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In this study, we leverage SCADA data from diverse wind turbines to predict power output, employing advanced time series methods, specifically Functional Neural Networks (FNN) and Long Short-Term Memory (LSTM) networks. A key innovation…

This paper describes a statistical method for short-term forecasting of surface layer wind velocity amplitude relying on the notion of continuous cascades. Inspired by recent empirical findings that suggest the existence of some cascading…

Atmospheric and Oceanic Physics · Physics 2010-04-20 Rachel Baile , Jean-Francois Muzy , Philippe Poggi

Power curves capture the relationship between wind speed and output power for a specific wind turbine. Accurate regression models of this function prove useful in monitoring, maintenance, design, and planning. In practice, however, the…

Machine Learning · Statistics 2021-12-01 L. A. Bull , P. A. Gardner , T. J. Rogers , N. Dervilis , E. J. Cross , E. Papatheou , A. E. Maguire , C. Campos , K. Worden

Quantum Neural Networks (QNNs), a prominent approach in Quantum Machine Learning (QML), are emerging as a powerful alternative to classical machine learning methods. Recent studies have focused on the applicability of QNNs to various tasks,…

Machine Learning · Computer Science 2025-07-01 Batuhan Hangun , Oguz Altun , Onder Eyecioglu

Wind power prediction, especially for turbines, is vital for the operation, controllability, and economy of electricity companies. Hybrid methodologies combining advanced data science with weather forecasting have been incrementally applied…

Machine Learning · Computer Science 2022-04-05 Hao Chen

Power load forecast with Machine Learning is a fairly mature application of artificial intelligence and it is indispensable in operation, control and planning. Data selection techniqies have been hardly used in this application. However,…

This study evaluates the performance of cointegrated vector autoregressive (VAR) models for very short- and short-term wind power forecasting. Preliminary results for a German data set comprising six wind power production time series…

Applications · Statistics 2020-10-16 Florian Ziel , Antonia Arsova

Ahead-of-time forecasting of incident solar-irradiance on a panel is indicative of expected energy yield and is essential for efficient grid distribution and planning. Traditionally, these forecasts are based on meteorological physics…

Computer Vision and Pattern Recognition · Computer Science 2019-01-16 Talha A. Siddiqui , Samarth Bharadwaj , Shivkumar Kalyanaraman

The future energy system will largely depend on volatile renewable energy sources and temperature-dependent loads, which makes the weather a central influencing factor. This article presents a novel approach for simulating weather scenarios…

Systems and Control · Electrical Eng. & Systems 2024-05-31 Jan Peper , David Kröger , Jonathan Kipp , Florian Ziel , Christian Rehtanz

Wind energy significantly contributes to the global shift towards renewable energy, yet operational challenges, such as Leading-Edge Erosion on wind turbine blades, notably reduce energy output. This study introduces an advanced, scalable…

Systems and Control · Electrical Eng. & Systems 2025-06-17 Emil Marcus Buchberg , Kent Vugs Nielsen

Due to the fluctuating nature of the wind and the increasing use of wind energy as a power source, wind power will have an increasing negative influence on the stability of the power grid. In this paper, a model predictive control strategy…

Systems and Control · Electrical Eng. & Systems 2020-07-14 Valentijn van de Scheur , Sjoerd Boersma

Accurate short-term wind speed forecasting is needed for the rapid development and efficient operation of wind energy resources. This is, however, a very challenging problem. Although on the large scale, the wind speed is related to…

Applications · Statistics 2014-12-08 Xinxin Zhu , Kenneth P. Bowman , Marc G. Genton

Each year a growing number of wind farms are being added to power grids to generate electricity. The power curve of a wind turbine, which exhibits the relationship between generated power and wind speed, plays a major role in assessing the…

Neural and Evolutionary Computing · Computer Science 2021-06-10 Farzad Karami , Nasser Kehtarnavaz , Mario Rotea

New methods are proposed for adjusting probabilistic forecasts to ensure coherence with the aggregation constraints inherent in temporal hierarchies. The different approaches nested within this framework include methods that exploit…

Methodology · Statistics 2020-08-18 Jooyoung Jeon , Anastasios Panagiotelis , Fotios Petropoulos

Short Term Load forecasting in this paper uses input data dependent on parameters such as load for current hour and previous two hours, temperature for current hour and previous two hours, wind for current hour and previous two hours, cloud…

Neural and Evolutionary Computing · Computer Science 2009-12-08 Mrs. J. P. Rothe , Dr. A. K. Wadhwani , Dr. Mrs. S. Wadhwani

To unlock access to stronger winds, the offshore wind industry is advancing towards significantly larger and taller wind turbines. This massive upscaling motivates a departure from wind forecasting methods that traditionally focused on a…

Machine Learning · Computer Science 2025-11-18 Feng Ye , Xinxi Zhang , Michael Stein , Ahmed Aziz Ezzat

Photovoltaic and wind power forecasts in power systems with a high share of renewable energy are essential in several applications. These include stable grid operation, profitable power trading, and forward-looking system planning. However,…

Machine Learning · Computer Science 2022-04-04 Stephan Vogt , Jens Schreiber , Bernhard Sick

Authors: Yifan Xu Abstract: Conventional wind power prediction methods often struggle to provide accurate and reliable predictions in the presence of sudden changes in wind speed and power output. To address this challenge, this study…

Machine Learning · Computer Science 2025-02-19 Yifan Xu

Electricity is a volatile power source that requires great planning and resource management for both short and long term. More specifically, in the short-term, accurate instant energy consumption forecasting contributes greatly to improve…

Artificial Intelligence · Computer Science 2022-07-05 Nuno Oliveira , Norberto Sousa , Isabel Praça

The integration of solar power has been increasing as the green energy transition rolls out. The penetration of solar power challenges the grid stability and energy scheduling, due to its intermittent energy generation. Accurate and near…

Machine Learning · Computer Science 2025-09-23 Jinbao Wang , Jun Liu , Shiliang Zhang , Xuehui Ma