Dynamic pricing of wind futures

Daily average wind speeds are dynamically modelled by a continuous-time autoregressive model with seasonal mean and volatility. Futures prices based on an index of aggregated wind speeds are derived, and it is shown that the Samuelson effect breaks down. The volatility of these futures will decrease when approaching maturity, an effect which is explained by the memory in higher-order autoregressive models.     

An equilibrium pricing model for weather derivatives in a multi-commodity setting

Many industries are exposed to weather risk. Weather derivatives can play a key role in hedging and diversifying such risk because the uncertainty in a company's profit function can be correlated to weather condition which affects diverse industry sectors differently. Unfortunately the weather derivatives market is a classical example of an incomplete market that is not amenable to standard methodologies used for derivative pricing in complete markets. In this paper, we develop an equilibrium pricing model for weather derivatives in a multi-commodity setting. The model is constructed in the context of a stylized economy where agents optimize their hedging portfolios which include weather derivatives that are issued in a fixed quantity by a financial underwriter. The supply and demand resulting from hedging activities and the supply by the underwriter are combined in an equilibrium pricing model under the assumption that all agents maximize some risk averse utility function. We analyze the gains due to the inclusion of weather derivatives in hedging portfolios and examine the components of that gain attributable to hedging and to risk sharing.     

考虑风光不确定性的分布式能源集成虚拟电厂收益-风险均衡模型

文章将风电场、光伏发电、小水电站等分布式能源聚合为虚拟电厂,并考虑价格型需求响应负荷及激励型需求响应负荷,以运营收益最大化为目标,综合考虑负荷供需平衡约束、机组运行约束以及旋转备用约束等,构建虚拟电厂常规调度优化模型,利用条件风险价值法(CVaR)和鲁棒随机优化理论构造虚拟电厂风险规避优化模型。最后,以独立微电网作为实例对象,验证了模型能够在最大化经济效益的同时,最大化利用清洁能源,合理控制运营风险,实现虚拟电厂最优化运营。     

An edge model for the evaluation of wind power ramps characterization approaches

Wind power forecasting is a recognized means of facilitating large‐scale wind power integration into power systems. Recently, there has been focus on developing dedicated short‐term forecasting approaches for large and sharp wind power variations, so‐called ramps. Accurate forecasts of specific ramp characteristics (e.g., timing and probability of occurrence) are important, as related forecast errors may lead to potentially large power imbalances, with a high impact on the power system. Various works about ramps’ periodicity or predictability have led to the development of new characterization approaches. However, a thorough analysis of these approaches has not yet been carried out. Such an analysis is necessary to ensure the reliability of subsequent conclusions on ramps’ characteristics. In this paper, we propose a comprehensive framework for evaluating and comparing different characterization approaches of wind power ramps. As a first step, we introduce a theoretical model of a ramp inspired from edge‐detection literature. The proposed model incorporates some important aspects of the wind power production process so as to reflect its non‐stationary and bounded aspects, as well as the random nature of ramp occurrences. Then, we introduce adequate evaluation criteria from signal‐processing and statistical literature, in order to assess the ability of an approach for reliably estimating ramp characteristics (i.e., timing and intensity). On the basis of simulations from this model and using the evaluation criteria, we study the performance of different ramp detection filters and multi‐scale characterization approaches. Our results show that some practical choices in wind‐energy literature are inappropriate, while others, namely, from signal‐processing literature, are preferable. Copyright © 2014 John Wiley & Sons, Ltd.     

计及风电消纳的源-荷-储环保经济型调度策略

为减少电力行业造成的环境污染、提升风电消纳比例,文章建立了考虑电力行业污染的电力系统日前调度模型。首先,依据热电联产机组及火电机组的燃料成本计算SO2,NOx,CO2排放量,并对其直接释放征收排污费用。然后,建立以总成本最低为目标的调度模型,综合考虑储能、储热装置的运行成本和投资成本、需求响应的激励成本以及弃风惩罚。最后,在保证系统安全、可靠基础上,通过遗传算法优化各个单元的有功功率。仿真结果表明,与不考虑环境成本的源荷储调度模型相比,CO2,SO2和NOx排放量分别减少14 944.07,48.85和42.54 kg,风电消纳比例提升10.60%。     

A seasonal copula mixture for hedging the clean spark spread with wind power futures

The recently introduced German wind power futures have brought the opportunity to address the problem of volume risk in wind power generation directly. In this paper, we study the hedging benefits of these instruments in the context of peak gas-fired power plants, by employing a strategy that allows trading in the day-ahead clean spark spread and wind power futures. To facilitate hedging decisions, we propose a seasonal copula mixture for the joint behavior of the day-ahead clean spark spread and the daily wind index. The model describes the data surprisingly well, both in terms of the marginals and the dependence structure, while being straightforward and easy to implement. Based on Monte Carlo simulations from the proposed model, the results indicate that significant benefits can be achieved by using wind power futures. Moreover, a comparison study shows that accounting for asymmetry, tail dependence, and seasonality in the dependence structure is especially important in the context of risk management.     

一种结合CNN和GRU网络的超短期风电预测模型

在大型电网和小型微电网中,风力发电预测对电力系统安全和经济运行发挥着至关重要的作用。针对传统建模中风电功率时变特性的局限,进一步探索风电时间序列波动特征的潜在信息,文章提出一种结合卷积神经网络(Convolutional Neural Network,CNN)和门控循环单元(Gated Recurrent Unit,GRU)的超短期风电预测模型。首先,该模型利用NWP气象数据为输入并将其归一化处理;然后,采用结合CNN和GRU网络对多变量时间序列进行动态时间建模,引入CNN来压缩GRU隐藏状态以减少计算模型的输出,克服训练过程中的梯度爆炸和消失问题;最后,根据风速和风力发电功率特性实现风电预测。通过实验仿真结果可知,与目前已投入运行的基于ANN的风电预测系统和近年来新兴的LSTM深度学习算法相比,该方法具有更高的预测精度,具有一定的工程价值。     

Multi-product pricing for electric power

This paper describes methods for determining the prices for a discrete set of interrelated products offered by a single supplier. Each product has a fixed marginal rate per unit, the demand for each product depends upon the price levels of all the products and the supplier's cost function depends upon the demands for all the products. For specific demand function forms, methods are described for determining the prices that maximize a weighted sum of net revenue and consumer surplus.     

Wind forecasts for wind power generation using the Eta model

The goal of this article is to apply the regional atmospheric numerical weather prediction Eta model and describe its performance in validation of the wind forecasts for wind power plants. Wind power generation depends on wind speed. Wind speed is converted into power through characteristic curve of a wind turbine. The forecasting of wind speed and wind power has the same principle.Two sets of Eta model forecasts are made: one with a coarse resolution of 22 km, and another with a nested grid of 3.5 km, centered on the Nasudden power plants, (18.22°E, 57.07°N; 3 m) at island Gotland, Sweden. The coarse resolution forecasts were used for the boundary conditions of the nested runs. Verification is made for the nested grid model, for summers of 1996–1999, with a total number of 19 536 pairs of forecast and observed winds. The Eta model is compared against the wind observed at the nearest surface station and against the wind turbine tower 10 m wind. As a separate effort, the Eta model wind is compared against the wind from tower observations at a number of levels (38, 54, 75 and 96 m).Four common measures of accuracy relative to observations - mean difference (bias), mean absolute difference, root mean square difference and correlation coefficient are evaluated. In addition, scatter plots of the observed and predicted pairs at 10 and 96 m are generated. Average overall results of the Eta model 10 m wind fits to tower observations are: mean difference (bias) of 0.48 m/s, mean absolute difference of 1.14 m/s, root mean square difference of 1.38 m/s, and the correlation coefficient of 0.79. Average values for the upper tower observation levels are the mean difference (bias) of 0.40 m/s; mean absolute difference of 1.46 m/s; root mean square difference of 1.84 m/s and the correlation coefficient of 0.80.     

An improved BEM model for the power curve prediction of stall‐regulated wind turbines

Blade element momentum (BEM) theory is the standard computational technique for the prediction of power curves of wind turbines; it is based on the two‐dimensional aerodynamic properties of aerofoil blade elements and some corrections accounting for three‐dimensional wing aerodynamics. Although most BEM models yield acceptable results for low‐wind and pitch‐controlled regimes where the local angles of attack are small, no generally accepted model exists up to date that consistently predicts the power curve in the stall regime for a variety of blade properties and operating conditions. In this article we present a modified BEM model which satisfactorily reproduces the power curves of four experimental wind turbines reported in the literature, using no free fit parameters. Since these four experimental cases comprehend a great variety of conditions (wind tunnel vs field experiments, different air densities) and blade parameters (no twist and no taper, no taper but twist, both twist and taper, different aerofoil families), it is believed that our model represents a useful working tool for the aerodynamic design of stall‐regulated wind turbines. Copyright © 2004 John Wiley & Sons, Ltd.     

An information diffusion-based model of oil futures price

Inspired by the increasing evidence of financialization/speculation in commodity pricing, this paper constitutes a first attempt to build an information diffusion-based asset pricing framework for the oil futures market. With gradual information dissemination, slowly decaying uncertainty about the asset's future fundamentals generates persistent conditional volatility and a drift in asset return. Volatility-based proxies for information flows are proposed to examine empirically the asset pricing implications. The results confirm a significant intertemporal relationship between return on the price of oil futures, information diffusion and volatility components. An important implication of our study is that the slow diffusion of information generates predictability in price dynamics. A forecasting model is then constructed and tested in relation to our theory. It is found that the lagged series of the pricing factors possess significant predicting power for returns.     

An analytical formula for the capacity credit of wind power

The capacity credit of wind power expresses how much ‘conventional’ power can be avoided or replaced by wind power. From data available in the literature, we have designed an analytical formula for the capacity credit based on the penetration level of the wind power in the power system, the overall capacity factor or annual use of the wind turbines, the reliability of the conventional part of the power system and the spread of the wind turbines. The resulting analytical formula avoids the use of elaborate stochastic reliability evaluations in providing a quick estimate of the capacity credit.     

链传动式风能转换装置理论模型的研究

针对传统风力机的特点及研究现状.设计了一种全新的链传动式风能转换装置.通过建立的理论模型,分析计算了在理想状况下叶片的最佳迎风角度,计算结果与试验数据基本吻合,为今后装置结构的进一步优化奠定了理论基础.     

Wind model for low frequency power fluctuations in offshore wind farms

This paper investigates the correlation between the frequency components of the wind speed Power Spectral Density. The results extend an already existing power fluctuation model that can simulate power fluctuations of wind power on areas up to several kilometers and for time scales up to a couple of hours, taking into account the spectral correlation between different wind turbines. The modelling is supported by measurements from two large wind farms, namely Nysted and Horns Rev. Measurements from individual wind turbines and meteorological masts are used. Finally, the models are integrated into an aggregated model which is used for estimating some electrical parameters as power ramps and reserves requirements, showing a quite good agreement between simulations and measurement. The comparison with measurements generally show that the inclusion of the correlation between low frequency components is an improvement, but the effect is relatively small. The effect of including the low frequency components in the model is much more significant. Therefore, that aggregated model is useful in the power system planning and operation, e.g. regarding load following and regulation. Copyright © 2009 John Wiley & Sons, Ltd.     

基于CEEMD-CNN-BiGRU-RF模型的短期风电功率预测

风电功率的准确预测对电网的安全运行和经济调度起着重要作用,为进一步提高风电功率的预测精度,文章提出了一种基于CEEMD-CNN-BiGRU-RF模型的短期风电功率预测模型。首先,利用完全集成经验模态分解(CEEMD)对风电功率时间序列进行模态分解;其次,对分解的各个风电功率时间序列利用卷积神经网络(CNN)进行特征提取;再次,建立双向门控循环单元(Bi GRU)模型对各个风电功率时间序列进行预测,叠加各个分量的预测值;最后,对误差进行进一步分析与预测,利用随机森林(RF)进行误差修正,得到最终的风电功率预测值。实验仿真表明,该模型的预测效果明显优于传统模型,模型的平均绝对百分比误差(MAPE)仅为2.09%。     

A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation

In this paper, a fuzzy model is suggested for the prediction of wind speed and the produced electrical power at a wind park. The model is trained using a genetic algorithm-based learning scheme. The training set includes wind speed and direction data, measured at neighboring sites up to 30 km away from the wind turbine clusters. Extensive simulation results are shown for two application cases, providing wind speed forecasts from 30 min to 2 h ahead. It is demonstrated that the suggested model achieves an adequate understanding of the problem while it exhibits significant improvement compared to the persistent method.     

Dynamic model of wind energy conversion systems with PMSG-based variable-speed wind turbines for power system studies

In order to study the impact of a wind farm on the dynamics of the power system, a significant issue is to develop appropriate equivalent models that allow characterizing the dynamics of all individual wind turbine generators (WTGs) composing the park. In this sense, with the advance of power electronics, direct-driven permanent magnet synchronous generators (PMSGs) have drawn increased interest to wind turbine manufacturers due to their advantages over other variable-speed WTGs. These include the possibility of multi-pole design with a gearless construction that offers slow speed operation and reduced maintenance since no brushes are used, elimination of the excitation system, full controllability for maximum wind power extraction and grid interface, and easiness in accomplishing fault-ride through and grid support. In this way, this paper presents a comprehensive dynamic equivalent model of a wind farm with direct-driven PMSG wind turbines using full-scale converters and its control scheme. The proposed simplified modelling is developed using the state-space averaging technique and is implemented in the MATLAB/Simulink environment. The dynamic performance of the wind farm and its impact on the power system operation is evaluated using the phasor simulation method.     

An analysis of wind power potential in Greece

In this paper an analysis of the available wind data for the Aegean Sea region of Greece is carried out to ascertain its potential for wind energy development. The effect of the limited number of daily observations available on the accuracy of the mean wind speed and annual wind energy estimates is ascertained. The applicability of the Weibull distribution is then examined and plots of the Weibull parameters are given. The annual average wind energy flux is calculated and found to be quite high (in excess of 600 W/m² per yr at 10 m) which makes the Aegean Islands likely candidates for wind power utilization.