A Multi-Attribute Model for Wind Farm Location Combining Cloud and Utility Theories

2013 ◽  
pp. 93-105 ◽  
Author(s):  
José Ramón San Cristóbal
Keyword(s):  
Wind Farm ◽  
Attribute Model ◽  
Wind Farm Location

scholarly journals Statistical characterization of roughness uncertainty and impact on wind resource estimation

2016 ◽  
Author(s):  
Mark Kelly ◽  
Hans Ejsing Jørgensen
Keyword(s):  
Wind Farm ◽  
Statistical Characterization ◽  
Wind Speeds ◽  
Industry Standard ◽  
Industry Practice ◽  
Mean Wind Speed ◽  
Atlas Method ◽  
Wind Farm Location ◽  
Drag Law ◽  
Wind Resource

Abstract. In this work we relate uncertainty in background roughness length (z0) to uncertainty in wind speeds, where the latter are predicted at a wind farm location based on wind statistics observed at a different site. Sensitivity of predicted winds to roughness is derived analytically for the industry-standard European Wind Atlas method, which is based on the geostrophic drag law. We consider roughness statistically and its corresponding uncertainty, in terms of both z0 derived from measured wind speeds, as well as that chosen in practice by wind engineers. We show the combined effect of roughness uncertainty arising from differing wind-observation and turbine-prediction sites; this is done for the case of roughness bias, as well as for the general case. For estimation of uncertainty in annual energy production (AEP), we also develop a generalized analytical turbine power curve, from which we derive a relation between mean wind speed and AEP. Following from our developments we provide guidance on approximate roughness uncertainty magnitudes to be expected in industry practice, and also find that sites with larger background roughness incur relatively larger uncertainties.

scholarly journals Elaboration of a Wind Energy Potential Map in Morocco using GIS and Analytic Hierarchy Process

2020 ◽  
Vol 10 (4) ◽  
pp. 6068-6075
Author(s):  
F. Elmahmoudi ◽  
O. E. K. Abra ◽  
A. Raihani ◽  
O. Serrar ◽  
L. Bahatti
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Energy Potential ◽  
Analytic Hierarchy ◽  
Potential Map ◽  
Wind Energy Potential ◽  
Wind Farm Location ◽  
Location Map ◽  
Hierarchy Process ◽  
Selection Of

The construction of a wind power generation center starts by the selection of a suitable wind farm location. The selection includes six factors, namely wind speed, slope, land use, distance from the power lines, distance from the roads, and distance from populated areas which have been integrated into QGIS by weights calculated using the Analytical Hierarchy Process (AHP) approach. As a result of this study, the areas having very high wind potentiality have been identified and a best wind farm location map has been prepared. The map, using the overlay function in GIS, exhibits the most and least suitable areas for the location of wind farms in Morocco. The approach could help identify suitable wind farm locations in other areas using their geographic information.

Investigation of wind farm location planning by considering budget constraints

2018 ◽  
Vol 37 (8) ◽  
pp. 799-817 ◽  
Author(s):  
Reza Lotfi ◽  
Ali Mostafaeipour ◽  
Nooshin Mardani ◽  
Shadi Mardani
Keyword(s):  
Wind Farm ◽  
Budget Constraints ◽  
Location Planning ◽  
Wind Farm Location

Factors in determining wind farm location: Integrating GQM, fuzzy DEMATEL, and ANP

2014 ◽  
Vol 66 ◽  
pp. 159-169 ◽  
Author(s):  
Tsu-Ming Yeh ◽  
Yu-Lang Huang
Keyword(s):  
Wind Farm ◽  
Fuzzy Dematel ◽  
Wind Farm Location

scholarly journals Modelling and resonance analysis of wind power integration via flexible HVDC considering wind speed and wind farm location

2018 ◽  
Vol 1087 ◽  
pp. 042081
Author(s):  
Xiaobao Hu ◽  
Xiao Wang ◽  
Hui Liu ◽  
Linlin Wu ◽  
Lele Niu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Farm ◽  
Wind Power Integration ◽  
Resonance Analysis ◽  
Wind Farm Location

scholarly journals Using the PROSA Method in Offshore Wind Farm Location Problems

Energies ◽  
2017 ◽  
Vol 10 (11) ◽  
pp. 1755 ◽  
Author(s):  
Paweł Ziemba ◽  
Jarosław Wątróbski ◽  
Magdalena Zioło ◽  
Artur Karczmarczyk
Keyword(s):  
Wind Farm ◽  
Offshore Wind ◽  
Location Problems ◽  
Offshore Wind Farm ◽  
Wind Farm Location

scholarly journals Performance Sensitivity of a Wind Farm Power Curve Model to Different Signals of the Input Layer of ANNs: Case Studies in the Canary Islands

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Sergio Velázquez Medina ◽  
José A. Carta ◽  
Ulises Portero Ajenjo
Keyword(s):  
Wind Farm ◽  
Meteorological Data ◽  
Model Performance ◽  
Meteorological Conditions ◽  
Original Model ◽  
Power Curve ◽  
The Neural Network ◽  
Input Layer ◽  
Curve Model ◽  
Wind Farm Location

Improving the estimation of the power output of a wind farm enables greater integration of this type of energy source in electrical systems. The development of accurate models that represent the real operation of a wind farm is one way to attain this objective. A wind farm power curve model is proposed in this paper which is developed using artificial neural networks, and a study is undertaken of the influence on model performance when parameters such as the meteorological conditions (wind speed and direction) of areas other than the wind farm location are added as signals of the input layer of the neural network. Using such information could be of interest, either to study possible improvements that could be obtained in the performance of the original model, which uses exclusively the meteorological conditions of the area where the wind farm is located, or simply because no reliable meteorological data for the area of the wind farm are available. In the study developed it is deduced that the incorporation of meteorological data from an additional weather station other than that of the wind farm site can improve by up to 17.6% the performance of the original model.

scholarly journals Identification of Relevant Criteria Set in the MCDA Process—Wind Farm Location Case Study

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6548
Author(s):  
Bartłomiej Kizielewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun
Keyword(s):  
Decision Support ◽  
Decision Model ◽  
Wind Farm ◽  
Location Problem ◽  
Correlation Coefficients ◽  
Similarity Coefficients ◽  
Practical Usefulness ◽  
Decision Support Models ◽  
Wind Farm Location

The paper undertakes the problem of proper structuring of multi-criteria decision support models. To achieve that, a methodological framework is proposed. The authors’ framework is the basis for the relevance analysis of individual criteria in any considered decision model. The formal foundations of the authors’ approach provide a reference set of Multi-Criteria Decision Analysis (MCDA) methods (TOPSIS, VIKOR, COMET) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). In the empirical research, a practical MCDA-based wind farm location problem was studied. Reference rankings of the decision variants were obtained, followed by a set of rankings in which particular criteria were excluded. This was the basis for testing the similarity of the obtained solutions sets, as well as for recommendations in terms of both indicating the high significance and the possible elimination of individual criteria in the original model. When carrying out the analyzes, both the positions in the final rankings, as well as the corresponding values of utility functions of the decision variants were studied. As a result of the detailed analysis of the obtained results, recommendations were presented in the field of reference criteria set for the considered decision problem, thus demonstrating the practical usefulness of the authors’ proposed approach. It should be pointed out that the presented study of criteria relevance is an important factor for objectification of the multi-criteria decision support processes.

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