Exploring the Sensitivity of Hosting Capacity Evaluations to Various Simulation Characteristics

Abstract

The increasing penetration of distributed energy resources (DERs) and concerns over the associated technical issues have stimulated research towards evaluating the loadability of existing networks with DERs, termed hosting capacity (HC). Various HC methodologies have been proposed and differ in four primary characteristics: (1) the characterization of input characteristics, including stochasticity, variability, and allocation uncertainty, (2) the formulation of the load flow to accommodate identified input uncertainties, (3) characterization and analysis of uncertain impact assessment outputs, and (4) HC quantification and characterization, including the scope of technical parameters considered. This paper investigates the impact of these aspects on the quality of conclusions on feeder HC on distribution networks. An adaptive stochastic framework involving a Monte-Carlo simulation for DER allocation and a probabilistic load flow method is used to solve the HC problem according to the selected simulation characteristics. The analysis is carried out on an LV residential low voltage feeder with electric vehicles. The sensitivity results encourage the development of comprehensive HC formulations and simulations that generate reliable, consistent, and replicable HC solutions and conclusions. The results have significant implications for the optimal regulation of DERs.