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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 朱致遠 | zh_TW |
| dc.contributor.advisor | James C. Chu | en |
| dc.contributor.author | 黃榆峻 | zh_TW |
| dc.contributor.author | Yu-Jun Huang | en |
| dc.date.accessioned | 2025-02-27T16:42:02Z | - |
| dc.date.available | 2025-02-28 | - |
| dc.date.copyright | 2025-02-27 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-02-14 | - |
| dc.identifier.citation | Bai, X., Chin, K. S., & Zhou, Z. (2019). A bi-objective model for location planning of electric vehicle charging stations with GPS trajectory data. Computers & Industrial Engineering, 128, 591-604.
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A multi-period optimization model for the deployment of capacitated charging station at highway service area [Unpublished master's thesis]. http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92519 Ghamami, M., Zockaie, A., & Nie, Y. M. (2016). A general corridor model for designing plug-in electric vehicle charging infrastructure to support intercity travel. Transportation Research Part C: Emerging Technologies, 68, 389-402. Hodgson, M. J. (1990). A flow‐capturing location‐allocation model. Geographical analysis, 22(3), 270-279. IEA. (2024). CO2 Emissions in 2023. IEA. https://www.iea.org/reports/co2-emissions-in-2023 Kadri, A. A., Perrouault, R., Boujelben, M. K., & Gicquel, C. (2020). A multi-stage stochastic integer programming approach for locating electric vehicle charging stations. Computers & Operations Research, 117, 104888. Kchaou-Boujelben, M. (2021). Charging station location problem: A comprehensive review on models and solution approaches. 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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/97212 | - |
| dc.description.abstract | 充電站選址問題的研究自流量捕捉選址模型以來逐漸成熟。由於大量溫室氣體排放對全球環境造成的嚴峻影響，這種趨勢伴隨著推動電動車普及的需求，使得充電基礎設施的部署更為迫切，因此眾多學者投入並加強了充電站選址問題模型的研究。本研究提出一種多期設施之容量限制的充電站佈設模型並同時考量路網中的電動車與燃油車之車流，旨在最大化所服務的總流量。研究同時提供一個混合整數規劃的數學模型，用於在服務區內透過替換既有設施來部署充電設備，並設計一套演算法，以確定駕駛者在服務區內進行資源或體力恢復的行動序列。案例研究展示了該模型的具體應用，並針對範例問題進行敏感度分析，針對實際案例進行情境分析，以探討不同參數對研究目標及部署策略的影響。 | zh_TW |
| dc.description.abstract | Studies on Charging Station Location Problem (CSLP) have evolved since the flow capturing location model was proposed. Plenty of researchers have fortified the model for CSLP due to the precarious global environment resulted from large emission of green-house gases, which causes a trend to promote electric vehicles and makes the deployment of charging infrastructures more urgent. The present study proposes a capacitated multiperiod optimization model to maximize the total flow of electric and internal combustion engine vehicles served. The model presents a mixed integer programming formulation to deploy chargers by replacing existing facilities in service areas, as well as an algorithm for determining action sequences for drivers to restore resources or stamina in service areas. Case studies are then demonstrating how the presented model works, and sensitivity analyses for the illustrative problem and scenario analyses for a real case problem are conducted to see the influence of parameters to the objective of the study and the deployment strategy. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-02-27T16:42:02Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-02-27T16:42:02Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 口試委員會審定書 I
Acknowledgements II 摘要 III Abstract IV Table of Contents V List of Tables VIII List of Figures XII Chapter 1: Introduction 1 1.1 Background and Motivation 1 1.2 Contributions 2 1.3 Flow chart 3 Chapter 2: Literature Review 5 2.1 Charging Station Location Problem 5 2.1.1 Demand Coverage Approaches 6 2.1.2 Charging Facility Capacity 8 2.1.3 Multiperiod Models 9 2.1.4 Vehicle Transition 10 2.2 Summary 11 Chapter 3: Methodology 13 3.1 Problem Statement 14 3.1.1 Network 14 3.1.2 O-D pairs 15 3.1.3 Vehicles 16 3.1.4 Drivers’ Actions 18 3.1.5 Operator’s Actions 19 3.2 Model Assumptions 21 3.2.1 Assumptions of Demand 22 3.2.2 Assumptions of Facilities 22 3.2.3 Assumptions of Traffic flows 23 3.3 Model Formulation 24 Sets: 24 Parameters: 26 Variables: 29 Objective Function: 30 Constraints: 30 3.4 Action sequence generating algorithm 34 Chapter 4: Case Study and Discussions 43 4.1 Illustrative Problem 43 4.1.1 Result 46 4.1.2 Sensitivity Analysis 52 4.1.3 Summary 76 4.2 Real world Problem 78 4.2.1 Results 83 4.2.2 Scenario Analysis 90 4.2.3 Summary 99 Chapter 5: Conclusions and Suggestions 101 5.1 Conclusions 101 5.2 Suggestions 103 Reference 105 | - |
| dc.language.iso | en | - |
| dc.subject | 電動車 | zh_TW |
| dc.subject | 多期佈設 | zh_TW |
| dc.subject | 充電站佈設 | zh_TW |
| dc.subject | 混合整數規劃 | zh_TW |
| dc.subject | 設施容量限制 | zh_TW |
| dc.subject | Capacitated facility | en |
| dc.subject | Multiperiod deployment | en |
| dc.subject | Electric vehicles | en |
| dc.subject | Charging infrastructures | en |
| dc.subject | Mixed integer programming | en |
| dc.title | 考量容量限制與電動車及燃油車混合車流之高速公路服務區設施多期佈設最佳化模型 | zh_TW |
| dc.title | A capacitated multiperiod optimization model for charging facility deployment at freeway service areas with mixed traffic flows of electric and internal combustion engine vehicles | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 盧宗成;陳柏華;許聿廷 | zh_TW |
| dc.contributor.oralexamcommittee | Chung-Cheng Lu;Albert Y. Chen;Yu-Ting Hsu | en |
| dc.subject.keyword | 充電站佈設,電動車,混合整數規劃,設施容量限制,多期佈設, | zh_TW |
| dc.subject.keyword | Charging infrastructures,Electric vehicles,Mixed integer programming,Capacitated facility,Multiperiod deployment, | en |
| dc.relation.page | 110 | - |
| dc.identifier.doi | 10.6342/NTU202500682 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2025-02-15 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 土木工程學系 | - |
| dc.date.embargo-lift | 2028-03-01 | - |
| 顯示於系所單位： | 土木工程學系 | |
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|---|---|---|---|
| ntu-113-1.pdf 此日期後於網路公開 2028-03-01 | 3.67 MB | Adobe PDF |
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