Enhanced Control of Grid-Connected PV-DSTATCOM Under Non-ideal Grid Conditions Using IGWO for Global MPPT with RSOGI-FLL-MIPRT

UK Singh and Shivam, IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY- TRANSACTIONS OF ELECTRICAL ENGINEERING, 49, 1501-1520 (2025).

DOI: 10.1007/s40998-025-00818-1

Grid integrated photovoltaic distributed static compensator with storage is an effective and leading approach to mitigate power quality issues and manage the energy demand. Due to extensive use of power electronics devices in residential, industrial, transportation and commercial applications current harmonic injection in the system has increased. This paper proposes artificial neural network tunned modified instantaneous power reactive theory with reformed second order generalised integrator-frequency locked loop to maintain the power requirement and mitigate the current harmonics in distorted or weak grid condition. This system swiftly supplies the PV power to load and grid in day time and functions as DSTATCOM to improve dynamic proficiency and power quality during night. The aim of this paper is to present an effective solution for addressing power quality issues in modern utility grid. To obtain the maximum power point tracking for varying day irradiance, the improved grey wolf optimization (IGWO) is implemented. The IGWO integrates differential learning with GWO to enhance its global maximum searching ability and dynamic response that can effectively maximize power extraction from PV panels under varying irradiance conditions. The highly lagging load, non-linear load and constant power load has been considered in this work which acts as next generation load of the power system. IEEE-519 standards on current harmonics are being strictly followed to keep the total harmonic distortion of grid current below 5%.

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