NDLI: Adaptive prediction of power fluctuations from a wind turbine at Kalpitiya area in Sri Lanka

Content Provider	IEEE Xplore Digital Library
Author	Narayana, M. Witharana, S.
Copyright Year	2012
Description	Author affiliation: Institute of Particle Science and Engineering, University of Leeds, LS2 9JT, UK (Witharana, S.) \|\| Department of Chemical and Process Engineering, University of Moratuwa, Sri Lanka (Narayana, M.)
Abstract	Hydro power is the major renewable energy contributor to the national grid in Sri Lanka amounting to 48% of the total installed capacity. Further expansion of hydropower however is limited due to environmental and resource constraints. Meanwhile the demand for electricity is estimated to rise at an annual rate of 8% – 10% prompting the need to find alternative power options. The wind energy has been identified as a promising candidate to generate electricity in Sri Lanka. However for a reliable integration of wind energy the volatile nature of wind has to be understood. Wind speed-time series data typically exhibit autocorrelation, which can be defined as the degree of dependence on preceding values. Generally, statistical models and neural network techniques are being used for time series analysis. Present study shows how an adaptive digital filter can serve as a modelling, forecasting and monitoring technique, and, how they contribute to a successful integration of wind power into the national grid. The north-western region of Kalpitiya has been identified as one of the potential location for wind power generation in the country. This study also predicts power generation and investigates power fluctuations for grid integrations of a commercially available wind turbine installed in Kalpitiya area by using measured wind speeds and performance of the wind turbine.
Starting Page	262
Ending Page	265
File Size	157080
Page Count	4
File Format	PDF
ISBN	9781467319768
e-ISBN	9781467319751
DOI	10.1109/ICIAFS.2012.6419914
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fluctuations Wind speed Time series analysis Adaptive filters Wind power generation Wind turbines
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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