The Research of Power System Stability Problems Caused by Integration of Large-Scale Wind Power

2013 ◽  
Vol 391 ◽  
pp. 291-294
Author(s):  
Xiao Ning Xu ◽  
Xue Song Zhou

In recent years, wind power in China developed rappidly. More and more problems occurred with the integration of large-scale wind power. Arounding the issues of power system stability which are resulted from the integration of wind power and ite relevant technology, this paper mainly introduced the voltage stability from the angle of the definition and the classification, and analyzed power systems which contains wind farms from the angle of the research contents and methods of static and dynamic voltage stability, especially emphasizing the necessity of the bifurcation theory used in power system contains wind power.

2013 ◽  
Vol 316-317 ◽  
pp. 64-67
Author(s):  
You Jie Ma ◽  
Yu Zhang ◽  
Xue Song Zhou

Wind power is a kind of special electric power, because of the volatility of the wind, making voltage stability has become an important research problem wind power system must facing with. Therefore, according to the relevant current research status and the main existent problems of wind power system, expounding the difference of voltage stability between the conventional energy sources and the wind power, and the influence of voltage stability to the power system which caused by wind power system. This paper mainly from the definition and the classification to introduce the voltage stability; from the research contents and methods of static and dynamic voltage stability to analyze power systems which contains wind farms, especially emphasizing the necessity of the bifurcation theory used in power system contains wind power. Finally points out that the research trend of analysis and improvement in this area.


2019 ◽  
Vol 2019 (16) ◽  
pp. 2514-2519 ◽  
Author(s):  
Guoyun Su ◽  
Long Xu ◽  
Wenjuan Du ◽  
Chen Chen ◽  
Yining Ji ◽  
...  

2019 ◽  
Vol 9 (4) ◽  
pp. 4384-4388 ◽  
Author(s):  
D. N. Truong ◽  
V. T. Bui

The objective of this paper is to perform a hybrid design for an Adaptive Neuro-Fuzzy Inference System (ANFIS) optimized by Particle Swarm Optimization (PSO) to improve the dynamic voltage stability of a grid-connected wind power system. An onshore 99.2MW wind farm using Doubly Fed Induction Generator (DFIG) is studied. To compensate the reactive power absorbed from the power grid of the wind farm, a Static VAR Compensator (SVC) is proposed. To demonstrate the performance of the proposed hybrid PSO–ANFIS controller, simulations of the voltage response in time-domain are performed in Matlab to evaluate the effectiveness of the designed controller. From the results, it can be concluded that the proposed hybrid PSO-optimized ANFIS-based model can be applied to enhance the dynamic voltage stability of the studied grid-connected wind power system.


2018 ◽  
Vol 8 (2) ◽  
pp. 2758-2763 ◽  
Author(s):  
D. V. Ngo ◽  
K. V. Pham ◽  
D. D. Le ◽  
K. H. Le ◽  
K. V. Huynh

An increase in load capacity during the operation of a power system usually causes voltage drop and leads to system instability, so it is necessary to monitor the effect of load changes. This article presents a method of assessing the power system stability according to the load node capacity considering uncertainty factors in the system. The proposed approach can be applied to large-scale power systems for voltage stability assessment in real-time.


2015 ◽  
Vol 737 ◽  
pp. 199-203
Author(s):  
Shao Hong Tsai ◽  
Yuan Kang Wu ◽  
Ching Yin Lee ◽  
Wen Ta Tsai

Modern wind turbine technology has been a great improvement over the past couple decades, leading to large scale wind power penetration. The increasing penetration of wind power resulted in emphasizing the importance of reliable and secure operation of power systems, especially in a weak power system. In this paper, the main wind turbine control schemes, the wind penetration levels and wind farm dynamic behavior for grid code compliance were investigated in the Penghu wind power system, a weak isolated power system.


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