Resilience Thorough Microgrids

Mojtahedzadeh, Shahram; Ravadanegh, Sajad Najafi; Haghifam, Mahmoud‐Reza; Tabatabaei, Naser Mahdavi

doi:10.1007/978-3-319-94442-5_5

Cited by 3 publications

(1 citation statement)

References 23 publications

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“…Due to the experiences of DSOs in the face of hurricanes, they can select the acceptable thresholds for the line damage scenarios generation. Using the pole fragility function, the failure probability of the distribution line ( i,j ) can be computed as follows [29–31]:

p_{p o l e} false(w_{m} false) = 0.0001 e^{0.0421 w}

p_{l} false(w_{m} false) = 1 - {(1 - p_{p o l e} false(w_{m} false))}^{N_{p o l e, l}}

…”

Section: Mathematical Frameworkmentioning

confidence: 99%

A three‐stage stochastic planning model for enhancing the resilience of distribution systems with microgrid formation strategy

Ghasemi

Kazemi

Mazza

et al. 2021

IET Generation Trans & Dist

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In recent years, severe outages caused by natural disasters such as hurricanes have highlighted the importance of boosting the resilience level of distribution systems. However, due to the uncertain characteristics of natural disasters and loads, there exists a research gap in the selection of optimal planning strategies coupled with provisional microgrid (MG) formation. For this purpose, this study proposes a novel three-stage stochastic planning model considering the planning step and emergency response step. In the first stage, the decisions on line hardening and Distributed Generation (DG) placement are made with the aim of maximising the distribution system resilience. Then, in the second stage, the line outage uncertainty is imposed via the given scenarios to form the provisional MGs based on a master-slave control technique. In addition, the non-anticipativity constraints are presented to guarantee that the MG formation decision is based on the line damage uncertainty. Last, with the realisation of the load demand, the cost of load shedding in each provisional MG is minimised based on a demand-side management program. The proposed method can consider the step-by-step uncertainty realisation that is near to the reality in MG formation strategy. Two standard distribution systems are utilised to validate the correctness and effectiveness of the presented model. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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