scholarly journals Characterization of Wind Farm Energy Production in a Zone by Artificial Neuronal Networks

2003 ◽  
Vol 1 (01) ◽  
pp. 545-552
Author(s):  
Joaquín Mur Amada ◽  
◽  
Ángel Antonio Bayod
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Neuronal Networks ◽  
Artificial Neuronal Networks

Elaboration and Characterization of the Properties of Refractory Cr Base Alloys

2010 ◽  
Vol 72 ◽  
pp. 46-52 ◽  
Author(s):  
Laurent Royer ◽  
Stéphane Mathieu ◽  
Christophe Liebaut ◽  
Pierre Steinmetz
Keyword(s):  
Mechanical Properties ◽  
Melting Point ◽  
Molten Glass ◽  
Energy Production ◽  
Creep Properties ◽  
Refractory Alloys ◽  
Industrial Use ◽  
Kinetics Of ◽  
Selection Of

For energy production and also for the glass industry, finding new refractory alloys which could permit to increase the process temperatures to 1200°C or more is a permanent challenge. Chromium base alloys can be good candidates, considering the melting point of Cr itself, and also its low corrosion rate in molten glass. Two families of alloys have been studied for this purpose, Cr-Mo-W and Cr-Ta-X alloys (X= Mo, Si..). A finer selection of compositions has been done, to optimize their chemical and mechanical properties. Kinetics of HT oxidation by air, of corrosion by molten glass and also creep properties of several alloys have been measured up to 1250°C. The results obtained with the best alloys (Cr-Ta base) give positive indications as regards the possibility of their industrial use.

scholarly journals Wind Farm Cable Connection Layout Optimization with Several Substations

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3615
Author(s):  
Adelaide Cerveira ◽  
Eduardo J. Solteiro Pires ◽  
José Baptista
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Programming Model ◽  
Optimal Solution ◽  
Wind Farms ◽  
Green Energy ◽  
Fossil Energy ◽  
Proposed Model ◽  
Short Time ◽  
Cable Connection

Green energy has become a media issue due to climate changes, and consequently, the population has become more aware of pollution. Wind farms are an essential energy production alternative to fossil energy. The incentive to produce wind energy was a government policy some decades ago to decrease carbon emissions. In recent decades, wind farms were formed by a substation and a couple of turbines. Nowadays, wind farms are designed with hundreds of turbines requiring more than one substation. This paper formulates an integer linear programming model to design wind farms’ cable layout with several turbines. The proposed model obtains the optimal solution considering different cable types, infrastructure costs, and energy losses. An additional constraint was considered to limit the number of cables that cross a walkway, i.e., the number of connections between a set of wind turbines and the remaining wind farm. Furthermore, considering a discrete set of possible turbine locations, the model allows identifying those that should be present in the optimal solution, thereby addressing the optimal location of the substation(s) in the wind farm. The paper illustrates solutions and the associated costs of two wind farms, with up to 102 turbines and three substations in the optimal solution, selected among sixteen possible places. The optimal solutions are obtained in a short time.

scholarly journals Scaling in a Geothermal Heat Exchanger at Soultz-Sous-Forêts (Upper Rhine Graben, France): A XRD and SEM-EDS Characterization of Sulfide Precipitates

Geosciences ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 271
Author(s):  
Béatrice A. Ledésert ◽  
Ronan L. Hébert ◽  
Justine Mouchot ◽  
Clio Bosia ◽  
Guillaume Ravier ◽  
...  
Keyword(s):  
Heat Exchanger ◽  
Energy Production ◽  
Electricity Production ◽  
Normal Operation ◽  
Upper Rhine Graben ◽  
Geothermal Heat ◽  
Deep Wells ◽  
Upper Rhine ◽  
Management Issues

The Soultz-Sous-Forêts geothermal site (France) operates three deep wells for electricity production. During operation, scales precipitate within the surface installation as (Ba, Sr) sulfate and (Pb, As, Sb) sulfide types. Scales have an impact on lowering energy production and inducing specific waste management issues. Thus scaling needs to be reduced for which a thorough characterization of the scales has to be performed. The geothermal brine is produced at 160 °C and reinjected at 70 °C during normal operation. In the frame of the H2020 MEET project, a small heat exchanger was tested in order to allow higher energy production, by reinjecting the geothermal fluid at 40 °C. Samples of scales were analyzed by XRD and SEM-EDS, highlighting that mostly galena precipitates and shows various crystal shapes. These shapes can be related to the turbulence of the flow and the speed of crystal growth. Where the flow is turbulent (entrance, water box, exit), crystals grow quickly and mainly show dendritic shape. In the tubes, where the flow is laminar, crystals grow more slowly and some of them are characterized by well-developed faces leading to cubes and derived shapes. The major consequence of the temperature decrease is the increased scaling phenomenon.

Artificial Neuronal Networks for the Prediction of Atmospheric Corrosion in Bronze with Nanostructured Patinas with SiO2

2021 ◽  
Vol MA2021-01 (54) ◽  
pp. 1313-1313
Author(s):  
Henevith Gisell Méndez Figueroa ◽  
Darío Colorado Garrido ◽  
R. Galván Martínez ◽  
Miguel Ángel Hernandez ◽  
Ricardo Orozco Cruz
Keyword(s):  
Atmospheric Corrosion ◽  
Neuronal Networks ◽  
Artificial Neuronal Networks

scholarly journals Inter-annual variability of wind climates and wind turbine annual energy production

2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Standard Deviation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Annual Variability ◽  
Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

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