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Applications of Battery Energy Storage Systems (BESS) in the power grids will be expanded in the coming years due to factors such as decreasing costs of such systems. In a modern power network, BESS systems can be optimally controlled for peak-load shaving and other ancillary services such as volt-var control, system balancing and loss reduction. However, all these “system-level” controls will depend on the capability of each individual BESS to independently control the active and reactive power injection/absorption at its connected bus, and to maintain the voltage of the DC link between its AC/DC and DC/DC converters. As a result, understanding the behavior and control requirements for the operation of the BESS is necessary. In this paper, an active AC/DC rectifier and a bidirectional DC/DC converter have been modeled and analyzed for charging and discharging of the batteries in a BESS system. The models used in these analyses have been developed based on an integrated state-space equation set for the converters and the battery. This type of modeling is proper for demonstration of the effects of massively integrated storage systems in the bulk power grids.

This paper presents an approach to utilize a Chinese machine-readable dictionary to acquire a conceptual network with five semantic relations; and then, the application of this conceptual resource is discussed text retrieval. Because of the low accuracy of current Chinese parser, our method is different from other traditional dictionary processing that need parsing the explanations of words when constructing this noun-based conceptual network. This construction is designed to be a new three-step process by statistical learning mechanism. This method acquires a relatively satisfying conceptual network based on Chinese nouns. In its application, this network is available for providing linkage-based knowledge for text retrieval.