Integrating renewable energy and V2G uncertainty into optimal power flow: A gradient bald eagle search optimization algorithm with local escaping operator DOI Creative Commons
Mohamed H. Hassan, Salah Kamel, José Luis Domínguez‐García

et al.

IET Renewable Power Generation, Journal Year: 2023, Volume and Issue: unknown

Published: Nov. 3, 2023

Abstract Here, a new approach is proposed for solving the optimal power flow (OPF) problem in transmission networks using Gradient Bald Eagle Search Algorithm (GBES) with Local Escaping Operator (LEO). The method takes into account uncertainty of renewable energy sources (wind and photovoltaic systems) Vehicle‐to‐Grid (V2G) stochastic OPF problem. To improve efficiency technique enhance its local exploitation capability, LEO method's selection features are utilized. Monte Carlo methods employed to estimate generation costs PEVs study their feasibility. represented by Weibull, lognormal, normal probability distribution functions (PDFs). GBES experimentally compared well‐known meta‐heuristics twenty‐three different test functions, results indicate superiority over BES other recently developed algorithms. Furthermore, effectiveness evaluated IEEE 30‐bus system under various scenarios, simulation demonstrate that it can effectively address issues considering V2G, providing superior solutions

Language: Английский

Marine predators algorithm: A comprehensive review DOI Creative Commons
Sylvère Mugemanyi, Zhaoyang Qu, François Xavier Rugema

et al.

Machine Learning with Applications, Journal Year: 2023, Volume and Issue: 12, P. 100471 - 100471

Published: June 1, 2023

Marine predators algorithm (MPA) is a recently proposed metaheuristic that mimics the marine behavior when attacking their preys. Recently, MPA has been broadly employed to tackle numerous optimization problems in various research areas and confirmed its supremacy over large number of algorithms regard convergence speed accuracy thanks simplicity, flexible implementation few adjustable parameters requirements. A comprehensive review presented this paper along with variants such as binary, discrete, modifications, hybridizations, chaotic, quantum multi-objective versions. This also reviews applications electrical engineering, computer science, medicine, etc. Moreover, further directions for are suggested. The source code can be found at: http://www.alimirjalili.com/MPA.html.

Language: Английский

Citations

20
Marine predator’s algorithm: a survey of recent applications DOI
Laith Abualigah,

Suhier Odah,

Abiodun M. Ikotun

et al.

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 133 - 145

Published: Jan. 1, 2024

Language: Английский

Citations

6
An innovative quadratic interpolation salp swarm-based local escape operator for large-scale global optimization problems and feature selection DOI
Mohammed Qaraad,

Souad Amjad,

Nazar K. Hussein

et al.

Neural Computing and Applications, Journal Year: 2022, Volume and Issue: 34(20), P. 17663 - 17721

Published: June 2, 2022

Language: Английский

Citations

25
Salp swarm algorithm with iterative mapping and local escaping for multi-level threshold image segmentation: a skin cancer dermoscopic case study DOI Creative Commons
Shuhui Hao, Changcheng Huang, Ali Asghar Heidari

et al.

Journal of Computational Design and Engineering, Journal Year: 2023, Volume and Issue: 10(2), P. 655 - 693

Published: Jan. 11, 2023

Abstract If found and treated early, fast-growing skin cancers can dramatically prolong patients’ lives. Dermoscopy is a convenient reliable tool during the fore-period detection stage of cancer, so efficient processing digital images dermoscopy particularly critical to improving level cancer diagnosis. Notably, image segmentation part preprocessing essential technical support in process processing. In addition, multi-threshold (MIS) technology extensively used due its straightforward effective features. Many academics have coupled different meta-heuristic algorithms with MIS raise quality. Nonetheless, these frequently enter local optima. Therefore, this paper suggests an improved salp swarm algorithm (ILSSA) method that combines iterative mapping escaping operator address drawback. Besides, also proposes ILSSA-based approach, which triumphantly utilized segment dermoscopic cancer. This uses two-dimensional (2D) Kapur’s entropy as objective function employs non-local means 2D histogram represent information. Furthermore, array benchmark test experiments demonstrated ILSSA could alleviate optimal problem more effectively than other compared algorithms. Afterward, experiment displayed proposed obtained superior results peers was adaptable at thresholds.

Language: Английский

Citations

16
Integrating renewable energy and V2G uncertainty into optimal power flow: A gradient bald eagle search optimization algorithm with local escaping operator DOI Creative Commons
Mohamed H. Hassan, Salah Kamel, José Luis Domínguez‐García

et al.

IET Renewable Power Generation, Journal Year: 2023, Volume and Issue: unknown

Published: Nov. 3, 2023

Abstract Here, a new approach is proposed for solving the optimal power flow (OPF) problem in transmission networks using Gradient Bald Eagle Search Algorithm (GBES) with Local Escaping Operator (LEO). The method takes into account uncertainty of renewable energy sources (wind and photovoltaic systems) Vehicle‐to‐Grid (V2G) stochastic OPF problem. To improve efficiency technique enhance its local exploitation capability, LEO method's selection features are utilized. Monte Carlo methods employed to estimate generation costs PEVs study their feasibility. represented by Weibull, lognormal, normal probability distribution functions (PDFs). GBES experimentally compared well‐known meta‐heuristics twenty‐three different test functions, results indicate superiority over BES other recently developed algorithms. Furthermore, effectiveness evaluated IEEE 30‐bus system under various scenarios, simulation demonstrate that it can effectively address issues considering V2G, providing superior solutions

Language: Английский

Citations

15