Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Optimizing Chromatographic Separations

Optimizing Chromatographic Separations

Optimizing chromatographic separations is crucial for obtaining clean separations in a minimum amount of time. Optimization is required for several factors, including kinetic effects related to band broadening, plate height, capacity factor, and separation factor.
Band broadening refers to spreading solute bands as they travel through the column. This broadening can impact resolution. Plate height (H) represents the length required for one theoretical plate. A lower plate height corresponds to...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Multidimensional Optimal Power Flow with Voltage Profile Enhancement in Electrical Systems via Honey Badger Algorithm.

Biomimetics (Basel, Switzerland)·2025

Same author

An adaptive coordination control solution to boost frequency stability for a hybrid distributed generation system.

PloS one·2025

Same author

Improving photovoltaic water pumping system performance with PSO-based MPPT and PSO-based direct torque control using real-time simulation.

Scientific reports·2025

Same author

Advanced AI approaches for the modeling and optimization of microgrid energy systems.

Scientific reports·2025

Same author

Improving photovoltaic water pumping system performance with ANN-based direct torque control using real-time simulation.

Scientific reports·2025

Same author

Optimization of solar water pumping systems through a combined approach based on MPPT-Bat and DTC.

PloS one·2025

Same journal

Novel Parent Survey Measures Sensory Behaviors Incorporating Sensory Modality and Stimulus Intensity.

Heliyon·2026

Same journal

Expression of concern: "SQSTM1/p62 promotes the progression of gastric cancer through epithelial-mesenchymal transition" [Heliyon 10 (2024) e24409].

Heliyon·2026

Same journal

Expression of concern: "TL1A promotes metastasis and EMT process of colorectal cancer" [Heliyon 10 (2024) e24392].

Heliyon·2026

Same journal

Expression of concern: "Factors affecting timing of surgery following neoadjuvant chemoradiation for esophageal cancer" [Heliyon 9 (2023) e23212].

Heliyon·2026

Same journal

Expression of concern: "On stratified single-valued soft topogenous structures" [Heliyon 10 (2024) e27926].

Heliyon·2026

Same journal

Expression of concern: "Artifact removal and motor imagery classification in EEG using advanced algorithms and modified DNN" [Heliyon 10 (2024) e27198].

Heliyon·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 14, 2025

Polycrystalline Silicon Thin-film Solar cells with Plasmonic-enhanced Light-trapping

Polycrystalline Silicon Thin-film Solar cells with Plasmonic-enhanced Light-trapping

Published on: July 2, 2012

A Fractional Order-Kepler Optimization Algorithm (FO-KOA) for single and double-diode parameters PV cell extraction.

Sultan Hassan Hakmi¹, Hashim Alnami¹, Ahmed Ginidi²

¹Department of Electrical and Electronic Engineering, College of Engineering and Computer Science, Jazan University, P.O. Box114, Jazan, 45142, Saudi Arabia.

|September 2, 2024

Summary

This summary is machine-generated.

The Fractional Order Kepler Optimization Algorithm (FO-KOA) significantly enhances photovoltaic (PV) parameter extraction accuracy. This novel method outperforms existing algorithms, improving efficiency and robustness in solar system applications.

Keywords:

Double-diode model Kepler optimization algorithm Parameters PV cell extraction Single-diode model

More Related Videos

Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass ADG Fresnel Lens for Concentrating Photovoltaics

Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass ADG Fresnel Lens for Concentrating Photovoltaics

Published on: October 27, 2017

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

Published on: August 20, 2019

Related Experiment Videos

Last Updated: Jun 14, 2025

Polycrystalline Silicon Thin-film Solar cells with Plasmonic-enhanced Light-trapping

Polycrystalline Silicon Thin-film Solar cells with Plasmonic-enhanced Light-trapping

Published on: July 2, 2012

Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass ADG Fresnel Lens for Concentrating Photovoltaics

Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass ADG Fresnel Lens for Concentrating Photovoltaics

Published on: October 27, 2017

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

Published on: August 20, 2019

Area of Science:

Electrical Engineering
Renewable Energy Systems
Computational Intelligence

Background:

Accurate photovoltaic (PV) module parameter identification is crucial for solar energy system performance and reliability.
Existing optimization algorithms often face challenges with premature convergence and local optima during parameter extraction.
The single-diode-model (SDM) and double-diode-model (DDM) are standard equivalent circuits used to represent PV module behavior.

Purpose of the Study:

To introduce and evaluate the Fractional Order Kepler Optimization Algorithm (FO-KOA) for enhanced PV module feature identification.
To improve the efficiency and robustness of parameter extraction for PV modules using FO-KOA.
To compare the performance of FO-KOA against the original Kepler Optimization Algorithm (KOA) and other contemporary methods.

Main Methods:

Development of FO-KOA by incorporating fractional order elements and a Local Escaping Approach (LEA) into the original KOA.
Application of FO-KOA for parameter extraction of PV modules using both SDM and DDM.
Comparative analysis of FO-KOA with KOA and other algorithms on KC-200, Ultra-Power-85, and SP-70 PV modules, and the RTC France PV cell.

Main Results:

FO-KOA demonstrated significant improvements in average accuracy, outperforming existing algorithms by 94.42%–99.73% in PV cell parameter extraction.
The algorithm showed remarkable robustness and consistent superiority, particularly for the KC200GT module.
Validation on SDM and DDM for the RTC France PV cell confirmed the effectiveness of FO-KOA.

Conclusions:

FO-KOA offers a superior approach for photovoltaic parameter extraction, overcoming limitations of traditional methods.
The algorithm's fractional order elements and LEA contribute to enhanced search efficiency and avoidance of local optima.
FO-KOA represents a significant advancement in optimizing PV module performance analysis for solar energy applications.