Budget‐constrained drone allocation for distribution system damage assessment. Issue 1 (19th August 2021)

• Record Type: Journal Article
• Authors: Arjomandi‐Nezhad, Ali; Moeini‐Aghtaie, Moein; Fotuhi‐Firuzabad, Mahmud; Aminifar, Farrokh
• Is Part Of: IET smart grid. Volume 5:Issue 1(2022)
• Page Start: 42
• Page End: 50
• Publication Date: 2021-08-19
• Subjects: damage assessment (DA) -- drone -- natural disasters -- resilience; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/stg2.12050
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract: Natural disasters threaten the sustainability of electric power supply. This fact highlights the importance of enhancing technological resourcefulness to handle the upcoming events. Once a natural disaster occurs, the most urgent undertaking is to rapidly pinpoint and assess component damages and dispatch the repair crews towards the most critical impaired elements. Practical efforts confirm that utilising a drone, which is an unmanned aerial vehicle, can notably reduce the duration of post‐disaster distribution system damage assessment (DA) and increase the resilience of power systems. This study presents an optimisation model to determine the optimal number and type of drones required for DA. The main goal is to minimise the time duration of the DA mission, which includes scanning the grid and identifying the damaged components. As a matter of fact, the financial resources are limited, so the problem is subject to the available budget constraint. Besides, the technical capacity of purchased drones for inspecting the grid is considered. The optimisation problem is formulated as a mixed‐integer programme with a guaranteed optimum solution. Case studies confirm the applicability of the model and the optimality of the results. As the major conclusion, the best allocation is a compromise between the speed and price of drones.