Critical Load Restoration using Distributed Energy Resources for Resilient Power Distribution System

TL;DR

This paper introduces an advanced method for restoring critical loads in power distribution systems affected by extreme weather, using distributed energy resources to enhance resilience and optimize restoration times.

Contribution

It proposes a mixed-integer linear programming approach for resilient feeder restoration that jointly maximizes critical load restoration and optimizes DER allocation.

Findings

Successfully restores maximum critical loads in IEEE test feeders.

Effectively optimizes DER resource allocation for resilience.

Demonstrates impact of DER availability and fuel reserves on restoration.

Abstract

Extreme weather events have a significant impact on the aging and outdated power distribution infrastructures. These high-impact low-probability (HILP) events often result in extended outages and loss of critical services, thus, severely affecting customers' safety. This calls for the need to ensure resilience in distribution networks by quickly restoring the critical services during a disaster. This paper presents an advanced feeder restoration method to restore critical loads using distributed energy resources (DERs). A resilient restoration approach is proposed that jointly maximizes the amount of restored critical loads and optimizes the restoration times by optimally allocating grid's available DER resources. The restoration problem is modeled as a mixed-integer linear program with the objective of maximizing the resilience to post-restoration failures while simultaneously satisfying grid's critical connectivity and operational constraints and ensuring a radial operation for a given open-loop feeder configuration. Simulations are performed to demonstrate the effectiveness of the proposed approach using IEEE 123-node feeder with 5 DERs supplying 11 critical loads and IEEE 906-bus feeder with 3 DERs supplying 17 critical loads. The impacts of DER availability and fuel reserve on restored networks are assessed and it is shown that the proposed approach is successfully able to restore a maximum number of critical loads using available DERs.