Control Methods of Inverter-Interfaced Distributed Generators in a Microgrid System

Microgrids are a new concept for future energy distribution systems that enable renewable energy integration and improved energy management capability. Microgrids consist of multiple distributed generators (DGs) that are usually integrated via power electronic inverters. In order to enhance power qu...

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Bibliographic Details
Published in:IEEE transactions on industry applications 2010-05, Vol.46 (3), p.1078-1088
Main Authors: Il-Yop Chung, Wenxin Liu, Cartes, David A, Collins, Emmanuel G, Seung-Il Moon
Format: Article
Language:English
Subjects:
Algorithms
Buses (vehicles)
Control systems
Control-parameter tuning
distributed generator (DG)
Distributed power generation
droop controller
Electric potential
Electronics
Energy management
Frequency
Generators
Inverters
microgrid
Optimal control
particle swarm optimization (PSO)
Power electronics
Power generation
Renewable energy resources
Voltage
Voltage control
{\rm L}_{1} theory
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Summary:Microgrids are a new concept for future energy distribution systems that enable renewable energy integration and improved energy management capability. Microgrids consist of multiple distributed generators (DGs) that are usually integrated via power electronic inverters. In order to enhance power quality and power distribution reliability, microgrids need to operate in both grid-connected and island modes. Consequently, microgrids can suffer performance degradation as the operating conditions vary due to abrupt mode changes and variations in bus voltages and system frequency. This paper presents controller design and optimization methods to stably coordinate multiple inverter-interfaced DGs and to robustly control individual interface inverters against voltage and frequency disturbances. Droop-control concepts are used as system-level multiple DG coordination controllers, and control theory is applied to device-level inverter controllers. Optimal control parameters are obtained by particle-swarm-optimization algorithms, and the control performance is verified via simulation studies.
ISSN:0093-9994
1939-9367
DOI:10.1109/TIA.2010.2044970