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The output of solar power generation is significantly dependent on the available solar radiation. Thus, with the proliferation of PV generation in the modern power grid, forecasting of solar irradiance is vital for proper operation of the…
Solar energy supply is usually highly volatile which limits its integration in the power grid. Accurate probabilistic intraday forecasts of solar resources are essential to increase the share of photovoltaic (PV) energy in the grid and…
This work deals with the problem of estimating a photovoltaic generation forecasting model in scenarios where measurements of meteorological variables (i.e. solar irradiance and temperature) at the plant site are not available. A novel…
The ability to accurately forecast power generation from renewable sources is nowadays recognised as a fundamental skill to improve the operation of power systems. Despite the general interest of the power community in this topic, it is not…
Satellite-based solar irradiation forecasting is useful for short-term intra-day time horizons, outperforming numerical weather predictions up to 3-4 hours ahead. The main techniques for solar satellite forecast are based on sophisticated…
Weather is one of the main problems in implementing forecasts for photovoltaic panel systems. Since it is the main generator of disturbances and interruptions in electrical energy. It is necessary to choose a reliable forecasting model for…
Renewable sources of energy are the future due to the environmental problems caused by non-renewable sources to produce energy. The biggest issue with renewable energy sources is that the power produced by devices such as PV solar panels…
The planning and operation of renewable energy, especially wind power, depend crucially on accurate, timely, and high-resolution weather information. Coarse-grid global numerical weather forecasts are typically downscaled to meet these…
Several energy management applications rely on accurate photovoltaic generation forecasts. Common metrics like mean absolute error or root-mean-square error, omit error-distribution details needed for stochastic optimization. In addition,…
Improving irradiance forecasting is critical to further increase the share of solar in the energy mix. On a short time scale, fish-eye cameras on the ground are used to capture cloud displacements causing the local variability of the…
Smooth power generation from solar stations demand accurate, reliable and efficient forecast of solar energy for optimal integration to cater market demand; however, the implicit instability of solar energy production may cause serious…
Accurate forecasting of photovoltaic power is essential for reliable grid integration, yet remains difficult due to highly variable irradiance, complex meteorological drivers, site geography, and device-specific behavior. Although…
In this paper, we present an application of neural networks in the renewable energy domain. We have developed a methodology for the daily prediction of global solar radiation on a horizontal surface. We use an ad-hoc time series…
Knowing the behavior of solar radiation at a geographic location is essential for the use of energy from the sun using photovoltaic systems; however, the number of stations for measuring meteorological parameters and for determining the…
Accurate photovoltaic (PV) power forecasting is critical for integrating renewable energy sources into the grid, optimizing real-time energy management, and ensuring energy reliability amidst increasing demand. However, existing models…
Meteorological agencies around the world rely on real-time flood guidance to issue life-saving advisories and warnings. For decades traditional numerical weather prediction (NWP) models have been state-of-the-art for precipitation…
Solar energy forecasting has seen tremendous growth in the last decade using historical time series collected from a weather station, such as weather variables wind speed and direction, solar radiance, and temperature. It helps in the…
Solar energy is one of the most economical and clean sustainable energy sources on the planet. However, the solar energy throughput is highly unpredictable due to its dependency on a plethora of conditions including weather, seasons, and…
Precipitation nowcasting, the high-resolution forecasting of precipitation up to two hours ahead, supports the real-world socio-economic needs of many sectors reliant on weather-dependent decision-making. State-of-the-art operational…
Accurate renewable energy production forecasting has become a priority as the share of intermittent energy sources on the grid increases. Recent work has shown that convolutional deep learning models can successfully be applied to forecast…