Application of Genetic Algorithm in Sensor Networks and Smart Grid

Abstract

This chapter describes the usage of genetic algorithms (GAs) in multiple real-time applications. The subarea of wireless sensor networks is explored with the help of a GA to get the best possible trajectory planning. Along with that, another major application of the smart grid is used to get a deeper understanding of GA optimization strategy to get the best possible reliability and availability of micro-grids. After characterizing the kind of different strategies motivating this approach, a brief overview of the GA is present. Three major approaches to using GA for optimum deployment of wireless sensor networks and reliability/availability assessment of microgrid is explained in detail along with some sample programs. Finally, the assessment of the strength and weaknesses of these approaches to these two major applications is provided. The area of genetic operators, fitness function, and hybrid algorithms are discussed concerning these applications. The optimization discussed with meta-heuristic, cross-over, mutation, and selection, variant of the GA along evolution using GAs.