Probabilistic Solar Forecasts as a Binary Event Using a Sky Camera

Article Energy & Fuels

Omnivision forecasting: Combining satellite and sky images for improved deterministic and probabilistic intra-hour solar energy predictions

Quentin Paletta et al.

Summary: Integrating sky cameras and satellite observations in a machine learning framework improves solar irradiance forecasting, especially in clear-sky conditions, laying the groundwork for future innovative approaches in solar nowcasting.

APPLIED ENERGY (2023)

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Article Energy & Fuels

Probabilistic solar nowcasting based on all-sky imagers

Bijan Nouri et al.

Summary: The interest in shortest-term solar irradiance forecasts (nowcasts) is increasing due to the increase in distributed solar power generation. All sky imager (ASI) systems provide highly resolved nowcasts based on sky conditions. However, these deterministic nowcasts have significant uncertainties, so probabilistic nowcasts with prediction intervals are developed to provide reliable uncertainty information. A benchmark against baseline models is conducted, and the probabilistic nowcasts achieve average skill scores of 0.72 +/- 0.08 and 0.62 +/- 0.09 for direct normal irradiance and global horizontal irradiance, respectively.

SOLAR ENERGY (2023)

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Article Energy & Fuels

Probabilistic solar forecasting: Benchmarks, post-processing, verification

Tilmann Gneiting et al.

Summary: Probabilistic solar forecasts can take the form of predictive probability distributions, ensembles, quantiles, or interval forecasts. The state-of-the-art approaches utilize input from numerical weather prediction models and apply statistical and machine learning methods for post-processing. This study proposes a probabilistic benchmark based on deterministic forecast and introduces new methods that merge statistical techniques with modern neural networks for post-processing.

SOLAR ENERGY (2023)

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Review Green & Sustainable Science & Technology

Deep learning algorithms for very short term solar irradiance forecasting: A survey

Meenu Ajith et al.

Summary: This study compares three categories of solar irradiance forecasting models and finds that the hybrid model MICNN-L performs better in predicting solar irradiance under cloudy conditions.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2023)

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Article Environmental Sciences

Nowcasting System Based on Sky Camera Images to Predict the Solar Flux on the Receiver of a Concentrated Solar Plant

Joaquin Alonso-Montesinos et al.

Summary: This research integrates different technologies to control the energy losses in solar power plant receivers, showing significant progress.

REMOTE SENSING (2022)

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Article Green & Sustainable Science & Technology

Benchmarking of solar irradiance nowcast performance derived from all-sky imagers

Stavros-Andreas Logothetis et al.

Summary: Accurate solar short-term forecasts are crucial for optimal utilization of solar energy systems. This study evaluated the performance of four all-sky imagers in forecasting global horizontal irradiance (GHI), and found that these imagers were able to accurately forecast GHI under different sky conditions, outperforming persistence models.

RENEWABLE ENERGY (2022)

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Review Energy & Fuels

Concentrating Solar Power Advances in Geometric Optics, Materials and System Integration

Georgios E. Arnaoutakis et al.

Summary: This paper reviews the technological advances in concentrating solar power, including geometric optics, receiver configurations, heat storage materials, and thermochemical processes. The comprehensive approach aims to highlight promising concentrating solar power components for further development and wider solar energy utilization.

ENERGIES (2021)

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Article Energy & Fuels