IEEE Technology and Society Magazine - June 2018 - 68

interactive complexity and that large disruptions are
seemingly intrinsic to large infrastructure systems [30].
They then describe self-organizing criticality as a prop-
erty of complex systems, where the nonlinear system
dynamics in the presence of perturbations actually
make the average system state more susceptible to
large disturbances [30]. When systems have self-orga-
nizing criticality, actions designed to mitigate problems
may actually increase the likelihood of large disruptions
[30]. This paper reinforced ideas central to the normal
accident framework with engineering theory, such as
independence and self-organizing criticality.
The same authors (Dobson, Carreras, and Newman)
and their collaborators (Lynch and Ren) continued
exploring the probability distribution of blackouts in
[32]-[34], focusing on the influence of different network
assumptions. These papers used engineering analysis
to answer questions relevant to both frameworks: how
do redundancy and scale change the likelihood of black-
outs? The researchers model the evolution of the power
system considering policy (system upgrades) and soci-
etal changes (load growth and the corresponding power
supply growth) [32]-[34]. This model demonstrates how
the power system self-organizes to its critical point -
serving increased load stresses the system and system
upgrades responding to that stress, in turn, allow for
more load to be served, keeping the network near its
critical point [32], [33].
The researchers examined three different approach-
es to line upgrades to evaluate their impact on blackout
probability: 1) upgrade as lines approach their loading
limits [32], 2) upgrade lines involved in a cascading out-
age after the outage [32], [33], and 3) upgrade when
lines violate the N-1 criterion [33]. The power grid is
designed to operate so it satisfies the "N-1" criterion,
meaning that the grid should remain fully operational
when any one major piece of equipment suffers an out-
age. To satisfy this criterion, lines cannot be loaded to
capacity; it provides a pseudo-redundancy, with spare
capacity shared over multiple lines. Comparing the first
two approaches, no difference in the likelihood of large
blackouts was found [32]. The second approach showed
greater grid utilization, while the third reduced the num-
ber of small outages [33]. None of the approaches yield-
ed a lower probability of large blackouts than the others
[32], [33]. Furthermore, the researchers found that
increasing the lines' reliability (mathematically equiva-
lent to decreasing the margin), actually increased the
probability of larger blackouts [32]. Defining outage risk
using probability and cost, the risk of large blackouts
was shown to increase with grid size [34]. This paper is
noteworthy because it tested the normal accident
framework against the engineering heuristic that larger
grids reduce outages, concluding that bigger is better

68

only until a threshold at which the risk of smaller black-
outs is balanced by that of larger blackouts [34].
In their 2012 article, Mazur and Metcalfe analyzed
three different power grids in the U.S. to determine
whether grid size determines reliability [35]. Proponents
of the normal accident framework would expect bene-
fits from increased integration to be outweighed by the
increased risk of catastrophic failure. The authors ulti-
mately found no relationship between grid size and reli-
ability, finding that the normal accident framework does
not accurately predict performance of the electric power
system [35]. However, their study only examined data
from 2007 to 2010, excluding the 2003 Blackout. Nor-
mal accidents happen "infrequently," with relevant time
intervals typically measured in decades, so studies
using only three years of reliability data cannot make
claims either for or against the framework. Based on
22 years of historical outage data, Dobson, Carreras,
and Newman characterized the probability of blackouts
for the Eastern and Western interconnections [36]. The
study results used historic data to confirm the power
law distribution mentioned previously [30], supporting
the normal accident framework.
Despite the clear applicability of both the normal
accident framework and the HRO framework, relatively
few groups of power systems engineers have adopted
ideas from either. As described, most work uses either
framework to analyze blackouts, specifically large or
cascading blackouts. I will now postulate on some spe-
cific areas where both frameworks could be applied and
discuss how the results from or questions inspired by
either framework would be useful. I will focus on cas-
cading blackouts, digital relays for protection and con-
trol, and cybersecurity.
In the post-event analysis of the U.S. 2003 Northeast
Blackout, investigators traced paths of failure that were
unclear to operators during the event, who instead saw
baffling interactions and an incomprehensible evolution
of problems - hallmarks of normal accidents. The final
report on the blackout cited "inadequate system under-
standing ... situational awareness ... [and] diagnostic
support" as causes of the cascading blackout [37]. It
also said that "[m]any of the institutional problems arise
not because NERC is an inadequate or ineffective orga-
nization, but rather because it has no structural inde-
pendence from the industry it represents and has no
authority to develop strong reliability standards and to
enforce compliance" [37]. This recalls Perrow's argu-
ment that the regulator must be independent of the
industry it regulates to reduce normal accidents. Engi-
neers can examine the role that redundancy played: did
it contribute to the blackout or did it help keep the grid
energized? The HRO framework could help companies
learn about management strategies - which companies

IEEE Technology and Society Magazine

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