Enhancing photovoltaic MPPT with P&O algorithm performance based on adaptive PID control using exponential forgetting recursive least squares method

Meena E. Girgis and Nasr A. Elkhateeb

Renewable Energy, 2024, vol. 237, issue PC

Abstract: To maximize power transfer from the PV panel, a Perturb and Observe (P&O) algorithm and a feedback controller are used to create the Maximum Power Point Tracking (MPPT) algorithm. The dynamic performance of the MPPT algorithm depends on the feedback controller’s ability to track the PV panel voltage to the reference voltage from the P&O algorithm. This research introduces an adaptive Proportional-Integral-Derivative (PID) controller that improves the dynamic characteristics of the MPPT algorithm. The proposed adaptive control technique utilizes a PID controller and the exponential forgetting recursive least squares (EFRLS) algorithm to update the PID gains online. The verification process involves simulations under three scenarios: slow and fast variations in temperature, solar insolation, resistive load, and partial shading situations. The proposed adaptive PID controller performs robustly during tracking PV panel voltage under different atmospheric conditions.

Keywords: Photovoltaic; MPPT; Adaptive; Recursive-least-squares; PID-control; P&O algorithm (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S096014812401869X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:237:y:2024:i:pc:s096014812401869x

DOI: 10.1016/j.renene.2024.121801

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().