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Real-Time Monitoring and Control for Wind Turbine Systems

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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 (22 March 2022) | Viewed by 18064
Please submit your paper and select the Journal "Energies" and the Special Issue "Real-Time Monitoring and Control for Wind Turbine Systems" via: https://susy.mdpi.com/user/manuscripts/upload?journal=energies. Please contact the journal editor Adele Min ([email protected]) before submitting.

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Special Issue Editors

Prof. Dr. Esmaeil S. Nadimi

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Guest Editor

The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Dk-5230 Odense, Denmark
Interests: Artificial Intelligence; Machine Learning; Data Science; Renewable Energy

Dr. Jürgen Herp

E-Mail Website
Guest Editor

The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Dk-5230 Odense, Denmark
Interests: wind turbines; fault detection; wakes; electric network analysis

Special Issue Information

Dear Colleagues,

While energy is an essential ingredient for human society, sustainable energy generation, in particular, is becoming increasingly important. Wind energy has been shown to be a suitable candidate to handle the task. However, to keep wind power competitive with other sources of energy, the availability, reliability, and lifetime of turbines will all need to be improved. Real-time monitoring will be able to aid operators, as well as business economics, to make educated operation and maintenance decisions online. This Special Issue aims to provide a platform for academic and industrial contributions to disseminate recent results, and emerging and novel research directions within monitoring and control of wind turbines and wind turbine systems. Research topics include but are not limited to condition monitoring techniques, diagnostics, and prognostic techniques for wind turbine systems and components, resilient control and management of wind turbines, including fault tolerance control, and remaining useful lifetime prediction and extension at component and system level.

Contributions to this Special Issue should pay attention to the real-time aspect of the aforementioned topics.

Prof. Dr. Esmaeil S. Nadimi
Dr. Jürgen Herp
Guest Editors

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 turbine
Condition monitoring
Health prognostics
Control
Fault diagnosis
Remaining useful lifetime

Published Papers (5 papers)

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Research

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27 pages, 8160 KiB

Open AccessArticle

A Sensor Data Processing Algorithm for Wind Turbine Hydraulic Pitch System Diagnosis

by Iker Elorza, Iker Arrizabalaga, Aritz Zubizarreta, Héctor Martín-Aguilar, Aron Pujana-Arrese and Carlos Calleja

Energies 2022, 15(1), 33; https://doi.org/10.3390/en15010033 - 21 Dec 2021

Cited by 4 | Viewed by 2971

Abstract

Modern wind turbines depend on their blade pitch systems for start-ups, shutdowns, and power control. Pitch system failures have, therefore, a considerable impact on their operation and integrity. Hydraulic pitch systems are very common, due to their flexibility, maintainability, and cost; hence, the relevance of diagnostic algorithms specifically targeted at them. We propose one such algorithm based on sensor data available to the vast majority of turbine controllers, which we process to fit a model of the hydraulic pitch system to obtain significant indicators of the presence of the critical failure modes. This algorithm differs from state-of-the-art, model-based algorithms in that it does not numerically time-integrate the model equations in parallel with the physical turbine, which is demanding in terms of in situ computation (or, alternatively, data transmission) and is highly susceptible to drift. Our algorithm requires only a modest amount of local sensor data processing, which can be asynchronous and intermittent, to produce negligible quantities of data to be transmitted for remote storage and analysis. In order to validate our algorithm, we use synthetic data generated with state-of-the-art aeroelastic and hydraulic simulation software. The results suggest that a diagnosis of the critical wind turbine hydraulic pitch system failure modes based on our algorithm is viable. Full article

(This article belongs to the Special Issue Real-Time Monitoring and Control for Wind Turbine Systems)

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18 pages, 7367 KiB

Open AccessArticle

Design and Validation of Demanded Power Point Tracking Control Algorithm for MIMO Controllers in Wind Turbines

by Taesu Jeon, Dongmyoung Kim, Yuan Song and Insu Paek

Energies 2021, 14(18), 5818; https://doi.org/10.3390/en14185818 - 14 Sep 2021

Cited by 4 | Viewed by 1686

Abstract

In this study, a demanded power point tracking (DPPT) control algorithm was designed for the application of multiple-input multiple-output (MIMO) modern control algorithms. The proposed DPPT control algorithm has been newly implemented as a multiple reference trajectory method for applying an MIMO control algorithm without mode switches. Dynamic simulations and wind tunnel experiments were performed using a scaled wind turbine to validate the proposed control algorithm. The wind speeds were 4.6 and 7.3 m/s, the average wind speeds corresponding to region 2 and region 3, respectively, with a turbulence intensity of 10%. Both sets of results demonstrated satisfactory performance for tracking the power commands transmitted from the wind farm controller. Furthermore, the proposed control algorithm was compared and validated with a DPPT control algorithm proposed in previous studies, and its improved control performance and validity were confirmed. Full article

(This article belongs to the Special Issue Real-Time Monitoring and Control for Wind Turbine Systems)

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19 pages, 1675 KiB

Open AccessArticle

Modelling Types 1 and 2 Wind Turbines Based on IEC 61400-27-1: Transient Response under Voltage Dips

by Tania García-Sánchez, Irene Muñoz-Benavente, Emilio Gómez-Lázaro and Ana Fernández-Guillamón

Energies 2020, 13(16), 4078; https://doi.org/10.3390/en13164078 - 6 Aug 2020

Cited by 4 | Viewed by 2787

Abstract

Wind power plants depend greatly on weather conditions, thus being considered intermittent, uncertain and non-dispatchable. Due to the massive integration of this energy resource in the recent decades, it is important that transmission and distribution system operators are able to model their electrical behaviour in terms of steady-state power flow, transient dynamic stability, and short-circuit currents. Consequently, in 2015, the International Electrotechnical Commission published Standard IEC 61400-27-1, which includes generic models for wind power generation in order to estimate the electrical characteristics of wind turbines at the connection point. This paper presents, describes and details the models for wind turbine topologies Types 1 and 2 following IEC 61400-27-1 for electrical simulation purposes, including the values for the parameters for the different subsystems. A hardware-in-the-loop combined with a real-time simulator is also used to analyse the response of such wind turbine topologies under voltage dips. The evolution of active and reactive powers is discussed, together with the wind turbine rotor and generator rotational speeds. Full article

(This article belongs to the Special Issue Real-Time Monitoring and Control for Wind Turbine Systems)

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11 pages, 1623 KiB

Open AccessArticle

Estimating the Remaining Power Generation of Wind Turbines—An Exploratory Study for Main Bearing Failures

by Benedikt Wiese, Niels L. Pedersen, Esmaeil S. Nadimi and Jürgen Herp

Energies 2020, 13(13), 3406; https://doi.org/10.3390/en13133406 - 2 Jul 2020

Cited by 6 | Viewed by 2131

Abstract

Condition monitoring for wind turbines is tailored to predict failure and aid in making better operation and maintenance (O&M) decisions. Typically the condition monitoring approaches are concerned with predicting the remaining useful lifetime (RUL) of assets or a component. As the time-based measures can be rendered absolute when changing the operational set-point of a wind turbine, we propose an alternative in a power-based condition monitoring framework for wind turbines, i.e., the remaining power generation (RPG) before a main bearing failure. The proposed model utilizes historic wind turbine data, from both run-to-failure and non run-to-failure turbines. Comprised of a recurrent neural network with gated recurrent units, the model is constructed around a censored and uncensored data-based cost function. We infer a Weibull distribution over the RPG, which gives an operator a measure of how certain any given prediction is. As part of the model evaluation, we present the hyper-parameter selection, as well as modeling error in detail, including an analysis of the driving features. During the application on wind turbine main bearing failures, we achieve prediction in the magnitude of 1 to 2 GWh before the failure. When converting to RUL this corresponds to predicting the failure, on average, 81 days beforehand, which is comparable to the state-of-the-art’s 94 days predictive horizon in a similar feature space. Full article

(This article belongs to the Special Issue Real-Time Monitoring and Control for Wind Turbine Systems)

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Review

Jump to: Research

30 pages, 38998 KiB

Open AccessReview

Review on Dynamics of Offshore Floating Wind Turbine Platforms

by Srikanth Bashetty and Selahattin Ozcelik

Energies 2021, 14(19), 6026; https://doi.org/10.3390/en14196026 - 22 Sep 2021

Cited by 29 | Viewed by 7385

Abstract

This paper presents a literature review of the dynamics of offshore floating wind turbine platforms. When moving further offshore, there is an increase in the capacity of wind power. Generating power from renewable resources is enhanced through the extraction of wind energy from an offshore deep-water wind resource. Mounting the turbine on a platform that is not stable brings another difficulty to wind turbine modeling. There is a need to introduce platforms that are more effective to capture this energy, because of the complex dynamics and control of these platforms. This paper highlights the historical developments and progresses in the design of different types of offshore floating wind turbine platforms needed for harvesting the energy from offshore winds. The relative advantages and disadvantages of the platform types with the design challenges are discussed. The major types of floating platforms included in this study are tension leg platform (TLP) type, spar type, and semisubmersible type. This study reviews the previous work on the dynamics of the floating platforms for a single turbine and multiple turbines under various operating environmental conditions. The numerical methods to analyze the aerodynamics of the wind turbine and hydrodynamics of floating platforms are discussed in this paper. This paper also investigates the performance of analytical wake loss models of Jensen, Larsen, and Frandsen that can provide guidelines for using these wake models in future applications. There are still a lot of challenges that need to be addressed to study the accurate behavior of floating platforms operating under combined wind–wave environmental conditions. With the current technological advancements, the offshore floating multi-turbine platform can be a potential solution to harness the abundant offshore wind resource. Based on this literature review, recommendations for future work are suggested. Full article

(This article belongs to the Special Issue Real-Time Monitoring and Control for Wind Turbine Systems)

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