Study of the variation of operation of a low voltage electric network due to the integration of distributed energy resources—Steady state condition

Abstract

Distributed energy resources (DERs) can significantly impact distribution networks, necessitating characterization studies to understand the technical consequences in various operating conditions. Existing literature primarily applies deterministic or probabilistic techniques for modeling and simulating networks and DERs, but lacks studies that integrate multiple DERs simultaneously. Additionally, assessing various indicators is necessary to determine the influence of DERs on network operation. Furthermore, resilience approaches often overlook DER integration as a disruptive event. To address these gaps, this work employs deterministic, probabilistic, and harmonic distortion analyses to characterize the impact of photovoltaic systems, storage units, and electric vehicles on a reference low voltage network. The study investigates how these DERs influence network operation at different time intervals throughout the day. By examining parameters and indicators (PaI) such as RMS values of voltages and currents, voltage unbalance, and harmonic distortions, the individual and collective effects of DERs are estimated. An adapted resilience evaluation technique groups the PaI values to generate a representative population of a single R indicator for each hour, allowing for quantification of network operation variations. Data for the analysis is obtained through PowerFactory-Python co-simulation, encompassing twenty operating scenarios.