REAL-TIME SIMULATION ANALYSIS OF LM ALGORITHM-BASED NN FOR THE CONTROL OF VSC IN GRID CONNECTED PV-DIESEL MICROGRID USING OP4500 RT-LAB SIMULATOR

Anantha Krishnan.V∗ and N. Senthil Kumar∗

Keywords

Dynamic stability, diesel generator, photovoltaic (PV) panel, artifi cial neural network (ANN), microgrid (MG), voltage source converter (VSC), opal realtime simulator (OpalRT)

Abstract

An effective and robust controller using Levenberg Marquardt (LM)-algorithm-based artificial neural network (ANN) controller to regulate the power flow in a photovoltaic (PV)-based generation is designed, implemented and validated in real time with OP4500 RT-Lab simulator. The controller functions as a regulator for voltage source converter (VSC), interfacing the PV source to the grid. Stable operation of VSC and microgrid system is the objective for both grid-connected and islanded operation characterizing the stability of the microgrid. The proposed ANN controller adaptively regulates the power outputs of the PV sources in accordance with the instantaneous power generation existing with other micro sources in the microgrid. The performance of the controller is investigated under varying irradiance and varying load conditions on both grid (AC load) and in the microgrid (DC load). Real-time information on the irradiance level is used to evaluate the performance of the controller in the microgrid. The robustness of the controller is tested in Opal-RT OP-4500 real-time simulator measurement considering solar irradiation for a day ranging between 2 am and 10 pm.

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