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It has become more and more demanding to investigate the impacts of wind farms on power system operation as ever-increasing penetration levels of wind power have the potential to bring about a series of dynamic stability problems for power systems. This paper undertakes such an investigation through investigating the small signal and transient stabilities of power systems that are separately integrated with three types of wind turbine generators (WTGs), namely the squirrel cage induction generator (SCIG), the doubly fed induction generator (DFIG), and the permanent magnet generator (PMG). To examine the effects of these WTGs on a power system with regard to its stability under different operating conditions, a selected synchronous generator (SG) of the well-known Western Electricity Coordinating Council (WECC three-unit nine-bus system and an eight-unit 24-bus system is replaced in turn by each type of WTG with the same capacity. The performances of the power system in response to the disturbances are then systematically compared. Specifically, the following comparisons are undertaken: (1) performances of the power system before and after the integration of the WTGs; and (2) performances of the power system and the associated consequences when the SCIG, DFIG, or PMG are separately connected to the system. These stability case studies utilize both eigenvalue analysis and dynamic time-domain simulation methods. [ABSTRACT FROM AUTHOR]

Optimization of schemes for black-start is one of the most important factors determining the speed of power system restoration after either a global blackout or a local outage. In this paper a novel method employing the entropy weight-based decision-making theory is proposed for this application. By using the method for the decision making in black start, the subjective weights acquired from knowledge and experience of experts could be used in conjunction with the objective weights (entropy weighs) deduced from some closely related indices. Obviously, the developed method can greatly improve the performance in power system restoration by overcoming the shortcomings of conventional methods that only use either the subjective or the objective weights. Furthermore, the proposed method is applicable in power systems with different levels of black-start experience for assisting the optimal black-start decision making. It is shown that the proposed method is suitable for power systems with different levels of black-start experience. [ABSTRACT FROM AUTHOR]