Wireless sensor monitoring network optimization research in smart substation

The poor computation ability and limited storage of power of nodes have seriously restricted wireless sensor network (WSN) applied to smart substation equipment condition monitoring. According to the application of substation equipment condition monitoring, clustering network model for equipment monitoring is proposed. And single-hop and multi-hop network consumption model is established respectively. Then using group search optimization algorithm, energy consumption optimization problem is analyzed under the influence of equipment monitoring network coverage, number of network nodes, node sensing radius and the distance of equipment monitoring node to information fusion node, information fusion node to sink node, in order to achieve minimal node cluster and cluster-head energy consumption. Compared to the particle swarm optimization, the simulation results show that the GSO algorithm is simpler and easier to implement, and has better performance in terms of convergence and computation speed. The results have direct reference value for optimization design of smart substation equipment condition monitoring used in WSN.