Bad Data Identification Based On Improved Fuzzy Clustering Analysis In Power System

The power industry is developing rapidly and the scale of power system is expanding.With the structure and operation mode of power network becoming more complicated,the probability of generating erroneous data in grid data transmission is getting higher and higher,due to the existence of objective reasons Of the error data is also known as bad data,because the bad data can not correctly display the operation of the system,its existence will seriously affect the accuracy and reliability of the state estimates,and thus the safe and stable operation of the power system have a negative impact.The purpose of the bad data detection and identification of the power system is to remove the bad data in the measurement data and to provide accurate data for the power system state estimation.At present,the method of detecting bad data is mainly based on the method of measuring data residuals.With the complication of power grid structure,the disadvantages of detection and false detection are becoming more and more obvious.In this paper,the fuzzy clustering method is used to separate the benign data from the original measurement from the bad data.The simulation results show that the method is superior to the traditional method.First of all,this paper introduces the knowledge background and research status of bad data detection and identification of power system,and compares the advantages and disadvantages of the current bad data detection and identification method.In this paper,I use the EGSA-FCM algorithm to realize the detection and identification of bad data.Fuzzy clustering algorithm based on the fuzzy C-means algorithm,through the introduction of universal gravitational search algorithm SCADA system upload data on the early search,the method to improve the computational efficiency and accuracy.Finally,the COS index for the validity judgment of clustering is applied to the determination of the optimal number of clusters,and the optimal clustering results are obtained.Through the clustering of the known benign data,the benign data and bad data Classification.Aiming at the bad data detection and identification method based on EGSA-FCM algorithm,this paper has developed a detection and identification program.The method is applied to the IEEE14-node power system and a regional power grid.The results of detection and identification show that the method proposed in this paper avoids the occurrence of false detection and missed detection,and the detection result is more accurate than the traditional detection and identification method.