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The increasing sophistication of wind turbine design and control generates a need for high-quality data. Therefore, the relatively limited set of measured wind data may be extended with computer-generated surrogate data, e.g. to make…

Signal Processing · Electrical Eng. & Systems 2021-03-02 D. D'Ambrosio , J. Schoukens , T. De Troyer , M. Zivanovic , M. C. Runacres

Accurate production forecasts are essential to continue facilitating the integration of renewable energy sources into the power grid. This paper illustrates how to obtain probabilistic day-ahead forecasts of wind power generation via…

Machine Learning · Computer Science 2026-02-16 Max Bruninx , Diederik van Binsbergen , Timothy Verstraeten , Ann Nowé , Jan Helsen

Multi-type Markov point processes offer a flexible framework for modelling complex multi-type point patterns where it is pertinent to capture both interactions between points as well as large scale trends depending on observed covariates.…

Methodology · Statistics 2025-10-15 Ib Thorsgaard Jensen , Jean-François Coeurjolly , Rasmus Waagepetersen

In this paper we concentrate on an alternative modeling strategy for positive data that exhibit spatial or spatio-temporal dependence. Specifically we propose to consider stochastic processes obtained trough a monotone transformation of…

Methodology · Statistics 2020-04-08 M. Bevilacqua , C. Caamaño , C. Gaetan

The wind energy community is gradually recognizing the significance of atmospheric stability in both power production and structural loading. However, estimating stability requires temperature gradient data which are not commonly measured…

Atmospheric and Oceanic Physics · Physics 2018-04-10 Sukanta Basu

Models based on neural networks and machine learning are seeing a rise in popularity in space physics. In particular, the forecasting of geomagnetic indices with neural network models is becoming a popular field of study. These models are…

Machine Learning · Computer Science 2022-03-15 Brecht Laperre , Jorge Amaya , Giovanni Lapenta

An extreme wind speed estimation method that considers wind hazard climate types is critical for design wind load calculation for building structures affected by mixed climates. However, it is very difficult to obtain wind hazard climate…

Machine Learning · Statistics 2019-08-30 Wei Cui , Teng Ma , Lin Zhao , Yaojun Ge

Wind energy production is very sensitive to instantaneous wind speed fluctuations. Thus rapid variation of wind speed due to changes in the local meteorological conditions can lead to electrical power variations of the order of the nominal…

Applications · Statistics 2008-10-27 Rudy Calif , Richard Emilion , Ted Soubdhan , Ruddy Blonbou

Fast and accurate hourly forecasts of wind speed and power are crucial in quantifying and planning the energy budget in the electric grid. Modeling wind at a high resolution brings forth considerable challenges given its turbulent and…

Applications · Statistics 2021-12-09 Huang Huang , Stefano Castruccio , Marc G. Genton

Renewable sources of energy such as wind power have become a sustainable alternative to fossil fuel-based energy. However, the uncertainty and fluctuation of the wind speed derived from its intermittent nature bring a great threat to the…

Applications · Statistics 2019-07-02 Daniela Castro-Camilo , Raphaël Huser , Håvard Rue

Wind Energy is a useful resource for Renewable energy purpose. Wind speed plays a vital role for wind energy calculation of certain location. So, it is very much necessary to know the wind speed data characteristics. In this paper fourier…

Computational Engineering, Finance, and Science · Computer Science 2014-08-07 Sabyasachi Mukhopadhyay , Debadatta Dash , Asish Mitra , Paritosh Bhattacharya

We introduce a class of semiparametric time series models by assuming a quasi-likelihood approach driven by a latent factor process. More specifically, given the latent process, we only specify the conditional mean and variance of the time…

Methodology · Statistics 2021-04-02 Gisele O. Maia , Wagner Barreto-Souza , Fernando S. Bastos , Hernando Ombao

Accurate prediction of wind power is essential for the grid integration of this intermittent renewable source and aiding grid planners in forecasting available wind capacity. Spatial differences lead to discrepancies in climatological data…

Machine Learning · Computer Science 2024-05-21 Md Saiful Islam Sajol , Md Shazid Islam , A S M Jahid Hasan , Md Saydur Rahman , Jubair Yusuf

In this paper, an offset-free bilinear model predictive control approach for wind turbines is presented. State-of-the-art controllers employ different control loops for pitch angle and generator torque which switch depending on wind…

Systems and Control · Electrical Eng. & Systems 2024-01-30 Arnold Sterle , Aaron Grapentin , Christian A. Hans , Jörg Raisch

Wind energy is a widely distributed, renewable, and environmentally friendly energy source that plays a crucial role in mitigating global warming and addressing energy shortages. Nevertheless, wind power generation is characterized by…

Machine Learning · Computer Science 2023-09-06 Meiyu Jiang , Jun Shen , Xuetao Jiang , Lihui Luo , Rui Zhou , Qingguo Zhou

Semi-Markov processes are Markovian processes in which the firing time of the transitions is modelled by probabilistic distributions over positive reals interpreted as the probability of firing a transition at a certain moment in time. In…

Formal Languages and Automata Theory · Computer Science 2017-12-04 Mathias Ruggaard Pedersen , Nathanaël Fijalkow , Giorgio Bacci , Kim Guldstrand Larsen , Radu Mardare

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately…

Applications · Statistics 2024-11-28 Eva Murphy , Whitney Huang , Julie Bessac , Jiali Wang , Rao Kotamarthi

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

Storm surge, the onshore rush of sea water caused by the high winds and low pressure associated with a hurricane, can compound the effects of inland flooding caused by rainfall, leading to loss of property and loss of life for residents of…

Applications · Statistics 2009-09-29 Brian J. Reich , Montserrat Fuentes

The reliable integration of wind energy into modern-day electricity systems heavily relies on accurate short-term wind forecasts. We propose a spatio-temporal model called AIRU-WRF (short for the AI-powered Rutgers University Weather…

Applications · Statistics 2023-08-31 Feng Ye , Joseph Brodie , Travis Miles , Ahmed Aziz Ezzat