Microgrid resilience: a holistic and context-aware resilience metric

Mishra, Sakshi; Kwasnik, Ted; Anderson, Kate

doi:10.1007/s12667-022-00509-4

Cited by 8 publications

(9 citation statements)

References 16 publications

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“…Resilience, a term frequently encountered in academic circles, captures a system’s ability to withstand, adapt, and recover from adverse scenarios, maintaining at least partial functionality. A prevalent interpretation of resilience is “the aptitude to diminish the impact and/or time frame of disruptions.” 106 This contrasts with “robustness,” which does not capture the nuance of gradual degradation and subsequent recovery. Strategies rooted in planning are often employed to achieve a specific reliability threshold.…”

Section: Enhancing Resilience In Multi-microgridsmentioning

confidence: 99%

State-of-the-art review on energy sharing and trading of resilient multi microgrids

Kumar,

Singh,

Raghav

et al. 2024

iScience

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Section: Enhancing Resilience In Multi-microgridsmentioning

confidence: 99%

State-of-the-art review on energy sharing and trading of resilient multi microgrids

Kumar,

Singh,

Raghav

et al. 2024

iScience

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“…To evaluate the microgrids' robustness, we aim to represent the complex interplay of multiple elements. The authors of [3] argue that a microgrid's site-specific absorption, recovery, and adaptation capacities may be measured. A person's level of proficiency in this area can be gauged by their level of situational consciousness.…”

Section: Related Workmentioning

confidence: 99%

“…To make sure a system can keep running even if some hardware fails, redundancy is implemented [2]. Medium-voltage power distribution feeders are typically supplied by two parallel transformers, with their capacities calibrated so that each transformer can provide the loads of the feeders [3]. Clients do not have to deal with load shedding in the event of an outage or maintenance.…”

Section: Introductionmentioning

confidence: 99%

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A Resilience-Oriented Bidirectional ANFIS Framework for Networked Microgrid Management

et al. 2022

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This study implemented a bidirectional artificial neuro-fuzzy inference system (ANFIS) to solve the problem of system resilience in synchronized and islanded grid mode/operation (during normal operation and in the event of a catastrophic disaster, respectively). Included in this setup are photovoltaics, wind turbines, batteries, and smart load management. Solar panels, wind turbines, and battery-charging supercapacitors are just a few of the sustainable energy sources ANFIS coordinates. The first step in the process was the development of a mode-specific control algorithm to address the system’s current behavior. Relative ANFIS will take over to greatly boost resilience during times of crisis, power savings, and routine operations. A bidirectional converter connects the battery in order to keep the DC link stable and allow energy displacement due to changes in generation and consumption. When combined with the ANFIS algorithm, PV can be used to meet precise power needs. This means it can safeguard the battery from extreme conditions such as overcharging or discharging. The wind system is optimized for an island environment and will perform as designed. The efficiency of the system and the life of the batteries both improve. Improvements to the inverter’s functionality can be attributed to the use of synchronous reference frame transformation for control. Based on the available solar power, wind power, and system state of charge (SOC), the anticipated fuzzy rule-based ANFIS will take over. Furthermore, the synchronized grid was compared to ANFIS. The study uses MATLAB/Simulink to demonstrate the robustness of the system under test.

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“…Holistic approaches for assessing threats and vulnerabilities in a microgrid as well as defining resilience metrics are proposed in [8] and [9]. The resilience metrics are defined based on a quantification of microgrid properties associated to the impact of an extreme event, and are defined as threats, vulnerability, and vulnerability impacts, each dependent on the other.…”

Section: Introductionmentioning

confidence: 99%

Introduction to the Minitrack on Digital and Social Media in Enterprise

Wang,

Gonzalez,

Deng

2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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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.

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Microgrid resilience: a holistic and context-aware resilience metric

Cited by 8 publications

References 16 publications

State-of-the-art review on energy sharing and trading of resilient multi microgrids

State-of-the-art review on energy sharing and trading of resilient multi microgrids

A Resilience-Oriented Bidirectional ANFIS Framework for Networked Microgrid Management

Introduction to the Minitrack on Digital and Social Media in Enterprise

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