Wind speed and solar irradiance forecasting techniques for enhanced renewable energy integration with the grid

A review

Edward Baleke Ssekulima, Muhammad Bashar Anwar, Amer Al Hinai, Mohamed Shawky El Moursi

Research output: Contribution to journalReview article

42 Citations (Scopus)

Abstract

Power generation from renewable energy resources is on the increase in most countries, and this trend is expected to continue in the foreseeable future. In an effort to enhance the integration of renewable power generation from solar and wind into the traditional power network, there is need to address the vulnerabilities posed to the grid as a result of the intermittent nature of these resources. Variability and ramp events in power output are the key challenges to the system operators due to their impact on system balancing, reserves management, scheduling and commitment of generating units. This has drawn the interest of utilities and researchers towards developing state of the art forecasting techniques for forecasting wind speeds and solar irradiance over a wide range of temporal and spatial horizons. The main forecasting approaches employ physical, statistical, artificial intelligence and hybrid methodologies. This study provides the rationale for forecasting in power systems, a succinct review of forecasting techniques as well as an assessment of their performance as applied in the literature. Also, techniques for improving the accuracy of forecasts have been presented together with key forecasting issues and developing trends.

Original languageEnglish
Pages (from-to)885-898
Number of pages14
JournalIET Renewable Power Generation
Volume10
Issue number7
DOIs
Publication statusPublished - Jul 1 2016

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Power generation
Renewable energy resources
Artificial intelligence
Scheduling

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

Cite this

Wind speed and solar irradiance forecasting techniques for enhanced renewable energy integration with the grid : A review. / Ssekulima, Edward Baleke; Anwar, Muhammad Bashar; Al Hinai, Amer; El Moursi, Mohamed Shawky.

In: IET Renewable Power Generation, Vol. 10, No. 7, 01.07.2016, p. 885-898.

Research output: Contribution to journalReview article

Ssekulima, Edward Baleke ; Anwar, Muhammad Bashar ; Al Hinai, Amer ; El Moursi, Mohamed Shawky. / Wind speed and solar irradiance forecasting techniques for enhanced renewable energy integration with the grid : A review. In: IET Renewable Power Generation. 2016 ; Vol. 10, No. 7. pp. 885-898.
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