A Novel and Alternative Approach for Direct and Indirect Wind-Power Prediction Methods

Neeraj Bokde, Andrés Feijóo, Daniel Villanueva and Kishore Kulat
Additional contact information
Neeraj Bokde: Department of Electronics and Communication Engineering, Visvesvaraya National Institute of Technology, Nagpur 440010, India
Andrés Feijóo: Departamento de Enxeñería Eléctrica-Universidade de Vigo, Campus de Lagoas-Marcosende, 36310 Vigo, Spain
Daniel Villanueva: Departamento de Enxeñería Eléctrica-Universidade de Vigo, Campus de Lagoas-Marcosende, 36310 Vigo, Spain
Kishore Kulat: Department of Electronics and Communication Engineering, Visvesvaraya National Institute of Technology, Nagpur 440010, India

Energies, 2018, vol. 11, issue 11, 1-19

Abstract: Wind energy is a variable energy source with a growing presence in many electrical networks across the world. Wind-speed prediction has become an important tool for many agents involved in energy markets. In this paper, an approach to this problem is proposed by means of a novel method that outperforms results obtained by current direct and indirect wind-power prediction procedures. The first difference is that it is not strictly a direct or indirect method in the conventional sense because it uses information from both wind-speed and wind-power data series to obtain a wind-power series. The second difference is that it smooths down the wind-power series obtained in the first stage, and uses the resulting series for predicting new wind-power values. The process of smoothing is based on the label sequence generation process discussed in the pattern sequence forecasting algorithm and the Naive Bayesian method-based matching process. The result is a less chaotic way to predict wind speed than those offered by other existing methods. It has been assessed in multiple simulations, for which three different error measures have been used.

Keywords: wind speed; wind power; prediction; indirect prediction approach; power curve (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/11/2923/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/11/2923/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:11:p:2923-:d:178573

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().