Design of a DC to DC converter for a residential grid connected solar energy system

Elgbaily, Mohamed, Anayi, Fatih ORCID: https://orcid.org/0000-0001-8408-7673 and Elgamli, Elmazeg 2022. Design of a DC to DC converter for a residential grid connected solar energy system. Presented at: 1st International Electronic Conference on Processes: Processes System Innovation, Online, 17–31 May 2022. Engineering Proceedings. Engineering Proceedings. (19(1)6) MDPI, 10.3390/ECP2022-12620

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Abstract

This article presents an investigation of a PV solar system based on Maximum Power Point Tracking (MPPT) using one of the artificial intelligence control techniques. To avoid the problems of the traditional P&O method, the optimization tool of Particle Swarm Optimization (PSO) is proposed to be employed with a Perturbation & Observation (P&O) technique with added a Proportional Integral (PI) controller (PSO + PI + P&O). This proposed method achieved the optimal operating variables of a photovoltaic (PV) module in terms to mitigating the issue of partial shading weather conditions. A DC–DC boost converter is designed to be switched to obtain the desired MPP based on the corresponding duty cycle according to the parameters provided by the IV characteristics. It is observed from the results that the proposed PSO + PI + P&O showed excellent improvement. Moreover, better performance was achieved in terms of extracting the maximum unique power point between both variables of current and voltage generated from the PV. The proposed MPPT control method was implemented in MATLAB/Simulink. The testbed of the suggested method was thorough and highlighted its high efficiency compared to the conventional P&O as well as the PI controller based on P&O methods.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Additional Information:	This is an open access article distributed under the Creative Commons Attribution License
Publisher:	MDPI
ISSN:	2673-4591
Date of First Compliant Deposit:	30 August 2022
Last Modified:	10 Nov 2022 11:51
URI:	https://orca.cardiff.ac.uk/id/eprint/152069

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