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系統識別號 U0026-1907201210393600
論文名稱(中文) 電力系統運轉效能強化與保護決策支援之智慧型演算法技術整合及研究
論文名稱(英文) A Study of Power System Operation Enhancement and Protection Decision Support Using Intelligent Computation Technology and Integration
校院名稱 成功大學
系所名稱(中) 電機工程學系碩博士班
系所名稱(英) Department of Electrical Engineering
學年度 100
學期 2
出版年 101
研究生(中文) 劉憲宗
研究生(英文) Xian-Zong Liu
學號 n28951251
學位類別 博士
語文別 英文
論文頁數 74頁
口試委員 口試委員-劉志文
口試委員-吳啟瑞
召集委員-廖聰明
口試委員-梁瑞勳
口試委員-蘇慶宗
口試委員-林惠民
指導教授-黃世杰
中文關鍵字 電容器配置  故障區域診斷  植物生長最佳化演算法  強化型蜜蜂繁殖演算法  智慧電網 
英文關鍵字 capacitor placement  fault section estimation  plant growth-based optimization algorithm  enhanced honey-bee mating optimization algorithm  smart grid 
學科別分類
中文摘要 隨著能資有效利用及兼顧環境承載能力之概念漸受重視,目前世界各國電力公司透過具體策略行動,積極進行溫室氣體抑制及減量,希冀有助於達成低碳社會之願景。基於此,電力公司則將改善輸配電系統運轉效能及強化電力系統自動化等提升電網供電穩定度與可靠度之措施,視為規劃布建智慧電網推動策略藍圖之一,期能建立兼具高品質、高效率、環境友善以用戶導向之電力網路系統。其中於改善輸配電系統運轉效能之策略中,則以改善輸配電運轉效率及減少線路損失為首要施行方案之一,而於電力運轉實務中,乃常加裝電容器於饋線,藉以改善饋線功率因數及提升系統整體供電品質,但因系統規劃人員於配置電容器時,主要係以技術經驗及相關配電技術規劃準則作為決策依據,倘若再考量負載變化、電容器成本及裝設電容器後之整體效益,將使電容器配置問題更顯繁雜,故在滿足多項限制條件下,如何進行電容器裝設位置、容量大小及型態之規劃,確已成為重要電力工程問題之一,且於未來智慧型電網施行中,此研究課題將持續具有其重要性。
此外,為能有效因應極端氣候變遷對電網供電穩定與安全之衝擊,電力公司目前係以強化電力系統自動化作為首要施行方向之一,調度人員利用監視控制與資料收集系統所記錄之保護電驛及斷路器的動作情形,進而推測故障可能發生之位置,用以採取適當操作策略,俾於達到恢復供電之目的。惟當調度人員面臨突發而來的大量故障警報時,卻有可能判斷錯誤或是未能立即掌握故障區域,致使故障範圍擴大,影響系統供電穩定度。此外,就所收集之警報訊息中,亦可能肇因於錯誤警報訊息或同時發生多重故障警報,致使求解故障診斷問題難度增加,因此如何於有限之警報訊息中,正確有效判斷故障區段,處於工業猛進及供電穩定更加重視之今日,確已躍為重要電力工程問題之一。
有鑑於此,本論文整體之研究目標,即致力研發整合應用智慧型演算技術於電力系統運轉效能強化及電力系統保護決策支援之研究,並至盼經由本論文所提之植物生長最佳化演算法及強化型蜜蜂繁殖演算法等仿生技術之輔助,不僅決策妥適之電容器配置方案,以達成降低線路損失及減少二氧化碳排放量之目標外,並能於系統發生故障時,可迅速偵測故障區域,以提供調度人員作為推測故障位置之依據,進而降低停電時間,以提升整體供電品質。另本論文為評估所提仿生智能演算法對提升電力系統運轉效益及強化電力系統保護決策之可行性,均已經由等效及實際系統予以模擬測試,同時利用其它方法針對相同系統架構測試比較,以驗證所提演算技術之計算效能。由測試結果可知,本論文所提方法除可迅速決定電力系統線路上之補償電容器類型與安裝位置,同時亦可準確診斷故障區段,應有助於分別提供系統規劃人員及運轉調度人員參考依據,進而俾於邁向優質潔淨電網及增強系統供電強健度之目標。
英文摘要 Following the increasing concern on the limited energy resources as well as environmen-tal enduring capability, power utilities around the world are being focused on mitigating carbon emissions and achieving a low-carbon society. Therefore, the improve¬ment of power transmission and distribution and the enhancement of power automation are constantly to be important concerns for electric power company, anticipating that a high-quality, high-efficiency, environmental-friendly and user-demand-oriented power grids will be reached. Among several strategies which have been proposed and conducted, the capacitors are usually suggested to be implemented with connected feeders in most engi-neering practices since they are beneficial to increase the power factor and improve the operation performance. Experience and related technical standards have been enacted as useful guides to determine the types, locations and sizes of capacitor banks. However, if the load duration curve, investment cost, social cost for carbon dioxide emissions and en-ergy losses are further included in the optimization consideration, the complexity of the problem would become significant.
Next, in order to cope with the impact of extreme weather on the stability and security of power delivery, the enhancement of power automation is also a vital task. At present, the dispatchers often employ the statuses of relays and circuit breakers collected from supervi-sory control and data acquisition (SCADA) systems with anticipation to estimate fault sec-tions in the early stage. However, for cases where the relay or circuit breaker fails to oper¬ate or facing the multiple faults as well as under the high stresses in interpreting the volumi-nous alarms, this task of fault section diagnosis can be extremely difficult, mean¬while implying that the development of an effective approach as a decision support to help identify the fault location would have its critical importance.
Being situated under the fast-paced industry and increased concerned of supplying power quality, this dissertation is aimed to enhance the operation performance of power systems and the decision support of power system protection strategies. Both the plant growth-based optimization (PGBO) approach and enhanced honey-bee mating optimiza-tion (e-HMO) algorithm have been developed and realized on real system applications. It is expected that through the extensive study of this dissertation, not only the optimization decision of capacitor placement can be attained through the reduction of system loss along with and the decrement of carbon dioxide emission, but the operators can also justify and isolate the fault sections swiftly such that the affected duration of outage can be minimized while the quality of supplying power can be upgraded. In order to evaluate the contribution of these proposed methods to power system operation, they were evaluated through the equivalent system simulations and practical operation data with comparisons to other meth-ods. Test results gained from this dissertation have confirmed the feasibility of the pro-posed methods to determine the capacitor placement and estimate fault sections in power systems, thereby serving as beneficial reference for planning engineers and opera¬tors and paving a road towards the goal of a clean and robust power network.
論文目次 摘要 I
Abstract III
誌謝 V
Contents VI
List of Tables VIII
List of Figures IX
Symbols and Abbreviations X
Chapter 1 Introduction 1
1.1 Background and Motivation 1
1.2 Literature Survey 3
1.3 Contribution of this Dissertation 5
1.4 Organization of this Dissertation 5
Chapter 2 Problem Description 9
2.1 Introduction 9
2.2 Capacitor Placement Problems 9
2.3 Fault Section Estimation Problems 10
2.3.1 Fault Section Estimation Problems Analysis 11
2.3.2 Mathematical Model Formulations of Fault Section Estimation Problems 13
2.4 Overview of Intelligent Computation Technology 15
2.5 Summary 16
Chapter 3 Application of Plant Growth-Based Optimization Algorithm to Capacitor Placement Optimization in Power Systems 18
3.1 Introduction 18
3.2 Overview of Plant Growth-Based Optimization Algorithm 18
3.2.1 Growth mechanism of a plant phototropism 19
3.2.2 Mathematical Model Formulation of PGBO Algorithm 19
3.2.3 PGBO Algorithm Paradigm 22
3.3 Computation Procedures of Plant Growth-Based Optimization Approach 24
3.4 Numerical Studies of Plant Growth-Based Optimization Algorithm 27
3.5 Summary 37
Chapter 4 Estimation of Fault Sections in Power Systems Using Enhanced Honey-Bee Mating Optimization Algorithm 38
4.1 Introduction 38
4.2 Overview of Enhanced Honey-Bee Mating Optimization Algorithm 38
4.2.1 Honey-Bee Mating Optimization 39
4.2.2 Enhanced Honey-bee Mating Optimization Algorithm 41
4.3 Computation Procedures of e-HMO Algorithm for FSE Problems 41
4.4 Test Results of e-HMO Algorithm for FSE Problem 43
4.4.1 Validation of Methods 44
4.4.2 Convergence Test 49
4.4.3 Robustness Test 51
4.4.4 Comparisons of Computation Efficiency 55
4.5 Summary 58
Chapter 5 Conclusions 59
5.1 Conclusions 59
5.2 Future Study 60
References 61
Biography 71
Publications List 71
Projects List 73
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