Multi-stage and resilience-based distribution network expansion planning against hurricanes based on vulnerability and resiliency metrics
| Autor: | Masoud Rashidinejad, Amirhossein Nasri, Amir Abdollahi |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Structure (mathematical logic)
Vulnerability index business.industry Computer science Distributed computing media_common.quotation_subject Sorting Energy Engineering and Power Technology Topology (electrical circuits) Automation Genetic algorithm Psychological resilience Electrical and Electronic Engineering business media_common Vulnerability (computing) |
| Zdroj: | International Journal of Electrical Power & Energy Systems. 136:107640 |
| ISSN: | 0142-0615 |
| Popis: | Distribution networks should be expanded to supply reliable and cost-effective services for new and existing customers to respond to the rising demand. On the other hand, there is an increasing awareness of resilience in the face of high impact low probability events. Therefore, this paper presents a multistage, dynamic, and resilient distribution network expansion planning framework to expand a distribution network resiliently. The proposed model is constructed as a six-step structure. The first step develops a network expansion topology. The hurricane occurrence model is executed in the second one that introduces a novel vulnerability index to recognize the most vulnerable facilities. Resilient planning based on the resilience resources such as distributed generations, hardening actions, and distributed automation systems is performed as the third step to reinforce the network preventive capabilities. In the fourth step, a resilient operation is considered to decrease unserved loads and restore the distribution system rapidly. Resiliency evaluation based on technical, financial, and social welfare metrics is employed as the fifth step. Finally, the non-dominated sorting genetic algorithm II optimization method operators are implemented in the sixth step to optimize the problem. Numerical simulations are performed on a 20 nodes distribution system and a real network. The results demonstrate the effectiveness of the proposed method. |
| Databáze: | OpenAIRE |
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