Mod Tanh-Activated Physical Neural Network MPPT Control Algorithm for Varying Irradiance Conditions

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10260632" target="_blank" >RIV/61989100:27240/25:10260632 - isvavai.cz</a>

Result on the web

<a href="https://scijournals.onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70062?getft_integrator=scopus&src=getftr&utm_source=scopus" target="_blank" >https://scijournals.onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70062?getft_integrator=scopus&src=getftr&utm_source=scopus</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/ese3.70062" target="_blank" >10.1002/ese3.70062</a>

Result language

angličtina

Original language name

Mod Tanh-Activated Physical Neural Network MPPT Control Algorithm for Varying Irradiance Conditions

Original language description

The increasing adoption of solar photovoltaic systems necessitates efficient maximum power point tracking (MPPT) algorithms to ensure optimal performance. This study proposes a Mod tanh-activated physical neural network (MAPNN)-based MPPT control algorithm, which addresses inefficiencies in existing models caused by spectral mismatch and improper converter control. The proposed method incorporates beta-distributed point estimation technique for mismatch factor correction and a Buck-Boost converter with a feedback control using the Chinese Remainder Theorem – Puzzle Optimization Algorithm-tuned PID controller. Simulations demonstrate an efficiency improvement of 98.42%, with a 4.54 dB reduction in total harmonic distortion and faster convergence compared to traditional methods such as ANN and LSTM. This system significantly enhances MPPT performance under dynamic irradiance conditions.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20201 - Electrical and electronic engineering

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Energy Science &amp; Engineering

ISSN

2050-0505

e-ISSN

—

Volume of the periodical

13

Issue of the periodical within the volume

6

Country of publishing house

US - UNITED STATES

Number of pages

14

Pages from-to

"2606 "- 2619

UT code for WoS article

001457606800001

EID of the result in the Scopus database

2-s2.0-105001834095