Title
Statistical Modeling Of Dsp-Based Hill-Climbing Mppt Algorithms In Noisy Environments
Abstract
The effect of measurement noise on DSP-based maximum power point tracking (MPPT) algorithms is investigated in this paper. Based on the probabilistic characteristics of noise signals, a statistical model is constructed that allows quantitative analysis of the behavior of such algorithms both during transients and in steady-state. This model is then used to classify tracking problems into those presented by noise, and others resulting from other non-idealities such as measurement bias. It is then used to inspect different noise fighting techniques in order to predict their validity, and to suggest more relevant techniques. The results arrived at are then experimentally verified and confirm the predictions of the statistical model. © 2005 IEEE.
Publication Date
12-1-2005
Publication Title
Conference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC
Volume
3
Number of Pages
1773-1777
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/APEC.2005.1453286
Copyright Status
Unknown
Socpus ID
33745009790 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/33745009790
STARS Citation
Al-Atrash, Hussam; Batarseh, Issa; and Rustom, Khalid, "Statistical Modeling Of Dsp-Based Hill-Climbing Mppt Algorithms In Noisy Environments" (2005). Scopus Export 2000s. 3317.
https://stars.library.ucf.edu/scopus2000/3317