Budget‐constrained drone allocation for distribution system damage assessment
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 damag...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-02-01
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| Series: | IET Smart Grid |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/stg2.12050 |
| _version_ | 1818483312480485376 |
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| author | Ali Arjomandi‐Nezhad Moein Moeini‐Aghtaie Mahmud Fotuhi‐Firuzabad Farrokh Aminifar |
| author_facet | Ali Arjomandi‐Nezhad Moein Moeini‐Aghtaie Mahmud Fotuhi‐Firuzabad Farrokh Aminifar |
| author_sort | Ali Arjomandi‐Nezhad |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-10T11:58:42Z |
| format | Article |
| id | doaj.art-261f211ca7984ba08fd3a04b63492f54 |
| institution | Directory Open Access Journal |
| issn | 2515-2947 |
| language | English |
| last_indexed | 2024-12-10T11:58:42Z |
| publishDate | 2022-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Smart Grid |
| spelling | doaj.art-261f211ca7984ba08fd3a04b63492f542022-12-22T01:49:41ZengWileyIET Smart Grid2515-29472022-02-0151425010.1049/stg2.12050Budget‐constrained drone allocation for distribution system damage assessmentAli Arjomandi‐Nezhad0Moein Moeini‐Aghtaie1Mahmud Fotuhi‐Firuzabad2Farrokh Aminifar3Department of Electrical Engineering Sharif University of Technology Tehran IranDepartment of Energy Engineering Sharif University of Technology Tehran IranDepartment of Electrical Engineering Sharif University of Technology Tehran IranSchool of Electrical and Computer Engineering College of Engineering University of Tehran Tehran IranAbstract 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.https://doi.org/10.1049/stg2.12050integer programmingautonomous aerial vehiclesdisastersmaintenance engineeringoptimisation |
| spellingShingle | Ali Arjomandi‐Nezhad Moein Moeini‐Aghtaie Mahmud Fotuhi‐Firuzabad Farrokh Aminifar Budget‐constrained drone allocation for distribution system damage assessment IET Smart Grid integer programming autonomous aerial vehicles disasters maintenance engineering optimisation |
| title | Budget‐constrained drone allocation for distribution system damage assessment |
| title_full | Budget‐constrained drone allocation for distribution system damage assessment |
| title_fullStr | Budget‐constrained drone allocation for distribution system damage assessment |
| title_full_unstemmed | Budget‐constrained drone allocation for distribution system damage assessment |
| title_short | Budget‐constrained drone allocation for distribution system damage assessment |
| title_sort | budget constrained drone allocation for distribution system damage assessment |
| topic | integer programming autonomous aerial vehicles disasters maintenance engineering optimisation |
| url | https://doi.org/10.1049/stg2.12050 |
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