An Efficient Metaheuristic Technique for Wireless Sensor Network Integrated Micro Grid Environment Using Improved Whale Optimization Algorithm (Iwoa)

Abstract

Wireless Sensor Network (WSN) nodes require careful power management to maintain long term operation without regular battery changes. Battery replacement can be challenging and expensive in a microgrid scenario where sensors may be installed in remote or i naccessible areas. To extend the life of WSN nodes, energy efficient design and power management strategies should be used. A potential strategy for effectively monitoring, controlling, and managing the distributed energy resources (DERs) inside a microgri d is theincorporation of WSNs with microgrids. This research work uses Improved Whale Optimization Algorithm (WOA) for optimizing the routing and performance. The humpback whale's hunting style served as the inspiration for the WOA, a metaheuristic optimization algorithm. WOA is an optimization technique that is used with MG and WSNs. During the optimization phase, WOA establishes a balance between exploitation and exploration. To increase the lifespan of a WSN in a microgrid, effective energy management i s frequently needed. When considering the dynamic energy availability from renewable sources and the energy requirements of the microgrid components, WOA is used to optimise energy allocation and routing in WSNs. This may lead to increased energy efficiency and longer network longevity. The IWOA attains 97.5% PDR that is higher than the existing state of art techniques.