Open AccessProbabilistic–proactive distribution network scheduling against a hurricane as a high impact–low probability event considering chaos theory
Author(s) -
Nasri Amirhossein,
Abdollahi Amir,
Rashidinejad Masoud
Publication year - 2021
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/gtd2.12008
Subject(s) - probabilistic logic , computer science , scheduling (production processes) , chaos theory , resilience (materials science) , probability distribution , mathematical optimization , reliability engineering , operations research , engineering , artificial intelligence , mathematics , statistics , chaotic , physics , thermodynamics
High impact–low probability (HILP) incidents, such as hurricanes, usually and gravely damage electric distribution networks. A resilient distribution network must have an ability to recover itself with a fast restoration methodology against the effects of HILP events. Due to improve the electric distribution network resiliency against HILP incidents, this paper suggests a probabilistic–proactive distribution network operation model based upon the chaos theory (P‐PDNOM C (. Here, a resilience index based upon operational cost and load shedding cost is employed to decrease the effects of a hurricane as an HILP incident. P‐PDNOM C is formulated as a framework that consists of a novel hurricane modelling and operation scheduling in normal and emergency conditions with uncertainties considering. It should be noted that a prediction approach based on the chaos theory and the least‐squares support vector machine (LS‐SVM) is also designed to consider the provisional and spatial behaviour of the hurricane. Furthermore, this paper proposes a novel optimization framework for damaged lines determination based upon the P‐PDNOM C (DLs P‐PDNOM C ) by considering multi‐zone and multi‐period damaged equipment budget constraints. Here, the load shedding cost is applied to present the efficiency of the proposed model. The numerical results indicate the resiliency enhancement of the electric distribution network in the face of HILP incidents.