Iterated unscented Kalman filter-based maximum power point tracking for photovoltaic applications

A. K. Abdelsalam, Shu Goh, O. Abdelkhalik, S. Ahmed, A. Massoud

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

One of main challenges in harvesting power from a PV source is maximum power point tracking (MPPT). This is due to the nonlinear behaviour and characteristics of PV arrays. Conventional MPPT techniques usually utilize a hill climbing process which requires partial/full scan of the array power-voltage (P-V) curve resulting in high power fluctuation during peak searching. Dynamic estimation techniques, such as the Kalman filter, benefit from their ability to estimate non-measurable signals with rapid convergence. In this paper, a MPPT technique based on the Iterated Unscented Kalman Filter (IUKF) is presented. The proposed technique achieves: (i) satisfactory MPPT for PV arrays working under varying environmental conditions, (ii) PV array modelling with full parameter estimation including temperature and insolation level, and (iii) full estimation of the working P-V curve for the PV array. Only six measurement points are required for MPPT, modelling, and curve estimation; hence no full scan for the P-V curve is needed. This paper presents the system mathematical model and simulations. Moreover, an experimental setup is implemented illustrating practical results at various insolation levels and temperatures to validate the proposed technique.

Original languageEnglish
Title of host publicationProceedings, IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society
Pages1685-1693
Number of pages9
DOIs
Publication statusPublished - 1 Dec 2013
Event39th Annual Conference of the IEEE Industrial Electronics Society, IECON 2013 - Vienna, Austria
Duration: 10 Nov 201314 Nov 2013

Publication series

NameIECON Proceedings (Industrial Electronics Conference)

Other

Other39th Annual Conference of the IEEE Industrial Electronics Society, IECON 2013
CountryAustria
CityVienna
Period10/11/1314/11/13

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Keywords

  • Kalman Filter
  • Maximum Power Point
  • Maximum Power Point Tracking
  • Photovoltaic

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Abdelsalam, A. K., Goh, S., Abdelkhalik, O., Ahmed, S., & Massoud, A. (2013). Iterated unscented Kalman filter-based maximum power point tracking for photovoltaic applications. In Proceedings, IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society (pp. 1685-1693). [6699386] (IECON Proceedings (Industrial Electronics Conference)). https://doi.org/10.1109/IECON.2013.6699386