Efficient Parameter Estimation of Double Diode-Based PV Cell Model Using Marine Predators Algorithm

Yeşilbudak, Mehmet; Çolak, Medine

doi:10.1109/icrera52334.2021.9598635

Cited by 6 publications

(2 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Marine Predator Algorithm (MPA) is a novel swarm-based algorithm proposed by Faramarzi [1]. The algorithm is broadly used to handle PV systems [2][3][4], electrical energy domain [5], image segmentation and recognition problems [6,7], task scheduling optimization [8], and other engineering problems. In MPA, the population is mainly searched near the optimal individuals during position updating without using the effective information of more individuals, which tends to lead to the reduction of population diversity.…”

Section: Introductionmentioning

confidence: 99%

Hybrid opposite-based learning marine predator algorithm

Geng¹,

Liu²

2023

International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023)

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Hybrid opposite-based learning marine predator algorithm

Geng¹,

Liu²

2023

International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023)

View full text Add to dashboard Cite

“…However, the information obtained from the PV manufacturer data sheets alone is insufficient for modeling PV cells, modules, and arrays. Therefore, it is necessary to create electrically equivalent circuit models *Sorumlu Yazar (Corresponding Author) e-posta : kezbankoc@gazi.edu.tr to PV models and extract unknown parameters [7]. Equivalent circuit equations are non-linear due to the diodes in the electrical equivalent circuits of PV cells.…”

Section: Introductionmentioning

confidence: 99%

Parameter Extraction of Photovoltaic Models by Honey Badger algorithm and Wild Horse Optimizer

KOÇ>

Demirtaş

Çetinbaş

2023

Journal of Polytechnic

View full text Add to dashboard Cite

Analyzing the processes ranging from the determination of the installation configuration of the photovoltaic (PV) systems to the operation at the maximum power, from the technical and economic feasibility study to the positive contribution to the region where the production is planned are just possible with the accurate and efficient simulation models of the PV systems. PV parameter extraction, which is a topic frequently discussed recently, is crucial for the detailed modeling of PV cells and modules and simulating the behavior of these systems. For this reason, the current study examined PV parameter extraction and solved this optimization problem with the honey badger algorithm (HBA) and wild horse optimizer (WHO). PV cells and modules were modeled with the single diode model (SDM) and double diode model (DDM) and tested with actual measurement data. The root-mean-square error (RMSE) was chosen as the objective function, and the results were compared with the evaluation metrics for computational accuracy and time. Based on four PV model results, RMSE values were calculated between 9.9318E-04 to 1.7011E-03 for HBA and between 9.8602E-04 and 1.7298E-03 for WHO. As a result, even though both algorithms produce successful, stable, and fast results in PV parameter extraction, the WHO yielded better results.

show abstract

Marine Predators Algorithm: A Review

Al-Betar

Awadallah

Makhadmeh

et al. 2023

Arch Computat Methods Eng

View full text Add to dashboard Cite

Marine Predators Algorithm (MPA) is a recent nature-inspired optimizer stemmed from widespread foraging mechanisms based on Lévy and Brownian movements in ocean predators. Due to its superb features, such as derivative-free, parameter-less, easy-to-use, flexible, and simplicity, MPA is quickly evolved for a wide range of optimization problems in a short period. Therefore, its impressive characteristics inspire this review to analyze and discuss the primary MPA research studies established. In this review paper, the growth of the MPA is analyzed based on 102 research papers to show its powerful performance. The MPA inspirations and its theoretical concepts are also illustrated, focusing on its convergence behaviour. Thereafter, the MPA versions suggested improving the MPA behaviour on connecting the search space shape of real-world optimization problems are analyzed. A plethora and diverse optimization applications have been addressed, relying on MPA as the main solver, which is also described and organized. In addition, a critical discussion about the convergence behaviour and the main limitation of MPA is given. The review is end-up highlighting the main findings of this survey and suggests some possible MPA-related improvements and extensions that can be carried out in the future.

show abstract

Efficient Parameter Estimation of Double Diode-Based PV Cell Model Using Marine Predators Algorithm

Cited by 6 publications

References 32 publications

Hybrid opposite-based learning marine predator algorithm

Hybrid opposite-based learning marine predator algorithm

Parameter Extraction of Photovoltaic Models by Honey Badger algorithm and Wild Horse Optimizer

Marine Predators Algorithm: A Review

Contact Info

Product

Resources

About