Controller design for automatic voltage regulator system using modified opposition-based weighted mean of vectors algorithm DOI
Serdar Ekinci, Özay Can, Davut İzci

et al.

International Journal of Modelling and Simulation, Journal Year: 2023, Volume and Issue: unknown, P. 1 - 18

Published: Oct. 27, 2023

This paper proposes a modified optimization technique to determine the parameters of real proportional-integral-derivative plus second-order derivative (real PIDD2) controller adopted in an automatic voltage regulator (AVR). In this regard, opposition learning (mOBL) based weighted mean vectors (INFO) algorithm (mOBL-INFO) is proposed for first time. The performance was initially tested on several benchmark functions with unimodal, multimodal, and low-dimensional properties. obtained results against test were compared original INFO as latter has already been shown present superior recent effective metaheuristic algorithms. developed mOBL-INFO then used adjust PIDD2 AVR system. method using analyses such transient response, stability, robustness. related demonstrated good promise system control. Furthermore, previously reported 26 methods also employed assess mOBL-INFO-based that study excellent response

Language: Английский

Improved adaptive gaining-sharing knowledge algorithm with FDB-based guiding mechanism for optimization of optimal reactive power flow problem DOI
Hüseyin Bakır, Serhat Duman, Uğur Güvenç

et al.

Electrical Engineering, Journal Year: 2023, Volume and Issue: 105(5), P. 3121 - 3160

Published: May 31, 2023

Language: Английский

Citations

18
Optimal PID Controllers for AVR Systems Using Hybrid Simulated Annealing and Gorilla Troops Optimization DOI Creative Commons
Sultan Alghamdi, Hatem F. Sindi, Muhyaddin Rawa

et al.

Fractal and Fractional, Journal Year: 2022, Volume and Issue: 6(11), P. 682 - 682

Published: Nov. 18, 2022

In the literature, all investigations dealing with regulator design in AVR loop observe system as a single input output (SISO) system, where is generator reference voltage, while voltage. Besides, parameters are determined by analyzing terminal voltage response for step change from zero to rated value of reference. Unlike literature approaches, this study, tuning controllers conducted modeling double (DISO) inputs setpoint and disturbance on excitation The transfer functions dependence were derived developed DISO-AVR model. A novel objective function estimating proposed. Also, metaheuristic algorithm named hybrid simulated annealing gorilla troops optimization employed solve problem. Many approaches compared using different structures practical limitations. Furthermore, experimental results 120 MVA synchronous generators HPP Piva (Montenegro) presented show drawbacks that value. Based results, proposed procedure efficient strongly applicable practice.

Language: Английский

Citations

25
Design of Multivariate PID Controller for Power Networks Using GEA and PSO DOI Open Access
Mahmoud Zadehbagheri, Alfian Ma’arif, Rahim Ildarabadi

et al.

Journal of Robotics and Control (JRC), Journal Year: 2023, Volume and Issue: 4(1), P. 108 - 117

Published: March 30, 2023

The issue of proper modeling and control for industrial systems is one the challenging issues in industry. In addition, recent years, PID controller design linear has been widely considered. topic discussed some articles mostly speed field electric machines, where various algorithms have used to optimize considered controller, always most important challenges this designing a with high degree freedom. these researches, focus more on searching an algorithm optimal results than others order estimate parameters appropriate way. There are many techniques controller. Among methods, meta-innovative methods studied. effectiveness controlling proven. paper, new method grid discussed. method, power systems, which can be controlled effectively, so that four parameters, determine optimization evolutionary genetics (EGA) PSO used. One advantages their accuracy. article, tested single-machine system, system model presented first, then components will examined. following, according transformation function matrix relative gain matrix, suitable inputs each outputs determined. At end, multivariable MIMO presented. To show proposed simulation was performed MATLAB environment simulations

Language: Английский

Citations

16
A self-competitive mutation strategy for Differential Evolution algorithms with applications to Proportional–Integral–Derivative controllers and Automatic Voltage Regulator systems DOI Creative Commons
Mojtaba Ghasemi, Abolfazl Rahimnejad, Milad Gil

et al.

Decision Analytics Journal, Journal Year: 2023, Volume and Issue: 7, P. 100205 - 100205

Published: March 22, 2023

The Differential Evolution (DE) algorithm is a powerful and simple optimizer for solving various optimization problems. Based on the literature, DE has shown suitable performance in exploring search spaces locating global optimums. However, it typically slow extracting problem solution. In this paper, exploration ability of augmented with competitive control parameter ω based value objective function mutating members. A new mutation strategy introduced, subtracting weaker members from superior ones. proposed algorithm, which referred to as self-competitive DE, been employed real-world Several algorithms are enhanced ω, efficiencies resulting tested. Furthermore, optimal Proportional–Integral–Derivative (PID) controller tuning an Automatic Voltage Regulator (AVR) system used investigate effectiveness Simulation results demonstrate good over several other well-known algorithms.

Language: Английский

Citations

15
Integration of optimal power flow with combined heat and power dispatch of renewable wind energy based power system using chaotic driving training based optimization DOI
Chandan Paul,

Tushnik Sarkar,

Susanta Dutta

et al.

Renewable energy focus, Journal Year: 2024, Volume and Issue: 49, P. 100573 - 100573

Published: April 27, 2024

Language: Английский

Citations

5
A novel artificial hummingbird algorithm improved by natural survivor method DOI Creative Commons
Hüseyin Bakır

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(27), P. 16873 - 16897

Published: June 2, 2024

Abstract The artificial hummingbird algorithm (AHA) has been applied in various fields of science and provided promising solutions. Although the demonstrated merits optimization area, it suffers from local optimum stagnation poor exploration search space. To overcome these drawbacks, this study redesigns update mechanism original AHA with natural survivor method (NSM) proposes a novel metaheuristic called NSM-AHA. strength developed is that performs population management not only according to fitness function value but also NSM score value. adopted strategy contributes NSM-AHA exhibiting powerful avoidance unique ability. ability proposed was compared 21 state-of-the-art algorithms over CEC 2017 2020 benchmark functions dimensions 30, 50, 100, respectively. Based on Friedman test results, observed ranked 1st out 22 competitive algorithms, while 8th. This result highlights provides remarkable evolution convergence performance algorithm. Furthermore, two constrained engineering problems including single-diode solar cell model (SDSCM) parameters design power system stabilizer (PSS) are solved better results other 9.86E − 04 root mean square error for SDSCM 1.43E 03 integral time PSS. experimental showed optimizer solving global problems.

Language: Английский

Citations

5
Improved stochastic fractal search algorithm involving design operators for solving parameter extraction problems in real-world engineering optimization problems DOI
Evren İşen, Serhat Duman

Applied Energy, Journal Year: 2024, Volume and Issue: 365, P. 123297 - 123297

Published: April 27, 2024

Language: Английский

Citations

4
FOX Optimization Algorithm Based on Adaptive Spiral Flight and Multi-Strategy Fusion DOI Creative Commons
Zheng Zhang, Xiangkun Wang, Li Cao

et al.

Biomimetics, Journal Year: 2024, Volume and Issue: 9(9), P. 524 - 524

Published: Aug. 30, 2024

Adaptive spiral flight and multi-strategy fusion are the foundations of a new FOX optimization algorithm that aims to address drawbacks original method, including weak starting individual ergodicity, low diversity, an easy way slip into local optimum. In order enhance population, inertial weight is added along with Levy variable strategy once population initialized using tent chaotic map. To begin process implementing fox position created Tent map in provide more ergodic varied beginning locations. improve quality solution, second place. The random walk mode then updated updating approach. Subsequently, algorithm’s global searches balanced, flying method greedy approach incorporated update location. enhanced technique thoroughly contrasted various swarm intelligence algorithms engineering application issues CEC2017 benchmark test functions. According simulation findings, there have been notable advancements convergence speed, accuracy, stability, as well jumping out optimum, upgraded algorithm.

Language: Английский

Citations

4
A modified grey wolf optimizer with multi-solution crossover integration algorithm for feature selection DOI
Muhammad Ihsan, Fakhrud Din, Kamal Z. Zamli

et al.

Journal of Ambient Intelligence and Humanized Computing, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 3, 2025

Language: Английский

Citations

0
Improved snow geese algorithm for engineering applications and clustering optimization DOI Creative Commons
Haihong Bian, Can Li, Yuhan Liu

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 6, 2025

The Snow Goose Algorithm (SGA) is a new meta-heuristic algorithm proposed in 2024, which has been proved to have good optimization effect, but there are still problems that easy fall into local optimal and premature convergence. In order further improve the performance of algorithm, this paper proposes an improved (ISGA) based on three strategies according real migration habits snow geese: (1) Lead goose rotation mechanism. (2) Honk-guiding (3) Outlier boundary strategy. Through above strategies, exploration development ability original comprehensively enhanced, convergence accuracy speed improved. paper, two standard test sets IEEE CEC2022 CEC2017 used verify excellent algorithm. practical application ISGA tested through 8 engineering problems, employed enhance effect clustering results show compared with comparison faster iteration can find better solutions, shows its great potential solving problems.

Language: Английский

Citations

0