Intelligent control strategy in the islanded network of a solar PV microgrid

In the islanded mode of MG network, due to the lack of inertia and under performance of PI based inverter control, variation in power and frequency level can be expected more during the transient conditions as compared to the grid connected mode. Thus, in this study, a Particle Swarm Optimization (PSO) algorithm with the proposed cost function was implemented in the Grid-support grid-forming (GsGfm) type Voltage Source Inverter (VSI) of the DG sources (solar PV and battery unit) for the islanded photovoltaic (PV) based MG model (built in Matlab-Simulink software environment) to reduce the variation in power and frequency level. The islanded MG model was also implemented with a reverse droop based on virtual impedance control strategy for the VSI and power management control strategy to ensure better power sharing among DG sources with regulation of frequency level and power balance with co-ordinated control operation of DG sources. Implementation of PSO based intelligent control strategy for the inverters of DG units, showed substantial improvement in the performance of controller in terms of reduced settling time and overshoot in power level along with the significant reduction of the power variation and frequency variation during the transient conditions (change in load and change in solar irradiance of PV units). Also proposed PSO control strategy ensured the frequency level to be within the acceptable operating range (Australian network standard) in the islanded MG network.