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The ever-increasing penetration of wind power integration into a power system can produce significant impacts on the operation of an interconnected power system. As the major energy conversion technology for large wind turbines, the doubly fed induction generator (DFIG) will play an important role in future power systems. Hence, the impacts of the DFIG on the low-frequency oscillations of interconnected power systems have become an important issue with extensive concerns. This paper examines the impacts of several factors, including the DFIG transmission distance, tie-line power of the interconnected system, DFIG capacity, with/without a power system stabilizer (PSS), on the low frequency oscillation characteristic of an interconnected power system using both eigenvalue analysis and dynamic simulations. To investigate the effects of these factors on the interarea oscillation mode, case studies are carried out on two two-area interconnected power systems, and some conclusions are obtained. [ABSTRACT FROM AUTHOR]

Abstract: Traditional analytic models for power system fault diagnosis are usually formulated as an unconstrained 0–1 integer programming problem. The key issue of the models is to seek the fault hypothesis that minimizes the discrepancy between the actual and the expected states of the concerned protective relays and circuit breakers. The temporal information of alarm messages has not been well utilized in these methods, and as a result, the diagnosis results may be not unique and hence indefinite, especially when complicated and multiple faults occur. In order to solve this problem, this paper presents a novel analytic model employing the temporal information of alarm messages along with the concept of related path. The temporal relationship among the actions of protective relays and circuit breakers, and the different protection configurations in a modern power system can be reasonably represented by the developed model, and therefore, the diagnosed results will be more definite under different circumstances of faults. Finally, an actual power system fault was served to verify the proposed method. [Copyright &y& Elsevier]

The fuzzy Petri net is a promising and efficient approach that can tackle the complexities of power system fault diagnosis. In this work, the temporal constraint between event occurrences in power systems is investigated. Then, it is introduced to a fuzzy Petri net (FPN) for fault diagnosis. The temporal attributes are assigned to the propositions in the Petri net, so that temporal information can be taken into account, which makes the true hypothesis distinguishable from the false ones. The modified matrix execution algorithm can enhance computational efficiency, with a “weighted average” operation included to improve the fault-tolerance. The developed model possesses a modular structure, which is easy to adapt to topology changes, and to accommodate modern protection schemes. A preliminary evaluation of the operating performance of protective devices is also carried out after fault section identification. The testing results on the IEEE 14-bus power system and Zhejiang provincial power system in China demonstrate that the developed model is correct and efficient. Compared with three existing fault diagnosis methods, the proposed one has stronger fault-tolerance with lower computational cost, and is suitable for on-line fault diagnosis in large-scale power systems. [ABSTRACT FROM AUTHOR]