Service Restoration in Distribution Networks Using Available Data Including Uncertainty

Abstract

The growth in penetration of photovoltaic generation systems (PVs) makes it difficult to reconfigure electrical power distribution networks, including service restorative operations. This is because distribution network operators cannot monitor or control the PVs, and this brings an additional uncertainty in available data that the operators must rely on. The authors focus on the service restorative operations and propose a problem framework and its solution method that finds the optimal restoration configuration under extensive PV installation. The traditional service restoration problems require accurate data on load sections; however, it is not practical in the distribution networks where PVs are extensively installed. Based on this background, the robust optimization and the two-stage stochastic programming are applied in the proposed formulation to address the PV-originated uncertainty using only readily available data. Through numerical simulations and discussion on their results, the validity of the proposal is verified.