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Direct AC control of grid assets

The objective of the proposed research is to investigate feasible approaches to dynamic control of the power grid. Growth in the demand for electric power, and an increase in the penetration of renewable energy resources are causing congestion on an already aging power grid. Conventional grid control involves the use of static assets that operate on long time scales. These assets provide no dynamic control on the grid, and are typically used for scheduled support. Existing solutions (FACTS devices) to dynamic grid control have seen minimal market penetration because of high cost and low reliability. The proposed research provides a solution for dynamic control of the power grid that augments existing grid assets with a thin AC converter (TACC) to realize enhanced dynamic control. The TACC is a direct AC converter with filter elements and no bulk energy storage that dynamically reflects the asset value on the grid. The converter has a fail-normal mode of operation that returns the asset to its initial operating state, thereby not degrading system reliability. Some applications of TACCs include Inverter-Less STATCOMs and Controllable Network Transformers, which are realized by augmenting shunt VAR capacitors and load tap changers respectively. The principle of virtual quadrature sources is proposed to enable conditioning of AC voltages and currents. The concept is a novel method to realize control of phase angle and, or harmonics in single-phase AC converters, with no bulk energy storage. This concept is used to control the TACC and provides the asset with significantly enhanced control capabilities. Scaling of the TACC to utility voltage and power levels has been addressed by proposing a novel multilevel direct AC converter. The concept proposes the use of commercially available low cost semiconductor devices to realize high power converters. The specific application chosen to validate the concept of TACCs, through a medium voltage design, is the Inverter-less STATCOM.

Identiferoai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/41109
Date20 May 2011
CreatorsSastry, Jyoti
PublisherGeorgia Institute of Technology
Source SetsGeorgia Tech Electronic Thesis and Dissertation Archive
Detected LanguageEnglish
TypeDissertation

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