Weather Statistical Modelling for Analyzing the Hybrid Power System

  • Alfrets Septy Wauran Electrical Engineering, Manado State Polytechnic, INDONESIA
  • Anritsu Polii Electrical Engineering, Manado State Polytechnic, INDONESIA
  • Anthoinete Waroh Electrical Engineering, Manado State Polytechnic, INDONESIA

Abstract

Hybrid Power System is a combination of different power resources and storage. For example, the combination of Solar Panel, Wind Turbine, Diesel Generator and Battery. The power production of the renewable energy resources, Solar Panel and Wind Turbine, is depended on the Weather (Wind Speed and Solar Irradiation). So, it is important to make a very good model for Wind Speed and Solar Irradiation. The objective of this research is to make a statistical model of wind speed and solar irradiation using ARIMA Model and R Language Programming. We use R language in RStudio editor for making the model of wind speed and solar irradiation. R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. RStudio is a visual editor for R. This software are integrated with R, but we can use the easy toolbox that already set for all function and facilities.

Published
Dec 31, 2016
How to Cite
WAURAN, Alfrets Septy; POLII, Anritsu; WAROH, Anthoinete. Weather Statistical Modelling for Analyzing the Hybrid Power System. PROCEEDINGS OF POSTER ABSTRACTS KCIC 2016, [S.l.], p. 17-18, dec. 2016. ISSN 2548-3773. Available at: <http://jurnal.polimdo.ac.id/index.php/kcic/article/view/142>. Date accessed: 28 mar. 2024.