风电场设计后评估活动的探讨

近年来,我国风电产业高速发展,国内风电装机容量连续3年翻番,但风电项目实际上网电量和设计发电量还存在一些差异.文章探讨了风电场的设计后评估,主要从设计角度考察设计指标与实际运行参数的差距,并找出产生差距的具体原因.通过后评估活动进一步优化风电场设计和更加准确地计算风电投资成本和上网电价.     

风电场平均风速变化对利用小时数的影响研究

本文分别采用两种方法,对风电场实测数据进行处理,得到平均风速依次递增的风速数据集序列,并提出一种结合数据集Weibull分布拟合结果及风电机组功率曲线数据,计算其对应发电量的数值积分方法;然后,本文结合3个风电场的实测风速数据,采用上述数据集处理和发电量计算方法,对其不同高度处的等效利用小时数进行了计算和对比分析研究,并与现有软件计算结果进行了对比验证。研究结果表明,本文提出的发电量计算方法可靠性较高,且平均风速每增加0.1m/s,等效利用小时数大致增加50h～60h。此研究结果也可为风能资源数据不同订正方法所造成的计算利用小时数变化规律的研究提供重要依据。     

计及风向不确定性的海上风电场年发电量计算

以欧洲Lillgrund海上风电场为例,建立基于Larsen尾流模型及线性叠加模型的风电场输出功率及发电量计算模型;考虑风电机组偏航偏差等风向不确定性的影响,建立基于高斯平均方法的风电场计算功率修正模型;结合风电场实测数据及发电量计算收敛过程分析,研究了修正模型对风电场功率及发电量计算的影响。结果表明,所建立的尾流作用下的风电场功率计算模型能够较好地反应实际风电场的尾流影响特征,高斯平均修正方法进一步提高了尾流作用下风电场功率计算精度,并提高了发电量计算的收敛速度。在风电场年发电量计算中考虑风向不确定性的影响,对于提高模型评估与验证的准确性具有重要意义。     

基于碳减排收入的风电成本电价研究

结合清洁能源发展机制(CDM)建立了净现值财务评价模型,以2010年注册为CDM项目的内蒙古风电场财务数据作为研究样本计算成本电价,并运用敏感性分析探究影响我国风电成本电价的因素。根据模型比较含碳减排收入和不含碳减排收入下的风电成本电价,分析两种情况下静态投资额、上网发电量、运营维护费用和贷款利率等因素对我国风电成本电价的影响程度,认为CDM是促进我国风电产业发展的重要因素,并与静态投资额、年上网发电量共同构成影响我国风电成本电价的主要因素。随着未来各敏感性因素的变化,我国风电成本价格将具备与火电成本价格竞争的可能性。     

湍流强度对风电场发电量的影响

准确估算湍流强度变化影响下的发电量,为风电项目开发与投资提供可靠的依据。从10 min级湍流强度变化的角度,提出了利用实时湍流强度计算风电场发电量的方法,通过多项式展开公式和数值积分,对风电机组的发电量进行估算。以新疆某风电场的实际风资源为例,与实际年发电量、静态理论年发电量和普遍采用的修正发电量功率曲线的方法对比,表明该方法估算的发电量误差小,更贴近实际年发电量。     

测风时间尺度对风电场设计参数的影响研究

文章以湖南地区多个风电场为例,选取10 min和1 h的测风时间序列采用单机计算法计算风电场风能资源参数、发电量和内部收益率指标,探讨测风时间尺度对风电场设计参数的影响。结果表明,10 min和1 h测风时间序列计算风能资源参数基本一致,但1 h测风时间序列计算发电量和内部收益率系统性偏小,同时差异随平均风速和风机叶片的减小有增大趋势。本成果可为风电场风能资源评估、发电量、内部收益率的不确定性及后评估提供参考,同时建议风电相关规程规范和风资源工程师采用10 min测风时间序列开展风能资源评估尤其是代表年订正及发电量计算工作。     

基于温度归一化的风电机组发电量模型研究

针对环境温度影响风电机组的输出功率及发电量计算的问题,通过分析风速的分布建立威布尔分布模型;分析温度对风电机组输出功率的影响,推导出温度归一化的功率折算公式,将功率折算到统一基准温度下,提出基于温度归一化的风电机组发电量计算模型。以新疆某风电场为算例,分别计算出4台风电机组的发电量,将温度归一化模型和传统算法计算的发电量与实测SCADA数据进行对比,验证温度归一化模型计算发电量的精确性。     

基于运行数据的风电机组转矩控制性能评估

风电机组的性能评估方法具有多样性及复杂性的特点,基于风电场SCADA系统中采集的大量风电机组运行数据,对风电机组转矩控制的性能评估方法进行了研究。在深入分析风电机组中发电机转速与发电机转矩关系的基础上,提出了风电机组在最佳风能利用系数Cp(max)跟踪区内的转矩优化控制的性能评估方法。通过筛选有效数据,拟合计算出风电机组的实际运行转矩增益系数;再通过与理论最优转矩增益系数进行对比,找出风能捕获能力较弱的风电机组,进而采取措施提高其发电量。通过软件仿真及案例分析表明,该方法在不增加设备及成本的情况下,可有效识别因转矩控制的性能差而影响发电量的风电机组,以便及时进行控制策略调校,维护风电场的利益。     

发电量估算不确定性对风电项目投资决策的影响

正风电场开发属于典型的资本密集型产业,风险控制是开发商做出投资决策时必须考虑的重要因素。控制风险需要尽量减少项目评价时的不确定因素,从电价、投资和发电量这三个影响风电项目收益最重要的因素来看,我国已确立的风电标杆价格政策帮助开发商锁定了电价风险;风电装备、施工、监理水平随着近年来风电的大规模开发取得了长足进步,经验的积累使得相关风险可以得到较好的     

基于WindPRO软件的不同时间尺度下的风电场产能评估

测风数据的准确性对风电场的产能评估具有重要的意义。文章以某风电场一年内每10 min的测风数据为基准,通过WindPRO软件,分别对3种时间尺度(30 min,1 h,2 h)的测风数据进行评估,对比了不同时间尺度下的发电量误差,分析了不同时间尺度下测风数据发电量的误差范围。当风电场选址区域的测风数据不完整时,研究结果可为测风数据时间尺度的选取提供指导性意见。     

基于风电机组可靠性的风电场平准化成本模型研究

考虑综合风电场总体运行成本、风电机组可靠性及风电场发电量等多个维度,从风电场全生命周期视角出发,建立基于风电机组可靠性的风电场平准化成本模型,并通过算例分析得出,提升风电机组可靠性可降低风电机组的故障维护成本,提高风电场运行小时数,进而降低风电场平准化成本。在此基础上测算当前阶段风电实现平价上网需达到的利用小时数,最后给出促进风电发展的合理化建议。     

Impact of wind farm integration on electricity market prices

Wind generation is considered one of the most rapidly increasing resources among other distributed generation technologies. Recently, wind farms with considerable output power rating are installed. The variability of the wind output power, and the forecast inaccuracy could have an impact on electricity market prices. These issues have been addressed by developing a single auction market model to determine the close to real-time electricity market prices. The market-clearing price was determined by formulating an optimal power flow problem while considering different operational strategies. Inaccurate power prediction can result in either underestimated or overestimated market prices, which would lead to either savings to customers or additional revenue for generator suppliers.     

Adding wind power to a wind-rich grid: Evaluating secondary suitability metrics

As the quantity of renewable electricity generation from wind farms increases in a region, the costs associated with integrating it into the broader electricity system also grow. This is primarily due to the need for dispatchable generators that vary power output to compensate for wind farm power variations. Such “balancing services” are an economic cost to the system that is typically not passed on to wind farms. We propose including the use of technical merits other than capacity factor and cost of energy for evaluating new wind farm sites and present a new graphical geospatial method, with the intention of identifying sites that minimize the need for additional electricity balancing service and transmission congestion. Specifically, locations with low correlation to existing wind farms, locations with high correlation to load, locations with high characteristic power time-shift from existing wind farms, and locations that relieve or do not negatively impact electricity transmission congestion are identified. A geospatial Venn diagram-based method of visualization is presented. These methods will equip regional planners with new tools to encourage wind farm development in areas that benefit the electricity grid beyond the lowest bid price.     

A combined modeling approach for wind power feed-in and electricity spot prices

Wind power generation and its impacts on electricity prices has strongly increased in the EU. Therefore, appropriate mark-to-market evaluation of new investments in wind power and energy storage plants should consider the fluctuant generation of wind power and uncertain electricity prices, which are affected by wind power feed-in (WPF). To gain the input data for WPF and electricity prices, simulation models, such as econometric models, can serve as a data basis.This paper describes a combined modeling approach for the simulation of WPF series and electricity prices considering the impacts of WPF on prices based on an autoregressive approach. Thereby WPF series are firstly simulated for each hour of the year and integrated in the electricity price model to generate an hourly resolved price series for a year. The model results demonstrate that the WPF model delivers satisfying WPF series and that the extended electricity price model considering WPF leads to a significant improvement of the electricity price simulation compared to a model version without WPF effects. As the simulated series of WPF and electricity prices also contain the correlation between both series, market evaluation of wind power technologies can be accurately done based on these series.     

A two-part feed-in-tariff for intermittent electricity generation

As electricity generation from intermittent energy sources (wind, sun, tides) is gaining momentum, it becomes increasingly important to price these electricity sources efficiently. Conventional flat feed-in-tariffs ignore the heterogeneity of these sources. Taking into account the degree of substitutability or complementarity of these sources with respect to each other and with respect to stochastic demand variations, this paper derives optimal pricing instruments composed of a feed-in-tariff (FIT) and a capacity-augmentation-tariff (CAT). An empirical analysis looks at wind and solar farms operating in Ontario in order to determine the optimal use of FIT-CAT pricing. The magnitude of optimal price differentiation turns out to be economically significant. Furthermore, the emergence of grid-scale electricity storage underscores the need to price energy and capacity separately.     

How does market power affect the impact of large scale wind investment in 'energy only' wholesale electricity markets?

In the short run, it is well known that increasing wind penetration is likely to reduce spot market electricity prices due to the merit order effect. The long run effect is less clear because there will be a change in new capacity investment in response to the wind penetration. In this paper we examine the interaction between capacity investment, wind penetration and market power by first using a least-cost generation expansion model to simulate capacity investment with increasing amounts of wind generation, and then using a computer agent-based model to predict electricity prices in the presence of market power. We find the degree to which firms are able to exercise market power depends critically on the ratio of capacity to peak demand. For our preferred long run generation scenario we show market power increases for some periods as wind penetration increases however the merit order counteracts this with the results that prices overall remain flat. Returns to peakers increase significantly as wind penetration increases. The market power in turn leads to inefficient dispatch which is exacerbated with large amounts of wind generation.     

Innovation and the price of wind energy in the US

In the last ten years, the wind energy industry has experienced many innovations resulting in wider deployment of wind energy, larger wind energy projects, larger wind turbines, and greater capacity factors. Using regression analysis, this paper examines the effects of technological improvements and other factors on the price of wind energy charged under long-term contracts in the United States. For wind energy projects completed during the period 1999–2006, higher capacity factors and larger wind farms contributed to reductions in wind energy contract prices paid by regulated investor owned utilities in 2007. However, this effect was offset by rising construction costs. Turbine size (in MW) shows no clear relationship to contract prices, possibly because there may be opposing factors tending to decrease costs as turbine size increases and tending to increase costs as turbine size increases. Wind energy is generally a low-cost resource that is competitive with natural gas-fired power generation.     

Wind farm electrical power production model for load flow analysis

The importance of renewable energy increases in activities relating to new forms of managing and operating electrical power: especially wind power. Wind generation is increasing its share in the electricity generation portfolios of many countries. Wind power production in Spain has doubled over the past four years and has reached 20 GW. One of the greatest problems facing wind farms is that the electrical power generated depends on the variable characteristics of the wind. To become competitive in a liberalized market, the reliability of wind energy must be guaranteed. Good local wind forecasts are therefore essential for the accurate prediction of generation levels for each moment of the day.This paper proposes an electrical power production model for wind farms based on a new method that produces correlated wind speeds for various wind farms. This method enables a reliable evaluation of the impact of new wind farms on the high-voltage distribution grid.     

Economic feasibility of electricity generation from wind farms: A case study

Environmental problems, population growth, and the recent energy crisis have emphasized the need for zero-emission technologies while also ensuring economic feasibility. This work presents the economic advantages of using wind energy for power generation in Iran. A theoretical model is developed, which predicts the output power under various geographical and operating conditions. The wind data (speed and direction) of 2-h interval long-term period from December 2010 to October 2015 was adopted and analyzed to evaluate the levelized costs of electricity (COE) for power generation from wind farms (Arsanjan, Lamerd, and Abadeh) for the year 2018 per time. The influence of two important geographical factors namely winds speed and air humidity on output power also was studied. The results showed that the output power increases continuously when the wind speed varies from 2.0 to 2.6 m/s probably due to the compression of air passing through the wind turbine.     

基于CVaR方法的风力发电项目投资风险度量

风力发电项目具备较为独立的特点,将CVaR方法引入风力发电项目的投资风险度量,不仅可以全面衡量技术风险、经济风险、政策风险等相关风险因素,同时可以最大限度地考虑投资者的损失承受底线。借助蒙特卡洛方法模拟风力发电的上网电量,很好地计量了风力发电的不确定性所带来的风险。以内蒙古地区某一风力发电项目为实例,分别计算了其VaR值和CVaR值。计算结果表明,CVaR方法能够更加谨慎有效地估计风力发电项目投资者的潜在损失。文章进一步研究了贴现率和电价等风险因素对风力发电项目整体风险的影响,认为较低的贴现率和较高的电价水平能够帮助投资者很好地规避投资风险。