Sustainable energy undergraduate research

Author

Chaar, Lana El ; Lamont, Lisa Ann

Author_Institution

Pet. Inst., Abu Dhabi, United Arab Emirates

fYear

2009

fDate

17-19 March 2009

Firstpage

1

Lastpage

5

Abstract

Issues such as climate change, global warming, increased blackouts, and oil price fluctuation continue to pepper the news. All the above mentioned facts led to an increase interest in renewable energy sources. This makes solar radiation, wind speed and climate effect important parameters to study, map and predict. One method to implement the following is using Neural Networks (NN). This paper presents the approach used in teaching both sustainable energy and NN to undergraduate students via research since those topics are often not incorporated in the electrical engineering curriculum.

Keywords

computer aided instruction; neural nets; power engineering computing; power engineering education; renewable energy sources; solar radiation; NN; climate change; electrical engineering curriculum; global warming; neural network; oil price fluctuation; renewable energy source; solar radiation; sustainable energy undergraduate research; wind speed; Artificial neural networks; Education; Meteorology; Ocean temperature; Renewable energy resources; Solar energy; Solar radiation; Electrical Engineering; Neural Networks; Renewable Energy; Solar Radiation; Undergraduate Research; Wind Speed;

fLanguage

English

Publisher

ieee

Conference_Titel

GCC Conference & Exhibition, 2009 5th IEEE

Conference_Location

Kuwait City

Print_ISBN

978-1-4244-3885-3

Type

conf

DOI

10.1109/IEEEGCC.2009.5734330

Filename

5734330