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Journals / Clean Energy Technologies Journal / 2025 / Volume: 3 Issue: 2

Post-Disaster EV Dispatch for Powering Base Stations A MILP Approach to Maximize Spatiotemporal Coverage

Ramazan Kilic(YILDIZ TECHNICAL UNIVERSITY, INSTITUTE OF SCIENCE, DEPARTMENT OF ENERGY TECHNOLOGIES)0009-0004-9144-3671
Alper Kağan Candan(MANISA CELAL BAYAR UNIVERSITY, FACULTY OF ENGINEERING, DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING)0000-0003-0320-7317
Ali Rıfat Boynueğri(YILDIZ TECHNICAL UNIVERSITY, FACULTY OF ELECTRICAL AND ELECTRONIC ENGINEERING, DEPARTMENT OF ELECTRICAL ENGINEERING)0000-0003-4734-3126
Pages
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Publication Date
2026-01-07
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Results demonstrate that feasible EV–BS assignments and service durations are obtained considering BS power demand, coverage areas, and EV initial energy parameters.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Disasters frequently disable the electrical grid, jeopardizing communication infrastructure and causing severe disruptions in emergency communications.
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Key Findings & Data:In a case study involving 20 BSs and 10 EVs, the optimization prioritizes early service to densely populated areas and delivers a total of 17,597 people for 228 minutes of communication access.
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Conclusion & Impact:Results demonstrate that feasible EV–BS assignments and service durations are obtained considering BS power demand, coverage areas, and EV initial energy parameters.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Post-disaster communication · MILP · Population-based temporal coverage

Abstract

Disasters frequently disable the electrical grid, jeopardizing communication infrastructure and causing severe disruptions in emergency communications. Ensuring rapid deployment of power sources for base stations (BS) is therefore critical in post-disaster conditions. This study presents a mixed-integer linear programming (MILP) framework that dispatches a fleet of electric vehicles (EVs) to energize multiple BSs and maximizes population-based temporal communication coverage (people × time). In a case study involving 20 BSs and 10 EVs, the optimization prioritizes early service to densely populated areas and delivers a total of 17,597 people for 228 minutes of communication access. Although served population gradually declines as EV energy depletes, the connectivity is sustained until 16:34. Results demonstrate that feasible EV–BS assignments and service durations are obtained considering BS power demand, coverage areas, and EV initial energy parameters. The proposed model enable communication availability after disasters without relying on additional fixed power resources.

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Cite This Article

Kilic, R., Candan, A. K., Boynueğri, A. R. (2026). Post-Disaster EV Dispatch for Powering Base Stations A MILP Approach to Maximize Spatiotemporal Coverage. Clean Energy Technologies Journal, Volume: 3 Issue: 2. https://ajindex.com/articles/1629384

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