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All issues Renew. Energy Environ. Sustain., 2 (2017) 23 Article references

Articles citing this article

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Cited article:

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Statistical analysis of cloud layers and solar irradiations for all seasons in Toyohashi city, Japan

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https://doi.org/10.1051/rees/2023018

Improving Solar Radiation Nowcasts by Blending Data-Driven, Satellite-Images-Based and All-Sky-Imagers-Based Models Using Machine Learning Techniques

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Distributed Generation Forecasting Based on Rolling Graph Neural Network (ROLL-GNN)

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Statistical Analysis of Cloud Layers and Derivation of Motion Directions of Two Layer Clouds

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https://doi.org/10.1541/ieejpes.142.490

Spatio-Temporal Graph Neural Networks for Multi-Site PV Power Forecasting

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Machine Learning techniques for solar irradiation nowcasting: Cloud type classification forecast through satellite data and imagery

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Assessment of new solar radiation nowcasting methods based on sky-camera and satellite imagery

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Optimal Sizing of a Grid Independent Renewable Heating System for Building Decarbonisation

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Frontiers in Energy Research 9 (2021)
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Advances in Electrical Control and Signal Systems

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Hybrid approaches based on deep whole-sky-image learning to photovoltaic generation forecasting

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Global Horizontal Irradiance Modeling for All Sky Conditions Using an Image-Pixel Approach

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https://doi.org/10.1016/j.apenergy.2019.113718

Transition Towards 100% Renewable Energy

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Irradiance Variability Quantification and Small-Scale Averaging in Space and Time: A Short Review

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https://doi.org/10.3390/atmos9070264