复杂地形风能资源评估研究初探

在实施可持续能源战略中，风能等可再生能源开发利用是重要的战略选择。风能资源评估是其开发利用的关键环节，如何利用有限的观测资料进行资源评估和分析就成为迫切需要解决的问题。本文正是基于此目的，就复杂地形下风能资源评估进行初步研究，通过对北京大学准静力模式进行改进，并进行数值模拟试验，探讨数值模拟在风能资源评估中的应用。模拟试验结果表明，改进后的模式很好地模拟出复杂地形条件下的流场特征，对复杂地形条件下的风能资源评估具有很好的指导意义。     

海上风能利用及其成本分析综述

以海上风能利用及其成本分析为研究对象,综述了海上风能资源,介绍了我国海上风电的成本构成、与陆上风电的成本差异及成本变化趋势,通过对设备购置费、建筑安装工程费等费用的测算,明确了海上风电成本控制的关键点。与陆上风电相比,海上风电具备风能资源丰富、风电场靠近能源负荷中心、海面可利用面积广阔、不存在土地占用等优势,发展海上风电是我国实现国家能源结构调整的有效保障,因此,海上风电的开发利用得到越来越多的重视。海上风电开发建设成本较高,降本增效将是海上风电良性发展的必然选择。     

海上风力发电技术

风力发电是一种清洁的能源利用方式。随着风力发电技术的发展,海上风力发电已逐渐成为风电发展的新领域。因为海上风资源丰富,而且不会受土地使用的限制。目前,一些欧洲国家已成功建立了自己的海上风电场,证实了海上风力发电是可行的。中国具有很长的海岸线,邻近海域具有丰富的风资源,如能充分利用这些风能,将有助于解决我国的能源和环境问题。我国的海上风力发电技术刚刚起步,开发设计适合我国海域特点,并具有自主知识产权的海上风力发电设备,对我国的风力发电技术及能源战略具有重大意义。     

GIS技术支持下的江苏省可用风能资源评估研究

传统的风能资源评估只考虑到风能的自然属性,没有和其社会属性结合起来。基于江苏省社会经济发展的需要和当地的实际情况,使用国际成熟的风能资源评估方法,创新性地把风能的自然属性和社会利用结合起来,根据风能资源的季节性变化,以四季平均风速分布作为重要指标,运用GIS技术的空间分析功能,结合风能在本地利用的实际情况对江苏省的风能资源可利用量进行了评估、分析和制图研究。结果显示,江苏省当前可实际开发利用的风能资源量达到146 336.16 GWh,在当地发展风能利用具有极大的资源潜力,可作为能源风险防范的关键技术进行开发。     

我国风能利用现状

我国有丰富的风能资源,风能总储量为３２－２６亿ｋＷ,实际可开发的风能储量为２－５３亿ｋＷ。风能是我国目前技术最成熟、最有开发利用前景的一种新能源。风能利用的主要方式有风力发电、风力提水、风帆助航等,本文就我国风能利用的现状向读者作一介绍。１风力提水我国适合风力提水的区域辽阔,作业众多因此发展风力提水是弥补当前农村、牧区能源不足的有效途径之一。我国东南沿海、辽东和山东半岛以及海上岛屿等地区,风能资源丰富,地表水源也丰富,是我国以抽提地表水为主的最佳风力提水区;内蒙、青海、甘肃和新疆北部河谷地带,风…     

岛屿型复杂地形地貌条件下有效风能分布的甚高分辨率数值模拟

利用MM5作为风能模拟模式,以地形复杂、气候背景特殊的海陵岛地区为研究区域,采用甚高分辨率(水平分辨率200m,最高垂直分辨率是10m)的模式设计,模拟了秋季海陵岛地区的风资源分布。研究表明,中尺度数值模式MM5的甚高分辨率的模式设计可以作为复杂海岛地形风资源评估的有效手段;海陵岛地区有效风能密度的大值区多数位于150～200W·m~(-2)之间,这说明我国沿海地区复杂地形地貌条件下潜在的风能资源完全可以开发利用,并需要更加深入而客观的评估。     

河北省海上风电发展浅析

海上风能是一种清洁、高效的绿色能源。开发利用海上风能对于减轻环境污染、解决能源危机有着重要意义。文章就河北省海上风能的特点、规划情况进行了分析介绍,并对河北省海上风电开发提出了一些建议与想法,以期为其海上风电的开发建设提供参考。     

海上风力发电进展

近年来风力发电工业发展迅速，海上风能以其突出的优势受到重视。本文对近年来国外几种典型的海上风能资源评估方法做出述评，简要叙述了国外海上风电技术发展与应用的现状，分析了海上风能利用的经济性，并介绍了一些主要国家进一步发展海上风电的计划。     

吉林长岭风场区风能资源统计评估

利用30 a风场数据作为基础研究资料,对吉林省长岭县风场区风能资源进行全面评估。评估结果发现,长岭县风场区风能资源蕴藏较为丰富,场区所在区域风向、风能分布相对集中,每年的3,4,5,10,11月,风场风速和风功率密度较高,1,7,8,12月较低。115 m高度处、80 m高度处的测风塔年平均风速、风功率密度分别为6.33,5.91 m/s和285.7,232.9 W/m²。115 m高度处、80 m高度处的虚拟测风塔年平均风速、风功率密度分别为6.42,6.00 m/s和299.1,243.8 W/m²。80 m处测风塔与虚拟测风塔风功率密度等级分别为1级和2级。了解长岭县风能资源分布规律,对于进一步合理开发利用吉林省可再生能源以及推进风电项目顺利开展具有一定的指导意义。     

基于WRF模式的海上风能资源特性分析及评价

掌握开发区域风能资源特性对优化调整大型海上风电基地布局,确定开发时序至关重要。采用WRF模式,对江苏省海上风能资源进行模拟,分析各区域风资源时空分布特性、互补特性、波动特性、随机特性并选择不同指标进行模糊综合评价。结果表明,江苏省海上风能资源时空分布明显,远海好于近海,南通优于盐城、连云港,年内3、4月份风速较大;资源互补特性与距离有明显的线性关系,与海岸线距离小于80 km时,互补性较差;波动性远海小于近海。评价结果也说明波动性与互补性为规划时需要考虑的重要指标。研究成果将为海上风电基地布局优化及评估体系提供重要参考。     

我国海上“风电三峡”及非并网风电应用系统开发建议

位于长三角地区的浅海辐射沙洲风能资源十分丰富,而且具有地质条件优越,灾害性气象概率低,没有主航道和大型地下线缆,地处电力负荷中心,高新技术产业基础好,人才基础和资本市场发育良好,已具备理论、技术和实践基础等优势,非常适合发展大规模海上风电场。如开发其中15%的风能资源,即可兴建一个相当于年产4250×104t标煤、每年减排二氧化碳1.12×108t的永续绿色能源基地,而且不占用一亩耕地,不产生一个移民,也不存在生态安全问题。由于风能的自身特性,导致风电的波动性、间歇性和不规则性,使电网难以承受海上大规模风电场的巨大电能。建议采用非并网风电技术,在辐射沙洲地区建设若干"低碳型"高耗能绿色工业园区,利用风能替代化石能源,实现"高碳能源向无碳能源"的跨越。如海水淡化产业基地,变输电上岸为输水上岸;氯碱生产基地及PVC等衍生产业;以电解铝为重点的有色冶金产业基地;新型绿色煤化工产业基地等。     

葫芦岛沿海地区风资源分析

以葫芦岛市沿海三站(连山、兴城、绥中)2006年逐日逐时10min平均风速资料为例,计算几项风资源评估参数,结果表明:葫芦岛市沿海地区均属于风能可利用区;各站风资源月分布均呈现双峰型,第一个高峰为2、3、4、5月,第二个高峰在10月;目前葫芦岛市连山站的位置距海岸较远,但结果仍表明该地的风资源比兴城、绥中丰富。     

The dynamics of an offshore wind turbine in parked conditions: a comparison between simulations and measurements

Offshore wind turbines are complex structures, and their dynamics can vary significantly because of changes in operating conditions, e.g., rotor‐speed, pitch angle or changes in the ambient conditions, e.g., wind speed, wave height or wave period. Especially in parked conditions, with reduced aerodynamic damping forces, the response due to wave actions with wave frequencies close to the first structural resonance frequencies can be high. Therefore, this paper will present numerical simulations using the HAWC2 code to study an offshore wind turbine in parked conditions. The model has been created according to best practice and current standards based on the design of an existing Vestas V90 offshore wind turbine on a monopile foundation in the Belgian North Sea. The damping value of the model's first fore‐aft mode has been tuned on the basis of measurements obtained from a long‐term ambient monitoring campaign on the same wind turbine. Using the updated model of the offshore wind turbine, the paper will present some of the effects of the different design parameters and the different ambient conditions on the dynamics of an offshore wind turbine. The results from the simulations will be compared with the processed data obtained from the real measurements. The accuracy of the model will be discussed in terms of resonance frequencies, mode shapes, damping value and acceleration levels, and the limitations of the simulations in modeling of an offshore wind turbine will be addressed. Copyright © 2014 John Wiley & Sons, Ltd.     

基于ERA5数据的江苏海域风能资源评估

利用欧洲中期天气预报中心（ECMWF）的ERA5风场数据，综合考虑风功率密度的时空分布、稳定性以及资源储量等要素，对江苏海域风能资源进行评估。结果表明，江苏海域多年平均风速和风功率密度总体呈现南高北低、离岸高近岸低的分布趋势。连云港近岸区域风功率密度等级小于2级，3级及以上区域主要分布在远海海域；盐城和南通除岸边潮间带滩涂区域外，大部分区域达到2级或3级，离岸约30 km可迅速提升至4级以上。风功率密度具有较明显的季节性分布特征；盐城南部和南通海域风能稳定性最好，连云港海域风能稳定性相对较差。南通和盐城南部风能资源有效储量最高，盐城北部次之，连云港最低。     

ENDOW (efficient development of offshore wind farms): modelling wake and boundary layer interactions

While experience gained through the offshore wind energy projects currently operating is valuable, a major uncertainty in estimating power production lies in the prediction of the dynamic links between the atmosphere and wind turbines in offshore regimes. The objective of the ENDOW project was to evaluate, enhance and interface wake and boundary layer models for utilization offshore. The project resulted in a significant advance in the state of the art in both wake and marine boundary layer models, leading to improved prediction of wind speed and turbulence profiles within large offshore wind farms. Use of new databases from existing offshore wind farms and detailed wake profiles collected using sodar provided a unique opportunity to undertake the first comprehensive evaluation of wake models in the offshore environment. The results of wake model performance in different wind speed, stability and roughness conditions relative to observations provided criteria for their improvement. Mesoscale model simulations were used to evaluate the impact of thermal flows, roughness and topography on offshore wind speeds. The model hierarchy developed under ENDOW forms the basis of design tools for use by wind energy developers and turbine manufacturers to optimize power output from offshore wind farms through minimized wake effects and optimal grid connections. The design tools are being built onto existing regional‐scale models and wind farm design software which was developed with EU funding and is in use currently by wind energy developers. Copyright © 2004 John Wiley & Sons, Ltd.     

Effects of sea surface temperature accuracy on offshore wind resource assessment using a mesoscale model

Offshore wind simulations were performed with the Weather Research and Forecasting (WRF) model driven by three different sea surface temperature (SST) datasets for Japanese coastal waters to investigate the effect of the SST accuracies on offshore wind simulations. First, the National Centers for Environmental Prediction Final analysis (FNL) (1° × 1° grid resolution) and the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) (0.05° × 0.05° grid resolution) datasets were compared with in situ measurements. The results show a decrease in accuracy of these datasets toward the coast from the open ocean. Aiming at an improved accuracy of SST data, we developed a new high‐resolution SST dataset (0.02° × 0.02° grid resolution). The new dataset referred to as MOSST is based on the Moderate Resolution Imaging Spectroradiometer (MODIS) product, provided by the Japan Aerospace Exploration Agency (JAXA). MOSST was confirmed to be more accurate than FNL and OSTIA for the coastal waters. Then, WRF simulations were carried out for 1 year with a 2 km grid resolution and by using the FNL, OSTIA and MOSST datasets. The use of the OSTIA dataset for a WRF simulation was found to improve the accuracy when compared with the FNL dataset, and further improvement was obtained when the MOSST dataset was applied. The sensitivity of wind speed and wind energy density to SST is also discussed. We conclude that the use of an accurate SST is a key factor not only for realistic offshore wind simulations near the surface but also for accurate wind resource assessments at the hub height of wind turbines. Copyright © 2014 John Wiley & Sons, Ltd.     

Evaluation of different wind fields for the investigation of the dynamic response of offshore wind turbines

As the size of offshore wind turbines increases, a realistic representation of the spatiotemporal distribution of the incident wind field becomes crucial for modeling the dynamic response of the turbine. The International Electrotechnical Commission (IEC) standard for wind turbine design recommends two turbulence models for simulations of the incident wind field, the Mann spectral tensor model, and the Kaimal spectral and exponential coherence model. In particular, for floating wind turbines, these standard models are challenged by more sophisticated ones. The characteristics of the wind field depend on the stability conditions of the atmosphere, which neither of the standard turbulence models account for. The spatial and temporal distribution of the turbulence, represented by coherence, is not modeled consistently by the two standard models. In this study, the Mann spectral tensor model and the Kaimal spectral and exponential coherence model are compared with wind fields constructed from offshore measurements and obtained from large‐eddy simulations. Cross sections and durations relevant for offshore wind turbine design are considered. Coherent structures from the different simulators are studied across various stability conditions and wind speeds through coherence and proper orthogonal decomposition mode plots. As expected, the standard models represent neutral stratification better than they do stable and unstable. Depending upon the method used for generating the wind field, significant differences in the spatial and temporal distribution of coherence are found. Consequently, the computed structural design loads on a wind turbine are expected to vary significantly depending upon the employed turbulence model. The knowledge gained in this study will be used in future studies to quantify the effect of various turbulence models on the dynamic response of large offshore wind turbines.     

Pricing offshore wind power

Offshore wind offers a very large clean power resource, but electricity from the first US offshore wind contracts is costlier than current regional wholesale electricity prices. To better understand the factors that drive these costs, we develop a pro-forma cash flow model to calculate two results: the levelized cost of energy, and the breakeven price required for financial viability. We then determine input values based on our analysis of capital markets and of 35 operating and planned projects in Europe, China, and the United States. The model is run for a range of inputs appropriate to US policies, electricity markets, and capital markets to assess how changes in policy incentives, project inputs, and financial structure affect the breakeven price of offshore wind power. The model and documentation are made publicly available.