A martrix based method enabling to compare a pair of alternatives at a time and thus calculating the assigned weights based on the comparisons.
Published in Chapter:
Technology Selection for Solar Power Generation in the Middle East: Case of Saudi Arabia
Tugrul Daim (Portland State University, USA), Paul R. Newman (Portland State University, USA), Hithem Sughi (Portland State University, USA), and Eyad Bakhsh (Portland State University, USA)
Copyright: © 2013
|Pages: 26
DOI: 10.4018/978-1-4666-1996-8.ch018
Abstract
Saudi Arabia is moving towards economical and technological development and to be an active player in the dynamics of the international community. The economic growth in the country requires significant additional electrical power generation in order to supply this increasing demand. At present, fossil fuel (petroleum and natural gas) reserves in Saudi Arabia are reliable in terms of feeding the needs of its conventional power plants. Fossil fuels, however, are not sustainable, are subject to eventual depletion and plants using these fuels produce large amounts of CO2 emissions. The authors have examined other power generation alternatives with an eye towards achieving sustainability. These requirements have led them to propose a renewable energy source—radiant energy from the sun as the way to achieve long-term success. The region is blessed with an abundant solar flux throughout most of the year. Recognizing this, the authors propose building solar-powered electrical generation plants in the Saudi deserts, but are faced with the problem: “Which solar technology is the ideal choice for this application?” Several different technologies have been identified and analyzed. A mathematical model was constructed and used to make a selection of the optimal technology. The decision model employed to determine the optimal technology, taking account of the fact that in making such a technology selection subjective judgment is required, is the Hierarchal Decision Model (HDM). This research relied on data extracted from scientific journals and industry sources as the inputs for the Decision Model. The authors also validated their research and derived expert opinion weighting factors with international experts in the solar technology. They have applied the model to a case study to demonstrate the use of it.