Research Paper
Year: 2018 | Month: July | Volume: 5 | Issue: 7 | Pages: 161-165
Application of Support Vector Machine for Wind Speed Forecasting
Yogesh. D Rashinkar1, PA Ghonge2
1PG Student, Department of Electrical Engineering, 2Asso Professor, Department of Electronics and Telecommunication Engineering,
Yadavrao Tasgaonkar Institute of Engineering and Technology, Karjat-Raigad, Maharashtra- India.
Corresponding Author: Yogesh. D Rashinkar
ABSTRACT
As the whole world is facing problem of global warming and energy crisis, technologists are looking for the renewable energy sources for better present and future of the next generation. Many countries pay more attention to the development of wind power, which will play an important role in meeting the target of electricity generation from renewable sources. The utility-scale generation of electricity from the wind has a number of desirable attributes such as no air pollution and low operating costs. Despite these attributes, operators of electric power systems remain concerned that wind, as an intermittent resource, can harm system reliability and raise operating costs. There is no doubt that the addition of large amounts of wind generation can impose a burden on system operators, who must dynamically schedule other types of generation to respond to changes in wind generation. Recent studies have indicated that accurate wind speed forecasts bring significant cost savings. Forecasts of wind speed are becoming critical as interest grows in wind as a clean and renewable source of energy, in addition to wide range of other usages. Support Vector Machine [LIBSVM] with MATLAB platform is used in the present work for the wind speed forecasting. Encouraging results are obtained on the data measured at the two different locations in Mumbai.
Key words: Support Vector Machine, Artificial Intelligence, Wind Speed, Forecasting.
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