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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 (31 May 2024) | Viewed by 26132

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Special Issue Editors

Prof. Dr. Guanghua He

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Guest Editor

School of Ocean Engineering, Harbin Institute of Technology, Weihai 264209, China
Interests: computational fluid dynamics (CFD); motion response and hydrodynamic analysis of ship and ocean engineering structures; tidal current and wind wave power generation technology; CIP technology; seakeeping analysis; fluid-structure Interaction (FSI)

Prof. Dr. Liang Sun

E-Mail Website
Guest Editor

School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430062, China
Interests: wind–wave power; fluid–structure interaction; hydrodynamic; finite element anal-ysis; costal engineering
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Yan Bao

E-Mail Website
Guest Editor

State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: computational fluid dynamics; multiphase flow; vortex-induced vibration suppression; fluid–structure interaction; wake control

Special Issue Information

Dear Colleagues,

Wind energy exploitation is suitable for large-scale development due to its abundant resources with less visual and sound pollution and excellent characteristics of high operating efficiency, and with no land-use restrictions. On the other hand, wave energy is widely exploited as a result of its higher energy density than other marine renewable energy sources. Wind energy, wave energy, and especially wind–wave combinations are becoming more promising for the development and utilization of marine renewable energy for the future. Therefore, wind and wave energy resource assessment, wind–wave utilization technology, optimal design of energy conversion devices, large-scale power generation, and grid-connected technology are practically important for the efficient assessment and utilization of wind and wave renewable resources.

This Special Issue aims to present and disseminate the most recent advances in the concept, application, control, optimization, smart grid technology, evaluation, and combined utilization of wind and wave energy.

Topics of interest for publication include, but are not limited to:

Wind and wave energy resource assessment and combined utilization;
Multi-energy integration and innovation;
Opportunities and challenges for the development of wind and wave power generation;
Control technologies of wind and wave energy;
Smart optimization algorithms for wind and wave energy;
Experiments of floating offshore wind turbines or WECs;
Smart grid;
Technological innovation of offshore wind power engineering;
Offshore wind power operation and maintenance technologies;
Energy conversion of wave energy.

Prof. Dr. Guanghua He
Prof. Dr. Liang Sun
Prof. Dr. Yan Bao
Guest Editors

Manuscript Submission Information

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Keywords

wind energy
wave energy
wind field observation
resource assessment
wave-wind energy
combined exploitation
numerical simulation
experiment
Site test
optimization
smart grid

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Published Papers (10 papers)

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Research

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19 pages, 13896 KiB

Open AccessArticle

Numerical Study on Auxiliary Propulsion Performance of Foldable Three-Element Wingsail Utilizing Wind Energy

by Yongxu Jiang, Chenze Cao, Ting Cui, Hao Yang and Zhengjun Tian

Energies 2024, 17(15), 3833; https://doi.org/10.3390/en17153833 - 3 Aug 2024

Viewed by 1140

Abstract

Sail-assisted propulsion is an important energy-saving technology in the shipping industry, and the development of foldable wingsails has recently become a hot topic. This type of sail is usually composed of multiple elements, and its performance at different folding configurations is very sensitive to changes in incoming airflow, which result in practical operational challenges. Therefore, original and optimized three-element wingsails (bare and concave) are modeled and simulated using the unsteady RANS method with the k-ω SST turbulence model. Next, certain key design and structural parameters (such as angle of attack, apparent wind angle, and camber) are employed to characterize the auxiliary propulsion performance, and the differences are explained in combination with the flow field details. The results show that, in the unfolded state, the aerodynamic performance of the concave wingsail is better than that of the bare wingsail, exhibiting higher lift coefficients, lower drag coefficients, and a more stable surface flow. In the fully folded state, wherein both the nose and flap are rotated, the thrust performance of the concave wingsail remains superior. Specifically, at an angle of attack of 8 degrees, the thrust coefficient of the concave wingsail is approximately 23.5% higher than that of the bare wingsail, indicating improved wind energy utilization. The research results are of great significance for engineering applications and subsequent optimization design. Full article

(This article belongs to the Special Issue Wind and Wave Energy Resource Assessment and Combined Utilization)

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13 pages, 3032 KiB

Open AccessArticle

Predication of Ocean Wave Height for Ocean Wave Energy Conversion System

by Yingjie Cui, Fei Zhang and Zhongxian Chen

Energies 2023, 16(9), 3841; https://doi.org/10.3390/en16093841 - 29 Apr 2023

Cited by 5 | Viewed by 1748

Abstract

Ocean wave height is one of the critical factors to decide the efficiency of the ocean wave energy conversion system. Usually, only when the resonate occurs between the ocean wave height (ocean wave speed in the vertical direction) and ocean wave energy conversion system, can the conversion efficiency from ocean wave energy into electric energy be maximized. Therefore, this paper proposes two predication methods to predict the future ocean wave height in 1.5–2.5 s. Firstly, the data fitting of real ocean wave height is achieved by the polynomial method, which is beneficial to the predication of ocean wave height. Secondly, the models of the moving average (MA) predication method and auto regressive (AR) predication method are presented by the time series analysis process. Lastly, after the predication of ocean wave height by the MA method and AR method, and compared with the data fitting result of real ocean wave height, it can be found that the AR method is more accurate for the predication of ocean wave height. In addition, the predication results also indicated that the error between the predication value and true value in the future 2.5 s is considered acceptable, which provides enough time to optimize the operation process of the ocean wave energy conversion system by a suitable control method. Full article

(This article belongs to the Special Issue Wind and Wave Energy Resource Assessment and Combined Utilization)

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16 pages, 3392 KiB

Open AccessArticle

Deep Learning for Modeling an Offshore Hybrid Wind–Wave Energy System

by Mahsa Dehghan Manshadi, Milad Mousavi, M. Soltani, Amir Mosavi and Levente Kovacs

Energies 2022, 15(24), 9484; https://doi.org/10.3390/en15249484 - 14 Dec 2022

Cited by 10 | Viewed by 3539

Abstract

The combination of an offshore wind turbine and a wave energy converter on an integrated platform is an economical solution for the electrical power demand in coastal countries. Due to the expensive installation cost, a prediction should be used to investigate whether the location is suitable for these sites. For this purpose, this research presents the feasibility of installing a combined hybrid site in the desired coastal location by predicting the net produced power due to the environmental parameters. For combining these two systems, an optimized array includes ten turbines and ten wave energy converters. The mathematical equations of the net force on the two introduced systems and the produced power of the wind turbines are proposed. The turbines’ maximum forces are 4 kN, and for the wave energy converters are 6 kN, respectively. Furthermore, the comparison is conducted in order to find the optimum system. The comparison shows that the most effective system of desired environmental condition is introduced. A number of machine learning and deep learning methods are used to predict key parameters after collecting the dataset. Moreover, a comparative analysis is conducted to find a suitable model. The models’ performance has been well studied through generating the confusion matrix and the receiver operating characteristic (ROC) curve of the hybrid site. The deep learning model outperformed other models, with an approximate accuracy of 0.96. Full article

(This article belongs to the Special Issue Wind and Wave Energy Resource Assessment and Combined Utilization)

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16 pages, 7980 KiB

Open AccessArticle

Numerical Study on a Cylinder Vibrator in the Hydrodynamics of a Wind–Wave Combined Power Generation System under Different Mass Ratios

by Hongyuan Sun, Jiazheng Wang, Haihua Lin, Guanghua He, Zhigang Zhang, Bo Gao and Bo Jiao

Energies 2022, 15(24), 9265; https://doi.org/10.3390/en15249265 - 7 Dec 2022

Cited by 3 | Viewed by 1671

Abstract

A hydrodynamic wind–wave combined power generation system is a new type of energy device that uses wind and ocean current energy to generate electricity. In this paper, the hydrodynamics of a wind–wave combined power generation system was simulated in Fluent. The fluid–structure coupling simulation of the vortex vibration of the cylindrical oscillator was realized using UDF and dynamic mesh technology. The Vortex-Induced Vibration (VIV) characteristics of the cylindrical oscillator were analyzed, and the reliability of the numerical simulation method was verified by comparing the amplitude and trajectory of the eddy-excited vibration with the classic experiments of Jauvtis and Williamson. The VIV characteristics of cylindrical oscillators with different mass ratios were studied in terms of vibration response, motion trajectory, and the streamwise equilibrium position. The effect of the mass ratio on the hydrodynamics of a wind–wave combined power generation system was simulated using spring damping, achieving the goal of carrying out preliminary research work simulating the wind–wave combined power generation device. Some useful conclusions were obtained through calculation, which provided data support for the corresponding platform device. This study shows that in cylindrical oscillators with different mass ratios, the overall trend at the same reduced velocity is that the larger the mass ratio, the smaller the crossflow amplitude. The cylindrical oscillators with mass ratios of one and two appear in the upper branch, while cylindrical oscillators with mass ratios of three and four do not appear, and with the increase in the mass ratio, the frequency ratio in the lower branch tends toward one. At the same reduced velocity, the lower the mass ratio, the larger the corresponding downstream equilibrium position, and the higher the energy acquisition efficiency. Full article

(This article belongs to the Special Issue Wind and Wave Energy Resource Assessment and Combined Utilization)

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16 pages, 5494 KiB

Open AccessArticle

Modeling, Experimental Analysis, and Optimized Control of an Ocean Wave Energy Conversion System in the Yellow Sea near Lianyungang Port

by Zhongxian Chen, Xu Li, Yingjie Cui and Liwei Hong

Energies 2022, 15(23), 8788; https://doi.org/10.3390/en15238788 - 22 Nov 2022

Cited by 3 | Viewed by 1673

Abstract

In this paper, an ocean wave energy conversion system (OWECS) is modeled and experimented in the Yellow Sea near Lianyungang port, and an optimized control method based on the sliding mode control is proposed to improve the efficiency of OWECS. Firstly, a motion model of a double-buoy OWECS is presented using a complex representation method, and the analysis results indicate that the efficiency of converting ocean wave energy into the outer buoy’s mechanical power is highest in a suitable ocean wave period. Secondly, a double-buoy OWECS is constructed and experimented in the Yellow Sea near Lianyungang port, which verified the correctness of the above analysis results. Lastly, in order to further improve the efficiency of the double-buoy OWECS, a sliding mode control method based on a linear generator is proposed to realize the phase synchronization between the outer buoy and ocean waves, and the simulation results may be beneficial for the next ocean test of the double-buoy OWECS. Full article

(This article belongs to the Special Issue Wind and Wave Energy Resource Assessment and Combined Utilization)

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16 pages, 6917 KiB

Open AccessArticle

Research on Size Optimization of Wave Energy Converters Based on a Floating Wind-Wave Combined Power Generation Platform

by Xianxiong Zhang, Bin Li, Zhenwei Hu, Jiang Deng, Panpan Xiao and Mingsheng Chen

Energies 2022, 15(22), 8681; https://doi.org/10.3390/en15228681 - 18 Nov 2022

Cited by 24 | Viewed by 2596

Abstract

Wind energy and wave energy often co-exist in offshore waters, which have the potential and development advantages of combined utilization. Therefore, the combined utilization of wind and waves has become a research hotspot in the field of marine renewable energy. Against this background, this study analyses a novel integrated wind-wave power generation platform combining a semi-submersible floating wind turbine foundation and a point absorber wave energy converter (WEC), with emphasis on the size optimization of the WEC. Based on the engineering toolset software ANSYS-AQWA, numerical simulation is carried out to study the influence of different point absorber sizes on the hydrodynamic characteristics and wave energy conversion efficiency of the integrated power generation platform. The well-proven CFD software STAR CCM+ is used to modify the heaving viscosity damping of the point absorber to study the influence of fluid viscosity on the response of the point absorber. Based on this, the multi-body coupled time-domain model of the integrated power generation platform is established, and the performance of the integrated power generation platform is evaluated from two aspects, including the motion characteristics and wave energy conversion efficiency, which provides an important reference for the design and optimization of the floating wind-wave power generation platform. Full article

(This article belongs to the Special Issue Wind and Wave Energy Resource Assessment and Combined Utilization)

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17 pages, 1286 KiB

Open AccessArticle

Numerical Investigation of Multi-Floater Truss-Type Wave Energy Convertor Platform

by Ruijia Jin, Jiawei Wang, Hanbao Chen, Baolei Geng and Zhen Liu

Energies 2022, 15(15), 5675; https://doi.org/10.3390/en15155675 - 4 Aug 2022

Cited by 3 | Viewed by 1826

Abstract

In order to solve the hydrodynamic characteristics of the multi-floater truss-type wave energy convertor (WEC) platform, the mathematical model is established by using the high-order boundary element method based on potential flow theory, in which the floater and the platform are connected by the floating arm based on the lever principle. The mathematical model is applied to study the heave motion response of each floater of the multi-floater truss-type WEC platform, and the effects of the floater number and the floater arrangement on the motion responses of floaters, as well as the power generation of the WEC platform are analyzed. The effect of the hydraulic cylinder on the floater is simulated by linear damping, and then, the work of the hydraulic cylinder is used to generate electricity, so as to achieve the purpose of simulating the multi-floater WEC power generation device. Some useful conclusions are obtained through calculation, which can provide data support for the corresponding platform. Full article

(This article belongs to the Special Issue Wind and Wave Energy Resource Assessment and Combined Utilization)

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20 pages, 1426 KiB

Open AccessArticle

Machine Learning Algorithms for Vertical Wind Speed Data Extrapolation: Comparison and Performance Using Mesoscale and Measured Site Data

by Luis Baquero, Herena Torio and Paul Leask

Energies 2022, 15(15), 5518; https://doi.org/10.3390/en15155518 - 29 Jul 2022

Cited by 6 | Viewed by 2485

Abstract

Machine learning (ML) could be used to overcome one of the largest sources of uncertainty in wind resource assessment: to accurately predict the wind speed (WS) at the wind turbine hub height. Therefore, this research defined and evaluated the performance of seven ML supervised algorithms (regressions, decision tree, support vector machines, and an ensemble method) trained with meteorological mast data (temperature, humidity, wind direction, and wind speeds at 50 and 75 m), and mesoscale data below 80 m (from the New European Wind Atlas) to predict the WS at the height of 102 m. The results were compared with the conventional method used in wind energy assessments to vertically extrapolate the WS, the power law. It was proved that the ML models overcome the conventional method in terms of the prediction errors and the coefficient of determination. The main advantage of ML over the power-law was that ML performed the task using either only mesoscale data (described in scenario A), only data from the measurement mast (described in scenario B) or combining these two data sets (described in scenario C). The best ML models were the ensemble method in scenario A with an

R^{2}

of 0.63, the linear regression in scenario B with an

R^{2}

of 0.97, and the Ridge regressor in scenario C with an

R^{2}

of 0.97. Full article

(This article belongs to the Special Issue Wind and Wave Energy Resource Assessment and Combined Utilization)

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Review

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24 pages, 12874 KiB

Open AccessReview

A Review of Wind Clustering Methods Based on the Wind Speed and Trend in Malaysia

by Amar Azhar and Huzaifa Hashim

Energies 2023, 16(8), 3388; https://doi.org/10.3390/en16083388 - 12 Apr 2023

Cited by 3 | Viewed by 2547

Abstract

Wind mapping has played a significant role in the selection of wind harvesting areas and engineering objectives. This research aims to find the best clustering method to cluster the wind speed of Malaysia. The wind speed trend of Malaysia is affected by two major monsoons: the southwest and the northeast monsoon. The research found multiple, worldwide studies using various methods to accomplish the clustering of wind speed in multiple wind conditions. The methods used are the k-means method, Ward’s method, hierarchical clustering, trend-based time series data clustering, and Anderberg hierarchical clustering. The clustering methods commonly used by the researchers are the k-means method and Ward’s method. The k-means method has been a popular choice in the clustering of wind speed. Each research study has its objectives and variables to deal with. Consequently, the variables play a significant role in deciding which method is to be used in the studies. The k-means method shortened the clustering time. However, the calculation’s relative error was higher than that of Ward’s method. Therefore, in terms of accuracy, Ward’s method was chosen because of its acceptance of multiple variables, its accuracy, and its acceptable calculation time. The method used in the research plays an important role in the result obtained. There are various aspects that the researcher needs to focus on to decide the best method to be used in predicting the result. Full article

(This article belongs to the Special Issue Wind and Wave Energy Resource Assessment and Combined Utilization)

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33 pages, 4640 KiB

Open AccessReview

Site Selection of Combined Offshore Wind and Wave Energy Farms: A Systematic Review

by Shabnam Hosseinzadeh, Amir Etemad-Shahidi and Rodney A. Stewart

Energies 2023, 16(4), 2074; https://doi.org/10.3390/en16042074 - 20 Feb 2023

Cited by 22 | Viewed by 5552

Abstract

Growing energy demand worldwide and onshore limitations have increased interest in offshore renewable energy exploitation. A combination of offshore renewable energy resources such as wind and wave energy can produce stable power output at a lower cost compared to a single energy source. Consequently, identifying the best locations for constructing combined offshore renewable energy farms is crucial. This paper investigates the technical, economic, social, and environmental aspects of Combined Offshore Wind and Wave Energy Farm (COWWEF) site selection. Past literature was evaluated using a systematic review method to synthesize, criticize, and categorize study regions, dataset characteristics, constraints, evaluation criteria, and methods used for the site selection procedure. The results showed that most studied regions belong to European countries, and numerical model outputs were mainly used in the literature as met-ocean data due to the limited coverage and low spatiotemporal resolution of buoy and satellite observations. Environmental and marine usage are the main constraints in the site selection process. Among all constraints, shipping lanes, marine protected areas, and military exercise areas were predominately considered to be excluded from the potential sites for COWWEF development. The technical viability and economic feasibility of project deployment are emphasized in the literature. Resource assessment and distance to infrastructures were mostly evaluated among techno-economic criteria. Wind and wave energy power are the most important criteria for evaluating feasibility, followed by water depth, indicators of variability and correlation of the energy resources, and distance to the nearest port. Multi-Criteria Decision-Making (MCDM) methods and resource-based analysis were the most-used evaluation frameworks. Resource-based studies mainly used met-ocean datasets to determine site technical and operational performance (i.e., resource availability, variability, and correlation), while MCDM methods were applied when a broader set of criteria were evaluated. Based on the conducted review, it was found that the literature lacks evaluation of seabed conditions (seabed type and slope) and consideration of uncertainty involved in the COWWEF site selection process. In addition, the market analysis and evaluation of environmental impacts of COWWEF development, as well as impacts of climate change on combined exploitation of offshore wind and wave energy, have rarely been investigated and need to be considered in future studies. Finally, by providing a comprehensive repository of synthesized and categorized information and research gaps, this study represents a road map for decision-makers to determine the most suitable locations for COWWEF developments. Full article

(This article belongs to the Special Issue Wind and Wave Energy Resource Assessment and Combined Utilization)

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