−5/3 Kolmogorov Turbulent Behaviour and Intermittent Sustainable Energies

We present a study about the atypical and spreading Sporadic E-layers (Es) observed in Digisonde data. We analyzed a set of days around space weather events from 2016 to 2018 over Cachoeira Paulista (CXP, 22.41°S, 45°W, dip ∼35°), a low-latitude Brazilian station. The inhomogeneous Es layer is associated with the auroral-type Es layer (Esa) occurrence in this region due to the presence of South American Magnetic Anomaly (SAMA). However, we also observe that the spreading Es layers occurred days before the magnetic storms or quiet times. Also, this specific type of Es layer has some different characteristics concerning the Esa layer. We used data from the imager, satellite, and meteor radar to understand the dynamic processes acting in this Es layer formation. Our results lead us to believe that other mechanisms affect the Es layer development. We show evidence that the instabilities added to the wind shear mechanism can cause the atypical Es layers, such as Kelvin-Helmholtz instability (KHI). Finally, an important discovery of this work is that the spreading Es layer, mainly during quiet times, is not necessarily due to the particle precipitation due to the SAMA. We found that the wind shear can be turbulent, influencing the Es layer development. Lastly, our analysis better understood the Es layer behavior during quiet and disturbed times.

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“…If this behavior happens, the winds are considered turbulent. All the details about the Kolmogorov technique are given by Calif et al, (2016).…”

Section: The Possible Instability Action In the Es Layer Developmentmentioning

confidence: 99%

Analysis of the different physical mechanisms in the atypical sporadic E (Es) layer occurrence over a low latitude region in the Brazilian sector

Resende

Zhu

Denardini

et al. 2023

Front. Astron. Space Sci.

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“…A tremendous amount of energy, nearly 4000 trillion kWh per day, is provided by the sun, which is much higher than the current energy supplied by tidal, nuclear, and fossil fuels [4,8]. The Direct Normal Insolation (DNI)is variable according to the geographic area, due to its stochastic character [9,10]. Two leading technologies for harvesting solar energy are solar photovoltaic (SPV) technology and concentrated solar power (CSP).…”

Section: Introductionmentioning

confidence: 99%

Performance Improvement and Energy Cost Reduction under Different Scenarios for a Parabolic Trough Solar Power Plant in the Middle-East Region

et al. 2019

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Concentrated solar power (CSP) is a leading renewable energy technology, and the parabolic trough (PT) is one of the most used configurations of CSP. In the present study, the performance improvement and energy cost reduction of a 50 MWe PT plant for Abu Dhabi, United Arab Emirates (UAE) is presented. The simulations were carried out using the System Advisor Model software. The analyses of a PT plant with different technologies/parameters are undertaken in the first instance for seven cases. These cases include solar multiple, solar collectors, receivers, heat transfer fluid, cooling system (evaporative and air-cooled), thermal energy storage system (4–12 h), and fossil dispatch mode (0.25 to 1.0). Based on these analysis, the eighth case, which is found to be the best-case scenario in this study, was considered by taking into account the best of preceding case results and was determined to be the most suitable both in terms of performance and cost reduction. It is, therefore, concluded from this study that the utilization of CSP plants with a proper selection of technology could help reduce energy costs and environmental pollution, enhance system performance, and meet energy demands effectively.

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“…The impact of intermittency generation [2] on the electrical grid is an undesired effect when it comes to electrical generation from alternative energy resources, such as wind speed and global solar radiation. Since this generation is dependent on weather conditions, one of the means to eliminate or reduce its uncertainties is the availability of good prediction methods for these resources [3].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Dynamic Ensemble Methods for Solar Irradiance and Wind Speed Predictions

Vidal Bezerra,

Pinto Marinho,

Costa Rocha

et al. 2023

Atmosphere

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This paper proposes to analyze the performance increase in the forecasting of solar irradiance and wind speed by implementing a dynamic ensemble architecture for intra-hour horizon ranging from 10 to 60 min for a 10 min time step data. Global horizontal irradiance (GHI) and wind speed were computed using four standalone forecasting models (random forest, k-nearest neighbors, support vector regression, and elastic net) to compare their performance against two dynamic ensemble methods, windowing and arbitrating. The standalone models and the dynamic ensemble methods were evaluated using the error metrics RMSE, MAE, R2, and MAPE. This work’s findings showcased that the windowing dynamic ensemble method was the best-performing architecture when compared to the other evaluated models. For both cases of wind speed and solar irradiance forecasting, the ensemble windowing model reached the best error values in terms of RMSE for all the assessed forecasting horizons. Using this approach, the wind speed forecasting gain was 0.56% when compared with the second-best forecasting model, whereas the gain for GHI prediction was 1.96%, considering the RMSE metric. The development of an ensemble model able to provide accurate and precise estimations can be implemented in real-time forecasting applications, helping the evaluation of wind and solar farm operation.

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−5/3 Kolmogorov Turbulent Behaviour and Intermittent Sustainable Energies

Cited by 7 publications

References 28 publications

Analysis of the different physical mechanisms in the atypical sporadic E (Es) layer occurrence over a low latitude region in the Brazilian sector

Analysis of the different physical mechanisms in the atypical sporadic E (Es) layer occurrence over a low latitude region in the Brazilian sector

Performance Improvement and Energy Cost Reduction under Different Scenarios for a Parabolic Trough Solar Power Plant in the Middle-East Region

Machine Learning Dynamic Ensemble Methods for Solar Irradiance and Wind Speed Predictions

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