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58 CHAPTER 2 Solar PV Power Plants Site Selection: A Review

The geographical information system (GIS) is a powerful tool for consulting,
analyzing, and editing data, map, and spatial information. In recent years, GIS
has become progressively popular as a tool for various site selection studies, in
particular for the energy planning. Developing a decision support model that inte-
grates GIS with multicriteria can promote determining the ideal location for solar
energy. Consequently, improving the performance of the solar PV projects plays a
vital role in maximizing the generated output power, contributing to minimal project
costs and assisting in planning future infrastructure projects.
In this chapter, theses, journal papers, and conference proceedings in the last
10 years (2007e17) are reviewed. Table 2.1 summarizes the associated studies
with solar PV site selection. It presents the type of RES integrated with solar PV.
The methodologies applied to tackle the problem with decision criteria is shown
along with a grid-connection option in different contexts.
Solar PV grid-connected systems are linked and deliver power into the public
electric grid. Such systems can be either distributed type, serving a certain grid-
connected customer or centralized type, acting as a centralized power station and
feeding into a transmission grid [43]. More than 80% of researches deal with
grid-connected systems. From the location standpoint, China leads the site suit-
ability studies followed by Spain and India as shown in Fig. 2.1.

1.1 MULTICRITERIA DECISION-MAKING TECHNIQUES FOR
PHOTOVOLTAIC SITE SELECTION
Given the fact that several criteria can influence site selection, applying multicriteria
decision-making (MCDM) methods can help ease site selection for utility-scale PV
solar energy systems by considering key factors in the decision process. Various
MCDM methods differ in their data requirement and the decision makers’ (DM)
goals and their respective characteristics. Jankowski explained the integration of
GIS and MCDM ways in supporting decision-making [59]. Greene et al. provided
an overview of the methods of MCDA and its spatial extension using GIS and sug-
gested improving integration of MCDA with GIS software for increasing accessi-
bility [60]. However, the research of GIS-MCDM has focused on a relatively
small number of multicriteria approaches including the weighted linear combination
(WLC), ideal points methods, the analytical hierarchy process (AHP), elimination
and choice translating reality (ELECTRE), and Technique for Order Preference
by Similarity to Ideal Solution (TOPSIS) [61] as shown in Table 2.1.MCDM
methods have been successfully applied in many energy-planning projects. Pohekar
and Ramachandran [62], Mateo [63], and Wang et al. [64] provide an excellent liter-
ature review on application of MCDM approach in the RE planning. According to
the survey of AHP literature by Sipahi and Timor [64a], the GIS-AHP applications
are among the most often used approaches for integrating AHP with other decision
support techniques. The GIS-AHP approach ranks third. It accounts for about 11%
of all the AHP-based integrated applications (while the first and second ranking
methods, simulation and TOPSIS), account for 15% and 12% [61].