Deployment optimization of wireless mesh networks in wind turbine condition monitoring system

Abstract

This study aims to propose a deployment optimization method based on IEEE 802.11 heterogeneous wireless mesh networks (WMNs) for the condition monitoring system (CMS) of wind turbines. This method can provide a flexible, low-cost, and easy-to-implement network framework for wind farms in harsh environments, thereby avoiding interference of the newly installed CMS on the communication network of the SCADA system. The K-medoids clustering algorithm transforms the continuous space location problem into the discrete space location problem. Moreover, the mesh client (MC) coverage and backbone network connectivity issues are considered to ensure that the generated candidate point set can meet the coverage and connectivity requirements without generating numerous redundant nodes. Firstly, according to the characteristics of the model, the K-medoids clustering algorithm is used to obtain a set of candidate points of mesh routers (MRs) that meet the coverage rate. Secondly, a reasonable connection algorithm is proposed according to the constraints, and the optimal deployment is selected from the candidate points. Thirdly, taking the number of hops from MR to MG and the priority of MC as the weight. The path planning with the least number of MRs and load balancing is obtained by constructing a minimum spanning tree (MST) based on the improved Kruskal algorithm. Finally, Multi-channel inter-frequency networking technology is adopted to reduce interference between co-channels and between adjacent channels. The result shows that the method proposed can minimize network operating costs, meet the capacity requirements of MC, and reduce link losses.