臺灣博碩士論文加值系統

本文旨在探討微電網基於主從控制下各種運轉的狀況與透過蟻群最佳化演算法制定儲能設備的排程策略，並透過蟻群最佳化演算法找出建置儲能設備的路徑規劃之最佳解。本文以核研所微電網作為模擬系統，並利用Matlab/Simulink模擬軟體建立微電網系統模型。模型可模擬多種微電網運轉模式：併網運轉、孤島運轉及併網運轉至孤島運轉，透過電壓調節將可有效降低分散式能源併網所產生的擾動。其次，本文應用蟻群最佳化演算法於微電網以優化儲能設備運轉排程策略，解決微電網的儲能設備充放電排程之問題，經由實驗結果顯示，透過蟻群最佳化演算法可滿足微電網的多種特性需求，使微電網達到削峰填谷、尖峰用電調節之作用，並可降低關鍵時段尖峰負載用電和保有系統之可靠性。最後，本文使用蟻群最佳化演算法應用於儲能設備建置之最佳路徑規劃，透過費洛蒙更新機制，並使用演算法排除冗餘路徑，模擬結果證實本文提出的方法用於路徑規劃具有相當穩健且搜尋全局最佳解時能更快收斂。

This thesis aims to discuss the various operating conditions of microgrid based on master slave control and the scheduling strategy of energy storage devices through ant colony optimization algorithm and try to find the optimal solution for the path planning of the energy storage devices through the ant colony optimization algorithm. This thesis uses the microgrid in the nuclear research institute as the simulation system and uses Matlab/Simulink simulation software to build models in microgrid systems. The model can simulate a variety of microgrid operating modes, such as grid-connected, islanded, and grid-connected to islanded operations. Through the voltage regulation, the disturbance caused by the interconnection of the distributed energy sources can be effectively reduced. Secondly, this thesis applies the ant colony optimization algorithm to the operation scheduling strategy of microgrid energy storage devices and solves the problem of charge and discharge scheduling of energy storage devices in microgrid. The experimental results show that the ant colony optimization algorithm can meet the multiple characteristics of the microgrid. The microgrid can achieve the function of peak cutting and peak shaving, and can reduce the peak load power during critical periods and maintain the reliability of the system. Finally, the ant colony optimization algorithm is applied to the optimal path planning for energy storage device construction. The pheromone update mechanism is used and the algorithm is used to eliminate redundant paths. The simulation results confirm that the proposed method is used for the path. The plan is fairly robust and searches for the global optimal solution for faster convergence.

摘要I
AbstractII
致謝III
目錄IV
圖目錄VIII
表目錄XII
第一章 緒論1
1.1研究背景1
1.2文獻探討2
1.3研究目標與方法3
1.4論文架構4
第二章 微電網系統介紹6
2.1微電網的背景及簡介6
2.1.1微電網的定義6
2.1.2分散式能源7
2.1.3儲能設備7
2.2國外微電網發展現況7
2.2.1美國8
2.2.2歐盟13
2.2.3日本15
2.3國內微電網發展現況17
2.3.1核能研究所微電網17
2.3.2澎湖智慧電網17
2.4微電網的好處18
2.5微電網的特性18
第三章 演算法介紹20
3.1前言20
3.2螞蟻系統原理20
3.2.1人工螞蟻21
3.2.2費洛蒙22
3.2.3費洛蒙揮發23
3.2.4轉換機率24
3.3蟻群最佳化演算法26
3.3.1正向與負向回饋機制26
3.3.2分散路徑的計算26
3.3.3建構啟發函數27
3.3.4費洛蒙更新機制27
3.3.5極大-極小螞蟻系統28
3.3.6終止條件28
第四章 微電網運轉模式分析29
4.1微電網的運轉模式29
4.2微電網Matlab/Simulink模型建立30
4.3微電網於各種運轉模式模擬結果與分析32
4.3.1併網運轉模式32
4.3.2併網模式下DG進行連結35
4.3.3孤島模式下DG進行連結38
4.3.4從併網模式至孤島模式41
第五章 儲能設備運轉排程策略及路徑規劃分析44
5.1前言44
5.2儲能設備運轉排程策略45
5.2.1運用搬運方法46
5.2.2評估指標51
5.2.3搬運選擇55
5.2.4目標函數與限制式56
5.2.5程式流程58
5.2.6實驗模擬結果62
5.3路徑規劃分析75
5.3.1研究方法75
5.3.2目標函數與限制式78
5.3.3模擬設計及參數設定80
5.3.4實驗模擬結果82
第六章 結論與未來展望92
6.1結論92
6.2未來展望94
參考文獻95

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