Journal ArticleDOI
Prediction of hourly solar radiation using a novel hybrid model of ARMA and TDNN
Ji Wu,Chee Keong Chan +1 more
TLDR
A novel hybrid model that combines both the ARMA and TDNN, is applied to produce better prediction of the hourly solar radiation series and shows that this hybrid model can take the advantages of both ARMAand TDNN and give excellent result.About:
This article is published in Solar Energy.The article was published on 2011-05-01. It has received 292 citations till now. The article focuses on the topics: Autoregressive–moving-average model & Autoregressive model.read more
Citations
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Journal ArticleDOI
Solar forecasting methods for renewable energy integration
TL;DR: In this article, the authors review the theory behind these forecasting methodologies, and a number of successful applications of solar forecasting methods for both the solar resource and the power output of solar plants at the utility scale level.
Journal ArticleDOI
Review of solar irradiance forecasting methods and a proposition for small-scale insular grids
TL;DR: In this article, the authors present an in-depth review of the current methods used to forecast solar irradiance in order to facilitate selection of the appropriate forecast method according to needs.
Online Short-term Solar Power Forecasting
TL;DR: The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h, where the results indicate that for forecasts up to 2 h ahead the most important input is the available observations ofSolar power, while for longer horizons NWPs are theMost important input.
Proceedings ArticleDOI
Deep Learning for solar power forecasting — An approach using AutoEncoder and LSTM Neural Networks
TL;DR: This work uses different Deep Learning and Artificial Neural Network algorithms, such as Deep Belief Networks, AutoEncoder, and LSTM, to show their forecast strength compared to a standard MLP and a physical forecasting model in the forecasting the energy output of 21 solar power plants.
Journal ArticleDOI
Ensemble Classification and Regression-Recent Developments, Applications and Future Directions [Review Article]
TL;DR: This paper reviews traditional as well as state-of-the-art ensemble methods and thus can serve as an extensive summary for practitioners and beginners.
References
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Likelihood ratio statistics for autoregressive time series with a unit root
David A. Dickey,Wayne A. Fuller +1 more
Book
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TL;DR: In this paper, Monte Carlo techniques are used to fit dependent and independent variables least squares fit to a polynomial least-squares fit to an arbitrary function fitting composite peaks direct application of the maximum likelihood.
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TL;DR: This revision of a classic, seminal, and authoritative book explores the building of stochastic models for time series and their use in important areas of application forecasting, model specification, estimation, and checking, transfer function modeling of dynamic relationships, modeling the effects of intervention events, and process control.