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研究生： 粘善
Nian, Shan
論文名稱： 參與非傳統機組即時備轉與電力調度之最佳化電能管理-以沙崙智慧綠能科學城C區微電網為例
Optimal Energy Management of Non-Conventional Units for Spinning Reserve and Regulation – Case Study on C-Zone Micro-Grid in SGESC
指導教授： 楊宏澤
Yang, Hong-Tzer
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年： 2020
畢業學年度： 108
語文別： 中文
論文頁數： 78
中文關鍵詞： 釩液流儲能系統 、電動車雙向充放電 、輔助服務 、電能管理系統 、改善型粒子群最佳化演算法
外文關鍵詞： vanadium redox battery energy storage system (VRBESS), electric vehicles (EV), grid-to-vehicle and vehicle-to-grid (G2V/V2G), ancillary services (AS), energy management system (EMS), improved PSO
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    • 為減緩全球暖化與環境變遷，世界各國紛紛發展綠能產業以取代傳統能源，智慧電網與能源轉型已成為全球趨勢。在綠能產業的發展下，相關產業的開發如儲能技術、低碳電動車也隨之提升，傳統的集中式發電由於廠址不易取得、新型能源具分散式特性，微電網發展乃逐漸普及化，如何有效整合多種分散式電源成為綠能產業發展的關鍵技術。
    本文以沙崙智慧綠能科學城C區實際場域為研究案例，開發最佳化排程及即時電能管理策略，以整合區域內的分散式電源與負載，並有效操作儲能系統與電動車的充放電使整體系統獲利最大化。最佳化排程模型考慮時間電價、電動車充電站營運模式、以及參與輔助服務市場等因素。
    本文透過改善型粒子群演算法，權衡各項成本與獲利以達成排程與運轉最佳化，此外，所提出的電能管理策略，可用以處理系統中的即時事件，如電動車充電需求、預測誤差，以及即時電能調度需求。模擬案例驗證所提出的電能管理系統可適用於不同時間電價方案與契約容量；在考慮參與輔助服務之情境中，模擬結果顯示在特定條件下最高可節省約12.5%的用電成本。

    In order to mitigate the global warming and environmental changes, countries around the world have developed green energy industries to replace the traditional energy sources. Smart grid and green energy policy have become a global trend nowadays, and it has also drive the development of related industries such as energy storage and electric vehicles. The micro-grid is gradually becoming popular because it’s hard to obtain the site for constructing a centralized power plant and the novel energy resources have decentralized characteristics. Integrating multiple distributed energy resources effectively will be a key technology in future.
    This thesis develops an optimal scheduling model and real-time energy management strategy to integrate the distributed energy resources and loads based on actual micro-grid architecture of the C-zone in SGESC. Through effectively operating vanadium redox battery energy storage system (VRBESS) and electric vehicles (EV) maximize the overall profit for micro-grid. The optimal scheduling model including many factors, such as time-of-use (TOU), electric vehicle charging station (EVCS) operation mode, and ancillary services market.
    In this thesis, the improved particle swarm optimization is applied to trade off the costs and profits contained in micro-grid to achieve optimal scheduling and operation. Moreover, the proposed energy management strategy is used to handle the real time events in this system, including EV charging demand, excessive forecast error, and real time energy regulation demand. The simulation results show that the proposed energy management system (EMS) can deal with different TOU tariff schemes and contracted capacity, and also increase the profit in the context of participating in ancillary services. The numerical results reveal that it can bring up to 12.5% electricity bill reduction for micro-grid under certain conditions.

    摘要 I EXTENDED ABSTRACT II 誌謝 VII 目錄 VIII 圖目錄 XII 表目錄 XIV 第一章 緒論 1 1.1 研究背景與動機 1 1.2 文獻回顧 2 1.3 研究方法與貢獻 4 1.4 論文架構 6 第二章 系統架構說明 7 2.1 簡介 7 2.2 微電網系統架構 7 2.3 釩液流儲能系統 8 2.3.1 釩液流儲能系統架構 8 2.3.2 釩液流儲能系統特性說明 9 2.3.3 釩液流儲能系統動態效率 10 2.4 電動車充電站 13 2.5 電力市場 14 2.5.1 時間電價方案 14 2.5.2 輔助服務市場機制 14 第三章 最佳化排程與即時電能管理策略介紹 19 3.1 簡介 19 3.2 整體微電網成本與獲利模型 19 3.2.1 釩液流儲能系統操作獲利模型 19 3.2.2 電動車充電服務獲利模型 20 3.2.3 系統超約用電成本模型 22 3.2.4 參與輔助服務獲利模型 23 3.3 整體系統限制 26 3.3.1 釩液流儲能系統限制 26 3.3.2 電動車充電站系統限制 27 3.3.3 區域變壓器容量及逆送電限制 29 3.3.4 輔助服務相關限制 29 3.4 最佳化目標函式 30 3.5 即時電能管理策略執行流程 30 3.6 最佳化問題求解方法 35 3.6.1 粒子群最佳化演算法簡介 35 3.6.2 粒子群最佳化演算法流程介紹 36 3.6.3 應用於粒子群最佳化演算法之改善方法 38 3.6.4 分段非線性加速因子參數調整策略 41 第四章 系統模擬與結果分析 43 4.1 簡介 43 4.2 系統相關參數設定 43 4.2.1 微電網系統參數設定 43 4.2.2 商業區電動車充電站進離場時間機率分布 45 4.2.3 大樓負載用電與再生能源發電 48 4.2.4 時間電價相關參數設定 49 4.3 情境說明與模擬結果分析 50 4.3.1 兩段式與三段式時間電價方案下最佳化排程結果分析 50 4.3.2 考慮假日商辦大樓負載較低情境最佳化排程結果分析 53 4.3.3 改善型PSO與其它PSO之收斂效果比較 55 4.3.4 不同契約容量對系統影響分析 57 4.3.5 考慮太陽能預測誤差對系統影響分析 59 4.3.6 考慮不同情境之輔助服務排程結果與獲利分析 63 第五章 結論與未來研究方向 69 5.1 結論 69 5.2 未來研究方向 70 參考文獻 72

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