PV Parameter Identification using Reduced I-V Data

Tay, S., Lim, I. , Ye, Z., Yang, D. and Garrigós, A. (2017) PV Parameter Identification using Reduced I-V Data. In: 43rd Annual Conference of the IEEE Industrial Electronics Society (IES), Beijing, China, 29 Oct - 01 Nov 2017, pp. 2653-2657. ISBN 9781538611272 (doi: 10.1109/IECON.2017.8216446)

Abstract

In this paper, possibility and accuracy of using reduced I-V data in PV parameter identification are discussed. Based on the linear identification method proposed in [1], six I-V points are used instead of the whole I-V curve to identify the PV parameters. The maximum power point (MPP) is then estimated using the identified I-V and P-V characteristics. Validation is done by using different sets of six points on the I-V curve. Experiment results show that the accurate curve fitting (with low RMSE and MPE) and good estimation of MPP can be achieved.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lim, Dr Li Hong Idris
• Authors: Tay, S., Lim, I., Ye, Z., Yang, D., and Garrigós, A.
• Subjects: Q Science > Q Science (General)
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• ISBN: 9781538611272
• Copyright Holders: Copyright © 2017 IEEE
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher