Robust Distribution System State Estimation Based on Smart Meter Data Under High PV Penetration

Distribution Systems State Estimation (DSSE) is increasingly important to support smart protection, optimization, and control applications in active distribution systems. This paper presents the implementation of an enhanced Tracking State Estimator (TSE) based on an Interlaced Extended Kalman Filter (IEKF) that relies on the Potter square-root method to mitigate the risk of numerical instabilities in the update step. The estimator performance is primarily investigated assuming to exploit Smart Meter (SM) data only, since their deployment in the EU is expected to be massive and to become dominant by 2030. Even though the Phasor Measurement Units (PMUs) are of course essential for protection and state estimation during fast transients, the considered TSE based on SM data exhibits excellent accuracy even under large, slowly-changing variations of load and PV generation power profiles. Indeed, the results obtained in two comparable test cases show that the 99th percentiles of the state estimation errors are consistent and much smaller than the maximum inherent fluctuations of the state variables even when PV penetration grows.