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338470

Monitoring and enhancing the performance of PV systems using IoT and artificial intelligence algorithms

Article

Last updated: 05 Jan 2025

Subjects

-

Tags

Section B: Artificial Intelligence

Abstract

Monitoring and enhancing the performance of PV systems is a critical criterion for PV power plants. Hence, in the present paper, a smart prototype of the IoT technique and AI algorithms (here PSO) were used to achieve monitoring and enhancing performance of PV systems. A smart IoT technique based on embedded system through Node MCU ESP8266 has been constructed to monitor the solar power irradiance of solar cell systems. The measured results were displayed by ubidots through the HTTP protocol. Meanwhile, enhancing the performance of PV system is carried out using the PSO algorithm. The measured solar power irradiance was inlaid to the MATLAB simulation program as hardware in the loop to estimate the current, voltage, and output power in order to study the performance of the proposed PSO algorithm. Many improvements were carried out on the conventional PSO algorithm by a continuous modulation of the duty cycle to harvest maximum power output for long hours daily. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system and the achieved power output using the improved PSO made them a strong candidate for enhancing the performance of PV systems.

DOI

10.21608/erurj.2024.241998.1080

Keywords

PV systems, Maximum power output, IOT, AI Algorithms

Authors

First Name

Ahmed

Last Name

Ali

MiddleName

-

Affiliation

Department of Telecommunications Engineering, Faculty of Engineering, Egyptian Russian University, Egypt

Email

ahmed-hamdy@eru.edu.eg

City

-

Orcid

-

First Name

Raafat

Last Name

El-Kammar

MiddleName

-

Affiliation

Electrical Eng. Department, Faculty of Eng. (Shoubra), Benha University, Egypt

Email

rafat.alkmaar@feng.bu.edu.eg

City

-

Orcid

-

First Name

Hesham

Last Name

Hamed

MiddleName

Fathy

Affiliation

Artificial Intelligence, Dean of Faculty of Artificial Intelligence, Egyptian Russian University, Badr, Egypt/Department of Electrical Engineering, Faculty of Engineering, Minia University, Minia, Egypt

Email

hfah66@yahoo.com

City

Badr

Orcid

-

First Name

Adel

Last Name

Elbaset

MiddleName

-

Affiliation

Department of Electromechanics Engineering, Faculty of Engineering, Heliopolis University, Cairo, Egypt

Email

adel.soliman@hu.edu.eg

City

-

Orcid

-

First Name

Aya

Last Name

Hossam

MiddleName

-

Affiliation

Electrical Engineering Department, Faculty of Engineering (Shoubra), Benha University, Benha, Egypt

Email

aya.ahmed@feng.bu.edu.eg

City

-

Orcid

-

Volume

3

Article Issue

1

Related Issue

45868

Issue Date

2024-01-01

Receive Date

2023-10-11

Publish Date

2024-01-01

Page Start

950

Page End

964

Print ISSN

2812-6211

Online ISSN

2812-622X

Link

https://erurj.journals.ekb.eg/article_338470.html

Detail API

https://erurj.journals.ekb.eg/service?article_code=338470

Order

338,470

Type

Original Article

Type Code

2,445

Publication Type

Journal

Publication Title

ERU Research Journal

Publication Link

https://erurj.journals.ekb.eg/

MainTitle

Monitoring and enhancing the performance of PV systems using IoT and artificial intelligence algorithms

Details

Type

Article

Created At

29 Dec 2024