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Renewable energy sources, especially wind energy, are to play a larger role in providing electricity to industrial and domestic consumers. This is already the case today for a number of European countries, closely followed by the US and…

Methodology · Statistics 2013-12-24 Pierre Pinson

Accurate prediction of non-dispatchable renewable energy sources is essential for grid stability and price prediction. Regional power supply forecasts are usually indirect through a bottom-up approach of plant-level forecasts, incorporate…

Signal Processing · Electrical Eng. & Systems 2026-02-24 Eloi Lindas , Yannig Goude , Philippe Ciais

The growing penetration of intermittent, renewable generation in US power grids, especially wind and solar generation, results in increased operational uncertainty. In that context, accurate forecasts are critical, especially for wind…

We propose a statistical space-time model for predicting atmospheric wind speed based on deterministic numerical weather predictions and historical measurements. We consider a Gaussian multivariate space-time framework that combines…

Applications · Statistics 2016-10-21 Julie Bessac , Emil Mihai Constantinescu , Mihai Anitescu

Climate change is one of the most concerning issues of this century. Emission from electric power generation is a crucial factor that drives the concern to the next level. Renewable energy sources are widespread and available globally,…

Machine Learning · Computer Science 2020-05-27 Md Amimul Ehsan , Amir Shahirinia , Nian Zhang , Timothy Oladunni

We study a smart grid with wind power and battery storage. Traditionally, day-ahead planning aims to balance demand and wind power, yet actual wind conditions often deviate from forecasts. Short-term flexibility in storage and generation…

Systems and Control · Electrical Eng. & Systems 2022-12-08 Thom S. Badings , Arnd Hartmanns , Nils Jansen , Marnix Suilen

This paper presents a method for probabilistic wind power forecasting that quantifies and integrates uncertainties from weather forecasts and weather-to-power conversion. By addressing both uncertainty sources, the method achieves…

Applications · Statistics 2025-02-18 Gabriel Dantas , Jethro Browell

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

The share of wind energy in total installed power capacity has grown rapidly in recent years around the world. Producing accurate and reliable forecasts of wind power production, together with a quantification of the uncertainty, is…

Applications · Statistics 2017-04-26 Amanda Lenzi , Ingelin Steinsland , Pierre Pinson

The increasing installation rate of wind power poses great challenges to the global power system. In order to ensure the reliable operation of the power system, it is necessary to accurately forecast the wind speed and power of the wind…

Machine Learning · Computer Science 2023-06-21 Yang Yang , Jin Lang , Jian Wu , Yanyan Zhang , Xiang Zhao

The increasing severity of climate change necessitates an urgent transition to renewable energy sources, making the large-scale adoption of wind energy crucial for mitigating environmental impact. However, the inherent uncertainty of wind…

Machine Learning · Computer Science 2024-10-18 Chongyang Wan , Shunbo Lei , Yuan Luo

Wind power forecasting has drawn increasing attention among researchers as the consumption of renewable energy grows. In this paper, we develop a deep learning approach based on encoder-decoder structure. Our model forecasts wind power…

Machine Learning · Computer Science 2021-10-08 Jiangyuan Li , Mohammadreza Armandpour

As an important clean and renewable kind of energy, wind power plays an important role in coping with energy crisis and environmental pollution. However, the volatility and intermittency of wind speed restrict the development of wind power.…

Machine Learning · Computer Science 2024-04-23 Haojian Huang

Aggregated stochastic characteristics of geographically distributed wind generation will provide valuable information for secured and economical system operation in electricity markets. This paper focuses on the uncertainty set prediction…

Systems and Control · Electrical Eng. & Systems 2021-10-08 Xiaopeng Li , Jiang Wu , Zhanbo Xu , Kun Liu , Jun Yu , Xiaohong Guan

Wind power is attracting increasing attention around the world due to its renewable, pollution-free, and other advantages. However, safely and stably integrating the high permeability intermittent power energy into electric power systems…

Machine Learning · Computer Science 2023-05-31 Yang Zhang , Lingbo Liu , Xinyu Xiong , Guanbin Li , Guoli Wang , Liang Lin

To forecast wind power generation in the scale of years to decades, outputs from climate models are often used. However, one major limitation of the data projected by these models is their coarse temporal resolution - usually not finer than…

Applications · Statistics 2023-09-19 Nina Effenberger , Nicole Ludwig , Rachel H. White

The ever-growing use of wind energy makes necessary the optimization of turbine operations through pitch angle controllers and their maintenance with early fault detection. It is crucial to have accurate and robust models imitating the…

Machine Learning · Computer Science 2023-07-28 Alfonso Gijón , Ainhoa Pujana-Goitia , Eugenio Perea , Miguel Molina-Solana , Juan Gómez-Romero

Wind power prediction is of vital importance in wind power utilization. There have been a lot of researches based on the time series of the wind power or speed, but In fact, these time series cannot express the temporal and spatial changes…

Machine Learning · Computer Science 2018-07-19 Ruiguo Yu , Zhiqiang Liu , Xuewei Li , Wenhuan Lu , Mei Yu , Jianrong Wang , Bin Li

World is looking for clean and renewable energy sources that do not pollute the environment, in an attempt to reduce greenhouse gas emissions that contribute to global warming. Wind energy has significant potential to not only reduce…

Machine Learning · Computer Science 2024-01-31 Alif Bin Abdul Qayyum , Xihaier Luo , Nathan M. Urban , Xiaoning Qian , Byung-Jun Yoon

We study short-term prediction of wind speed and wind power (every 10 minutes up to 4 hours ahead). Accurate forecasts for these quantities are crucial to mitigate the negative effects of wind farms' intermittent production on energy…