Single-diode model parameter extraction from truncated data and estimated remarkable points

X. Moreno-Vassart, F. J. Toledo, V. Herranz, V. Galiano

This talk introduces two novel single-diode model (SDM) parameter extraction methods for incomplete I-V curves. Since, obtaining complete voltage-current curves can be challenging without interrupting normal operation, our new methods are optimised for incomplete measurements with samples around the MPP. We make use of previously identified relationships between the maximum power point (MPP), and the short-circuit and open-circuit points to circumvent the missing of information. Our proposed methods, "E parameter Reconstruction with Added Remarkable Point Estimation" (ER-ARPE), and "E parameter and Maximum Power Point Reconstruction with Added Remarkable Point Relationships" (EMPPR-ARPR), are detailed step by step and evaluated for different levels of incompleteness. These new algorithms improve modelling accuracy and enhance monitoring and predictive maintenance for photovoltaic systems.

Keywords: SDM parameter extraction, relationship of PV SDM remarkable points, reconstruction of incomplete SDM curves, real time SDM parameters, optimization techniques for SDM parameter extraction

Continuous Optimization II
June 10, 2025  3:30 PM
MR 3

J. Vicente Pérez

J. Castro Pérez, L. F. Escudero Bueno, J. F. Monge Ivars

J. Rückmann

M. Rodríguez Álvarez, J. Vicente Pérez, J. E. Martínez Legaz