Resilient Operational Planning for Microgrids Against Extreme Events

TL;DR

This paper introduces a new resilience index for microgrids and an operational planning algorithm that enhances resilience against extreme events by optimizing survivability, outperforming traditional energy management models especially under higher inverter failure risks.

Contribution

The paper presents a novel resilience index and a resilient operational planning algorithm that incorporates failure probabilities to improve microgrid survivability during extreme events.

Findings

The ROP algorithm achieves higher survivability rates than traditional models.

Resilience improvements increase with higher inverter failure probabilities.

The proposed method effectively enhances microgrid resilience during extreme events.

Abstract

This paper proposes a novel resilience index, a microgrid survivability rate (SR) under extreme events, and then proposes a novel Resilient Operational Planning (ROP) algorithm to maximize the proposed resilience index SR. The proposed ROP algorithm can incorporate predetermined inverter failure probabilities and generate multiple scenarios accordingly to optimize resilient operations during an extreme event. The implemented ROP algorithm consists of two main steps: (i) optimization of resilient operational planning, and (ii) preventive resilience enhancement if minimum SR is not met per the analysis in step 1. A typical microgrid (MG) is studied to compare the proposed ROP algorithm against a traditional microgrid energy management (MEM) model. Results indicate that an enhanced resilience operation is achieved by the ROP algorithm, which is demonstrated by the quantification of resilience via the SR. Moreover, the proposed ROP algorithm is able to obtain a greater SR overall compared to that achieved by the traditional MEM, and this benefit of using the proposed ROP increases as the inverter failure probabilities increase.