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"A Novel Hybrid MPPT Approach for Solar PV Systems Using Particle-Swarm" by Dilip Kumar, Yogesh Kumar Chauhan et al.

In this paper, a novel hybrid Maximum Power Point Tracking (MPPT) algorithm using Particle-Swarm-Optimization-trained machine learning and Flying Squirrel Search Optimization (PSO ML-FSSO) has been proposed to obtain the optimal efficiency for solar PV systems. The proposed algorithm was compared with other well-known methods viz. Perturb & Observer (P&O), Incremental Conductance (INC), Particle Swarm Optimization (PSO), Cuckoo Search Optimization (CSO), Flower Pollen Algorithm (FPA), Gray Wolf Optimization (GWO), Neural-Network-trained Machine Learning (NN ML), Genetic Algorithm (GA), and PSO-trained Machine Learning. The proposed algorithm was modelled in the MATLAB/Simulink environment under different operating conditions, for example, with step changes in temperature, solar irradiance, and partial shading. The proposed algorithm improved the efficiency up to 0.72% and reduced the settling time up to 76.4%. The findings of the research highlight that PSO ML-FSSO is a potenti ....

Perturb Observer Po Incremental Conductance , Maximum Power Point Tracking , Flying Squirrel Search Optimization , Incremental Conductance , Particle Swarm Optimization , Cuckoo Search Optimization , Flower Pollen Algorithm , Gray Wolf Optimization , Neural Network Trained Machine Learning , Genetic Algorithm ,

How Digital Transformation Is Upgrading Businesses Across The Globe

This article analyzes how digital transformation is modernizing companies globally and changing the labour market altogether. ....

Chitra Sabapathy Ranganathan , Harris Hawks Optimization , Particle Swarm Optimization ,