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Energies
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Distributed Control of Wind Farm System
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Distributed Control of Wind Farm System

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A3: Wind, Wave and Tidal Energy".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 7216

Special Issue Editor

Dr. Thai-Thanh Nguyen

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Clarkson University, Potsdam, NY 13699, USA
Interests: wind farm system; distributed control; microgrids; power converter control; model predictive control; power system analysis

Special Issue Information

Dear Colleagues,

The mature wind power technologies lead to rapid growth in utility-scale wind power generations. Since large-scale wind farm projects range from hundreds up to thousands of multi-MW wind turbines, traditional wind farm control implemented in a supervisory computer will require significant computing power to produce setpoints for every wind turbine. Instead of using a centralized controller for the entire wind farm, modern wind farms can be managed in a distributed manner like smart grids, in which the desired global behavior of the wind farm system can be achieved by the coordination of all turbines. Distributed control of wind farms has shown great potential as it enhances system resilience and reduces the computational burden. The goal of this Special Issue is to promote new research concepts and achievements in the distributed control of wind farms.

Topics of interest include, but are not limited to:

  • Distributed control and operation of wind farms
  • Machine learning for distributed wind farm control
  • Model-based predictive control of wind farms
  • Advanced control for improving cybersecurity resilience in wind farms
  • Real-time control strategies of wind farms
  • Real-time modelling and analysis of distributed wind farm control
  • Dynamic modelling of wind turbines and large-scale wind farms

Dr. Thai-Thanh Nguyen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wind farm control
  • distributed control
  • real-time control
  • offshore wind farms

Published Papers (2 papers)

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Research

16 pages, 8653 KiB  
Article
Design, Implementation, and Evaluation of an Output Prediction Model of the 10 MW Floating Offshore Wind Turbine for a Digital Twin
by Changhyun Kim, Minh-Chau Dinh, Hae-Jin Sung, Kyong-Hwan Kim, Jeong-Ho Choi, Lukas Graber, In-Keun Yu and Minwon Park
Energies 2022, 15(17), 6329; https://0-doi-org.brum.beds.ac.uk/10.3390/en15176329 - 30 Aug 2022
Cited by 11 | Viewed by 2332
Abstract
Predicting the output power of wind generators is essential to improve grid flexibility, which is vulnerable to power supply variability and uncertainty. Digital twins can help predict the output of a wind turbine using a variety of environmental data generated by real-world systems. [...] Read more.
Predicting the output power of wind generators is essential to improve grid flexibility, which is vulnerable to power supply variability and uncertainty. Digital twins can help predict the output of a wind turbine using a variety of environmental data generated by real-world systems. This paper dealt with the development of a physics-based output prediction model (P-bOPM) for a 10 MW floating offshore wind turbine (FOWT) for a digital twin. The wind power generator dealt with in this paper was modeled considering the NREL 5 MW standard wind turbine with a semi-submersible structure. A P-bOPM of a 10 MW FOWT for a digital twin was designed and simulated using ANSYS Twin Builder. By connecting the P-bOPM developed for the digital twin implementation with an external sensor through TCP/IP communication, it was possible to calculate the output of the wind turbine using real-time field data. As a result of evaluating the P-bOPM for various marine environments, it showed good accuracy. The digital twin equipped with the P-bOPM, which accurately reflects the variability of the offshore wind farm and can predict the output in real time, will be a great help in improving the flexibility of the power system in the future. Full article
(This article belongs to the Special Issue Distributed Control of Wind Farm System)
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18 pages, 16287 KiB  
Article
Simplified Floating Wind Turbine for Real-Time Simulation of Large-Scale Floating Offshore Wind Farms
by Thanh-Dam Pham, Minh-Chau Dinh, Hak-Man Kim and Thai-Thanh Nguyen
Energies 2021, 14(15), 4571; https://0-doi-org.brum.beds.ac.uk/10.3390/en14154571 - 28 Jul 2021
Cited by 10 | Viewed by 4016
Abstract
Floating offshore wind has received more attention due to its advantage of access to incredible wind resources over deep waters. Modeling of floating offshore wind farms is essential to evaluate their impacts on the electric power system, in which the floating offshore wind [...] Read more.
Floating offshore wind has received more attention due to its advantage of access to incredible wind resources over deep waters. Modeling of floating offshore wind farms is essential to evaluate their impacts on the electric power system, in which the floating offshore wind turbine should be adequately modeled for real-time simulation studies. This study proposes a simplified floating offshore wind turbine model, which is applicable for the real-time simulation of large-scale floating offshore wind farms. Two types of floating wind turbines are evaluated in this paper: the semi-submersible and spar-buoy floating wind turbines. The effectiveness of the simplified turbine models is shown by a comparison study with the detailed FAST (Fatigue, Aerodynamics, Structures, and Turbulence) floating turbine model. A large-scale floating offshore wind farm including eighty units of simplified turbines is tested in parallel simulation and real-time software (OPAL-RT). The wake effects among turbines and the effect of wind speeds on ocean waves are also taken into account in the modeling of offshore wind farms. Validation results show sufficient accuracy of the simplified models compared to detailed FAST models. The real-time results of offshore wind farms show the feasibility of the proposed turbine models for the real-time model of large-scale offshore wind farms. Full article
(This article belongs to the Special Issue Distributed Control of Wind Farm System)
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