風力發電是世界上增長最快的可再生能源。全球尋求更清潔的環境，改進風力渦輪機技術以及政府承諾支持可再生能源發電，導致電力系統中可再生能源的滲透率顯著提高。由於傳統機器在系統中萎縮，高滲透率以及其可再生能源的間歇性，波動性和不可調度性導致動力儲備和系統慣性不足。
電力系統運營商（PSO）制定了專門為可再生能源製定的電網規範，以提供電網連接，穩態和動態操作指南。在這項研究中，考慮了風力渦輪機的低電壓穿越（LVRT）電網規範。 LVRT要求規定，如果故障後電壓恢復到標稱電壓的90％比不同垂度水平的設定時間慢，風電場可能會從電網斷開。在嚴重受限的系統中斷開風力可能是災難性的，需要避免，因為系統具有較少的動力儲備。
電壓恢復受動態負載的影響很大。電力系統負載估計約為60％的動態負載，主要是感應電動機。在該研究中，使用具有馬達子模型的PSS / E CLOD複合載荷模型。通過在戰略位置使用靜態同步補償器（STATCOM）設備進行LVRT增強，可以減少不希望的風電場斷開（WF）。最佳STATCOM容量取決於系統中的實際或預期動態負載比例以及所需的電壓恢復時間。
通過使用電壓偏差的平均積分絕對誤差（AIAE）作為指標來確定STATCOM位置，並確定容量符合德國LVRT電網規範電壓恢復要求。在該研究中，顯示動態變量規劃可以改善風力渦輪機的正常運行時間，整體系統完整性，並且單個策略定位的動態變量源可以服務於幾個相鄰的WF，以降低LVRT增強的成本。

Wind power is the fastest growing renewable energy source in the world. The global quest for a cleaner environment, improvement in wind turbine technology and government pledges to support renewable energy generation has resulted in significantly high renewable energy penetration in power systems. The high penetration coupled with its intermittency, fluctuation and non dispatchability of renewable power has resulted in shortage of power reserves and system inertia as conventional machines are shrinking in the system.
Grid codes specially formulated for renewable energy sources have been enacted by power system operators (PSO) to give grid connection, steady state and dynamic operational guidelines. In this study, the low voltage ride through (LVRT) grid code for wind turbines is considered. The LVRT requirement stipulates that if voltage recovery to 90% of nominal voltage following a fault is slower than the set-times at different sag levels, wind farm could disconnect from the grid. Disconnection of wind power in a heavily constrained system can be catastrophic and need to be avoided as the system has less power reserves.
Voltage recovery is greatly affected by dynamic loads. Power systems loads are estimated to be roughly 60% dynamic loads which are mostly induction motors. In this study, a PSS/E CLOD composite load model with motor sub-models are used. Undesired disconnection of wind farms (WF) could be mitigated through LVRT enhancement by static synchronous compensator (STATCOM) device at strategic locations. The optimal STATCOM capacity depends on the actual or anticipated dynamic load proportion in the system and the required voltage recovery time.
STATCOM locations are determined through the use of Average Integral Absolute Error (AIAE) of voltage deviation as indices and the capacity is determined to comply with German LVRT grid code voltage recovery requirement. In the study it is shown that dynamic var planning can improve wind turbine uptime, overall system integrity and that a single strategically located dynamic var source could serve several adjacent WFs to reduce costs of LVRT enhancement.

Thesis Validation Letter i
Acknowledgement ii
摘要 iii
Abstract iv
Table of Contents v
List of Figures viii
List of Tables x
Abbreviations xi
Chapter 1 Introduction 1
1.1 Introduction 1
1.2 Motivation 4
1.3 Research Objectives 5
1.4 Contribution of the Study 6
1.5 Thesis Layout 7
Chapter 2 Theoretical Background 8
2.1 Introduction 8
2.2.1 Wind Farm Impact Study 8
2.2.2 Wind Turbine Technologies 12
2.3 WTG Grid Codes 14
2.3.1 LVRT Grid Code 15
2.3.2 LVRT Testing 16
2.3.3 LVRT Test Benchmark 19
2.4 Dynamic Load Models 22
2.4.1 Composite Load Model 24
2.4.2 Complex Load Model 25
2.5 Wind Aggregation Models 27
2.6 Conclusion 29
Chapter 3 System Modeling 30
3.1 Introduction 30
3.2 PSS/E Simulation Package 30
3.3 Wind Farm Aggregation Model 30
3.3.1 Wind Farm Model Validation 32
3.3.2 Conclusion 35
Chapter 4 Effects of Dynamic Load Proportion on Voltage Recovery and LVRT Performance 36
4.1 Introduction 36
4.2 System for Voltage Recovery Simulations 36
4.3 LVRT Tripping Algorithm 39
4.4 Dynamic Load Proportion 40
4.5 Fault Clearing Time 41
4.6 AIAE of Voltage Deviation 42
4.7 Conclusion 43
Chapter 5 Optimal STATCOM Sizing and Location 44
5.1 Introduction 44
5.2 System Dynamic Equations 45
5.3 Optimal STATCOM Sizing and Location 46
STATCOM Dynamic Model 50
5.4 Case Study 51
5.4.1 STATCOM Location 52
5.4.2 Optimal STATCOM Capacity 53
5.4.3 Conclusion 56
Chapter 6 Test Results 58
6.1 Introduction 58
6.2 System Description 58
6.3 STATCOM Location Bus 60
6.4 Optimal STATCOM Capacity 62
6.5 V-Q sensitivities 69
6.6 Discussion 73
Chapter 7 Conclusion and Future work 75
7.1 Conclusion 75
7.2 Future work 76
Chapter 8 REFERENCES 77
Appendix A Wind Farm Design Data 83
Appendix B Test Bus Dynamic PSS/E Data 85
Appendix C Test Bus Raw PSS/E Data 89
Appendix D Augmented IEEE24 RTS PSS/E Raw Data 95
Appendix E Augmented IEEE24 RTS PSS/E Dynamic Data 102

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