Distribution system state estimation with measurement data using different compression methods

In the near future, massive amount of data will be available to the state estimator model for a distribution system. In this work, different compression methods - Singular Value Decomposition (SVD) method and Principal Component Analysis (PCA) algorithm - were utilized in compressing that big data before being fed into the state estimation step. The branch current-based state estimation (BCSE) method was used to estimate the system states for the distribution system which was modeled with additional distributed generation. An IEEE 33-node distribution network was used to illustrate the applicability and effectiveness of the data compression methods. Results from the state estimator model show that compressing data can save time and speed up the convergence of state estimation for a distribution system.