An intelligent management of power flow in the smart grid system using hybrid NPO-ATLA approach

In this manuscript, an intelligent hybrid approach is proposed to manage the power flow (PF) in the smart grid (SG) system. The proposed approach is the combined execution of Nomadic People Optimizer (NPO) algorithm and artificial transgender longicorn algorithm (ATLA), hence it is named NPO-ATLA approach. The Renewable energy system consists of photovoltaic (PV), wind turbine (WT), battery and grid. The major aim of this work is to control the power flow in the hybrid renewable energy sources (HRES) depending on parameter variation of source and load side and satisfies the load demand of the system. The voltage source inverter (VSI) control signals are generated through the NPO approach based upon the variation of power transfer amid the source and load side. ATLA is utilized to recognize the control signals of the system against the variation of active with reactive power. The proposed approach is carried out in MATLAB, then the performance is compared with various existing approaches.

Automated summary

This manuscript proposes an intelligent hybrid approach for managing power flow in smart grid systems. It combines the Nomadic People Optimizer (NPO) algorithm with the artificial transgender longicorn algorithm (ATLA) to control power flow in hybrid renewable energy systems. The approach is implemented in MATLAB and compared with existing methods to evaluate its performance.