Probabilistic Load Flow Analysis Using Spherical Unscented Transformation

Today's with the increasing development of distributed energy resources, power system analysis has been entered a new level of attention. Since the majority of these types of energy resources are affected by environmental conditions, the uncertainty in the power system has been expanded; so probabilistic analysis has become more important. Among the various methods of probabilistic analysis, point estimation methods have always been of interest to researchers. Using unscented transformation (UT) is one of these methods which have been introduced recently for probabilistic analysis. UT-based methods are powerful algorithms for probabilistic studies in which correlation between random variables could be considered.
In this paper, the use of spherical unscented transformation (SUT) in probabilistic load flow (PLF) is proposed. In order to evaluate the method and compare with existing procedures, a test power system is used. Simulation results show the proper performance of the proposed method as well as the higher speed than the existing methods. As a result, the proposed SUT-based PLF algorithm could be used as a fast and accurate method especially in large and complicated power systems.