scholarly journals Predictive Fixed Switching Maximum Power Point Tracking Algorithm with Dual Adaptive Step-Size for PV Systems

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3109
Author(s):  
Mostafa Ahmed ◽  
Ibrahim Harbi ◽  
Ralph Kennel ◽  
Mohamed Abdelrahem

Maximum power point tracking (MPPT) is an essential and primary objective in photovoltaic (PV) systems implementation. Thus, in this article, the predictive fixed switching MPPT technique is proposed for a two-stage PV system, where the system under consideration consists of a PV source, boost converter, and two-level inverter. The MPPT design is based on dual adaptive step-size realization to limit the duty cycle oscillations at a steady state. Furthermore, the PI controller is eliminated, which simplifies the MPPT implementation. The suggested tuning procedure of the duty cycle is compared with the conventional adaptive step-size perturb and observe (P&O) method. The inverter is controlled using an efficient finite-set model predictive control (FS-MPC) algorithm with reduced computation burden, where the optimal switching state vector is identified based on the polarity of the reference voltage in the α-β reference frame and without any need for sector determination. Furthermore, the cost function of the FS-MPC algorithm is modified to include the reduction of the switching frequency as a secondary objective for the inverter control. The overall control methodology is evaluated using experimental results at different operating conditions.

2015 ◽  
Vol 787 ◽  
pp. 227-232 ◽  
Author(s):  
L.A. Arun Shravan ◽  
D. Ebenezer

In recent years there has been a growing attention towards use of solar energy. Advantages of photovoltaic (PV) systems employed for harnessing solar energy are reduction of greenhouse gas emission, low maintenance costs, fewer limitations with regard to site of installation and absence of mechanical noise arising from moving parts. However, PV systems suffer from relatively low conversion efficiency. Therefore, maximum power point tracking (MPPT) for the solar array is essential in a PV system. The nonlinear behaviour of PV systems as well as variations of the maximum power point with solar irradiance level and temperature complicates the tracking of the maximum power point. This paper reviews various MPPT methods based on three categories: offline, online and hybrid methods. Design of a PV system in a encoding environment has also been reviewed here. Furthermore, different MPPT methods are discussed in terms of the dynamic response of the PV system to variations in temperature and irradiance, attainable efficiency, and implementation considerations.


Author(s):  
Yan Xiao ◽  
Yaoyu Li ◽  
John E. Seem ◽  
Kaushik Rajashekara

This paper presents a Maximum Power Point Tracking (MPPT) strategy for multi-string photovoltaic (PV) systems using the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm. The multi-string PV system considered is a decentralized control configuration, controlling the voltage reference to each PV module but based on the feedback of the total power at the DC bus. This requires only one pair of voltage and current measurements. The MPPT control problem for such topology of multi-string PV systems features a high input dimension, which can dramatically slow down the searching process for the real-time optimization process involved. The SPSA algorithm is considered in this study due to its remarkable capability of fast convergence for high dimensional search problems endorsed by various applications recently. Simulation study is performed for an 8-string PV system, and experimental study is performed for a 4-string PV system. Good performances are observed for both simulation and experimental results.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 953
Author(s):  
Ali M. Eltamaly

The problem of partial shading has serious effects on the performance of photovoltaic (PV) systems. Adding a bypass diode in shunt to each PV module avoids hot-spot phenomena, but causes multi-peaks in the power–voltage (P–V) characteristics of the PV array, which cause traditional maximum power point tracking (MPPT) techniques to become trapped in local peaks. This problem has forced researchers to search for smart techniques to track global peaks and prevent the possibility of convergence at local peaks. Swarm optimization techniques have been used to fill this shortcoming; unfortunately, however, these techniques suffer from unacceptably long convergence time. Cuckoo search (CS) is one of the fastest and most reliable optimization techniques, making it an ideal option to be used as an MPPT of PV systems under dynamic partial shading conditions. The standard CS algorithm has a long conversion time, high failure rate, and high oscillations at steady state; this paper aims to overcome these problems and to fill this research gap by improving the performance of the CS. The results obtained from this technique are compared to five swarm optimization techniques. The comparison study shows the superiority of the improved CS strategy introduced in this paper over the other swarm optimization techniques.


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