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.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479960910
DOIs
Publication statusPublished - 14 Jul 2015
Event2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015 - Shenzhen, China
Duration: 12 Jun 201514 Jun 2015

Publication series

Name2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015

Conference

Conference2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015
Country/TerritoryChina
CityShenzhen
Period12/06/1514/06/15

Keywords

  • Modeling
  • Stochastic Petri Net
  • Wind Speed

Fingerprint

Dive into the research topics of 'Stochastic Petri Nets for very short-term wind speed modeling'. Together they form a unique fingerprint.

Cite this