Polytechnic School of Algiers

About: Polytechnic School of Algiers is a education organization based out in Algiers, Algeria. It is known for research contribution in the topics: Control theory & Chemistry. The organization has 99 authors who have published 114 publications receiving 1678 citations.

Artificial intelligence-based maximum power point tracking controllers for Photovoltaic systems: Comparative study

Abstract: In Photovoltaic (PV) systems, maximum power point tracking (MPPT) is an indispensable task. To date, various MPPT techniques have been proposed in the literature using classical and artificial intelligence methods. However, those techniques are tested on different PV systems and under different environmental conditions. In this work, we attempt to summarize and to give a comprehensive comparative study of the most adopted Artificial Intelligence (AI)-based MPPT techniques. The MPPT techniques which will be described are based on: Proportional-Integral-Derivative (PID), Fuzzy Logic (FL), Artificial Neural Network (ANN), Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The developed MPPT controllers are tested under the same weather profile in the same photovoltaic system which is composed of a PV module, a DC-DC Buck-Boost converter and a DC load. Initially, Modelling and simulation of the system is performed using the MATLAB/Simulink environment. Thereafter, the sliding mode control is applied to the converter in order to improve its performance. In a further stage, the different steps of development for each MPPT technique are presented. Simulation is performed to confirm the validity of the proposed controllers under the same variable temperature and solar irradiance conditions. Finally, a comparative study is carried out in order to evaluate the developed techniques regarding two principal criteria: the performance and the implementation cost. The performance is evaluated using comparative analysis of the tracking speed, the average tracking error, the variance and the efficiency. To estimate the implementation cost, a classification is carried out according to the type of the used sensors, the type of circuitry and the software level complexity. Recommendations that expected to be useful for researchers in the MPPT area about the validity of each MPPT technique are given in the last section.

An Effective Hybrid Maximum Power Point Tracker of Photovoltaic Arrays for Complex Partial Shading Conditions

Abstract: This paper proposes an improved maximum power point tracker (MPPT) for photovoltaic (PV) system. The scheme is a hybrid between the adaptive perturb and observe and particle swarm optimization (PSO). The algorithm incorporates the search-skip-judge (SSJ) mechanism to minimize the region within the P−V curve to be searched by the PSO. Furthermore, the PSO performance is enhanced by ensuring that the regions that have been previously explored (by other particle) will not be searched again by (another particle). Thus, the unnecessary movement of particles is minimized—leading to faster convergence. The proposed method is evaluated against four well-known MPPT techniques, namely the modified incremental conductance, the original version of SSJ, the modified cuckoo search, and the hybrid PSO. In addition, an experimental prototype, which is based on PV array simulator is used to verify the simulation. The competing algorithms are tested with a buck-boost converter, driven by the TMS320F240 DSP on the dSPACE DS1104 platform. It was found that the proposed scheme converges to the global maximum power point (GMPP) most rapidly and the GMPP tracking is guaranteed even under complex partial shading conditions.