Proceedings ArticleDOI
Very short term forecasting in global solar irradiance using linear and nonlinear models
Alvaro D. Orjuela-Cañón,Johann Hernandez,Cristian Rodriguez Rivero +2 more
- pp 1-5
TLDR
In this article, a very short term forecasting model is proposed to improve the available supplies of photovoltaic systems, which is based on solar radiation that focuses on the panels, thus the generation of energy depends on this resource.Abstract:
The behavior of the Photovoltaic Systems are based on solar radiation that focuses on the panels, thus the generation of energy depends on this resource. Planning of these systems makes that demanding energy can be interrupted due to variant radiation behavior. Very short term forecasting models can be useful to improve the available supplies. Present proposal allows a first approach for term shorter prediction of global solar irradiance. Linear and nonlinear models were compared to implement this forecasting. Results show that nonlinear models based on computational intelligence techniques provide better results with a simpler methodology to get the models.read more
Citations
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Journal ArticleDOI
Real-Time Coordinated Voltage Control of PV Inverters and Energy Storage for Weak Networks With High PV Penetration
TL;DR: A real-time method is designed to coordinate PV inverters and BESS for voltage regulation to keep up with fast fluctuations of PV power and it will provide valuable insights and applicable strategies to both utilities and PV owners for large-scale PV farm integration into rural networks.
Journal ArticleDOI
A current perspective on the accuracy of incoming solar energy forecasting
TL;DR: The state-of-the-art in the accuracy of solar resources forecasting is obtained by using results reported in 1705 accuracy tests reported in several geographic regions and the hybrid models have the best performance.
Journal ArticleDOI
Using Smart Persistence and Random Forests to Predict Photovoltaic Energy Production
Javier Huertas Tato,Miguel Brito +1 more
TL;DR: In this paper, the authors integrated a prediction algorithm (Smart Persistence), irradiance, and past production data, using a state-of-the-art machine learning technique (Random Forests).
Journal ArticleDOI
A New Approach for Prediction of Solar Radiation with Using Ensemble Learning Algorithm
TL;DR: The results show empirically that ensemble models improve prediction accuracies of various base regression models and it can be applied to other machine learning models used in solar irradiance prediction.
Journal ArticleDOI
Novel short-term solar radiation hybrid model: Long short-term memory network integrated with robust local mean decomposition
TL;DR: It is ascertained that the newly designed approach can be a potential candidate for real-time energy management, renewable energy integration into a power grid and other decisions to optimise the overall system's scheduling and performance.
References
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