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2. Criteria for Site Selection 65

1.3 DEALING WITH UNCERTAINTIES IN PHOTOVOLTAIC
SITE SELECTION

In many of real-life situations, there is ambiguous and incomplete information due to
measurements errors and conceptual inaccuracy; these limitations must be taken into
account particularly in the GIS-MCDM analysis. The huge study area along with a
large number of alternative sites might have noteworthy uncertainties that had better
be considered. Validating the data with ground monitoring devices could reduce the
uncertainty. There are several aspects of uncertainty during a solar PV site selection
process, uncertainty in the solar irradiation estimation is one of the significant sour-
ces of the general energy production uncertainty. Making the composition of accu-
rate data is critical for reducing uncertainty in the solar resource estimate; therefore,
it increases the assurance in the project’s power estimate [79]. On the other side, two
types of uncertainty could be combined with the decision-making process: (1) uncer-
tainty associated with the ambiguous concerning the description of the semantic
meaning of the statements and events, and (2) uncertainty related to the limited
data about the decision situation and errors within. However, the main source of un-
certainty in MCDM tools is related to the criteria weights (DM preferences) and
criteria values (criteria maps) [61]. For instance, to deal with uncertainty in the
DM evaluation in classic AHP, fuzzy AHP selected to elicit the decision criteria
weights in this integration of GIS with AHP for the site selection as shown in
Table 2.1.
Comparisons between different methodologies under the same environment
could bring insightfulness to the criteria influences and the outcomes. Further-
more, wherever the uncertainty in results designated as a function of the uncer-
tainty of the input, one can develop a framework for MCDA using a simulation
method, such as Monte Carlo for generating probability distributions of the in-
puts [80].
Sensitivity analysis focuses on how uncertainty in the output is affected by the
uncertainty in the model input factors. Hence, the influence of varying criterion
weights on the MCDA model output is, without a doubt, the most frequently applied
form of sensitivity analysis in GIS-based multicriteria modeling [81].

2. CRITERIA FOR SITE SELECTION
To deploy a solar project on a utility-scale, several criteria and factors should be
considered with the aim of optimizing the location which will result in more efficient
system, more economic to supply the needed customers and less impact on the envi-
ronment. Typically, the decision criteria are derived based on the study aim, acces-
sibility to the geo-referenced database and the existing literature. The review results
in 39 subcriteria assessed mostly under location and climate criteria. Most solar site
suitability studies deliberate solar irradiation as the most important decision criteria,
as shown in Table 2.2.