NDLI: Stochastic Petri Nets for very short-term wind speed modeling

Content Provider	IEEE Xplore Digital Library
Author	Putri, R.I. Priyadi, A. Purnomo, M.H.
Copyright Year	2015
Description	Author affiliation: Electr. Eng. Dept., Inst. Teknol. Sepuluh Nopember, Surabaya, Indonesia (Putri, R.I.; Priyadi, A.; Purnomo, M.H.)
Abstract	To overcome the limitations of fossil energy and protect the environment from emissions of greenhouse gases, it is essential to develop the use of renewable energy as a substitute. At present, one of the renewable sources of energy is wind energy, which has the advantage of being pollution free and inexhaustible. However, the use of wind energy is strongly influenced by wind speed, which is not constant. Such varying wind speeds lead to the creation of fluctuated wind power. Consequently, there is a need for modeling and the accurate prediction of wind speed to help optimize the design of the turbine and control system in a wind energy conversion system to maintain system stability. This paper presents the modeling of very short-term wind speed using Stochastic Petri Nets (SPN) that is based on the measurement results of wind speed in Nganjuk. In this study, Stochastic Petri Nets was designed by using 7 places and 7 transitions. Transition to the SPN is defined as a function that generates random values using a uniform function. Wind speed data that was generated during a 500 seconds interval, was compared with the observed wind speeds. The comparison of the generated wind speed and observed ones shows that both its statistical characteristic have similar value.
Starting Page	1
Ending Page	4
File Size	782512
Page Count	4
File Format	PDF
ISBN	9781479960927
DOI	10.1109/CIVEMSA.2015.7158619
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic Petri Net Wind energy Wind speed Petri nets Wind Speed Predictive models Markov processes Data models Modeling
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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