Enhancing Grid-Connected DFIG’s LVRT Capability Using Dandelion Optimizer Based the Hybrid Fractional-Order PI and PI Controlled STATCOM

Abstract

This study aims to improve the low-voltage ride-through (LVRT) capabilities of wind power plants (WPPs) during various types of grid faults, such as line-to-ground (L-G), double line-to-ground (LL-G), line-to-line (L-L), and three-phase-to-ground (LLL-G) faults. The paper proposes an enhanced cascaded Fractional-Order Proportional-Integral and Proportional-Integral (FOPI-PI)-controlled static synchronous compensator (STATCOM). The Dandelion Optimizer (DO), a novel optimization approach, is employed to fine-tune the STATCOM being studied. The DO optimizer was selected for its exceptional performance and robustness. The efficacy of the DO algorithm was assessed in comparison to three well-established methods such as the Water Cycle Approach (WCA), the Particle Swarm Optimizer (PSO), and a novel hybrid technique that combines WCA and PSO. The analysis focuses on two test systems: the 9MW wind power plant connected to an infinite bus system over a 30 km transmission line, and the IEEE 39 bus system. The results are displayed using MATLAB (R2018b) using time-domain simulation. The suggested system monitors multiple LVRT metrics, including WPP active and reactive power, voltage, and speed as well as DC link capacitor voltage. Upon conducting a comparative analysis, it was found that both the proposed cascaded (FOPI-PI) and conventional PI controller-based DO outperform other methods, such as the PI controller-based WCA algorithm, PSO optimizer, and even a combination WCA/PSO algorithm. The findings indicate that the FOPI-PI controller demonstrates superior performance compared to the PI controller. When the 9MW system has a fault, the recommended FOPI-PI controller restricts the voltage drop of the WPP to specific percentages. Specifically, the voltage drop is limited to 3% for L-G faults, 5% for L-L faults, 6% for LL-G faults, and 10% for LLL-G faults. Finally, the performance of wind power plants is much improved by adopting the proposed FOPI-PI controller optimized by DO in comparison to all other controllers in various test scenarios.