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Wind turbines located in wind farms are operated to maximize only their own power production. Individual operation results in wake losses that reduce farm energy. In this study, we operate a wind turbine array collectively to maximize total…

This paper presents a new active power control algorithm designed to maximize the power reserve of the individual turbines in a farm, in order to improve the tracking accuracy of a power reference signal. The control architecture is based…

Fluid Dynamics · Physics 2023-07-11 Simone Tamaro , Carlo L. Bottasso

Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets…

Applications · Statistics 2017-10-03 Jaehong Jeong , Stefano Castruccio , Paola Crippa , Marc G. Genton

Understanding wind turbine wake mixing and recovery is critical for improving the power generation and structural stability of downwind turbines in a wind farm. In the field, where incoming flow and turbine operation are constantly…

Fluid Dynamics · Physics 2019-05-09 Aliza Abraham , Jiarong Hong

Green manufacturing has become a strategic priority for many firms seeking to address sustainability and social responsibility, while improving production efficiency and profitability. However, integrating green technologies and renewable…

Optimization and Control · Mathematics 2026-04-28 Xin Zhou , Zhengsong Lu , Bo Zeng , Na Geng

The rapid expansion of wind and solar energy leads to an increasing volatility in the electricity generation. Previous studies have shown that storage devices provide an opportunity to balance fluctuations in the power grid. An economical…

Optimization and Control · Mathematics 2017-11-06 Lars Siemer , Wided Medjroubi

This paper presents a new generation of fast-running physics-based models to predict the wake of a semi-infinite wind farm, extending infinitely in the lateral direction but with finite size in the streamwise direction. The assumption of a…

The increasing integration of large-scale volatile and uncertain wind generation has brought great challenges to power system operations. In this paper, a risk-based admissibility assessment approach is proposed to quantitatively evaluate…

Optimization and Control · Mathematics 2015-10-29 Cheng Wang , Feng Liu , Jianhui Wang , Wei Wei , Shengwei Mei

The growth of wind generation capacities in the past decades has shown that wind energy can contribute to the energy transition in many parts of the world. Being highly variable and complex to model, the quantification of the…

Signal Processing · Electrical Eng. & Systems 2022-07-19 Federico Amato , Fabian Guignard , Alina Walch , Nahid Mohajeri , Jean-Louis Scartezzini , Mikhail Kanevski

The penetration of distributed renewable energy (DRE) greatly raises the risk of distribution network operation such as peak shaving and voltage stability. Battery energy storage (BES) has been widely accepted as the most potential…

Optimization and Control · Mathematics 2017-07-03 Chenghui Tang , Jian Xu , Yuanzhang Sun , Siyang Liao , Deping Ke , Xiong Li

This paper addresses the energy management of a grid-connected renewable generation plant coupled with a battery energy storage device in the capacity firming market, designed to promote renewable power generation facilities in small…

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

Distributionally robust optimization (DRO) is an effective approach for data-driven decision-making in the presence of uncertainty. Geometric uncertainty due to sampling or localized perturbations of data points is captured by Wasserstein…

Machine Learning · Statistics 2023-11-10 Sloan Nietert , Ziv Goldfeld , Soroosh Shafiee

Wind farms are a crucial driver toward the generation of ecological and renewable energy. Due to their rapid increase in capacity, contemporary wind farms need to adhere to strict constraints on power output to ensure stability of the…

Wind generation is traditionally treated as a non-dispatchable resource and is fully absorbed unless there are security issues. To tackle the operational reliability issues caused by the volatile and non-dispatchable wind generation, many…

Optimization and Control · Mathematics 2015-11-13 Cheng Wang , Feng Liu , Feng Qiu , Wei Wei , Jianhui Wang , Shengwei Mei

Wasserstein distributionally robust optimization (DRO) has recently achieved empirical success for various applications in operations research and machine learning, owing partly to its regularization effect. Although connection between…

Machine Learning · Computer Science 2020-11-02 Rui Gao , Xi Chen , Anton J. Kleywegt

Wind power is expected to play a crucial role in future net-zero energy systems, but wind power simulations to support deployment strategies vary drastically in their results, hindering reliable design decisions. Therefore, we present a…

Motivated by the inadequacy of conventional control methods for power networks with a large share of renewable generation, in this paper we study the (stochastic) passivity property of wind turbines based on the Doubly Fed Induction…

Systems and Control · Electrical Eng. & Systems 2021-03-05 Amirreza Silani , Michele Cucuzzella , Jacquelien M. A. Scherpen , Mohammad Javad Yazdanpanah

We propose two distributionally robust optimization (DRO) models for a mobile facility (MF) fleet sizing, routing, and scheduling problem (MFRSP) with time-dependent and random demand, as well as methodologies for solving these models.…

Optimization and Control · Mathematics 2022-02-23 Karmel S. Shehadeh

Wasserstein distributionally robust optimization (DRO) aims to find robust and generalizable solutions by hedging against data perturbations in Wasserstein distance. Despite its recent empirical success in operations research and machine…

Machine Learning · Computer Science 2022-05-03 Rui Gao