A quantitative risk framework for DER-rich power system planning and decision making

Abstract

The increased penetration of Distributed Energy Resources (DERs) within power networks is bringing challenges, an important one being the potential voltage excursions within the system that must be mitigated, as voltage must be maintained within statutory range at all times and at any node of the system by regulation. This paper proposes a scalable framework based on machine learning techniques (ML) to assess voltage excursion risks node by node and derive the related marginal probabilities in response to any net-loads under various DER penetration scenarios. The framework is then used to quantify the resulting financial impact of voltage excursion in large-scale networks. Therefore, this no..