Location Optimization Mechanism Of Base Station For Power Wireless Private Network Based On Simulated Annealing And Genetic Hybrid Algorithm

With the development of smart grid construction,the demand for power services in terms of security,real-time,reliability and the like has been continuously raised.The construction of power wireless private networks has drawn more and more attention.In general,the deployment of base stations is the most crucial part in the entire wireless network construction,and its investment accounts for more than half of the total network construction investment.How to combine the features of the wireless communication service in the smart grid and the existing power infrastructure to optimize the site selection and realize the optimal network coverage with less base station construction cost has become an urgent problem to be solved.This article compares and analyzes the simulated annealing algorithm and genetic algorithm in the current site optimization problem.It is found that the input group size and the superiority of the parental gene in genetic algorithm will have a significant impact on the convergence speed,stability and solution effects,but its global search ability is strong and has good parallelism,which is suitable for the global solution process.Simulated annealing algorithm is easy to implement,insensitive to the size of the input and has strong local solving ability,but the global solution performance is slightly poor and the convergence rate is slow.According to the characteristics of the two algorithms,this article proposes a simulated annealing and genetic hybrid location algorithm.The core idea is to use the strong local solver ability of the simulated annealing algorithm to solve the initial feasible solution set.After the solution is encoded,it becomes the input initial population of the genetic algorithm,and the population can be found to meet the following characteristics:First,after simulated annealing algorithm,the size of the population has been reduced compared to the initial input parameters.Second,since all the individuals in the population are encoded by the initial feasible solution,the basic coverage requirements have been met,so each individual's gene is superior.Afterwards,the subsequent part of the optimal location algorithm by genetic algorithm finally improves the performance and the convergence speed.Based on simulated annealing-genetic hybrid algorithm,this article builds a power wireless private network location system based on browser-server architecture.The user can upload the site-related information through the browser,and return the site-selection result after the server-side location calculation is completed.Using this system,the article tests the site selection results for different data sets and verifies the effectiveness of the site selection mechanism.Afterwards,this article compares the performance of the proposed algorithm with genetic algorithm and simulated annealing algorithm,and proves that the proposed algorithm has better location optimization performance and faster solving speed.