[HTML][HTML] Using artificial intelligence to improve real-time decision-making for high-impact weather

A McGovern, KL Elmore, DJ Gagne… - Bulletin of the …, 2017 - journals.ametsoc.org
Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather
in: Bulletin of the American Meteorological Society Volume 98 Issue 10 (2017) Jump to …

Unified theory for stochastic modelling of hydroclimatic processes: Preserving marginal distributions, correlation structures, and intermittency

SM Papalexiou - Advances in water resources, 2018 - Elsevier
Hydroclimatic processes come in all “shapes and sizes”. They are characterized by different
spatiotemporal correlation structures and probability distributions that can be continuous …

[HTML][HTML] Spatio-temporal short-term wind forecast: A calibrated regime-switching method

AA Ezzat, M Jun, Y Ding - The annals of applied statistics, 2019 - ncbi.nlm.nih.gov
Accurate short-term forecasts are indispensable for the integration of wind energy in power
grids. On a wind farm, local wind conditions exhibit sizeable variations at a fine temporal …

Improved very short‐term spatio‐temporal wind forecasting using atmospheric regimes

J Browell, DR Drew, K Philippopoulos - Wind Energy, 2018 - Wiley Online Library
We present a regime‐switching vector autoregressive method for very short‐term wind
speed forecasting at multiple locations with regimes based on large‐scale meteorological …

A spliced gamma-generalized Pareto model for short-term extreme wind speed probabilistic forecasting

D Castro-Camilo, R Huser, H Rue - Journal of Agricultural, Biological and …, 2019 - Springer
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 …

Sparse vector Markov switching autoregressive models. Application to multivariate time series of temperature

V Monbet, P Ailliot - Computational Statistics & Data Analysis, 2017 - Elsevier
Multivariate time series are of interest in many fields including economics and environment.
The dynamical processes occurring in these domains often exhibit a mixture of different …

Towards a sustainable power grid: Stochastic hierarchical planning for high renewable integration

S Atakan, H Gangammanavar, S Sen - European Journal of Operational …, 2022 - Elsevier
Driven by ambitious renewable portfolio standards, large-scale inclusion of variable energy
resources (such as wind and solar) are expected to introduce unprecedented levels of …

A Non‐Gaussian Spatio‐Temporal Model for Daily Wind Speeds Based on a Multi‐Variate Skew‐t Distribution

F Tagle, S Castruccio, P Crippa… - Journal of Time Series …, 2019 - Wiley Online Library
Facing increasing domestic energy consumption from population growth and
industrialization, Saudi Arabia is aiming to reduce its reliance on fossil fuels and to broaden …

Coherence for multivariate random fields

W Kleiber - Statistica Sinica, 2017 - JSTOR
Multivariate spatial field data are increasingly common and their modeling typically relies on
building cross-covariance functions to describe cross-process relationships. An alternative …

Stochastic weather generator for the design and reliability evaluation of desalination systems with Renewable Energy Sources

P Ailliot, M Boutigny, E Koutroulis, A Malisovas… - Renewable Energy, 2020 - Elsevier
Abstract The operation of Renewable Energy Sources (RES) systems is highly affected by
the continuously changing meteorological conditions and the design of a RES system has to …