Deterministic versus probabilistic approaches to self-healing in Smart Grid

This paper presents a comparison between deterministic and probabilistic approaches to support decision making process for self-healing in smart grid, aiming to improve reliability indexes. Probabilistic load flow (PLF) considers inputs as probability density functions (PDFs) or cumulative distribution functions (CDFs), and therefore may give a more reliable power analysis. Three methodologies, namely deterministic load flow (backward/forward sweep), probabilistic load flow through Monte Carlo simulation and probabilistic load flow through Herman-Beta method were tested with real data of two distribution feeders located in Rio de Janeiro, Brazil. The simulations show that probabilistic approaches are able to provide valuable information to a more reliable decision making process for service restoration.