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Capturing the uncertainty in probabilistic wind power forecasts is challenging, especially when uncertain input variables, such as the weather, play a role. Since ensemble weather predictions aim to capture the uncertainty in the weather…

Applications · Statistics 2022-04-26 Kaleb Phipps , Sebastian Lerch , Maria Andersson , Ralf Mikut , Veit Hagenmeyer , Nicole Ludwig

Despite the increasing importance of forecasts of renewable energy, current planning studies only address a general estimate of the forecast quality to be expected and selected forecast horizons. However, these estimates allow only a…

Applications · Statistics 2019-06-03 Jens Schreiber , Artjom Buschin , Bernhard Sick

Generation and load balance is required in the economic scheduling of generating units in the smart grid. Variable energy generations, particularly from wind and solar energy resources, are witnessing a rapid boost, and, it is anticipated…

Machine Learning · Computer Science 2017-04-07 Mohamed Abuella , Badrul Chowdhury

By the end of 2021, the renewable energy share of the global electricity capacity reached 38.3% and the new installations are dominated by wind and solar energy, showing global increases of 12.7% and 18.5%, respectively. However, both wind…

Machine Learning · Statistics 2024-09-18 Ágnes Baran , Sándor Baran

In this article, we propose a novel ensemble technique with a multi-scheme weighting based on a technique called coopetitive soft gating. This technique combines both, ensemble member competition and cooperation, in order to maximize the…

Applications · Statistics 2018-03-20 André Gensler , Bernhard Sick

Nowadays, with the unprecedented penetration of renewable distributed energy resources (DERs), the necessity of an efficient energy forecasting model is more demanding than before. Generally, forecasting models are trained using observed…

Machine Learning · Statistics 2017-07-18 Hossein Sangrody , Morteza Sarailoo , Ning Zhou , Ahmad Shokrollahi , Elham Foruzan

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…

Machine Learning · Computer Science 2022-05-18 Soham Vyas , Yuvraj Goyal , Neel Bhatt , Sanskar Bhuwania , Hardik Patel , Shakti Mishra , Brijesh Tripathi

One essential component of operational space weather forecasting is the prediction of solar flares. With a multitude of flare forecasting methods now available online it is still unclear which of these methods performs best, and none are…

Space Physics · Physics 2020-08-04 Jordan A. Guerra , Sophie A. Murray , D. Shaun Bloomfield , Peter T. Gallagher

As renewable distributed energy resources (DERs) penetrate the power grid at an accelerating speed, it is essential for operators to have accurate solar photovoltaic (PV) energy forecasting for efficient operations and planning. Generally,…

Machine Learning · Statistics 2017-09-26 Hossein Sangrody , Morteza Sarailoo , Ning Zhou , Nhu Tran , Mahdi Motalleb , Elham Foruzan

Weather forecasting has seen a shift in methods from numerical simulations to data-driven systems. While initial research in the area focused on deterministic forecasting, recent works have used diffusion models to produce skillful ensemble…

Machine Learning · Computer Science 2025-04-15 Martin Andrae , Tomas Landelius , Joel Oskarsson , Fredrik Lindsten

Rising penetration levels of (residential) photovoltaic (PV) power as distributed energy resource pose a number of challenges to the electricity infrastructure. High quality, general tools to provide accurate forecasts of power production…

Machine Learning · Computer Science 2020-10-16 Elizaveta Kharlova , Daniel May , Petr Musilek

Reliable forecasts of the power output from variable renewable energy generators like solar photovoltaic systems are important to balancing load on real-time electricity markets and ensuring electricity supply reliability. However, solar PV…

Computational Engineering, Finance, and Science · Computer Science 2025-05-07 Andea Scott , Sindhu Sreedhara , Folasade Ayoola

In this paper, a stochastic model with regime switching is developed for solar photo-voltaic (PV) power in order to provide short-term probabilistic forecasts. The proposed model for solar PV power is physics inspired and explicitly…

Applications · Statistics 2017-09-19 Raksha Ramakrishna , Anna Scaglione , Vijay Vittal

Renewable Energies (RES) penetration is progressing rapidly: in France, the installed capacity of photovoltaic (PV) power rose from 26MW in 2007 to 8GW in 2017 [1]. Power generated by PV plants being highly dependent on variable weather…

Applications · Statistics 2019-10-15 Kevin Bellinguer , Robin Girard , Guillaume Bontron , Georges Kariniotakis

Photovoltaic (PV) power forecasting in edge-enabled grids requires balancing forecasting accuracy, robustness under weather-driven distribution shifts, and strict latency constraints. Existing models work well under normal conditions but…

Machine Learning · Computer Science 2026-03-26 Nan Qiao , Shuning Wang , Sijing Duan , Wenpeng Cui , Yuzhe Chen , Qingchen Yang , Xingyuan Hua , Ju Ren

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…

Machine Learning · Computer Science 2025-05-08 Guang Wu , Yun Wang , Qian Zhou , Ziyang Zhang

Accurate and reliable prediction of Photovoltaic (PV) power output is critical to electricity grid stability and power dispatching capabilities. However, Photovoltaic (PV) power generation is highly volatile and unstable due to different…

Machine Learning · Computer Science 2022-10-04 Sarah Almaghrabi , Mashud Rana , Margaret Hamilton , Mohammad Saiedur Rahaman

The prediction of electrical power in combined cycle power plants is a key challenge in the electrical power and energy systems field. This power output can vary depending on environmental variables, such as temperature, pressure, and…

Signal Processing · Electrical Eng. & Systems 2019-08-06 Jesus L. Lobo , Igor Ballesteros , Izaskun Oregi , Javier Del Ser

Power supply from renewable resources is on a global rise where it is forecasted that renewable generation will surpass other types of generation in a foreseeable future. Increased generation from renewable resources, mainly solar and wind,…

Machine Learning · Statistics 2017-06-28 Mohana Alanazi , Mohsen Mahoor , Amin Khodaei

Energy production using renewable sources exhibits inherent uncertainties due to their intermittent nature. Nevertheless, the unified European energy market promotes the increasing penetration of renewable energy sources (RES) by the…

Machine Learning · Computer Science 2021-07-09 Argyrios Vartholomaios , Stamatis Karlos , Eleftherios Kouloumpris , Grigorios Tsoumakas