Localized Yearlong Power Flow Estimation Based on Limited Data Using Adaptive Filtering

Quasi-Static-Time-Series (QSTS) simulation is a powerful tool for power system analysis. Through a QSTS simulation, the variable nature of loads and the dynamic of autonomous controllers can be replicated within a time window. However, depending on the simulation granularity and the time window length, a QSTS simulation can be time consuming; a characteristic that makes QSTS simulations difficult to adopt by utilities and planners to perform day by day analysis. This paper presents a method for estimating yearlong power flows at a given point within the power system model using short term QSTS simulations. The dataset generated by these simulations is processed using adaptive filter techniques for reconstructing the yearly power flow. This solution can be used for different analysis purposes reducing the amount of computational time required.