共查询到20条相似文献，搜索用时 15 毫秒
1.
Wind farms must periodically take their turbines offline in order to perform scheduled maintenance repairs. Given that these interruptions impact energy generation and that under Power Purchase Agreements productions shortfalls must be replaced by energy purchases in the spot market, the optimal time to begin maintenance work in a wind farm is a function of both the expected wind speeds and electricity spot prices. In this article, we develop a model to determine the optimal maintenance schedule of a wind farm based on forecasted wind speeds and energy prices. We analyze a window of opportunity in the most likely period of the year and perform weekly updates of expected wind speeds and energy price forecasts. Wind speeds are forecasted with an ARMAX model, where monthly dummies are used as exogenous variables to capture the seasonality of wind speeds, while spot prices are simulated under a standard dual stochastic programing model. The decision to defer maintenance to a future date is modeled in a probabilistic model and also under the real options approach. We test these models with actual data from a wind farm in the Brazilian Northeast and provide comparisons with current practice in order to determine the benefits of the model. The results suggest that this model may provide advantages over a stopping decision that randomly chooses a week to begin maintenance within the opportunity window and is close to the optimal stopping date considering perfect information on future wind speeds and electricity prices. 相似文献
2.
Sourabh Kumar 《国际可持续能源杂志》2013,32(2):98-109
A mathematical model is developed and presented for calculating the energy usage and costs for the dry milling corn-ethanol production process. The model is formulated into a spreadsheet to facilitate the study of the process. While considering the whole process, the model focuses on the primary energy-consuming cooking and distillation processes. This model is a feed-backwards model, which means process input requirements are calculated based on user-entered values for total annual plant production and various process parameters. Based on these input requirements, the total energy usage and the cost and amount of fuel used during the process are calculated. The accuracy of the model was verified through comparisons between modelling results and published data. This model can be used as a source for investigating other potential energy sources, such as the incorporation of solar energy and wind energy, for use in the ethanol production process. 相似文献
3.
The existence of vertical wind shear in the atmosphere close to the ground requires that wind resource assessment and prediction with numerical weather prediction (NWP) models use wind forecasts at levels within the full rotor span of modern large wind turbines. The performance of NWP models regarding wind energy at these levels partly depends on the formulation and implementation of planetary boundary layer (PBL) parameterizations in these models. This study evaluates wind speeds and vertical wind shears simulated by the Weather Research and Forecasting model using seven sets of simulations with different PBL parameterizations at one coastal site over western Denmark. The evaluation focuses on determining which PBL parameterization performs best for wind energy forecasting, and presenting a validation methodology that takes into account wind speed at different heights. Winds speeds at heights ranging from 10 to 160 m, wind shears, temperatures and surface turbulent fluxes from seven sets of hindcasts are evaluated against observations at Høvsøre, Denmark. The ability of these hindcast sets to simulate mean wind speeds, wind shear, and their time variability strongly depends on atmospheric static stability. Wind speed hindcasts using the Yonsei University PBL scheme compared best with observations during unstable atmospheric conditions, whereas the Asymmetric Convective Model version 2 PBL scheme did so during near‐stable and neutral conditions, and the Mellor–Yamada–Janjic PBL scheme prevailed during stable and very stable conditions. The evaluation of the simulated wind speed errors and how these vary with height clearly indicates that for wind power forecasting and wind resource assessment, validation against 10 m wind speeds alone is not sufficient. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
4.
This paper introduces the use of a multivariate regression analysis to explain factors that impact aggregate energy intensity. This kind of study is useful to evaluate the past and predicts the future trends for energy‐policy evaluation. Historical aggregate fuel and electricity intensities of the entire U.S. manufacturing sector (Standard Industrial Classification, SIC, codes of 20–39) over the 1977–1998 period are used to develop the proposed multivariate regression model. The proposed model allows identifying the structural effect of aggregate energy intensity changes without relying on detailed disaggregated energy data. Its results are validated by comparison with those from conventional decomposition techniques based on economic index numbers. For illustration, the historical aggregate fuel intensity of the U.S. primary metal industry (SIC 33) is used as an example of a situation for which economic index numbers fail to decompose the historical aggregate energy intensity since the disaggregated energy data are unavailable, while the multivariate regression analysis can still be applied. Empirical results show that a structural shift contributes to decreases of about 28, 41 and 19% of total declines of U.S. manufacturing aggregate fuel, U.S. manufacturing aggregate electricity, and U.S. primary metal industry aggregate fuel intensities, respectively, for the 1977–1998 period. The method based on multivariate regression models estimates the time series structural effects within deviation averages of 8.5 and 7.0% of the time series structural effect estimates based on the economic index numbers for the U.S. manufacturing aggregate fuel and electricity intensities, respectively, even though the multivariate regression model does not require disaggregated energy data. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
5.
Akhil Garg Surinder Singh Wei Li Liang Gao Xujian Cui Chin-Tsan Wang Xiongbin Peng Natarajan Rajasekar 《国际能源研究杂志》2020,44(12):9513-9526
The development of fault diagnosis of Li-ion batteries used in electric vehicles is vital. In this perspective, the present work conducted a comprehensive study for the evaluation of coupled and interactive influence of charging ratio, number of cycles, and voltage on the discharge capacity of Li-ion batteries to predict the life of battery. The charging-discharging experimental tests on Li-ion batteries have been performed. The data such as charging ratio, number of cycles, voltage, and discharge capacity of Li-ion batteries are measured. Machine learning approach of neural networks is then applied on the obtained data to compute the effects, normal distribution, parametric analysis, and sensitivity analysis of the input parameters on the capacity of battery. It can be noticed that discharge capacity increased with an increase in full voltage. Further, it has been observed from the sensitivity analysis that the full voltage is most relevant parameters to the capacity of the battery. Additionally, scanning electron microscopy/energy dispersive spectroscopy (SEM/EDS) of the electrodes before and after experiments have been performed, to investigate the elemental dissolution due to the charging/discharging cycles. The findings and analysis from the proposed study shall facilitate experts in making decisions on the remaining life and charging capacity of the battery. 相似文献
6.
E. García‐Bustamante J. F. González‐Rouco P. A. Jiménez J. Navarro J. P. Montávez 《风能》2009,12(7):640-659
Monthly wind energy estimations obtained by means of three different methodologies are evaluated. Hourly wind and wind power production data measured at five wind farms in the Northeast of Spain within the period spanning from June 1999 to June 2003 were employed for this purpose. One of the approaches is based on the combined contribution of the hourly wind speed frequency distribution and the corresponding power production. Several alternatives to represent the empirical wind power versus wind speed relationship are considered and their impacts on the error of monthly energy estimations assessed. Two more approaches derive monthly energy estimates directly from monthly wind values: one uses the theoretical power curve to obtain interpolated monthly wind power production values and the other consists in a simple linear regression between the observed wind speed and wind power monthly pairs, which serves as an approximation to the global power curve. The three methodologies reproduce reliably the total monthly wind energy. Results also reveal that linearity is a reasonable assumption for the relation between wind speed and power production at monthly timescales. This approach involves a simplification with respect to other standard procedures that require finer temporal resolution data. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
7.
This case study highlights the importance of taking into consideration diurnal variations of wind velocity for wind energy resources assessment. Previous studies of wind energy distribution that are based on the two-parameter Weibull density function have so far neglected to consider time of day fluctuations in wind speed, instead concentrating primarily on seasonal deviations. However, this has serious implications where such a wind energy model is the underpinning of calculations for the potential power production from a wind turbine and in particular where the timing of the energy output is essential to meet electricity loads. In the case of Grenada the energy output from a wind turbine during the day is approximately two times the output at night thereby fluctuating enormously around the seasonal mean distribution. When this is not taken into account the economic and technological viability of a wind turbine project may be overestimated or not even be identified. This work shows how a wind energy resources assessment based on the Weibull distribution model can be done and how the power output of a horizontal axis turbine is calculated. An analysis of the recorded wind data confirms the application of the Weibull density function as a suitable tool for modelling wind regimes. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
8.
Aditya Choukulkar Yelena Pichugina Christopher T. M. Clack Ronald Calhoun Robert Banta Alan Brewer Michael Hardesty 《风能》2016,19(8):1439-1452
The spurt of growth in the wind energy industry has led to the development of many new technologies to study this energy resource and improve the efficiency of wind turbines. One of the key factors in wind farm characterization is the prediction of power output of the wind farm that is a strong function of the turbulence in the wind speed and direction. A new formulation for calculating the expected power from a wind turbine in the presence of wind shear, turbulence, directional shear and direction fluctuations is presented. It is observed that wind shear, directional shear and direction fluctuations reduce the power producing capability, while turbulent intensity increases it. However, there is a complicated superposition of these effects that alters the characteristics of the power estimate that indicates the need for the new formulation. Data from two field experiments is used to estimate the wind power using the new formulation, and results are compared to previous formulations. Comparison of the estimates of available power from the new formulation is not compared to actual power outputs and will be a subject of future work. © 2015 The Authors. Wind Energy published by John Wiley & Sons, Ltd. 相似文献
9.
10.
酒泉地区风电场风电功率预报研究 总被引：1，自引：0，他引：1
利用NOAA天气预报模式Weather Research andForecasting Model(WRF)结合统计订正方法对酒泉地区短期风电功率预报进行了预报实验。与实际出力比较24 h短期风电功率预报精度较高。并在此基础上利用风电场附近测风塔观测数据通过时间序列发进行了0~4 h超短期预报实验,预报结果显示0~2 h预报结果有利于运行调度。 相似文献
11.
过分析我国内陆河北省张北县和吉林地区风电场内的风速廓线变化特性发现,各高度间风速的差异分布大体相同：各高度间风速差异由夜间到白天逐渐缩小,在中午达到最小,由白天到夜间逐渐增大,并且在各个阶段又相对稳定,即在日出后由地面向上的热量输送逐渐增强,湍流加强,各层间的风速差异减少,并迅速趋于稳定,直至日落湍流减弱。各层间的风速差异迅速增大,并趋于稳定。这一规律的发现对解释涡轮高度不同时间、相同风速条件下风机出力不同及风电功率建模有重要意义。 相似文献
12.
Wind farm power curve modeling, which characterizes the relationship between meteorological variables and power production, is a crucial procedure for wind power forecasting. In many cases, power curve modeling is more impacted by the limited quality of input data rather than the stochastic nature of the energy conversion process. Such nature may be due the varying wind conditions, aging and state of the turbines, etc. And, an equivalent steady‐state power curve, estimated under normal operating conditions with the intention to filter abnormal data, is not sufficient to solve the problem because of the lack of time adaptivity. In this paper, a refined local polynomial regression algorithm is proposed to yield an adaptive robust model of the time‐varying scattered power curve for forecasting applications. The time adaptivity of the algorithm is considered with a new data‐driven bandwidth selection method, which is a combination of pilot estimation based on blockwise least‐squares parabolic fitting and the probability integral transform. The regression model is then extended to a more robust one, in which a new dynamic forgetting factor is defined to make the estimator forget the out‐of‐date data swiftly and also achieve a better trade‐off between robustness against noisy data and time adaptivity. A case study based on a real‐world dataset validates the properties of the proposed regression method. Results show that the new method could flexibly respond to abnormal data at different lead times and has better performance than common benchmarks for short‐term forecasting. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
13.
14.
根据灰色理论建立了西北风电发电量的预测模型。该模型对原始数据进行了平滑处理、对背景值进行了改造,同时分析了外推值的置信区间,提高了预测精度。实例证明,该模型在西北风电电量预测中取得了较好效果。 相似文献
15.
16.
Karl J. Eidsvik 《风能》2005,8(2):237-249
In mountainous terrain, where the wind power potential is largest, the estimation of the local wind power can be done rationally by means of available information about the large‐scale flow and the detailed terrain and numerical flow models for downscaling, provided that the numerical model estimates can be assigned sufficient confidence. In this study the confidence of a local model in such an estimation system is discussed. The model is based upon the Reynolds‐averaged Navier–Stokes equations with (K, ?) turbulence closure and integrated with finite element numerical techniques. The model has previously been validated relative to complicated laboratory‐scale flows and appears to predict some full‐scale geophysical flows plausibly. Here its predictions are compared quantitatively with the full‐scale Askervein hill experimental data. The model estimates the data to within the experimental uncertainty, which we judge to be comparable to 10%, as other comparable models also do. This contributes to assign confidence to the downscaling estimation system mentioned. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
17.
18.
In this study, an innovative model has been developed for wind speed estimation through the Deep Learning method using hourly wind speed data from the measurement stations of the General Directorate of Meteorology in Van and Hakkari provinces in Turkey in conjunction with simultaneous satellite images from Eumetsat. Obtained satellite images were used during the introduction of the model, while wind speed data were used at the output stage. As a result of the findings, it was found that 85% accuracy performance could be achieved to provide sufficient insight for systems that are widely established worldwide. The model, developed as a result of the study, eliminates the need to install wind measuring stations for any region on earth within the satellite field in terms of determining wind potential. Since the field of view of the Meteosat 7 satellite covers the whole of Eastern Europe, it was determined that it could predict a high rate of up to 6 hours later by the method used in image analysis. The systems to be controlled with this method will be able to examine the weather events instantly at each point in the satellite field of view and make more accurate decisions. Also, companies will be able to perform a more detailed and rapid field scan compared to existing limited methods, and reduce initial investment costs and operating costs in terms of renewable energy resources investments. 相似文献
19.
Michael R. Milligan 《风能》2000,3(4):167-206
As the worldwide use of wind turbine generators in utility‐scale applications continues to increase, it will become increasingly important to assess the economic and reliability impact of these intermittent resources. Although the utility industry appears to be moving towards a restructured environment, basic economic and reliability issues will continue to be relevant to companies involved with electricity generation. This article is the second in a two‐part series that addresses modelling approaches and results that were obtained in several case studies and research projects at the National Renewable Energy Laboratory (NREL). This second article focuses on wind plant capacity credit as measured with power system reliability indices. Reliability‐based methods of measuring capacity credit are compared with wind plant capacity factor. The relationship between capacity credit and accurate wind forecasting is also explored. Published in 2000 by John Wiley & Sons, Ltd. 相似文献
20.
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. 相似文献