A Bayesian Model Committee Approach to Forecasting Global Solar Radiation

Details A Bayesian Model Committee Approach to Forecasting Global Solar Radiation A Bayesian Model Committee Approach to Forecasting Global Solar Radiation

2012-03-24

arxiv.org/abs/1203.5446v1

Statistics

Applications

WREF 2012 : World Renewable Energy Forum, Denver : United States (2012)

Scientific paper

This paper proposes to use a rather new modelling approach in the realm of solar radiation forecasting. In this work, two forecasting models: Autoregressive Moving Average (ARMA) and Neural Network (NN) models are combined to form a model committee. The Bayesian inference is used to affect a probability to each model in the committee. Hence, each model's predictions are weighted by their respective probability. The models are fitted to one year of hourly Global Horizontal Irradiance (GHI) measurements. Another year (the test set) is used for making genuine one hour ahead (h+1) out-of-sample forecast comparisons. The proposed approach is benchmarked against the persistence model. The very first results show an improvement brought by this approach.

Affiliated with

Also associated with

No associations

Rating

A Bayesian Model Committee Approach to Forecasting Global Solar Radiation does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Bayesian Model Committee Approach to Forecasting Global Solar Radiation, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Bayesian Model Committee Approach to Forecasting Global Solar Radiation will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-74717