151. Multi-Attribute Decision-Making: Applying a Modified Brown–Gibson Model and RETScreen Software to the Optimal Location Process of Utility-Scale Photovoltaic Plants
- Author
-
Mustafa Dagbasi and Nasser Yimen
- Subjects
RETScreen ,Payback period ,Operations research ,analytic hierarchy process (AHP) ,Computer science ,020209 energy ,Site selection ,Analytic hierarchy process ,Bioengineering ,02 engineering and technology ,010501 environmental sciences ,lcsh:Chemical technology ,01 natural sciences ,Net present value ,lcsh:Chemistry ,photovoltaic ,Software ,multi-criteria decision-making (MCDM) ,0202 electrical engineering, electronic engineering, information engineering ,Chemical Engineering (miscellaneous) ,lcsh:TP1-1185 ,Cameroon ,Brown–Gibson model ,0105 earth and related environmental sciences ,business.industry ,Process Chemistry and Technology ,Photovoltaic system ,optimal location ,Multiple-criteria decision analysis ,renewable energy ,Renewable energy ,lcsh:QD1-999 ,business - Abstract
Due to environmental and economic drawbacks of fossil fuels, global renewable energy (RE) capacity has increased significantly over the last decade. Solar photovoltaic (PV) is one of the fastest-growing RE technologies. Selecting an appropriate site is one of the most critical steps in utility-scale solar PV planning. This paper aims at proposing a rational multi-criteria decision-making (MCDM) approach based on the Brown&ndash, Gibson model for optimal site selection for utility-scale solar PV projects. The proposed model considers the project&rsquo, s net present value (NPV) along with seven suitability factors and six critical (constraint) factors. The RETScreen software was applied in calculating the NPV, the simple payback period and the carbon emission savings of the project at each alternative site. The weights of the suitability factors were determined using the analytical hierarchy process. Applied to the case study of finding the best location for a 5 MW solar PV project in northern Cameroon, the optimization results showed that Mokolo was the optimal location. The sensitivity analysis results revealed that the rankings of alternative sites based on the project&rsquo, s NPV and the proposed model are not consistent. Compared to the traditional MCDM approaches, the proposed model provides decision-makers with a more practical thinking method in the optimal location process of utility-scale solar projects.
- Published
- 2019