Uneven Clustering For WSN And Abnormal Data Detection For Microgrid Condition Monitoring

Due to the relatively poor environment of microgrid,abnormal and malfunctions are inevitable in the long running process,and effective monitoring and diagnosis means are needed.However,there are many kinds of objects in microgrid,wide range of distribution and large amount of monitoring data,the adoption of wireless sensor network is the ideal way to communicate.The application of wireless sensor network technology in the microgrid can be used to monitor the state information of microgrid flexibly and comprehensively.Optimizing the energy consumption of wireless sensor network in microgrid state monitoring system,prolonging the life cycle of network,speeding up the detection of abnormal data and ensuring the quality of monitoring are required to be solved in microgrid state monitoring.Aiming at the problem of energy consumption in wireless sensor networks,a kind of uneven clustering algorithm based on the real-time energy of the nodes in microgrid was proposed.The algorithm introduces node real time energy as part weight in cluster head competition radius,avoiding a node with small energy to act as a cluster head and cause the node to die ahead of time.Combined with communication energy consumption,cluster heads will achieve non-uniform distribution.The algorithm uses cluster judgment factor to allocate the cluster size reasonably,the number of cluster heads near the convergence point is in large quantities,and the scale is small.In this way,it balances the energy consumption of nodes and prolongs the life cycle of the network which is used to monitor the state information of the microgrid and makes the death nodes evenly distributed.Aiming at the complex collection of data in the monitoring network,this thesis proposes an optimization scheme for detection of abnormal data nodes.Combining the time mechanism of clustering topology control,the sampling value of the nodes with similar positions has the characteristics of similarity,the scheme uses the neighboring nodes to obtain the outliers of the node data,and introduces authority factors to improve the credibility of detection results,so as to realize the accurate judgement of outliers.The simulation results show that the reasonable cluster topology control for monitoring network with the analysis and the judgment of abnormal data comprehensively improve the quality of monitoring.