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Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Complex network theory is introduced to solve the islanding problem in an emergency of distribution networks. In this study, the authors put forward an intentional islanding method based on community detection. In this method, a new index has been defined called electrical edge betweenness, on the strength of edge betweenness in complex networks, which fuses electrical characteristics with topological features of actual power lines. Based on the index, the Girvan–Newman algorithm is employed to detect the community structure of distribution networks. Through referring to the modularity value (function Q) and coherent generator groups, they can get a reasonable amount and regions of communities. Then the whole distribution network can be partitioned into several self‐sustainable islands meeting the stable operation constraints. The effectiveness of the authors' proposed method is tested on a standard IEEE 118‐bus system. [ABSTRACT FROM AUTHOR]

Modern power systems are a very complex dynamical system spreading over a large geographical area. They indicate very complex phenomena in some parts as well as in the whole interconnected power system. In large and complex systems, there are coherent groups of generators. A group of generators in one area swings against a group of generators in another area. In this paper, using the Huang's Empirical Mode Decomposition (EMD) signals of the rotor-angle oscillations are separated into several Intrinsic Mode Functions (IMFs) and, thereafter, the correlations between IMFs are applied as a coherency measure and criterion for identification of coherent- generator groups in a power system. The applied approach is analysed for the Kundur two area-four machines test system and New England (NE) bus 39 test system. A comparison between the results of NE bus 39 test system with those of other researches shows a high degree of similarity. [ABSTRACT FROM AUTHOR]

Electromechanical oscillations are inherent to interconnected power systems. However, the frequency of the oscillations and the number of generators that oscillate in any electromechanical oscillatory mode depend on the structure of the power system network. Low frequency electromechanical oscillations occur when existing generation/load areas are connected to other similar areas by relatively weak transmission lines. Weak interconnections are obvious in many interconnected systems, for example, when two independent electric grids are interconnected for the first time through one or two tie lines. However, in systems that have been interconnected for some time, such as the US/Canadian interconnected systems, and that are being stressed by increased load, weak links are less obvious. Often, the first signs of trouble are low frequency oscillations becoming unstable. The connection between loading and stability is not always obvious. It is also unclear which contingencies may lead to oscillatory instability. This tutorial examines in detail the relationship between low frequency oscillations and weak interconnections in the transmission system network. The basis of the analysis is the observation that generators in specific areas of a power system behave coherently in low frequency oscillations and that groups of coherent generators are separated from other groups of coherent generators by weak interconnections. This observation is also the starting point for dynamic system reduction [ABSTRACT FROM PUBLISHER]