Intelligent hybrid controller for power flow management of PV/battery/FC/SC system in smart grid applications

Abstract

In this manuscript, a Smart Grid (SG) system for intelligent power flow management from hybrid renewable energy source is presented. The presented structure consists of photovoltaic (PV) generator, battery, fuel cell (FC) and super capacitor (SC). The novelty of the proposed approach is the combined execution of the Levy Whale Optimization Algorithm (LWOA) and Modified Crow Search Optimizer (MCSO) named as LWMCSO technique. LWOA mimics the social behavior of humpback whales. In WOA, Levy flight is utilized to restore walk depend on motion of spiral. A creative chosen of crows as well as adaptive adjustment of MCSO flight length introduced. In this paper, the main objective of the proposed strategy is to control the power flow in the HRES based on the source side and load side parameters variations. Source of voltage inverter LWOA is implemented to develop the control signals, due to variation of power exchange among source and load side. Real as well as reactive power is created, depend on source of accessible power; multi-objective operation is formed with the requirement of grid. The MCSO methodology is implemented to recognize the signals, according to the variation of real as well as reactive power. Based on model of control, presentation method improves control parameters of power controller at light due to variant of power flow. SG's system is dominated which is reliant on the sides of source and load parameters. Additionally, the presented method is in charge of controlling the sources of energy to challenge the grid produce power, implement the source of renewable energy and storage energy devices. By at that point the presented method utilized at worksite of MATLAB/Simulink as well as its execution is compared to another method.