| 研究生: |
郭冠祥 Kuo, Kuan-Hsiang |
|---|---|
| 論文名稱: |
基於儲能及電動車排程之儲能與契約容量最佳化 Optimal Sizing of ESS and Contract Capacity Based on Scheduling of ESS and EVs |
| 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: | 75 |
| 中文關鍵詞: | 儲能系統 、電動車 、契約容量 、容量最佳化 、儲能系統充/放電排程 、電動車充/放電排程 、k-means分群法 、線性規劃 、吸引排斥粒子群演算法 |
| 外文關鍵詞: | energy storage system(ESS), electric vehicles(EVs), contract capacity, optimal sizing, optimal scheduling of ESS, optimal scheduling of EVs, vehicle-to-grid and grid-to-vehicle (V2G/G2V), k-means, linear programming, attractive and repulsive particle swarm optimization(ARPSO) |
| 相關次數: | 點閱:167 下載:0 |
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儲能系統之建置能減緩再生能源間歇性及電動車大量充電需求等問題,但因其建置成本高昂,如何選擇合理之容量並配合適當之契約容量對其進行最大利益操作,以減少微電網整體營運成本並同時穩定微電網運作,為本論文研究目標。
本論文提出於10年長期規劃下,微電網儲能系統容量及契約容量之最佳化方法,並考慮集中式儲能系統充放電最佳化排程及電動車雙向充放電(G2V/V2G)最佳化排程,在配合微電網整體負載進行充/放電以抑低負載尖峰的同時,達到滿足電動車使用者之充電需求及最小化微電網整體成本之目標。
於模擬結果中則考慮不同太陽能發電系統容量、充電樁數量及三段式/兩段式時間電價對最佳化結果之影響,進行儲能系統容量、契約容量、電動車充電站營運利潤、儲能系統操作利潤及微電網整體成本之比較。由結果中可得知,在本文所使用之負載型態下使用兩段式時間電價,並同時裝設最佳之儲能系統容量對其進行最佳化充/放電排程,將使微電網整體成本平均減少22.78%。
The installation of the energy storage system(ESS) can mitigate the problems which are caused by the intermittency of renewable energy system(RES) and the massive charging demand of electric vehicles(EVs). However, due to the high investment cost of ESS, how to choose a reasonable capacity and cooperate with the appropriate contract capacity to operate it in the best interests to reduce the overall cost of the microgrid and stabilize the operation simultaneously is the primary goal of this thesis.
Therefore, we propose a size optimization method for ESS and contract capacity in the microgrid to optimize the investment cost. At the same time, it considers the centralized optimal schedule for charging/discharging ESS and EVs’ grid-to-vehicle/vehicle-to-grid (G2V/V2G) program so as to optimize the operation cost. In this way, the microgrid can not only shed the peak load but also satisfy the charging demand for every EV user. In the simulation results, we consider the different photovoltaic(PV) capacity, number of EV chargers and electricity price mechanism to compare the size of ESS, contract capacity and overall cost in the microgrid.
From the simulation results, it will bring a positive influence to the microgrid when applies 2-stage time-of-use(TOU) mechanism and installs the ESS. The overall cost of microgrid reduces by an average of 22.78%.
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