臺灣能源期刊發行
- 創刊日期：
102年11月30日
- 發行所：
經濟部能源署
- 發行人：
游振偉
- 地址：
台北市復興北路2號13樓
- 電話：
02-2772-1370
- 執行單位：
財團法人工業技術研究院
- 地址：
新竹縣竹東鎮中興路四段195號26館
- 服務專線：
03-5916006
- 服務信箱：
- 總編輯：
王漢英胡均立
- 顧問：
王運銘童遷祥楊日昌
- 執行主編：
劉子衙陳志臣
- 編輯委員：
方良吉王錫福李堅明李叢禎林師模馬鴻文陳介力陳希立廖芳玲廖肇寧劉文獻蕭志同顧洋(依筆畫順序排列)
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臺灣能源期刊論文全文
臺灣能源期刊第11卷第1期內容
出刊日期：March, 2024
- 題目
- 加油站提供電動汽車快速充電服務之最佳選址分布 研究–以臺北市為例
- Title
- A Study on Optimal Siting of Electric Vehicle Fast Charging at Existing Gas Stations – A Case Study of Taipei City
- 作者
- 曾麟惠 黃韻勳
- Authors
- Lin-Hui Zeng, Yun-Hsun Huang
- 摘要
- 近年來氣候變遷對全球環境造成了嚴重的影響，因此全球各國已陸續宣示2050年淨零排放目 標。然而全球最終能源消費的主要部門中，運輸部門占比高達27%，而公路運輸的能源需求占運輸 部門的比例達75%，因此為達成2050年淨零排放目標，各國開始推行禁售內燃機引擎汽車，並加速 推廣電動車及高效能運具。我國亦針對運具電氣化及無碳化設定目標，預計2030年新售小客車30% 為電動車、2035年進一步達到60%，最終目標則為2040年新售小客車全面電動化。為達成所設定的 電動車發展目標，增設快速充電設施至關重要。基此，本研究以臺北市作為研究案例，建立一個 電動車快速充電站的最佳選址規劃模型，納入設置快速充電站的主要考量因素(分別為交通幹道沿 途、該區域人口數及該區域電動車數量)，以評估哪些現行加油站適合優先設置快速充電站，使規 劃結果兼顧學術理論與實務應用性。研究中蒐集了臺北市內各區域的相關資料，以估算充電站服務 半徑及充電站數量，接著使用K-means演算法進行分群，使充電站能均勻分散，並以與交通幹道距 離最近為目標函數，進行最佳化求解，以獲得各情境下所需設置之快速充電站數量及充電站最佳選 址分布結果。最後，本研究將臺北市各情境下快速充電站最佳選址的分布情況以視覺化方式加以呈 現，這些分析結果有助於臺北市加油站未來進行建置快速充電站之參考，以進一步推動電動車發 展，達成淨零排放目標。
- 關鍵字
- 淨零排放，電動車，充電站選址，K-means演算法
- Abatract
- Many countries are pursuing net-zero greenhouse gas emissions to reduce the severity and speed of climate change. The International Energy Agency’s Energy Efficiency 2022 Report found that the transportation sector accounted for 27% of global energy consumption, with road transportation contributing 75%. Many countries and regions have begun to set targets for banning the sale of internal combustion engine vehicles and vigorously promoting high-efficiency, low-emission electric vehicles (EVs). In March 2022, Taiwan revealed its 2050 net-zero strategy, featuring twelve key targets with an emphasis on EVs. It is intended that by 2030, 30% of all new passenger cars will be EVs, increasing to 60% EVs by 2035, and full electrification by 2040. The adoption of EVs, however, depends on an accessible charging infrastructure. The installation of fast EV charging at gas stations makes it possible to repurpose existing facili-ties as multi-purpose energy hubs. This study developed a model by which to optimize the installation of EV fast charging stations based on land area, passenger car density, the loca-tion of gas stations, and proximity to highways and major roads in Taipei city. The proposed system calculates the number of vehicles served by a given station as well as the coverage radius and vehicle density to estimate the number and reach of charging stations. The K-means algorithm was used to ensure a balanced distribution of charging stations in various scenarios, prioritizing proximity to major roads. The clustering of facilities underwent further optimization to achieve a rational distribution, i.e., minimizing the distance to major trans-portation arteries. The simulation results were analyzed in terms of the number of fast charging stations required for each scenario (slow, moderate, and rapid development) and optimal distribution of these stations. Our results could serve as valuable references for the establishment of fast charging stations at existing gas stations to promote the adoption of EVs for net-zero emis-sions in Taipei City.
- Keywords
- Net-zero emissions, Electric vehicles, Charging station site selection, K-means algorithm