Optimizing the operation of photovoltaic panels using mathematical regression models

• Published in: Journal of physics. Conference series Vol. 2540; no. 1; pp. 12004 - 12016
• Main Authors: Rat, C L, Ichim-Burlacu, C, Bistrian, D A
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.07.2023
• Subjects: Algorithms; Control algorithms; Current distribution; Equivalence; Extreme values; Mathematical analysis; Maximum power tracking; Microcontrollers; Optimization; Photovoltaic cells; Physics; Programming environments; Regression models; Response surface methodology; Tracking control; Weather
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/2540/1/012004

Solar (PV) panel models are necessary for the implementation of solar panel control algorithms such as maximum power point tracking. If real-time control is required, these models will be used on microcontrollers and, therefore, will be subject to constraints of memory and execution time: the model implemented on the microcontroller must occupy a memory area as small as possible and the mathematical relationships it contains can be computed in the shortest possible time. Analytical models usually do not fit this criteria, therefore searching for equivalent models which do fit it is required. In this paper, equivalent mathematical models are determined in the MATLAB programming environment based on data obtained by simulating an analytical model in the LabVIEW programming environment. In this paper, the models were obtained by modeling the current distribution in the panel through regression methods, more specifically by using an optimal response surface which has been validated through the resolution of an optimization problem with restrictions. The optimal response surface was used to estimate the extreme values of the power produced by the panel for certain given weather conditions (maximum power in summer and minimum power in winter).