NDLI: A new approach to the design of multiple inverter systems using evolutionary optimization

Content Provider	IEEE Xplore Digital Library
Author	Kong, S. Cornforth, D. Berry, A.
Copyright Year	2009
Description	Author affiliation: Commonwealth Scientific and Industrial Research Organisation (CSIRO), Steel River Industrial Estate, Mayfield West, Newcastle, NSW 2304, Australia (Kong, S.; Cornforth, D.; Berry, A.)
Abstract	The use of distributed generators (DGs), especially renewables like wind and solar photovoltaics, depends upon inverter technology to provide compatibility between multiple DGs on a local bus. It is becoming more common to group dissimilar DGs together to form microgrids, and desirable to allow DGs to be connected or disconnected without detrimental effects upon the stability of the microgrid. This has implications for the design of suitable control systems for operating inverters in a heterogeneous microgrid. Evolutionary computing provides a powerful optimization tool that has the potential to assist in the design of control systems for microgrids. As a first step, we introduce a feasibility study, where evolutionary design is used to optimize control parameters for an islanded microgrid with a large number of inverters. We show that the evolutionary optimization provides improved transient response when compared to a manual design, and propose that this approach is worthy of further investigation.
Starting Page	1
Ending Page	8
File Size	2108579
Page Count	8
File Format	PDF
ISBN	9781424442416
ISSN	19449925
DOI	10.1109/PES.2009.5276021
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-26
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Inverters Design optimization Power generation Control systems Wind energy generation Distributed power generation Transient response Power system reliability Voltage control Waste heat evolutionary computing microgrids control optimization transient response
Content Type	Text
Resource Type	Article

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