural network, and the prediction model parameters are optimized using the united algorithm of coral reefs and particle swarm optimization. The united algorithm adopts a double-layer structure: the data of the first layer are grouped and optimized by the particle swarm optimization algorithm for a preliminary optimization, …
Error Estimation For Material Simulation Data Based On Hybrid Learning Algorithm, Wang Juan, Xiaoyu Yang, Zongguo Wang, Ren Jie, Xushan Zhao
Error Estimation For Material Simulation Data Based On Hybrid Learning Algorithm, Wang Juan, Xiaoyu Yang, Zongguo Wang, Ren Jie, Xushan Zhao
Journal of System Simulation
Abstract: In order to obtain high quality material simulation data from Density Functional Theory material calculation software package, a modeling method based on BP neural network was proposed to build model estimating the error of material simulation data. A novel hybrid algorithm combining simple particle swarm optimization algorithm that excludes speed item with BP algorithm, also referred to tsPSO-BP, was proposed to optimize the connection weights of the BP neural network. The hybrid learning algorithm not only makes use of strong global searching ability of the PSO, but also strong local searching ability of the BP algorithm. The BP …
Target Decision In Collaborative Air Combats Using Multi-Agent Particle Swarm Optimization, Yuewen Fu, Yuancheng Wang, Chen Zhen, Wenlan Fan
Target Decision In Collaborative Air Combats Using Multi-Agent Particle Swarm Optimization, Yuewen Fu, Yuancheng Wang, Chen Zhen, Wenlan Fan
Journal of System Simulation
Abstract: Under the research background of collaborative multi-aircraft and multi-target air combats, combined with the actual combat constraint conditions and the threat assessment functions on both sides, a collaborative air combat target decision simulation model is established for complex and changeable battlefield situations, which can reflect the priority of fire attack. To solve the decision scheme quickly and accurately, an improved multi-agent particle swarm optimization algorithm is proposed by introducing the interaction mechanism of the multi-agent theory into particle swarm optimization algorithm; and the neighborhood cooperation operator, mutation operator and self-learning operator for the agent are designed respectively. …
Prediction Of Alumina Density Based On Lssvm, Guimei Cui, Haijin Yang, Piliang Liu, Yu Kai
Prediction Of Alumina Density Based On Lssvm, Guimei Cui, Haijin Yang, Piliang Liu, Yu Kai
Journal of System Simulation
Abstract: The prediction model of alumina density based on the PSO algorithm with swarm activity to optimize LSSVM method is built. According to the production process characteristics of aluminum electrolysis and historical data, the input variables of the model is determined. It can solve these problems that Particle Swarm Optimization (PSO) algorithm is with the risk of premature convergence and least square support vector machine is time consuming with parameter selection. The method uses swarm activity as diversity index. When swarm activity is quickened to descend, evolution operation is added to modify the positions or velocities of particles to …
Optimization Design Of Fuzzy Energy Management For Plug-In Hybrid Electric Vehicles, Xiaolan Wu, Zhifeng Bai, Xiaohui Shi, Binggang Cao
Optimization Design Of Fuzzy Energy Management For Plug-In Hybrid Electric Vehicles, Xiaolan Wu, Zhifeng Bai, Xiaohui Shi, Binggang Cao
Journal of System Simulation
Abstract: Because of complex system configuration, it is difficult to find precise mathematics model of PHEV drivetrain. The fuzzy controller design depends mainly on expert’s experience and has much subjectivity. A fuzzy energy management strategy (EMS) based on particle swarm optimization (PSO) is presented. In this EMS, the fuzzy rules obtained from expert knowledge are unaltered and the PSO is used to optimize the parameters of membership functions of the fuzzy controller. The provided EMS model is built by Matlab/simulink and embedded in the Advisor software for simulation and comparative analysis. The result shows that, compared with the conventional …
Ingan/Gan Tandem Solar Cell Parameter Estimation: A Comparative Stud, Abdelmoumene Benayad, Smail Berrah
Ingan/Gan Tandem Solar Cell Parameter Estimation: A Comparative Stud, Abdelmoumene Benayad, Smail Berrah
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, two hybrid estimation approaches, hybrid genetic algorithm (TR-GA) and hybrid particle swarm optimization (TR-PSO), are used to estimate single-diode model InGaN/GaN solar cell parameters from J?V experimental data under AM0 illumination. These parameters are photocurrent density ($J_{ph}$), reverse saturation current density ($J_{s}$), ideality factor ($A$), series resistance ($R_{s}$), and shunt resistance ($R_{sh}$). The trust region (TR) method used in both approaches provides the initial conditions and helps to avoid the problem of premature convergence (due to local minimum). Simulation results based on the minimization of the mean square error between experimental and theoretical J-V characteristics show that …
Performance Comparison Of Optimization Algorithms In Lqr Controller Design For A Nonlinear System, Ümi̇t Önen, Abdullah Çakan, İlhan İlhan
Performance Comparison Of Optimization Algorithms In Lqr Controller Design For A Nonlinear System, Ümi̇t Önen, Abdullah Çakan, İlhan İlhan
Turkish Journal of Electrical Engineering and Computer Sciences
The development and improvement of control techniques has attracted many researchers for many years. Especially in the controller design of complex and nonlinear systems, various methods have been proposed to determine the ideal control parameters. One of the most common and effective of these methods is determining the controller parameters with optimization algorithms.In this study, LQR controller design was implemented for position control of the double inverted pendulum system on a cart. First of all, the equations of motion of the inverted pendulum system were obtained by using Lagrange formulation. These equations were linearized by Taylor series expansion around the …
Automatic Generation Control Analysis Of Power System With Nonlinearities Andelectric Vehicle Aggregators With Time-Varying Delay Implementing A Novel Control Strategy, Nimai Charan Patel, Binod Kumar Sahu, Manoj Kumar Debnath
Automatic Generation Control Analysis Of Power System With Nonlinearities Andelectric Vehicle Aggregators With Time-Varying Delay Implementing A Novel Control Strategy, Nimai Charan Patel, Binod Kumar Sahu, Manoj Kumar Debnath
Turkish Journal of Electrical Engineering and Computer Sciences
Automatic generation control (AGC) also known as load frequency control plays a vital role in interconnected power system for frequency regulation. Electric vehicles (EVs) with battery as the storage device can participate in frequency regulation service. In practice, a large number of EVs are aggregated as a single unit called EV aggregator for participation in frequency regulation service in AGC system. Participation of EV aggregators in AGC system for frequency regulation will be encouraged in near future because EVs have less environmental pollution than the conventional vehicles. However, participation of EV aggregators in AGC system may introduce time delay which …
Parameter Estimations From Gravity And Magnetic Anomalies Due To Deep-Seated Faults:Differential Evolution Versus Particle Swarm Optimization, Yunus Levent Eki̇nci̇, Çağlayan Balkaya, Gökhan Göktürkler
Parameter Estimations From Gravity And Magnetic Anomalies Due To Deep-Seated Faults:Differential Evolution Versus Particle Swarm Optimization, Yunus Levent Eki̇nci̇, Çağlayan Balkaya, Gökhan Göktürkler
Turkish Journal of Earth Sciences
Estimation of causative source parameters is an essential tool in exploration geophysics and is frequently applied using potential field datasets. Naturally inspired metaheuristic optimization algorithms based on some stochastic procedures have attracted more attention during the last decade due to their capability in finding the optimal solution of the model parameters from the parameter space via direct search routines. In this study, the solutions obtained through differential evolution algorithm, a rarely used metaheuristic algorithm in geophysics, and particle swarm optimization, which is one of the most used global optimization algorithms in geophysics, have been compared in terms of robustness, consistency, …
Particle Swarm Optimization-Based Collision Avoidance, Ti̇mur İnan, Ahmet Fevzi̇ Baba
Particle Swarm Optimization-Based Collision Avoidance, Ti̇mur İnan, Ahmet Fevzi̇ Baba
Turkish Journal of Electrical Engineering and Computer Sciences
Collision risk assessment and collision avoidance of vessels have always been an important topic in ocean engineering. Decision support systems are increasingly becoming the focus of many studies in the maritime industry today as vessel accidents are often caused by human error. This study proposes an anticollision decision support system that can determine surrounding obstacles by using the information received from radar systems, obtain the position and speed of obstacles within a certain time period, and suggest possible routes to prevent collisions. In this study we use a neural network to predict the subsequent positions of surrounding vessels, a fuzzy …
Available Transfer Capability Enhancement With Facts Using Hybrid Pi-Pso, Abubakar Sadiq Ahmad, Sunusi Sani Adamu, Muhammad Buhari
Available Transfer Capability Enhancement With Facts Using Hybrid Pi-Pso, Abubakar Sadiq Ahmad, Sunusi Sani Adamu, Muhammad Buhari
Turkish Journal of Electrical Engineering and Computer Sciences
In deregulation, growth in electrical loads necessitates improving power delivery, while nondiscriminatory access to transmission grid is a requirement. Deregulation causes a significant rise in transactions, which requires adequate transfer capability to secure economic transactions. In sustainable power delivery, FACTS devices are deployed to enhance available transfer capability (ATC). However, the high investment cost of FACTS makes the problem formulation a multiobjective optimization: power transfer maximization and minimization of FACTS sizes. Furthermore, due to the complexity in optimizing the control variables of voltage source converter types of FACTS, often the solution results in local optima and high computational time. This …
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. …
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 …
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 …
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 …
Modeling And Control Of A Permanent-Magnet Brushless Dc Motor Drive Using A Fractional Order Proportional-Integral-Derivative Controller, Swapnil Khubalkar, Anjali Junghare, Mohan Aware, Shantanu Das
Modeling And Control Of A Permanent-Magnet Brushless Dc Motor Drive Using A Fractional Order Proportional-Integral-Derivative Controller, Swapnil Khubalkar, Anjali Junghare, Mohan Aware, Shantanu Das
Turkish Journal of Electrical Engineering and Computer Sciences
This paper deals with the speed control of a permanent-magnet brushless direct current (PMBLDC) motor. A fractional order PID (FOPID) controller is used in place of the conventional PID controller. The FOPID controller is a generalized form of the PID controller in which the order of integration and differentiation is any real number. It is shown that the proposed controller provides a powerful framework to control the PMBLDC motor. Parameters of the controller are found by using a novel dynamic particle swarm optimization (dPSO) method. The frequency domain pole-zero (p-z) interlacing method is used to approximate the fractional order operator. …
An Intelligent Pso-Based Energy Efficient Load Balancing Multipath Technique In Wireless Sensor Networks, Sukhchandan Randhawa, Sushma Jain
An Intelligent Pso-Based Energy Efficient Load Balancing Multipath Technique In Wireless Sensor Networks, Sukhchandan Randhawa, Sushma Jain
Turkish Journal of Electrical Engineering and Computer Sciences
To provide a reliable and efficient service, load balancing plays an important role in wireless sensor networks (WSNs). There is a need to maximize the network lifetime for WSNs applications with periodic generation of data. Due to the relationship between energy consumption and network sensor node lifetime, energy consumption in a network should be minimized and balanced in order to increase network lifetime. Energy-efficient load-balancing techniques are needed to solve this problem. In this paper, a particle swarm optimization (PSO)-based energy-efficient load-balancing technique is proposed, in which the required number of routing paths and energy consumption of different nodes and …
Time-Jerk Optimal Trajectory Planning Of A 7-Dof Redundant Robot, Shaotian Lu, Jingdong Zhao, Li Jiang, Hong Liu
Time-Jerk Optimal Trajectory Planning Of A 7-Dof Redundant Robot, Shaotian Lu, Jingdong Zhao, Li Jiang, Hong Liu
Turkish Journal of Electrical Engineering and Computer Sciences
In order to improve the efficiency and smoothness of a robot and reduce its vibration, an algorithm called the augmented Lagrange constrained particle swarm optimization (ALCPSO), which combines constrained particle swarm optimization with the augmented Lagrange multiplier method to realize time-jerk (defined as the derivative of the acceleration) optimal trajectory planning is proposed. Kinematic constraints such as joint velocities, accelerations, jerks, and traveling time are considered. The ALCPSO algorithm is used to avoid local optimization because a new particle swarm is newly produced at each initial time process. Additionally, the best value obtained from the former generation is saved and …
Optimal Siting And Sizing Of Rapid Charging Station For Electric Vehicles Considering Bangi City Road Network In Malaysia, Mainul Islam, Hussain Shareef, Azah Mohamed
Optimal Siting And Sizing Of Rapid Charging Station For Electric Vehicles Considering Bangi City Road Network In Malaysia, Mainul Islam, Hussain Shareef, Azah Mohamed
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, electric vehicles (EVs) have been seen as a felicitous option towards a less carbon-intensive road transport. The key issue in this system is recharging the EV batteries before they are exhausted. Thus, charging stations (CSs) should be carefully located to make sure EV users can access a CS within their driving range. Considering geographic information and traffic density, this paper proposes an optimization overture for optimal siting and sizing of a rapid CS (RCS). It aims to minimize the daily total cost (which includes the cost of substation energy loss, traveling cost of EVs to the CS, and investment, …
Applying Metaheuristic Optimization Methods To Design Novel Adaptive Pi-Type Fuzzy Logic Controllers For Load-Frequency Control In A Large-Scale Power Grid, Thimaiphuong Dao, Yaonan Wang, Ngockhoat Nguyen
Applying Metaheuristic Optimization Methods To Design Novel Adaptive Pi-Type Fuzzy Logic Controllers For Load-Frequency Control In A Large-Scale Power Grid, Thimaiphuong Dao, Yaonan Wang, Ngockhoat Nguyen
Turkish Journal of Electrical Engineering and Computer Sciences
Due to the complexity and diversity of large-scale power systems in practice, designing load-frequency control (LFC) strategies against load variations faces big challenges to ensure the stability and economy of the network. The focus of this paper is to design a novel adaptive PI-type fuzzy logic (FL)-based LFC architecture for solving the LFC problem in such an interconnected electric power grid. Applying 2 biologically inspired optimization methods, namely particle swarm optimization method and a genetic algorithm, the membership functions and rule base of a basic PI-type FL model were parameterized and optimized simultaneously and successfully. An online self-tuning method was …
Fuzzy Pso-Based Algorithm For Controlling Base Station Movements In A Wireless Sensor Network, Moosa Ayati, Mahdi Pasha Zanousi
Fuzzy Pso-Based Algorithm For Controlling Base Station Movements In A Wireless Sensor Network, Moosa Ayati, Mahdi Pasha Zanousi
Turkish Journal of Electrical Engineering and Computer Sciences
There are strong limitations on the software, energy, and hardware capacities of a wireless sensor network (WSN) and therefore algorithms that increase the lifetime of a WSN are of great significance. In this paper, a mobile base station movement control strategy for WSNs is proposed. This strategy combines fuzzy logic node clustering, fuzzy cluster-head selection, and fuzzy logic control (FLC) of the base station movements. After determining cluster-heads, according to the distance and energy of the heads, the base station moves on a predefined square, triangle, circle, or hexagon shaped path. Direction and speed of the movements are controlled by …
The Parallel Resonance Impedance Detection Method For Parameter Estimation Of Power Line And Transformer By Using Csa, Ga, And Pso, Bahadir Akbal, Abdullah Ürkmez
The Parallel Resonance Impedance Detection Method For Parameter Estimation Of Power Line And Transformer By Using Csa, Ga, And Pso, Bahadir Akbal, Abdullah Ürkmez
Turkish Journal of Electrical Engineering and Computer Sciences
Power line parameters are an important factor in relay applications and power quality studies. In the literature, the phasor measurement unit method and measuring of current and voltage at two ends of the power line were usually used to estimate the power line parameters. In this study, the parallel resonance impedance detection method was used to estimate the power line parameter to obtain input data. The real measurement values are used to obtain parallel resonance impedance in this method. The real measurement values include the measurement errors of the current and voltage transformer. Thus, the estimated parameter values are realistic. …
Lifetime Maximization Of Wireless Sensor Networks Using Particle Swarm Optimization, Aleem Kabeer Mir, Muhammad Zubair, Ijaz Mansoor Qureshi
Lifetime Maximization Of Wireless Sensor Networks Using Particle Swarm Optimization, Aleem Kabeer Mir, Muhammad Zubair, Ijaz Mansoor Qureshi
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless sensor networks have multiple applications in intelligent environment and structural monitoring. The major challenge in wireless sensor networks is the power constraint. This paper deals with minimizing the energy utilization of wireless sensor nodes and maximizing their overall life span. The objective of our proposed scheme is to find a method for grouping sensors into the maximum number of distinct sensor cover sets to totally monitor the required area. This problem can be solved by using the disjoint cover set problem. Present optimization techniques take much time and deliver unsatisfactory results in large-scale networks. This paper proposes a technique …