scholarly journals Solar energy production forecasting through artificial neuronal networks, considering the Föhn, north and south winds in San Juan, Argentina

2019 ◽  
Vol 2019 (18) ◽  
pp. 4824-4829
Author(s):  
Luis Carlos Parra Raffán ◽  
Andrés Romero ◽  
Maximiliano Martinez
Keyword(s):  
Solar Energy ◽  
Energy Production ◽  
Neuronal Networks ◽  
San Juan ◽  
Production Forecasting ◽  
Artificial Neuronal Networks ◽  
North And South

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

Preliminary results on the determination of solar energy potential using LiDAR technology

2015 ◽  
Vol 6 (1) ◽  
pp. 11-17 ◽  
Author(s):  
G. Szabó ◽  
P. Enyedi ◽  
Gy. Szabó ◽  
I. Fazekas ◽  
T. Buday ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Energy Production ◽  
Alternative Energy ◽  
Surface Model ◽  
Solar Panels ◽  
Energy Potential ◽  
Potential Surfaces ◽  
Large Power ◽  
Automatic Data

According to the challenge of the reduction of greenhouse gases, the structure of energy production should be revised and the increase of the ratio of alternative energy sources can be a possible solution. Redistribution of the energy production to the private houses is an alternative of large power stations at least in a partial manner. Especially, the utilization of solar energy represents a real possibility to exploit the natural resources in a sustainable way. In this study we attempted to survey the roofs of the buildings with an automatic method as the potential surfaces of placing solar panels. A LiDAR survey was carried out with 12 points/m2 density as the most up-to-date method of surveys and automatic data collection techniques. Our primary goal was to extract the buildings with special regard to the roofs in a 1 km2 study area, in Debrecen. The 3D point cloud generated by the LiDAR was processed with MicroStation TerraScan software, using semi-automatic algorithms. Slopes, aspects and annual solar radiation income of roof planes were determined in ArcGIS10 environment from the digital surface model. Results showed that, generally, the outcome can be regarded as a roof cadaster of the buildings with correct geometry. Calculated solar radiation values revealed those roof planes where the investment for photovoltaic solar panels can be feasible.

scholarly journals A Measured Energy Use, Solar Production, and Building Air leakage Dataset for a Zero Energy Commercial Building

2021 ◽  
Author(s):  
Philip Agee ◽  
Leila Nikdel ◽  
Sydney Roberts
Keyword(s):  
Solar Energy ◽  
Energy Production ◽  
Energy Use ◽  
The United States ◽  
Test Method ◽  
Army Corps ◽  
Air Leakage ◽  
Commercial Building ◽  
Zero Energy ◽  
Measured Energy

This paper provides an open dataset of measured energy use, solar energy production, and building air leakage data from a 328 m2 (3,531 ft2) all-electric, zero energy commercial building in Virginia, USA. Over two years of energy use data were collected at 1-hour intervals using circuit-level energy monitors. Over six years of solar energy production data were measured at 1-hour intervals by 56 microinverters. The building air leakage data was measured post-construction per ASTM-E779 Standard Test Method for Determining Air Leakage Rate by Fan Pressurization and the United States Army Corps (USACE) Building Enclosure Testing procedure; both pressurization and depressurization results are provided. The architectural and engineering (AE) documents are provided to aid researchers and practitioners in reliable modelling of building performance. The paper describes the data collection methods, cleaning, and convergence with weather data. This dataset can be employed to predict, benchmark, and calibrate operational outcomes in zero energy commercial buildings.

Silver prices and solar energy production

2019 ◽  
Vol 26 (9) ◽  
pp. 8525-8532 ◽  
Author(s):  
Iraklis Apergis ◽  
Nicholas Apergis
Keyword(s):  
Solar Energy ◽  
Energy Production
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