Nature-Inspired Dragonfly MPPT Algorithm for Solar PV System

In recent years, renewable energy attracts the researchers interest due to its environment free nature and abundant availability. Solar photovoltaic (PV) is widely used to generation power from the sun light. Major issue in solar PV power generation is tracking the peak power from the available multiple power peaks in the operating points. A proper MPPT algorithm is required to capture the maximum power point (MPP) from the characteristic curves of a solar PV under partial shaded conditions (PSC). An optimized maximum power point tracking (MPPT) and fault classification in solar PV systems are presented in this research work. To select the best optimization model for MPPT under PSC, the nature-inspired dragonfly algorithm (DA), is used in this work to evaluate the Maximum power <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\mathrm{P}_{\max})$</tex>, MPPT power (MPPTP), and tracking efficiency (TE) of the solar PV systems. From the simulation results, DA priveds a 94.66% TE. Similarly, the proposed algorithm exhibits a Pmax of 774.63 watts and MPPTP of 733.37 watts.

Authors

Institutions

Publication Details

Published
2024-12-11
DOI
https://doi.org/10.1109/ieeeconf63577.2024.10881507
Citations
1
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.17
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Nature-Inspired Dragonfly MPPT Algorithm for Solar PV System

S. Senthilkumar, M. Nuthal Srinivasan, S. P. Mangaiyarkarasi, Prathibha S. Babu et al.
1 citations
Power Systems and Renewable Energy
0.17
article

Nature-Inspired Dragonfly MPPT Algorithm for Solar PV System

S. Senthilkumar, M. Nuthal Srinivasan, S. P. Mangaiyarkarasi, Prathibha S. Babu, R. Gandhi Raj, B S Gopika
article en
1 citations

Abstract

In recent years, renewable energy attracts the researchers interest due to its environment free nature and abundant availability. Solar photovoltaic (PV) is widely used to generation power from the sun light. Major issue in solar PV power generation is tracking the peak power from the available multiple power peaks in the operating points. A proper MPPT algorithm is required to capture the maximum power point (MPP) from the characteristic curves of a solar PV under partial shaded conditions (PSC). An optimized maximum power point tracking (MPPT) and fault classification in solar PV systems are presented in this research work. To select the best optimization model for MPPT under PSC, the nature-inspired dragonfly algorithm (DA), is used in this work to evaluate the Maximum power <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\mathrm{P}_{\max})$</tex>, MPPT power (MPPTP), and tracking efficiency (TE) of the solar PV systems. From the simulation results, DA priveds a 94.66% TE. Similarly, the proposed algorithm exhibits a Pmax of 774.63 watts and MPPTP of 733.37 watts.

Anna University, Chennai (IN), Open International University for Alternative Medicines (IN), Dhanalakshmi Srinivasan Group of Institutions (IN), E.G.S. Pillay Engineering College
Openalex Percentile: Top 40%
Power Systems and Renewable Energy
0.17
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Nature-Inspired Dragonfly MPPT Algorithm for Solar PV System — S. Senthilkumar, M. Nuthal Srinivasan, et al. · (2024) | TGRS Research Map | TGRS