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Distributed generation in deregulated Chapter | 9 231

6. the variations in network operational topology; and
7. the uncertainty in the economic factors, such as the variations in inflation
rates, unemployment rate, and gross domestic product.
Accordingly, the HC of an electrical system will not be a unique level, but
a range of levels is obtained according to the uncertainty degree examined.
The MCS approach is considered as one of the most efficient techniques
to handle the uncertainty of electrical parameters, such as DG generation
fluctuations and load profile changes [16,20].
The Electric Power Research Institute highlighted that the uncertainty in
the evaluation of HC levels took place due to the unpredictable DG integration
location, variety of unit ratings, the variable nature of DG output power due to
climate fluctuations, alteration of load demand, and the absence of accurate
system parameters when establishing the HC analysis calculations [21].
A comparison between the deterministic and probabilistic HC calculation
methods is presented in Table 9.2 and Fig. 9.2, respectively.
As previously described, the HC assessment should not be handled as a
deterministic problem. Instead, it should be solved as a probabilistic prob-
lem, whereby appropriate accuracy and uncertainty levels are considered.
Throughout the literature, it was concluded that using deterministic solutions
based on worst-case scenarios leads to a considerable underestimation of the
HC levels. The concept of uncertainty management in HC analysis is illus-
trated in a simplified manner in Fig. 9.3, while considering the bus voltage
as a sample PI for the HC calculation.
From Fig. 9.3, it can be observed that various HC levels exist in the pres-
ence of uncertain parameters of the system. In addition, it is clear that a pes-
simistic HC level (HCU) can be achieved when the system planner considers
the upper uncertainty level. On the other hand, an optimistic HC level (HCL)
can be obtained when the lower uncertainty level is considered. Furthermore,
it is obvious that using high percentiles of the studied index (such as the
95th percentile) leads to a realistic HC level (HC95).

9.4 Overview of related applications

The various uncertainties associated with the massive integration of renew-
able energy resources into existing electrical distribution networks have been
examined by many works. This section provides a comprehensive overview
of some relevant researches, which sheds light on the impact of uncertainty
handling techniques on the HC assessment and relevant decision-making
tools.
In Ref. [22], Lennerhag et al. studied the role of using actual network
measurements in the assessment of the HC. The authors concluded that using
actual network measurements leads to higher levels of the network’s HC,
because the dependence on the deterministic calculations only causes a