Next Article in Journal
Particulate Characteristics during a Haze Episode Based on Two Ceilometers with Different Wavelengths
Next Article in Special Issue
Changing Trends and Abrupt Features of Extreme Temperature in Mainland China from 1960 to 2010
Previous Article in Journal
Carbon Sequestration and Carbon Markets for Tree-Based Intercropping Systems in Southern Quebec, Canada
Previous Article in Special Issue
Review and Extension of Suitability Assessment Indicators of Weather Model Output for Analyzing Decentralized Energy Systems
Article Menu

Export Article

Open AccessArticle
Atmosphere 2016, 7(2), 18; doi:10.3390/atmos7020018

Solar Forecasting in a Challenging Insular Context

1
PIMENT laboratory, University of La Réunion, 15 avenue René Cassin, 97715 Saint-Denis, France
2
Department of Physics, University of Oldenburg, Carl-von-Ossietzky-Street 9-11, 26129 Oldenburg, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: John Boland
Received: 15 December 2015 / Revised: 18 January 2016 / Accepted: 22 January 2016 / Published: 29 January 2016
(This article belongs to the Special Issue Climate Variable Forecasting)
View Full-Text   |   Download PDF [2906 KB, uploaded 29 January 2016]   |  

Abstract

This paper aims at assessing the accuracy of different solar forecasting methods in the case of an insular context. Two sites of La Réunion Island, Le Tampon and Saint-Pierre, are chosen to do the benchmarking exercise. Réunion Island is a tropical island with a complex orography where cloud processes are mainly governed by local dynamics. As a consequence, Réunion Island exhibits numerous micro-climates. The two aforementioned sites are quite representative of the challenging character of solar forecasting in the case of a tropical island with complex orography. Hence, although distant from only 10 km, these two sites exhibit very different sky conditions. This work focuses on day-ahead and intra-day solar forecasting. Day-ahead solar forecasts are provided by the European Center for Medium-Range Weather Forecast (ECMWF). This organization maintains and runs the Numerical Weather Prediction (NWP) model named Integrated Forecast System (IFS). In this work, post-processing techniques are applied to refine the output of the IFS model for day-ahead forecasting. Statistical models like a recursive linear model or a nonlinear model such as an artificial neural network are used to produce the intra-day solar forecasts. It is shown that a combination of the IFS model and the neural network model further improves the accuracy of the forecasts. View Full-Text
Keywords: solar forecasting; statistical models; NWP model; model output statistics solar forecasting; statistical models; NWP model; model output statistics
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Lauret, P.; Lorenz, E.; David, M. Solar Forecasting in a Challenging Insular Context. Atmosphere 2016, 7, 18.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Atmosphere EISSN 2073-4433 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top