隨著環保意識逐漸上升，包含電動車充電站的設置以及整合各種不同的分散式能源與儲能系統的應用將越來越廣。充電站的運轉必須考慮許多層面，如時間電價、能源的調度以及充電的需求，如何滿足客戶端的需求同時降低充電站營運的成本。充電站若結合利用分散式能源經由適當的控制直接以直流微電網傳輸使用，不但能使電力的損失變小也可以增加能源利用效率，結合太陽能發電、儲能系統以及電動車充電需求，本論文建立一充電站微電網模型，在考慮該系統所存在之不確定性下，利用模型預測控制法結合動態規劃找出儲能系統的最佳調度策略。本研究討論模型預測控制法調度充電站能源的效益，分析各種不同地區建置充電站、不同電池容量大小等對該充電站電網電能調度的影響。

Due to environmental awareness, more and more distributed energy and storage systems are developed and included in the charging station design. In order to meet the charging demands and reduce operation costs, several issues, such as time of use tariff, energy dispatch and charging demand forecast; need to be addressed. Integrating distributed energy resources through DC microgrid would help reduce loss and improved energy efficiency. In this thesis, the power dispatch of energy storage system in an eco-synergy charging station that integrates intermittent solar power output and energy storage system is investigated. A model predictive control scheme in conjunction with a dynamic programming procedure is used to minimize the charging station operation cost. Effects of battery capacities and charging station locations on the operation costs are analyzed.

論文審定書 i
誌謝 ii
中文摘要 iii
Abstract iv
目錄 v
圖目錄 vii
表目錄 ix
第一章 緒論 1
1.1 研究背景與動機 1
1.2 微電網管理 3
1.3 相關文獻回顧 7
1.4 論文架構 12
第二章 含分散式能源之電動車充電站簡介 13
2.1 電動車充電站負載模擬 15
2.1.1 電動車充電站負載模擬 15
2.1.2 電動車充電功率計算 18
2.2 太陽能發電 21
2.3 儲能電池充放電系統 24
2.3.1 儲能電池特性簡介 24
2.3.2 儲能電池等效模型 28
2.3.3 電池使用成本 32
2.4 時間電價 35
2.4.1 我國住宅時間電價制度面臨課題 35
2.4.2 費率計價方式探討 37
2.4.3 各國時間電價計費方式 39
第三章 結合分散式電源之充電站最佳化運轉 41
3.1 模型預測控制法的介紹 41
3.1.1 模型預測控制的發展 41
3.1.2 模型預測控制的探討 42
3.1.3 模型預測控制之架構 43
3.1.4 模型預測控制模型推導 44
3.1.5 模型預測控制法最佳化 48
3.2 動態規劃方法介紹 50
3.3 模型預測控制法結合動態規劃法最佳化模型 52
第四章 案例模擬與結果分析 55
4.1 模型預測控制法比較結果 57
4.2 不同電池容量對系統成本的影響 61
4.3 充電站建置在不同地區找出最佳適合電池容量 64
4.3.1 商業區充電站模擬 64
4.3.2 工業區充電站模擬 67
第五章 結論與未來研究方向 70
5.1 結論 70
5.2 未來研究方向 71
參考文獻 72

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