Interpretable deep learning framework for hourly solar radiation forecasting based on decomposing multi-scale variations

Li, You; Zhou, Weisheng; Wang, Yafei; Miao, Sheng; Yao, Wanxiang; Gao, Weijun

doi:10.1016/j.apenergy.2024.124409

Applied Energy

2025

DOI: 10.1016/j.apenergy.2024.124409

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Interpretable deep learning framework for hourly solar radiation forecasting based on decomposing multi-scale variations

You Li,

Weisheng Zhou,

Yafei Wang

et al.

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Analysis of Grid-Scale Photovoltaic Plants Incorporating Battery Storage with Daily Constant Setpoints

Tejero-Gómez,

Bayod-Rújula

2024

Energies

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A global energy transition is crucial to combat climate change, involving a shift from fossil fuels to renewable sources and low-emission technologies. Solar photovoltaic technology has grown exponentially in the last decade, establishing itself as a cost-effective and sustainable option for electricity generation. However, its large-scale integration faces challenges due to its intermittency and lack of dispatchability. This study evaluates, from an energy perspective, the case of hybrid photovoltaic (PV) plants with battery storage systems. It addresses an aspect little explored in the literature: the sizing of battery storage to maintain a steady and constant 24 h power supply, which is usually avoided due to its high cost. Although the current economic feasibility is limited, the rapidly falling price of lithium batteries suggests that this solution could be viable in the near future. Using Matlab simulations, the system’s ability to deliver a constant energy production of electricity is assessed. Energy indicators are used to identify the optimal system size under different scenarios and power setpoints. The results determine the optimal storage size to supply a constant power that covers all or a large part of the daily PV generation, achieving steady and reliable electricity production. In addition, the impact of using setpoints at different time horizons is assessed. This approach has the potential to redefine the perception of solar PV, making it a dispatchable energy source, improving its integration into the electricity grid, and supporting the transition to more sustainable and resilient energy systems.

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Analysis of Grid-Scale Photovoltaic Plants Incorporating Battery Storage with Daily Constant Setpoints

Tejero-Gómez,

Bayod-Rújula

2024

Energies

View full text Add to dashboard Cite

show abstract

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Interpretable deep learning framework for hourly solar radiation forecasting based on decomposing multi-scale variations

Cited by 1 publication

References 55 publications

Analysis of Grid-Scale Photovoltaic Plants Incorporating Battery Storage with Daily Constant Setpoints

Analysis of Grid-Scale Photovoltaic Plants Incorporating Battery Storage with Daily Constant Setpoints

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