Search research articles

Related Concept Videos

Maximum Power Transfer

Maximum Power Transfer

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...

You might also read

Related Articles

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

Sort by

Same author

Design, Implementation, and Evaluation of an ADDIE Model-Based Structured Educational Intervention to Improve Anesthesia Students' Patient Handover Skills: A Sequential Explanatory Mixed-Methods Study.

Health science reports·2026

Same author

Effect of the BOPPPS model on pre-anesthesia care education for nurse anesthesia students in Iran: a quasi-experimental study.

BMC medical education·2026

Same author

Implementation of an online flipped classroom combined with case-based learning in small groups to improve knowledge of obstetric anesthesia.

Journal of education and health promotion·2026

Same author

Enhancing anesthesia monitoring training: a SPOC and Gagné's model hybrid personalized by artificial intelligence.

BMC medical education·2026

Same author

Specifying the Objectives and Techniques of a Competency-based Training Program to Improve Post-anesthesia Care Unit Nurse Performance: A Delphi Study.

Iranian journal of nursing and midwifery research·2025

Same author

Evaluating shear strength and acoustic emission in rock-like materials with non-persistent joint geometries under freeze-thaw conditions.

Scientific reports·2025

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

Search research articles

Related Experiment Video

Updated: May 2, 2026

A Protocol for Real-time 3D Single Particle Tracking

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

A novel algorithm for maximum power point tracking using computer vision (CVMPPT).

Morteza Ahmadi^1,2, Masoud Abrari¹, Majid Ghanaatshoar¹

¹Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, Iran.

|April 11, 2024

Summary

This study introduces a novel computer vision algorithm for solar module maximum power point (MPP) tracking. It enhances speed and reliability by replacing iterative methods with digital image processing, improving solar energy harvesting.

More Related Videos

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Published on: November 14, 2018

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

Related Experiment Videos

Last Updated: May 2, 2026

A Protocol for Real-time 3D Single Particle Tracking

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Published on: November 14, 2018

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

Area of Science:

Renewable Energy Systems
Photovoltaic Technology
Artificial Intelligence in Energy

Background:

Solar module performance is defined by power-voltage curves, with peak tracking crucial for maximum power extraction.
Environmental factors like temperature and irradiance shift the maximum power point (MPP).
Partial shading creates multiple peaks, complicating traditional iterative maximum power point tracking (MPPT) methods, which are often slow and unreliable under dynamic conditions.

Purpose of the Study:

To develop and validate a novel computer vision-based algorithm for accurate and efficient global maximum power point (MPP) tracking in solar modules.
To overcome the limitations of conventional iterative MPPT techniques, particularly under partial shading and rapidly changing environmental conditions.

Main Methods:

A new algorithm employing computer vision techniques to identify the global MPP on the solar module's power-voltage curve was developed.
The algorithm was implemented using Matlab/Simulink, focusing on replacing iterative analogue calculations with digital processing.
Experimental validation was performed to verify the algorithm's effectiveness and real-time performance.

Main Results:

The proposed computer vision algorithm successfully identified the global maximum power point (MPP) without relying on iterative voltage calculations.
The algorithm demonstrated increased speed and enhanced reliability in MPP tracking compared to traditional methods.
Real-time data acquisition for the MPP was achieved, confirming the algorithm's practical applicability.

Conclusions:

The novel computer vision algorithm offers a significant advancement in maximum power point tracking (MPPT) for solar modules.
This approach provides a faster, more reliable, and iteration-free method for optimizing solar energy harvesting, especially under challenging conditions.
The digital, vision-based strategy represents a promising direction for future solar energy management systems.