This paper aims at finding the optimal gain scheduling of the conventional Proportional Integral (PI) and the Fractional Order (FOPI) through the use of the advanced meta-heuristic optimization techniques in… Click to show full abstract
This paper aims at finding the optimal gain scheduling of the conventional Proportional Integral (PI) and the Fractional Order (FOPI) through the use of the advanced meta-heuristic optimization techniques in PV-grid connected systems. Therefore, the hybridization of the optimization techniques with both PI and FOPI controllers is proposed for attaining an optimal dynamic performance through a specific criterion. This latter is a function of different response characteristics such as the settling time, maximum overshoot, steady state error and execution time. Based on the proposed criterion, the meta-heuristic technique that provides the best enhanced dynamic performance can be simply identified. For this purpose, a comprehensive state of art of the on-grid PV system performance dilemma is initially discussed. The problem of designing current and voltage regulators for the PV-grid connected system is addressed, seeking for an adequate dynamic behavior. Then, different metaheuristic optimization techniques such as Artificial Bee Colony (ABC), Cuckoo Search (CS), Grey Wolf Optimizer (GWO), Mine Blast Algorithm (MBA), Whale Optimization Algorithm (WOA) and Moth Swarm Algorithm (MSA) are employed for determining the optimal PI/FOPI controller gains, forming a hybrid optimal FOPI or PI control. From the numerical simulation analysis of Matlabâ„¢/Simulink results, the significant dynamic behavior enhancement of the overall on-grid PV system is illustrated using PI/FOPI controllers optimally tuned with the proposed meta-heuristic algorithms considering solar irradiation variation conditions. The impact of the optimized PI and FOPI controllers on the overall system dynamic responses is explicitly analyzed while using different meta-heuristic algorithms through qualitative and quantitative comparisons.
               
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