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2 Power Electronics and Drives

2 2024

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Enhancing PV Systems with Intelligent MPPT and Improved control strategy of Z-Source Inverter

Bettahar Fares, Abdeddaim Sabrina, Achour Betka

Power Electronics and Drives

2024

Vol. 9 (44)

1--20

The Improved Z-Source Inverter (IZSI) has gained attention in the photovoltaic industry for its ability to boost PV voltage with a singlestage topology, simplifying system design and reducing costs. However, research on integrating IZSI into PV systems, particularly regarding the Maximum Power Point Tracker (MPPT) and IZSI control strategy, is limited. This study proposes an Intelligent Improved Particle Swarm Optimization (IPSO) algorithm as an MPPT method for PV systems under constant and varying irradiance conditions. The IPSO algorithm is compared to the FPA, CSA, and traditional MPPT algorithm (PSO), and the results demonstrate that IPSO outperforms all algorithms in terms of speed, efficiency, and convergence in finding the Maximum Power Point (MPP). Two methods, Simple Boost Control (SBC) and Maximum Constant Boost Control with Third Harmonic Injection (THIMCBC), are employed to control IZSI. Simulation results using MATLAB-Simulink show that both strategies successfully find and track the MPP, but THIMCBC exhibits superior voltage-boosting performance compared to SBC. Overall, the proposed IZSI topology with the IPSO MPPT method and THIMCBC IZSI control strategy offers several advantages, including improved voltage boost ability, reduced z-source capacitor voltage stress, inherent inrush current limitation, and cost-effectiveness. These advantages make the proposed system a promising solution for photovoltaic systems.

A Comparative Study of PSO, GWO, and HOA Algorithms for Maximum Power Point Tracking in Partially Shaded Photovoltaic Systems

Bettahar Fares, Abdeddaim Sabrina, Betka Achour, Omar Charrouf

Power Electronics and Drives

2024

Vol. 9 (44)

86--105

Solar energy harnessed through photovoltaic technology plays a crucial role in generating electrical energy. Maximising the power output of solar modules requires optimal solar radiation. However, challenges arise due to obstacles such as stationary objects, buildings, and sand-laden winds, resulting in multiple points of maximum power on the P–V curve. This problem requires the use of maximum power point tracking algorithms, especially in unstable climatic conditions and partial shading scenarios. In this study, we propose a comparative analysis of three MPPT methods: particle swarm optimisation (PSO), grey wolf optimisation (GWO) and Horse Herd Optimization Algorithm (HOA) under dynamic partial shading conditions. We evaluate the accuracy of these methods using Matlab/Simulink simulations. The results show that all three methods solve partial shading problems effectively and with high precision. Furthermore, the Horse Herd Optimization approach has superior tracking accuracy and faster convergence compared with the other proposed methods.