Abstract
This paper presents the development of a discrete model of a photovoltaic (PV) system consisting of a PV panel, Maximum Power Point Tracking (MPPT), a dual-axis solar tracker, and a buck converter. The discrete model is implemented on a 32-bit embedded system. The goal of the developed discrete PV model is to provide an efficient way for evaluating several algorithms and models used by the PV system in real-time fashion. The proposed discrete model perfectly matches the continuous and discrete model simulated with MATLAB-SIMULINK. The real-time performance is tested by running the model to simulate the PV system, where the fastest time sampling of 1 ms is achieved by the buck converter model, while the longest time sampling of 100 ms is achieved by the solar tracker model. Moreover, a novel method is proposed to optimize the net energy, which is calculated by subtracting the energy consumed by the tracker from the PV energy generated. The proposed net energy optimization method varies the operation time interval of the solar tracker under high and low solar irradiation conditions. Based on the real-time simulation of the discrete model, our approach increases the net energy by 29.05% compared to the system without the solar tracking and achieves an increase of 1.08% compared to the existing method.
Highlights
A photovoltaic (PV) system requires several technologies such as Maximum Power Point Tracking (MPPT) and Solar Tracking to improve its energy efficiency
We propose a discrete model of a PV system with MPPT and solar tracking
The latter strategy is based on the fact that the energy consumed by the solar tracker depends only on the time interval, while the energy produced by the PV depends on both the time interval and the solar irradiation
Summary
A photovoltaic (PV) system requires several technologies such as Maximum Power Point Tracking (MPPT) and Solar Tracking to improve its energy efficiency. MPPT is a technique that is used to improve the energy efficiency by operating the PV at the maximum power point This method relies on the non-linear characteristic of the current and voltage relationship of the PV. FLC-based MPPT methods [12,13,14,15] use fuzzy logic to adjust the PV voltage in finding the maximum power point. A system to monitor the MPPT algorithm was developed in [38] This system could be used to monitor MPPT parameters such as the PV voltage, PV current, and duty cycle of the converter in real time via a website.
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