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Daniel Villanueva
Industrial Engineering School, Universidade de Vigo, Rúa Maxwell s/n, 36310 Vigo, Spain

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Journal article
Published: 29 August 2021 in Applied Sciences
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Accurate prediction from electricity demand models is helpful in controlling and optimizing building energy performance. The application of machine learning techniques to adjust the electrical consumption of buildings has been a growing trend in recent years. Battery management systems through the machine learning models allow a control of the supply, adapting the building demand to the possible changes that take place during the day, increasing the users’ comfort, and ensuring greenhouse gas emission reduction and an economic benefit. Thus, an intelligent system that defines whether the storage system should be charged according to the electrical needs of that moment and the prediction of the subsequent periods of time is defined. Favoring consumption in the building in periods when energy prices are cheaper or the renewable origin is preferable. The aim of this study was to obtain a building electrical energy demand model in order to be combined with storage devices with the purpose of reducing electricity expenses. Specifically, multilayer perceptron neural network models were applied, and the battery usage optimization is obtained through mathematical modelling. This approach was applied to a public office building located in Bangkok, Thailand.

ACS Style

Moisés Cordeiro-Costas; Daniel Villanueva; Pablo Eguía-Oller. Optimization of the Electrical Demand of an Existing Building with Storage Management through Machine Learning Techniques. Applied Sciences 2021, 11, 7991 .

AMA Style

Moisés Cordeiro-Costas, Daniel Villanueva, Pablo Eguía-Oller. Optimization of the Electrical Demand of an Existing Building with Storage Management through Machine Learning Techniques. Applied Sciences. 2021; 11 (17):7991.

Chicago/Turabian Style

Moisés Cordeiro-Costas; Daniel Villanueva; Pablo Eguía-Oller. 2021. "Optimization of the Electrical Demand of an Existing Building with Storage Management through Machine Learning Techniques." Applied Sciences 11, no. 17: 7991.

Review
Published: 28 June 2021 in Applied Sciences
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The aim of this paper is to shed light on the question regarding whether the integration of an electric battery as a part of a domestic installation may increase its energy efficiency in comparison with a conventional case. When a battery is included in such an installation, two types of electrical conversion must be considered, i.e., AC/DC and DC/AC, and hence the corresponding losses due to these converters must not be forgotten when performing the analysis. The efficiency of the whole system can be increased if one of the mentioned converters is avoided or simply when its dimensioning is reduced. Possible ways to achieve this goal can be: to use electric vehicles as DC suppliers, the use of as many DC home devices as possible, and LED lighting or charging devices based on renewables. With all this in mind, several scenarios are proposed here in order to have a look at all possibilities concerning AC and DC powering. With the aim of checking these scenarios using real data, a case study is analyzed by operating with electricity consumption mean values.

ACS Style

Daniel Villanueva; Moisés Cordeiro-Costas; Andrés Feijóo-Lorenzo; Antonio Fernández-Otero; Edelmiro Miguez-García. Towards DC Energy Efficient Homes. Applied Sciences 2021, 11, 6005 .

AMA Style

Daniel Villanueva, Moisés Cordeiro-Costas, Andrés Feijóo-Lorenzo, Antonio Fernández-Otero, Edelmiro Miguez-García. Towards DC Energy Efficient Homes. Applied Sciences. 2021; 11 (13):6005.

Chicago/Turabian Style

Daniel Villanueva; Moisés Cordeiro-Costas; Andrés Feijóo-Lorenzo; Antonio Fernández-Otero; Edelmiro Miguez-García. 2021. "Towards DC Energy Efficient Homes." Applied Sciences 11, no. 13: 6005.

Journal article
Published: 08 April 2021 in Applied Sciences
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Nowadays, there is a growing trend to incorporate renewables in electrical power systems and, in particular, wind energy, which has become an important primary source in the electricity mix of many countries, where wind farms have been proliferating in recent years. This circumstance makes it particularly interesting to understand wind behavior because generated power depends on it. In this paper, a method is proposed to synthetically generate sequences of wind speed values satisfying two important constraints. The first consists of fitting the given statistical distributions, as the generally accepted fact is assumed that the measured wind speed in a location follows a certain distribution. The second consists of imposing spatial and temporal correlations among the simulated wind speed sequences. The method was successfully checked under different scenarios, depending on variables, such as the number of locations, the duration of the data collection period or the size of the simulated series, and the results were of high accuracy.

ACS Style

Moisés Cordeiro-Costas; Daniel Villanueva; Andrés Feijóo-Lorenzo; Javier Martínez-Torres. Simulation of Wind Speeds with Spatio-Temporal Correlation. Applied Sciences 2021, 11, 3355 .

AMA Style

Moisés Cordeiro-Costas, Daniel Villanueva, Andrés Feijóo-Lorenzo, Javier Martínez-Torres. Simulation of Wind Speeds with Spatio-Temporal Correlation. Applied Sciences. 2021; 11 (8):3355.

Chicago/Turabian Style

Moisés Cordeiro-Costas; Daniel Villanueva; Andrés Feijóo-Lorenzo; Javier Martínez-Torres. 2021. "Simulation of Wind Speeds with Spatio-Temporal Correlation." Applied Sciences 11, no. 8: 3355.

Journal article
Published: 25 August 2020 in Applied Sciences
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Nowadays, common electrical household appliances are mostly being powered by means of alternate current (AC), although there are cases where direct current (DC) is used instead. In all cases, internal devices are supplied with DC, and this fact involves there are losses due to the need for AC/DC converters. At the same time, most electrical home consumption takes place during peak hours when electricity is more expensive in many electricity markets. The addition of a battery in these installations permits storing electrical energy during certain periods of the day with the aim of supplying it during other ones—when this operation is more efficient or convenient—simultaneously reducing costs and greenhouse gas emissions. In this paper, a comparison is proposed between three possible home consumption scenarios, i.e., one consisting of a current AC system, one consisting of an AC system with a battery, and a third consisting of a hybrid AC/DC system with a battery.

ACS Style

Daniel Villanueva; Moisés Cordeiro; Andrés Feijóo; Edelmiro Míguez; Antonio Fernández. Effects of Adding Batteries in Household Installations: Savings, Efficiency and Emissions. Applied Sciences 2020, 10, 5891 .

AMA Style

Daniel Villanueva, Moisés Cordeiro, Andrés Feijóo, Edelmiro Míguez, Antonio Fernández. Effects of Adding Batteries in Household Installations: Savings, Efficiency and Emissions. Applied Sciences. 2020; 10 (17):5891.

Chicago/Turabian Style

Daniel Villanueva; Moisés Cordeiro; Andrés Feijóo; Edelmiro Míguez; Antonio Fernández. 2020. "Effects of Adding Batteries in Household Installations: Savings, Efficiency and Emissions." Applied Sciences 10, no. 17: 5891.

Review
Published: 18 June 2020 in Applied Sciences
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Over the last decades, wind energy has been arising as one of the most promising sources for the future of energy supply, and this trend should be reinforced in the future due to the foreseeable environmental and climatological catastrophe. Therefore, all technologies and issues regarding its development are relevant. Among them, research on wind turbine power curve modeling is of importance for stakeholders and researchers because it allows them to easily obtain information about the amount of power and energy that can be captured from the primary resource, i.e., the wind. The task can be simplified by means of the use of wind turbine power curve models, and many researchers have been presenting their contributions on the topic in parallel with such a development. In this paper, a review on the formulation of wind turbine deterministic power curve models is presented.

ACS Style

Daniel Villanueva; Andrés Feijóo. A Review on Wind Turbine Deterministic Power Curve Models. Applied Sciences 2020, 10, 4186 .

AMA Style

Daniel Villanueva, Andrés Feijóo. A Review on Wind Turbine Deterministic Power Curve Models. Applied Sciences. 2020; 10 (12):4186.

Chicago/Turabian Style

Daniel Villanueva; Andrés Feijóo. 2020. "A Review on Wind Turbine Deterministic Power Curve Models." Applied Sciences 10, no. 12: 4186.

Journal article
Published: 10 May 2020 in Applied Sciences
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Power curves provided by wind turbine manufacturers are obtained under certain conditions that are different from those of real life operation and, therefore, they actually do not describe the behavior of these machines in wind farms. In those cases where one year of data is available, a logistic function may be fitted and used as an accurate model for such curves, with the advantage that it describes the power curve by means of a very simple mathematical expression. Building such a curve from data can be achieved by different methods, such as using mean values or, alternatively, all the possible values for given intervals. However, when using the mean values, some information is missing and when using all the values the model obtained can be wrong. In this paper, some methods are proposed and applied to real data for comparison purposes. Among them, the one that combines data clustering and simulation is recommended in order to avoid some errors made by the other methods. Besides, a data filtering recommendation and two different assessment procedures for the error provided by the model are proposed.

ACS Style

Daniel Villanueva; Adrián Sixto; Andrés Feijóo; Antonio Fernández; Edelmiro Miguez. Methods to Apply a 3-Parameter Logistic Model to Wind Turbine Data. Applied Sciences 2020, 10, 3317 .

AMA Style

Daniel Villanueva, Adrián Sixto, Andrés Feijóo, Antonio Fernández, Edelmiro Miguez. Methods to Apply a 3-Parameter Logistic Model to Wind Turbine Data. Applied Sciences. 2020; 10 (9):3317.

Chicago/Turabian Style

Daniel Villanueva; Adrián Sixto; Andrés Feijóo; Antonio Fernández; Edelmiro Miguez. 2020. "Methods to Apply a 3-Parameter Logistic Model to Wind Turbine Data." Applied Sciences 10, no. 9: 3317.

Conference paper
Published: 14 October 2019 in E3S Web of Conferences
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The wind is an uncontrollable primary resource, although its energy can be stored. This fact can be used for the design of strategies for a better management of electric power networks. An option for achieving this goal is to install Battery Energy Storage Systems (BESS) in the wind farms (WF). When dealing with WFs combined with BESSs the most important is to manage the power production in order to meet the requirements of the network or those related with the owner of the plant. Both challenges constitute an optimization problem. This paper proposes an Evolutionary Algorithm (EA) to solve it, where a fitness function must be maximized under the consideration of certain constraints. The fitness function depends on the target of the power production, which may be either to help the network become more stable or to maximize the profit, assessing each scenario and accepting the best one. The constraints of the optimization problem are related to the levels of the BESSs: the maximum power transferred to or from it and the output power of the plant.

ACS Style

Daniel Villanueva; Andrés E. Feijóo; Neeraj D. Bokde. A Strategy for Power Generation Optimization in a Hybrid Wind-BESS Power Plant. E3S Web of Conferences 2019, 122, 04004 .

AMA Style

Daniel Villanueva, Andrés E. Feijóo, Neeraj D. Bokde. A Strategy for Power Generation Optimization in a Hybrid Wind-BESS Power Plant. E3S Web of Conferences. 2019; 122 ():04004.

Chicago/Turabian Style

Daniel Villanueva; Andrés E. Feijóo; Neeraj D. Bokde. 2019. "A Strategy for Power Generation Optimization in a Hybrid Wind-BESS Power Plant." E3S Web of Conferences 122, no. : 04004.

Conference paper
Published: 14 October 2019 in E3S Web of Conferences
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Wind power constitutes a variable energy source that introduces unbalance in electrical network management because it cannot be programmed. Then, the possibility of storing wind energy becomes very important. The lack of control is a drawback that disappears when the combination of a wind farm (WF) and a battery energy storage system (BESS) is considered. In that case, the goal is to adjust the power plant output and the load requirements of electrical network, i.e., to contribute to system adequacy as much as possible. Considering the features of the problem, it can be defined as an optimization problem. Two algorithms are proposed to solve it: the primal dual algorithm and the Mehrotra predictor-corrector one. In both cases, the best solution of the proposed problem is reached in an efficient manner. The primal dual algorithm performs better in terms of time and the Mehrotra predictor-corrector one needs fewer iterations.

ACS Style

Pablo Durán; Daniel Villanueva; Andrés E. Feijóo; Neeraj D. Bokde. Interior Point Algorithm Applied to the Optimization of the Power Supplied by a Wind Farm with a BESS. E3S Web of Conferences 2019, 122, 04002 .

AMA Style

Pablo Durán, Daniel Villanueva, Andrés E. Feijóo, Neeraj D. Bokde. Interior Point Algorithm Applied to the Optimization of the Power Supplied by a Wind Farm with a BESS. E3S Web of Conferences. 2019; 122 ():04002.

Chicago/Turabian Style

Pablo Durán; Daniel Villanueva; Andrés E. Feijóo; Neeraj D. Bokde. 2019. "Interior Point Algorithm Applied to the Optimization of the Power Supplied by a Wind Farm with a BESS." E3S Web of Conferences 122, no. : 04002.

Review
Published: 15 January 2019 in Energies
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Reliable and accurate planning and scheduling of wind farms and power grids to ensure sustainable use of wind energy can be better achieved with the use of precise and accurate prediction models. However, due to the highly chaotic, intermittent and stochastic behavior of wind, which means a high level of difficulty when predicting wind speed and, consequently, wind power, the evolution of models capable of narrating data of such a complexity is an emerging area of research. A thorough review of literature, present research overviews, and information about possible expansions and extensions of models play a significant role in the enhancement of the potential of accurate prediction models. The last few decades have experienced a remarkable breakthrough in the development of accurate prediction models. Among various physical, statistical and artificial intelligent models developed over this period, the models hybridized with pre-processing or/and post-processing methods have seen promising prediction results in wind applications. The present review is focused on hybrid empirical mode decomposition (EMD) or ensemble empirical mode decomposition (EEMD) models with their advantages, timely growth and possible future in wind speed and power forecasting. Over the years, the practice of EEMD based hybrid models in wind data predictions has risen steadily and has become popular because of the robust and accurate nature of this approach. In addition, this review is focused on distinct attributes including the evolution of EMD based methods, novel techniques of treating Intrinsic Mode Functions (IMFs) generated with EMD/EEMD and overview of suitable error measures for such studies.

ACS Style

Neeraj Bokde; Andrés Feijóo; Daniel Villanueva; Kishore Kulat. A Review on Hybrid Empirical Mode Decomposition Models for Wind Speed and Wind Power Prediction. Energies 2019, 12, 254 .

AMA Style

Neeraj Bokde, Andrés Feijóo, Daniel Villanueva, Kishore Kulat. A Review on Hybrid Empirical Mode Decomposition Models for Wind Speed and Wind Power Prediction. Energies. 2019; 12 (2):254.

Chicago/Turabian Style

Neeraj Bokde; Andrés Feijóo; Daniel Villanueva; Kishore Kulat. 2019. "A Review on Hybrid Empirical Mode Decomposition Models for Wind Speed and Wind Power Prediction." Energies 12, no. 2: 254.

Journal article
Published: 26 October 2018 in Energies
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Wind energy is a variable energy source with a growing presence in many electrical networks across the world. Wind-speed prediction has become an important tool for many agents involved in energy markets. In this paper, an approach to this problem is proposed by means of a novel method that outperforms results obtained by current direct and indirect wind-power prediction procedures. The first difference is that it is not strictly a direct or indirect method in the conventional sense because it uses information from both wind-speed and wind-power data series to obtain a wind-power series. The second difference is that it smooths down the wind-power series obtained in the first stage, and uses the resulting series for predicting new wind-power values. The process of smoothing is based on the label sequence generation process discussed in the pattern sequence forecasting algorithm and the Naive Bayesian method-based matching process. The result is a less chaotic way to predict wind speed than those offered by other existing methods. It has been assessed in multiple simulations, for which three different error measures have been used.

ACS Style

Neeraj Bokde; Andrés Feijóo; Daniel Villanueva; Kishore Kulat. A Novel and Alternative Approach for Direct and Indirect Wind-Power Prediction Methods. Energies 2018, 11, 2923 .

AMA Style

Neeraj Bokde, Andrés Feijóo, Daniel Villanueva, Kishore Kulat. A Novel and Alternative Approach for Direct and Indirect Wind-Power Prediction Methods. Energies. 2018; 11 (11):2923.

Chicago/Turabian Style

Neeraj Bokde; Andrés Feijóo; Daniel Villanueva; Kishore Kulat. 2018. "A Novel and Alternative Approach for Direct and Indirect Wind-Power Prediction Methods." Energies 11, no. 11: 2923.

Journal article
Published: 28 September 2018 in Applied Sciences
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The representation of a wind turbine power curve by means of the cumulative distribution function of a Weibull distribution is investigated in this paper, after having observed the similarity between such a function and real WT power curves. The behavior of wind speed is generally accepted to be described by means of Weibull distributions, and this fact allows researchers to know the frequency of the different wind speeds. However, the proposal of this work consists of using these functions in a different way. The goal is to use Weibull functions for representing wind speed against wind power, and due to this, it must be clear that the interpretation is quite different. This way, the resulting functions cannot be considered as Weibull distributions, but only as Weibull functions used for the modeling of WT power curves. A comparison with simulations carried out by assuming logistic functions as power curves is presented. The reason for using logistic functions for this validation is that they are very good approximations, while the reasons for proposing the use of Weibull functions are that they are continuous, simpler than logistic functions and offer similar results. Additionally, an explanation about a software package has been discussed, which makes it easy to obtain Weibull functions for fitting WT power curves.

ACS Style

Neeraj Bokde; Andrés Feijóo; Daniel Villanueva. Wind Turbine Power Curves Based on the Weibull Cumulative Distribution Function. Applied Sciences 2018, 8, 1757 .

AMA Style

Neeraj Bokde, Andrés Feijóo, Daniel Villanueva. Wind Turbine Power Curves Based on the Weibull Cumulative Distribution Function. Applied Sciences. 2018; 8 (10):1757.

Chicago/Turabian Style

Neeraj Bokde; Andrés Feijóo; Daniel Villanueva. 2018. "Wind Turbine Power Curves Based on the Weibull Cumulative Distribution Function." Applied Sciences 8, no. 10: 1757.

Journal article
Published: 01 February 2018 in Electric Power Systems Research
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In recent years logistic functions have been used to model wind turbine power curves. Generally speaking, it can be said that the results provided by the logistic functions are good enough to choose them over other options considering its continuity and adaptability. However, there are some logistic functions that have never been used to model wind turbine power curves although their use can be adequate. Comparing all logistic functions can help definitely to decide which are the best options. In this paper, the most known logistic functions are presented and tested to model wind turbine power curves, included those already used. Moreover, a comparison is made among them, after which two logistic functions are eventually recommended and some other are definitively discarded.

ACS Style

Daniel Villanueva; Andrés Feijóo. Comparison of logistic functions for modeling wind turbine power curves. Electric Power Systems Research 2018, 155, 281 -288.

AMA Style

Daniel Villanueva, Andrés Feijóo. Comparison of logistic functions for modeling wind turbine power curves. Electric Power Systems Research. 2018; 155 ():281-288.

Chicago/Turabian Style

Daniel Villanueva; Andrés Feijóo. 2018. "Comparison of logistic functions for modeling wind turbine power curves." Electric Power Systems Research 155, no. : 281-288.

Journal article
Published: 27 April 2017 in IEEE Transactions on Sustainable Energy
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This letter is an additional contribution to the calculation of wind farm power curves and power probability density functions with the help of the logistic function and Jensens model for wake effect calculation. The goal is to complete a previous formulation based on the use of the 3P-DP logistic function, with two other, called the 4P-DS and the 4P-DP ones.

ACS Style

Andres Feijoo; Daniel Villanueva. Four-Parameter Models for Wind Farm Power Curves and Power Probability Density Functions. IEEE Transactions on Sustainable Energy 2017, 8, 1783 -1784.

AMA Style

Andres Feijoo, Daniel Villanueva. Four-Parameter Models for Wind Farm Power Curves and Power Probability Density Functions. IEEE Transactions on Sustainable Energy. 2017; 8 (4):1783-1784.

Chicago/Turabian Style

Andres Feijoo; Daniel Villanueva. 2017. "Four-Parameter Models for Wind Farm Power Curves and Power Probability Density Functions." IEEE Transactions on Sustainable Energy 8, no. 4: 1783-1784.

Journal article
Published: 05 October 2016 in IEEE Transactions on Power Systems
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This letter is a contribution to the calculation of wind farm power curve distributions. The logistic function is used to represent a wind turbine power curve and the Jensen model is used to simulate the wake effects.

ACS Style

Andres Feijoo; Daniel Villanueva. Wind farm power distribution function considering wake effects. IEEE Transactions on Power Systems 2016, 32, 1 -1.

AMA Style

Andres Feijoo, Daniel Villanueva. Wind farm power distribution function considering wake effects. IEEE Transactions on Power Systems. 2016; 32 (4):1-1.

Chicago/Turabian Style

Andres Feijoo; Daniel Villanueva. 2016. "Wind farm power distribution function considering wake effects." IEEE Transactions on Power Systems 32, no. 4: 1-1.

Journal article
Published: 24 August 2016 in IEEE Transactions on Energy Conversion
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Presents corrections to the paper, "A PQ model for asynchronous machines based on rotor voltage calculation," (Feijoo, A. and Villanueva, D.), IEEE Trans. Energy Convers., vol. 31, no. 2, pp. 813-814, Jun. 2016.

ACS Style

Andres Feijoo; Daniel Villanueva. Correction to “A PQ Model for Asynchronous Machines Based on Rotor Voltage Calculation” [Jun 16 813-814]. IEEE Transactions on Energy Conversion 2016, 31, 1228 -1228.

AMA Style

Andres Feijoo, Daniel Villanueva. Correction to “A PQ Model for Asynchronous Machines Based on Rotor Voltage Calculation” [Jun 16 813-814]. IEEE Transactions on Energy Conversion. 2016; 31 (3):1228-1228.

Chicago/Turabian Style

Andres Feijoo; Daniel Villanueva. 2016. "Correction to “A PQ Model for Asynchronous Machines Based on Rotor Voltage Calculation” [Jun 16 813-814]." IEEE Transactions on Energy Conversion 31, no. 3: 1228-1228.

Journal article
Published: 01 August 2016 in Electric Power Systems Research
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The current procedure for obtaining the parameters of the logistic function, used as a model for the power curve of wind turbines, provides meaningless values. These values are different for each wind turbine and obtaining them requires an optimization process. This paper proposes a procedure to obtain the parameters of the 4-parameter logistic function based on the features of the power curve, providing a model that is a function of the power curve parameters supplied by the manufacturer. Furthermore, that model can be used to derive another 4-parameter model and a 3-parameter model is proposed for certain conditions. The three models consist of a continuous function which simplifies the implementation of the curve in a computer program compared to piecewise models. In addition, the probability density function of the output power of a wind turbine is derived by using each model.

ACS Style

Daniel Villanueva; Andrés E. Feijóo. Reformulation of parameters of the logistic function applied to power curves of wind turbines. Electric Power Systems Research 2016, 137, 51 -58.

AMA Style

Daniel Villanueva, Andrés E. Feijóo. Reformulation of parameters of the logistic function applied to power curves of wind turbines. Electric Power Systems Research. 2016; 137 ():51-58.

Chicago/Turabian Style

Daniel Villanueva; Andrés E. Feijóo. 2016. "Reformulation of parameters of the logistic function applied to power curves of wind turbines." Electric Power Systems Research 137, no. : 51-58.

Journal article
Published: 30 June 2016 in Wind Energy
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This paper presents a contribution to wind farm ouput power estimation. The calculation for a single wind turbine involves the use of the power coefficient or, more directly, the power curve data sheet. Thus, if the wind speed value is given, a simple calculation or search in the data sheet will provide the generated power as a result. However, a wind farm generally comprises more than one wind turbine, which means the estimation of power generated by the wind farm as a function of the wind speed is a more complex process that depends on several factors, including the important issue of wind direction. While the concept of a wind turbine power curve for a single wind turbine is clear, it is more subject to discussion when applied to a whole wind farm. This paper provides a simplified method for the estimation of wind farm power, based on the use of an equivalent wake effect coefficient. Copyright © 2016 John Wiley & Sons, Ltd.

ACS Style

Andrés Feijóo; Daniel Villanueva. Contributions to wind farm power estimation considering wind direction-dependent wake effects. Wind Energy 2016, 20, 221 -231.

AMA Style

Andrés Feijóo, Daniel Villanueva. Contributions to wind farm power estimation considering wind direction-dependent wake effects. Wind Energy. 2016; 20 (2):221-231.

Chicago/Turabian Style

Andrés Feijóo; Daniel Villanueva. 2016. "Contributions to wind farm power estimation considering wind direction-dependent wake effects." Wind Energy 20, no. 2: 221-231.

Journal article
Published: 19 May 2016 in IEEE Transactions on Energy Conversion
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Presents corrections to author names as well as several equations for the paper, "A PQ model for asynchronous machines based on rotor voltage calculation,” IEEE Trans. Energy Convers., to be published, doi: 10.1109/TEC.2016.2529502.

ACS Style

Andrés Feijóo; D. Villanueva. Correction to “A PQ Model for Asynchronous Machines Based on Rotor Voltage Calculation” [Jun 16 813-814]. IEEE Transactions on Energy Conversion 2016, 31, 818 -818.

AMA Style

Andrés Feijóo, D. Villanueva. Correction to “A PQ Model for Asynchronous Machines Based on Rotor Voltage Calculation” [Jun 16 813-814]. IEEE Transactions on Energy Conversion. 2016; 31 (2):818-818.

Chicago/Turabian Style

Andrés Feijóo; D. Villanueva. 2016. "Correction to “A PQ Model for Asynchronous Machines Based on Rotor Voltage Calculation” [Jun 16 813-814]." IEEE Transactions on Energy Conversion 31, no. 2: 818-818.

Journal article
Published: 01 April 2016 in Renewable and Sustainable Energy Reviews
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ACS Style

Andrés Feijóo; Daniel Villanueva. Assessing wind speed simulation methods. Renewable and Sustainable Energy Reviews 2016, 56, 473 -483.

AMA Style

Andrés Feijóo, Daniel Villanueva. Assessing wind speed simulation methods. Renewable and Sustainable Energy Reviews. 2016; 56 ():473-483.

Chicago/Turabian Style

Andrés Feijóo; Daniel Villanueva. 2016. "Assessing wind speed simulation methods." Renewable and Sustainable Energy Reviews 56, no. : 473-483.

Journal article
Published: 26 February 2016 in IEEE Transactions on Energy Conversion
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This letter contributes toward improving the calculation of the power balance of an asynchronous machine in a power system. This is useful in power system steady-state analysis, particularly when there are wind farms in electrical power networks.

ACS Style

Andrés Feijóo; Daniel Villanueva. A PQ Model for Asynchronous Machines Based on Rotor Voltage Calculation. IEEE Transactions on Energy Conversion 2016, 31, 813 -814.

AMA Style

Andrés Feijóo, Daniel Villanueva. A PQ Model for Asynchronous Machines Based on Rotor Voltage Calculation. IEEE Transactions on Energy Conversion. 2016; 31 (2):813-814.

Chicago/Turabian Style

Andrés Feijóo; Daniel Villanueva. 2016. "A PQ Model for Asynchronous Machines Based on Rotor Voltage Calculation." IEEE Transactions on Energy Conversion 31, no. 2: 813-814.