An Improved System Performance Using ANN-FUZZY Logic and MSHO Control for BES-Solar PV and Wind Plant Based Micro-Grid System

In this work, severe grid voltage distortion and voltage sag/swells are occurred by inadequate utility networks. A micro grid with a weaker grid connection and hybrid renewable energy generation scheme is incorporated with artificial neural network. The feasible functioning of machine side power converter is achieved during change in wind speeds equipped with a wind turbine. A observing and perturbing based maximum power-point tracking is also adopted for extracting the maximum wind power. And, fuzzy-logic based maximum power point tracking is also adopted for extracting the maximum power form PV solar during varying temperature or irradiation levels. Also, a bidirectional inverter is integrated to batteries for charging purposes when unusual solar-PV is available. The major problem is identified such as; the solar-PV integrated inverter may charge or discharge the batteries which reduce the asset utilization and profitability. To overcome this issue, a frequency adaptive multistage harmonic oscillator based control technique has been used in grid-side power converters. The main objective is to eliminate them by using a multistage filter adjusted to the dominant lower order harmonics.