Control of Steady-State Disturbances in Microgrids using Smell Agent Symbiotic Organism Search

This paper presents an optimal control of steady-state disturbances in the power flow of microgrids. In microgrid operations, the variation in loads induces instability in line-parameters such as voltage and frequency, resulting in a decrease in power quality and overall system stability. To address these challenges, a Smell Agent Symbiotic Organism Search (SASOS) algorithm, which integrates Smell Agent Optimizer (SAO) and Symbiosis Organism Search (SOS) algorithms, was codified in the design of an optimized controller to improve power quality control. The SASOS, SAO, and SOS algorithms were applied in the Microgrid’s Centralized Controller (MCC) for the control of steady-state disturbances. The simulation results showed the viability of the MCC-SASOS technique compared to the MCC-SOS, MCC-SAO, and MCC techniques.