Performance Comparison of ARIMA and k-NN Models for Short-term Wind Speed Forecasting

11 Pages Posted: 13 Apr 2020

See all articles by Tushar Shikhola

Tushar Shikhola

Netaji Subhas Institute of Technology (NSIT) - Netaji Subhas University of Technology

Rajneesh Sharma

Netaji Subhas Institute of Technology (NSIT) - Netaji Subhas University of Technology

Date Written: April 11, 2020

Abstract

The rapid generation in the wind power is a result of extensive research which is centrally focused on environmental and productive advantages of wind power. A major requirement for this growth is efficient prediction of local wind speed, which provide an estimated potential of wind speed distribution of a region. This paper proposes a methodology for accurate one minute ahead wind speed prediction for two sites of Gujarat region, India. Herein, a comparison between conventional ARIMA and machine learning K-NN model has been presented. Reduced value of performance indices for k-NN makes it a simple and efficient model for prediction of wind speed.

Keywords: Auto Regressive Integrated Moving Average; k-Nearest Neighbor; one-step ahead forecasting

Suggested Citation

Shikhola, Tushar and Sharma, Rajneesh, Performance Comparison of ARIMA and k-NN Models for Short-term Wind Speed Forecasting (April 11, 2020). Proceedings of the International Conference on Advances in Electronics, Electrical & Computational Intelligence (ICAEEC) 2019, Available at SSRN: https://ssrn.com/abstract=3573458 or http://dx.doi.org/10.2139/ssrn.3573458

Tushar Shikhola (Contact Author)

Netaji Subhas Institute of Technology (NSIT) - Netaji Subhas University of Technology ( email )

ICE Division
NSUT
Dwarka, Delhi, 110078
India

Rajneesh Sharma

Netaji Subhas Institute of Technology (NSIT) - Netaji Subhas University of Technology ( email )

ICE Division
NSUT
Dwarka, Delhi, 110078
India

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