What is it about?
Rooftop solar panels and home battery systems are becoming more common, changing how electricity customers experience power outages. While these technologies can help some homes stay powered during disruptions, they also make it harder to evaluate grid reliability using traditional methods that focus on system-wide averages rather than individual customer experiences. This paper presents a new way to assess distribution grid reliability that accounts for how households adopt solar and batteries at different levels. Using probabilistic models and simulation, the approach shows how reliability outcomes can vary widely across customers. The results demonstrate that high and coordinated adoption of solar and storage can significantly improve reliability, while uneven or limited adoption may lead to mixed outcomes. Overall, the study provides utilities and planners with a realistic view of how residential energy technologies affect reliability in modern power systems.
Featured Image
Photo by Umair Ali Asad on Unsplash
Why is it important?
Utility reliability metrics increasingly influence investment decisions, performance incentives, and regulatory oversight, yet they often fail to reflect how risk is distributed across customers in systems with behind-the-meter resources. As solar and battery adoption grows, relying only on system-average indices can mask localized reliability risks and misrepresent true service performance. This work helps utilities and regulators assess reliability risk more accurately by revealing how different adoption patterns affect both expected outcomes and their variability, supporting more informed planning decisions and policy design in DER-rich distribution systems.
Perspectives
This work reflects my interest in advancing reliability assessment beyond system-average metrics toward a more risk-aware, customer-level understanding of distribution system performance. I hope it encourages utilities, regulators, and researchers to rethink how reliability is evaluated in DER-rich systems and to adopt approaches that better reflect real-world risk and customer experience.
Arun Kumar Karngala
Eaton Corp
Read the Original
This page is a summary of: Predictive Reliability Assessment of Distribution Grids with Residential Distributed Energy Resources, CSEE Journal of Power and Energy Systems, January 2025, Tsinghua University Press,
DOI: 10.17775/cseejpes.2025.03040.
You can read the full text:
Contributors
The following have contributed to this page
