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系統識別號 U0026-2207201217045300
論文名稱(中文) 智慧電網下電動車之電能調度與需量反應
論文名稱(英文) Energy Management and Demand Response of Electric Vehicles in a Smart Grid
校院名稱 成功大學
系所名稱(中) 電機工程學系碩博士班
系所名稱(英) Department of Electrical Engineering
學年度 100
學期 2
出版年 101
研究生(中文) 簡振宇
研究生(英文) Chen-Yu Chien
電子信箱 miracle761013@gmail.com
學號 n26991344
學位類別 碩士
語文別 中文
論文頁數 60頁
口試委員 召集委員-楊金石
口試委員-陳朝順
口試委員-梁佩芳
口試委員-黃慶連
指導教授-楊宏澤
中文關鍵字 電動車  智慧電網  集中器  需量反應 
英文關鍵字 Electric Vehicle  Smart grid  Aggregator  Demand responds 
學科別分類
中文摘要 電動車的滲透率日益增加,倘若大量的電動車併入電網而未妥善控制充電時程,將大幅增加配電系統負擔並可能發生變壓器過載現象;另外未來電力系統隨著分散式再生能源系統滲透率升高,於輕載時亦可能導致配電系統逆送潮流問題。
本文提出ㄧ電動車停車場之充電排程最佳化系統,並透過智慧電網中集中器(Aggregator)之架構,執行配電系統層級之需量反應策略。本文所提出之電動車充電排程最佳化系統同時考量時間電價費率、緊急備轉容量費率、電池充放電劣化成本、車輛使用隨機性等,此外亦將停車場中之電動車作為電力系統之緊急備轉容量,以提供市電輔助服務並考慮配電系統裡過載與逆送電力問題。
本文藉Opal-RT系統模擬一座50個停車位之電動車停車場模型(最大充電限制約200kW),以評估所提出之充電排程最佳化策略之效益。此外以IEEE 13 節點之測試系統為基礎,將最佳化排程後之家庭負載分配至該測試系統各節點,再併入前述停車場之充電負載資料視其產生過載或逆送電力問題,以執行本文所提出之需量反應策略,藉此達到用戶電費支出最小化及維護系統穩定安全之目的。最後,本文亦模擬不同電動車滲透率對電力系統負載曲線之影響,所提最佳化方法可有效縮短尖離峰負載差距,以達成確保系統經濟、可靠與安全之運轉任務。
英文摘要 With the gradual increase in the penetration rate of electric vehicles, significant amount of burden can be added to the distribution system. Consequently, the problem of overloading of transformer may occur if large numbers of EVs are connected to the grid without proper control. Also, the reverse power problem may happen as the penetration rate of renewable energy increases in the future power system.
This thesis proposes an optimal charging scheduling system for EV parking lots. By integrating the system with aggregators in a smart grid, a demand response control strategy on the distribution level can be executed. The topics of electricity tariff, battery degradation cost, and vehicle usage are considered in the system. Moreover, the EVs in the parking lot are used as operating reserve capacity to supply ancillary service for the power system to solve the problems of overloading and reverse power.
An EV charging parking lot with 50 spaces is modeled and simulated with the Opal-RT system in this thesis to evaluate the feasibility of the proposed optimal charging scheduling strategy. The IEEE 13-node test system with the integration of scheduled household load distributed in each of the node is used as the base system. The load of the parking lot mentioned is combined with the test system to examine the problem of overloading and reverse power. When any of the problems occurs, the proposed DR strategy is initiated to achieve the goals of system stabilization for the utility and electricity payment minimization for end-users.
Finally, the impact of different EV penetration rates to the load curve in Taiwan is also discussed in this thesis. With the use of the proposed energy management strategy, the tasks of system efficiency, reliability and safe operation can be assured.
論文目次 摘 要 I
Abstract II
誌 謝 IV
目 錄 V
表目錄 VIII
圖目錄 IX
第一章 緒論 1
1.1 研究背景 1
1.2 文獻回顧 3
1.2.1 智慧電網系統架構 3
1.2.2 電動車智慧充放電(Vehicle to Grid, V2G) 5
1.2.3 電動車電能管理最佳化排程 6
1.2.4 需求面管理 7
1.2.4.1 時間電價 8
1.2.4.2 需量反應 9
1.2.5 備轉容量收購電價與策略 10
1.3 研究方法 12
1.4 論文結構 13
第二章 台灣電力系統現況與本文整體系統架構 15
2.1 簡介 15
2.2 台灣電力系統現況 15
2.2.1 尖峰負載 15
2.2.2 備用容量 18
2.2.3 備轉容量 19
2.2.4 電動車的發展 19
2.2.5 智慧型電表基礎建設的發展 21
2.3 本文整體系統架構 22
2.4 本章結論 24
第三章 電動車停車場電能管理與需量反應策略 25
3.1 簡介 25
3.2 問題定義 25
3.2.1 本文採用之時間電價費率 26
3.2.2 緊急備轉容量輔助服務費率 27
3.2.3 電池劣化成本 28
3.2.4 用戶電動車充電隨機性 29
3.2.5 充電安全限制 31
3.3 需量反應策略 32
3.3.1 配電系統架構 33
3.3.2 因應變壓器過載之需量反應策略 35
3.3.3 逆送電力需量反應 36
3.4 本章結論 37
第四章 模擬數值結果 39
4.1 簡介 39
4.2 電動車停車場充放電排程 39
4.3 需量反應策略模擬結果 43
4.3.1 Opal-RT模擬系統 43
4.3.2 需量反應模擬結果 45
4.4 最佳化結果對電力系統之影響 49
4.5 本章結論 52
第五章 結論與未來展望 53
5.1 結論 53
5.2 未來展望 54
參考文獻 55
作者簡介 60
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