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Wind Energy: Fundamentals, Resource Analysis and Economics
01 Jan 2006-
TL;DR: In this article, the authors discuss the performance of wind energy conversion systems and the economic and environmental impact of wind power conversion systems in terms of energy efficiency and renewable energy sources, as well as wind energy and environment.
Abstract: Basics of wind energy conversion.- Analysis of wind regimes.- Wind energy conversion systems.- Performance of wind energy conversion systems.- Wind energy and environment.- Economics of wind energy.
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TL;DR: In this paper, a review of the use of the probability density function (PDF) of wind speed is carried out for a wide collection of models, and the methods that have been used to estimate the parameters on which these models depend are reviewed and the degree of complexity of the estimation is analyzed in function of the model selected.
Abstract: The probability density function (PDF) of wind speed is important in numerous wind energy applications. A large number of studies have been published in scientific literature related to renewable energies that propose the use of a variety of PDFs to describe wind speed frequency distributions. In this paper a review of these PDFs is carried out. The flexibility and usefulness of the PDFs in the description of different wind regimes (high frequencies of null winds, unimodal, bimodal, bitangential regimes, etc.) is analysed for a wide collection of models. Likewise, the methods that have been used to estimate the parameters on which these models depend are reviewed and the degree of complexity of the estimation is analysed in function of the model selected: these are the method of moments (MM), the maximum likelihood method (MLM) and the least squares method (LSM). In addition, a review is conducted of the statistical tests employed to see whether a sample of wind data comes from a population with a particular probability distribution. With the purpose of cataloguing the various PDFs, a comparison is made between them and the two parameter Weibull distribution (W.pdf), which has been the most widely used and accepted distribution in the specialised literature on wind energy and other renewable energy sources. This comparison is based on: (a) an analysis of the degree of fit of the continuous cumulative distribution functions (CDFs) for wind speed to the cumulative relative frequency histograms of hourly mean wind speeds recorded at weather stations located in the Canarian Archipelago; (b) an analysis of the degree of fit of the CDFs for wind power density to the cumulative relative frequency histograms of the cube of hourly mean wind speeds recorded at the aforementioned weather stations. The suitability of the distributions is judged from the coefficient of determination R2. Amongst the various conclusions obtained, it can be stated that the W.pdf presents a series of advantages with respect to the other PDFs analysed. However, the W.pdf cannot represent all the wind regimes encountered in nature such as, for example, those with high percentages of null wind speeds, bimodal distributions, etc. Therefore, its generalised use is not justified and it will be necessary to select the appropriate PDF for each wind regime in order to minimise errors in the estimation of the energy produced by a WECS (wind energy conversion system). In this sense, the extensive collection of PDFs proposed in this paper comprises a valuable catalogue.
690 citations
TL;DR: A comprehensive comparison study on the application of different artificial neural networks in 1-h-ahead wind speed forecasting shows that even for the same wind dataset, no single neural network model outperforms others universally in terms of all evaluation metrics.
636 citations
Cites methods from "Wind Energy: Fundamentals, Resource..."
...Note that wind speed at the height of 10 m was used as recommended by the World Meteorological Organization (WMO) [26]....
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01 Jan 2009
TL;DR: In this paper, a review of the use of the probability density function (PDF) of wind speed is carried out for a wide collection of models, and the methods that have been used to estimate the parameters on which these models depend are reviewed and the degree of complexity of the estimation is analyzed in function of the model selected.
Abstract: The probability density function (PDF) of wind speed is important in numerous wind energy applications. A large number of studies have been published in scientific literature related to renewable energies that propose the use of a variety of PDFs to describe wind speed frequency distributions. In this paper a review of these PDFs is carried out. The flexibility and usefulness of the PDFs in the description of different wind regimes (high frequencies of null winds, unimodal, bimodal, bitangential regimes, etc.) is analysed for a wide collection of models. Likewise, the methods that have been used to estimate the parameters on which these models depend are reviewed and the degree of complexity of the estimation is analysed in function of the model selected: these are the method of moments (MM), the maximum likelihood method (MLM) and the least squares method (LSM). In addition, a review is conducted of the statistical tests employed to see whether a sample of wind data comes from a population with a particular probability distribution. With the purpose of cataloguing the various PDFs, a comparison is made between them and the two parameter Weibull distribution (W.pdf), which has been the most widely used and accepted distribution in the specialised literature on wind energy and other renewable energy sources. This comparison is based on: (a) an analysis of the degree of fit of the continuous cumulative distribution functions (CDFs) for wind speed to the cumulative relative frequency histograms of hourly mean wind speeds recorded at weather stations located in the Canarian Archipelago; (b) an analysis of the degree of fit of the CDFs for wind power density to the cumulative relative frequency histograms of the cube of hourly mean wind speeds recorded at the aforementioned weather stations. The suitability of the distributions is judged from the coefficient of determination R2. Amongst the various conclusions obtained, it can be stated that the W.pdf presents a series of advantages with respect to the other PDFs analysed. However, the W.pdf cannot represent all the wind regimes encountered in nature such as, for example, those with high percentages of null wind speeds, bimodal distributions, etc. Therefore, its generalised use is not justified and it will be necessary to select the appropriate PDF for each wind regime in order to minimise errors in the estimation of the energy produced by a WECS (wind energy conversion system). In this sense, the extensive collection of PDFs proposed in this paper comprises a valuable catalogue.
634 citations
TL;DR: In this paper, a new method is developed to estimate Weibull distribution parameters for wind energy applications, which is called power density (PD) method and it has simple formulation, it does not require binning and solving linear least square problem or iterative procedure.
455 citations
Cites methods or result from "Wind Energy: Fundamentals, Resource..."
...compared several times [12–20] however results and recommendations of the previous studies are different....
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...Several methods have been proposed to estimate Weibull parameters [7–14]....
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TL;DR: In this paper, an open-loop optimal control scheme was proposed to incorporate the operating constraints of the battery energy storage system (BESS), such as state of charge limits, charge/discharge current limits, and lifetime.
Abstract: Integrating a battery energy storage system (BESS) with a large wind farm can make a wind farm more dispatchable. This paper focuses on development of a control strategy for optimal use of the BESS for this purpose. The paper considers an open-loop optimal control scheme to incorporate the operating constraints of the BESS, such as state of charge limits, charge/discharge current limits, and lifetime. The goal of the control is to have the BESS to provide as much smoothing as possible, so that the wind farm can be dispatched on an hourly basis based on the forecasted wind conditions. The effectiveness of this control strategy has been tested by using an actual wind farm data. Furthermore, a real-time implementation strategy using model predictive control is also proposed. Finally, it is shown that the control strategy is very important in improving the BESS performance for this application.
327 citations
Cites background from "Wind Energy: Fundamentals, Resource..."
...The trend for this sustainable energy resource is from small area harnessing to a large wind farm that could generate significant amount of energy to loads [1], [2]....
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