Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

1.1K
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the power...
1.1K
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

742
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
742
Power Factor Correction01:20

Power Factor Correction

739
The power transmission to a factory involves the transfer of apparent power, a combination of active and reactive power. The power factor measures how effectively electrical power is converted into useful work output. The ratio of the real power (KW) that does the work to the apparent power (KVA) supplied to the circuit.
739
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

916
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
916
Maximum Power Transfer01:16

Maximum Power Transfer

1.2K
Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
1.2K
Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

934
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
934

You might also read

Related Articles

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

Sort by
Same author

Automatic detection and quantification of antimicrobial inhibition zones using YOLO11n with <i>post-hoc</i> interpretability validation.

Frontiers in microbiology·2026
Same author

Parameter Estimation in photovoltaic systems using a hybrid Bat and crow metaheuristic algorithm.

Scientific reports·2026
Same author

Alzheimer's Disease Prediction Using Fisher Mantis Optimization and Hybrid Deep Learning Models.

Diagnostics (Basel, Switzerland)·2025
Same author

Melanoma Skin Cancer Recognition with a Convolutional Neural Network and Feature Dimensions Reduction with Aquila Optimizer.

Diagnostics (Basel, Switzerland)·2025
Same author

Deep Learning Neural Network Based on PSO for Leukemia Cell Disease Diagnosis from Microscope Images.

Journal of imaging informatics in medicine·2025
Same author

Alzheimer's Prediction Methods with Harris Hawks Optimization (HHO) and Deep Learning-Based Approach Using an MLP-LSTM Hybrid Network.

Diagnostics (Basel, Switzerland)·2025

Related Experiment Video

Updated: Apr 19, 2026

Fabrication of High Contrast Gratings for the Spectrum Splitting Dispersive Element in a Concentrated Photovoltaic System
12:08

Fabrication of High Contrast Gratings for the Spectrum Splitting Dispersive Element in a Concentrated Photovoltaic System

Published on: July 18, 2015

11.3K

A Fuzzy Fishier Mantis Optimizer method for MPPT in PV solar system.

Hamza Elamouri Elwaer1, Selçuk Alparslan Avci1, Javad Rahebi2

  • 1Department of Electrical and Electronics Engineering, Karabuk University, Karabuk, Turkey.

Scientific Reports
|April 17, 2026
PubMed
Summary

This study introduces a novel Fuzzy Fishier Mantis Optimizer (FFMO) algorithm for photovoltaic (PV) systems to maximize power output. The FFMO algorithm effectively tracks the maximum power point (MPP) under changing environmental conditions.

Keywords:
Fishier Mantis OptimizerMPPT algorithmPV solar system

More Related Videos

Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass ADG Fresnel Lens for Concentrating Photovoltaics
09:00

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

9.4K

Related Experiment Videos

Last Updated: Apr 19, 2026

Fabrication of High Contrast Gratings for the Spectrum Splitting Dispersive Element in a Concentrated Photovoltaic System
12:08

Fabrication of High Contrast Gratings for the Spectrum Splitting Dispersive Element in a Concentrated Photovoltaic System

Published on: July 18, 2015

11.3K
Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass ADG Fresnel Lens for Concentrating Photovoltaics
09:00

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

9.4K

Area of Science:

  • Renewable Energy Systems
  • Electrical Engineering
  • Control Systems

Background:

  • Optimizing power extraction from photovoltaic (PV) solar systems is crucial for efficiency.
  • Existing maximum power point tracking (MPPT) methods face challenges with dynamic environmental conditions.

Purpose of the Study:

  • To develop and evaluate a novel MPPT algorithm for PV systems using the Fuzzy Fishier Mantis Optimizer (FFMO).
  • To enhance the performance of PV battery systems through optimized voltage control and fuzzy logic MPPT.

Main Methods:

  • Implementation of a Fuzzy Logic-based MPPT algorithm combined with the FFMO.
  • Optimization of a proportional integral (PI) voltage controller using the Fishier-Mantis optimizer.
  • System modeling and simulation using MATLAB Simulink.
  • Comparative analysis against particle swarm optimization and genetic algorithms.

Main Results:

  • The FFMO-based MPPT algorithm effectively tracks the maximum power point (MPP) under varying irradiance and load conditions.
  • The optimized PI controller ensures stable voltage across the load, supporting the MPPT function.
  • Simulations demonstrated superior performance of the proposed PV battery system compared to conventional methods.

Conclusions:

  • The novel FFMO-based MPPT algorithm offers a robust solution for maximizing PV system efficiency.
  • The integrated fuzzy logic MPPT and optimized PI controller provide enhanced performance and stability.
  • This approach is a competitive alternative to existing optimization techniques for PV systems.