A Critical Review of Wind Power Forecasting Methods—Past, Present and Future

Hanifi, Shahram, Liu, Xiaolei, Lin, Zi and Lotfian, Saeid (2020) A Critical Review of Wind Power Forecasting Methods—Past, Present and Future. Energies, 13 (15). p. 3764. ISSN 1996-1073

[img]
Preview
Text
energies-13-03764.pdf - Published Version
Available under License Creative Commons Attribution 4.0.

Download (1MB) | Preview
Official URL: https://doi.org/10.3390/en13153764

Abstract

The largest obstacle that suppresses the increase of wind power penetration within the power grid is uncertainties and fluctuations in wind speeds. Therefore, accurate wind power forecasting is a challenging task, which can significantly impact the effective operation of power systems. Wind power forecasting is also vital for planning unit commitment, maintenance scheduling and profit maximisation of power traders. The current development of cost-effective operation and maintenance methods for modern wind turbines benefits from the advancement of effective and accurate wind power forecasting approaches. This paper systematically reviewed the state-of-the-art approaches of wind power forecasting with regard to physical, statistical (time series and artificial neural networks) and hybrid methods, including factors that affect accuracy and computational time in the predictive modelling efforts. Besides, this study provided a guideline for wind power forecasting process screening, allowing the wind turbine/farm operators to identify the most appropriate predictive methods based on time horizons, input features, computational time, error measurements, etc. More specifically, further recommendations for the research community of wind power forecasting were proposed based on reviewed literature.

Item Type: Article
Uncontrolled Keywords: wind power forecasting; artificial neural networks; hybrid methods; performance evaluation
Subjects: F900 Others in Physical Sciences
H100 General Engineering
H300 Mechanical Engineering
H900 Others in Engineering
Department: Faculties > Engineering and Environment > Mechanical and Construction Engineering
Depositing User: Rachel Branson
Date Deposited: 05 Aug 2020 10:36
Last Modified: 21 Aug 2020 12:28
URI: http://nrl.northumbria.ac.uk/id/eprint/43994

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics