Artificial Intelligence Based MPPT Techniques for Solar Power System: A review

In the last decade,artificial intelligence(AI)techniques have been extensively used for maximum power point tracking(MPPT)in the solar power system.This is because conventional MPPT techniques are incapable of tracking the global maximum power point(GMPP)under partial shading condition(PSC).The output curve of the power versus voltage for a solar panel has only one GMPP and multiple local maximum power points(MPPs).The integration of AI in MPPT is crucial to guarantee the tracking of GMPP while increasing the overall efficiency and performance of MPPT.The selection of AI-based MPPT techniques is complicated because each technique has its own merits and demerits.In general,all of the AI-based MPPT techniques exhibit fast convergence speed,less steady-state oscillation and high efficiency,compared with the conventional MPPT techniques.However,the AI-based MPPT techniques are computationally intensive and costly to realize.Overall,the hybrid MPPT is favorable in terms of the balance between performance and complexity,and it combines the advantages of conventional and AI-based MPPT techniques.In this paper,a detailed comparison of classification and performance between 6 major AI-based MPPT techniques have been made based on the review and MATLAB/Simulink simulation results.The merits,open issues and technical implementations of AI-based MPPT techniques are evaluated.We intend to provide new insights into the choice of optimal AI-based MPPT techniques.

Fuzzy Logic Controller-based Synchronverter in Grid-connected Solar Power System with Adaptive Damping Factor

In recent years,renewable energy sources,specifically solar power systems,have developed rapidly owing to their technological maturity and cost effectiveness.However,its grid integration deteriorates frequency stability because of insufficient rotating masses and inertial response.Hence,a synchronverter,which is an inverter that mimics the operation of a synchronous generator,is crucial to interface solar power in a power grid.It stabilizes the power grid by emulating a virtual inertia.However,a conventional proportional-integral(PI)-based synchronverter is not equipped with an adaptive damping factor(Dp)or a digitalized smart controller to manage fast-responding solar inputs.Hence,a novel fuzzy logic controller(FLC)framework is proposed such that the synchronverter can operate in a grid-connected solar power system.In this study,Dp is controlled in real time using an FLC to achieve balance between speed and stability for frequency error correction based on frequency difference.Results of four case studies performed in Matlab/Simulink show that the proposed FLC-based synchronverter can stabilize the grid frequency by reducing the frequency deviation by at least 0.2 Hz(0.4%),as compared with the conventional PI-based synchronverter.