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Short term wind power forcasting using adaptive neuro-fuzzy inference systems

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Johnson, PL and Negnevitsky, M and Muttaqi, KM (2008) Short term wind power forcasting using adaptive neuro-fuzzy inference systems. In: 2007 Australasian Universities Power Engineering Conference, 9-12 Dec, 2007, Perth, Western Australia.

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Abstract

As the global political will to address climate change gains momentum, the issues associated with integrating an increasing penetration of wind power into power systems need to be addressed. This paper summarises the current trends in wind power and how it is accepted into electricity markets. The need for accurate short term wind power forecasting is highlighted with particular reference to the five minute dispatch interval for the proposed Australian Wind Energy Forecasting System. Results from a case study show that adaptive neuro-fuzzy inference system (ANFIS) models can be a useful tool for short term wind power forecasting providing a performance improvement over the industry standard "persistence" approach.

Item Type: Conference or Workshop Item (Paper)
Page Range: pp. 652-657
Additional Information: ©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE
Date Deposited: 07 Apr 2008 14:57
Last Modified: 18 Nov 2014 03:36
URI: http://eprints.utas.edu.au/id/eprint/4777
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