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A Detail Investigation on the Antarctic wind energy

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中国海洋工程:英文版 2023年第4期37卷 698-708页

作者： WANG Kai-shan WU Di ZHENG Chong-wei TAO Gui-sheng LI Wei GAO Yuan-bo YU Yue WU Kai Dalian Naval Academy Dalian 116018China Marine Resources and Environment Research Group on the Maritime Silk Road Dalian 116018China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082China

The scientific development of wind energy based on local conditions is conducive to the urgent energy demand and environmental protection of Antarctic region.In this study,the ERA5 reanalysis data are used to evaluate the wind energy resources in the Antarctic region.A series of key indicators,such as wind power density,effective wind speed occurrence,energy level occurrence and stability,are comprehensively considered by using climate statistical analysis methods to analyze the temporal and spatial distribution characteristics of Antarctic wind energy resources.The results show that the Antarctic region contains abundant wind energy resources,which benefits the construction of scientific research stations.The superior areas are the Southern Ocean and the coast of the East Antarctica,followed by the Transantarctic Mountains,the coast of the Bellingshausen Sea and Amundsen Sea.These areas have advantages in terms of wind power density(500-2500 W/m2),effective wind speed occurrence(80%-90%),energy level occur-rence(60%-90%)and stability(Cv:0.6-1,Mv:1.2-1.8,Sv:0.8-1.2).The Antarctic’s wind energy resources in wind power density,effective wind speed occurrence and energy level occurrence in autumn and winter are better than those in summer,while the coefficient of variation in summer is worse than that in autumn and winter.

关键词： Antarctic wind energy resource evaluation temporal and spatial characteristics

A humidity resistant and high performance triboelectric nanogenerator enabled by vortex-induced vibration for scavenging wind energy

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Nano Research 2022年第4期15卷 3246-3253页

作者： Yan Wang Tianyu Chen Shuowen Sun Xiangyu Liu Zhiyuan Hu Zhenhui Lian Long Liu Qiongfeng Shi Hao Wang Jianchun Mi Tongming Zhou Chengkuo Lee Minyi Xu Dalian Key Lab of Marine Micro/Nano energy and Self-powered System Marine Engineering CollegeDalian Maritime UniversityDalian 116026China Center for Intelligent Sensors and MEMS(CISM) National University of Singapore Engineering Drive 3 Singapore 117576Singapore3 College of EngineeringPeking UniversityBeijing 100871China School of Civil Environmental and Mining EngineeringThe University of Western AustraliaWA 6009Australia

wind energy is a promising renewable energy source for a low-carbon society.This study is to develop a fully packaged vortexinduced vibration triboelectric nanogenerator(VIV-TENG)for scavenging wind energy.The VIV-TENG consists of a wind vane,internal power generation unit,an external frame,four springs,a square cylinder and a circular turntable.The internal power generation unit consists of polytetrafluoroethylene(PTFE)balls,a honeycomb frame and two copper electrodes.Different from most of the previous wind energy harvesting TENGs,the bouncing PTFE balls are fully packaged in the square cylinder.The distinct design separates the process of contact electrification from the external environment,and at the same time avoids the frictional wear of the ordinary wind energy harvesting TENGs.The corresponding VIV parameters are investigated to evaluate their influence on the vibration behaviors and the energy output.Resonant state of the VIV-TENG corresponds to the high output performance from the VIV-TENG.The distinct,robust structure ensures the full-packaged VIV-TENG can harvest wind energy from arbitrary directions and even in undesirable weather conditions.The study proposes a novel TENG configuration for harvesting wind energy and the VIV-TENG proves promising powering micro-electro-mechanical appliances.

关键词： vortex-induced vibration wind energy triboelectric nanogenerator self-powered

Ensemble Machine Learning greatly improves ERA5 skills for wind energy applications

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Energy and AI

energy and AI 2023年第3期13卷 197-206页

作者： Mattia Cavaiola Peter Enos Tuju Francesco Ferrari Gabriele Casciaro Andrea Mazzino DICCA Department of CivilChemical and Environmental Engineering.University of GenoaVia Montallegro 1Genoa16145GenoaItaly INFN National Institute of Nuclear PhysicsGenoa sectionVia Dodecaneso 33Genoa16146GenoaItaly EGO Data S.r.l. Via Felice Romani 9/5Genoa16122GenoaItaly

The skill of ERA5 has been assessed in relation to the prediction of the wind energy associated with 28 SYNOP stations located in Italy for a time span of 20 years(2001–2020).For comparison,a WRF-based high-resolution downscaling(3 km horizontally)was also produced for the same period.We found that simple predictions based on materialized past wind measures outperform the wind energy predictions from ERA5.This result can be ascribed to the particularly complex characteristics of the Italian territory.Motivated by this expected behavior,we have implemented a Quantile Random Forest(QRF)calibration which greatly alleviates the problems encountered in the ERA5 reanalysis dataset.This technique provides a calibrated ensemble prediction system for the wind speed at the station.Surprisingly,the calibrated ERA5 outperforms wind energy estimations from the high-resolution 3-km downscaling.Once properly calibrated,the high-resolution downscaling provides predictions very similar to the calibrated ERA5.Limiting our conclusions to the estimation of wind energy over a long time span(here 20 years),having at disposal a high-resolution wind-field dataset does not necessarily mean greater accuracy.A careful calibration of the original coarser wind-field dataset produces better results than the raw high-resolution dataset.

关键词： wind energy ERA5 reanalysis Quantile random forest Machine learning calibration

Joint Model of wind Speed and Corresponding Direction Based on wind Rose for wind energy Exploitation

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Journal of Ocean University of China 2022年第4期21卷 876-892页

作者： YANG Zihao LIN Yifan DONG Sheng College of Engineering Ocean University of ChinaQingdao 266100China Huadian Heavy Industries Co. Ltd.Beijing 100070China

As a common and extensive datum to analyze wind,wind rose is one of the most important components of the meteorological elements.In this study,a model is proposed to establish the joint probability distribution of wind speed and direction using grouped data of wind rose.On the basis of the model,an algorithm is presented to generate pseudorandom numbers of wind speed and paired direction data.Afterward,the proposed model and algorithm are applied to two weather stations located in the Liaodong Gulf.With the models built for the two cases,a novel graph representing the continuous joint probability distribution of wind speed and direction is plotted,showing a strong correlation to the corresponding wind rose.Moreover,the joint probability distributions are utilized to evaluate wind energy potential successfully.In cooperation with Monte Carlo simulation,the model can approximately predict annual directional extreme wind speed under different return periods under the condition that the wind rose can represent the meteorological characters of the wind field well.The model is beneficial to design and install wind turbines.

关键词： angular-linear distribution wind speed wind direction wind rose wind energy Monte Carlo simulation

Overview of the development and application of wind energy in New Zealand

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Energy and Built Environment

energy and Built Environment 2023年第6期4卷 725-742页

作者： Zhiguo Zhang Xiran Liu Dan Zhao Scott Post Jiasen Chen School of Mechanical and energy Engineering Zhejiang University of Science and TechnologyHangzhou310023China Department of Mechanical Engineering College of EngineeringUniversity of CanterburyNew Zealand Department of Aerospace Engineering College of EngineeringEmbry-Riddle Aeronautical UniversityFLUSA

The restructuring of the energy industry is imperative,as New Zealand strives to reduce greenhouse gas emissions.New Zealand has abundant renewable energy resources,and about 85%of current electricity generation is from renewable energy sources.However,in recent years,it appears that a considerable fraction of wind energy has been underutilized.This article reviews the history,current status,and future trends of wind energy development in New Zealand.The main challenges to the current development of wind energy are summarized compared to other countries.The main challenges come from the bi-cultural influence,environmental influence,and economic and social influence due to the variable nature of wind power,it is critical to store and operate power safely and reliably during peak power generation periods.This article compares seven mainstream wind energy storage technologies and analyzes the best solution for wind energy storage in New Zealand.This article analyzes the feasibility of using small-scale household(standard power rating range from 0.004 to 16 kW)wind turbines in New Zealand cities regarding their construction and operation process.The life cycle and the maximum capacity coefficient of such small-scale wind turbines are overviewed via three case studies and later compared with large commercial wind turbines(standard power rating ranges from 1 to 3 MW)in power generation capacity.It has been found that small-scale household wind turbines have notable power generation potential and economic benefits in the long term.

关键词： Renewable energy wind energy energy storage technologies Small-scale wind turbines

Modeling,Parameter Measurement,and Control of PMSG-based Grid-connected wind energy Conversion System

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Journal of Modern Power Systems and Clean energy 2021年第5期9卷 1054-1065页

作者： Mohammad Kamruzzaman Khan Prince Graduate Mohammad TArif Ameen Gargoom Aman MTOo Md Enamul Haque Renewable energy&Electric Vehicle(REEV)Lab Centre for Smart Power&Energy Research(cSPER)School of EngineeringDeakin UniversityWaurn pondsAustralia

The design of reliable controllers for wind energy conversion systems(WECSs)requires a dynamic model and accurate parameters of the wind generator.In this paper,a dynamic model and the parameter measurement and control of a direct-drive variable-speed WECS with a permanent magnet synchronous generator(PMSG)are presented.An experimental method is developed for measuring the key parameters of the PMSG.The measured parameters are used in the design of the controllers.The generator-side converter is controlled using a vector control scheme that maximizes the power extraction under varying wind speeds.A model predictive controller(MPC)is designed for the grid-side voltage source converter(VSC)to regulate the active and reactive power flows to the power grid by controlling the d-and q-axis currents in the synchronous reference frame.The MPC predicts the future values of the control variables and takes control actions based on the minimum value of the cost functions.To comply with the grid code requirement,a modified design approach for an LCL filter is presented and incorporated into the system.The design process is simple and incorporates significant filter parameters while avoiding iterative calculations.The comparative analysis of the designed filter with conventional L,LC,and iterative LCL filters demonstrates the effectiveness of the modified design approach.The proposed wind energy system with MPC and LCL filter is simulated in MATLAB/Simulink and experimentally implemented in the laboratory using the dSpace digital signal processor(DSP)system.The simulation and experimental results validate the efficacy of the designed controllers using the measured parameters and show dynamic and steady-state performance under varying wind speeds.

关键词： wind energy permanent magnet synchronous generator(PMSG) parameter measurement model predictive controller(MPC) LCL filter

A comprehensive review of miniatured wind energy harvesters

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Nano Materials Science 2021年第2期3卷 170-185页

作者： Quan Wen Xianming He Zhuang Lu Reinhard Streiter Thomas Otto Key Laboratory of Fundamental Science of Micro/Nano-Device and System Technology Chongqing UniversityChongqing400044People's Republic of China Microsystem Research Center Chongqing UniversityChongqing400044People's Republic of China Fraunhofer Institute for Electronic Nano Systems(ENAS) Chemnitz09131Germany

Following the current rapid development of the Internet of Things(IoT)and wireless condition monitoring systems,energy harvesters which use ambient energy have become a key part of achieving an energy-autonomous system.Miniature wind energy harvesters have attracted widespread attention because of their great potential of power density as well as the rich availability of wind energy in many possible areas of application.This article provides readers with a glimpse into the state-of-the-art of miniature wind energy harvesters.The crucial factors for them to achieve high working efficiency under lower operational wind speed excitation are analyzed.Various potential energy coupling mechanisms are discussed in detail.Design approaches for broadening operational wind-speed-range given a variety of energy coupling mechanisms are also presented,as observed in the literature.Performance enhancement mechanisms including hydrodynamic configuration optimization,and non-linear vibration pick-up structure are reviewed.Conclusions are drawn and the outlook for each coupling mechanisms is presented.

关键词： energy harvester wind energy Miniature wind-induced vibration energy harvester energy coupling mechanism Performance enhancement mechanisms

Future changes in wind energy potential over China using RegCM4 under RCP emission scenarios

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Advances in Climate Change Research 2021年第4期12卷 596-610页

作者： WU Jia HAN Zhen-Yu YAN Yu-Ping SUN Chao-Yang XU Ying SHI Ying National Climate Center China Meteorological AdministrationBeijing100081China Laboratory for Climate Studies China Meteorological AdministrationBeijing100081China

To provide a scientific basis for the policies for the development of wind energy and towards the goal of carbon neutrality in China and local governments,changes in wind energy potential over China were investigated based on the bias-corrected ensemble mean(CENS)of high-resolution dynamical downscaling projections using the RCP2.6,RCP4.5 and RCP8.5 emission scenarios.Firstly,evaluation indicated that CENS could better reproduce the long-term mean and interannual variability of surface wind speed over China compared to the original simulation outputs,providing a reliable basis for future projections.Projection of the averaged wind power density of China showed a decreasing trend during 2020-2099 in all four seasons under all three scenarios,with the significant(pwind energy located in northern China and the low-speed wind energy in South China were projected to decrease by the middle and late of the 21st century.Although the projected decrease in annual wind power density ranged from-1.14%to-0.36%per decade among the three scenarios,we believe that,considering the strong inter-annual variability and uncertainty involved,these changes would not substantially affect China's future wind energy plans.Also of note was that a low emission scenario could to some extent mitigate the reduction in wind energy potential in the future.Furthermore,we suggest that implementation of newly developed wind power technology should consider the impact of changes in wind energy in different sub-regions(e.g.,the low wind speed region over South China),which is pivotal to China's strategic planning in this sector.

关键词： wind energy Regional climate model Future projection China

A review and taxonomy of wind and solar energy forecasting methods based on deep learning

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能源与人工智能(英文)

能源与人工智能(英文) 2021年第2期4卷 136-160页

作者： Ghadah Alkhayat Rashid Mehmood Department of Computer Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia High Performance Computing Centre King Abdulaziz UniversityJeddah 21589Saudi Arabia

Renewable energy is essential for planet sustainability.Renewable energy output forecasting has a significant impact on making decisions related to operating and managing power systems.Accurate prediction of renewable energy output is vital to ensure grid reliability and permanency and reduce the risk and cost of the energy market and systems.Deep learning’s recent success in many applications has attracted researchers to this field and its promising potential is manifested in the richness of the proposed methods and the increasing number of publications.To facilitate further research and development in this area,this paper provides a review of deep learning-based solar and wind energy forecasting research published during the last five years discussing extensively the data and datasets used in the reviewed works,the data pre-processing methods,deterministic and probabilistic methods,and evaluation and comparison methods.The core characteristics of all the reviewed works are summarised in tabular forms to enable methodological comparisons.The current challenges in the field and future research directions are given.The trends show that hybrid forecasting models are the most used in this field followed by Recurrent Neural Network models including Long Short-Term Memory and Gated Recurrent Unit,and in the third place Convolutional Neural Networks.We also find that probabilistic and multistep ahead forecasting methods are gaining more attention.Moreover,we devise a broad taxonomy of the research using the key insights gained from this extensive review,the taxonomy we believe will be vital in understanding the cutting-edge and accelerating innovation in this field.

关键词： Deep learning Renewable energy forecasting Solar energy wind energy Taxonomy Hybrid methods