Ardyono Priyadi, Mauridhi Hery Purnomo : Stochastic Petri Nets For Very Short-Term Wind
Ardyono Priyadi ST, M.Eng
Prof.Dr.Ir. Mauridhi Hery Purnomo M.Eng.
Computational Intelligence and Virtual Environments for Measurement Systems and Applications
Wind Speed; Stochastic Petri Net; Modeling
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.