基於共識性協調之智慧型控制策略於多聚落式微電網之韌性強化

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姓名

蘇子銘(ZI-MING SU) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

基於共識性協調之智慧型控制策略於多聚落式微電網之韌性強化
(Resilience Enhancement of Multiple Microgrid Clusters by Intelligent Control Strategy Based on Consensus Coordination)

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至系統瀏覽論文 (2029-8-1以後開放)

摘要(中)

現代電力系統日益複雜，分散式能源（DERs）的日益整合，需要先進的控制策略來管理微電網集群（MGCs）。本研究探討了在MGCs中採用多項式派翠模糊神經網絡（PPFNN）控制器，以應對這些挑戰。PPFNN控制器結合了多項式理論、派翠網和模糊神經網絡的優勢，提供了一個強大的框架，用於互連微電網之間的動態共識和協調。傳統的控制方法往往難以應對微電網系統的動態和隨機特性。PPFNN控制器結合了模糊邏輯的強健性和神經網絡的學習能力，為維持電壓穩定、頻率調節和高效電力分配提供了優越的解決方案。本研究證明，採用PPFNN控制器不僅提高了微電網集群的運行韌性，還維持了電壓和頻率的穩定性，增強了系統對抗干擾的強健性。通過利用神經網絡的自適應學習能力和派翠網的邏輯結構，PPFNN控制器為現代微電網集群的實時運行需求提供了一個先進的解決方案，確保了一個具有韌性和高效的電力系統。通過實時模擬，本研究強調了控制器在處理各種情景時的有效性，從而提供了一個可擴展且可靠的現代能源網挑戰解決方案。

摘要(英)

The growing complexity of modern power systems and the increasing integration of distributed energy resources (DERs) necessitate advanced control strategies for microgrid clusters (MGCs). This study investigates the adoption of Polynomial Petri Fuzzy Neural Network (PPFNN) based controller in MGCs to address these challenges. The PPFNN based controller combines the strengths of polynomial theory, Petri nets, and fuzzy neural networks, providing a robust framework for dynamic consensus and coordination among interconnected microgrids. Traditional control methods often fall short in dealing with the dynamic and stochastic nature of microgrid systems. The PPFNN based controller, with its ability to combine the robustness of fuzzy logic and the learning capabilities of neural networks, offers a superior solution for maintaining voltage stability, frequency regulation, and efficient power sharing. This study demonstrates that adopting PPFNN based controller not only improves the operational resilience of microgrid clusters but also maintains voltage and frequency stability, enhances system robustness against disturbances. By leveraging the adaptive learning capabilities of neural networks and the logical structuring of Petri nets, PPFNN based controller provides a sophisticated solution for the real-time operational demands of modern microgrid clusters, ensuring a resilient and efficient power system. Through real-time simulation, the research highlights the controller′s effectiveness in handling various scenarios, thus providing a scalable and reliable approach to modern energy grid challenges.

關鍵字(中)

★ 微電網集群
★ 多項式派翠模糊類神經網路
★ 共識性協調
★ 韌性
★ 電壓穩定性
★ 頻率調節

關鍵字(英)

★ microgrid clusters (MGCs)
★ Polynomial Petri Fuzzy Neural Network (PPFNN)
★ consensus control
★ operational resilience
★ voltage stability
★ frequency regulation

論文目次

目綠
摘要 i
ABSTRACT ii
誌謝 iii
目綠 iv
圖目綠 vii
表目錄 xiii
1 第一章緒論 1
1.1 研究動機 1
1.2 文獻回顧 1
1.3 論文大綱 3
2 第二章微電網與分散式電源介紹 4
2.1 介紹 4
2.2 微電網控制策略 4
2.2.1 定功率控制(P/Q control) 4
2.2.2 電壓頻率控制(V/F control) 4
2.2.3 主從控制 4
2.2.4 分級控制 5
2.2.5 共識性協調 7
2.3 微電網標準 7
2.3.1 IEEE 1547-2018 標準 7
2.4 分散式電源介紹 9
2.4.1 太陽能電池特性 9
2.4.2 儲能系統 12
3 第三章系統架構與控制策略 15
3.1 簡介 15
3.2 三相座標軸轉換 15
3.3 鎖相迴路 16
3.4 變流器之實、虛功控制與電流控制 17
3.5 電力系統架構與控制 18
3.5.1 系統架構與控制策略 18
3.5.2 主控制策略 20
3.5.3 從控制策略 22
3.5.4 預同步控制策略 24
4 第四章多項式派翠模糊類神經網路 25
4.1 簡介 25
4.2 多項式派翠模糊類神經網路架構 25
4.3 多項式派翠模糊類神經網路之線上學習法則 28
4.4 多項式派翠模糊類神經網路收斂性分析 31
5 第五章模擬情境 34
5.1 模擬情境 34
5.2 情境一之模擬結果與討論 34
5.3 情境二之模擬結果與討論 54
5.4 情境三之模擬結果與討論 60
6 第六章硬體迴圈與實驗結果 103
6.1 簡介 103
6.2 即時模擬系統 103
6.2.1 即時模擬介紹 103
6.2.2 OP4510及OP4512硬體 106
6.2.3 軟體介面 RT-LAB 109
6.2.4 模型分割 111
6.2.5 硬體迴圈規劃 114
6.3 IEC-61850 通訊協定 116
6.4 實驗結果 117
6.4.1 情境一之實驗結果 117
6.4.2 情境二之實驗結果 136
6.4.3 情境三之實驗結果 142
7 第七章結果與未來展望 176
7.1 結論 176
7.2 未來展望 176
參考文獻 177
作者簡歷 183

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指導教授

林法正(Faa-Jeng Lin)

審核日期

2024-8-7

推文