Robust strategic planning of dynamic wireless charging infrastructure for electric buses

Name: Robust strategic planning of dynamic wireless charging infrastructure for electric buses
Author: Alwesabi, Y., Avishan, Farzad, Yanıkoğlu, İhsan, Liu, Z., Wang, Y.

İsim	Robust strategic planning of dynamic wireless charging infrastructure for electric buses
Yazar	Alwesabi, Y., Avishan, Farzad, Yanıkoğlu, İhsan, Liu, Z., Wang, Y.
Basım Tarihi:	2022-02-01
Basım Yeri	- Elsevier
Konu	Battery electric bus, Dynamic wireless charging, Electromobility, Robust optimization, Vehicle scheduling
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0306-2619
Kayıt Numarası	ba9443bd-6315-4016-b5e9-a9f258467573
Lokasyon	Industrial Engineering
Tarih	2022-02-01
Örnek Metin	Electromobility in public bus systems is growing rapidly and experiencing a fundamental transformation in their infrastructure and operations. The dilemma of limited driving range and charging time of battery electric buses (BEBs) hinders their adoption. A novel approach to address BEB limitations is to utilize dynamic wireless charging (DWC) technology that allows buses to charge while in motion. This paper aims to analyze robust strategic planning of DWC and BEB fleet scheduling based on a real bus network at Binghamton University. The problem is first formulated as a new deterministic mixed-integer linear programming model to simultaneously optimize both the charging planning problem and fleet scheduling problem in an integrated fashion. To address the uncertainty of energy demand and charging time, a robust counterpart model (RCM) has been derived. To increase RCM flexibility, the battery status variable is formulated in a cumulative form. Dependent and independent budget uncertainty sets have been developed to control the robustness. A sensitivity analysis has been conducted to study the system behavior in response to different charging types, auxiliary energy demand, depth of discharge, charging options at terminals, battery degradation, and electricity cost. The deterministic model shows that eight homogeneous BEBs are required to operate on the selected routes with a battery capacity of 54.01 kWh and a total cost of $3,636,347. The results show that joint planning of charging infrastructure and fleet scheduling can save 19.2% of total cost compared to disjoint planning. The RCM results in 10 BEBs to ensure feasiblility against uncertainty.
DOI	10.1016/j.apenergy.2021.118243
Cilt	307

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Robust strategic planning of dynamic wireless charging infrastructure for electric buses

Yazar Alwesabi, Y., Avishan, Farzad, Yanıkoğlu, İhsan, Liu, Z., Wang, Y.

Basım Tarihi 2022-02-01

Basım Yeri - Elsevier

Konu Battery electric bus, Dynamic wireless charging, Electromobility, Robust optimization, Vehicle scheduling

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0306-2619

Kayıt Numarası ba9443bd-6315-4016-b5e9-a9f258467573

Lokasyon Industrial Engineering

Tarih 2022-02-01

Örnek Metin Electromobility in public bus systems is growing rapidly and experiencing a fundamental transformation in their infrastructure and operations. The dilemma of limited driving range and charging time of battery electric buses (BEBs) hinders their adoption. A novel approach to address BEB limitations is to utilize dynamic wireless charging (DWC) technology that allows buses to charge while in motion. This paper aims to analyze robust strategic planning of DWC and BEB fleet scheduling based on a real bus network at Binghamton University. The problem is first formulated as a new deterministic mixed-integer linear programming model to simultaneously optimize both the charging planning problem and fleet scheduling problem in an integrated fashion. To address the uncertainty of energy demand and charging time, a robust counterpart model (RCM) has been derived. To increase RCM flexibility, the battery status variable is formulated in a cumulative form. Dependent and independent budget uncertainty sets have been developed to control the robustness. A sensitivity analysis has been conducted to study the system behavior in response to different charging types, auxiliary energy demand, depth of discharge, charging options at terminals, battery degradation, and electricity cost. The deterministic model shows that eight homogeneous BEBs are required to operate on the selected routes with a battery capacity of 54.01 kWh and a total cost of $3,636,347. The results show that joint planning of charging infrastructure and fleet scheduling can save 19.2% of total cost compared to disjoint planning. The RCM results in 10 BEBs to ensure feasiblility against uncertainty.

DOI 10.1016/j.apenergy.2021.118243

Cilt 307