Predictive Reliability Assessment of Distribution Grids with Residential Distributed Energy Resources

TL;DR

This paper presents a probabilistic, bottom-up method for assessing distribution grid reliability considering residential DERs like PV and storage, using Monte Carlo simulations to evaluate user-level reliability variations.

Contribution

It introduces a novel probabilistic approach that models residential DER penetration and assesses its impact on distribution system reliability at the individual user level.

Findings

The method effectively quantifies reliability variations due to DER adoption.

Application to RBTS test system demonstrates practical utility.

Scenario analysis highlights the impact of DER penetration levels.

Abstract

Distribution system end users are transforming from passive to active participants, marked by the push towards widespread adoption of edge-level Distributed Energy Resources (DERs). This paper addresses the challenges in distribution system planning arising from these dynamic changes. We introduce a bottom-up probabilistic approach that integrates these edge-level DERs into the reliability evaluation process. Our methodology leverages joint probability distributions to characterize and model the penetration of rooftop photovoltaic (PV) systems and energy storage across a distribution network at the individual residential level. Employing a scenario-based approach, we showcase the application of our probabilistic method using a Monte Carlo Simulation process to assess average system reliability indices and their variations at the user level. To validate our approach, we applied this methodology to the RBTS test system across various adoption scenarios, effectively showcasing the capability of our proposed method in quantifying the variation in end-user reliability indices for each scenario within the distribution system.